IL308102A - The polarity and specificity of sars-cov2 -specific t lymphocyte responses as a biomarker of disease susceptibility - Google Patents

The polarity and specificity of sars-cov2 -specific t lymphocyte responses as a biomarker of disease susceptibility

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IL308102A
IL308102A IL308102A IL30810223A IL308102A IL 308102 A IL308102 A IL 308102A IL 308102 A IL308102 A IL 308102A IL 30810223 A IL30810223 A IL 30810223A IL 308102 A IL308102 A IL 308102A
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sars
cov
peptides
aminoacids
spike
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IL308102A
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Laurence Zitvogel
Jean-Eudes Fahrner
Markus Maeurer
Sousa Eric De
Joana Lerias
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Roussy Inst Gustave
Funda??O D Anna De Sommer Champalimaud E Dr Carlos Montez Champalimaud
Univ Paris Saclay
Transgene
Laurence Zitvogel
Fahrner Jean Eudes
Markus Maeurer
Sousa Eric De
Joana Lerias
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Application filed by Roussy Inst Gustave, Funda??O D Anna De Sommer Champalimaud E Dr Carlos Montez Champalimaud, Univ Paris Saclay, Transgene, Laurence Zitvogel, Fahrner Jean Eudes, Markus Maeurer, Sousa Eric De, Joana Lerias filed Critical Roussy Inst Gustave
Publication of IL308102A publication Critical patent/IL308102A/en

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Description

The polarity and specificity of SARS-CoV2 -specific T lymphocyte responses as a biomarker of disease susceptibility FIELD OF THE INVENTION The present invention relates to the field of antiviral vaccination. More particularly, the invention provides immunogenic compositions for vaccination against SARS-CoV-2 and methods for in vitro determining if an individual is likely to resist to an infection by SARS-CoV-2.
BACKGROUND OF THE INVENTION The emergence and spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of coronavirus disease 2019, have resulted in devastating morbidities and socioeconomic disruption. The development of community protective immunity relies on long-term B and T cell memory responses to SARS-CoV-2. This can be achieved through viral infection [1] or by vaccination [2–4]. Reports on rapidly decreasing spike- and nucleocapsid-specific antibody titers post-COVID-19 infection [5] or reduced neutralizing capacity of vaccine-induced antibodies against viral escape variants compared to the ancestral SARS-CoV-2 strain [6,7] have shed doubts on the importance of humoral immunity as a standalone response. In contrast, T cell immunity was identified as an important determinant of recovery and long-term protection against SARS-CoV-1, even 17 years after infection [8–11]. The TH1 versus TH2 concept suggests that modulation of the relative contribution of TH1 or TH2 cytokines regulates the balance between immune protection against microbes and immunopathology [12–14]. TH1 cells (as well as cytotoxic T cells with a similar cytokine pattern referred to as Tc1 cells) produce IFNγ, IL-2, and TNFα, promote macrophage activation, antibody-dependent cell cytotoxicity, delayed type hypersensitivity, and opsonizing and complement-fixing IgG2a antibody production [12] Therefore, TH1/Tc1 cells drive the phagocyte-dependent host response and are pivotal for antiviral responses [13,14]. In contrast, TH2 (and Tc2) cells produce IL-4, IL-5, IL-and IL-13, providing optimal help for both humoral responses and mucosal immunity, through the production of mast cell and eosinophil growth and differentiation factors, thus contributing to antiparasitic and allergic reactions. Naïve T cell differentiation to distinct TH fates is guided by inputs integrated from TCR affinity, CD25 expression, costimulatory molecules, and cytokines [15]. SARS-CoV-2-specific T cell immunity plays a key role during acute COVID-19, and up to eight months after convalescence [16–20]. Indeed, functional T cell responses remain increased in both frequency and intensity up to six months post-infection [5]. They are mainly directed against spike, membrane and nucleocapsid proteins, and have been studied in greater detail by single cell sequencing in a limited number of patients [21]. Memory TH1/Tc1 T cells specific for SARS-CoV-2 and follicular T helper cells (TFH) cells have been detected in mild cases [21]. However, cases of reinfection have been reported [22], raising questions on the clinical significance of T cell polarization and peptide repertoire specificities against current viral variants. Moreover, pioneering reports suggest that, before SARS-CoV-2 became prevalent (i.e., before 2020), some individuals exhibit immune responses, mainly among CD4+ T cells, against SARS-CoV-1 nucleocapsid (NC) and ORF1a/b, or common cold coronaviruses (CCC) spike and nucleocapsid proteins that are cross-reactive with SARS-CoV-2 [9,23–25] However, the relevance of CCC or SARS-CoV-1-specific memory T cells for effective protection against the current pandemic remains questionable [21,26]. The current study was designed to correlate T cell responses to clinical protection against COVID-19, in healthy individuals and cancer patients, who are more susceptible to severe infections, and by extension to reinfection and breakthrough infection post-vaccination. In the Example 1 below, the inventors studied SARS-CoV-2 –specific T cell responses in 382 cancer-bearing or cancer-free subjects, and prospectively followed up 227 COVID-free individuals to understand which T cell polarity and peptide repertoire may convey resistance to COVID-19. They found that a SARS-CoV-2-specific IL-2/IL-5 lymphokine ratio<1 conferred susceptibility to COVID-19 infection or reinfection in both health care workers (HCW) and cancer patients, coinciding with defective TH1/Tc1 recognition of the receptor binding domain (RBD) of the spike protein, likely affecting viral evolution by selecting for new antigenic variants. Moreover, T cell immunity against the S1-RBD reference strain tended to decrease with time and in cancer patients, and crossreacted to some degree with the RBD sequences of viral variants of concern.
SUMMARY OF THE INVENTION In the Example 1 below, the inventors characterized the polarity and specificity of circulating SARS-CoV-2-specific T cell responses against whole virus lysates and 186 unique peptides derived from the SARS-CoV-1 or SARS-CoV-2 ORFeomes to determine T cell immune correlates with spontaneous (crossreactive), virus-elicited or vaccine-induced protection against COVID-19 infection or reinfection in healthy individuals and in a more vulnerable population composed of cancer patients. Irrespective of the presence of malignant disease, a high ratio between the prototypic T helper 1 (TH1)/ T cytotoxic type 1 (Tc1) cytokine, interleukin-2 (IL-2), and the prototypic 35 T helper 2 (TH2) cytokine, interleukin-5 (IL-5), released from SARS-CoV-2-specific memory T cells measured in early 2020, among SARS-CoV-2-negative persons, was associated with low susceptibility of these individuals to develop PCR-detectable SARS-CoV-2 infection in late 2020 or 2021. Of note, T cells from individuals who recovered after SARS-CoV-2 reinfection spontaneously produced elevated levels of IL-5 and secreted the immunosuppressive TH2 cytokine interleukin-10 in response to SARS-CoV-lysate, suggesting that TH2 responses to SARS-CoV-2 are maladaptive. Moreover, individuals susceptible to SARS-CoV-2 infection, reinfection or breakthrough infection post-vaccination exhibited a selective deficit in the TH1/Tc1 peptide repertoire affecting the highly mutated receptor binding domain (RBD) amino acids (331-525) of the spike protein. The inventors thus deduced that a SARS-CoV-2-specific IL-2/IL-5 lymphokine ratio<1 conferred susceptibility to COVID-19 infection or reinfection in both health care workers (HCW) and cancer patients, coinciding with defective TH1/Tc1 recognition of the receptor binding domain (RBD) of the spike protein, likely affecting viral evolution by selecting for new antigenic variants. Current vaccines triggered anti-S1-RBD specific TH1/Tc1 responses in most healthy subjects, albeit with reduced efficacy in cancer patients. T cell immunity against the S1-RBD reference strain tended to decrease with time and in cancer patients, and crossreacted to some degree with the RBD sequences of viral variants of concern. T cell immunity against the RBD sequences of viral variants of concern was reduced in vaccinees independently of age, gender and cancer. These findings indicate that COVID-19 protection relies on TH1/Tc1 cell immunity against SARS-CoV-2 S1-RBD, which in turn likely drives the phylogenetic escape of the virus. The inventors then found that the most important response for being protected against a circulating strain of SARS-CoV-2 is a TH1 response against the RBD (amino acids 331-525 of the spike protein) of said circulating strain. For example, a high TH1 response against the S1-RBD of the reference (Wuhan) strain was not only insufficient to protect against infection by the omicron strain, but it could even facilitate this infection. The next generation of COVID-19 vaccines should elicit high-avidity TH1/Tc1 (rather than TH2)-like T cell responses against the RBD domain of current and emerging viral variants, while booster vaccinations should be guided by prior T cell assays. According to a first aspect, the present invention thus pertains to a method for in vitro determining whether an individual is likely to resist to an infection by SARS- CoV-2, comprising: (i) generating dendritic cells (DC) from monocytes obtained from said individual; (ii) loading said DC with a SARS-CoV-2 lysate or SARS-CoV-antigens; (iii) contacting peripheral blood lymphocytes (PBL) from said individual with the DC obtained in step (ii), in appropriate conditions to activate said PBL; (iv) following the PBL activation, measuring the expression of at least one cytokine secreted by Th1 cells, selected from the group consisting of IL-2, IFNγ and TNFa, and measuring the expression of at least one cytokine secreted by Th2 cells, selected from the group consisting of IL-5, IL-4, IL-9, IL-10 and IL-13; and (v) from the results of step (iv), assessing the Th1/Th2 polarization of SARS-CoV-2-specific memory T cell response in said individual, wherein a Th1 polarization indicates that the individual is likely to resist to an infection by SARS-CoV-2, and a Th2 polarization indicates that the individual is susceptible to an infection by SARS-CoV-2. The invention also pertains to another method for in vitro determining whether an individual is likely to resist to an infection by SARS-CoV-2, comprising: (i) incubating T lymphocytes from said individual with a mix of antigenic peptides from SARS-CoV-2, under conditions appropriate to stimulate Thand/or Th2 lymphocytes specific for said peptides; and (ii) assessing the presence of Th1 and/or Th2 lymphocytes; wherein the presence of Th1 lymphocytes specific for said peptides indicates that the individual is likely to resist to an infection by SARS-CoV-2, and/or the absence of Th1 lymphocytes and/or the presence of Th2 lymphocytes specific for said peptides indicates that the individual is susceptible to an infection by SARS-CoV-2. A method for monitoring the efficacy of a vaccination against SARS-CoV-in an individual, comprising performing any of the above methods with a biological sample from said individual, is also part of the present invention. Another aspect of the invention is also the use of one of the above methods for in vitro assessing the susceptibility or resistance status of an individual after vaccination, to monitor the efficacy of a vaccination against SARS-CoV-2 in an individual or in a population. The invention also relates to an immunogenic composition comprising, in one or several polypeptides, the epitopes present in a sequence corresponding to amino acids 331 to 525 of a SARS-CoV-2 spike protein, as well as, optionally, the epitopes present in a sequence corresponding to amino acids 1 to 165 of a SARS-CoV-2 spike protein.
A nucleic acid molecule encoding the above-defined polypeptides is also part of the invention, as well as an immunogenic composition comprising the same. The present invention also relates to a vaccine comprising an immunogenic composition as described above, as well as a pharmaceutically acceptable excipient and/or adjuvant. Another aspect of the present invention is an immunogenic composition comprising a polypeptide comprising or consisting of the sequence LDSKVGGNY (SEQ ID No: 262), or a nucleic acid encoding the same, for use in the treatment of cancer.
BRIEF DESCRIPTION OF THE DRAWINGS Figure Legends Figure 1. SARS-CoV-2 TH1/Tc1 responses in COVID-19 and unexposed individuals. A.Graphical representation of the prospective patient cohorts used for the study (refer to Table 1 to 3). B. First experimental in vitro stimulation assay of peripheral blood lymphocytes (PBL) using crosspresentation of viral lysates by autologous dendritic cells (DC). Twelve plex flow cytometric assay to monitor cytokine release in replicates. C.Mean fold changes (Log 2, F.C) between SARS-CoV-2-specific cytokine secretions of acute COVID-19 patients or convalescent COVID-19 individuals and controls (also refer to S1C). D. Ratios of cytokine secretion between PBL stimulated with DC pulsed with SARS-CoV-2 (or the other CCC lysates) versus VeroE6 (or versus CCC respective control cell lines), at the acute or convalescent phases of COVID-19. One typical example is outlined in Figure S1A of Fahrner et al., 2022 [100]. Each dot represents the mean of replicate wells for one patient (Controls, n=304; Convalescent COVID-19, n=54; Acute COVID-19, n=24). Asterisks indicate statistically significant differences in comparison to the control group determined using two-sided Wilcoxon-Mann-Whitney test (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). E. Spearman correlations between SARS-CoV-2-specific IL-2 release and anti-NC IgG antibody titers (Controls, n=63; Convalescent, n =16). F. Spearman correlations between SARS-CoV-2-specific IL-release and anti-NC IgG antibody titers (Controls, n=63; Convalescent, n=16). Figure 2. Unexposed individuals susceptible to COVID-19 exhibited a SARS-CoV- 2 specific TH2 profile during the first surge of the pandemic. A-B. Upper scheme: Outline of the prospective collection of blood samples used to identify COVID-19 resistant (light grey) versus susceptible (black) cancer patients (A, upper panel, Table 1, Tables 4&5) and pie chart indicating the absolute numbers (and %) of patients reported as contact (resistant) or infected (susceptible) or unexposed (grey) 35 during one-year follow-up (B). Lower scheme: Outline of the prospective collection of blood samples used for the comparison of T cell responses in the cohort of cancer-free individuals who lived in the same household with family members tested positive for COVID-19 during the 2020 lock down (Table 4). C. Number of positive cytokines released by SARS-CoV-2-specific PBL during the crosspresentation assay (Figure 1B) in each group (Unexposed, n=159; Resistant, n=48; Susceptible, n=22). D-E.SARS-CoV-2-specific IL-2 (left panel) and IL-5 (right panel) secretion contrasting resistant (light grey) versus infected (black) cancer cases. Each dot represents the ratio (D) of the replicate wells in one individual and the box plots indicate medians, 25th and 75th percentiles for each cancer patient subset. The bar plots (E) represent the percentage of positive patients (resist., n=41; suscept., n=19). Fisher exact test to compare the number of cytokine positive patients across groups (*p<0.05). F.SARS-CoV-2-specific IL-2/IL-5 ratios (means+SEM) in the different subsets of healthy and cancer individuals presented in panel A. Refer to Figure 7 for the waterfall plots to visualize variations in the percentages of individuals with IL-2/IL-5 ratios > or < 1 according to subject category. All group comparisons were performed using two-sided Wilcoxon-Mann-Whitney test and asterisks indicate statistically significant differences. G . CCC (OC43 and 229E)-specific IL-2 ratio (left panel) or IL-5 secretion ratio (right panel) contrasting contact (resistant, light grey dots, n=34) versus infected (susceptible, black dots, n=11) cases. H . Spearman correlations between OC43 and SARS-CoV-2-specific IL-2 (left panel) and IL-5 (right panel) secretions in 156 controls. I . Anti-spike IgG titers (means+SEM) specific of seasonal betacoronaviruses in contact (resist., light grey dots, n=34) versus infected (suscept., black dots, n=11) cases. J-K . SARS-CoV-2-specific T cell reactivity monitored by IL-5 and IFNγ-ELISA ( J ) or IFNγ ELISpot (K) before and after Dupilumab in 9 patients diagnosed with atopic dermatitis. Each line represents the mean of two experimental replicates that are shown for n=3 samples before Dupilumab, and for n=7 samples after Dupilumab, including 7/9 in COVID-19 convalescence, only one patient had paired samples pre- and post-Dupilumab. Wilcoxon signed rank test for paired comparisons of clustered data ( J ) or linear mixed model ( K ) were used to compare experimental groups. L. Scheme detailing the two groups of cancer-free individuals from the same hospital with opposite clinical phenotypes (multi-exposed individuals (n=12) versus patients reinfected with SARS-CoV-2 (n=17) patients) (K, left panel). Results of the crosspresentation assay against SARS-CoV-2 for IL-10 (K, right panel) and IL-2. IL-levels at baseline and after TCR cross-linking are depicted in the middle panel. Each dot represents the mean of two replicates for one patient. All group comparisons were performed using two-sided Wilcoxon-Mann-Whitney test and asterisks indicate statistically significant differences (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001).
Figure 3. Peptide recognition patterns in all distinct subsets of individuals: repertoire breadth of peptide does not predict resistance to COVID-19. A. Experimental setting for the 185 peptide-based in vitro stimulation assays. B-C. Percentages of positive peptides in individuals from the pre-COVID19 era (n=24) versus contemporary controls (n=97) (B, right panel) and in cancer (n=111) versus cancer free contemporary individuals (n=10) (B, left panel) and in uninfected (control (contemporary), n=97) versus convalescent (recovery, n=27) (C, left panel) and resistant individuals (non-infected contact cases (n=44) versus susceptible (infected, n=18) individuals (C, right panel). Group comparisons were performed using two-sided Wilcoxon-Mann-Whitney test and asterisks indicate statistically significant differences (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). Figure 4. Spike Receptor Binding Domain (S1-RBD)-directed TH1/Tc1 recall responses predict resistance to COVID-19. A. Volcano plot showing statistical significance (p values) and magnitude of change in odd ratios of IFNγ secretion in response to SARS-CoV-1 (sarbecovirus) and SARS-CoV- 2 peptides belonging to distinct viral proteins (each scatterplot) between susceptible versus resistant individuals. B-D . Percentages of patients recognizing at least one of the S1-RBD peptides in the IFNγ ELISA of the peptide IVS assay across patients’ groups described in Figure 2A (B) or convalescent versus reinfected patients (C) or vaccinees experiencing breakthrough infection (D). E. Percentages and absolute numbers of mutations contained in our S1-RBD peptide list reported in the current SARS-CoV-variants (refer to Table S12 of Fahrner et al., 2022). The difference of the probability of mutation in S1-RBD region and in other regions was evaluated using logistic regression (Odd Ratio=0.21, 95% confidence interval [0.06; 0.68], p=0.01). F, H. High-throughput screening T cell assay using the Enzyme Linked Fluorescent Assay technique in an automatic platform monitoring IFNγ levels in whole blood samples from several independent cohorts of HCW (F) or cancer patients (H) with or without COVID-19 history (F), pre- and/or per (after 1 immunization, Day 21) and/or post vaccination (Day 90, Day 180) using different peptide pools (Table 12,). Monitoring of IFNγ release (F, H lower panels) and percentages of individuals with IFNγ levels > threshold of detection (upper panels). G. Influence of covariates (refer to Subtables S13a and S13b of Fahrner et al., 2022 for statistics). Specimen were not systematically paired in the kinetic study. The log 10 normalized IFNγ secretions for all peptide stimulation were pooled to model simultaneously their dynamics from the first vaccine to day 180 using linear mixed effect regression adjusted for the patient age, sex, cancer status, COVID history, and vaccine schedule (cf statistical method section for more details). The Forest plot depicts the impact of the different variables on the PEPwtRBD IFNγ secretion levels (a positive or negative coefficient indicating increase or decrease of IFNγ IU/ml respectively) (G). I . Paired analysis of the differential magnitude of TH1/Tc1 reactivity against PEP wtRBD versus PEP mutRBD in 343 cancer-free HCW vaccinees with no history of COVID-19. Each line represents one patient sample. Group comparisons were performed using two-sided paired Wilcoxon-Mann-Whitney test and asterisks indicate statistically significant differences (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). Figure 5. Detailed SARS-CoV-2 and CCC-specific cytokine release for convalescent COVID-19 patients compared with unexposed individuals. A. Percentage and number of patients in each cohort (Pre-COVID19 era (yes (+)/no(-)), Cancer (yes (+)/no(-) and COVID-19 (yes (+)/no(-)) who had a SARS-CoV-2-specific cytokine release (for the 5 statistically significant cytokines at the convalescent phase) compared with VeroE6 (Control, n=304; Convalescent, n=54). B-C. Idem as in Figure 1D comparing frequencies of patients with CoV-2/VeroE6 ratios>2 for the most relevant cytokines in cancer versus cancer-free control individuals, taking into account cancer staging (C). Asterisks indicate statistically significant differences of SARS-CoV-2- specific cytokine release proportions between two groups determined using Fisher exact test (*p<0.05). Figure 6. TH1/Tc1 differentiation patterns in susceptible versus resistant individuals. A-B. Unsupervised hierarchical clustering of SARS-CoV-2-specific cytokine release. Heatmap of cytokine release in the crosspresentation assay performed during the first surge of the pandemic in unexposed individuals (n=60), aligning cytokines in the two subject categories, susceptible (persons who got infected during the second or the third surge of the pandemic) versus resistant (contact) individuals. Group comparisons were performed using a two-sided Wilcoxon-Mann-Whitney test. C. Dynamic study of the stability of the TH1/TH2 profile in individuals that were followed up at two time points. Ratio of cytokine release at the acute and convalescent phase (left panel) and corresponding IL-2/IL-5 ratio (right panel) in 5 cancer patients. Two-sided Wilcoxon-Mann-Whitney test did not reveal significant difference between both time points. D.Validation cohort of 2A with 8 additional HCW from Hospices Civils de Lyon (HCL) and 10 cancer patients from Gustave Roussy (D). E . Percentages of SARS-CoV-specific TH1 or TH2 cell responses determined by dual Elispot assay (CoV2/VeroE>1.5 increase in IFNγ+(left) or IL-5+ (middle) SFC respectively). Calculation of the IFNγ+ /IL-5+ SFC ratio per individual in VeroE6 or SARS-CoV-2 condition, and percentages of patients with an increased (>2) ratio in the SARS-CoV-2 condition, in both Resist versus Suscep. Groups (right panel). Fisher’s exact test to compare the number of patients positive for each category between groups (*p<0.05, **p<0.01).
Figure 7. Waterfall plots indicating the IL-2/IL-5 ratio in all patient or individual groups.Waterfall plot between IL-2 and IL-5 ratio of cytokine release in the Figure 1B IVS assay in all patients during the first surge of the pandemic depicting cancer (grey) versus cancer free (black) COVID-19+ convalescent patients (D), resistant (grey) versus susceptible (black) (A), locked down (or unknown) subjects (B, n=301) and healthy individuals in contact with their COVID-19+ family members (C). Each bar represents one patient. Proportion of patients exhibiting an IL-2/IL-5 ratio superior or inferior to 1 is indicated in each panel. Clinical conditions are annotated as 0, +, ++, +++ for asymptomatic, mild, moderate, and severe COVID-19 severity, respectively. Refer to Figure 2F where percentages are compared inbetween groups. Figure 8. Crosspresentation assays using viral variants. A.Percentage and number of patients in Fig2L right panel who had a SARS-CoV-2-specific IL-2 release. Of note, only 4 reinfected patients could be tested because DC could not be differentiated into monocytes in the others to allow the crosspresentation assay. B. Cytokine ratio in the crosspresentation assay detailed in Figure 1B, using the original strain IHUMI846 (early 2020 episode) (CoV-2 in (A)), versus the Danish mink (B.1.160, 20A.EU2, GH) and North African (B1.367, 20C, GH) strains in 25 control individuals. Statistical comparisons were performed using paired two-sided Wilcoxon-Mann-Whitney test and the asterisks indicate statistically significant differences (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). Figure 9. Logistic regression analyses identifying cohort -specific fingerprints of T cell repertoires. A. Statistically significant peptide signatures in the peptide-based IVS assay (Figure 3A) using a multivariable logistic regression analysis adjusted for period (pre-COVID-19 era or contemporary patients), COVID-19 history and cancer (refer to Tables 2 and 3). The left column shows variables, and the x axis indicates the significant peptides (pval<0.05). The magnitude of the log (Odd Ratio) is indicated in the red/blue color code while that of the p-value is represented by the circle size. B-C.Log10 of the p value of the Fisher exact test comparing two groups of 101 individuals, based on their reactivity to PEP wtRBD (yes/no) for each HLA allele (B), followed by selection of the most significant allele with its relative proportion among RBD reactive or areactive vaccinees (C).
DETAILED DESCRIPTION According to a first aspect, the present invention pertains to a method for in vitro determining whether an individual is likely to resist to an infection by SARS-CoV-2, comprising: (i) generating dendritic cells (DC) from monocytes obtained from said individual; (ii) loading said DC with a SARS-CoV-2 lysate or SARS-CoV-2 antigens; (iii) contacting peripheral blood lymphocytes (PBL) from said individual with the DC obtained in step (ii), in appropriate conditions to activate said PBL; (iv) following the PBL activation, measuring the expression of at least one cytokine secreted by Th1 cells, selected from the group consisting of IL-2, IFNγ and TNFa, and measuring the expression of at least one cytokine secreted by Th2 cells, selected from the group consisting of IL-5, IL-4, IL-9, IL-10 and IL-13; and (v) from the results of step (iv), assessing the Th1/Th2 polarization of SARS-CoV-2-specific memory T cell response in said individual, wherein a Th1 polarization indicates that the individual is likely to resist to an infection by SARS-CoV-2, and a Th2 polarization indicates that the individual is susceptible to an infection by SARS-CoV-2. An individual "susceptible" to an infection by SARS-CoV-2 is one having little resistance to such an infection, and therefore capable of being infected. In the above method, a "SARS-CoV-2 lysate" preferably refers to a lysate of a SARS-CoV-2 circulating strain, against which the resistance status of the individual is sought, or a lysate of a strain genetically close to said circulating strain. Similarly, "SARS-CoV-2 antigens" preferably refers to antigens of a SARS-CoV-2 circulating strain, against which the resistance status of the individual is sought, or antigens of a strain genetically close to said circulating strain. According to a particular embodiment, the SARS-CoV-2 antigens comprise or consist of a SARS-CoV-Spike protein or a fragment thereof comprising the receptor binding domain (RBD) of the Spike protein (corresponding to amino acids 331-525 of the spike protein of the reference Wuhan strain). Preferably, the Spike RBD present in the antigen(s) used for loading the dendritic cells is identical to that of the circulating strain, or has at least 80%, preferably at least 90% and more preferably at least 95% identity with the RBD of the Spike protein of the circulating strain. According to a particular embodiment of the above method, the expressions of IL-2 and IL-5 are measured in step (iv), and the ratio IL2/IL-5 is calculated in step (v). A ratio IL2/IL5>1 indicates that the individual is likely to resist to an infection 35 by SARS-CoV-2, and IL2/IL5≤1 indicates that the individual is susceptible to an infection by SARS-CoV-2. According to another embodiment, the present invention relates to a method for in vitro determining whether an individual is likely to resist to an infection by SARS-CoV-2, comprising: (i) incubating T lymphocytes from said individual with a mix of antigenic peptides from SARS-CoV-2, under conditions appropriate to stimulate Th1 and/or Thlymphocytes specific for said peptides; and (ii) assessing the presence of Th1 and/or Th2 lymphocytes; wherein the presence of Th1 lymphocytes specific for said peptides indicates that the individual is likely to resist to an infection by SARS-CoV-2, and/or the absence of Thlymphocytes and/or the presence of Th2 lymphocytes specific for said peptides indicates that the individual is susceptible to an infection by SARS-CoV-2. While the experimental part illustrates this method with an incubation time of several days, the skilled person can of course modify the protocol to shorten this incubation time and/or automate the whole process, for example by using techniques disclosed in WO2018/202864 and in references cited therein. In the above method, the "mix of antigenic peptides from SARS-CoV-2" preferably comprises peptides comprising epitopes of the RBD of the Spike protein of a circulating strain, or epitopes able to trigger an immune reaction cross-reacting with the RBD of a SARS-CoV-2 circulating strain, against which the resistance status of the individual is sought. According to a particular embodiment, the mix of antigenic peptides comprises at least five peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 331 to 555 of a SARS-CoV-2 spike protein (preferably identical or having at least 80%, at least 90% and preferably at least 95% identity with the aminoacids 331 to 555 of the SARS-CoV-2 spike protein of a circulating strain). As already mentioned, in the present text, the aminoacid positions are those of the proteins of the reference strain (Wuhan), which are disclosed in GenBank (MN908947.3). According to another particular embodiment, the mix of antigenic peptides used to perform the above method comprises: - at least five peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 331 to 555 of a SARS-CoV-2 spike protein; and - at least one, preferably at least two or at least three peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 nucleocapsid protein.
As described in the experimental part below, the inventors identified the subregions of the spike proteins which are of particular importance in the immune response against the virus. Thus, according to another particular embodiment, the mix of antigenic peptides used to perform the above method comprises: - at least five peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 361 to 555 of a SARS-CoV-2 spike protein, wherein at least one or two of said peptides are preferably from a sequence consisting of aminoacids 361 to 495 of a SARS-CoV-2 spike protein and at least one or two of said peptides are preferably from a sequence consisting of aminoacids 466 to 555 of a SARS-CoV-2 spike protein; and - at least two, preferably at least 3 peptides of 9 to 50 aminoacids, preferably to 25 aminoacids, from a sequence consisting of aminoacids 1 to 135 of a SARS-CoV-spike protein. According to yet another particular embodiment, the mix of antigenic peptides used to perform the above method comprises: - at least one, preferably at least two or at least three peptides of 9 to aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids to 270 of a SARS-CoV-2 nucleocapsid protein; and/or - at least one, preferably at least two or at least three peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 331 to 419 of a SARS-CoV-2 nucleocapsid protein; and/or - one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF3a_AB protein, preferably consisting of or encompassing a sequence consisting of aminoacids 244 to 258 of said SARS-CoV-2 ORF3a_AB protein; and/or - at least two peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 856 to 1050 of a SARS-CoV-2 spike protein. According to yet another particular embodiment, the mix of antigenic peptides used to perform the above method comprises: - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 1 to 165 of a SARS-CoV-2 spike protein; and/or - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF10 protein; preferably from a sequence consisting of aminoacids to 22 of a SARS-CoV-2 ORF10 protein and/or - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF8 protein, preferably from a sequence consisting of aminoacids 1 to 36 or 99 to 121 of a SARS-CoV-2 ORF8 protein.
When performing the above method, step (i) can be performed by incubating T lymphocytes with the mix of antigenic peptides from SARS-CoV-2 in the presence of IL-2 and IL-15 to stimulate Th1 and/or Th2 lymphocytes specific for said peptides; in step (ii), the presence of Th1 lymphocytes can then be assessed by measuring the production of IFNγ and/or the presence of Th2 lymphocytes can be assessed by measuring the production of at least one cytokine selected from IL-5, IL-4, IL-6, IL-9 IL-10 and IL-13. Alternatively, the stimulation of Th1 and/or Th2 lymphocytes in step (i) can be done by incubating T lymphocytes with the mix of antigenic peptides from SARS-CoV-2 in the presence of low doses of IL-2 or IL-15, or PMA/ionomycine, or low dose of anti CD3/anti CD28 antibodies to sensitize the TCR, in addition to IL-4 and/or anti-ILantibodies; then, in step (ii), the presence of Th2 lymphocytes can be assessed by measuring the production of at least one cytokine selected from IL-5, IL-9 IL-10 and IL-13. According to a particular embodiment, the above method can be performed using at least one recipient that contains a mix of peptides which are common to all known strains of SARS-CoV-2 or induce cross-reactive immunity. Alternatively or additionally, the above method is performed using at least one recipient that contains a mix of peptides which encompass the RBD region of circulating strain(s) of SARS-CoV-2 or induce cross-reactive immunity against this region in circulating strain(s). According to a particular embodiment of the above method, the mix of peptides is dispatched in several recipients for performing the method, wherein at least one recipient contains a mix of peptides which are specific for one or more SARS-CoV-variant(s). The skilled person can thus establish a detailed profile of the individual or of a population, for example to assess the prevalence or the dynamics of a given strain. According to a particular embodiment of the above method, the mix of peptides is dispatched in several recipients for performing the method, wherein at least one recipient contains a mix of peptides which are common to all known strains of SARS-CoV-2 or induce cross-reactive immunity, and at least another recipient comprises a mix of peptides which are specific for one or more SARS-CoV-2 variant(s). When the above method is performed with a recipient that contains a mix of peptides which are common to all known strains of SARS-CoV-2 or induce cross-reactive immunity, detection of Th1 lymphocytes in said recipient indicates that the individual is likely to resist to an infection by any SARS-CoV-2 strain. Conversely, when the method is performed with a mix of peptides comprising only peptides present in the proteins of a given variant strain of SARS-CoV-2, the result indicates whether the individual is likely to resist to an infection by this variant strain of SARS-CoV-2. According to a particular embodiment of the above method, the Thresponse is assessed using a first mix of peptides comprising at least 3, 4, 5, 6 or more peptides relevant for assessing Th1 response against SARS-CoV-2 and the Th2 response is assessed using a second mix of peptides comprising at least 3, 4, 5, 6 or more peptides relevant for assessing Th2 response against SARS-CoV-2. The skilled person can chose the peptides present in the first and/or second mixes of peptides so that they comprise at least one peptide described in Table 12. According to a particular embodiment, several peptides are selected amongst those of Table 12. These two mixes of peptides can be identical or partially or totally different. According to a particular embodiment, the first and second mixes of peptides are present in separate recipients/tubes. When performing the above method, the presence of Th1 lymphocytes can be assessed in step (ii) by measuring the production of IFNγ in the recipient comprising the first mix of peptides and the presence of Th2 lymphocytes can be assessed by measuring the production of at least one cytokine selected from IL-5 in the recipient comprising the second mix of peptides. In the absence of Th1 after incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 521 and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein (under conditions appropriate to stimulate Th1), the skilled person performing the method can deduce that the individual is susceptible to an infection by SARS-CoV-2 and its variants. The same interpretation can be deduced if the results show the presence of a Th2 response combined to the absence or weak presence of Th1 after incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 521 and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein indicates that the individual is susceptible to an infection by SARS-CoV-2 and its variants (under conditions appropriate to stimulate Th1/Th2). Conversely, the presence of Th1 after incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 521 and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein indicates that the individual is likely to resist to an infection by SARS-CoV-2 and its variants, at least to an infection by a SARS-CoV-2 strain having a RBD sequence with a high level of identity (at least 80%, 90%, 95% or 99%) with the sequences used to perform the method.
The inventors identified that the most important target for a protective Thresponse is that of the RBD of the spike protein. If this region is not tested or elicits a poor Th1 response, the presence of Th1 after incubation of the T lymphocytes with a mix of peptides comprised in a sequence consisting of amino acids 1 to 135 of a SARS-CoV-spike protein indicates that the individual is likely to resist to an infection by SARS- CoV-2 and its variants, only if a Th1 response has also been obtained against another part of the virus, e.g. against peptides of the nucleocapsid. According to another of its aspects, the present invention pertains to a method for monitoring the efficacy of a vaccination against SARS-CoV-2 in an individual, comprising performing a method as those described above with a biological sample from said individual (after vaccination). This method can advantageously be used to assess the efficacy of a vaccine for inducing a protective immune response against one or several new variant(s). For example, using peptides specific for said new variant(s) to stimulate Thand/or Th2 lymphocytes after vaccination (prime or boost) of the individual with a vaccine based on the Wuhan strain, a skilled person can assess whether the individual has become resistant to said new variant(s) thanks to this vaccination. Doing so in a representative cohort would provide information useful for dynamically establishing a correct vaccination policy in a population, depending of the population (age, …) and the time (circulating and/or emerging strains). Of course, at the individual level, this method can be used to monitor the efficacy of a vaccination against SARS-CoV-2 in an individual. Another aspect of the present invention is an immunogenic composition comprising, in one or several polypeptides, the epitopes present in a sequence corresponding to amino acids 331 to 525 of a SARS-CoV-2 spike protein; such an immunogenic composition can additionally comprise, in the same or in different polypeptides, the epitopes present in a sequence corresponding to amino acids 1 to 1of a SARS-CoV-2 spike protein. According to a particular embodiment such an immunogenic composition comprises a first polypeptide sequence comprising amino acids 331 to 525 of a SARS- CoV-2 spike protein, and a second polypeptide sequence comprising amino acids 1 to 165 of a SARS-CoV-2 spike protein, wherein said first and second polypeptide sequences are in the same polypeptide molecule or in separate polypeptides which are distinct from a natural spike protein. According to an example of such an immunogenic composition, the first polypeptide sequence consists of amino acids 331 to 525 of a SARS-CoV-2 spike protein, and/or the second polypeptide sequence consists of amino acids 1 to 165 of a SARS-CoV-2 spike protein. According to another example of such an immunogenic composition, the first polypeptide sequence consists of amino acids 331 to 600 of a SARS-CoV-2 spike protein or a fragment thereof, and/or the second polypeptide sequence consists of amino acids 1 to 270 of a SARS-CoV-2 spike protein or a fragment thereof. As already mentioned, the above amino acid positions are those of the reference Wuhan strain, it being clearly understood that the immunogenic composition can comprise sequences originating from one or several other SARS-CoV-2 strain, for example from circulating variant(s) of concern. In addition to the polypeptides mentioned above, an immunogenic composition according to the invention can further comprise a polypeptide sequence comprising amino acids 1 to 270 of a SARS-CoV-2 nucleocapsid protein, and/or a polypeptide sequence comprising amino acids 244 to 258 of a SARS-CoV-2 ORF3a_AB protein, and/or a polypeptide sequence comprising amino acids 29 to 92 of a SARS- CoV-2 ORF8 protein, and/or a polypeptide sequence comprising amino acids 1 to 36 of a SARS-CoV-2 ORF8 protein, and/or a polypeptide sequence comprising amino acids to 38 of a SARS-CoV-2 ORF10 protein, wherein said additional polypeptide sequence(s) are in the same polypeptide molecule as the first and/or second polypeptide sequences or are in one or several separate polypeptide(s). As shown in Example 2, the inventors also tested tumor infiltrating lymphocytes (TIL) from patients in the pre-pandemic time, and during the pandemic, to identify potential T-cell cross-reactivity between SARS-CoV-2 and self or viral proteins. By doing so, they identified cross-reactivity with SARS-CoV-1 but not with other circulating Coronaviral species, as well as a possible cross-reactivity to non-mutant or mutant human ‘self proteins’. TIL are an interesting source to screen for potential autoimmunity in viral targets because they invade tissues. Positive reactivity against SARS-CoV-2 peptides, based on the cytokine production pattern, can thus indicate an increased risk for autoimmune diseases upon exposure to the viral pathogen, or an increased pathogenicity upon viral infection due to an overt immune response (unproductive inflammation in the lung and other organs). To avoid such reaction and possible resulting organ-specific damage (such as myocarditis or damage of olfactory receptors for example), immunogenic compositions designed for being administered to humans should thus be devoid of sequences which could be recognized by T-cells also recognizing non-mutant human tissue. 35 Hence, according to a particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence LVRDLPQGFSALE (SEQ ID No: 377). According to another particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence DVRVVLDFI (SEQ ID No: 178). According to another particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence LLNKHIDAY (SEQ ID No: 275). According to another particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence IELCVDEAG (SEQ ID No: 305). According to another particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence MKFLVFLGI (SEQ ID No: 308). According to another particular embodiment, the immunogenic composition according to the invention does not comprise the peptide sequence MKFLVFLGIITTV (SEQ ID No:378). Of course, the immunogenic compositions according to the invention can be administered as polypeptide(s), or in the form of a nucleic acid molecule encoding the same. Such a nucleic acid molecule encoding the polypeptide(s) present in immunogenic compositions defined above are thus also part of the present invention, as well as an immunogenic composition comprising the same such as, for example, a viral vector comprising the same. According to a preferred embodiment, the nucleic acid molecule according to the invention is a RNA molecule. Another aspect of the present invention is a vaccine composition against SARS-CoV-2. In a particular embodiment, such a vaccine composition comprises an immunogenic composition as any one of those described above, as well as a pharmaceutically acceptable excipient and/or adjuvant. Preferred adjuvants are those that favor a Th1 response. Examples of adjuvants which are appropriate for being included in a vaccine composition according to the invention thus include TLR4 agonists, TLR3 ligands/ agonists, TLR7-8 agonists and TLR9 agonists. More particularly, a vaccine composition according to the invention can advantageously comprise at least one adjuvant selected from the group consisting of lipopolysaccharides, MPL: 3-O-desacyl-4’-monophosphoryl lipid A derived from Salmonella minnesotta LPS, poly A :U, poly I :C, IMIQUIMOD, CpG DNA and CpG ODNs. Surprisingly, the inventors also identified a sequence in the spike protein of SARS-CoV-2 that shares antigenic sites with an antigen that is specific for certain forms of cancers. Due to this antigenic mimicry, an infection by SARS-CoV-2 could elicit an immune response ameliorating the patients’ antitumor response. The present invention thus pertains to an immunogenic composition comprising a polypeptide comprising a sequence selected amongst LDSKVGGNY (SEQ ID No: 262), NSNNLDSKV (SEQ ID No: 263) and NSNNLDSKVGGNY (SEQ ID No: 379), or a nucleic acid encoding the same, for use in the treatment of cancer. According to a preferred embodiment, such an immunogenic composition is used in the treatment of a cancer overexpressing Tensin-1. Such an immunogenic composition according to the invention is particularly useful for immunotherapy of a pancreas adenocarcinoma or a colon adenocarcinoma. Other characteristics of the invention will also become apparent in the course of the description which follows of the experimental assays which have been performed in the framework of the invention and which provide it with the required experimental support, without limiting its scope.
EXAMPLES Example 1: The polarity and specificity of SARS-CoV2 -specific T lymphocyte responses determine disease susceptibility Material and methods Patient and cohort characteristics.All clinical studies were conducted after written informed consent in accordance with Good Clinical Practice guidelines and the provisions of the Declaration of Helsinki. Cohorts’ and subsets’ characteristics are detailed in Tables 1 to 8, 10 and 14, and Figure 1A. Two cohorts of cancer patients (from the pre-COVID-19 era and from the COVID-19 era) and three cohorts of healthy volunteers (from the pre- COVID-19 era and from the COVID-19 period including three cohorts of vaccinees (HCL, GR, cancer/cancer free) were exploited to set up the translational research analyses. Peripheral blood mononuclear cells (PBMC) were provided by Gustave Roussy Cancer Campus (Villejuif, France) and IHU Méditerranée Infection (Marseille, France) (see Blood analyses section). The type of ancillary studies is detailed in Table 1. Contemporary clinical studies (COVID-19 era): 1/ ONCOVID clinical trial and regulatory approvals. Principles. The protocol NCT04341207 is available on the clinicaltrials.gov website. Gustave Roussy Cancer Center sponsored the trial named `ONCOVID` and collaborated with the academic authors on the trial design and on the collection, analysis, and interpretation of the data. Sanofi provided trial drugs. Protocol approval was obtained from an independent ethics committee (ethics protocol number EudraCT No: 2020-001250-21). For details, refer to previous report [32]. Samples for translational research.PMBCs were isolated less than 8 hours after the blood collection (at patient inclusion and at every hospital visit) and kept frozen at-80°C. 2/ PROTECT-Cov clinical trial and regulatory approvals. Principles.IHU Méditerranée Infection sponsored the trial named `PROTECT-Cov` and collaborated with the academic authors on the trial design and on the collection, analysis, and interpretation of the data. Protocol approval was obtained from an independent ethics committee (ethics protocol number ANSM No: 2020-A01546-33). The trial was conducted in accordance with Good Clinical Practice guidelines and the provisions of the Declaration of Helsinki. All patients provided written informed consent. Subjects. PROTECT-Cov eligible subjects were members of the same family/home composed of two or more people and selected from the microbiology laboratory register on SARS-Cov-2 tests performed between March 23 and April 10, 2020. Trial design. Members of the same family/home who had at least one (a)symptomatic COVID-19 + case (RT-qPCR <35 Ct values for SARS-CoV-2 on nasopharyngeal swabs) and at least one member with negative RT-qPCR for SARS-CoV-2 (≥35 Ct) were screened. A telephone interview was conducted in order to confirm and complete the list of family circles in connection with the positive case. The compliant subjects finally selected were invited to come back to the IHU Méditerranée Infections hospital where they were included in the trial and had a blood test. 3/ COVID-SER clinical trial and regulatory approvals. Principles.At the "Hospices Civils de Lyon", France was conducted the trial named COVID-SER. Protocol approval was obtained from an independent ethics committee (the national review board for biomedical research, Comité de Protection des Personnes Sud Méditerranée, ID-RCB-2020- A00932-37). The clinical study was registered on ClinicalTrial.gov (NCT04341142). For details, refer to Mouton et al. [43]. Written informed consent was obtained from all participants and the study. Blood sampling was performed before vaccination and weeks after receiving 1 or 2 doses of vaccine for naive and convalescent health care workers respectively. According to French procedures, a written non-opposition to the use of donated blood for research purposes was obtained from healthy volunteers. The donors’ personal data were anonymized before transfer to our research laboratory. We obtained approval from the local ethical committee and the French ministry of research (DC-2008-64) for handling and conservation of these samples. Human biological samples and associated data were obtained from NeuroBioTec (CRB HCL, Lyon France, Biobank BB-0033-00046) and Virginie Pitiot. 4/ COV3AP-HP clinical trial and regulatory approvals. Principles BioMérieux S.A is the promotor of the trial "COV3AP-HP" approved by the local ethical committee (number N° ID-RCB : 2021-A00304-37). The trial was conducted in accordance with Good Clinical Practice guidelines and the provisions of the Declaration of Helsinki at Gustave Roussy and Cochin Institute, France. All subjects provided written informed consent. 5/ Dupilumab for atopic dermatitis translational study. This trial was conducted at the Department of Dermatology, Center of Excellence in Eczema Laboratory of Inflammatory Skin Diseases, Icahn School of Medicine at Mount Sinai New York, NY, USA with Regeneron sponsorship after ethical committee approval (STUDY-20-00682-MOD001). Clinical studies from the Pre-COVID-19 era: 1/ Series of patients with cancer:This cohort is composed of different IGR clinical trials. Patients were included and blood was collected and banked between 1999 and 2018 (Pre-COVID-19 era). Clinical studieshave been described in previous reports [29,31,77] (CALEX protocol, n1 ID RCB 2007-A01074-49, date 29 February 2008). (Study code « Dex2 »: NCT01159288, date 19 December 2005) (Study code « LUD 99 003 »: N-CSET : 99/090/752, date 1 December 1999) (Phase I IMAIL-2 trial approved by the Kremlin Bicêtre Hospital Ethics Committee [no 07–019] and the Agence Française de Sécurité Sanitaire des Produits de Santé [no A70385–27; EudraCT N°:2007–001699–35 in 2007). 2/ Series of patients without cancer :Peripheral blood was obtained from healthy volunteers at the Etablissement Français du Sang (EFS, Paris France, n 18EFS031 date 24 September 2018). Blood analyses. Blood samples (for serum and PBL) were drawn from patients enrolled in the different cohorts presented in the cohort description section above. Whole human peripheral blood was collected into sterile vacutainer tubes. Anti-SARS-CoV-2 immunoglobulins measurements. Serum was collected from whole blood after centrifugation at 600 g for 10 min at room temperature and transferred to -80°C freezer to await analysis. Serological analysis SARS-CoV-2 specific IgA, IgM and IgG antibodies were measured in 119 serum samples from 87 patients with The Maverick™ SARS-CoV-Multi-Antigen Serology Panel (Genalyte Inc. USA) according to the manufacturer’s instructions. The Maverick™ SARS-CoV-2 Multi-Antigen Serology Panel (Genalyte Inc) is designed to detect antibodies to five SARS-CoV-2 antigens: nucleocapsid, Spike S1 RBD, Spike S1S2, Spike S2 and Spike S1 or seasonal HCoV -NL-63 nucleocapsid, -OC-43, -229E and -HK-U1 Spike in a multiplex format based on photonic ring resonance technology. This system detects and measures with good reproducibility changes in resonance when antibodies bind to their respective antigens in the chip. The instrument automates the assay. Briefly, 10µl of each serum samples were added in a sample well plate array containing required diluents and buffers. The plate and chip are loaded in the instrument. First the chip is equilibrated with the diluent buffer to get baseline resonance. Serum sample is then charged over the chip to bind specific antibodies to antigens present on the chip. Next, chip is washed to remove low affinity binders. Finally, specific antibodies of patients are detected with anti-IgG or -IgA or -IgM secondary antibodies. Isolation of peripheral blood mononuclear cells (PBMCs) from fresh blood sampling.Venous blood samples (10ml to 30ml) were collected in heparinized tubes (BD Vacutainer® LH 170 U.I., Dutscher, UK). On the same day, blood was processed in a biosafety level 2 laboratory at Gustave Roussy Institute, Villejuif, France, or in IHU Méditerranée Infection, Marseille, France. Peripheral blood mononuclear cells (PBMCs) were freshly isolated by LSM, Lymphocyte Separation Medium (Eurobio Scientific, France) density gradient centrifugation according to manufacturer’s instructions. (Leucosep tubes, Greiner; Biocoll, Bio&SELL). PBMCs were then collected, washed once with phosphate-buffered saline solution (PBS) and aliquoted in 1ml of cryopreservation medium (CryoStor®, STEMCELLS Technologies, USA) in cryovials (two cryovials per patient). Cryovials (CryotubeTM vials ThermoFisher Scientific, Denmark) were conserved for 24h at -80°C in a cryo-freezing container (Mr.FrostyTM,Thermo Fisher Scientific) before storage in liquid nitrogen. Serum and serologies . Specific anti-SARS-CoV-2 IgG antibodies were detected by the Liaison XL automated chemiluminescent immunoassay (CLIA) (Diasorin Inc., Saluggia, Italy) according to the manufacturer’s recommendations. Seroneutralization was performed as already described [78]. Reagents: culture media, cytokines, ELISA and multiplex assays. PBMC isolation. Blood samples were collected in heparinized tubes BD Vacutainer® LH 170 U.I., from Dutscher (catalog reference: 367526), diluted in PBS 1X purchased from Eurobio Scientific (catalog reference: CS3PBS01-01) and transferred in LeucosepTM - 50mL purchased from Greiner Bio-One (catalog reference: 227290). Blood was centrifuged using MF48-R Centrifuge from AWEL Industries (catalog reference: 20023001). PBMC were collected in Centrifuge tube 50mL TPP from Dutscher (catalog reference: 91050), washed with PBS 1X, resuspended in CryoStor® CS10 purchased from STEMCELLTM technologies (catalog reference: 5100-0001) and transferred in CryotubeTM vials from ThermoFisher Scientific (catalog reference: 377267). Samples were finally conserved for 24h at -80°C in a cryo-freezing container Mr.FrostyTM from Thermo Fisher Scientific before storage in liquid nitrogen. Crosspresentation assay or peripheral blood lymphocyte stimulation with autologous monocyte derived- dendritic cells (DC).Frozen PBMCs were thawed, washed and resuspended in RPMI Medium 1640 (1X) purchased from GIBCO (catalog reference: 31870-025). Counting and viability were evaluated using Vi-CELLTM XR Cell Viability Analyzer from Beckman Coulter (catalog reference: AV13289).To separate adherent and non-adherent cell populations, PBMC were transferred in 6 or 24 well flat bottom Sterile tissue culture testplate TPP purchased from Dutscher (catalog reference: 92006 / 92024) and cultured in complex medium (Complex Medium 1) containing human AB serum (catalog reference: 201021334), purchased from Institut de Biotechnologies Jacques Boy France), RPMI Medium 16(1X) (catalog reference: 31870-025), Sodium Pyruvate (catalog reference: 11360-039), Penicillin /Streptomycin (catalog reference: 15140-122), L-Glutamine (200mM) (catalog reference: 25030-024) HEPES Buffer Solution (catalog reference: 15630-056), MEM NEAA (catalog reference: 1140-035), purchased from GIBCO/ThermoFisher Scientific. The Non-adherent fraction was cultured in another complex medium (Complex Medium 2) containing human AB serum, Iscove’s Modified Dulbecco’s Medium (catalog reference: I3390), from Sigma-Aldrich, Sodium Pyruvate (catalog reference: 11360-039), Penicillin/Streptomycin (catalog reference: 15140-122), L-Glutamine (200mM) (catalog reference: 25030-024) HEPES Buffer Solution (catalog reference: 15630-056), MEM NEAA (catalog reference: 1140-035) from GIBCO/ThermoFisher Scientific and Recombinant Human IL-2 (PHAR000306) from Gustave Roussy Institute pharmacy. The adherent fraction was differentiated into monocyte derived- dendritic cells (mo-DC) in a mo-DC differentiating media constituted with Complex Medium 1 supplemented with Recombinant Human GM-CSF Premium purchased from Miltenyi (catalog reference: 130-093-867) and human IFNα-2b (Introna) purchased from MSD (France) (catalog reference: PHAR008943). For activation and maturation, DCs were stimulated with LPS purchased from Invivogen (catalog reference: ) and GM-CSF purchased from Miltenyi Biotec (catalog reference: 130-093-867). PBL and mo-DC were finally co-cultured into well V bottom Sterile NuncTM plate, VWR purchased from Dutscher (catalog reference: 92097). For positive control, PBL were stimulated with DynabeadsTM Human T-Activator CD3/CD28 purchased from GIBCO / ThermoFisher Scientific (catalog reference: 11131D). All cell cultures were performed at 37°C, 5% CO 2 into Heraus® incubator purchased from Kendro Laboratory Products, ThermoFisher Scientific (catalog reference: BB 6220) And supernatants were transferred into 96 well V bottom Sterile NuncTM plate, VWR purchased from Dutscher (catalog reference: 734-0491) and frozen. Peptide-based assay.96 well V bottom Sterile NuncTM plate were coated with peptides at 2µg/mL in RPMI Medium 1640 (1X) (catalog reference: 31870-025) supplemented with 1% Penicillin/Streptomycin (catalog reference: 15140-122) and conserved at -80°C. PBMCs were then thawed and plated in plate containing peptides in RPMI Medium 16(1X) (catalog reference: 31870-025) supplemented with 1% Penicillin/Streptomycin (catalog reference: 15140-122) supplemented with Recombinant Human IL-15 Premium grade from Miltenyi biotec (catalog reference: 130-095-765) and Recombinant Human IL-2 (PHAR000306) from Gustave Roussy Hospital. For positive, PBMC were stimulated with functional grade CD3, OKT3 purchased from ThermoFisher Scientific (catalog reference: 16-0037-85). Cell cultures were then supplemented with human AB serum (catalog reference: 201021334) purchased from Institut de Biotechnologies Jacques Boy (France) and cultured at 37°C, 5% CO 2. Cytokines monitoring. Supernatants from cultured cells from Crosspresentation assay were monitored using the MACSPlex Cytokine 12 Kit human purchased from Miltenyi Biotec (catalog reference: 130-099-169). Acquisitions and analyses were performed on CytoFLEX S purchased from Beckman Coulter (catalog reference: B75442)/FACSAria Fusion purchased from BDbiosciences and FlowJo Software from Treestar respectively. Whereas Supernatants from cultured cells from peptide-based assay were monitored using ELISA tests purchased from BioLegend: ELISA MAXTM Deluxe Set Human IFN-γ (catalog reference: 430104) ELISA MAXTM Deluxe Set Human IL-17 (catalog reference: 433914) and ELISA MAXTM Deluxe Set Human IL-9 (catalog reference: 434705).
Viral studies. Biosafety levels for in vitro experiments.Frozen PBMCs from patients with a confirmed negative RT-qPCR for SARS-CoV-2 genome at the time of blood drawing were processed in a biosafety level 2 laboratory at Gustave Roussy Institute, Villejuif, France. All samples from patients with positive RT-qPCR were processed in a biosafety level 3 laboratory at Henri Mondor Hospital, Créteil, France. When a patient was sampled at different timepoints, samples were processed together in the same laboratory. RT-qPCR analysis.SARS-CoV-2 diagnostic testing of clinical nasopharyngeal swabs or other samples by RT-qPCR was conducted from 14 March to March 2020 at an outside facility using the Charité protocol. From the 23th March 20testing was performed internally at the Gustave Roussy. The cycle thresholds were collected only for assays performed at Gustave Roussy. Nasopharyngeal swab samples were collected using flocked swabs (Sigma Virocult) and placed in viral transport media. SARS-CoV-2 RNA was detected using one of two available techniques at Gustave Roussy: the GeneFinder COVID-19 Plus RealAmp kit (ELITech Group) targeting three regions (RdRp gene, nucleocapsid and envelope genes) on the ELITe InGenius (ELITech Group) or the multiplex real-time RT-PCR diagnostic kit (the Applied Biosystems TaqPath COVID-19 CE-IVD RT-PCR Kit) targeting three regions (ORF1ab, nucleocapsid and spike genes) with the following modifications. Nucleic acids were extracted from specimens using automated Maxwell instruments following the manufacturer’s instructions (Maxwell RSC simplyRNA Blood Kit; AS1380; Promega). Real-time RT-PCR was performed on the QuantiStudio 5 Dx Real-Time PCR System (Thermo Fisher Scientific) in a final reaction volume of 20 μl, including 5 μl of extracted nucleic acids according to the manufacturer instruction. Viral lysates and their production. SARS-CoV-2 IHUMI2, IHUMI845, IHUMI846, IHUMI847 (early 20episode), IHUMI2096 (20A.EU2, B.1.160) and IHUMI2514 (20C, B.1.367) [25] IHUMI3076 (20I/501Y.V1, B.1.1.7), IHUMI3147 (20H/501Y.V2, B.1.351) and IHUMI31(20J/501Y.V3, P.1) strains were isolated from human nasopharyngeal swab as previously described [25] and grown in Vero E6 cells (ATCC CRL-1586) in Minimum Essential Medium culture medium (MEM) with 4% fetal calf serum (FCS) and 1% L-glutamine. Influenza strains H1N1 (0022641132) and H3N2 (8091056304) were isolated then produced from human nasopharyngeal swab in MDCK cells (ATCC CCL-34) in MEM with 10% FCS and 1% L-glutamine. All these clinical isolates were characterized by whole viral genome sequencing from culture supernatants. Coronavirus OC43 (ATCC vr-1558) was grown in HCT8 cells (ATCC CCL-244) in RPMI with 10% FCS. Coronavirus 229E (ATCC vr-740) was grown in MRC5 cells (ATCC CCL-171) in MEM with 10% FCS. All reagents for culture were from ThermoFisher Scientific and all cultures were incubated at 37°C under 5% CO 2 without antibiotics. All viral strains were produced in 125 cm cell culture flasks. When destruction of cell monolayer reached approximately 80%, between 2 to 7 days according to cell line and viral strain, culture supernatant was harvested. After low -speed centrifugation to remove cells and debris (700 x g for 10 min.) supernatants were filtered through 0.45 then 0.22 µm pore-sized filters. These viral suspensions were then inactivated for 1 hour at 65°C before use. BaTches of scrapped control uninfected cells were rinsed twice in PBS, and then finally resuspended in 5 ml of PBS at 5.10 cells/ml. All cells and antigens were tested negative for Mycoplasma before use. In vitro stimulation assays. Crosspresentation assay or peripheral blood lymphocyte stimulation with autologous monocyte derived- dendritic cells (DC). Frozen PBMCs were thawed, washed and resuspended in RPMI 1640 media (GIBCO). Viability and count were evaluated using a Vi-Cell XR Cell Counter (Beckman Coulter, Brea). PBMC were then cultured in RPMI 1640 supplemented with 10% human AB serum, 1mM Glutamine, 1% sodium pyruvate, 1% HEPES, 1% penicillin/streptomycin at a cell density of 0.5M cells/cm for 2 hours at 37°C, 5% CO 2 and separated into adherent and non-adherent cell populations. Non-adherent cells, containing Peripheral Blood Lymphocytes (PBL), were collected and cultured 4 days at 37°C, 5% CO 2 in IMDM medium (Sigma-Aldrich, UK), supplemented with 10% human AB serum (Institut de Biotechnologies Jacques Boy, France), 1mM Glutamine (GIBCO/ThermoFisher Scientific, UK) 1% Sodium Pyruvate (GIBCO/ThermoFisher Scientific, UK), 1% HEPES (GIBCO/ThermoFisher Scientific, UK), 1% penicillin/streptomycin (GIBCO/ThermoFisher Scientific, UK) and 200 UI/mL rhIL-2 (Miltenyi, Germany). The adherent cell population was cultured for 3 days, at 37°C, 5% CO 2, in a mo-DC differentiating media containing RPMI 1640 supplemented with 10% human AB serum, 1mM Glutamine, 1% sodium pyruvate, 1% HEPES, 1% penicillin /streptomycin, 1000UI/mL rhGM-CSF (Miltenyi) and 250UI/mL human IFNα-2b (Introna, MSD France). At day 3, adherent cells were slowly detached by pipetting after 20 minutes of incubation at 4°C and 20.000 cells were seeded in 96 well round bottom plate and were pulsed, or not (control condition), overnight, at 37°C, 5% CO 2, with 1/10 heat inactivated viral lysates, or their respective control (see viral lysates production section). Spinoculation (800g for 2h, Centrifuge 5810R, Eppendorf, Germany) was next performed to ensure synchronized capture of the viral particles by mo-DCs. For activation and maturation, adherent cells were stimulated with LPS (10 ng/mL, Thermofisher) and GM-CSF (1000UI/mL). After 6h, mo-DCs were washed twice to remove LPS from the media and 100 000 PBL/well were seeded onto mature mo-DCs. PBL alone served as negative control, and PBL stimulated with anti-CD3 and anti-CD28 microbeads (1μL/mL, Dynabeads T-Activator, InVitrogen) as a positive control. moDC-PBL co-culture was incubated at 37°C, 5% CO 2 for 48h and supernatants were harvested and stored at -20°C. Multiplex Cytokine Analysis or bead-based multiplex assays.moDC-PBL co-culture supernatants were analyzed using bead-based multiplex kit assays (MACSplex cytokine human, Miltenyi) according to the manufacturer protocol. Briefly, 50uL of supernatant were used with a MACSPLEX Cytokine12 Capture Beads (Miltenyi, France) to measure the concentration of 12 cytokines (GM-CSF, IFN-α, IFN-γ, IL-10, IL-12, IL-17A, IL-2, IL-4, IL-5, IL-6, IL-9, TNF-a). Bead fluorescence was acquired on a CytoFLEX flow cytometer (Beckman Coulter) for samples processed at Gustave Roussy Institute and on a FACSAria Fusion (Becton Dickinson) for samples processed in the biosafety level 3 laboratory at Henri Mondor Hospital. FlowJo (Treestar, Ashland, OR, USA) software was used for analysis. Positivity threshold determination for cytokine concentration using multiplex assays and commercial ELISA assays. For multiplex assays (or ELISA), a 4 parameter logistic regression was fitted for each cytokine based on the APC mean fluorescent intensity (or Optical Density) of standard dilution samples using nlpr(v0.1-7). This model was then used to calculate the concentration of each sample of unknown concentration. For multiplex assays, a ratio was computed for each cytokine using the cytokine concentration measured in response to each virus (SARS-CoV-2, HCoV-229E, HCoV-OC43) divided by the median concentration of their respective biological controls (Vero 81, MRC5, HCT8). A positivity threshold was set up based on the ratio for each cytokine. A ratio of above 1.5 minimum was requested to consider the supernatant "positive" for a cytokine. When necessary, a higher threshold was set up as such, median cytokine concentration of the biological controls + 2 times the standard deviation of the biological control concentrations divided by the median concentration. For ELISA assays, a ratio was computed as the concentration of the sample divided by the mean concentration of the negative controls. ELISpot assay. The enumeration of antigen-specific IFNγ and IL-5 producing T cells was performed using the ImmunoSpot human IFNγ/IL-5 double-color enzymatic ELISPOT kit (Cellular Technology Limited (CTL), Germany). Peripheral blood lymphocytes were stimulated with autologous monocyte derived- dendritic cells loaded with SARS-CoV-2 lysates or their respective controls (see cross presentation assay section). After 48 hours, cells were resuspended in serum-free testing medium (CTL, Germany) containing 1 mM GlutaMAX (Gibco) and 1% penicillin/streptomycin (GIBCO) at a final volume 200 µL/well and seeded in a 96-well nitrocellulose plate coated with human IFNγ and IL-5 capture antibody. Plates were incubated for 18h at 37 °C in 5% CO2. ELISPOT assays were then performed according to manufacturer’s instructions. Spots were counted by CTL ImmunoSpot Analyzer using ImmunoSpot software.
Flow cytometric analyses. Sample preparation. Cells from the crosspresentation assays (PBL+DC loaded with viral lysates or VeroE6 supernatants) were stained for viability with Zombie Aqua (BioLegend Cat#423102) for 20 min at +4°C, then washed in staining buffer (PBS 1X, BSA 2%, 2mM EDTA). Then, cells were stained with a panel of antibodies (as indicated in table for supplementary methods below) for 20 min at room temperature in staining buffer with Brillant Strain Buffer (BD, Cat#563794). Cells were then washed, fixed and permeabilized (Foxp3/Transcription Factor Staining Buffer Set eBiosciences Cat#00-55-23-00) for 40 min at +4°C before being stained with intracellular antibodies for 30 min at +4°C. Data Acquisition. Samples were acquired on a BD LSRFortessaTM X-20 Flow Cytometer. Data analysis. Analysis was performed with FlowJo software (Tree Star). Table for supplementary methods: Channel Target Clone Reference Company BUV496 CD8 RPA-T8 612942 BD BUV737 CCR7/CD197 2-L1-A 749676 BD BUV805 CD4 SK3 612887 BD BUV396 CD3 UCHT1 563546 BD PE-Cy7 CCR4/CD194 1G1 557864 BD FITC CXCR3/CD183 G025H7 353704 BioLegend APC-R700 CCR6/CD196 11A9 565173 BD PE-CF594 4-1BB/CD137 4B4-1 309826 BioLegend BV605 CD25 2A3 562660 BD BV650 OX40/CD134 ACT35 563658 BD BV786 CD45RA HI100 563870 BD BV711 CD69 FN50 310944 BioLegend BV510 CD14 M0P9 563079 BD BV510 CD19 SJ25C1 562947 BD BV421 Ki67 B56 562899 BD BB700 GATA3 L50-823 566642 BD PE T-bet eBio4B10 12-5825-82 eBiosciences Whole-transcriptome RNA-sequencing . PBL from eleven resistant and 7 susceptible patients as well as 8 and 10 patients for whom crosspresentation assays revealed an IL-2/IL-5 ratio > and <1 respectively were used for the RNA sequencing of PBLs at 48 hrs after incubation with DC loaded with viral lysates. Cells from 18 wells post-stimulation with SARS-CoV-2 or VEROE6 were analyzed. The RNA integrity (RNA Integrity Score ≥7.0) was checked on the Agilent 2100 Bioanalyzer (Agilent) and quantity was determined using Qubit (Invitrogen). SureSelect Automated Strand Specific RNA Library Preparation Kit was used according to manufacturer's instructions with the Bravo Platform. Briefly, to 100 ng of total RNA sample was used for poly-A mRNA selection using oligo(dT) beads and subjected to thermal mRNA fragmentation. The fragmented mRNA samples were subjected to cDNA synthesis and were further converted into double stranded DNA using the reagents supplied in the kit, and the resulting dsDNA was used for library preparation. The final libraries were bar-coded, purified, pooled together in equal concentrations and subjected to paired-end sequencing (2 x 100 bp) on Novaseq-60sequencer (Illumina) at Gustave Roussy. Peptide-based assays. Rationale of peptide selection and peptide synthesis (Refers to Table 9).Peptide selection and synthesis: the peptides from the spike and nucleocapsid proteins were selected by dividing the sequences of the SARS-CoV-2 spike protein (RefSeq ID QHD43416.1) and of the nucleocapsin protein (RefSeq ID QHD43423.2) in non-overlapping 15 amino acid segments. The peptides from the membrane protein were selected by dividing the sequence of 2 potential immunogenic regions of the SARS-CoV-(RefSeq QHD43422.1) membrane protein in overlapping 15 amino acid segments. The peptides from the ORF8 and ORF10 proteins were selected by dividing the sequences of the SARS-CoV-2 ORF8 protein (RefSeq ID QHD43422.1) and of the ORF10 protein (RefSeq ID QHI42199.1) in overlapping 15 amino acid segments. The peptides from ORF3 and some for ORF8 were selected based on a previous study. The SARS-CoV-1peptides were peptides found to be immunogenic in previous reported studies [11,54,80,81,82,83,84]. The peptides were synthesized by peptides&elephants GmbH (Berlin, Germany). The peptide pools for the controls for Influenza, EBV and CMV were acquired from peptides&elephants GmbH (Berlin, Germany) order numbers LB01774, LB01361 and LB01232 respectively. 186-Single peptide in 96 well plates.Lyophilized peptides were dissolved in sterile water and used at 2µg/mL in RPMI 1640 glutamax media (GIBCO) supplemented with 1% penicillin/streptomycin (GIBCO). 185 single peptides were plated in duplicates in well round bottom TPP treated culture plates. Peptide plates were then stored at -80°C until use. The day of the experiment, peptide plates were thawed at room temperature. Frozen PBMCs were thawed, washed and resuspended in RPMI 1640 media (GIBCO). Viability and count were evaluated using a Vi-Cell XR Cell Counter (Beckman Coulter, Brea). PBMCs were then plated in RPMI 1640 glutamax media (GIBCO) supplemented with 1% penicillin/streptomycin (GIBCO), with 200UI/mL rhIL-2 (Miltenyi) and 200UI/mL rhIL-15 (Miltenyi) at a cell density of 10x10 cells and incubated with each peptide at 37°C, 5% CO 2. PBMCs were stimulated with 60 ng/mL OKT-3 antibody (ThermoFisher Scientific, clone OKT3) or with 10µg/mL phytohemagglutinin as positive controls and PBMCs alone served as negative controls. After 6 hours, 20µL of human AB serum was added to each well and plates were incubated at 37°C, 5% CO 2 for 6 additional days. On day 7, supernatants were harvested and frozen at -80°C. Concentration of IFNγ, IL-9, IL-5 and IL-17A in the culture supernatant was determined using a commercial ELISA kit (ELISA Max Deluxe set human IFN-γ, Biolegend). Peptide pools and COVID IGRA Biomérieux assay utilized for the COVID-SER clinical trial vaccinees[43] .Fresh blood collected in heparanized tubes was stimulated for 22 hours at 37°C under 5% of CO2 with peptide pools targeting RBD (46 peptides) (bioMérieux,France) diluted in IFA solution (bioMérieux, France). The IFA solution was used as a negative control and a mitogen was used as a positive control. The peptides (15-mer) encompassed the whole RBD protein sequence and overlapped by 5-residues. The concentration of IFNγ in the supernatant was measured using the VIDAS automated platform (VIDAS® IFNγ RUO, bioMérieux). The positivity range was 0.08 -8 IU/mL and IFA positivity thresholds were defined at 0.08 IU/mL. The IFNγ response was defined as positive when the IFNγ concentration of the test was above threshold and the negative control was below threshold or when the IFNγ concentration of the test minus IFNγ concentration of the negative control was above threshold. All positive controls were ≥IU/mL. Peptide pools and high throughput screening T cell assay with COVID IGRA Biomérieux assay utilized for the COV3AP-HP clinical trial vaccinees[43] .Same process but using different peptides pools that are detailed in Figure 5C of Fahrner et al., 2022 and Table 12. Generating TH2 cell lines.Generating SARS-CoV-2 lysates specific clones. 10 million peripheral blood lymphocytes from a healthy donor with history of SARS-CoV-2-specific IL-5 release (refer to Figure 1D) were stimulated with autologous monocyte derived- dendritic cells loaded with SARS-CoV-2 lysates (see cross presentation assay section). After 18 hours, cells were harvested and CD137+ cells were isolated using CD137 MicroBead Kit, human (Miltenyi, France) according to manufacturer’s instructions. Limiting dilution of CD137+ cells was performed by seeding 100µL of CD137 positive cellular suspension at a cells/mL concentration in 96 round botom well plates in sterile conditions. Feeder cells were generated by isolating CD14 positive cells using CD14 MicroBead Kit, human (Miltenyi,France). Isolated feeder cells were co-cultured with CD137 positive cells at a 1000:1 ratio and cultivated in IMDM medium (Sigma-Aldrich, UK), supplemented with 10% human AB serum (Institut de Biotechnologies Jacques Boy, France), 1mM Glutamine (GIBCO/ThermoFisher Scientific, UK), 1% Sodium Pyruvate (GIBCO/ThermoFisher Scientific, UK), 1% HEPES (GIBCO/ThermoFisher Scientific, UK), 1% penicillin/streptomycin (GIBCO/ThermoFisher Scientific, UK), supplemented with 100UI/mL IL-7 (Miltenyi,France) and 100UI/mL IL-15 (Miltenyi,France). Medium was changed every 2-3 days. Clones were screened for IFN-γ and IL-5 secretion by quantification of the accumulation of these cytokines in supernatants between day 7 and day 13 using commercial ELISA kits. 93 clones of interest were identified and screened for specificity against SARS-CoV-2 lysates by quantifying IFN-γ and IL-5 secretion after restimulation with autologous monocyte- derived dendritic cells loaded with SARS-CoV-lysate or its respective control at day 21. Three rounds of IVS were performed over weeks. Clones were starved in a cytokine free media two days before restimulation. Six SARS-CoV-2 specific cell lines could be identified and their MHC-I/MHC-class II recognition dependency was assessed by monitoring IFN-γ and IL-5 production after stimulation with autologous monocyte derived- dendritic cells loaded with SARS-CoV-lysate or its respective control in the presence or absence of neutralizing anti-HLA-ABC and HLA-DR, DP, DQ antibodies (W6/32 & Tü39) at day 28. Flow cytometric determination of CD4, CD8, T-bet, GATA3 was performed on the IL-5 producing SARS-CoV-2 specific cell lines according to methods already reported [32]. Generating Spike 25- specific cell lines. PBMC from an healthy donor with previous history of breakthrough COVID-19 infection after complete vaccination were stimulated using 186 peptides spaning the ORFeome of SARS-CoV-2 (Figure 3A). IFNγ and IL-5 were monitored in supernatants after 7 days of culture using commercial ELISA kits to identify IL-5 -restricted reactivity. One Spike -specific IL-5 producing (but IFNγ negative) T cell line was identified and further expanded using monocyte derived -dendritic cells (DC) pulsed with Spike 25 for one week (at a concentration of 1 µg/mL in RPMI supplemented with 10% human AB serum (Institut de Biotechnologies Jacques Boy, France), 1mM Glutamine (GIBCO/ThermoFisher Scientific, UK), 1% Sodium Pyruvate (GIBCO/ThermoFisher Scientific, UK), 1% penicillin/streptomycin (GIBCO/ThermoFisher Scientific, UK), IL-2 200UI/mL (Miltenyi) and IL-15 (Miltenyi). After the 3rd week, the T cell line was restimulated with Spike 25 -loaded DC in the presence or absence of neutralizing anti-HLA-ABC and HLA-DR, DP, DQ antibodies (W6/32; Tü39) in duplicate wells to monitor cytokine release using the 12 plex assay and stained with CD3, CD4, CD8, GATA3, T-bet, -specific antibodies to assess phenotypical characteristic by flow cytometry (refer to flow cytometric analyses).
Statistical analyses. All calculations, statistical tests, and data visualization were performed using R v4.0.3. All analyses were performed on independent samples, excepting when the presence of replicates is mentioned. The associations between continuous variables were evaluated using Spearman correlation. Group comparisons were performed using non-parametric test with the wilcox.test R function: the Wilcoxon- Mann-Whitney test for independent samples, and the Wilcoxon signed rank test for paired samples. When the number of replicates was unbalanced between the individuals, the Wilcoxon signed rank test for paired comparisons of clustered data was performed with the clusWilcox.test function of the R package clusrank. The comparison of categorical data was performed using the Fisher exact test with the fisher.test R function. Hierarchical clustering was performed with the package hclust, using the Euclidean distance. Linear and logistic regressions were performed with respectively the lm and the glm R base functions. A peptide set enrichment analysis was performed with the R package fgsea (version 1.14.0), using as statistic the t-value of the coefficient of univariable linear regressions of the logarithm-normalized IL-2 secretion on the different peptides. All hypothesis tests (including those of regression coefficients) were two-sided and considered as statistically significant when p<0.05. Graphical illustrations were drawn using the standard R packages dedicated to the data visualization (ggplot2, ggpubr, corrplot, complexheatmap, circlize, and Hmisc). RNA-seq data analysis. Quality control were made on raw FastQ files with FastQC (v0.11.9) [85]. Quality reports were gathered with MultiQC (v1.9) [86]. Abundance estimation was performed with Salmon (v0.9.0) [87] using GENCODE (GRCh38, v34) annotation [88]. Quantification results were aggregated with tximport (v1.14.0), and differential gene analysis was performed with DESeq2 (v1.30.0), according to the Soneson et al. [89] procedure. The whole pipeline was powered by both Snakemake [90] and SnakemakeWrappers. Gene set enrichment analysis on DESeq2 results was performed with GSEA software (v4.1.0, pre-ranked based on Wald test statistic, 1000 permutations, weighted enrichment statistic) and immunologic signature gene sets coming from MSigDB (C7, v7.4) [91]. Multivariate analyses of peptide pool -specific T cell responses according to co-variates (Figure 4, Subtables S13a and S13b of Fahrner et al., 2022). We pooled the log10 normalized IFNγ secretion measurements obtained with the three peptide pools to model simultaneously their dynamics from the first shot of vaccine using linear mixed effect regression adjusted for the patient age, sex, cancer status (yes/no), COVID history, and vaccine schedule. To identify the differences between the dynamics of each panel, we adjusted the model for the peptide pool (representing baseline differences), and added interaction terms between the peptide pool and each covariable (including the time since the first vaccine). The intra-patient and intra-panel correlation were considered by adding patient-peptide random effect for the intercept. A statistically significant interaction indicates that the covariable has an impact on the peptide-specific IFNγ measurement that is statistically different from its impact on the reference peptide pool (Subtables S13a and S13b of Fahrner et al., 2022). 5 Table 1. Overview of all subgroups and cohorts.
COHORTS CROSS- Presentation* PEPTIDES NAME Cancer Covid Vaccinees Elisa ELISPOT° 7 day-long IVS (Single peptide)** 22hr ex vivo (Pool)*** Yes No Yes No Yes No ONCOVID x x x x x x x x PROTECT-CoV x x x x HCW-HCL x x x x x x x x CoV3APHP x x x x x x x x Re-infected (2nd covid) x x x x x Breakthrough infection x x x x x Dupilumab x x * Refer to Figure 1B ** Refer to Figure 3A *** Refer to Figure 5C of Fahrner et al., 2022 ° Refer to Figure 6C 33 Table 2. Characteristics of cancer patients and healthy individuals (ONCOVID and others) Controls (n=320) Acute COVID-19 (n=40) P.value* Convalescent COVID-19 (n=69) P.value # n % n % n % Years2000 - Nov. 2002 7 2 - - < 0.- - < 0.Nov. 2002 - 2018 61 19 - - - - Unknown 2 1 - - - - 2020 - 2021 250 78 40 100 1 Age (years)Median 61 63 0.56 0.[Range] [18-89] [20-90] [21-85] GenderMale 124 45 22 0.410.05 Female 150 55 18 45 Unknown 46 - - - - - MalignancyYes 257 80 40 1< 0.< 0.No 63 20 0 0 42 Refers to available samples described in table S* : statistical analyses between controls and aAcute COVID-19; # : statistical analyses between controls and convalescent 34 Table 3. Clinical characteristics of vaccinated cancer patients. Vaccinated cancer patients (n=92) Age (years)Median [Range] [20-86] n % Gender Male 34 Female 57 Unknown 1 Type of cancerSolid tumors 73 Hematologic tumors Unknown 1 Cancer spreadLocalized 10 Locally advanced Metastatic 62 Unknown 2 Patients under cancer treatment before sampling (windows of 2 months) All 87 Unknown 1 Cancer treatment Chemotherapy 45 Immunotherapy Radiotherapy 5 Others 28 Unknown 1 Table 4. Characteristics of family members during the 2020 lockdown (PROTECT- CoV). Total Contact (n=22) Convalescent (n=29) P.value Age (years)Median 46 39 0.[Range] [17-75] [17-75] [20-62] n % n % n % Gender Male 26 51 13 59 13 0.Female 25 49 9 41 16 Number of contacts per case within the family 1-3 5 23 1 < 0.4-6 14 64 15 7-9 1 5 8 10-12 2 9 0 > 12 0 0 5 Number of SARS-CoV-2 positive individuals in the family 4 18 0 < 0.1-3 18 82 18 4-6 0 0 5 7-15 0 0 6 Household size 2 9 0 < 0.1-2 0 0 5 3-5 18 82 16 6-8 2 9 8 Household living space (m ) < 70 7 32 6 0.16 70-100 3 14 11 > 100 12 55 12 Number of rooms in the household 2-3 10 45 7 0.22 4-5 6 27 14 6-8 6 27 8 Number of individuals using personal protective equipment 13 59 18 62 Number of individuals respecting barriers gestures 16 73 22 76 1 Table 5. Characteristics of contact (resistant) and infected (susceptible) cancer patients and corresponding swimmer plot. Resistant (n=54) Susceptible (n=22) P.value Age (years)Median 54 0.[Range] [19-81] [22-80] n % n % Gender Male 17 31 11 0.Female 37 69 11 MalignancyYes 54 100 22 11.No 0 0 0 Type of cancerSolid tumors 52 96 19 0.Hematologic tumors 2 4 3 Cancer spreadLocalized 25 46 4 0.07 Locally advanced 8 15 5 Metastatic 21 39 13 Table 6. Characteristics of contact (resistant) and infected (susceptible) cancer patients and corresponding swimmer plot. Resistant (n=9) Susceptible (n=9) P.value Age (years)Median 50 0.4[Range] [28-71] [28-82] n % n % Gender Male 4 44 2 1.0Female 5 56 7 MalignancyYes 5 56 3 1.0No 4 44 6 Type of cancerSolid tumors 5 100 3 11.0Hematologic tumors 0 0 0 Cancer spreadLocalized 1 20 1 1.000 Locally advanced 0 0 1 Metastatic 4 80 1 Results 1.1. Effector and memory T cell responses against coronaviruses during COVID-19 infectionWe conducted a cross-sectional analysis of the functional T cell responses across several cohorts of healthy individuals and cancer patients enrolled during the first surge of the pandemic (Figure 1A, Figure 2A) with the final aim of determining T cell correlates with clinical protection against COVID-19 diagnosed until March 2021 (Tables 1-6) [27]. First, we focused on the quality of SARS-CoV-2-specific T cell responses detected in 215 cancer patients who stayed COVID-19-free between mid-March and September 2020, that we compared to 24 and 28 cancer patients in the acute and convalescence phase of SARS-COV-2 infection respectively (Tables 2&3, Figure 1A). In parallel, we analyzed 22 COVID-19-free healthy volunteers (HV) from distinct families at the same time as their family members who were in convalescent phase for COVID-19 (n=26) (Figure 2A, Table 4). A third cohort of 67 individuals from the pre-COVID-19 era (leukocytes frozen between 1999 and 2018) were either HV from the blood bank (n=38) or cancer patients (n=29) recruited in the context of clinical trials (Figure 1A) [28–31]. T cell responses directed against viral lysates from the reference SARS-CoV-2 strain IHUMI846 (CoV-2) isolated in early 2020 or two endemic common cold coronaviruses (CCC), OC43 and 229E, were evaluated by an in vitro stimulation assay (IVS, Figure 1B). Autologous monocyte derived-dendritic cells (DC) were differentiated for each individual and pulsed with heat-inactivated viral lysates before exposure to LPS. The specific viral lysates were compared to supernatants from cell lines permissive for viral replication (such as VeroE6 for SARS-CoV-2, Figure S1A of Fahrner et al., 2022). Peripheral blood lymphocytes (PBL) were then stimulated for 48hrs by viral lysate- loaded DC (Figure 1B). The cytokines accumulating in the supernatants were analyzed by means of a 12-plex flow cytometry-based bead assay (Figure S1A of Fahrner et al., 2022). In this crosspresentation assay, SARS-CoV-2-related cytokine release from PBL depended on MHC class I and MHC class II molecules, as shown using specific neutralizing antibodies (Figure S1B of Fahrner et al., 2022). We calculated the ratio of cytokine release by dividing interleukin concentrations following exposure to viral lysates by those obtained with the respective control supernatants, to ascribe the specificity of the reactivity to SARS-CoV-2 or to common cold coronaviruses (CCC) antigens for each subject. First, we characterized the intensity and the quality of PBL responses elicited at the acute phase of SARS-CoV-2 infection (day of symptom onset and/or first positive qPCR of the oropharyngeal swab and/or serology), between mid-March and mid-May 2020 in 24 interpretable tests performed on COVID-19+ subjects compared to a cohort of 304 controls (Tables 2&3). Robust SARS-CoV-2 specific IL-2 and IFNγ release, most likely caused by TH1/Tc1 cells, and the secretion of IL-4, IL-5 and IL-10, most likely mediated by TH2/Tc2 effector T cells, were detectable (Figure 1C, Figure 1D). Of note, COVID-19 infection did not reactivate CCC-specific T cell responses (Figure 1D, Figure S2A of Fahrner et al., 2022). We next examined the polarization of SARS-CoV-2-specific memory T cell responses between May and September 2020 in convalescent COVID-19 individuals (median time lapse between PCR negative and T cell assay: 85 days, range: 13-106 days) compared with contemporary controls (Figure 1A, Figure 1C-D, Figure S1C, S2A-B of Fahrner et al., 2022, Figure 5, Tables 2&3). A mixed SARS-CoV-2-specific memory TH1/TH2 response was observed in most convalescent subjects within the next 2-3 months after acute infection. Differences in memory T cell responses between unexposed controls and COVID-19+ individuals could not be attributed to age, gender or cancer status as they were still statistically significant for IL-2, IL-5 and TNF-α in a separate analysis matching 51 convalescent patients to 51 control patients using a propensity score adjusting for age, gender and cancer status (Figure S1C of Fahrner et al., 2022). More specifically, SARS-CoV-2 -specific IL-2 and IL-5 secretion levels were comparable in cancer and cancer-free COVID-19 patients during the recovery phase. Flow cytometric analyses of SARS-CoV-2-reactive T cells revealed central memory (TCM) TH1 (CD3+CD4+CD45RA-CCR7+T-bet+GATA3- CD69+Ki67-) and effector/effector memory (TEM) Tc1 (CD3+CD8+CD45RA-CCR7-T-bet+CD25+Ki67+) phenotypes (Figure S1D of Fahrner et al., 2022). Of note, SARS-CoV-2 specific IL-2 release at recovery correlated with an increase in the frequency of circulating non-activated TFH cells (Figure S1E of Fahrner et al., 2022) 32. In some of these patients, we performed double-color IFNγ/IL-5 ELISpot assays which were consistent which ELISA-based cytokine measurements (Figure S3B of Fahrner et al., 2022). Moreover, the frequency of IFNγ-secreting cells correlated with the percentage of CD4+T-bet+TEM, and the frequency of IL-5-secreting cells was associated with the proliferation of CD8+CCR4+T-bet- in the crosspresentation assay (Figure S3C of Fahrner et al., 2022). Finally, SARS-CoV-2 specific IL-2 secretion was the only parameter correlating with anti-SARS-CoV-2 nucleocapsid (NC) antibody titers (reported to be stable for 8 months 5) but not with IgG and IgA antibodies targeting the S1 domain of the SARS-CoV-2 spike protein including the RBD (Figure 1E-F). As previously described [21,23,24,33,34], contemporary COVID-negative subjects also harbored spontaneous (cross-reactive) SARS-CoV-2 specific- polyfunctional TH1/Tc1 memory responses that appear to pre-exist in cancer patients and healthy individuals whose blood was drawn in the pre-COVID-19 era, including prior to outbreaks of SARS-CoV-1 and MERS (Figure S2A-B of Fahrner et al., 2022 and Figure 2A). The unsupervised hierarchical clustering considering 12 cytokines monitored in 358 subjects did not segregate pre-COVID-19 from contemporary unexposed individuals nor convalescent patients (Figure S2A of Fahrner et al., 2022). Preexisting frequencies of SARS-CoV-2-specific IL-2+ and IL-5+ T cell responses were comparable (about 15%) in individuals with or without cancer, with no impact of the cancer staging (Figure 5B-C). Hence, while TH1 and TH2 cell responses were elicited during the acute phase of COVID-19, preexisting and SARS-CoV-2-induced memory responses leading to IL-2 and IL-5 release were similarly detectable in healthy subjects and cancer patients. 1.2. Clinical relevance of the IL-2/IL-5 ratio to predict COVID-19 infection We next determined the clinical significance of these memory T cell responses monitored in unexposed individuals during the first surge of COVID-19 (mid-March to mid-May 2020) to decipher the nature of memory T cells contributing to susceptibility or resistance to the successive surges of this viral pandemic in fall 20and winter 2021. We phoned 229 patients to discover that 22 individuals had developed COVID-19 infections (diagnosed by qPCR or serology) with different degrees of severity according to WHO criteria (Figure 2A, Table 5). Indeed, about one third of the initially COVID-19-free individuals became contact cases (n=70) and 29% among these contact cases were diagnosed with COVID-19 infection by specific RT-qPCR or serology (n=22, Figure 2B, Tables 5&6). The unsupervised hierarchical clustering of the T cell secretory profiles in these 70 individuals failed to correctly segregate resistant (contact) from susceptible (infected) cases (Figure 6A). In addition, the polyfunctionality of T cell responses failed to segregate the two categories of cancer patients (Figure 2C, Figure 6B). However, IL-2 and IL-5 secreted by memory T cells responding to SARS-CoV-2 correlated with resistance and susceptibility to SARS-CoV-2, respectively (Figure 2D-E). Indeed, the levels of IL-2 in the recall response and the proportions of individuals exhibiting IL-2 polarized T cell memory responses were both associated with resistance to COVID-19 (Figure 2D, p=0.01, two-sided Wilcoxon-Mann-Whitney test, Figure 2E, p=0.049, Fisher exact test). In contrast, IL-5 levels in recall responses were associated with increased susceptibility to COVID-19 (Figure 2D, p=0.057, two-sided Wilcoxon-Mann-Whitney test). Of note, the intra-individual variability of the spontaneous SARS-CoV-2 -specific recall TH1 or TH2 responses were negligible over time (Figure 6C). Next, we analyzed the clinical significance of the ratio between SARS- CoV-2-specific IL-2 and IL-5 release. Indeed, the IL-2/IL-5 recall response ratio was significantly higher in cancer patients who were SARS-CoV-2-resistant (Figure 2F) and in convalescent patients (Figure 7A). The vast majority (15 out of 19) of cancer patients doomed to be infected with SARS-CoV-2 exhibited an IL-2/IL-5 ratio ≤1, with the two severe COVID-19 cases displaying an IL-2/IL-5 ratio <10 (Figure 7B). Moreover, the transcription profile of PBL in the crosspresentation assays leading to IL-2/IL-5 ratios> versus <1 performed in 18 patients (8 with an IL-2/IL-5 ratio>1 and 10 with an IL-2/IL-5 ratio < 1) was enriched in genes expressed in TH1/Tc1 (e.g. IFNγ & GRZMB) versus TH2/Tc2 (e.g. CXCR5 & CD79A), respectively (Figure S3D of Fahrner et al., 2022). In contrast, CCC-specific T cell reactivities did not allow to discriminate susceptible from resistant individuals (Figure 2G), although IL-5 (not IL-2) stood out as the strongest correlate between SARS-CoV-2 and OC43-specific T cell responses among 156 individuals (Figure 2H). Of note, titers of IgG antibodies directed against the spike of the seasonal betacoronaviruses OC43 and HKU1 (but not the alphacoronavirus 229E and NL63) were higher in individuals susceptible to SARS-CoV-2 compared to resistant individuals (Figure 2I). The SARS-CoV-2-specific IL-2/IL-5 recall response ratio was also clinically significant in the cohort of cancer-free individuals that were locked down together with their COVID-19-positive family members (Figure 2A, Table 4, Figure 7C-D). Individuals who did not get infected harbored IL-2/IL-5 ratios>1 reaching mean values comparable to those achieved in convalescent individuals (Figure 2F, Figure 7A) at higher frequencies than the overall population (Figure 7C). We next utilized the double- color IFNγ/IL-5 ELISpot assay to enumerate cytokine-producing T cells in blood from cancer patients (n=8) and HCW (n=10) drawn in March 2020 and followed up for months for the COVID-19 diagnosis (Figure 6D, Figure 2I of Fahrner et al., 2022, Table 6). While 6 out 9 resistant subjects (who did not develop COVID-19) exhibited a SARS-CoV-2 specific 2 fold increase in IFNγ+/IL-5+ spot ratios, none of the 9 susceptible subjects (who developed asymptomatic or mild COVID-19) did so (Figure 6E). Of note, Dupilumab, a monoclonal antibody blocking IL-4Rα signaling that reduces the severity of COVID-19 in rodents and patients with allergy [35], improved the IFNγ/IL-5 balance of the SARS-CoV-2-specific response in a group of 9 patients suffering from atopic dermatitis (Table 7). Thus, injections of Dupilumab inhibited SARS- CoV-2-specific IL-5 release but stimulated SARS-CoV-2-specific IFNγ secretion (Figure 2J, K).
Table 7. Characteristics of atopic dermatitis patients treated (or not) with dupilumab during the pandemic. Allergic patients (n=9) SUBJECT # Age Gender Type of Allergy Severity of the Allergy Other atopic conditions Treatment Date of Start Date of blood sampling COVID-19 Date of COVID-19 diagnosis COVID-19 symptoms 1Female Atopic DermatitisModerate None Dupilumab 25/05/2017 22/06/2020 Control NA NA 2Male Atopic Dermatitis Moderate Food allergies, seasonal allargies Dupilumab 21/11/2017 07/07/2020 Control NA NA 3Male Atopic DermatitisSevere None Dupilumab 06/03/2019 25/06/2020 Convalescent 29/03/2020 Unk 4Male Atopic Dermatitis Moderate Food allergies Dupilumab Unk/03/2019 15/07/2020 Acute Asymptomatic, 15/07/20No 5Male Atopic Dermatitis Severe Seasonal allergies, history of asthma Dupilumab 23/03/2018 21/08/2020 Convalescent Unk/03/ 2020 Unk 6Male Atopic DermatitisSevere None Dupilumab Unk/04/2017 07/01/2021 Acute 07/01/2021 No 7Female Atopic Dermatitis Moderate Food allergies, seasonal allergies No systemic treatment NA 27/07/2020 Acute 27/07/2020 No 8Female Atopic Dermatitis Moderate Seasonal allergies No systemic treatment NA 16/11/2020 Acute 16/11/2020 Yes 9 41 Female Atopic Dermatitis Moderate Seasonal allergies No systemic treatment NA Sample 1: 21/01/2021Sample 2: 13/05/21 Acute 21/01/2021 No NA: not applicable Unk: unknown 42 Table 8. Characteristics of multi-contact and re-infected cancer-free individuals.
Re-infected (n=17) Multi-exposed cases (n=12) P.value Age (years)Median 37 0.[Range] [16-78] [28-69] n % n % GenderMale 7 41 6 0.Female 10 59 6 ComorbiditiesYes 5 31 - - - No 11 69 - - Unknown 1 - - - Type of comorbidities Asthma 3 60 - - - Obesity 2 40 - - Type diabetes 40 - - Cancer 20 - - HIV* 1 20 - - HBP** 2 40 - - Time to reinfection (mo.) < 03 2 17 - - - - 06 7 58 - - > 06 3 25 - - Unknown 5 - - - Second surge variants B.1.177 1 - - - - B.1.160 6 - - - B.1.351 1 - - - B.1.1.7 2 - - - Unknown 7 - - - Refers to eligible patients described in Table S*Human Immunodeficiency Virus **High Blood Pressure Given that 15-25% of individuals exhibit a TH2/Tc2 memory response to SARS-CoV-2 (Figure 7D), we wondered whether such individuals would be at higher risk to get reinfected by SARS-CoV-2 variants. Hence, we analyzed PBMCs in a series of individuals (n=17) who were diagnosed with COVID-19 during the first surge of the SARS-CoV-2 pandemic and then were reinfected with viral variants prevailing during the later outbreak occurring in fall 2020 or winter 2021, comparing them to HCW who, in spite of multi-exposure and multiple oropharyngeal PCR tests, remained SARS-CoV-2-negative (n=12) (Table 8, Figure 2L). Surprisingly, monocytes could be differentiated into DC only in 4 out of 17 reinfected patients. Unstimulated PBL from reinfected and re-convalescent subjects spontaneously secreted much higher levels of IL-5 than did PBL from multi-exposed cases, reaching similar ranges as those obtained after TCR crosslinking (Figure 2L, middle panel). After specific restimulation with SARS-CoV-lysates, IL-10 was markedly increased in recall responses from reinfected but not multi- exposed cases (Figure 2L, right panel), and IL-2 was undetectable (Figure 8A). In this small cohort of multi-contact individuals, the recognition pattern of the United Kingdom (UK) (IHUMI3076, B.1.1.7), South Africa (IHUMI3147, B.1.351) and Brazil (IHUMI3191, P.1)[25] strains were rather variable, some individuals losing the TH1/Tc1 or acquiring a TH2/Tc2 profile, depending on the strain (Figure S4A of Fahrner et al., 2022). We next compared the immunogenicity of the lysates derived from the original SARS-CoV-strain (IHUMI846) with that of the Danish (IHUMI2096, 20A.EU2, B.1.367, GH) and North African (IHUMI2514, 20C, B.1.160, GH) strains isolated at the end of 2020 [25]. Of note, T cells lost their capacity to produce IL-2 in response to the IHUMI2096 and IHUMI25viral variants while IL-17 release tended to increase (p=0.0857, Figure 8B). We conclude that an imbalanced TH1/Tc1 versus TH2/Tc2 polarity of SARS-CoV-2 specific-memory T cell responses determines susceptibility to infection, an IL-2/IL-5 ratio >1 indicating resistance to COVID-19. 1.3. Defects in the Th1 repertoire residing in SARS-CoV-2 RBD in susceptible individuals In hosts affected by viral infections or cancer, the breadth of T cell epitope recognition is a prerequisite for protective immunity [36–38]. We analyzed the diversity of SARS-CoV-2 T cell responses by single peptide mapping using 186 peptides with to 51 amino acids corresponding to 146 non-overlapping or poorly overlapping epitopes of the SARS-CoV-2 ORFeome (among which 25 epitopes were shared with SARS-CoV- 1), encompassing membrane, nucleocapsid, spike, ORF3a, ORF8 and ORF10 proteins, plus 41 epitopes covering the SARS-CoV-1 ORFeome of immunological relevance (among which 8 epitopes were shared with SARS-CoV-2), as well as a series of positive controls, namely epitopes from influenza virus, Epstein Barr virus (EBV) and cytomegalovirus (CMV), phytohemagglutinin (PHA), and anti-CD3ɛ (OKT3) antibody (Table 9). IFNγ responses against the 186 peptides were evaluated in 148 individuals (121 unexposed individuals, 27 convalescent COVID-19-positive patients, 18 reinfected patients). To enable the detection of low-frequency SARS-CoV-2 peptide-specific T cells, we used an in vitro 7 day-long, IL-2+IL-15 enriched IVS assay in the presence of each individual peptide (Figure 3A). We chose to monitor IFNγ, a proxy for TH1/Tc1 responses, as opposed to IL-2, in the 7 day- coculture supernatants by ELISA because recombinant human IL-2 was already added to the IVS assay to maintain T cell viability (Figure 3A). The overall recognition patterns of these peptides across various patient populations, and their individual frequencies are detailed in Figure 3B, 3C and S5 of Fahrner et al., 2022. About 10% convalescent individuals recognized more than 15% of our peptide selection within the SARS-CoV-2 ORFeome. T cell responses in unexposed patients, in particular in the pre-COVID-19 era, covered large specificities, as suggested by previous reports [9,21,24] (Figure 3B, right panel and Figure 3C of Fahrner et al., 2022). In accord with the literature [9,24], the T cell repertoire of convalescent COVID-19 patients was larger than that of unexposed individuals, mainly directed against spike, membrane, and nucleocapsid (NC) and, to a lower extent, against ORF3a, ORF8, and ORF10 (Figure 3B, 3D left panel). The breadth of the peptide recognition coverage tended to be reduced in cancer patients compared with others (Figure 3B left panel, Figure 3B of Fahrner et al., 2022). In a limited number of individuals, we measured not only IFNγ but also IL-5, IL-9 and IL-17 by ELISA. The recognition profile specific to the spike (and more specifically the RBD) as well as ORFwas more geared toward TH1/Tc1 (IFNγ) than TH2 (IL-5), TH9 (IL-9) or TH17 (IL-17) production (Figure S6A-C of Fahrner et al., 2022). The membrane- and NC-specific repertoire was strongly TH17 oriented (Figure S6B of Fahrner et al., 2022). Using logistic regression analyses, we determined the TH1/Tc1 peptide recognition fingerprint significantly associated with each patient category (Figure 9A). The hallmark repertoire of the pre-COVID-19 era consisted in a stretch of peptides covering part of the SARS-CoV-1 genome (spike, membrane, ORF3a, NC), some peptide residues sharing high or complete homology with SARS-CoV-2, as well as numerous ORF8 sequences (Table 9). Of note, the recognition pattern of these SARS-CoV-1 epitopes highly correlated with responses directed against ORF8 peptides. In contrast, the COVID-19-associated blueprint encompassed many nucleocapsid peptides (NC_1 (residues 1-15), NC_6-7 (residues 76-105, NC_8 (residues 106-120) sharing 93% and 100% homology with OC43 and HKU1, respectively, the HLA-A2- restricted nonamer (RLNQLESKV) NC_226-234 from SARS-CoV-1 (sharing high structural homology with the SARS-CoV-2 epitope RLNQLESKM) and another SARS-CoV-1 NC nonamer peptide (NC_345-361), three peptides residing in ORF8, two epitopes belonging to the RBD region ("SPIKE29") found at high frequency across subjects (23.5%), as well as a peptide from the C terminal portion of spike ("SPIKE84", residues 1246-1260) (Figure 9A). Cancer patients tended to lack some specificities, yet with no prototypical signature (Figure 9A).
Table 9. SARS-CoV-1 and CoV-2 orfeome peptide list: sequences and positions.
Peptide name Peptide sequence SEQ ID Virus Protein Similar sequence in SARS-CoV-2 SEQ ID SARS-CoV-2 1st pos SARS- CoV-2 last pos SARS- CoV-1 1st pos SARS- CoV-1 last pos Spike1MFVFLVLLPLVSSQC SARS-CoV-2 Spike 1 15 Spike2VNLTTRTQLPPAYTN SARS-CoV-2 Spike 16 30 Spike3SFTRGVYYPDKVFRS SARS-CoV-2 Spike 31 45 Spike4SVLHSTQDLFLPFFS SARS-CoV-2 Spike 46 60 Spike5NVTWFHAIHVSGTNG SARS-CoV-2 Spike 61 75 Spike6TKRFDNPVLPFNDGV SARS-CoV-2 Spike 76 90 Spike7YFASTEKSNIIRGWI SARS-CoV-2 Spike 91 105 Spike8FGTTLDSKTQSLLIV SARS-CoV-2 Spike 106 120 Spike9NNATNVVIKVCEFQF SARS-CoV-2 Spike 121 135 Spike10CNDPFLGVYYHKNNK SARS-CoV-2 Spike 136 150 Spike11SWMESEFRVYSSANN SARS-CoV-2 Spike 151 165 Spike12CTFEYVSQPFLMDLE SARS-CoV-2 Spike 166 180 Spike13GKQGNFKNLREFVFK SARS-CoV-2 Spike 181 195 Spike14NIDGYFKIYSKHTPI SARS-CoV-2 Spike 196 210 Spike15NLVRDLPQGFSALEP SARS-CoV-2 Spike 211 225 46 Spike16LVDLPIGINITRFQT SARS-CoV-2 Spike 226 240 Spike17LLALHRSYLTPGDSS SARS-CoV-2 Spike 241 255 Spike18SGWTAGAAAYYVGYL SARS-CoV-2 Spike 256 270 Spike19QPRTFLLKYNENGTI SARS-CoV-2 Spike 271 285 Spike20TDAVDCALDPLSETK SARS-CoV-2 Spike 286 300 Spike21CTLKSFTVEKGIYQT SARS-CoV-2 Spike 301 315 Spike22SNFRVQPTESIVRFP SARS-CoV-2 Spike 316 330 Spike23NITNLCPFGEVFNAT SARS-CoV-1 + SARS-CoV-Spike 331 345 318 3 Spike24RFASVYAWNRKRISN SARS-CoV-2 Spike 346 360 Spike25CVADYSVLYNSASFS SARS-CoV-2 Spike 361 375 Spike26TFKCYGVSPTKLNDL SARS-CoV-2 Spike 376 390 Spike27CFTNVYADSFVIRGD SARS-CoV-2 Spike 391 405 Spike28EVRQIAPGQTGKIAD SARS-CoV-2 Spike 406 420 Spike29YNYKLPDDFTGCVIA SARS-CoV-2 Spike 421 435 Spike30WNSNNLDSKVGGNYN SARS-CoV-2 Spike 436 450 Spike31YLYRLFRKSNLKPFE SARS-CoV-2 Spike 451 465 Spike32RDISTEIYQAGSTPC SARS-CoV-2 Spike 466 480 Spike33NGVEGFNCYFPLQSY SARS-CoV-2 Spike 481 495 47 Spike34GFQPTNGVGYQPYRV SARS-CoV-2 Spike 496 510 Spike35VVLSFELLHAPATVC SARS-CoV-2 Spike 511 525 Spike36GPKKSTNLVKNKCVN SARS-CoV-2 Spike 526 540 Spike37FNFNGLTGTGVLTES SARS-CoV-2 Spike 541 555 Spike38NKKFLPFQQFGRDIA SARS-CoV-2 Spike 556 570 Spike39DTTDAVRDPQTLEIL SARS-CoV-2 Spike 571 585 Spike40DITPCSFGGVSVITP SARS-CoV-2 Spike 586 600 Spike41GTNTSNQVAVLYQDV SARS-CoV-2 Spike 601 615 Spike42NCTEVPVAIHADQLT SARS-CoV-2 Spike 616 630 Spike43PTWRVYSTGSNVFQT SARS-CoV-2 Spike 631 645 Spike44RAGCLIGAEHVNNSY SARS-CoV-2 Spike 646 660 Spike45ECDIPIGAGICASYQ SARS-CoV-2 Spike 661 675 Spike46TQTNSPRRARSVASQ SARS-CoV-2 Spike 676 690 Spike47SIIAYTMSLGAENSV SARS-CoV-2 Spike 691 705 Spike48AYSNNSIAIPTNFTI SARS-CoV-2 Spike 706 720 Spike49SVTTEILPVSMTKTS SARS-CoV-2 Spike 721 735 Spike50VDCTMYICGDSTECS SARS-CoV-2 Spike 736 750 Spike51NLLLQYGSFCTQLNR SARS-CoV-1 + SARS-CoV-Spike 751 765 733 7 48 Spike52ALTGIAVEQDKNTQE SARS-CoV-2 Spike 766 780 Spike53VFAQVKQIYKTPPIK SARS-CoV-2 Spike 781 795 Spike54DFGGFNFSQILPDPS SARS-CoV-2 Spike 796 810 Spike55KPSKRSFIEDLLFNK SARS-CoV-2 Spike 811 825 Spike56VTLADAGFIKQYGDC SARS-CoV-2 Spike 826 840 Spike57LGDIAARDLICAQKF SARS-CoV-2 Spike 841 855 Spike58NGLTVLPPLLTDEMI SARS-CoV-2 Spike 856 870 Spike59AQYTSALLAGTITSG SARS-CoV-2 Spike 871 885 Spike60WTFGAGAALQIPFAM SARS-CoV-1 + SARS-CoV-Spike 886 900 868 8 Spike61QMAYRFNGIGVTQNV SARS-CoV-1 + SARS-CoV-Spike 901 915 883 8 Spike62LYENQKLIANQFNSA SARS-CoV-2 Spike 916 930 Spike63IGKIQDSLSSTASAL SARS-CoV-2 Spike 931 945 Spike64GKLQDVVNQNAQALN SARS-CoV-1 + SARS-CoV-Spike 946 960 928 9 Spike65TLVKQLSSNFGAISS SARS-CoV-1 + SARS-CoV-Spike 961 975 943 9 Spike66VLNDILSRLDKVEAE SARS-CoV-1 + SARS-CoV-Spike 976 990 958 9 Spike67VQIDRLITGRLQSLQ SARS-CoV-1 + SARS-CoV-Spike 991 1005 973 9 Spike68TYVTQQLIRAAEIRA SARS-CoV-1 + SARS-CoV-Spike 1006 1020 988 10 Spike69SANLAATKMSECVLG SARS-CoV-1 + SARS-CoV-Spike 1021 1035 1003 10 49 Spike70QSKRVDFCGKGYHLM SARS-CoV-1 + SARS-CoV-Spike 1036 1050 1018 10 Spike71SFPQSAPHGVVFLHV SARS-CoV-2 Spike 1051 1065 Spike72TYVPAQEKNFTTAPA SARS-CoV-2 Spike 1066 1080 Spike73ICHDGKAHFPREGVF SARS-CoV-2 Spike 1081 1095 Spike74VSNGTHWFVTQRNFY SARS-CoV-2 Spike 1096 1110 Spike75EPQIITTDNTFVSGN SARS-CoV-2 Spike 1111 1125 Spike76CDVVIGIVNNTVYDP SARS-CoV-2 Spike 1126 1140 Spike77LQPELDSFKEELDKY SARS-CoV-1 + SARS-CoV-Spike 1141 1155 1123 11 Spike78FKNHTSPDVDLGDIS SARS-CoV-1 + SARS-CoV-Spike 1156 1170 1111 Spike79GINASVVNIQKEIDR SARS-CoV-1 + SARS-CoV-Spike 1171 1185 1153 11 Spike80LNEVAKNLNESLIDL SARS-CoV-1 + SARS-CoV-Spike 1186 1200 1168 11 Spike81QELGKYEQYIKWPWY SARS-CoV-1 + SARS-CoV-Spike 1201 1215 1183 11 Spike82IWLGFIAGLIAIVMV SARS-CoV-2 Spike 1216 1230 Spike83TIMLCCMTSCCSCLK SARS-CoV-2 Spike 1231 1245 Spike84GCCSCGSCCKFDEDD SARS-CoV-2 Spike 1246 1260 Spike85SEPVLKGVKLHYT SARS-CoV-1 + SARS-CoV-Spike 1261 1273 1243 12 Nucleocapsid_1MSDNGPQNQRNAPRI SARS-CoV-2 Nucleocapsid 1 15 Nucleocapsid_2TFGGPSDSTGSNQNG SARS-CoV-2 Nucleocapsid 16 30 50 Nucleocapsid_3ERSGARSKQRRPQGL SARS-CoV-2 Nucleocapsid 31 45 Nucleocapsid_4PNNTASWFTALTQHG SARS-CoV-1 + SARS-CoV-Nucleocapsid 46 60 47 Nucleocapsid_5KEDLKFPRGQGVPIN SARS-CoV-2 Nucleocapsid 61 75 Nucleocapsid_6TNSSPDDQIGYYRRA SARS-CoV-2 Nucleocapsid 76 90 Nucleocapsid_7TRRIRGGDGKMKDLS SARS-CoV-2 Nucleocapsid 91 105 Nucleocapsid_8PRWYFYYLGTGPEAG SARS-CoV-2 Nucleocapsid 106 120 Nucleocapsid_9LPYGANKDGIIWVAT SARS-CoV-2 Nucleocapsid 121 135 Nucleocapsid_10EGALNTPKDHIGTRN SARS-CoV-1 + SARS-CoV-Nucleocapsid 136 150 137 1 Nucleocapsid_11PANNAAIVLQLPQGT SARS-CoV-2 Nucleocapsid 151 165 Nucleocapsid_12TLPKGFYAEGSRGGS SARS-CoV-1 + SARS-CoV-Nucleocapsid 166 180 167 1 Nucleocapsid_13QASSRSSSRSRNSSR SARS-CoV-2 Nucleocapsid 181 195 Nucleocapsid_14NSTPGSSRGTSPARM SARS-CoV-2 Nucleocapsid 196 210 Nucleocapsid_15AGNGGDAALALLLLD 100 SARS-CoV-2 Nucleocapsid 211 225 Nucleocapsid_16RLNQLESKMSGKGQQ 101 SARS-CoV-2 Nucleocapsid 226 240 Nucleocapsid_17QQGQTVTKKSAAEAS 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 241 255 242 2 Nucleocapsid_18KKPRQKRTATKAYNV 103 SARS-CoV-2 Nucleocapsid 256 270 Nucleocapsid_19TQAFGRRGPEQTQGN 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 271 285 272 2 Nucleocapsid_20FGDQELIRQGTDYKH 105 SARS-CoV-2 Nucleocapsid 286 300 51 Nucleocapsid_21WPQIAQFAPSASAFF 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 301 315 302 3 Nucleocapsid_22GMSRIGMEVTPSGTW 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 316 330 317 3 Nucleocapsid_23LTYTGAIKLDDKDPN 108 SARS-CoV-2 Nucleocapsid 331 345 Nucleocapsid_24FKDQVILLNKHIDAY 109 SARS-CoV-2 Nucleocapsid 346 360 Nucleocapsid_25KTFPPTEPKKDKKKK 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 361 375 362 3 Nucleocapsid_26ADETQALPQRQKKQQ 111 SARS-CoV-2 Nucleocapsid 376 390 Nucleocapsid_27TVTLLPAADLDDFSK 112 SARS-CoV-2 Nucleocapsid 391 405 Nucleocapsid_28QLQQSMSSADSTQA 113 SARS-CoV-2 Nucleocapsid 406 419 Membrane_1MADSNGTITVEELKK 114 SARS-CoV-2 Membrane 1 15 Membrane_2ITVEELKKLLEQWNL 115 SARS-CoV-2 Membrane 8 22 Membrane_3KKLLEQWNLVIGFLF 116 SARS-CoV-2 Membrane 15 29 Membrane_4EQWNLVIGFLFLTWI 117 SARS-CoV-2 Membrane 22 36 Membrane_5LLESELVIGAVILRG 118 SARS-CoV-2 Membrane 133 147 Membrane_6IGAVILRGHLRIAGH 119 SARS-CoV-2 Membrane 140 154 Membrane_7HLRIAGHHLGRCDIK 120 SARS-CoV-2 Membrane 148 162 SARS_2016.05.006LLNKHIDAYKTFP 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 352 364 353 3 SARS_10.1128_1PLQASLPFGWLVIGV 122 SARS-CoV-1 ORF3a P I QASLPFGWLIVGV 188 36 50 36 SARS_10.1128_2NYNYKYRYLRGKLRPF 123 SARS-CoV-1 Spike NYNY L YR LF R KSN L K PF 189 448 464 435 4 52 SARS_10.1128_3AGCLIGAEHVDTSYECDI 124 SARS-CoV-1 Spike AGCLIGAEHV NN SYECDI 190 647 664 633 6 SARS_10.1128_4GETALALLLLDRLNQ 125 SARS-CoV-1 Nucleocapsid G DA ALALLLLDRLNQ 191 215 229 216 2 SARS_10.1128_5GHLRMAGHSLGRCDI 126 SARS-CoV-1 Membrane GHLR I AGH H LGRCDI 192 147 161 146 1 SARS_10.1128_6NFNGLTGTGVLTPSSKRF 127 SARS-CoV-1 Spike NFNGLTGTGVLT E S N K K F 193 542 559 528 5 SARS_10.1128_7DIPIGAGICASYHTVSLL 128 SARS-CoV-1 Spike DIPIGAGICASY QTQTNS 194 663 680 649 6 SARS_10.1128_8SWFITQRNFFSPQII 129 SARS-CoV-1 Spike H WF V TQRNF YE PQII 195 1101 1115 1083 10 SARS_HLA-A*02:01_1 FIAGLIAIV 1SARS-CoV-1 + SARS-CoV-Spike 1220 1228 1202 12 SARS_HLA-A*02:01_2 LITGRLQSL 1SARS-CoV-1 + SARS-CoV-Spike 996 1004 978 9 SARS_HLA-A*02:01_3 RLNEVAKNL 1SARS-CoV-1 + SARS-CoV-Spike 1185 1193 1111 SARS_HLA-A*02:01_4 ILPDPLKPT 133 SARS-CoV-1 Spike ILPDP S KP S 196 805 813 787 7 SARS_HLA-A*02:01_5 VVFLHVTYV 1SARS-CoV-1 + SARS-CoV-Spike 1060 1068 1042 10 SARS_HLA-A*02:01_6 KLPDDFMGCV 135 SARS-CoV-1 Spike KLPDDF T GCV 197 424 433 411 4 SARS_HLA-A*02:01_7 VLNDILSRL 1SARS-CoV-1 + SARS-CoV-Spike 976 984 958 9 SARS_HLA-A*02:01_8 LLLDRLNQL 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 222 230 223 2 SARS_HLA-A*02:01_9 RLNQLESKV 138 SARS-CoV-1 Nucleocapsid RLNQLESK M 198 226 234 227 2 SARS_HLA-A*02:01_10 GMSRIGMEV 1SARS-CoV-1 + SARS-CoV-Nucleocapsid 316 324 317 3 SARS_HLA-A*02:01_11WLTYHGAIKLDDKDPQF 140 SARS-CoV-1 Nucleocapsid WLTY T GAIKLDDKDP N F 199 330 346 331 3 SARS_HLA-A*02:01_12QFKDNVILLNKHIDAYK 141 SARS-CoV-1 Nucleocapsid N FKD Q VILLNKHIDAYK 200 345 361 346 3 SARS_HLA-A*02:01_13MASGGGETALALLLLDRLNQLESKV 142 SARS-CoV-1 Nucleocapsid MAGNGG DA ALALLLLDRLNQLESK M 201 210 234 211 2 53 SARS_HLA-A*02:01_14TWLTYHGAIKLDDKDPQFKDNVILL 143 SARS-CoV-1 Nucleocapsid TWLTY T GAIKLDDKDP N FKD Q VILL 202 329 353 330 3 SARS_HLA-A*02:01_15 GETALALLLL 144 SARS-CoV-1 Nucleocapsid GD AALALLLL 203 215 224 216 2 SARS_HLA-A*02:01_16LVIGFLFLAWIMLLQFAYSNRNRF 145 SARS-CoV-1 Membrane LVIGFLFL T WI C LLQFAY A NRNRF 204 22 45 21 SARS_HLA-A*02:01_17VLAAVYRINWVTGGIAIAMACIVGLMW 146 SARS-CoV-1 Membrane VLAAVYRINWITGGIAIAMAC L VGLMW 205 66 92 65 SARS_HLA-A*02:01_18ILLNVPLRGTIVTRPLMESELVIG 147 SARS-CoV-1 Membrane ILLNVPL H GTI L TRPL L ESELVIG 206 116 141 117 1 SARS_HLA-A*02:01_19IGNYKLNTDHAGSNDNIALLV 148 SARS-CoV-1 Membrane IGNYKLNTDH SS S S DNIALLV 207 199 221 200 2 SARS_HLA-A*02:01_20GHLRMAGHPLGRCDI 149 SARS-CoV-1 Membrane GHLRIAGH H LGRCDI 192 147 161 146 1 SARS_HLA-A*02:01_21PLQASLPFGWLVIGV 150 SARS-CoV-1 ORF3a P I QASLPFGWLIVGV 188 36 50 SARS_01026-XDVNCTDVSTAIHADQLTPAWR 151 SARS-CoV-1 Spike DVNCT E V PV AIHADQLTP T WR 208 614 634 600 6 SARS_01025-8_1KDKKKKTDEAQPLPQRQKKQ 152 SARS-CoV-1 Nucleocapsid KDKKKKADE T Q A LPQRQKKQ 209 370 389 371 3 SARS_01025-8_2QRQKKQPTVTLLPAADMDDFSRQ 153 SARS-CoV-1 Nucleocapsid QRQKKQ Q TVTLLPAAD L DDFS K Q 210 384 406 385 4 SARS_HLA-DR0401_1NAFNCTFEYISDAFSLDV 154 SARS-CoV-1 Spike 155 1 SARS_HLA-DR0401_2YISDAFSLDVSEKSGNFK 155 SARS-CoV-1 Spike 163 1 SARS_HLA-DR0401_3YLRHGKLRPFERDISNVP 156 SARS-CoV-1 Spike 442 4 SARS_HLA-DR0401_4RPFERDISNVPFSPDGK 157 SARS-CoV-1 Spike 449 4 54 SARS_3726.2005_1MADNGTITVEELKQLLEQWNLVIGFLFLAWI 158 SARS-CoV-1 Membrane MAD S NGTITVEELKKLLEQWNLVIGFLFL T WI 211 1 32 1 SARS_3726.2005_2LMESELVIGAVIIRGHLRMAGHPLGRCDIK 159 SARS-CoV-1 Membrane L L ESELVIGAVI L RGHLR I AGH H LGRCDIK 212 133 162 132 1 SARS_5314.2004_1NNNAATVLQLPQGTTLPKGFYAEGSR 160 SARS-CoV-1 Nucleocapsid A NNAA I VLQLPQGTTLPKGFYAEGSR 213 152 175 153 1 SARS_5314.2004_2KTFPPTEPKKDKKKKTDEAQPLPQRQKKQPTVTLLPAADMDDFSRQLQNSM 161 SARS-CoV-1 Nucleocapsid KTFPPTEPKKDKKKK A DE T Q A LPQRQKKQQTVTLLPAAD L DDFSKQLQ Q SM 214 361 411 362 4 ORF8_1MKFLVFLGIITTVAA 162 SARS-CoV-2 ORF8 1 15 ORF8_2GIITTVAAFHQECSL 163 SARS-CoV-2 ORF8 8 22 ORF8_3AFHQECSLQSCTQHQ 164 SARS-CoV-2 ORF8 15 29 ORF8_4LQSCTQHQPYVVDDP 165 SARS-CoV-2 ORF8 22 36 ORF8_5QPYVVDDPCPIHFYS 166 SARS-CoV-2 ORF8 29 43 ORF8_6PCPIHFYSKWYIRVG 167 SARS-CoV-2 ORF8 36 50 ORF8_7SKWYIRVGARKSAPL 168 SARS-CoV-2 ORF8 43 57 ORF8_8GARKSAPLIELCVDE 169 SARS-CoV-2 ORF8 50 64 ORF8_9LIELCVDEAGSKSPI 170 SARS-CoV-2 ORF8 57 71 ORF8_10EAGSKSPIQYIDIGN 171 SARS-CoV-2 ORF8 64 78 55 ORF8_11IQYIDIGNYTVSCLP 172 SARS-CoV-2 ORF8 71 85 ORF8_12NYTVSCLPFTINCQE 173 SARS-CoV-2 ORF8 78 92 ORF8_13PFTINCQEPKLGSLV 174 SARS-CoV-2 ORF8 85 99 ORF8_14EPKLGSLVVRCSFYE 175 SARS-CoV-2 ORF8 92 106 ORF8_15VVRCSFYEDFLEYHD 176 SARS-CoV-2 ORF8 99 113 ORF8_16EDFLEYHDVRVVLDF 177 SARS-CoV-2 ORF8 106 120 ORF8_17 DVRVVLDFI 178 SARS-CoV-2 ORF8 113 121 ORF10_1MGYINVFAFPFTIYS 179 SARS-CoV-2 ORF10 1 15 ORF10_2AFPFTIYSLLLCRMN 180 SARS-CoV-2 ORF10 8 22 ORF10_3SLLLCRMNSRNYIAQ 181 SARS-CoV-2 ORF10 15 29 ORF10_4NSRNYIAQVDVVNFN 182 SARS-CoV-2 ORF10 22 36 ORF10_5 QVDVVNFNLT 183 SARS-CoV-2 ORF10 29 38 ORF8_AGNYTVSCSPFTINCQ 184 SARS-CoV-2 ORF8 77 91 ORF8_BCGNYTVSCLPFTINCQ 185 SARS-CoV-2 ORF8 77 91 ORF3a_ABVQIHTIDGSSGVVNP 186 SARS-CoV-2 ORF3a 244 258 ORF3a_CVQIHTIDVSSGVVNP 187 SARS-CoV-2 ORF3a 244 258 SARS-CoV-2 Refseq ID : QHD43416.1 (Spike); QHD43423.2 (nucleocapsid); QHD43419.1 (membrane); QHD43417.1 and QHZ00380.(Orf3a); QHD43422.1 (Orf8); QHI42199.1 (Orf10); SARS-CoV-1 Refseq ID : AAP41037.1 (Spike); AAP41047.1 (nucleocapsid); AYV99779.1 (membrane); AYV99776.1 (Orf3a); (Orf8); (Orf10) 56 Next, we investigated the ORFeome peptide repertoire associated with SARS-CoV-2-specific IL-2 (supposedly protective) memory responses in 118 unexposed individuals by means of linear regression analysis (Figure 4B of Fahrner et al., 2022, left panel). Among the 9 peptides associated with a positive contribution to IL-2 secretion, one nonamer (KLPDDFMGCV in SARS-CoV-1 genome and KLPDDFTGCV in the SARS-CoV- 2 genome) resided in the RBD region that constitutes the binding site for its cellular receptor angiotensin-converting enzyme 2 (ACE2) 39 while, conversely among the 13 peptides associated with a hole in the TH1 response, 5 resided within the RBD of the spike glycoprotein. More specifically, there was a statistically significant enrichment of RBD-related peptides within this TH1/Tc1 hole (Figure 4B of Fahrner et al., 2022, right panel). In order to validate the clinical significance of the TH1/Tc1 repertoire hole and the assumption that a defect in the TH1/Tc1 recognition pattern of the RBD sequence could be a risk factor for COVID-19, we annotated the presence of at least one positive peptide selected from the RBD region spanning aminoacid 331-525 residues (called "SPIKE23" to "SPIKE35" in Table 9), versus other regions of the Orfeome in each of the 83 individuals who were comprehensively explored in the peptide-based IVS assay, resistant (contact) individuals, 14 infected persons (susceptible) as well as 32 controls (unexposed lockdown and/or unknown) using the IFNγ ELISA (Figure 4A). The Volcano plot assigning significant odd ratios of TH1/Tc1 reactivities to different SARS-CoV1/CoVaminoacid sequences between susceptible versus resistant individuals, highlighted that anti-S1-RBD TH1/Tc1 reactivity best correlated with resistance to infection (Figure 4A). In accordance with the immunodominance of S1-RBD, the other signatures indicated by our logistic regression analysis (Figure 9A), namely the convalescent or the pre-COVID-19 era -related blueprints were not significantly associated with COVID-19 resistance (Figure 4E-F of Fahrner et al., 2022). While susceptible individuals exhibited a significant defect in the RBD-related TH1/Tc1 repertoire (Figure 4B), up to 25% of the resistant individuals harbored robust TH1/Tc1 responses to the 331-525 aminoacid residues of RBD (Figure 4B, p=0.049, Fisher exact test). Secondly, the RBD-specific TH1/Tc1 responses were almost undetectable in patients who got infected twice with SARS-CoV-2 (Table 8), while they could be measured in 50% convalescent COVID-19 patients (Figure 4C, p=0.011, Fisher exact test) in accordance with a recent report highlighting the immunodominance of the S346-365 region (corresponding to our "SPIKE24" epitope) in convalescent individuals [40]. Thirdly, patients diagnosed with COVID-19 breakthrough infections more than one month after complete vaccination (Table 10) harbored a major defect in S1-RBD-specific TH1/Tccell responses (Figure 4D). Of note, neutralizing antibody titers were above the detection limit in 66% of COVID-19 patients infected once versus 40% of reinfected patients. In contrast, in vaccinees experiencing breakthrough infection, IgG antibody titers against trimeric Spike assessed within 2 months post-2nd vaccine were comparable to levels measured in unaffected vaccinees (Figure S6D of Fahrner et al., 2022). Thus the cellular anti-S1-RBD TH1/Tc1 response might be a better predictor of protection against SARS-CoV-2 infection than the humoral response against trimeric Spike. Table 10. Characteristics of vaccinees experiencing a breakthrough infection. Breakthrough infection p value No (n=20) Yes (n=9) Age (years)Median 48 0.0[Range] [21-77] [51-88] n % n % Gender Male 4 20 6 0.0Female 16 80 3 MalignancyYes 7 35 1 0.3No 13 65 8 ObesityYes 0 0 1 11 No 0 0 8 89 - Unknown 20 0 0 0 AsthmaYes 0 0 3 33 No 0 0 6 67 - Unknown 20 0 0 0 Days from second vaccination and COVID-19 first symptoms Median NA [Range] [9-69] - Unknown 2 COVID-19 variant Alpha NA 9 100 - IFNγ and IL-5 T cell responses to S1-RBD peptides were evaluated in patients. Less than 10% individuals harbored S1-RBD-specific TH2/Tc2 responses (Table 11). Long-lived TH2 clones could be derived from two patients exhibiting robust spontaneous or breakthrough COVID19-induced SARS-CoV-2 or SPIKE25 -specific IL-5 release (Figure S7A-F of Fahrner et al., 2022). Of note, there was a robust concordance of the polarization status of patients between the two (cross-priming and peptide-based) IVS assays (p=2.2e-16 for the TH1/Tc1 cytokines IL-2 and IFNγ release; p <1e-16 for the TH2/Tc2 factor IL-5, McNemar test). 15 Table 11. Peptide-specific T cell polarisation determined by IL-5 or IFN-γ quantification.
Spontaneous immunity SARS-CoV-2 protein n* IL-5 - /IFNγ - IL-5 + /IFNγ - IL-5 - /IFNγ + IL-5 + /IFNγ + P.value MembraneResistant 3 1 0.Susceptible 10 0 0 NucleocapsidResistant 3 7 0.Susceptible 9 0 3 S1Resistant 0 9 0.Susceptible 7 0 1 S1-RBDResistant 3 10 0.Susceptible 8 0 0 S2Resistant 0 7 0.Susceptible 5 0 2 ORF8Resistant 0 5 1.Susceptible 4 0 2 ORF10Resistant 0 1 0.Susceptible 6 0 1 ORF3aResistant 0 1 1.Susceptible 7 0 0 Vaccine-induced immunity Peptide pool Vaccinated n IL-5 - /IFNγ - IL-5 + /IFNγ - IL-5 - /IFNγ + IL-5 + /IFNγ + P.value PEPorfNo 6 2 6 0.0Yes 3 0 26 PEPwtRBDNo 12 0 3 0.0Yes 30 0 38 PEPmutRBDNo 14 0 1 0.1Yes 20 1 9 *The numbers correspond to the enumeration of patients who were positive for at least one of the epitopes of each protein listed in Table 9. Given that immunoselection may drive antigenic drift of viruses as well as the evolution of viral phylogeny, we analyzed the coincidence of mutations (mutations occurring in at least 75% of emergent variant or predicted to decrease antibody neutralizing activity) in the SARS-CoV-2 ORFeome41 with T cell memory patterns of clinical significance (Table S12 of Fahrner et al., 2022). Significantly higher mutation frequencies were detected within the S1-RBD-specific TH1 response (62%) compared with other regions of the SARS-CoV-2 orfeome (25.5%) (odds ratio = 0.21, 95% confidence interval [0.06; 0.68], p=0.01, Figure 4E). 10 During the course of this study, SARS-CoV-2 mRNA and DNA vaccines were approved by FDA and EMA based on reports that they prevent COVID-19 infection with an efficacy of >90%.3,42 Using a simple 22hr-whole blood stimulation assay allowing the quantitative measurement of IFNγ using the Enzyme Linked Fluorescent Assay technique in an automated platform (VIDAS® IFNγ RUO, 43 we analyzed RBD-specific T cell reactivities before and/or after dual vaccination with BNT162b2 mRNA (BioNTech/Pfizer) and/or AZD1222 adenovirus (Astrazeneca) in 233 unexposed HCW and 92 cancer patients, as well as in 69 convalescent individuals before and/or after one vaccine. Firstly, using a pool of 42 overlapping peptides spanning the S1-RBD sequence, we observed 90% reactivity in naive (cancer-free, no COVID-19 infection) HCW (n=70) 3 weeks after the second immunization, as well as in convalescent patients (n=14) after the sole vaccination (not shown). Secondly, we reduced the S1-RBD 42 peptide pool to our collection of 11 non overlapping peptides ("PEP wtRBD") (Figure 5C of Fahrner et al., 2022, Tables 9 and 12). PBL reactivities to both of these peptide pools were MHC class I and class II dependent (Figure S8 of Fahrner et al., 2022). As a positive control of memory responses against SARS-CoV-2 [44], we used a pool of eighteen 15-mer epitopes "PEP Orf" comprising not only different stretches of overlapping S1-RBD peptides but also peptides spanning Spike Sand S2, membrane and nucleocapside sequences (Figure 5C of Fahrner et al., 2022, Table 12). At day 90 post-vaccine initiation, 75% of HCW (with no history of COVID-19 nor cancer) mounted PEP wtRBD -specific TH1/Tc1 responses while >90% responded to PEP Orf, reaching similar levels as individuals with a history of COVID-19 or one course of vaccination with an impact of gender and time of sampling (Figure 4F, upper panel, Table 13). The magnitude of PEP wtRBD -specific IFNγ release post-vaccination was maintained up to day 180 in both patient subsets (Figure 4F, lower panel). Multivariate analyses confirmed that administration of two vaccines or COVID-19 infection followed by one vaccine elicited significant TH1/Tc1 immune responses against S1-RBD independently of age, gender, cancer and time of sampling (Figure 4G). Of note, the titers of IgG S1-RBD antibodies poorly correlated with PEP wtRBD-specific T cell IFNγ secretions in 176 HCW vaccinees without a history of COVID-19 (Figure 5G of Fahrner et al., 2022, R=0.17, p=0.025).
Table 12. Epitope sequences for PEPOrf, PEPwtRBD, PEPmut RBD, PEPovRBD.
Peptide pools name Peptide sequence Seq ID No Virus Protein SARS-CoV-2 position st lastPEPorf SASFSTFKCYGVSPT 215 SARS-CoV-2 Spike 371 3PEPorf YKLPDDFTGCVIAWN 216 SARS-CoV-2 Spike 423 4PEPorf NNLDSKVGGNYNYLY 217 SARS-CoV-2 Spike 439 4PEPorf SKVGGNYNYLYRLFR 218 SARS-CoV-2 Spike 443 4PEPorf YLYRLFRKSNLKPFE 31 SARS-CoV-2 Spike 451 4PEPorf SNLKPFERDISTEIY 219 SARS-CoV-2 Spike 459 4PEPorf CTFEYVSQPFLMDLE 12 SARS-CoV-2 Spike 166 1PEPorf NIDGYFKIYSKHTPI 14 SARS-CoV-2 Spike 196 2PEPorf LMDLEGKQGNFKNLR 220 SARS-CoV-2 Spike 176 1PEPorf NFSQILPDPSKPSKR 221 SARS-CoV-2 Spike 801 8PEPorf NLLLQYGSFCTQLNR 51 SARS-CoV-2 Spike 751 7PEPorf LLWPVTLACFVLAAV 222 SARS-CoV-2 Membrane 56 PEPorf CLVGLMWLSYFIASF 223 SARS-CoV-2 Membrane 85 PEPorf RGHLRIAGHHLGRCD 224 SARS-CoV-2 Membrane 146 1PEPorf YRINWITGGIAIAMA 225 SARS-CoV-2 Membrane 71 PEPorf KEITVATSRTLSYYK 226 SARS-CoV-2 Membrane 166 1PEPorf LLESELVIGAVILRG 118 SARS-CoV-2 Membrane 133 1PEPorf PSGTWLTYTGAIKLD 227 SARS-CoV-2 Nucleocapsid 326 3PEPwtRBD CVADYSVLYNSASFS 25 SARS-CoV-2 Spike 361 3PEPwtRBD TFKCYGVSPTKLNDL 26 SARS-CoV-2 Spike 376 3PEPwtRBD CFTNVYADSFVIRGD 27 SARS-CoV-2 Spike 391 4PEPwtRBD EVRQIAPGQTGKIAD 28 SARS-CoV-2 Spike 406 4PEPwtRBD YNYKLPDDFTGCVIA 29 SARS-CoV-2 Spike 421 4PEPwtRBD WNSNNLDSKVGGYN 228 SARS-CoV-2 Spike 436 4PEPwtRBD YLYRLFRKSNLKPFE 31 SARS-CoV-2 Spike 451 4PEPwtRBD RDISTEIYQAGSTPC 32 SARS-CoV-2 Spike 466 4PEPwtRBD NGVEGFNCYFPLQSY 33 SARS-CoV-2 Spike 481 4PEPwtRBD GFQPTNGVGYQPYRV 34 SARS-CoV-2 Spike 496 5PEPwtRBD VVLSFELLHAPATVC 35 SARS-CoV-2 Spike 511 5PEPmutRBD CVADYS F LYNSASFS 229 SARS-CoV-2 Spike 361 3PEPmutRBD EVRQIAPGQTG N IAD 230 SARS-CoV-2 Spike 406 4PEPmutRBD EVRQIAPGQTG T IAD 231 SARS-CoV-2 Spike 406 4PEPmutRBD WNS K NLDSKVGGNYN 232 SARS-CoV-2 Spike 436 4PEPmutRBD WNSN K LDSKVGGNYN 233 SARS-CoV-2 Spike 436 4PEPmutRBD Y R YRLFRKSNLKPFE 234 SARS-CoV-2 Spike 451 4PEPmutRBD RDISTEIYQ V GSTPC 235 SARS-CoV-2 Spike 466 4PEPmutRBD RDISTEIYQAG N TPC 236 SARS-CoV-2 Spike 466 4PEPmutRBD RDISTEIYQAGS K PC 237 SARS-CoV-2 Spike 466 480 PEPmutRBD NG A EGFNCYFPLQSY 238 SARS-CoV-2 Spike 481 4PEPmutRBD NGV K GFNCYFPLQSY 239 SARS-CoV-2 Spike 481 4PEPmutRBD NGV Q GFNCYFPLQSY 240 SARS-CoV-2 Spike 481 4PEPmutRBD NGVEGFNCYFPL R SY 241 SARS-CoV-2 Spike 481 4PEPmutRBD GFQPT Y GVGYQPYRV 242 SARS-CoV-2 Spike 496 5PEPovRBD SASFSTFKCYGVSPT 243 SARS-CoV-2 Spike 371 3PEPovRBD YKLPDDFTGCVIAWN 244 SARS-CoV-2 Spike 423 4PEPovRBD NNLDSKVGGNYNYLY 245 SARS-CoV-2 Spike 439 4PEPovRBD SKVGGNYNYLYRLFR 246 SARS-CoV-2 Spike 443 4PEPovRBD YLYRLFRKSNLKPFE 31 SARS-CoV-2 Spike 451 4PEPovRBD SNLKPFERDISTEIY 247 SARS-CoV-2 Spike 459 4PEPovRBD LLWPVTLACFVLAAV 248 SARS-CoV-2 Membrane 56 PEPovRBD CLVGLMWLSYFIASF 249 SARS-CoV-2 Membrane 85 PEPovRBD RGHLRIAGHHLGRCD 250 SARS-CoV-2 Membrane 146 1Spike28_a2 EVRQIAPGQTG P IAD 251 SARS-CoV-2 Spike 406 4SpikeG339D NITNLCPF D EVFNAT 252 SARS-CoV-2 Spike 331 3SpikeS371L CVADYSVLYN L ASFS 253 SARS-CoV-2 Spike 361 3SpikeS373L CVADYSVLYNSA L FS 254 SARS-CoV-2 Spike 361 3SpikeS375F CVADYSVLYNSASF F 255 SARS-CoV-2 Spike 361 3SpikeT478K RDISTEIYQAGS K PC 237 SARS-CoV-2 Spike 466 4SpikeE484A NGV A GFNCYFPLQSY 256 SARS-CoV-2 Spike 481 4SpikeG496S S FQPTNGVGYQPYRV 257 SARS-CoV-2 Spike 496 5SpikeQ498R GF R PTNGVGYQPYRV 258 SARS-CoV-2 Spike 496 5SpikeY505H GFQPTNGVG H QPYRV 259 SARS-CoV-2 Spike 496 5 The percentages and magnitude of these responses were reduced in cancer patients who were mostly under therapy (Tables 2&3) as compared to 187 cancer-free individuals (adjusted p value for differences in percentages of PEP Orf positivity=0.016, adjusted p value for differences in IFNγ levels upon stimulation with PEP wtRBD=0.027, Figure 4H). The binding affinity of S1-RBD peptides to MHC class I and class II proteins was calculated using the NetMHCpan algorithm. This approach predicted strong binding to MHC class I HLA-A, -B and -C alleles for the RBD epitopes "SPIKE25" (residues 361_375), "SPIKE27" (residues 391-405), "SPIKE31" (residues 451-465). In contrast, "SPIKE33" (residues 481_495) was estimated to have a low affinity for HLA-B and no affinity for HLA-C alleles (Subtable S13a of Fahrner et al., 2022). Only "SPIKE24", "SPIKE25" and "SPIKE31 were predicted to bind with a high affinity to MHC class II HLA-DR alleles (Subtable S13b of Fahrner et al., 2022) as already reported for the immunodominant S346-365 region [40]. To investigate potential links between the lack of spontaneous or vaccine-induced S1-RBD-specific TH1 responses and HLA genotypes, we analyzed the distribution of HLA-I and HLA-II alleles in 101 individuals, 53 vaccinees and 48 cancer patients prior to vaccination, of which 45% presented anti-S1-RBD TH1 responses (Figure 9B-C). As already reported in severe COVID19 in an Indian population [45], we found that HLA-DPB1*04:01 was significantly associated with RBD areactivity (Figure 9B-C). This is in line with the observation that none of the RBD peptides were predicted to be strong binders for this allele (Subtable S13b of Fahrner et al., 2022). Moreover, the HLA-DQA1*01:02 allele paired with the DQB1*05:02 allele was significantly associated with RBD areactivity (14% versus 0% in RBD areactive versus reactive respectively, p=0.042, Figure 9B). Finally, we analyzed T cell responses directed against S1-RBD sequences of the viral variants of concern (VOC) that were recently renamed by WHO as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2). Indeed, these strains predominantly mutate in the S gene compared with the reference (Wuhan) strain and more precisely within the S1-RBD peptide residues of the "PEP wtRBD" pool. Therefore, we generated a fourth peptide pool "PEP mutRBD" encompassing the 14 mutations described within the S1-RBD sequences of VOC (Table S12 of Fahrner et al., 2022) that we tested in 343 individuals. TH1/Tc1 cell reactivity was higher against PEP wtRBD than PEP mutRBD in univariate analyses (n=33 positive/48 (68%) vs 18/38 (47%) at D90, p value=0.051, n=positive/94 (46%) vs 23/82 (28%) at D180, p value=0.019), coinciding with a drop in the magnitude of IFNγ secretion levels in cancer free individuals (Figure 4F, Figure 4I). The multivariate analysis indicated that this difference was independent from age, gender and time of sampling (Table 13). The difference of T cell reactivity between PEP wtRBD and PEP mutRBD cannot be ascribed to non mutated peptide residues missing in PEP mutRBD pool (such as the immunodominant spike 29, which was recognized in <3% of vaccinees when tested separately in this high-throughput screening T cell assay (p=0.4, Figure S8G of Fahrner et al., 2022).
Table 13a. Multivariate analyses for vaccine or infection-induced IFNg release. PEPorf Multivariate analysis P.value Sampling time -0.001 (-0.003 to 0.000) 0.0 Age (years) 0.003 (-0.001 to 0.006) 0.1 Gender Male -0.117 (-0.213 to -0.019) 0.0 Cancer Yes -0.161 (-0.307 to -0.020) 0.0 Covid history and vaccine rounds No COVID-19 history ; 1 round 0.334 (0.209 to 0.460) <0.0No COVID-19 history ; 2 round 0.685 (0.484 to 0.900) <0.0Convalescent ; no round 0.411 (0.247 to 0.574) <0.0Convalescent ; 1 round 0.875 (0.689 to 1.069) <0.0 Table 13b. Multivariate analyses for vaccine or infection-induced IFNg release. PEPwtRBD Multivariate analysis P.value Sampling time -0.001 (-0.002 to 0.000) 0.2 Age (years) 0.001 (-0.003 to 0.004) 0.6 Gender Male -0.042 (-0.120 to 0.030) 0.3 Cancer Yes -0.179 (-0.342 to -0.002) 0.0 Covid history and vaccine rounds No COVID-19 history ; 1 round 0.101 (-0.004 to 0.215) 0.0No COVID-19 history ; 2 round 0.310 (0.123 to 0.507) 0.0Convalescent ; no round -0.028 (-0.163 to 0.109) 0.6Convalescent ; 1 round 0.397 (0.242 to 0.566) <0.0 Table 13c. Multivariate analyses for vaccine or infection-induced IFNg release . PEPmutRBD versus PEPwtRBD Multivariate analysis P.value PEPmutRBD 0.152 (-0.055 to 0.378) 0.1 Sampling time 0.001 (-0.001 to 0.003) 0.1 Age (years) -0.002 (-0.006 to 0.003) 0.5 Gender Male -0.046 (-0.167 to 0.078) 0.4 Cancer Yes 0.216 (-0.026 to 0.454) 0.0 Covid history and vaccine rounds No COVID-19 history ; 1 round -0.104 (-0.260 to 0.042) 0.1No COVID-19 history ; 2 round -0.336 (-0.620 to -0.037) 0.0Convalescent ; no round -0.023 (-0.215 to 0.153) 0.8Convalescent ; 1 round -0.358 (-0.617 to -0.151) 0.0 Altogether, these results suggest that defects in the TH1 repertoire affecting the recognition of SARS-CoV-2 S1-RBD are associated with susceptibility to infection or reinfection by SARS-CoV-2 or failure of Spike-based vaccines. T cell responses against 5 S1-RBD from VOCs appear to be reduced in vaccinees as of August 2021, commensurate with the fact that this antigenic region mutates more than other regions of the SARS-CoV-orfeome. Discussion Identifying immune correlates of protection from SARS-CoV-2 is critical to predict the efficacy of existing and future vaccines and to follow a potential decay in immune protection imposing repeated immunizations. Thus the titers of neutralizing antibodies that correlate with IgG antibodies against trimeric S or RBD represent a good proxy of protection against breakthrough infections [46,47]. The landscape of prevalence and immunodominance of SARS-CoV-2 T cell epitopes - supposedly associated with protection during the acute phase - has been thoroughly investigated [48]. Using 40-mer peptide pools covering regions of membrane, nucleocapsid, ORF3a, ORF7/8, and spike proteins, Tan et al. observed a statistically significant correlation between the early appearance of SARS-CoV-2 peptide-reactive cells and shorter duration of infection [49]. Here, we unravel the first prospective correlation between preexisting (before the first surge) SARS-CoV-2-specific TH2/Tc2 immune responses and susceptibility to infection with SARS-CoV-2 or reinfection with viral variants, based on 3 independent cohorts and two different methods to monitor TH1/Tc1 and TH2/Tc2 cytokines (ELISA and ELISpot). Both in healthy individuals and cancer subjects, the best immunological correlate for the susceptibility to infection with SARS-CoV-2 was undistinguishably a recall response characterized by a low ratio of TH1/TH2 lymphokines (and more precisely an IL-2/IL-5 ratio <1) secreted upon exposure to the reference SARS-CoV-2 viral strain. The IL-5 memory response coincided with a hole within the TH1/Tc1 cell repertoire affecting the RBD of the spike protein. Five lines of evidence argue in favor of the clinical significance and protective effect against the infection of TH1/Tc1 immune responses directed against anti-S1-RBD for the current pandemic. TH1/Tc1 responses were undetectable i) in individuals from the pre-vaccine era who are susceptible to infection by SARS-CoV-2, ii) in reinfected persons, and iii) in subjects manifesting breakthrough infections after vaccination, and iv) were somehow reduced against the S1-RBD mutated sequences from VOC in vaccinated HCW. Finally, given the high rate of mutations residing in the immunologically and clinically relevant sequence of interest (331-525 aminoacid residues of the spike protein), we are tempted to conclude that an immune-driven selection process of viral phylogeny is currently occurring, as already discussed [50,51]. Reportedly, CD4+ TH1 and TH2 responses are induced during the primary phase of viral infection, and both TH1 and TH2 can generate an anamnestic response upon rechallenge with the same virus [52]. Survivors from SARS-CoV-1 infection developed polyfunctional T cells producing TH1 cytokines and long-term CD8+ T cell responses as late as 11 years post-infection [9]. The TH1 cytokine IL-2 (which correlated with circulating non-activated TFH cells in convalescent patients in our study) was the pivotal factor distinguishing susceptible from resistant individuals. Signaling via the high-affinity IL-receptor (which requires CD25/IL-2Rα expression) favors the generation of CXCR5− T effector cells, and this is associated with TH1 responses sustained by the transcription factor TBX21. Moreover, the development of IFNγ producing effector memory T cells depends upon CD25.15 Accordingly, upon infection with lymphocytic choriomeningitis (LCMV), CD25-deficient CD4+ T cells largely fail to form IFNγ producing T effector cells in secondary lymphoid organs and to generate lung tissue resident memory T cells [53]. In contrast, increased TH2 cytokine release correlated with poor outcome in patients, a finding corroborated in mouse studies of SARS-CoV-1 [54,55] and SARS-CoV-2 [35]. During SARS-CoV-2 infection, TH2-associated blood markers, such as eosinophilia and circulating IL-5, IL-33, eotaxin-2 and eotaxin- 3 correlate with COVID-19 severity [56]. In fact, Dupilumab, an anti-IL-4Rα antibody blocking IL-13 and IL-4 signaling [57] protected against inflammatory and severe COVID-19 in two retrospective cohorts [35]. We found that Dupilumab boosts SARS-CoV-2-specific TH1 responses, supporting the rationale of current Phase II trials that evaluate this antibody in the prevention of severe COVID-19 lung infection. TCR signaling plays a major role in CD4+ polarization and can vary according to the TCR affinity, the amount of peptide/MHC-II complexes perceived by a TCR, or the length of time a T cell spends proofreading peptide/MHC-II complexes [15]. Of note, the RBD-specific TH1/Tc1 responses against spike regions 361-375 and 391-405 exhibited robust binding capacities across all MHC class I alleles. Several authors reported cross-reactivities between CCC and SARS-CoV-2 [9,20,23,24,33,34,58,59]. However, such cross-reactive T cells may correlate with poor clinical outcome [60–65]. Indeed, according to one report [21], preexisting CCC-specific memory CD4+ T cells exhibit low TCR avidity in almost all unexposed individuals, and are strongly expanded in severe but not mild COVID-19. Moreover, CCC/SARS-CoV-2-cross-reactive T cell clones shared among convalescent and infected individuals harbored lower functional avidity than non-cross-reactive clones, suggesting antigenic imprinting of the TCR repertoire by previous exposure to CCC [26,66]. Of note, these spike-specific cross-reactive CD4+ T cells might not only re-expand during infection but also following vaccination. In line with this possibility, we detected a strong positive correlation between CCC and SARS-CoV-2-specific IL-5 release by memory T cells in unexposed individuals. Moreover, CCC-specific IgG titers were higher in susceptible compared to resistant individuals. Finally, the SARS-CoV-1 and ORF8-specific T cell repertoire prevailing in the pre-COVID-19 era failed to be clinically relevant for the avoidance of COVID-19 and such a repertoire was frequently detected in reinfected individuals during their convalescence phase. Of note, we generated S1-RBD-specific IL-or IL-5 producing T cell lines and CD4+CD8+ T cell clones from one HCW presenting a breakthrough infection after vaccination. Hence, we cannot rule out the possibility that a preexisting TH2 immunity, for instance directed against S1-RBD sequences shared by sarbecoviruses9 could increase the susceptibility to, and severity of, SARS-CoV-2 infection [54–56,67]. Our data fuel the theory that i) robust TH1 memory immune responses against RBD might restrain viral infection, thus exerting a selective pressure on the virus, obliging it to generate escape variants by mutation of RBD, ii) preexisting TH2 antiviral responses might not only be incapable of eliminating SARS-CoV-2-infected cells but actually favor (re)infection with SARS-CoV-2, ultimately increasing the viral reservoir, thus favoring the emergence of viral variants. Hence, immunization strategies should aim at triggering TH1/Tc1 (rather than TH2/Tc2) responses against S1-RBD. The efficacy of cellular immune response relies on three components, (i) the antigen, (ii) the adjuvant and (iii) the dynamics of viral evolution [68]. Immunization with inactivated SARS-CoV-1 or with the whole spike (S) protein, caused eosinophilic infiltration following viral re-exposure in mice [69,70]. Unfortunately, the efficacy of the vaccines composed of inactivated virus produced by Sinovac Biotech (CoronaVac) and Sinopharm (BBIBP-CorV) against VOC have not yet been reported. In contrast, at least in the case of SARS-CoV-1, immunization with RBD induced neutralizing antibodies in the absence of TH2/Tc2 responses [71]. Vaccine adjuvants can stimulate TH1/Tc1-favorable innate immunity, as this is the case for multiple viral vectors, virus-like particles and mRNA containing nanoparticles [66,72]. Finally, virus adaptation to the host has to be outcompeted. One might infer from our data that the currently protective immunodominant regions generating a TH1/Tc1 profile may be the focus of the future antigenic drift of SARS-CoV-2, in which case vaccines would have to be updated regularly [73]. Therefore, to win the race against emerging variants, an expedited world-wide vaccination rollout ensuring an immunization en masse against relevant epitopes (and in particular the entire RBD region of the former or current VOCs and Sarbecovirus [67] with vaccine formulations ensuring TH1/Tc1 (rather than TH2/Tc2) responses should outwit the COVID-19 pandemic. In countries of broad vaccine coverage, it may be advantageous to screen the population for IFNγ responses against S1-RBD and hence to determine the need of each individual for booster vaccination. Finally, current efforts to decipher HLA haplotypes associated with maladaptive S1-RBD TH1 responses may open an avenue for personalized vaccine design [74–76].
Example 2: Tumor infiltrating lymphocytes (TIL) as a source to predict tissue resident reactivity to epitopes within viral species that give rise to increased risk to autoimmunity, increased protection or overt, non-productive inflammation. The clinical characteristics of the patients and multicontact cases from whom the results below are derived are shown in Example 1 (Tables 1, 8) and in Table 14. Table 14: Clinical characteristics of indexed and contaminated Patients' characteristics Index (n=54) Contaminated (n=22) P.value Age (years)Median 56 0.[Range] [21-83] [23-82] n % n % Gender Male 17 31 11 0.Female 37 69 11 MalignancyYes 54 100 22 11.No 0 0 0 SymptomsYes 51 94 7 0.54 No - - 7 Unknown 3 6 8 Clinical course Day hospital (Mild) - - 5 <0.0Hospitalization (Moderate) - - 1 Admission to ICU (Severe) - - 1 ICU: Intensive care unit Peptide selection The final version of the genome of the SARS-CoV-2 virus was released on January 17th 2020 (RefSeq ID MN908947.3). On March 6th 2020 there was no information regarding the immunogenicity of SARS-CoV-2 proteins, from the publicly available sequence data we synthesized peptides covering the entire spike (RefSeq ID QHD43416.1) and nucleocapsid proteins (RefSeq ID QHD43423.2). From the membrane protein the peptides were selected to cover 2 potential immunogenic regions of the SARS-CoV-2 membrane protein (RefSeq QHD43419.1); these regions had immunogenic potential because there is a similar region in the SARS-CoV-1 membrane protein. We also selected peptides covering the entire ORF8 (RefSeq ID QHD43422.1) and ORF(RefSeq ID QHI42199.1) proteins, these peptides were chosen because these two proteins do not exist in the SARS-CoV-1 and might reveal to be interesting immunogenic targets due their uniqueness of being non-shared with SARS-CoV-1, and not to be present in other Coronaviruses. They will also aid to differentiate between vaccination and exposure since they are not shared between other Coronavirus-species. Other SARS-CoV peptides were peptides found to be immunogenic in previous reported studies (92-99). In addition, the selected peptides do not have any exact match with the other human coronaviruses. ResultsTIL (tumor infiltrating lymphocytes) are T-cells, mostly CD4+ and CD8+ T-cells that home preferentially into malignant tissue. They have a particularly homing mechanism and are believed to derive about 10% from immune cells from peripheral blood and from 90% from tissue-resident immune cells: cells that home into tissues and rarely or never leave the tissue. The reactivity of TIL – that are harvested from tumor lesions during surgery – allows a unique view into tissue-reactive T-cells. It also allows to examine potential autoimmune reactivity, since – in principle – anti-cancer directed cellular immune responses are in fact very focused auto-immune responses. TIL reactivity therefore reflects i) an anti-cancer response, and ii) autoimmune response in general. TIL were expanded ex vivo from tumor specimens from patients with different cancer lesions and tested for reactivity to the 187 peptides derived from the SARS-CoV-2 targets. Reactivity was determined by IFN-gamma production in 10e4 TIL / peptide species or as IL-17 production / 10e4 TIL / peptide target. TIL were tested from two different populations: patients who underwent surgery for tumors in the pre-pandemic time, i.e., starting in 2017 till early 2019 in Lisbon, Portugal, and patients during the pandemic time (as shown in Tables 15 and 16). T-cell reactivity resided in the SARS-CoV-2 Spike protein, in the nucleocapside protein, as well as in viral proteins whose functions are still ill-defined (e.g. ORF8). The SARS-CoV2 peptide selection allowed to identify cross-reactivity with SARS-CoV-1 but not with other circulating Coronaviral species. Cross-reactivity to non-mutant or mutant human ‘self proteins’ is possible. 1. IFN production. Table 15 : SARS-2016.05.006 (similarity to human proteins and to bacterial species, identified in Table 17 ), Spike peptide 30 (human tissue proteins, e.g. Tensin which is responsible for driving tissue remodeling in lung tissue and other organs, extracellular matrix formation) and the nucleocapsid 12 (no similarities found) are recognized in TIL harvested from patients in the pre-pandemic and in the pandemic timeframes.
Reactivity to SARS-2016.05.006, to the spike peptide 30 and nucleocapsid 12 in the pre-pandemic period (e.g. 2017, 2018, early 2019). Cross-reactivity between human proteins and SARS-CoV are responsible for the recognition defined by IFN production in the pre-pandemic and can also drive the T-cell responses in the pandemic time frame. The Spike protein 15 is preferentially recognized in the post-pandemic time frame (human proteins and / or bacteria, implying that cross-reactivity does not only pre-exist in the immune repertoire but T-cells can be stimulated and expanded upon exposure to SARS-CoV-2 that also recognize human proteins. The ORF8-9 in the pre-pandemic time frame (similar to human Mycocilin, a protein that is normally secreted into the aqueous humor of the eye), is recognized in the pre-pandemic time frame, yet less in the pandemic, suggesting T-cell anergy or clonal deletion. Exposure to the virus may eliminate these T-cells or keep them non-functional. 2. Other cytokines.Not only IFN-gamma (a strongly inflammatory cytokine associated with immune protection and also with overt, i.e. too strong immune responses), yet other cytokines, such as IL-17, that particularly drives autoimmune responses, are detected in the pre-pandemic time frame against peptides that derived from SARS-CoV-2 (Table 16).For instance peptide ORF8-1 that shares homology to human proteins or bacterial species. Exposure of the immune system to SARS-CoV-2 would allow for activation and expansion of SARS-CoV-2 specific T-cell responses that would also recognize human. Also ORF8-17 is recognized from T-cells prior to the pandemic time (in October 2017) in tumor infiltrating T-cells. This peptide does not share homology to human proteins or bacterial species and shows that the human T-cell receptor repertoire did not delete anti-SARS-CoV-2 directed T-cell responses during thymic education, i.e. the individual development of the human immune system. IL-17 productive T-cells that are pre-existing against SARS-CoV, can augment anti-viral responses and induce overt inflammation or induce autoimmune responses in case of similarities between viral targets and human proteins. 3. The spike 30 peptide that represents a target for T-cells in the pre-pandemic and pandemic time frame defined by IFN gamma production – that would also be able to drive autoimmune response due to the cross-reactivity to the peptide species listed in Table 17 is also affected by mutations in the spike protein. Such cross-reactive T-cells may also be protective or drive overt tissue damaging immune responses.
Potential protection / design of future vaccinesTumor infiltrating T-cells are a source of tissue resident T-cells that enable to detect autoimmune responses (e.g. reactivity against non-mutant) self proteins that can be screened for reactivity against viral targets. TIL are a superior source as compared to immune cells from blood to screen for potential autoimmunity in viral targets since they are able to invade tissues and since anti-cancer immune responses are a certain form of autoimmune responses. Positive reactivity against SARS-CoV-2 peptides or viral targets in general in TIL, based on the cytokine production pattern, may indicate i) increased risk for autoimmune diseases upon exposure to the viral pathogen, ii) increased protection (since the virus-reactive T- cells are already present), and/or iii) increased pathogenicity upon viral infection due to an overt immune response (unproductive inflammation in the lung and other organs). Organ-specific damage is therefore not only a bystander effect of the cellular immune response, it is associated with the presence of T-cells that recognize both the viral pathogen and non-mutant human tissue. The reactivity pattern is quite consistent in TIL from patients in the pre-pandemic time frame. TIL are therefore a source to predict increased risk for autoimmunity, increased protection or non-productive inflammation. Screening should be made with different cytokines: IFN-gamma indicates inflammation, peptide targets eliciting IL-17 may indicate increased risk for autoimmune responses since IL-17 is in general associated with autoimmunity. Such peptide species may be eliminated from vaccine candidates.  Examples eliciting IFN-gamma responses: - Spike15: NLVRDLPQGFSALEP (SEQ ID No: 15) preferentially pandemic period Crossreactivity to tissue and bacteria - Spike30: WNSNNLDSKVGGNYN (SEQ ID No: 30) pre and pandemic periods Crossreactivity to tissue and bacteria - nucleocapsid_12: TLPKGFYAEGSRGGS (SEQ ID No: 97) (SARS-CoV1/2) pre and pandemic periods No hits found - SARS_2016.05.006: LLNKHIDAYKTFP (SEQ ID No: 121) (SARS-CoV1/2) pre and pandemic periods Crossreactivity to tissue and bacteria - ORF8_9: LIELCVDEAGSKSPI (SEQ ID No: 170) preferentially pre-pandemic Cross-reactivity to tissue  Examples eliciting IL-17 responses: - ORF8_1: MKFLVFLGIITTVAA (SEQ ID No: 162) Crossreactivity to tissue and bacteria - ORF8_17: DVRVVLDFI (SEQ ID No: 178) No hits identified Table 15 COVID PEPTIDES D1 TILs (metastasis pancreas adenocarci noma INFg pg 10000 cells D11 TILs (metastasis pancreas adenocarci noma) INFg pg 10000 cells D13 TILs (metastasis pancreas adenocarci noma) INFg pg 10000 cells D126 TILs (pancreas adenocar cinoma) INFg pg 10000 cells D303 TILs (rectum adenocar cinoma) INFg pg 10000 cells D306 TILs (pancreas adenocarci noma) INFg pg 10000 cells D309 TILs (pancreas adenocar cinoma) INFg pg 10000 cells D310 TILs (colon adenocarci noma) INFg pg 10000 cells D311 TILs (colon adenocar cinoma) INFg pg 10000 cells D1209 PBMCs (pancreas adenocarci noma) INFg pg 10000 cells SARS_HLA- A*02:01_10,0 137,00 101,66 54,9 32,3 166,5 5,6 9,3 303,1 0, SARS_HLA- A*02:01_20,0 0,00 11,48 3,3 19,2 0,0 2,0 5,4 128,9 0, SARS_HLA- A*02:01_30,0 0,00 51,79 2,0 4,5 0,0 4,5 0,0 123,9 0, SARS_HLA- A*02:01_40,0 0,00 0,00 0,2 11,3 0,0 3,6 3,6 134,3 0, SARS_HLA- A*02:01_50,0 0,00 0,00 5,1 0,0 0,0 20,0 0,0 74,1 0, SARS_HLA- A*02:01_60,0 0,00 48,30 32,0 0,9 0,0 3,7 0,0 74,2 0, SARS_HLA- A*02:01_70,0 0,00 95,26 23,5 2,9 0,0 21,8 7,5 128,1 0, SARS_HLA- A*02:01_80,0 129,08 32,70 69,7 0,4 209,3 6,6 23,0 144,7 0, SARS_HLA- A*02:01_90,0 0,00 0,00 46,6 0,0 0,0 3,0 0,0 157,7 0, SARS_HLA- A*02:01_100,0 0,00 0,00 4,5 0,0 0,0 4,9 0,0 96,2 0, SARS_HLA- A*02:01_110,0 0,00 1,58 147,5 0,0 0,0 1,4 0,0 81,5 0, SARS_HLA- A*02:01_120,0 0,00 0,00 0,0 0,0 0,0 1,8 0,0 76,2 0, SARS_HLA- A*02:01_130,0 0,00 57,80 0,0 0,0 0,0 8,6 0,0 49,4 0, 73 SARS_HLA- A*02:01_140,0 0,00 18,74 0,0 0,0 0,0 3,7 0,0 97,7 0, SARS_HLA- A*02:01_150,0 0,00 0,00 0,0 0,0 0,0 0,7 0,0 91,0 0, SARS_HLA- A*02:01_160,0 8,36 14,17 54,3 2,8 0,0 10,2 0,0 137,8 0, SARS_HLA- A*02:01_170,0 0,00 0,00 9,0 0,9 0,0 10,3 12,2 138,0 0, SARS_HLA- A*02:01_180,0 0,00 0,00 0,0 0,0 0,0 0,2 0,0 137,4 0, SARS_HLA- A*02:01_190,0 0,00 0,00 0,0 0,0 0,0 6,7 0,0 56,8 0, SARS_HLA- A*02:01_200,0 0,00 0,00 0,0 0,0 0,0 2,1 0,0 81,5 0, SARS_HLA- A*02:01_210,0 0,00 0,00 0,0 0,0 0,0 0,4 0,0 43,0 0, SARS_10.1128 _10,0 0,00 0,00 0,0 0,0 0,0 1,0 0,0 75,7 0, SARS_10.1128 _20,0 0,00 56,67 0,0 0,0 0,0 5,7 0,0 90,1 0, SARS_10.1128 _30,0 0,00 36,61 17,8 0,0 0,0 4,0 0,0 138,9 0, SARS_10.1128 _40,0 0,00 69,16 7,5 0,9 0,0 8,6 0,0 107,2 0, SARS_10.1128 _50,0 0,00 0,00 0,0 0,0 0,0 1,7 0,0 83,8 0, SARS_10.1128 _60,0 0,00 0,00 0,0 0,0 0,0 0,6 0,0 75,4 0, SARS_10.1128 _70,0 0,00 28,08 0,0 0,0 0,0 0,6 0,0 78,9 0, SARS_10.1128 _80,0 0,00 63,26 0,0 0,0 0,0 3,2 0,0 68,2 0, SARS_HLA- DR0401_10,0 0,00 0,00 0,0 0,0 0,0 31,3 0,0 104,6 0, SARS_HLA- DR0401_20,0 0,00 0,00 0,0 0,0 0,0 5,3 0,0 39,7 0, 74 SARS_HLA- DR0401_30,0 21,84 10,43 28,7 118,3 0,0 4,3 5,8 130,9 0, SARS_HLA- DR0401_40,0 5,41 0,00 0,0 0,0 0,0 6,5 3,0 219,3 0, SARS_3726.20 05_10,0 0,00 0,00 5,8 0,0 0,0 9,4 0,0 129,4 0, SARS_3726.20 05_20,0 0,00 0,00 0,0 0,0 0,0 3,8 0,0 109,5 0, SARS_5314.20 04_10,0 0,00 90,98 0,0 0,0 0,0 0,5 0,0 83,8 0, SARS_5314.20 04_20,0 0,00 0,00 0,0 0,0 0,0 3,6 0,0 85,8 0, SARS_01025- 8_10,0 0,00 32,33 1,6 0,0 0,0 3,0 0,0 93,2 0, SARS_01025- 8_20,0 0,00 151,43 0,0 0,0 0,0 0,0 0,0 83,1 0, SARS_01026- X0,0 0,00 27,36 14,6 0,0 0,0 3,9 2,9 122,0, SARS_2016.05 .0060,0 145,37 179,35 117,6 11,2 261,2 4,9 14,6 322,3 0, membrane_1 0,0 0,00 0,00 24,0 0,0 0,0 2,7 1,3 169,8 0,0 membrane_2 0,0 0,00 15,32 160,6 0,0 0,0 3,9 0,0 153,6 0,0 membrane_3 0,0 0,00 0,00 166,1 0,0 0,0 2,3 0,0 154,1 0,0 membrane_4 0,0 0,00 0,00 1,9 0,4 0,0 4,0 0,0 157,0 0,0 membrane_5 0,0 0,00 0,00 103,9 0,0 0,0 3,1 0,0 139,0 0,0 membrane_6 0,0 0,00 209,89 128,1 0,0 0,0 4,5 4,5 111,2 0,0 membrane_7 0,0 35,79 155,66 68,6 4,9 16,3 4,5 25,6 276,7 0,0 Spike1 0,0 176,71 0,00 21,8 7,2 0,0 3,0 54,7 327,9 0,0 Spike2 0,0 0,00 0,00 0,0 4,2 0,0 2,0 5,1 125,3 0,0 Spike3 0,0 0,00 0,00 0,0 0,0 0,0 5,5 2,6 164,5 0,0 Spike4 0,0 0,00 0,00 0,0 0,0 0,0 3,7 0,0 160,3 0,0 Spike5 0,0 0,00 0,00 0,0 5,8 0,0 2,5 9,7 122,8 0,0 Spike6 0,0 0,00 0,00 0,0 0,0 0,0 3,1 0,0 137,1 0,0 Spike7 0,0 0,00 0,00 0,0 10,4 0,0 7,1 0,0 165,4 0,0 Spike8 0,0 0,24 0,00 213,8 23,0 21,7 2,8 1,5 285,8 0,0 Spike9 0,0 12,96 189,32 0,0 2,6 0,0 21,6 8,4 204,3 0,0 Spike10 0,0 0,00 32,66 0,0 0,0 0,0 2,8 0,0 94,2 0,0 Spike11 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 127,4 0,0 Spike12 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 59,0 0,0 Spike13 0,0 0,00 0,00 0,0 9,0 0,0 3,1 0,0 75,4 0,0 Spike14 0,0 0,00 0,00 0,0 0,0 0,0 2,8 0,0 69,1 0,0 Spike15 0,0 0,00 0,00 0,0 0,0 0,0 1,2 0,0 141,6 0,0 Spike16 0,0 0,00 0,00 0,0 0,0 0,0 10,4 0,0 176,1 0,0 Spike17 0,0 0,00 0,00 0,0 0,0 0,0 8,9 0,0 241,4 0,0 Spike18 0,0 0,00 0,00 0,0 0,0 0,0 1,8 0,0 69,9 5,0 Spike19 0,0 0,00 0,00 0,0 0,0 0,0 1,3 0,0 87,5 0,0 Spike20 0,0 0,00 0,00 0,0 0,0 0,0 1,5 0,0 79,7 0,0 Spike21 0,0 0,00 0,00 0,0 0,0 0,0 1,1 0,0 114,5 0,0 Spike22 0,0 0,00 0,00 0,0 0,0 0,0 3,4 0,0 82,5 0,0 Spike23 0,0 0,00 0,00 0,0 0,0 0,0 4,3 0,0 63,3 0,0 Spike24 0,0 15,63 0,00 0,0 0,0 0,0 4,6 0,0 147,6 0,0 Spike25 0,0 0,00 47,33 0,0 0,0 0,0 2,6 0,0 259,9 0,0 Spike26 0,0 0,00 0,00 39,7 0,0 0,0 0,0 0,0 127,3 0,0 Spike27 0,0 0,00 0,00 65,1 0,0 0,0 0,5 0,0 57,3 0,0 Spike28 0,0 0,00 0,00 0,0 0,0 0,0 0,7 0,0 131,7 0,0 Spike29 0,0 0,00 158,41 0,0 0,0 0,0 0,0 0,0 83,1 0,0 Spike30 0,0 0,00 69,14 36,8 0,0 0,0 0,9 0,0 131,1 0,0 Spike31 0,0 0,00 0,00 0,0 0,0 0,0 15,0 0,0 61,0 0,0 Spike32 0,0 160,05 21,95 0,0 0,0 25,2 2,3 1,6 167,0 0,0 Spike33 0,0 0,00 0,00 31,9 0,0 0,0 3,0 0,0 201,2 0,0 Spike34 0,0 0,00 0,00 0,0 0,0 0,0 2,9 0,0 104,5 0,0 Spike35 0,0 0,00 0,00 0,0 0,0 2,4 1,1 0,0 101,0 0,0 Spike36 0,0 0,00 0,00 99,7 0,0 0,0 0,0 0,0 103,4 0,0 Spike37 0,0 0,00 0,00 0,0 0,0 0,0 0,5 0,0 113,0 0,0 Spike38 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 165,5 0,0 Spike39 0,0 0,00 0,00 0,0 0,0 0,0 1,7 0,0 146,5 0,0 Spike40 0,0 0,00 0,00 21,0 0,0 0,0 2,0 0,0 205,5 0,0 Spike41 0,0 105,07 0,00 55,0 0,0 442,7 3,0 100,6 206,2 0,0 Spike42 0,0 0,00 0,00 31,9 0,0 0,0 1,9 2,9 164,5 0,0 Spike43 0,0 0,00 0,00 6,2 0,0 0,0 0,0 0,0 104,2 0,0 76 Spike44 0,0 0,00 0,00 0,0 0,0 26,5 1,4 0,0 158,1 0,0 Spike45 0,0 139,74 0,00 1,9 0,0 0,0 21,8 0,0 99,9 0,0 Spike46 0,0 0,00 0,00 0,0 0,0 0,0 9,7 0,0 103,7 0,0 Spike47 0,0 0,00 0,00 29,4 0,0 0,0 0,0 0,1 123,4 0,0 Spike48 0,0 0,00 0,00 45,7 0,0 0,0 2,4 137,3 205,5 0,0 Spike49 0,0 112,71 27,08 73,0 6,0 30,8 0,2 24,9 261,3 0,0 Spike50 0,0 0,00 0,00 0,0 0,0 0,0 0,7 0,0 144,5 0,0 Spike51 0,0 0,00 11,90 0,0 0,0 0,0 13,9 8,1 154,4 0,0 Spike52 0,0 0,00 13,42 0,0 0,0 0,0 0,0 0,0 122,9 0,0 Spike53 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 89,1 0,0 Spike54 0,0 0,00 0,00 0,0 0,0 0,0 6,1 0,0 149,6 0,0 Spike55 0,0 0,00 0,00 0,0 0,0 0,0 1,7 24,0 66,1 0,0 Spike56 0,0 97,90 15,25 80,9 0,0 200,4 1,9 40,2 247,9 0,0 Spike57 0,0 2,64 0,00 0,0 3,1 0,0 0,6 0,0 230,5 0,0 Spike58 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 102,3 0,0 Spike59 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 165,9 0,0 Spike60 0,0 0,00 0,00 0,0 0,0 0,0 0,3 0,0 83,8 0,0 Spike61 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 73,1 0,0 Spike62 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 86,3 0,0 Spike63 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 66,4 0,0 Spike64 0,0 0,00 0,00 0,0 2,9 0,0 2,2 4,5 169,5 0,0 Spike65 0,0 0,00 337,93 0,0 0,0 0,0 0,5 8,9 190,7 0,0 Spike66 0,0 0,00 186,03 0,0 0,0 0,0 1,5 0,0 145,2 0,0 Spike67 0,0 0,00 160,38 0,0 0,0 0,0 0,0 0,0 83,3 0,0 Spike68 0,0 0,00 0,00 0,0 0,0 0,0 1,0 0,0 72,9 0,0 Spike69 0,0 0,00 411,14 0,0 0,0 0,0 5,7 0,0 83,9 0,0 Spike70 0,0 0,00 0,00 0,0 0,0 0,0 0,1 0,0 47,1 0,0 Spike71 0,0 0,00 284,52 0,0 0,0 0,0 0,0 0,0 59,2 0,0 Spike72 0,0 228,65 37,46 0,0 5,6 31,2 0,3 0,5 189,7 0,0 Spike73 0,0 0,00 39,74 0,0 0,0 0,0 0,2 1,7 182,9 0,0 Spike74 0,0 0,00 68,17 0,0 0,0 0,0 9,0 0,0 80,7 0,0 Spike75 0,0 0,00 0,00 0,0 0,0 0,0 12,6 0,0 92,7 0,0 Spike76 0,0 0,00 0,00 0,0 0,0 0,0 2,9 0,0 125,6 0,0 Spike77 0,0 0,00 0,00 0,0 0,0 0,0 2,4 0,0 97,5 0,0 Spike78 0,0 0,00 0,00 0,0 0,0 0,0 0,6 0,0 94,2 0,0 77 Spike79 0,0 0,00 0,00 0,0 0,0 0,0 0,0 0,0 81,3 0,0 Spike80 0,0 113,50 0,00 0,0 0,0 0,0 0,0 0,0 126,4 0,0 Spike81 0,0 110,22 0,00 2,9 0,0 13,7 4,0 20,7 209,7 0,0 Spike82 0,0 0,00 142,05 0,0 0,0 0,0 3,0 0,0 142,4 0,0 Spike83 0,0 0,00 0,00 0,0 0,0 0,0 2,6 0,0 50,5 0,0 Spike84 0,0 0,00 171,10 0,0 0,0 0,0 0,3 0,0 44,4 0,0 Spike85 0,0 0,00 0,00 0,0 12,4 0,0 0,1 0,0 42,8 0,0 nucleocapsid_ 10,0 0,00 0,00 0,0 0,0 0,0 2,0 0,0 26,3 0, nucleocapsid_ 20,0 0,00 0,00 0,0 0,0 0,0 0,4 0,0 63,8 0, nucleocapsid_ 30,0 66,40 93,72 67,8 0,0 110,1 4,5 21,1 180,4 0, nucleocapsid_ 40,0 1,42 155,76 2,9 0,0 0,0 0,8 13,9 109,7 0, nucleocapsid_ 50,0 0,00 155,89 4,5 2,4 0,0 0,6 0,0 111,0, nucleocapsid_ 60,0 0,00 31,01 0,0 2,5 0,0 20,4 17,7 137,7 0, nucleocapsid_ 70,0 19,39 302,81 11,4 12,9 0,0 11,2 0,0 106,2 0, nucleocapsid_ 80,0 0,00 0,00 5,8 0,0 0,0 1,9 14,9 142,8 0, nucleocapsid_ 90,0 39,72 314,80 3,1 0,0 1,5 0,0 3,8 45,6 0, nucleocapsid_ 100,0 11,71 302,99 22,5 2,2 64,7 6,7 23,2 139,8 0, nucleocapsid_ 110,0 0,00 0,00 0,0 3,2 0,0 30,1 7,8 55,3 0, nucleocapsid_ 120,0 64,45 174,67 23,2 24,4 0,0 3,2 58,1 235,8 0, nucleocapsid_ 130,0 0,00 177,14 0,0 24,4 0,0 1,8 14,4 191,3 0, nucleocapsid_ 140,0 0,00 202,62 0,0 3,0 0,0 9,5 20,4 95,6 0, 78 nucleocapsid_ 150,0,00 111,0,69,6 0,0 8,0 19,0 240,4 0,0 nucleocapsid_ 160,110,92 32,0,24,0 0,0 1,7 0,0 175,3 0,0 nucleocapsid_ 170,67,01 0,0,10,7 0,0 1,7 0,0 120,4 0,0 nucleocapsid_ 180,0,00 269,0,45,8 0,0 2,5 0,0 198,4 0,0 nucleocapsid_ 190,25,74 184,37,49,7 0,0 9,3 80,0 334,4 0,0 nucleocapsid_ 200,0 0,00 20,79 0,0,0 0,0 3,7 4,6 184,4 0,0 nucleocapsid_ 210,0 0,00 73,90 0,0,0 0,0 0,0 0,0 60,2 0,0 nucleocapsid_ 220,0 0,00 177,89 0,0,0 0,0 1,8 0,0 125,00, nucleocapsid_ 230,0 0,00 0,00 0,0,0 0,0 0,3 0,0 92,6 0,0 nucleocapsid_ 240,0 0,00 46,80 0,0,0 0,0 0,0 0,0 92,5 0,0 nucleocapsid_ 250,0 0,00 0,00 0,0,0 0,0 1,1 0,0 75,8 0,0 nucleocapsid_ 260,0 0,00 8,29 0,0,0 0,0 0,6 0,0 114,8 0,0 nucleocapsid_ 270,0 48,34 83,05 0,0,0 0,0 3,5 0,0 240,9 0,0 nucleocapsid_ 280,0 128,71 0,00 0,149,1 0,0 2,3 44,7 195,6 0,0 ORF8_1 0,0 284,71 0,00 0,0 0,0 0,0 1,1 6,2 8,3 0,0 ORF8_2 0,0 0,00 0,00 0,0 0,0 0,0 1,2 0,0 0,0 0,0 ORF8_3 0,0 0,00 0,00 0,0 0,0 0,0 6,4 0,0 3,5 0,0 ORF8_4 0,0 0,00 76,94 0,0 0,0 0,0 4,0 0,0 1,3 0,0 ORF8_5 0,0 146,76 62,95 0,0 0,0 0,0 0,0 0,0 0,0 0,0 ORF8_6 0,0 204,83 0,00 0,0 0,0 0,0 2,0 0,0 0,0 0,0 ORF8_7 0,0 217,82 94,47 0,0 0,0 0,0 0,0 0,0 0,0 0,0 79 ORF8_8 0,0 69,59 37,50 0,0 0,0 0,0 1,9 4,6 28,1 0,0 ORF8_9 0,0 112,66 251,07 9,2 0,0 0,0 1,6 0,0 1,8 0,0 ORF8_10 0,0 0,00 0,00 0,0 0,0 0,0 0,7 0,0 0,0 0,0 ORF8_11 0,0 0,00 0,00 0,0 0,0 0,0 2,8 0,0 0,0 0,0 ORF8_12 0,0 0,00 83,89 0,0 0,0 0,0 1,0 0,0 0,0 0,0 ORF8_13 0,0 0,00 19,58 0,0 0,0 0,0 0,0 0,0 0,0 0,0 ORF8_14 0,0 0,00 0,00 0,0 0,0 0,0 0,9 0,0 0,0 0,0 ORF8_15 0,0 0,00 0,00 0,0 0,0 0,0 2,7 0,0 0,0 0,0 ORF8_16 0,0 38,17 100,81 0,0 0,0 0,0 5,6 0,0 0,0 0,0 ORF8_17 0,0 139,79 0,00 89,0 45,1 0,0 1,4 2,5 9,3 0,0 ORF10_1 0,0 41,30 0,00 7,8 8,7 0,0 0,5 0,0 0,0 0,0 ORF10_2 0,0 45,48 0,00 5,9 21,5 0,0 1,1 0,0 0,0 0,0 ORF10_3 0,0 19,81 0,00 0,1 16,3 0,0 1,2 0,0 0,0 0,0 ORF10_4 0,0 29,29 0,00 2,2 23,9 0,0 2,7 0,0 0,0 0,0 ORF10_5 0,0 30,02 0,00 0,0 21,7 0,0 3,1 0,0 0,0 0,0 ORF8_A 0,0 48,99 0,00 0,0 15,9 0,0 1,3 0,0 0,0 0,0 ORF8_BC 0,0 129,49 60,03 46,8 26,6 277,2 2,5 17,3 0,0 0,0 ORF3a_AB 0,0 265,83 0,00 151,3 1,4 133,5 6,2 116,2 6,9 0,0 ORF3a_C 0,0 130,79 0,00 14,4 0,0 32,3 16,2 8,9 6,8 0,0 VIRUS (SARS- CoV-2) No Data 254,69 0,7,6 No Data No Data No Data No Data No Data 0,0 OKT3 0,0 28,20 27,76 175,3 24,0 407,6 497,8 320,1 724,7 0,0 PHA 0,0 337,76 0,00 0,0 39,7 113,0 552,2 325,6 64,4 0,0 EBNA 0,0 0,00 0,00 0,0 0,0 0,0 1411,0 3594,0 9,3 1,0 CMV 0,0 0,00 0,00 0,0 9,0 0,0 1207,0 3446,0 19,5 0,0 CMV Pool No Data 140,66 0,00 65,0 No Data No Data No Data No Data No Data 0,0 M1 0,0 166,14 16,49 0,4 1,1 82,4 4,5 0,0 0,0 0,0 80 Table 16 Pre Pandemic Post Pandemic COVID PEPTIDES D1 TILs (metastasis pancreas adenocarcinoma) IL17 pg 10000 cells D303 TILs (rectum adenocarcinoma) IL17 pg 10000 cells D306 TILs (pancreas adenocarcinoma) IL17 pg 10000 cells D309 TILs (pancreas adenocarcinoma) IL17 pg 10000 cells D311 TILs (colon adenocarcinoma) IL17 pg 10000 cells SARS_HLA- A*02:01_10,0 59,4 0,0 0,0 43, SARS_HLA- A*02:01_20,0 77,9 0,0 0,0 16, SARS_HLA- A*02:01_30,0 48,1 0,0 0,0 24, SARS_HLA- A*02:01_40,0 57,3 0,0 0,0 20, SARS_HLA- A*02:01_50,0 99,5 0,0 0,0 39, SARS_HLA- A*02:01_60,0 30,5 0,0 0,0 20, SARS_HLA- A*02:01_70,0 78,1 4,3 0,0 25, SARS_HLA- A*02:01_80,0 130,5 12,4 0,0 35, SARS_HLA- A*02:01_90,0 35,2 0,0 0,0 33, SARS_HLA- A*02:01_100,0 21,1 0,0 0,0 14, SARS_HLA- A*02:01_110,0 16,3 0,0 0,0 24, SARS_HLA- A*02:01_120,0 32,3 0,0 0,0 18, 81 SARS_HLA- A*02:01_130,0 35,8 0,0 0,0 11, SARS_HLA- A*02:01_140,0 22,8 0,0 0,0 12, SARS_HLA- A*02:01_150,0 24,5 0,0 0,0 15, SARS_HLA- A*02:01_160,0 49,9 0,0 0,0 22, SARS_HLA- A*02:01_170,0 40,6 0,0 0,0 27, SARS_HLA- A*02:01_180,0 18,0 0,0 0,0 12, SARS_HLA- A*02:01_190,0 13,4 0,0 0,0 16, SARS_HLA- A*02:01_200,0 31,1 0,0 0,11, SARS_HLA- A*02:01_210,0 16,3 0,0 0,0 16, SARS_10.1128_1 0,0 27,7 0,0 0,0 14, SARS_10.1128_2 0,0 21,9 0,0 0,0 18,9 SARS_10.1128_3 0,0 44,1 0,0 0,0 18,2 SARS_10.1128_4 0,0 36,5 0,0 0,0 28,8 SARS_10.1128_5 0,0 26,6 0,0 0,0 9,7 SARS_10.1128_6 0,0 12,3 0,0 0,0 15,8 SARS_10.1128_7 0,0 18,1 0,0 0,0 11,5 SARS_10.1128_8 0,0 5,3 0,0 0,0 17,9 SARS_HLA- DR0401_10,0 20,5 0,0 0,0 11, SARS_HLA- DR0401_20,0 20,2 0,0 0,0 26, SARS_HLA- DR0401_30,0 44,4 0,3 0,0 18, 82 SARS_HLA- DR0401_40,0 57,5 0,0 0,0 29, SARS_3726.2005_1 0,0 20,2 0,0 0,0 11, SARS_3726.2005_2 0,0 7,2 0,0 0,0 17, SARS_5314.2004_1 0,0 24,2 0,0 0,0 16, SARS_5314.2004_2 0,0 36,8 0,0 0,0 18, SARS_01025-8_1 0,0 27,3 0,0 0,0 12, SARS_01025-8_2 0,0 31,4 0,0 0,0 20, SARS_01026-X 0,0 58,8 0,0 0,0 16, SARS_2016.05.006 0,0 141,3 38,8 0,0 43, membrane_1 0,0 30,7 0,0 0,0 15, membrane_2 0,0 40,3 0,0 0,0 21, membrane_3 0,0 60,6 15,7 0,0 33, membrane_4 0,0 73,7 22,7 0,0 59, membrane_5 0,0 65,4 7,1 0,0 26, membrane_6 0,0 44,5 0,0 0,0 30,5 membrane_7 0,0 143,4 15,7 0,0 27,7 Spike1 0,0 134,7 6,8 0,0 33, Spike2 0,0 52,2 0,0 0,0 15,5 Spike3 0,0 38,8 0,0 0,0 17,1 Spike4 0,0 38,4 3,0 0,0 27,0 Spike5 0,0 89,3 14,6 0,0 43,9 Spike6 0,0 69,5 11,4 0,0 42,0 Spike7 0,0 67,6 0,0 0,0 11,1 Spike8 0,0 254,5 17,1 0,0 16,9 Spike9 0,0 50,9 0,0 0,0 30,4 Spike10 0,0 31,0 0,0 0,0 6,3 Spike11 0,0 26,2 0,0 0,0 11,6 Spike12 0,0 28,5 0,0 0,0 17,9 Spike13 0,0 68,2 9,8 0,0 39,1 Spike14 0,0 36,6 0,0 0,0 31,4 Spike15 0,0 32,5 0,0 0,0 10,6 83 Spike16 0,0 56,7 0,0 0,0 11,6 Spike17 0,0 58,3 0,0 0,0 19, Spike18 0,0 23,6 0,0 0,0 13,2 Spike19 0,0 29,7 0,0 0,0 11,6 Spike20 0,0 27,5 0,0 0,0 8, Spike21 0,0 29,4 1,6 0,0 21, Spike22 0,0 15,7 0,0 0,0 7, Spike23 0,0 27,8 0,0 0,0 6, Spike24 0,0 62,4 0,0 0,0 11, Spike25 0,0 55,4 0,0 0,0 14, Spike26 0,0 23,7 0,0 0,0 5, Spike27 0,0 29,6 0,0 0,0 9, Spike28 0,0 28,3 0,0 0,0 6, Spike29 0,0 31,1 0,0 0,0 7, Spike30 0,0 26,6 0,0 0,0 15, Spike31 0,0 30,0 0,0 0,0 12, Spike32 0,0 74,6 0,0 0,0 9, Spike33 0,0 98,6 0,8 0,0 20, Spike34 0,0 26,5 0,0 0,0 10, Spike35 0,0 25,3 0,0 0,0 12, Spike36 0,0 30,9 0,0 0,0 12, Spike37 0,0 63,0 0,0 0,0 8, Spike38 0,0 28,3 0,0 0,0 15, Spike39 0,0 31,1 0,0 0,0 9, Spike40 0,0 75,6 0,0 0,0 13, Spike41 0,0 118,4 17,8 0,0 37, Spike42 0,0 44,4 0,0 0,0 15, Spike43 0,0 50,0 0,0 0,0 10, Spike44 0,0 47,3 0,0 0,0 13, Spike45 0,0 76,4 5,3 0,0 8, Spike46 0,0 28,9 0,0 0,0 18, Spike47 0,0 61,5 0,0 0,0 12, 84 Spike48 0,0 62,1 0,0 0,0 16,9 Spike49 5,7 121,9 0,0 0,0 37, Spike50 0,0 95,3 0,0 0,0 17,7 Spike51 0,0 66,9 0,0 0,0 22,7 Spike52 0,0 74,0 12,1 0,0 19, Spike53 0,0 96,6 0,0 0,0 17, Spike54 0,0 70,9 0,0 0,0 14, Spike55 0,0 98,9 0,0 0,0 10, Spike56 0,0 149,0 21,3 0,0 31, Spike57 0,0 105,2 0,0 0,0 20, Spike58 0,0 50,0 0,0 0,0 5, Spike59 0,0 17,9 0,0 0,0 17, Spike60 0,0 32,5 0,0 0,0 3, Spike61 0,0 36,2 0,0 0,0 8, Spike62 0,0 49,3 0,0 0,0 8, Spike63 0,0 41,3 0,0 0,0 10, Spike64 0,0 70,5 0,0 0,0 18, Spike65 0,0 83,5 0,0 0,0 21, Spike66 0,0 33,7 0,0 0,0 4, Spike67 0,0 26,4 0,0 0,0 12, Spike68 0,0 32,9 0,0 0,0 10, Spike69 0,0 38,7 0,0 0,0 14, Spike70 0,0 31,5 0,0 0,0 11, Spike71 0,0 29,8 0,0 0,0 8, Spike72 0,0 56,3 0,0 0,0 15, Spike73 0,0 82,5 0,0 0,0 21, Spike74 0,0 38,8 0,0 0,0 9, Spike75 0,0 32,6 5,9 0,0 10, Spike76 0,0 26,0 0,0 0,0 7, Spike77 0,0 43,0 0,0 0,0 19, Spike78 0,0 28,1 0,0 0,0 11, Spike79 0,0 30,9 0,0 0,0 7, 85 Spike80 0,0 69,0 0,0 0,0 14,1 Spike81 0,0 99,1 0,0 0,0 31, Spike82 0,0 45,0 0,0 0,0 5,9 Spike83 0,0 29,6 0,0 0,0 0,0 Spike84 0,0 34,6 0,0 0,0 3, Spike85 0,0 35,7 0,0 0,0 12, nucleocapsid_1 0,0 38,7 0,0 0,0 10, nucleocapsid_2 0,0 31,4 0,0 0,0 6, nucleocapsid_3 0,0 187,2 0,0 0,0 5, nucleocapsid_4 0,0 49,7 0,0 0,0 0, nucleocapsid_5 0,0 53,1 0,0 0,0 0, nucleocapsid_6 0,0 104,9 0,0 0,0 21, nucleocapsid_7 0,0 65,4 0,0 0,0 2, nucleocapsid_8 0,0 65,4 0,0 0,0 0, nucleocapsid_9 0,0 68,3 0,0 0,0 0, nucleocapsid_10 0,0 127,7 0,0 0,0 7, nucleocapsid_11 0,0 81,9 0,0 0,0 19, nucleocapsid_12 69,0 84,7 0,0 0,0 31, nucleocapsid_13 0,0 59,6 0,0 0,0 15, nucleocapsid_14 0,0 35,8 0,0 0,0 14, nucleocapsid_15 51,9 63,6 0,0 0,0 26, nucleocapsid_16 0,0 49,8 0,0 0,0 12, nucleocapsid_17 0,0 35,1 0,0 0,0 15, nucleocapsid_18 0,0 47,8 0,0 0,0 19, nucleocapsid_19 37,1 77,5 0,0 0,0 62, nucleocapsid_20 11,6 13,1 0,0 0,0 29, nucleocapsid_21 0,0 1,1 0,0 0,0 7, nucleocapsid_22 0,0 4,8 0,0 0,0 2, nucleocapsid_23 0,0 6,1 0,0 0,0 13, nucleocapsid_24 0,0 0,6 0,0 0,0 12, nucleocapsid_25 0,0 2,4 0,0 0,0 11, nucleocapsid_26 0,0 7,4 0,0 0,0 24, 86 nucleocapsid_27 0,0 27,4 0,0 0,0 32,8 nucleocapsid_28 0,0 22,0 0,0 0,0 25, ORF8_1 14,5 44,1 0,0 0,0 0, ORF8_2 0,0 0,0 0,0 0,0 0, ORF8_3 0,0 5,0 0,0 0,0 0, ORF8_4 0,0 5,2 0,0 0,0 0, ORF8_5 0,0 10,0 0,0 0,0 0, ORF8_6 0,0 5,9 0,0 0,0 0, ORF8_7 0,0 11,0 0,0 0,0 0, ORF8_8 0,0 30,3 4,7 0,0 0, ORF8_9 0,0 79,2 0,0 0,0 1, ORF8_10 0,0 33,9 0,0 0,0 0, ORF8_11 0,0 44,3 0,0 0,0 0, ORF8_12 0,0 59,3 0,0 0,0 0, ORF8_13 0,0 47,7 0,0 0,0 0, ORF8_14 0,0 37,7 0,0 0,0 0, ORF8_15 0,0 29,5 0,0 0,0 0, ORF8_16 0,0 38,9 0,1 0,0 0, ORF8_17 80,7 105,2 0,0 0,0 0, ORF10_1 0,0 84,2 1,8 0,0 0, ORF10_2 0,0 82,2 3,7 0,0 0, ORF10_3 0,0 88,4 0,0 0,0 0, ORF10_4 0,0 88,0 0,0 0,0 0, ORF10_5 0,0 87,3 0,0 0,0 0, ORF8_A 0,0 76,7 0,0 0,0 0, ORF8_BC 0,0 76,9 0,0 0,0 7, ORF3a_AB 6,9 55,4 40,9 0,0 0, ORF3a_C 0,0 67,1 13,4 0,0 0, Virus (SARS-CoV-2) No Data No Data No Data No Data No Data OKT3 1101,0 17,8 92,5 0,0 205, OKT3 1186,7 30,3 67,5 0,0 177, 87 OKT3 No Data 11,2 97,4 0,0 128,9 OKT3 No Data 91,0 0,0 0,0 2, PHA 1033,7 17,4 0,0 0,0 0,0 PHA 1132,7 23,6 0,0 0,0 0,0 PHA No Data 26,1 0,0 0,0 0, PHA No Data 92,0 0,0 0,0 0, EBNA 0,0 23,6 0,0 0,0 1, CMV 0,0 18,0 0,0 0,0 6, M1 2,2 68,0 1,0 0,0 0, 88 Table 17 IA3:G80L-5 Signature Peptide Virus Sequence SEQ ID Potential Cross Reactive Sequence SEQ ID Protein Name Spike27 No Hits No Hits Spike28 RQIAPGQTG 260 REIAPGLTG 310 Activating molecule in BECN1-regulated autophagy protein 1 EVRQIAPGQ 261 ELRQGAPGQ 311 SUN domain-containing protein EVRQIAPGQ 261 EVRQAAPEQ 312 Protein translocase subunit SecA Protein translocase subunit SecA [Bacteroides thetaiotaomicron VPI-5482] EVRQIAPGQ 261 EVRQAAPEQ 312 Protein translocase subunit SecA [Bacteroides fragilis NCTC 9343]Spike29 No Hits No Hits Spike30 LDSKVGGNY 262 LKSKHGGNY 313 Tensin- NSNNLDSKV 263 NSYNLNSKV 314 Probable cell division protein WhiA [Clostridium botulinum A str. Hall] LDSKVGGNY 262 LGSKVGNNY 315 Uridine permease [Saccharomyces cerevisiae S288C] Spike31 YRLFRKSNL 264 YMLFRKYNL 316 THUMP domain-containing protein LYRLFRKSN 265 LWRLFRKKN 317 Protein O-linked-mannose beta-1,2-N-acetylglucosaminyltransferase 1LYRLFRKSN 265 LYNLFTKSN 318 Probable G-protein coupled receptor LYRLFRKSN 265 LYRDFRKEN 319 Zinc finger protein with KRAB and SCAN domains LYRLFRKSNL 266 LFRLFRHSNL 320 Protein transport protein sec1 [Schizosaccharomyces pombe 972h-]Spike32 STEIYQAGS 267 STQIYQAVS 321 Phospholipid-transporting ATPase ABCA DISTEIYQA 268 DISTGIYKA 322 CDK-activating kinase [Saccharomyces cerevisiae S288C] ISTEIYQAG 269 IATEIYGAG 323 Formyltetrahydrofolate synthetase [Campylobacter curvus 525.92] 89 Spike33 GFNCYFPLQS270 GFNIYFPLMS 324 FXNA-like protease [Schizosaccharomyces pombe 972h-] EGFNCYFPL 271 ENFNCMFPL 325 ABC-transporter-regulating transcription factor [Aspergillus oryzae RIB40]ORF8_5 No Hits No Hits nucleocapsid_8 FYYLGTGPE 272 FYYLGSGRE 326 Xyloside xylosyltransferase PRWYFYYLGTGPEA 273 PRWYFYYLGTGPHA 327 Human coronavirus OC PRWYFYYLGTGP 274 PRWYFYYLGTGP 274 Human coronavirus HKU SARS_2016.05.0LLNKHIDAY 275 LLYKAIDAY 328 Voltage-dependent L-type calcium channel subunit alpha-1F LLNKHIDAY 275 LLNKNIDVY 329 Menaquinone biosynthesis protein MenD [Staphylococcus aureus RF122] LNKHIDAYK 276 LPKHIDAFK 330 Methenyltetrahydrofolate cyclohydrolase [Pediococcus pentosaceus ATCC 25745]Spike2 RTQLPPAYT 277 RTQSPPVYT 331 Potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 1TQLPPAYTN 278 TQTPPAYIN 332 E3 ubiquitin-protein ligase TTCVNLTTRTQL 279 VELTTKTQL 333 Transcription termination/antitermination protein NusG [Mycoplasma pneumoniae M129]LTTRTQLPP 280 LVVRTQLPP 334 Quinic acid utilization activator [Neurospora crassa OR74A]NLTTRTQLP 281 NLTTRIALP 335 RNase Y [Helicobacter pylori 26695] Spike3 No Hits No Hits Spike15 LVRDLPQGF 282 LVQDLAQGF 336 Tryptophan--tRNA ligase, mitochondrial LVRDLPQGFS 283 LVRDLVTGFS 337 U11/U12 small nuclear ribonucleoprotein 35 kDa protein LPQGFSALE 284 LAQGFSGLE 338 UDP-N-acetylmuramate dehydrogenase [Pseudomonas fluorescens Pf0-1]Spike21 KSFTVEKGI 285 KTFTVQKGI 339 Desmoglein- 90

Claims (43)

1.CLAIMS 1. A method for in vitro determining whether an individual is likely to resist to an infection by SARS-CoV-2, comprising: (i) generating dendritic cells (DC) from monocytes obtained from said individual; (ii) loading said DC with a SARS-CoV-2 lysate or SARS-CoV-2 antigens; (iii) contacting peripheral blood lymphocytes (PBL) from said individual with the DC obtained in step (ii), in appropriate conditions to activate said PBL; (iv) following the PBL activation, measuring the expression of at least one cytokine secreted by Th1 cells, selected from the group consisting of IL-2, IFNγ and TNFa, and measuring the expression of at least one cytokine secreted by Th2 cells, selected from the group consisting of IL-5, IL-4, IL-9, IL-10 and IL-13; and (v) from the results of step (iv), assessing the Th1/Th2 polarization of SARS-CoV-2-specific memory T cell response in said individual, wherein a Th1 polarization indicates that the individual is likely to resist to an infection by SARS-CoV-2, and a Th2 polarization indicates that the individual is susceptible to an infection by SARS-CoV-2.
2. The method of claim 1, wherein in step (iv), the expressions of IL-2 and IL-are measured, and in step (v), the ratio IL2/IL-5 is calculated, wherein IL2/IL5>indicates that the individual is likely to resist to an infection by SARS-CoV-2, and IL2/IL5≤1 indicates that the individual is susceptible to an infection by SARS-CoV-
3. A method for in vitro determining whether an individual is likely to resist to an infection by SARS-CoV-2, comprising (i) incubating T lymphocytes from said individual with a mix of antigenic peptides from SARS-CoV-2, under conditions appropriate to stimulate Th1 and/or Th2 lymphocytes specific for said peptides; and (ii) assessing the presence of Th1 and/or Th2 lymphocytes; wherein the presence of Th1 lymphocytes specific for said peptides indicates that the individual is likely to resist to an infection by SARS-CoV-2, and/or the absence of Th1 lymphocytes and/or the presence of Th2 lymphocytes specific for said peptides indicates that the individual is susceptible to an infection by SARS-CoV-2. 1
4. The method of claim 3, wherein the mix of antigenic peptides comprises: - at least five peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 331 to 555 of a SARS-CoV-2 spike protein; and - at least one, preferably at least two or at least three peptides of 9 to aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-nucleocapsid protein.
5. The method of claim 3 or claim 4, wherein the mix of antigenic peptides comprises: - at least five peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 361 to 555 of a SARS-CoV-2 spike protein, wherein at least one or two of said peptides are preferably from a sequence consisting of aminoacids 361 to 495 of a SARS-CoV-2 spike protein and at least one or two of said peptides are preferably from a sequence consisting of aminoacids 466 to 555 of a SARS-CoV-2 spike protein; and - at least two, preferably at least 3 peptides of 9 to 50 aminoacids, preferably to 25 aminoacids, from a sequence consisting of aminoacids 1 to 135 of a SARS-CoV-2 spike protein.
6. The method of any of claims 3 to 5, wherein the mix of antigenic peptides further comprises: - at least one, preferably at least two or at least three peptides of 9 to aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 1 to 270 of a SARS-CoV-2 nucleocapsid protein; and/or - at least one, preferably at least two or at least three peptide of 9 to aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 331 to 419 of a SARS-CoV-2 nucleocapsid protein; and/or - one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF3a_AB protein, preferably consisting of or encompassing a sequence consisting of aminoacids 244 to 258 of said SARS-CoV-ORF3a_AB protein; and/or - at least two peptides of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 856 to 1050 of a SARS-CoV-spike protein. 1
7. The method of any of claims 3 to 6, wherein the mix of antigenic peptides further comprises: - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a sequence consisting of aminoacids 1 to 165 of a SARS-CoV-2 spike protein; and/or - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF10 protein; preferably from a sequence consisting of aminoacids 1 to 22 of a SARS-CoV-2 ORF10 protein and/or - at least one peptide of 9 to 50 aminoacids, preferably 12 to 25 aminoacids, from a SARS-CoV-2 ORF8 protein, preferably from a sequence consisting of aminoacids 1 to 36 or 99 to 121 of a SARS-CoV-2 ORF8 protein.
8. The method of any of claims 3 to 7, wherein in step (i), T lymphocytes are incubated with the mix of antigenic peptides from SARS-CoV-2 in the presence of IL-2 and IL-15; and in step (ii), the presence of Th1 lymphocytes is assessed by measuring the production of IFNγ and/or the presence of Th2 lymphocytes is assessed by measuring the production of at least one cytokine selected from IL-5, IL-4, IL-6, IL-9 IL-10 and IL-13.
9. The method of any of claims 3 to 7, wherein in step (i), T lymphocytes are incubated with the mix of antigenic peptides from SARS-CoV-2 in the presence of low doses of IL-2 or IL-15, or PMA/ionomycine, or low dose of anti CD3/anti CD28 antibodies to sensitize the TCR, in addition to IL-4 and/or anti-ILantibodies; and in step (ii), the presence of Th2 lymphocytes is assessed by measuring the production of at least one cytokine selected from IL-5, IL-9, IL-10 and IL-13.
10. The method of any of claims 3 to 9, wherein the method is performed in at least one recipient that contains a mix of peptides which are common to all known strains of SARS-CoV-2 or induce cross-reactive immunity.
11. The method of any of claims 3 to 10, wherein the mix of peptides is dispatched in several recipients for performing the method, wherein at least one recipient contains a mix of peptides which are common to all known strains of SARS-CoV-2 or induce cross-reactive immunity, and at least another recipient comprises a mix of peptides which are specific for one or more SARS-CoV-variant(s). 1
12. The method of claim 10 or claim 11, wherein detection of Th1 lymphocytes in said at least one recipient containing a mix of peptides which are common to all known strains of SARS-CoV-2 indicates that the individual is likely to resist to an infection by any SARS-CoV-2 strain.
13. The method of any of claims 3 to 12, for assessing whether an individual is likely to resist to an infection by a variant strain of SARS-CoV-2, wherein the method is performed with a mix of peptides comprising only peptides present in the proteins of said variant strain.
14. A method for monitoring the efficacy of a vaccination against SARS-CoV-2 in an individual, comprising performing the method of any of claims 1 to 13 with a biological sample from said individual.
15. Use of the method according to any one of claims 1 to 14, to monitor the efficacy of a vaccination against SARS-CoV-2 in an individual.
16. An immunogenic composition comprising, in one or several polypeptides, the epitopes present in a sequence corresponding to amino acids 331 to 525 of a SARS-CoV-2 spike protein, as well as the epitopes present in a sequence corresponding to amino acids 1 to 165 of a SARS-CoV-2 spike protein.
17. The immunogenic composition of claim 16, comprising a first polypeptide sequence comprising amino acids 331 to 525 of a SARS-CoV-2 spike protein, and a second polypeptide sequence comprising amino acids 1 to 165 of a SARS-CoV-2 spike protein, wherein said first and second polypeptide sequences are in the same polypeptide molecule or in separate polypeptides.
18. The immunogenic composition of claim 17, wherein said first polypeptide sequence consists of amino acids 331 to 525 of a SARS-CoV-2 spike protein, and/or the second polypeptide sequence consists of amino acids 1 to 165 of a SARS-CoV-2 spike protein.
19. The immunogenic composition of claim 16 or claim 17, wherein the first polypeptide sequence consists of amino acids 331 to 600 of a SARS-CoV-spike protein or a fragment thereof, and/or the second polypeptide sequence consists of amino acids 1 to 270 of a SARS-CoV-2 spike protein or a fragment thereof. 1
20. The immunogenic composition of any of claims 17 to 19, further comprising a rd polypeptide sequence comprising amino acids 1 to 270 of a SARS-CoV-nucleocapsid protein, and/or a 4th polypeptide sequence comprising amino acids 244 to 258 of a SARS-CoV-2 ORF3a_AB protein, and/or a 5th polypeptide sequence comprising amino acids 29 to 92 of a SARS-CoV-2 ORF8 protein, and/or a 6th polypeptide sequence comprising amino acids 1 to 36 of a SARS-CoV-2 ORF8 protein, and/or a 7th polypeptide sequence comprising amino acids 22 to 38 of a SARS-CoV-2 ORF10 protein, wherein said 3rd, 4th, 5th, 6th and/or 7th polypeptide sequences are in the same polypeptide molecule as the first and/or second polypeptide sequences or are in one or several separate polypeptide(s).
21. The immunogenic composition of any of claims 16 to 20, which does not comprise the peptide LVRDLPQGFSALE (SEQ ID No: 377).
22. The immunogenic composition of any of claims 16 to 21, which does not comprise the peptide DVRVVLDFI (SEQ ID No: 178).
23. The immunogenic composition of any of claims 16 to 22, which does not comprise the peptide LLNKHIDAY (SEQ ID No:275).
24. The immunogenic composition of any of claims 16 to 23, which does not comprise the peptide IELCVDEAG (SEQ ID No:305).
25. The immunogenic composition of any of claims 16 to 24, which does not comprise the peptide MKFLVFLGIITTV (SEQ ID No: 378).
26. A nucleic acid molecule encoding the polypeptides defined in any of claims to 25.
27. The nucleic acid molecule, which is a RNA molecule.
28. An immunogenic composition comprising the nucleic acid molecule of claim or claim 27.
29. The immunogenic composition of claim 28, comprising a viral vector. 1
30. A vaccine, comprising the immunogenic composition of any of claims 16 to and 28 to 29, as well as a pharmaceutically acceptable excipient and/or adjuvant.
31. The vaccine of claim 30, comprising at least one adjuvant selected from the group consisting of TLR4 agonists, TLR3 ligands/ agonists, TLR7-8 agonists and TLR9 agonists.
32. The vaccine of claim 30 or 31, comprising at least one adjuvant selected from the group consisting of lipopolysaccharides, MPL: 3-O-desacyl-4’-monophosphoryl lipid A derived from Salmonella minnesotta LPS, poly A :U, poly I :C, IMIQUIMOD, CpG DNA and CpG ODNs.
33. An immunogenic composition comprising a polypeptide comprising the sequence LDSKVGGNY (SEQ ID No: 262), or a nucleic acid encoding the same, for use in the treatment of cancer.
34. The immunogenic composition of claim 33, for use in the treatment of a cancer overexpressing Tensin-1.
35. The immunogenic composition of claim 34, for the use of claim 33 or 34, wherein said cancer is a pancreas adenocarcinoma or a colon adenocarcinoma.
36. The immunogenic composition of claim 33, for the use of claims 33 to 35, wherein said polypeptide comprises the sequence NSNNLDSKVGGNY (SEQ ID No: 379).
37. The method of any of claims 3 to 13, wherein the Th1 response is assessed using a first mix of peptides comprising at least 3, 4, 5, 6 or more peptides relevant for assessing Th1 response against SARS-CoV-2 and the Thresponse is assessed using a second mix of peptides comprising at least 3, 4, 5, 6 or more peptides relevant for assessing Th2 response against SARS-CoV-2.
38. The method of claim 37, wherein said first and second mixes of peptides are present in separate recipients/tubes. 1
39. The method of claim 37 or claim 38, wherein in step (ii) of the method, the presence of Th1 lymphocytes is assessed by measuring the production of IFNγ in the recipient comprising the first mix of peptides and the presence of Thlymphocytes is assessed by measuring the production of at least one cytokine selected from IL-5, IL-4, IL-9, IL-10 and IL-13 (preferable IL-5) in the recipient comprising the second mix of peptides.
40. The method of any of claims 3 to 13 and 37 to 39, wherein the absence of Thafter incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 5and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein indicates that the individual is susceptible to an infection by SARS-CoV-2 and its variants.
41. The method of any of claims 3 to 13 and 37 to 40, wherein the presence of a Th2 response combined to the absence or weak presence of Th1 after incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 521 and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein indicates that the individual is susceptible to an infection by SARS-CoV-2 and its variants.
42. The method of any of claims 3 to 13 and 37 to 41, wherein the presence of a Th1 response after incubation of the T lymphocytes with a mix of peptides covering a sequence comprising amino acids 331 to 525 and/or amino acids 329 to 521 and/or amino acids 391 to 555 of a SARS-CoV-2 spike protein indicates that the individual is likely to resist to an infection by SARS-CoV-and its variants.
43. The method of any of claims 3 to 13 and 37 to 42, wherein the presence of a Th1 response after incubation of the T lymphocytes with a mix of peptides comprised in a sequence consisting of amino acids 1 to 135 of a SARS-CoV-spike protein indicates that the individual is likely to resist to an infection by SARS-CoV-2 and its variants, only if a Th1 response has also been obtained against another part of the virus, e.g. against peptides of the nucleocapsid. Dr. Hadassa Waterman Patent Attorney G.E. Ehrlich (1995) Ltd. 35 HaMasger Street Sky Tower, 13th Floor Tel Aviv 6721407
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