WO2024047441A1 - Method for monitoring tumor burden in subjects during therapeutic intervention - Google Patents
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- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
- G01N33/57488—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving compounds identifable in body fluids
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- G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
Definitions
- the present invention belongs to the field of protein biomarkers for diagnosis and discloses a method for monitoring tumor burden in subjects during therapeutic intervention, in order to assess their response to the treatment regimen.
- the tumor burden can be defined as the tumor load in the body, i.e., the number of cancer cells, the size of a tumor, or the amount of cancer. Since it has long been considered a major prognostic indicator in oncological practice, the improved performance to track changes in tumor burden would be important for assessing whether a patient is responding to the therapy regimen or not.
- Pancreatic ductal adenocarcinoma was the seventh cause of cancer-related fatalities globally in 2020 1 .
- SEER End Results Program
- the incidence of PDAC has increased over the past seven years 3 , being projected to be the second biggest cause of cancer-related deaths by 2030 4 .
- the majority of metastatic patients continue to have median survival outcomes of less than one year 5, 6 , with less than 30 % of patients eligible for second line chemotherapy 7 .
- Imaging techniques based on the Response Evaluation Criteria in Solid Tumors (RECIST) criteria 8 which evaluate the number and size of tumor lesions over the course of treatment, remain gold standards for determining treatment response during chemotherapy.
- RECIST Response Evaluation Criteria in Solid Tumors
- these techniques have several drawbacks, including a lack of precision in detecting small tumors and an inability to differentiate between benign inflammatory and malignant lesions. This also includes the necessity to arbitrarily target lesions to evaluate the evolution of the disease in accordance with the treatment, and the usual delay between the imagiological response and the real-time detection of differences in tumor dimensions 9 .
- the evaluation solely based on dimensions doesn’t consider changes in tumor attenuation, nor does it discriminate viable cells from non-viable ones, thus complicating the measurement of treatment response 10 .
- CA19.9 Carbohydrate antigen 19.9
- Serological markers like Carbohydrate antigen 19.9 are widely utilized to supplement the ability of RECIST to assess PDAC treatment response 11 .
- CA19.9 When elevated at the start of treatment, CA19.9 demonstrates dependable outcomes in conjunction with imaging evaluation 12 .
- the CA19.9 evaluation in PDAC patients has limitations since it is not expressed in 5-20 % of patients 12, 13 .
- false positives are common, especially in patients with obstructive lesions of the biliary tract, which may affect up to 70 % of PDAC patients 14 .
- EVs are nanovesicles that contain all active biomolecules, including nucleic acids, lipids, and proteins 19 .
- EVs are critical mediators of cell-to-cell communication under physiological and pathological settings 20 .
- Studies using EVs as cancer biomarkers usually focus on specific disease timepoints, disregarding potential changes in the molecular composition and population dynamics of EVs during the course of the disease, and investigating the utility of EVs exclusively for prognosis or diagnosis 21 .
- studies of EV biomarkers for follow up of metastatic PDAC patients have been limited by challenges involving their dismal prognosis, which complicates patient recruitment for longer longitudinal studies.
- IgG + plasma EVs obtained from metastatic PDAC patients who were monitored throughout their treatment and evolution of the disease were characterized.
- a population of plasma EVs bound to IgG was identified, which is connected with the diagnosis of PDAC and the treatment response of PDAC patients (including those without CA19.9 expression).
- IgG + plasma EVs may represent a new tool for enhancing the efficacy of chemotherapeutic treatments in patients with PDAC by improving detection of therapy response and resistance.
- Document EP2542696B1 discloses a method for detecting cancer in a subject in need thereof, comprising (a) identifying a biosignature of a population of vesicles isolated from a body fluid of the subject; and (b) comparing the biosignature to a value of reference.
- the biosignature comprises the presence or level of a particular protein (which varies according to the type of cancer to be analyzed) and its identification makes it possible to verify the presence of the disease or the effectiveness of the treatment used.
- the vesicle population with a specific biosignature can be detected using a binding agent for the biomarker, such as immunoglobulin molecules or immunologically active portions of immunoglobulin molecules.
- a binding agent for the biomarker such as immunoglobulin molecules or immunologically active portions of immunoglobulin molecules.
- the method is performed in vitro, and the vesicles are tested directly from the sample without previous isolation, purification, or concentration.
- document EP2176665B1 describes a method for the diagnosis and prognosis of pancreatic cancer, which makes it possible to monitor the progression of the disease and/or the therapeutic efficacy of an anticancer treatment, which comprises the steps of (a) collecting a biological sample obtained from a subject with cancer at a first time point; isolating microvesicles from this first sample and measuring an oncogenic microRNA in the microvesicles obtained from the first sample; and (b) collecting a second biological sample obtained from a subject with cancer at a second time point, the second time point occurring after the first time point, isolating microvesicles from this second sample, and measuring the oncogenic microRNA in the microvesicles obtained from the second sample.
- the first time point occurs before the subject has received anti-cancer treatment and the subsequent time points occur after or while the subject has received said treatment.
- An increase in the amount of an EV population carrying a specific protein measured from a sample compared to the proportion of EVs carrying the same specific protein obtained from previous sample collections indicates that the cancer has progressed or that the individual is unresponsive to treatment.
- a decrease in the amount of an EV population carrying a specific protein measured from a sample compared to the proportion of EVs carrying the same specific protein obtained from previous sample collections indicates that the cancer has regressed or that the individual is responding to treatment.
- document WO2022046576A1 relates to nucleic acid products as PDAC biomarkers and methods of detecting the same in a biological sample from a subject. Methods of diagnosis, prognosis and/or treatment of said disease are also described, wherein a characteristic in relation to the treatment of a patient, a patient's response to a treatment and/or their survival is determined or predicted based on the detection of one or more of the nucleic acid biomarkers. Instead of measuring the overall levels of cancer-related biomolecules, the present invention focuses in monitoring a specific population of EVs, identified by specific proteins, linked with cancer response to therapy.
- biomarkers described in this invention correspond, in particular, to gene expression signatures and immune signatures of the tumor microenvironment. Quantitative results can be generated by quantifying the proportion of EVs carrying a specific protein of interest in relation to the total EV present in the studied biofluid.
- document EP2718721A1 describes the use of specific biomolecules to isolate populations of EVs and then evaluate the bulk content of these isolates as a method to (i) identify the stage or progression of a disease, (ii) select candidate treatment regimens for the disease; and (iii) determine the effectiveness of the treatment.
- the disease is cancer, such as pancreatic cancer.
- Biomarkers are selected from nucleic acids, proteins and circulating structures such as vesicles and nucleic acid-protein complexes. Vesicles can be analyzed using one or more antibodies specific for one or more antigens present on the vesicle, where the antigens can be immunoglobulin molecules or immunologically active portions of immunoglobulin molecules.
- the novelty and inventiveness of the present invention are in the fact that the sample obtained from the subject is processed for qualitative and quantitative determination of the population of vesicle-associated proteins, wherein the determination of the proportion of EVs that express IgG are a marker of response to therapy in patients with cancer, more specifically, PDAC.
- the data processing consists of monitoring the levels (percentages) of EVs that express IgG throughout the treatment, in order to assess whether or not these subjects are responding to therapy (through reduction, stabilization, or increased plasma levels of IgG + EVs over time).
- the object of the present invention is a method for monitoring tumor burden in subjects during therapeutic intervention, wherein the method comprises the steps of:
- the percentage of EVs that express IgG is a marker of response to treatment in patients with cancer, wherein the levels of IgG + EVs decrease in case of response to treatment and increase in case of non-response to treatment.
- PDAC pancreatic ductal adenocarcinoma
- imaging evaluation cannot detect small lesions and is not an immediate indicator of the tumor's status, as there is a delay between the progression of the disease and its imagiological identification 8, 10 .
- IgG + EVs plasma extracellular vesicles
- EVs have the potential to carry biomarkers for liquid biopsies, in both oncologic and non-oncologic diseases 39 , due to their abundance in body fluids. EVs produced by tumor cells can populate and alter the composition of biofluids. As a result, the identification of molecular modifications in EVs associated with tumor profile has been utilized to identify putative cancer biomarkers 19, 40 , including the diagnosis of PDAC 41 . The majority of these studies, however, have focused on the differential expression of specific nucleic acids and proteins in bulk EV samples for diagnosis or prognosis, using single collections from each patient 42 . Also, failure to distinguish between EV populations may obscure real differences between experimental groups. In cancer patients, longitudinal studies like ours evaluating the response to chemotherapy in a single individual are still scarce 43, 44 .
- the present invention discloses a method for monitoring pancreatic ductal adenocarcinoma (PDAC) in subjects during therapeutic intervention, in order to assess their response to the treatment regimen.
- PDAC pancreatic ductal adenocarcinoma
- IgG attaches to the surface of EVs in PDAC patients via an interaction with the tumor antigen MAGE B1, and this process is independent of IgG plasma levels and the inflammatory status of the patient.
- IgG + EVs can detect therapy response in a subset of individuals with PDAC who lack the standard PDAC marker CA19.9.
- emerging markers of therapy response in PDAC should assist in separating PDAC patients into new groups, hence aiding the development of tailored, more effective treatments.
- NTA Nanoparticle Tracking Analysis
- A samples isolated from healthy controls
- B PDAC patients at diagnosis that did not respond
- C responded
- D is a panel depicting the presence status of the indicated proteins in isolated EVs
- E is representative Western blots of EV-markers CD9, CD81, Alix and non-EV markers GM130 and Calnexin for EV samples isolated from healthy control and PDAC plasma (H1975 cell lysate was used as a control).
- FIG. 1 shows (A) Volcano plot representing the identified proteins in MS (comparison between patients (PDAC) and healthy control samples) and (B) Volcano plot representing the identified proteins in mass spectrometry (comparison between patients that are nonresponders and responders to chemotherapy).
- the green points represent proteins significantly regulated after correction for multiple testing.
- the blue points represent proteins significantly regulated without correction for multiple testing.
- Black points represent proteins with insignificant regulation.
- E ROC curve for the IgG + EV to discriminate response in patients with metastatic PDAC. Data was obtained from patients 15, 23, 34, 49, 63, 69, 70, 73, and 94 (D); and patients 8, 10, 15, 21, 22, 23, 34, 49, 66, and 73 (E).
- NLR neutrophil/lymphocyte ratio
- the object of the present invention is a method for monitoring tumor burden in subjects during therapeutic intervention, in order to assess their response to therapy.
- the method comprises the steps of:
- step (a) the blood sample is collected from a liquid biopsy of the tumor.
- a blood sample was collected every time the patient came to the Clinical Centre for a follow-up visit (usually every 1 to 2 months).
- the clinical data is registered in a database stored in a computing device.
- the clinical data is at least one of the groups consisting of magnetic resonance imaging (MRI) / Computer Tomography (CT) or conventional biomarkers of the disease to be tested.
- MRI magnetic resonance imaging
- CT Computer Tomography
- biomarker is CA19.9.
- step (c) in order to prepare the blood sample for the analysis of the protein content of plasma EVs, such blood sample is centrifuged twice in a temperature range from 4 to 10 oC and a centrifugal force in the range from 500 g to 3000 g for a time range from 10 to 20 minutes.
- the plasma-derived EV samples obtained may be aliquoted and stored in a temperature range from -80 to 4 oC.
- step (c) the plasma-derived EV sample is analyzed by Nanoparticle Tracking Analysis (NTA), in order to determine particle concentration and size distribution, and Vesicle Flow Cytometry, in order to measure the proportion of EVs bound to IgG.
- NTA Nanoparticle Tracking Analysis
- Vsicle Flow Cytometry in order to measure the proportion of EVs bound to IgG.
- the plasma-derived EV samples are previously diluted in filtered phosphate-buffered saline (PBS) to achieve a concentration within the range for optimal NTA analysis.
- PBS filtered phosphate-buffered saline
- the plasma-derived EV samples are submitted to two incubation substeps to stain EVs prior to the Vesicle Flow Cytometry analysis.
- the EVs are stained with anti-IgG in PBS and incubated for a time range from 1 to 3 h in a temperature range from 20 to 37 °C.
- the antibody-stained sample is then incubated with an EV specific fluorescent dye for a time range from 1 to 2 h in a temperature range from 20 to 37 °C.
- the EV specific fluorescent dye is Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE).
- SEC Size Exclusion Chromatography
- the method of the invention allows the analysis of EVs directly in plasma, without the need of a centrifugation step of the plasma samples for the isolation of EVs.
- step (d) the treatment of the data is performed by a central processing unit and consists of monitoring the levels (percentages) of EVs that express IgG throughout the treatment of the patients, in order to assess whether or not these patients are responding to the therapy (through reduction, stabilization, or increased plasma levels of IgG + EVs over time).
- the method of the present invention allows investigating the percentage of EVs that express IgG as a marker of response to therapy, wherein the levels of IgG + EVs decrease in case of response to treatment and increase in case of non-response to treatment.
- Treatment proposals were done at the multidisciplinary tumor board. Patients were treated in a sequence of chemotherapy with the following approved regimens: association of 5-fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX); association of gemcitabine and nab-paclitaxel; association of 5-fluorouracil and liposomal irinotecan; or single gemcitabine.
- the decision on the choice of the chemotherapy regimen was at the discretion of the treating oncologist. Demographic and clinical information from the patients, including neutrophil-to-lymphocyte ratio and C-Reactive Protein levels, was collected. Treatment response was classified based on the imaging response based on RECIST v1.1 criteria 8 .
- Timepoints were selected as follows: timepoint I (pretreatment) was collected before the beginning of a new chemotherapy regimen, and timepoint II (posttreatment) at the time of either the best imaging response (if tumor responded with chemotherapy) or the worst (if not responding to chemotherapy).
- timepoint II posttreatment
- the same patient can be a responder at one point of treatment and a nonresponder at another.
- the first samples of one patient that met these criteria were selected until the calculated minimum number of total required samples was obtained.
- Plasma samples from patients and healthy donors were collected in a 9 mL Vacuette NV EDTA K3 tube and centrifuged twice at 10 degrees Celsius (500 g for 10 minutes and 3 000 g for 20 minutes). Prior to analysis, plasma samples were aliquoted and stored at -80oC. A protocol previously described involving sequential ultracentrifugation combined with sucrose cushion was used to purify EVs 23 .
- EV samples were analyzed by Nanoparticle Tracking Analysis (NTA) using a NanoSight NS300 equipped with red laser (638 nm) to determine particle concentration and size distribution (Malvern Panalytical, United Kingdom). Samples were pre-diluted in filtered PBS to achieve a concentration within the range for optimal NTA analysis. Video acquisitions were performed at 25oC using a camera level of 16, and a threshold between 4 and 6. Five videos of 30 s with 10-50 particles per frame were captured per sample. The total protein content of EV samples was determined using the PierceTM BCA Protein Assay Kit (Thermo Fisher Scientific).
- plasma-derived EV samples from PDAC patients were used. Four patients that responded and four patients that displayed disease progression were selected. For each patient, samples were collected at diagnosis and after treatment response evaluation, totaling sixteen samples. In parallel, five plasma-derived EV samples from healthy controls were also compared to eight PDAC patients at diagnosis.
- the EV solution containing sodium dodecyl sulfate (SDS) and dithiothreitol (DTT) was loaded onto filtering columns and washed exhaustively with 8 M urea in HEPES buffer 24 . Proteins were reduced with DTT and alkylated with IAA. Protein digestion was performed by overnight digestion with trypsin sequencing grade (Promega).
- Mass spectra were acquired in positive ion mode applying automatic data-dependent switch between one Orbitrap survey MS scan in the mass range of 350–1200 m/z followed by higher-energy collision dissociation (HCD) fragmentation and Orbitrap detection of fragment ions with a cycle time of 2 s between each master scan.
- MS and MSMS settings maximum injection times were set to “Auto”, normalized collision energy was 30%, ion selection threshold for MSMS analysis was 10,000 counts, and dynamic exclusion of sequenced ions was set to 30 s.
- TBS-T TBS with 0.1% Tween-20
- secondary antibodies for 1 h at RT. Incubation was followed by three additional washes with TBS-T, 5 min each. Blots were imaged using the Odyssey Infrared Imaging System (LI-COR Biosciences). The detailed list of primary and secondary antibodies used is provided in Table 1 above.
- Table 1 List of primary and secondary antibodies used for Western blotting Primary Antibodies Antibody Manufacturer Catalog no Dilution/concentration CD81 Santa Cruz Biotechnology sc-166029 1:50 CD9 Cell Signaling #13174 1:1000 Alix Sigma Aldrich SAB4200476-200UL 1.25 ug/mL Calnexin Abcam ab22595 1:2000 GM130 Abcam ab52649 1:1000 Secondary Antibodies Antibody Manufacturer Catalog no Dilution Goat anti-rabbit IgG IRDye 800CW LI-COR Biosciences 926-32211 1:5000 Goat anti-mouse IgG IRDye 800CW LI-COR Biosciences 926-32210 1:5000
- Flow cytometry analysis of plasma EVs was performed as described by our group 29 .
- a volume of plasma containing 2 ⁇ 10 9 particles was used for staining with 0.5 ⁇ L of anti-IgG in PBS, in a final volume of 40 ⁇ L, and incubated for 1 h at 37°C.
- the antibody-stained sample was then incubated with Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE – Thermo Fisher Scientific LTI C34554, MA, United States) to a final concentration of 25.6 ⁇ M, for 90 min at 37°C.
- SEC Size Exclusion Chromatography
- EV-enriched fractions #7, #8, and #9 were then pooled (total of 1500 ⁇ L) and retrieved for analysis with the flow cytometer Apogee A60-Micro-Plus (Apogee Flow Systems, United Kingdom) configured as described in Table 2. For all subsequent analyses, quadrant thresholds were established with unstained and single-stained extracellular vesicles (with CFSE or with anti-IgG) ( ).
- Table 2 Cytometer configuration and laser power Channel number Short Channel Name Full Channel Name Optical Filter Name Laser Wavelength Laser Power PMT Voltage Ch1 405-SALS Small Angle Light Scatter 405 nm 200 mW 400 V Ch2 405-LALS Large Angle Light Scatter 405 nm 200 mW 400 V Ch3 405-Gm Green Fluorescence BP-525/50 405 nm 200 mW 500 V Ch4 405-Org Orange Fluorescence LWP-590/35 405 nm 200 mW 500 V Ch5 APC Red Fluorescence BP-676/36 638 nm 150 mW 550 V Ch6 CFSE Green Fluorescence BP-525/50 488 nm 200 mW 525 V Ch7 PE Orange Fluorescence BP-575/30 488 nm 200 mW 500 V Ch8 488-Red Red Fluorescence BP-676/36 488 nm 200 mW 500 V Ch9 488-DRed Deep Red Fluorescence
- biotinylated surface proteins of EVs were collected using streptavidin magnetic beads 30 (DynabeadsTM MyOneTM Streptavidin C, Invitrogen, 65001), and then detached from the beads (deionized water, 70oC) 31 .
- streptavidin magnetic beads 30 DynabeadsTM MyOneTM Streptavidin C, Invitrogen, 65001
- surface EV proteins that were associated with IgG were co-immunoprecipitated using magnetic beads (DynabeadsTM Protein G for Immunoprecipitation, Invitrogen, 10003D) conjugated with anti-human IgG antibody (Goat anti-Human IgG F(ab')2 Secondary Antibody, Invitrogen, 31122), then eluted and analyzed by MS.
- Sample size was based on previous liquid biopsy studies 32 .
- the analysis involves 155 observations from 30 different situations (15 responders x 15 nonresponders). Experiments were not randomized. The researchers were blinded to allocation during experiments and outcome assessment. The response evaluation to the treatment was previously done by a different researcher. Error bars in graphical data represent means ⁇ standard errors of the means (SEM). Normality and homogeneity of variances from the analyzed variables were tested with Shapiro-Wilk test and Bartlett or Levene tests, respectively. If data were parametric, Student’s t test (two populations) were used. If data were not parametric, Wilcoxon or Mann-Whitney tests were performed.
- the size distribution and concentration of plasma EVs isolated from patients and healthy controls were characterized. Proteins frequently present or absent in small EVs were measured in our samples ( ). MS analysis of plasma EV samples from five healthy controls and sixteen samples from eight PDAC patients was performed, both at the time of diagnosis and after treatment. Four of these eight patients were considered chemotherapy responders, as tumor shrinkage was observed between the diagnosis and treatment timepoints. In contrast, based on the observed imaging progression of the disease between the two time points, the remaining four patients corresponded to nonresponders to chemotherapy. For the MS analysis, the same amounts of protein (20 ⁇ g) and concentrations (0.5 ⁇ g/ ⁇ L) were utilized.
- Protein expression analysis revealed that 102 distinct proteins exhibited statistically significant differences between PDAC patients and healthy controls, 59 of which were upregulated in PDAC patients. Of these, the presence of multiple IgG fragments ( Figure 4A, Table 3) was identified. In fact, the functional analysis of proteins significantly upregulated or downregulated in EVs from PDAC patients (Responders and Nonresponders) and as compared to healthy controls revealed enrichment in proteins associated with humoral immune response and complement activation, among others ( ).
- a new marker should: a) be consistent, independent of the treatment of choice; b) be able to identify differences in patients with and without CA19.9 expression; and c) be able to predict treatment response in comparison to the imagiological evaluation, in order to reinforce the maintenance of applied treatment or to suspend futile treatments early 33, 34 .
- IgG + EVs may derive, at least in part, from alterations in the inflammatory status of immune cells during the progression of PDAC.
- the neutrophil/lymphocyte ratio (NLR) is a clinical marker of inflammation calculated as the quotient of the absolute neutrophil and lymphocyte counts 36 .
- NLR neutrophil/lymphocyte ratio
- IgG fragments were detected in both healthy controls and PDAC patients.
- soluble proteins alpha-2-macroglobulin
- cell surface receptors i.e., Glutamine Receptor
- cytoskeletal proteins i.e., Keratin
- cytoplasmic proteins were detected in both groups (e.g. Chloride intracellular channel protein 4, Golgi integral membrane protein 4, Chondroitin sulfate synthase 3 and Protein Argonaute 2).
- IgG was bound to Melanoma associated antigen B1 (MAGE B1) in the EVs of PDAC patients, in addition to IgG fragments and Albumin.
- MAGE B1 Melanoma associated antigen B1
- MAGE B1 is a well-known PDAC antigen 38 , suggesting that the population of IgG + EVs described here is the consequence of an interaction between tumoral antigens on the surface of EVs released by tumor cells and IgG in circulation (Table 5).
- the analysis of EV bulks is an effective method for identifying molecules of interest (e.g., proteins, lipids, and RNA) in EV liquid biopsies.
- MS analysis of EVs in bulk was used to identify IgG as a possible EV marker of therapeutic response in PDAC patients.
- failure to distinguish between EV populations may obscure real differences between experimental groups.
- the implementation of EV biomarkers in clinical practice is hindered by the laborious and time-consuming isolation and analysis protocols commonly employed for EVs.
- a vesicle flow cytometry protocol was used 29 . By not requiring EV isolation prior to analysis, the processing time is reduced from >24 hours to 4 hours. Therefore, the use of vesicle flow cytometry has the potential to facilitate the clinical evaluation of IgG + EVs.
- IgG + EV populations may be utilized in the follow-up of PDAC patients, including those who lack CA19.9 expression. Due to the absence of this established marker, these patients rely solely on imaging evaluations to determine their clinical response to chemotherapy; therefore, a new reliable marker would represent a substantial improvement in their care.
- cytokines/chemokines 52 proteins that frequently display quantitative changes in cancer patients, such as cytokines/chemokines 52 , extracellular matrix proteins 53 , coagulation factors 54 , complement factors 55 , immunoglobulins 56 and albumin 57 , can interact with EVs after their release and change their composition 51 .
- MAGE B1 was identified as an EV surface ligand of IgG in 8 different PDAC patients, further study, including methods other than MS, will be necessary to validate this finding in larger cohorts of PDAC patients.
- immunoglobulins Igs were traditionally thought to be exclusively produced by B-lineage cells, recent studies have shown that these molecules can also be produced by a large diversity of tumor types 21 , including PDAC 35, 60, 61 .
- MAGE B1 is a tumor antigen found in a variety of tumor types, including melanoma and tumors of epithelial origin, such as breast, colorectal carcinoma, lung, and pancreatic 38, 62-66 .
- MAGE is identified as an antigen normally expressed by the placenta and male germ cells in cancerous testes. It is expressed in 47 percent of pancreatic tumors 67 , giving cells that express it a survival advantage 68 and negatively correlating with prognosis and patient survival 67, 69 .
- MAGE B1 was identified as one of the proteins found exclusively in EVs from PDAC patients.
- IgG + EV is independent of the availability of circulating IgG.
- this may be the result of elevated levels of tumor EV secretion and/or enhanced packaging of tumor antigens (such as MAGE B1) in PDAC EVs.
- tumor antigens such as MAGE B1
- this process may result in tumor-directed IgG absorption by tumor EVs and, as a result, may contribute to tumor immune-escape 45 and the chronic inflammatory state observed in metastatic PDAC patients 70 .
- the binding of IgGs to EVs could also affect the efficacy of targeted therapies (e.g., immunotherapies). Additional re-search will be required to fully comprehend the aforementioned implications.
- pancreas 40 Li, X., R. Ni, J. Chen, Z. Liu, M. Xiao, F. Jiang and C. Lu. "The presence of ighg1 in human pancreatic carcinomas is associated with immune evasion mechanisms.” Pancreas 40 (2011): 753-61. 10.1097/MPA.0b013e318213d51b. https://www.ncbi.nlm.nih.gov/pubmed/21654544.
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Abstract
The present invention discloses a method for monitoring tumor burden in subjects during therapeutic intervention, in order to assess their response to the treatment regimen. More specifically, the method consists of performing a liquid biopsy based on extracellular vesicles (EVs) for the qualitative and quantitative determination of the population of vesicle-associated proteins. The percentage of EVs that express IgG is a marker of response to treatment, wherein the levels of IgG+EVs decrease in case of response and increase in case of non-response.
Description
The present invention belongs to the field of protein biomarkers for diagnosis and discloses a method for monitoring tumor burden in subjects during therapeutic intervention, in order to assess their response to the treatment regimen.
The tumor burden can be defined as the tumor load in the body, i.e., the number of cancer cells, the size of a tumor, or the amount of cancer. Since it has long been considered a major prognostic indicator in oncological practice, the improved performance to track changes in tumor burden would be important for assessing whether a patient is responding to the therapy regimen or not.
Pancreatic ductal adenocarcinoma (PDAC) was the seventh cause of cancer-related fatalities globally in 20201. As reported by the Surveillance, Epidemiology, and End Results Program (SEER)2, the incidence of PDAC has increased over the past seven years3, being projected to be the second biggest cause of cancer-related deaths by 20304. The majority of metastatic patients continue to have median survival outcomes of less than one year5, 6, with less than 30 % of patients eligible for second line chemotherapy7.
Imaging techniques based on the Response Evaluation Criteria in Solid Tumors (RECIST) criteria8, which evaluate the number and size of tumor lesions over the course of treatment, remain gold standards for determining treatment response during chemotherapy. However, these techniques have several drawbacks, including a lack of precision in detecting small tumors and an inability to differentiate between benign inflammatory and malignant lesions. This also includes the necessity to arbitrarily target lesions to evaluate the evolution of the disease in accordance with the treatment, and the usual delay between the imagiological response and the real-time detection of differences in tumor dimensions9. In addition, the evaluation solely based on dimensions doesn’t consider changes in tumor attenuation, nor does it discriminate viable cells from non-viable ones, thus complicating the measurement of treatment response10.
Serological markers like Carbohydrate antigen 19.9 (CA19.9) are widely utilized to supplement the ability of RECIST to assess PDAC treatment response11. When elevated at the start of treatment, CA19.9 demonstrates dependable outcomes in conjunction with imaging evaluation12. However, the CA19.9 evaluation in PDAC patients has limitations since it is not expressed in 5-20 % of patients12, 13. In addition, false positives are common, especially in patients with obstructive lesions of the biliary tract, which may affect up to 70 % of PDAC patients14.
Due to the aforementioned constraints, it is of the utmost need to develop additional techniques for assessing the therapy response of PDAC. Studies with potential new response indicators, including circulating tumor cells and circulating tumor DNA, have previously been conducted to uncover new readouts15. This also includes recent findings that plasma extracellular vesicles (EVs) can detect incidence16, predict progression17, and locate18 metastases in PDAC patients. However, the majority of current research lacks longitudinal information on response to therapy and clinical follow-up.
EVs are nanovesicles that contain all active biomolecules, including nucleic acids, lipids, and proteins19. EVs are critical mediators of cell-to-cell communication under physiological and pathological settings20. Studies using EVs as cancer biomarkers usually focus on specific disease timepoints, disregarding potential changes in the molecular composition and population dynamics of EVs during the course of the disease, and investigating the utility of EVs exclusively for prognosis or diagnosis21. Besides, studies of EV biomarkers for follow up of metastatic PDAC patients have been limited by challenges involving their dismal prognosis, which complicates patient recruitment for longer longitudinal studies.
In the present invention, EVs obtained from metastatic PDAC patients who were monitored throughout their treatment and evolution of the disease were characterized. A population of plasma EVs bound to IgG (IgG+ EVs) was identified, which is connected with the diagnosis of PDAC and the treatment response of PDAC patients (including those without CA19.9 expression). Thus, a longitudinal examination of IgG+ plasma EVs may represent a new tool for enhancing the efficacy of chemotherapeutic treatments in patients with PDAC by improving detection of therapy response and resistance.
Some documents of the state of the art mention the expression of proteins in EVs as a potential marker of cancer diseases. Differently from the present invention, which identifies a protein biomarker to monitor a population of EVs linked with response to therapy in patients already diagnosed with cancer, Document EP2542696B1 discloses a method for detecting cancer in a subject in need thereof, comprising (a) identifying a biosignature of a population of vesicles isolated from a body fluid of the subject; and (b) comparing the biosignature to a value of reference.
The biosignature comprises the presence or level of a particular protein (which varies according to the type of cancer to be analyzed) and its identification makes it possible to verify the presence of the disease or the effectiveness of the treatment used.
The vesicle population with a specific biosignature can be detected using a binding agent for the biomarker, such as immunoglobulin molecules or immunologically active portions of immunoglobulin molecules. The method is performed in vitro, and the vesicles are tested directly from the sample without previous isolation, purification, or concentration.
Differently from the present invention, which utilizes a protein biomarker to identify an EV population linked with cancer response to therapy, document EP2176665B1 describes a method for the diagnosis and prognosis of pancreatic cancer, which makes it possible to monitor the progression of the disease and/or the therapeutic efficacy of an anticancer treatment, which comprises the steps of (a) collecting a biological sample obtained from a subject with cancer at a first time point; isolating microvesicles from this first sample and measuring an oncogenic microRNA in the microvesicles obtained from the first sample; and (b) collecting a second biological sample obtained from a subject with cancer at a second time point, the second time point occurring after the first time point, isolating microvesicles from this second sample, and measuring the oncogenic microRNA in the microvesicles obtained from the second sample.
The first time point occurs before the subject has received anti-cancer treatment and the subsequent time points occur after or while the subject has received said treatment. An increase in the amount of an EV population carrying a specific protein measured from a sample compared to the proportion of EVs carrying the same specific protein obtained from previous sample collections indicates that the cancer has progressed or that the individual is unresponsive to treatment. Likewise, a decrease in the amount of an EV population carrying a specific protein measured from a sample compared to the proportion of EVs carrying the same specific protein obtained from previous sample collections indicates that the cancer has regressed or that the individual is responding to treatment.
Differently from the present invention, which utilizes a protein biomarker to identify an EV population linked with cancer response to therapy, document WO2022046576A1 relates to nucleic acid products as PDAC biomarkers and methods of detecting the same in a biological sample from a subject. Methods of diagnosis, prognosis and/or treatment of said disease are also described, wherein a characteristic in relation to the treatment of a patient, a patient's response to a treatment and/or their survival is determined or predicted based on the detection of one or more of the nucleic acid biomarkers. Instead of measuring the overall levels of cancer-related biomolecules, the present invention focuses in monitoring a specific population of EVs, identified by specific proteins, linked with cancer response to therapy.
The biomarkers described in this invention correspond, in particular, to gene expression signatures and immune signatures of the tumor microenvironment. Quantitative results can be generated by quantifying the proportion of EVs carrying a specific protein of interest in relation to the total EV present in the studied biofluid.
Differently from the present invention, which utilizes a protein biomarker to monitor the proportion of an EV population linked with cancer response to therapy in biofluids, document EP2718721A1 describes the use of specific biomolecules to isolate populations of EVs and then evaluate the bulk content of these isolates as a method to (i) identify the stage or progression of a disease, (ii) select candidate treatment regimens for the disease; and (iii) determine the effectiveness of the treatment. Preferably, the disease is cancer, such as pancreatic cancer.
Biomarkers are selected from nucleic acids, proteins and circulating structures such as vesicles and nucleic acid-protein complexes. Vesicles can be analyzed using one or more antibodies specific for one or more antigens present on the vesicle, where the antigens can be immunoglobulin molecules or immunologically active portions of immunoglobulin molecules.
Although these documents mention the expression of proteins in EVs as a potential marker of cancer, the novelty and inventiveness of the present invention are in the fact that the sample obtained from the subject is processed for qualitative and quantitative determination of the population of vesicle-associated proteins, wherein the determination of the proportion of EVs that express IgG are a marker of response to therapy in patients with cancer, more specifically, PDAC.
The data processing consists of monitoring the levels (percentages) of EVs that express IgG throughout the treatment, in order to assess whether or not these subjects are responding to therapy (through reduction, stabilization, or increased plasma levels of IgG+EVs over time).
The object of the present invention is a method for monitoring tumor burden in subjects during therapeutic intervention, wherein the method comprises the steps of:
- collection of a blood sample from the subject;
- recording of the clinical data;
- centrifuging the blood sample in a centrifuge and processing the plasma sample for extracellular vesicle (EV) staining followed by qualitative and quantitative determination of the population of vesicle-associated proteins; and
- data processing to assess the subject’s response to therapy.
The percentage of EVs that express IgG is a marker of response to treatment in patients with cancer, wherein the levels of IgG+EVs decrease in case of response to treatment and increase in case of non-response to treatment.
Currently, the assessment of treatment response in patients with metastatic pancreatic ductal adenocarcinoma (PDAC) relies mainly on CA19.9 and imaging evaluations, both of which have limitations. 5 - 20 % of PDAC patients lack CA19.9, and false-positive elevations are associated with biliary tree inflammation or infections12, 13.
On the other hand, imaging evaluation cannot detect small lesions and is not an immediate indicator of the tumor's status, as there is a delay between the progression of the disease and its imagiological identification8, 10. By characterizing a population of plasma extracellular vesicles (IgG+ EVs) that correlates with the treatment response status of metastatic PDAC patients, a potentially new tool to complement treatment response evaluation is described.
EVs have the potential to carry biomarkers for liquid biopsies, in both oncologic and non-oncologic diseases39, due to their abundance in body fluids. EVs produced by tumor cells can populate and alter the composition of biofluids. As a result, the identification of molecular modifications in EVs associated with tumor profile has been utilized to identify putative cancer biomarkers19, 40, including the diagnosis of PDAC41. The majority of these studies, however, have focused on the differential expression of specific nucleic acids and proteins in bulk EV samples for diagnosis or prognosis, using single collections from each patient42. Also, failure to distinguish between EV populations may obscure real differences between experimental groups. In cancer patients, longitudinal studies like ours evaluating the response to chemotherapy in a single individual are still scarce43, 44.
The present invention discloses a method for monitoring pancreatic ductal adenocarcinoma (PDAC) in subjects during therapeutic intervention, in order to assess their response to the treatment regimen.
IgG attaches to the surface of EVs in PDAC patients via an interaction with the tumor antigen MAGE B1, and this process is independent of IgG plasma levels and the inflammatory status of the patient.
A longitudinal population analysis of plasma EVs revealed that EVs bound to IgG increase during disease progression and decrease when patients react to chemotherapy. Importantly, IgG+ EVs can detect therapy response in a subset of individuals with PDAC who lack the standard PDAC marker CA19.9.
These findings not only have the potential to expand the current monitoring options for PDAC metastasis, but also represent a promising new tool for identifying effective treatments and indicating alternate treatments in the event of disease progression.
In addition, emerging markers of therapy response in PDAC, such as IgG+ EVs, should assist in separating PDAC patients into new groups, hence aiding the development of tailored, more effective treatments.
In order to promote an understanding of the principles according to the modalities of the present invention, reference will be made to the embodiments illustrated in the figures and the language used to describe them.
It should also be understood that there is no intention to limit the scope of the invention to the content of the figures and that modifications to the inventive features illustrated herein, as well as additional applications of the principles and embodiments illustrated, which would normally occur to a person skilled in the art having the possession of this description, are considered within the scope of the claimed invention.
The object of the present invention is a method for monitoring tumor burden in subjects during therapeutic intervention, in order to assess their response to therapy.
More specifically, the method comprises the steps of:
- collection of a blood sample from the subject;
- recording of the clinical data;
- centrifuging the blood sample in a centrifuge and processing the plasma sample for extracellular vesicle (EV) staining followed by qualitative and quantitative determination of the population of vesicle-associated proteins; and
- data processing to assess the subject’s response to therapy.
In step (a), the blood sample is collected from a liquid biopsy of the tumor. In order to perform the monitoring of the disease, a blood sample was collected every time the patient came to the Clinical Centre for a follow-up visit (usually every 1 to 2 months).
In step (b), for each blood sample collection, the clinical data is registered in a database stored in a computing device. In a specific embodiment of the invention, the clinical data is at least one of the groups consisting of magnetic resonance imaging (MRI) / Computer Tomography (CT) or conventional biomarkers of the disease to be tested. In a preferred embodiment of the invention, the disease is pancreatic ductal adenocarcinoma (PDAC), and the biomarker is CA19.9.
In step (c), in order to prepare the blood sample for the analysis of the protein content of plasma EVs, such blood sample is centrifuged twice in a temperature range from 4 to 10 ºC and a centrifugal force in the range from 500 g to 3000 g for a time range from 10 to 20 minutes. Prior to analysis, the plasma-derived EV samples obtained may be aliquoted and stored in a temperature range from -80 to 4 ºC.
In step (c), the plasma-derived EV sample is analyzed by Nanoparticle Tracking Analysis (NTA), in order to determine particle concentration and size distribution, and Vesicle Flow Cytometry, in order to measure the proportion of EVs bound to IgG.
For the NTA, the plasma-derived EV samples are previously diluted in filtered phosphate-buffered saline (PBS) to achieve a concentration within the range for optimal NTA analysis.
The plasma-derived EV samples are submitted to two incubation substeps to stain EVs prior to the Vesicle Flow Cytometry analysis. In the first incubation substep, the EVs are stained with anti-IgG in PBS and incubated for a time range from 1 to 3 h in a temperature range from 20 to 37 °C. In the second incubation step, the antibody-stained sample is then incubated with an EV specific fluorescent dye for a time range from 1 to 2 h in a temperature range from 20 to 37 °C. In a preferred embodiment of the invention, the EV specific fluorescent dye is Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE).
For the removal of unbound EV specific fluorescent dye and antibody, Size Exclusion Chromatography (SEC) columns were used. The EV-enriched fractions are pooled and retrieved for analysis with the flow cytometer.
The method of the invention allows the analysis of EVs directly in plasma, without the need of a centrifugation step of the plasma samples for the isolation of EVs.
At last, in step (d), the treatment of the data is performed by a central processing unit and consists of monitoring the levels (percentages) of EVs that express IgG throughout the treatment of the patients, in order to assess whether or not these patients are responding to the therapy (through reduction, stabilization, or increased plasma levels of IgG+EVs over time).
More specifically, the method of the present invention allows investigating the percentage of EVs that express IgG as a marker of response to therapy, wherein the levels of IgG+EVs decrease in case of response to treatment and increase in case of non-response to treatment.
Examples
Materials and Methods
Patients and Controls
Patients were eligible to participate if they had a confirmed histological or cytological diagnosis of metastatic PDAC, according to the 8th edition of AJCC Cancer Staging22, and were able to receive chemotherapy. Samples from healthy individuals were collected from voluntary donors at Champalimaud Clinical Center and Champalimaud Research. Exclusion criteria were previous diagnosis of other tumors or inflammatory diseases. Written informed consent was obtained from both patients and control individuals, and samples were deidentified for confidentiality. All the procedures were conducted in accordance with the Helsinki Declaration and its amendments, with the approval of the Ethical Committees of Nova Medical School and of the Champalimaud Foundation.
Treatment proposals were done at the multidisciplinary tumor board. Patients were treated in a sequence of chemotherapy with the following approved regimens: association of 5-fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX); association of gemcitabine and nab-paclitaxel; association of 5-fluorouracil and liposomal irinotecan; or single gemcitabine. The decision on the choice of the chemotherapy regimen was at the discretion of the treating oncologist. Demographic and clinical information from the patients, including neutrophil-to-lymphocyte ratio and C-Reactive Protein levels, was collected. Treatment response was classified based on the imaging response based on RECIST v1.1 criteria8. Timepoints were selected as follows: timepoint I (pretreatment) was collected before the beginning of a new chemotherapy regimen, and timepoint II (posttreatment) at the time of either the best imaging response (if tumor responded with chemotherapy) or the worst (if not responding to chemotherapy). The same patient can be a responder at one point of treatment and a nonresponder at another. The first samples of one patient that met these criteria were selected until the calculated minimum number of total required samples was obtained.
Five of the 19 patients were used exclusively for the proteomic analysis of EVs, as there were no samples left for the subsequent experiments. The remaining 14 patients, in a total of 155 plasma samples, were studied by vesicles flow cytometry. provides information on the metastatic profile, treatment regimens, and sample collection times. For the control group, the same exclusion criteria (previous oncological diagnosis or previous inflammatory diseases) were applied. The group included 21 individuals (ten males and eleven females) with a mean age of 47 years old (minimum of 25 years; maximum of 85 years).
Purification and characterization of EVs from plasma
Blood samples from patients and healthy donors were collected in a 9 mL Vacuette NV EDTA K3 tube and centrifuged twice at 10 degrees Celsius (500 g for 10 minutes and 3 000 g for 20 minutes). Prior to analysis, plasma samples were aliquoted and stored at -80oC. A protocol previously described involving sequential ultracentrifugation combined with sucrose cushion was used to purify EVs23.
All EV samples were analyzed by Nanoparticle Tracking Analysis (NTA) using a NanoSight NS300 equipped with red laser (638 nm) to determine particle concentration and size distribution (Malvern Panalytical, United Kingdom). Samples were pre-diluted in filtered PBS to achieve a concentration within the range for optimal NTA analysis. Video acquisitions were performed at 25ºC using a camera level of 16, and a threshold between 4 and 6. Five videos of 30 s with 10-50 particles per frame were captured per sample. The total protein content of EV samples was determined using the PierceTM BCA Protein Assay Kit (Thermo Fisher Scientific).
Characterization of EV protein composition by Mass Spectrometry (MS)
For evaluation by MS, plasma-derived EV samples from PDAC patients were used. Four patients that responded and four patients that displayed disease progression were selected. For each patient, samples were collected at diagnosis and after treatment response evaluation, totaling sixteen samples. In parallel, five plasma-derived EV samples from healthy controls were also compared to eight PDAC patients at diagnosis.
The EV solution containing sodium dodecyl sulfate (SDS) and dithiothreitol (DTT) was loaded onto filtering columns and washed exhaustively with 8 M urea in HEPES buffer24. Proteins were reduced with DTT and alkylated with IAA. Protein digestion was performed by overnight digestion with trypsin sequencing grade (Promega).
Peptides samples were analyzed by nano-LC-MSMS (Dionex RSLCnano 3000) coupled to an Exploris 480 Orbitrap mass spectrometer (Thermo Scientific, Hemel Hempstead, UK) virtually as previously described25. Briefly, samples were loaded (flowrate 5 µL per minute for 6 minutes) onto a custom made fused capillary pre-column (2 cm length, 360 µm OD, 75 µm ID) packed with ReproSil Pur C18 5.0 µm resin (Dr. Maish, Ammerbuch-Entringen, Germany) followed by the separation on a custom made fused capillary column (25 cm length, 360 µm outer diameter, 75 µm inner diameter) packed with ReproSil Pur C18 1.9-µm resin (Dr. Maish, Ammerbuch-Entringen, Germany) using a flow of 250 nL per minute. Gradient was from 89% A (0.1% formic acid) to 32% B (0.1% formic acid in 80% acetonitrile) over 56 min. Mass spectra were acquired in positive ion mode applying automatic data-dependent switch between one Orbitrap survey MS scan in the mass range of 350–1200 m/z followed by higher-energy collision dissociation (HCD) fragmentation and Orbitrap detection of fragment ions with a cycle time of 2 s between each master scan. MS and MSMS settings: maximum injection times were set to “Auto”, normalized collision energy was 30%, ion selection threshold for MSMS analysis was 10,000 counts, and dynamic exclusion of sequenced ions was set to 30 s.
Data obtained from 46 LC-MS runs of 21 subjects and 32 LC-MS runs of IgG bound proteins were searched using VEMS26, 27 and MaxQuant28. A standard proteome database from UniProt (3AUP000005640), in which common contaminants were included, was also searched. Trypsin cleavage, allowing a maximum of four missed cleavages, was used. Carbamidomethyl cysteine was included as fixed modification. Methionine oxidation and N-terminal protein acetylation were included as variable modifications; 5 ppm mass accuracy was specified for precursor ions and 0.01 m/z for fragment ions. The FDR for protein identification was set at 1% for peptide and protein identifications. No restriction was applied to the minimal peptide length for VEMS search. Identified proteins were divided into evidence groups as defined27. Functional pathway analysis was performed with STRING (string-db.org).
Western blotting
Western blotting was used to assess the presence of EV and non-EV protein markers. Equal protein amounts of EV samples were mixed with 4X Laemmli buffer (Bio-Rad), denatured for 5 min at 95°C, and loaded onto 4-20% Mini-PROTEAN TGX Stain-Free Protein Gels (Bio-Rad). SDS-PAGE was run for 1.5 h at 90 V and then proteins were transferred to nitrocellulose membranes (Cytiva) at 100 V for 1 h. Membranes were blocked with LI-COR Intercept Blocking Buffer (LI-COR Biosciences) for 1 h at RT. Blocked membranes were incubated overnight at 4°C with primary antibodies diluted in LI-COR blocking buffer with 0.1% Tween-20. Membranes were washed with TBS-T (TBS with 0.1% Tween-20) three times for 5 min and then incubated with secondary antibodies for 1 h at RT. Incubation was followed by three additional washes with TBS-T, 5 min each. Blots were imaged using the Odyssey Infrared Imaging System (LI-COR Biosciences). The detailed list of primary and secondary antibodies used is provided in Table 1 above.
Table 1 – List of primary and secondary antibodies used for Western blotting
Primary Antibodies | |||
Antibody | Manufacturer | Catalog no | Dilution/concentration |
CD81 | Santa Cruz Biotechnology | sc-166029 | 1:50 |
CD9 | Cell Signaling | #13174 | 1:1000 |
Alix | Sigma Aldrich | SAB4200476-200UL | 1.25 ug/mL |
Calnexin | Abcam | ab22595 | 1:2000 |
GM130 | Abcam | ab52649 | 1:1000 |
Secondary Antibodies | |||
Antibody | Manufacturer | Catalog no | Dilution |
Goat anti-rabbit IgG IRDye 800CW | LI-COR Biosciences | 926-32211 | 1:5000 |
Goat anti-mouse IgG IRDye 800CW | LI-COR Biosciences | 926-32210 | 1:5000 |
Analysis of IgG
+
EV population by vesicle flow cytometry
Flow cytometry analysis of plasma EVs was performed as described by our group29. A volume of plasma containing 2 × 109 particles was used for staining with 0.5 μL of anti-IgG in PBS, in a final volume of 40 μL, and incubated for 1 h at 37°C. The antibody-stained sample was then incubated with Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE – Thermo Fisher Scientific LTI C34554, MA, United States) to a final concentration of 25.6 μM, for 90 min at 37°C. For the removal of unbound CFSE and antibody, Size Exclusion Chromatography (SEC) columns (iZON qEV original columns SP1, United Kingdom) were used. EV-enriched fractions #7, #8, and #9 were then pooled (total of 1500 μL) and retrieved for analysis with the flow cytometer Apogee A60-Micro-Plus (Apogee Flow Systems, United Kingdom) configured as described in Table 2. For all subsequent analyses, quadrant thresholds were established with unstained and single-stained extracellular vesicles (with CFSE or with anti-IgG) ( ).
Internal controls across assays were performed as previously described29. The acquired data was exported and analyzed with FlowJo software v10.4.2 (FlowJo LLC, United States).
Table 2 – Cytometer configuration and laser power
Channel number | Short Channel Name | Full Channel Name | Optical Filter Name | Laser Wavelength | Laser Power | PMT Voltage |
Ch1 | 405-SALS | Small Angle Light Scatter | 405 nm | 200 mW | 400 V | |
Ch2 | 405-LALS | Large Angle Light Scatter | 405 nm | 200 mW | 400 V | |
Ch3 | 405-Gm | Green Fluorescence | BP-525/50 | 405 nm | 200 mW | 500 V |
Ch4 | 405-Org | Orange Fluorescence | LWP-590/35 | 405 nm | 200 mW | 500 V |
Ch5 | APC | Red Fluorescence | BP-676/36 | 638 nm | 150 mW | 550 V |
Ch6 | CFSE | Green Fluorescence | BP-525/50 | 488 nm | 200 mW | 525 V |
Ch7 | PE | Orange Fluorescence | BP-575/30 | 488 nm | 200 mW | 500 V |
Ch8 | 488-Red | Red Fluorescence | BP-676/36 | 488 nm | 200 mW | 500 V |
Ch9 | 488-DRed | Deep Red Fluorescence | LWP-740 | 488 nm | 200 mW | 500 V |
Total plasma immunoglobulin G quantification
For the quantification of the plasma IgG, samples were processed using the nephelometry method (BNProSpec – Synlab, Portugal). Reference values for healthy controls were 700 - 1 600 mg/dL.
Identification of EV surface proteins associated with IgG
To identify which surface proteins of EVs bind to IgG, 200 μg of EVs isolated from 8 PDAC patients and 8 healthy controls were first biotinylated (EZ-Link™ Sulfo-NHS-SS-Biotin, Thermo Scientific, 21331) and then lysed using 0.5% NP-40 lysis buffer (150 mM NaCl, 10 mM Tris-HCl pH 7.5, 0.5 mM EDTA, 0.5% NP-40). Next, the biotinylated surface proteins of EVs were collected using streptavidin magnetic beads30 (Dynabeads™ MyOne™ Streptavidin C, Invitrogen, 65001), and then detached from the beads (deionized water, 70ºC)31. After separation, surface EV proteins that were associated with IgG were co-immunoprecipitated using magnetic beads (Dynabeads™ Protein G for Immunoprecipitation, Invitrogen, 10003D) conjugated with anti-human IgG antibody (Goat anti-Human IgG F(ab')2 Secondary Antibody, Invitrogen, 31122), then eluted and analyzed by MS.
Statistical analysis
Sample size was based on previous liquid biopsy studies32. The analysis involves 155 observations from 30 different situations (15 responders x 15 nonresponders). Experiments were not randomized. The researchers were blinded to allocation during experiments and outcome assessment. The response evaluation to the treatment was previously done by a different researcher. Error bars in graphical data represent means ± standard errors of the means (SEM). Normality and homogeneity of variances from the analyzed variables were tested with Shapiro-Wilk test and Bartlett or Levene tests, respectively. If data were parametric, Student’s t test (two populations) were used. If data were not parametric, Wilcoxon or Mann-Whitney tests were performed. For ROC analysis, values were obtained from the division of IgG+EVs and CA19.9 readings after treatment by those before treatment in each studied point, as previously described11. Statistical packages used were R v.4.0.2. For all evaluations, a P-value under 0.05 was considered statistically significant and the null hypothesis was rejected. Graphical design was performed with the GraphPad Prism software (GraphPad software)
Results
Identification of possible EV markers for PDAC diagnosis and therapeutic response
The size distribution and concentration of plasma EVs isolated from patients and healthy controls were characterized. Proteins frequently present or absent in small EVs were measured in our samples ( ). MS analysis of plasma EV samples from five healthy controls and sixteen samples from eight PDAC patients was performed, both at the time of diagnosis and after treatment. Four of these eight patients were considered chemotherapy responders, as tumor shrinkage was observed between the diagnosis and treatment timepoints. In contrast, based on the observed imaging progression of the disease between the two time points, the remaining four patients corresponded to nonresponders to chemotherapy. For the MS analysis, the same amounts of protein (20 μg) and concentrations (0.5 μg/μL) were utilized.
Protein expression analysis revealed that 102 distinct proteins exhibited statistically significant differences between PDAC patients and healthy controls, 59 of which were upregulated in PDAC patients. Of these, the presence of multiple IgG fragments (Figure 4A, Table 3) was identified. In fact, the functional analysis of proteins significantly upregulated or downregulated in EVs from PDAC patients (Responders and Nonresponders) and as compared to healthy controls revealed enrichment in proteins associated with humoral immune response and complement activation, among others ( ).
Table 3 – EV proteins upregulated in patients with PDAC (vs. healthy controls)
Protein IDs | Gene names | Mean Healthy Controls | Mean PDAC | logFC | P.Value |
P02675 | FGB | 30,80916 | 32,63287 | 1,823711 | 1,7E-15 |
P01591 | IGJ | 31,04684 | 29,11787 | -1,92898 | 1,71E-12 |
Q16610;Q16610-4;Q16610-2;Q16610-3 | ECM1 | 22,3285 | 24,74706 | 2,418563 | 5,83E-10 |
P01871;P01871-2 | IGHM | 32,80839 | 31,13976 | -1,66863 | 3,11E-09 |
P02679 | FGG | 31,73688 | 32,79369 | 1,056811 | 5,31E-09 |
P07360 | C8G | 24,25857 | 25,95475 | 1,69618 | 1,28E-08 |
Q9Y2I7 | PIKFYVE | 8.610452 | 18,488365 | 9,877913 | 5,23E-08 |
P08603;P08603-2 | CFH | 25,70408 | 26,9523 | 1,24822 | 8,16E-08 |
P02751;P02751-8;P02751-3;P02751-15 | FN1 | 29,12809 | 30,96719 | 1,839091 | 8,28E-08 |
O75636;O75636-2 | FCN3 | 27,6463 | 30,25062 | 2,604322 | 1,07E-07 |
P12111-4;P12111-2;P12111;P12111-3;P12111-5 | COL6A3 | 0.7664544 | 13,3798081 | 12,61335 | 1,14E-07 |
Q9C0K7-3;Q9C0K7-2;Q9C0K7 | STRADB | 6.21537 | 19,08732 | 12,87195 | 1,86E-07 |
P81605;P81605-2 | DCD | 15,62981 | 1.59704 | -14,0328 | 2,21E-07 |
P00488;P16452-3;P16452;P16452-2 | F13A1 | 23,53023 | 25,2402 | 1,709968 | 2,47E-07 |
A0A0B4J1V6 | IGHV3-73 | 24,99557 | 23,20821 | -1,78736 | 3,07E-07 |
P09871 | C1S | 22,88309 | 23,99478 | 1,111685 | 3,33E-07 |
P02679-2 | FGG | 13,1101 | 21,87546 | 8,765356 | 6,49E-07 |
O43866 | CD5L | 29,42484 | 27,78712 | -1,63772 | 8,76E-07 |
Q08830 | FGL1 | 13,01631 | 21,4914 | 8,475092 | 9,83E-07 |
P0DOY3 | 32,86217 | 31,9975 | -0,86467 | 1,03E-06 | |
P01709 | 27,85825 | 25,97132 | -1,88692 | 1,71E-06 | |
A0A0B4J1V0 | IGHV3-15 | 25,76245 | 24,63909 | -1,12337 | 2,45E-06 |
P00451;P00451-2 | F8 | 18,60007 | 21,25979 | 2,659721 | 3,93E-06 |
P07358 | C8B | 23,55035 | 24,45246 | 0,902108 | 5,32E-06 |
P01011;P01011-2 | SERPINA3 | 24,59445 | 25,81344 | 1,218999 | 1E-05 |
P01042 | KNG1 | 22,39664 | 23,79217 | 1,395532 | 1,05E-05 |
O14791;O14791-2;O14791-3 | APOL1 | 26,07611 | 24,37361 | -1,7025 | 1,76E-05 |
P04275;P04275-2 | VWF | 27,3174 | 29,24253 | 1,925138 | 1,9E-05 |
P04196 | HRG | 24,01787 | 25,45884 | 1,440968 | 2,94E-05 |
P12109 | COL6A1 | 5.053083 | 15,624026 | 10,57094 | 3,88E-05 |
P01780 | 29,81985 | 28,87501 | -0,94484 | 6,6E-05 | |
A0A087WW87;P01614 | IGKV2-40 | 28,98482 | 28,20821 | -0,77661 | 9,96E-05 |
P06312 | IGKV4-1 | 27,12003 | 26,34662 | -0,77341 | 0,00014 |
P04211 | 23,414648 | 9.843152 | -13,5715 | 0,000152 | |
Q08380 | LGALS3BP | 27,12358 | 25,96748 | -1,1561 | 0,000168 |
P13671 | C6 | 22,07315 | 23,13764 | 1,064495 | 0,000171 |
P10909-4;P10909;P10909-5;P10909-2;P10909-3 | CLU | 26,44996 | 27,21772 | 0,767758 | 0,000203 |
A0M8Q6 | IGLC7 | 16,343175 | 4.559787 | -11,7834 | 0,000234 |
P02792 | FTL | 23,44187 | 26,07389 | 2,632021 | 0,000249 |
Q4LDE5;Q4LDE5-4;Q4LDE5-3;Q4LDE5-2 | SVEP1 | 4.153104 | 14,13788 | 9,984777 | 0,000271 |
Q9HCU4 | CELSR2 | 7.209845 | 18,779373 | 11,56953 | 0,000376 |
Q14520-2;Q14520 | HABP2 | 9.420802 | 18,345494 | 8,924692 | 0,000449 |
Q9Y6R7 | FCGBP | 22,3186 | 20,91387 | -1,40473 | 0,000479 |
Q9NZT1 | CALML5 | 15,381387 | 4.785034 | -10,5964 | 0,000542 |
Q08554-2;Q08554 | DSC1 | 12,67823 | 3.226449 | -9,45178 | 0,000723 |
Q96IY4;Q96IY4-2 | CPB2 | 9.124999 | 18,288738 | 9,163739 | 0,000772 |
P01009;P01009-2;P01009-3;P20848 | SERPINA1 | 27,45175 | 28,67493 | 1,223177 | 0,000823 |
A0A0C4DH68 | IGKV2-24 | 27,98671 | 27,01923 | -0,96748 | 0,00084 |
P02743 | APCS | 26,49926 | 27,12377 | 0,624511 | 0,000918 |
O43166 | SIPA1L1 | 3,611292 | 0 | -3,61129 | 0,001353 |
P01859 | IGHG2 | 28,50515 | 29,53058 | 1,025437 | 0,001748 |
Q01469 | FABP5 | 13,333104 | 3.547731 | -9,78537 | 0,001785 |
Q562R1 | ACTBL2 | 4,454414 | 0 | -4,45441 | 0,001804 |
A0A0A0MRZ9 | IGLV5-52 | 4,580166 | 0 | -4,58017 | 0,001869 |
P01860 | IGHG3 | 28,57457 | 29,43901 | 0,86444 | 0,002166 |
P02763 | ORM1 | 23,88044 | 25,18618 | 1,30574 | 0,002263 |
P29622 | SERPINA4 | 15,58681 | 20,29616 | 4,709354 | 0,002959 |
O00189 | AP4M1 | 8.074653 | 16,858605 | 8,783952 | 0,003489 |
P07357 | C8A | 24,73622 | 25,25004 | 0,513816 | 0,004064 |
P01594;P01593 | 23,88627 | 24,80415 | 0,91788 | 0,004506 | |
Q15582 | TGFBI | 5.345572 | 13,679386 | 8,333814 | 0,005173 |
P98160 | HSPG2 | 8.859966 | 15,662051 | 6,802085 | 0,005736 |
A2NJV5;A0A075B6S2;A0A0A0MRZ7 | IGKV A18;IGKV2D-29;IGKV2D-26 | 6,2640694 | 0,5281823 | -5,73589 | 0,006043 |
P00748 | F12 | 21,33945 | 22,1381 | 0,798658 | 0,006085 |
P22792 | CPN2 | 22,25886 | 22,8205 | 0,561642 | 0,006173 |
P11021 | HSPA5 | 3.720965 | 11,713255 | 7,992289 | 0,006826 |
P01876 | IGHA1 | 31,13867 | 30,24995 | -0,88872 | 0,006911 |
Q92496-2;Q92496;Q92496-3 | CFHR4 | 2.42436 | 11,03821 | 8,613846 | 0,007766 |
A0A075B6I1 | IGLV4-60 | 13,87167 | 5.185394 | -8,68628 | 0,010051 |
P01703 | 17,37782 | 23,23569 | 5,857872 | 0,010649 | |
P18428 | LBP | 11,47416 | 18,31519 | 6,841032 | 0,011323 |
Q8NI99 | ANGPTL6 | 11,526017 | 4.144387 | -7,38163 | 0,011906 |
A0A0B4J1U7 | IGHV6-1 | 22,59996 | 26,62302 | 4,023052 | 0,012004 |
Q9BXR6 | CFHR5 | 5.800607 | 13,338935 | 7,538328 | 0,014154 |
P02751-10;P02751-13 | FN1 | 9.087818 | 16,69571 | 7,607892 | 0,01441 |
P02790 | HPX | 25,28332 | 26,11439 | 0,831076 | 0,014443 |
P21980-2;P21980;P21980-3 | TGM2 | 4,2720915 | 0,4457934 | -3,8263 | 0,014565 |
P02746 | C1QB | 27,56949 | 28,01983 | 0,450336 | 0,019773 |
P02760 | AMBP | 24,33717 | 24,93431 | 0,597142 | 0,020355 |
P01701 | 27,48918 | 26,60877 | -0,88041 | 0,021183 | |
P01766 | 24,45966 | 17,99343 | -6,46623 | 0,023374 | |
P01019 | AGT | 23,4802 | 22,67968 | -0,80053 | 0,023513 |
A0A0G2JS06 | 25,3019 | 19,47542 | -5,82649 | 0,024552 | |
P01704 | 19,9328 | 25,27153 | 5,338733 | 0,024827 | |
Q5T749 | KPRP | 4,4687764 | 0,5660902 | -3,90269 | 0,024872 |
O00187;O00187-2 | MASP2 | 19,93343 | 20,97891 | 1,04548 | 0,026433 |
Q03591 | CFHR1 | 23,1884 | 23,76836 | 0,579961 | 0,02717 |
P11217-2;P11217;P06737-2;P11216;P06737 | PYGM | 4,6574862 | 0,6082011 | -4,04929 | 0,027593 |
P07225 | PROS1 | 25,57112 | 25,99843 | 0,427312 | 0,029207 |
Q12805-5;Q12805-2;Q12805-4;Q12805-3;Q12805 | EFEMP1 | 2,296374 | 8,973493 | 6,67712 | 0,029245 |
A0A075B6H9 | IGLV4-69 | 25,56016 | 20,4878 | -5,07236 | 0,029928 |
P01715 | 19,30839 | 11,32053 | -7,98786 | 0,031146 | |
Q02413;Q02413-2 | DSG1 | 3,6552677 | 0,5459463 | -3,10932 | 0,036858 |
Q66K66 | TMEM198 | 20,92864 | 23,50407 | 2,575437 | 0,038233 |
P08473 | MME | 15,310028 | 8.574814 | -6,73521 | 0,038239 |
P68133;P68032;P63267;P62736;P63267-2 | ACTA1;ACTC1;ACTG2;ACTA2 | 7.430236 | 13,875415 | 6,44518 | 0,040955 |
A0A0C4DH24 | IGKV6-21 | 24,16357 | 18,66946 | -5,4941 | 0,041297 |
P01817 | 12,696209 | 5.607219 | -7,08899 | 0,042827 | |
P15144 | ANPEP | 20,31834 | 14,37981 | -5,93853 | 0,045148 |
P62987;P62979;P0CG47;P0CG48 | UBA52;RPS27A;UBB;UBC | 19,56519 | 12,92859 | -6,63661 | 0,046162 |
A0A075B6S6 | IGKV2D-30 | 12,474057 | 5.802547 | -6,67151 | 0,048532 |
P08519;Q16609 | LPA | 5.945479 | 12,500058 | 6,554579 | 0,049001 |
It was also an objective to identify treatment response indicators. By comparing EVs isolated from PDAC patients who responded to therapy with those who did not, 43 proteins that exhibited statistically significant differences between responders and nonresponders were identified, with 24 of these upregulated in nonresponders (Figure 4B, Table 4). It was found that 16 of the upregulated proteins in patients who did not respond to chemotherapy were IgG fragments. As a result, it was chosen to investigate further whether the presence of IgG in populations of plasma EVs is indeed associated with PDAC diagnosis and therapeutic response.
Table 4 – EV proteins upregulated in nonresponders PDAC patients (vs. responders)
Protein IDs | Gene names | Mean Non-Responders | Mean Responders | logFC | P.Value |
A0A0C4DH72;A0A0C4DH73;P01611 | IGKV1-6 | 15,060969 | 3.574371 | -11,4866 | 0,000489 |
P04432;P01597 | 14,692537 | 3.558026 | -11,1345 | 0,000562 | |
P01817 | 10,90292 | 0.00000 | -10,9029 | 0,000293 | |
A0A0C4DH68 | IGKV2-24 | 26,58469 | 27,47934 | 0,894657 | 0,000201 |
P02746 | C1QB | 27,77124 | 28,28304 | 0,511799 | 0,001447 |
P01714 | 25,10489 | 26,84546 | 1,740563 | 0,00226 | |
P15814;P15814-2 | IGLL1 | 8,060513 | 0 | -8,06051 | 0,002832 |
Q08554-2;Q08554 | DSC1 | 0 | 6,642689 | 6,642689 | 0,004575 |
A0A075B6S5;A0A0C4DH69 | IGKV1-27 | 15,14843 | 5.662179 | -9,48625 | 0,004863 |
P62987;P62979;P0CG47;P0CG48 | UBA52;RPS27A;UBB;UBC | 8.622959 | 17,487488 | 8,864529 | 0,007196 |
P15144 | ANPEP | 10,49458 | 18,49358 | 7,998998 | 0,009811 |
A0A0B4J1V0 | IGHV3-15 | 24,3923 | 24,90039 | 0,508095 | 0,009961 |
Q9NZP8 | C1RL | 9,544 | 2,343031 | -7,20097 | 0,010317 |
A0A0A0MT36 | IGKV6D-21 | 10,839119 | 2.553621 | -8,2855 | 0,013266 |
P07357 | C8A | 25,08541 | 25,42435 | 0,338941 | 0,013604 |
Q13103 | SPP2 | 9,603383 | 2,31008 | -7,2933 | 0,014323 |
Q9BXR6 | CFHR5 | 16,619122 | 9.865795 | -6,75333 | 0,017651 |
Q8TCG1-2;Q8TCG1 | KIAA1524 | 8,173923 | 1,876418 | -6,2975 | 0,020795 |
P08637;O75015 | FCGR3A | 11,79168 | 18,71712 | 6,925439 | 0,021632 |
Q9BWP8-8;Q9BWP8-7;Q9BWP8-6;Q9BWP8-5 | COLEC11 | 12,04857 | 4.62706 | -7,42151 | 0,023107 |
P01857 | IGHG1 | 32,56523 | 31,99845 | -0,56677 | 0,02629 |
P03952;P20718 | KLKB1 | 23,64847 | 23,94836 | 0,299895 | 0,026916 |
P13164;Q01629;Q01628 | IFITM1;IFITM2;IFITM3 | 0 | 5,501942 | 5,501942 | 0,027497 |
P05106-2;P05106-3;P05106 | ITGB3 | 0 | 3,959515 | 3,959515 | 0,027508 |
P02745 | C1QA | 27,34568 | 27,7409 | 0,395215 | 0,02757 |
A0A0C4DH43;P01814 | 23,72722 | 17,35704 | -6,37018 | 0,028112 | |
A0A0A0MS15 | IGHV3-49 | 23,7816 | 22,93867 | -0,84293 | 0,028814 |
P07225 | PROS1 | 25,81825 | 26,18921 | 0,370953 | 0,028895 |
P04278-4;P04278-2;P04278-3;P04278;P04278-5 | SHBG | 13,2751 | 6.543573 | -6,73153 | 0,029683 |
P08670;P17661;Q16352;P07197-2 | VIM | 0 | 4,58408 | 4,58408 | 0,029827 |
P02747 | C1QC | 28,01889 | 28,39234 | 0,373451 | 0,030901 |
P23083 | 25,56806 | 26,25761 | 0,689546 | 0,031442 | |
P28074-3;P28074 | PSMB5 | 8,442728 | 2,336585 | -6,10614 | 0,03599 |
P04430 | 21,55277 | 16,68508 | -4,8677 | 0,036212 | |
A0A087WSX0 | IGLV5-45 | 5,619149 | 0 | -5,61915 | 0,037874 |
P01699 | 4,512501 | 0 | -4,5125 | 0,037909 | |
P27169 | PON1 | 23,04364 | 23,63591 | 0,592268 | 0,040998 |
A0A0C4DH29 | IGHV1-3 | 21,04053 | 15,33251 | -5,70801 | 0,042131 |
A0A075B6I0 | IGLV8-61 | 25,2758 | 19,73274 | -5,54307 | 0,04525 |
A0A075B6Q5 | IGHV3-64 | 18,17808 | 11,41315 | -6,76493 | 0,047306 |
Q01469 | FABP5 | 1,009046 | 6,235751 | 5,226705 | 0,04767 |
P01861 | IGHG4 | 27,21168 | 26,56055 | -0,65113 | 0,048619 |
P00739;P00739-2 | HPR | 26,29785 | 25,7406 | -0,55725 | 0,049185 |
Evaluation of IgG
+
EVs as possible markers of PDAC treatment response
In accordance with the MS findings, vesicle flow cytometry revealed that metastatic PDAC patients have a larger population of IgG+ EVs compared to healthy control donors (Figure 6A), suggesting that IgG+ EVs may be a useful diagnostic marker for advanced PDAC disease. Next, it was examined whether these IgG+ EV populations could be used to determine whether a patient is responding to chemotherapy or not.
At and after diagnosis, prospective clinical information, CT data, serum levels of CA19.9, hemograms, and serial whole-blood results were collected from patients with stage IV PDAC. To be considered suitable in clinical practice for the care of metastatic PDAC patients, a new marker should: a) be consistent, independent of the treatment of choice; b) be able to identify differences in patients with and without CA19.9 expression; and c) be able to predict treatment response in comparison to the imagiological evaluation, in order to reinforce the maintenance of applied treatment or to suspend futile treatments early33, 34.
Keeping this in mind, the proportion of IgG+ EVs in the plasma of multiple patients who had received at least two lines of chemotherapy (FOLFIRINOX - first line; Gemcitabine/nabpaclitaxel - second line) was analyzed. In contrast to the increase of IgG+ EV populations in the plasma of PDAC patients during tumor progression (nonresponse), the monthly evaluation of IgG+ EV populations in the plasma of PDAC patients (Figure 6B) revealed a decrease in IgG+ EVs upon imagiological response.
To determine whether IgG+ EVs meet the criteria for independence from CA19.9 expression, it was performed the same monthly IgG+ EVs analysis on two patients without CA19.9 expression. The same pattern was observed as for patients with CA19.9 expression, suggesting that the evaluation of IgG+ EVs as a marker of response to therapy may be applicable to all metastatic PDAC patients (Figure 6C). In addition, the measurement of IgG+ EVs was compared to the measurement of CA19.9, the gold standard serological marker in PDAC12. As expected, it was observed a significant downregulation of CA19.9 in patients who responded to therapy (Figure 7A) and an upregulation of CA19.9 in nonresponders (Figure 7B).
In addition to the individual longitudinal analysis of patients, chemotherapy response and nonresponse timepoints were grouped to investigate the population of IgG+ EVs in responders and nonresponders. As shown in Figure 6D, it was observed a significant decrease in the IgG+ EV population in responders following treatment. In contrast, the proportion of IgG+ EVs significantly increased in patients who did not respond to chemotherapy (Figure 6E). The same patterns of response were observed with CA19.9, as predicted. The evaluation of sensitivity and specificity of IgG+EV for response evaluation of patients with metastatic PDAC showed an AUC of 0.8311 (95% confidence interval 0.6788 to 0.9834, p= 0.0020) (Figure 6F), compared to an AUC of 0.9911 (95% confidence interval 0.9679 to 1.00, p<0001) for the same evaluation for CA19.9 in our population ( ).
Our findings suggest that levels of IgG+ EVs are associated with imaging evaluations of clinical response to treatment, suggesting that IgG+ EVs could be used as a readout in PDAC clinical settings.
Evaluation of the potential role of plasmatic IgG levels and inflammation status in IgG
+
EV proportion
The fluctuations in the plasmatic proportion of IgG+ EVs could, in theory, be a direct result of variations in plasma IgG35 levels. To test this hypothesis, the total amount of plasmatic IgG was measured in the same set of patients. It was found no significant differences in plasmatic IgG levels during treatment response or disease progression in patients with PDAC (Figure 8A and 8B). Consequently, it was found no correlation between the percentage of IgG+ EVs and total plasmatic IgG levels, indicating that the variation of IgG+ EVs is not due to fluctuations in plasmatic IgG levels (Figure 8C).
Alternately, IgG+ EVs may derive, at least in part, from alterations in the inflammatory status of immune cells during the progression of PDAC. The neutrophil/lymphocyte ratio (NLR) is a clinical marker of inflammation calculated as the quotient of the absolute neutrophil and lymphocyte counts36. In light of this, it was found no differences between the groups (responders and nonresponders) and no correlation between levels of IgG+ EVs and neutrophil-to-lymphocyte ratio. In addition, it was found no correlation between the levels the inflammatory marker C-Reactive Protein37 and the levels of IgG+ EVs ( ), further suggesting that in the context of the present invention, the inflammatory status has no effect on IgG+ EV levels.
Identification of IgG-associated proteins on the surface of PDAC patient EVs
Next, it was investigated potential differences in the molecular mechanisms of IgG transport by plasma EVs between healthy controls and PDAC patients. To test this, a method for characterizing protein interactions at the surface of EVs was devised. Briefly, biotinylated surface proteins of lysed EVs were isolated by streptavidin binding, followed by co-immunoprecipitation with an antigen-specific antibody. Here, IgG was precipitated from the mixture and searched for EV surface proteins bound to IgG.
Several IgG fragments were detected in both healthy controls and PDAC patients. In addition, soluble proteins (alpha-2-macroglobulin), cell surface receptors (i.e., Glutamine Receptor), cytoskeletal proteins (i.e., Keratin), and cytoplasmic proteins were detected in both groups (e.g. Chloride intracellular channel protein 4, Golgi integral membrane protein 4, Chondroitin sulfate synthase 3 and Protein Argonaute 2). IgG was bound to Melanoma associated antigen B1 (MAGE B1) in the EVs of PDAC patients, in addition to IgG fragments and Albumin. MAGE B1 is a well-known PDAC antigen38, suggesting that the population of IgG+ EVs described here is the consequence of an interaction between tumoral antigens on the surface of EVs released by tumor cells and IgG in circulation (Table 5).
Table 5 – IgG associated proteins identified by MS
Cancer Patients | Immunoglobulin lambda variable 3-21 |
Melanoma-associated antigen B1 | |
Albumin | |
Probable non-functional immunoglobulin heavy variable 3-16 | |
Healthy + Cancer | Keratin, type II cytoskeletal 1 |
Chloride intracellular channel protein 4 | |
Alpha-2-macroglobulin | |
Glutamate receptor ionotropic, kainate 3 | |
Keratin, type II cytoskeletal 6B | |
HUMAN Ig kappa chain V-I region Lay | |
HUMAN Ig kappa chain V-III region NG9 (Fragment) | |
HUMAN Ig kappa chain V-III region POM | |
HUMAN Ig kappa chain V-III region CLL | |
HUMAN Ig kappa chain V-III region VH (Fragment) | |
Immunoglobulin kappa variable 3D-7 | |
Immunoglobulin kappa variable 3/OR2-268 (non-functional) | |
Immunoglobulin kappa constant | |
Immunoglobulin kappa variable 3-15 | |
Probable non-functional immunoglobulin kappa variable 3-7 | |
Ig lambda chain V-II region NIG-84 | |
Chondroitin sulfate synthase 3 | |
Ig lambda chain V-II region BUR | |
Keratin, type I cytoskeletal 10 | |
Protein argonaute-2 | |
Golgi integral membrane protein 4 | |
Healthy Donors | S100A9 |
Ig kappa chain V-III region Ti | |
Uncharacterized protein (Fragment) |
The analysis of EV bulks is an effective method for identifying molecules of interest (e.g., proteins, lipids, and RNA) in EV liquid biopsies. In fact, MS analysis of EVs in bulk was used to identify IgG as a possible EV marker of therapeutic response in PDAC patients. However, failure to distinguish between EV populations may obscure real differences between experimental groups. Moreover, the implementation of EV biomarkers in clinical practice is hindered by the laborious and time-consuming isolation and analysis protocols commonly employed for EVs. In an effort to characterize populations of extracellular vesicles (EVs) using a method that permits rapid analysis of markers in EV samples, a vesicle flow cytometry protocol was used29. By not requiring EV isolation prior to analysis, the processing time is reduced from >24 hours to 4 hours. Therefore, the use of vesicle flow cytometry has the potential to facilitate the clinical evaluation of IgG+ EVs.
Although the main objective of our work was to identify a novel biomarker to monitor therapy response of diagnosed metastatic PDAC patients, instead of identifying a new marker to diagnose PDAC, it was found elevated levels of IgG+ EVs in PDAC patients compared to healthy controls, reinforcing previous descriptions of the potential application of this marker for PDAC diagnosis45. In the present invention, it was found that levels of IgG+ EVs did not correlate with validated clinical markers for inflammation (Neutrophil-to-Lymphocyte Ratio and C-Reactive Protein), suggesting this biomarker is not affected by the inflammatory background of the patients. However, as the recruitment criteria for the analysis excluded individuals with inflammatory conditions, further study will be necessary to address the potential impact of inflammatory background in the specificity of IgG+ EVs as a diagnostic marker for PDAC.
It was possible to observe the dynamics of IgG+ EV populations within each PDAC patient and their association with the evaluation of chemotherapy response. It is also demonstrated that the analysis of IgG+ EV populations may be utilized in the follow-up of PDAC patients, including those who lack CA19.9 expression. Due to the absence of this established marker, these patients rely solely on imaging evaluations to determine their clinical response to chemotherapy; therefore, a new reliable marker would represent a substantial improvement in their care.
During the characterization of proteins bound to IgG in circulating EVs, a number of proteins were identified in both healthy donors and PDAC patients. This suggests that at least some IgGs bind to EVs via protein-protein interactions that may occur after EVs are secreted by cells. Consequently, circulating IgG and IgG ligands in EVs may interact in the extracellular environment of both cancer patients and healthy donors46. This is further supported by previous studies on autoimmune diseases, showing that immuno-globulins can bind to circulating EVs and form immune complexes that contribute to disease pathology47-50. In fact, the composition of EVs is not a mere result of their intracellular biogenesis, as their surface is highly interactive with proteins present at the extracellular milieu. The interaction of EVs with secreted proteins has been shown to modulate their immune recognition, mobility, uptake and signaling capabilities51. Remarkably, many proteins that frequently display quantitative changes in cancer patients, such as cytokines/chemokines52, extracellular matrix proteins53, coagulation factors54, complement factors55, immunoglobulins56 and albumin57, can interact with EVs after their release and change their composition51.
The MS analysis of proteins bound to IgG focused on EV surface proteins, as only these proteins were biotinylated during the immunoprecipitation protocol. Also, as vesicle flow cytometry studies were performed with intact EVs, all IgG+ signals derived from IgG bound at the external face of the EV surface. This agrees with the conventional mechanism of IgG binding to the surface of cells, which depends on the binding of IgG to a cell membrane protein on B cells, the Igα/Igβ heterodimer (CD79α/CD79β) [58, 59]. Therefore, as to CD79α/CD79β, at least part of IgG anchorage on EVs relies on binding to surface proteins of EVs, such as MAGE B1. Although MAGE B1 was identified as an EV surface ligand of IgG in 8 different PDAC patients, further study, including methods other than MS, will be necessary to validate this finding in larger cohorts of PDAC patients. Importantly, although immunoglobulins (Igs) were traditionally thought to be exclusively produced by B-lineage cells, recent studies have shown that these molecules can also be produced by a large diversity of tumor types21, including PDAC35, 60, 61. Therefore, although the association with MAGE B1 suggests that IgG binding to circulating EVs may be the result of post-secretion interactions with tumor neoantigens present on tumor EVs, at least part of the circulating IgG+EVs associated with metastatic PDAC burden could potentially be packed and secreted at the surface of EVs directly by PDAC cells.
MAGE B1 is a tumor antigen found in a variety of tumor types, including melanoma and tumors of epithelial origin, such as breast, colorectal carcinoma, lung, and pancreatic38, 62-66. In addition, MAGE is identified as an antigen normally expressed by the placenta and male germ cells in cancerous testes. It is expressed in 47 percent of pancreatic tumors67, giving cells that express it a survival advantage68 and negatively correlating with prognosis and patient survival67, 69. MAGE B1 was identified as one of the proteins found exclusively in EVs from PDAC patients. In addition, it was found that healthy controls had a significantly smaller IgG+ EV population, being the presence of IgG on the surface of these EVs unrelated to neo-antigens such as MAGE B1 (Table 5). Although the correlation between IgG+ EVs and the response of PDAC patients to chemotherapy is insufficient to conclude that the IgG+ EV population that varies based on chemotherapy response is tumor derived, it is proposed that at least a portion of the IgG+ EVs upregulation during PDAC progression may be due to IgG binding with PDAC EVs expressing MAGE B1. Due to samples limitations, it is not possible to further validate this result by additional methods. In spite of that, as the interaction of IgG with MAGE1 and other proteins was verified in all of the 8 different PDAC patients studied in our MS analysis, the results found are unlikely to be false positive.
We also found that the proportion of IgG+ EV is independent of the availability of circulating IgG. Alternatively, this may be the result of elevated levels of tumor EV secretion and/or enhanced packaging of tumor antigens (such as MAGE B1) in PDAC EVs. Moreover, it is plausible that this process may result in tumor-directed IgG absorption by tumor EVs and, as a result, may contribute to tumor immune-escape45 and the chronic inflammatory state observed in metastatic PDAC patients70. The binding of IgGs to EVs could also affect the efficacy of targeted therapies (e.g., immunotherapies). Additional re-search will be required to fully comprehend the aforementioned implications.
The subject matter described above is provided as an illustration of the present invention and, therefore, should not be construed to limit it. The terminology employed for the purpose of describing preferred embodiments of the present invention should not be restricted to them.
As used in the description, defined and indefinite articles, in their singular form, are intended for interpretation to also include plural forms, unless the context of the description explicitly indicates otherwise.
Undefined articles "one" should generally be interpreted as "one or more", unless the meaning of a singular modality is clearly defined in a specific situation.
It will be understood that the terms "understand" and "include", when used in this description, specify the presence of characteristics, elements, components, steps, and related operations, but do not exclude the possibility of other characteristics, elements, components, steps, and operations as well contemplated.
As used throughout this patent application, the term "or" is used in an inclusive sense rather than an exclusive sense, unless the exclusive meaning is clearly defined in a specific situation. In this context, a phrase of the type "X uses A or B" should be interpreted as including all relevant inclusive combinations, for example "X uses A", "X uses B" and "X uses A and B".
In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from the context to be directed to a singular form.
All changes, provided they do not modify the essential characteristics of the following claims, must be considered within the scope of the protection of the present invention.
The citation list is as follows:
EP2542696B1
EP2176665B1
WO2022046576A1
EP2718721A1
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Claims (13)
- Method for monitoring tumor burden in subjects during therapeutic intervention characterized in that it comprises the steps of:
- collection of a blood sample from the subject;
- recording of the clinical data;
- centrifuging the blood sample in a centrifuge and processing of the plasma sample for extracellular vesicle staining followed by qualitative and quantitative determination of the population of vesicle-associated proteins; and
- data processing to assess the subject’s response to therapy.
- Method, according to claim 1, characterized in that, in step (a), the blood sample is collected from a liquid biopsy of the tumor every time the patient came to a follow-up visit.
- Method, according to claim 1, characterized in that, in step (b), for each blood sample collection, the clinical data is registered.
- Method, according to claim 3, characterized in that the clinical data is at least one of the groups consisting of Magnetic Resonance Imaging / Computer Tomography or conventional biomarkers of the disease to be tested.
- Method, according to claim 4, characterized in that the disease to be tested is pancreatic ductal adenocarcinoma and the biomarker is CA19.9.
- Method, according to claim 1, characterized in that, in step (c), the blood sample is centrifuged twice in a temperature range from 4 to 10 ºC and a centrifugal force in the range from 500 g to 3000 g for a time range from 10 to 20 minutes and the plasma-derived extracellular vesicle sample obtained is analyzed by Nanoparticle Tracking Analysis and Vesicle Flow Cytometry.
- Method, according to claim 6, characterized in that the plasma-derived extracellular vesicle sample is diluted in filtered phosphate-buffered saline prior to the Nanoparticle Tracking Analysis.
- Method, according to claim 6, characterized in that the plasma-derived extracellular vesicle sample is submitted to two incubation substeps to stain extracellular vesicles prior to the Vesicle Flow Cytometry analysis.
- Method, according to claim 8, characterized in that the first incubation substep comprises staining the plasma-derived extracellular vesicle sample with anti-IgG in phosphate-buffered saline for a time range from 1 to 3 h and in a temperature range from 20 to 37 °C.
- Method, according to claim 8, characterized in that the second incubation substep comprises adding an extracellular vesicle specific fluorescent dye to the antibody-stained sample for a time range from 1 to 2 h in a temperature range from 20 to 37 °C.
- Method, according to claim 8, characterized in that the extracellular vesicle specific fluorescent dye is Carboxyfluorescein Diacetate Succinimidyl Ester.
- Method, according to claims 8 to 11, characterized in that the unbound extracellular vesicle specific fluorescent dye and antibody are removed prior to the Vesicle Flow Cytometry by Size Exclusion Chromatography.
- Method, according to claim 1, characterized in that, in step (d), the treatment of the data consists of monitoring the levels of extracellular vesicles that express IgG throughout the treatment of the patients.
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