CN114480608A

CN114480608A - Peripheral blood sample analysis method and kit

Info

Publication number: CN114480608A
Application number: CN202111246105.1A
Authority: CN
Inventors: 黄丹; 梁广锡; 邓亮生
Original assignee: Cell Atlas Co ltd; Chinese University of Hong Kong CUHK
Current assignee: Cell Atlas Co ltd; Chinese University of Hong Kong CUHK
Priority date: 2020-10-27
Filing date: 2021-10-26
Publication date: 2022-05-13
Also published as: WO2022089426A1

Abstract

Methods of peripheral blood sample analysis are provided, comprising determining transcript abundance of at least one B lymphocyte target gene and transcript abundance of at least one B lymphocyte reference gene in a peripheral blood sample; the B lymphocyte target gene is selected from TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, and the B lymphocyte reference gene is selected from TNFRSF13C and FCRLA. The method can be used to predict vaccination effectiveness and immunotherapy effectiveness at the early stages of vaccination. The application also provides a kit for implementing the method and related applications.

Description

Peripheral blood sample analysis method and kit

Technical Field

The application relates to the field of biological detection and analysis, in particular to a peripheral blood sample analysis method, a corresponding kit and application, which can be used for evaluating the effectiveness of a vaccine and the effect of immunotherapy.

Background

Detection and analysis of peripheral blood is an important aspect of medical examination. Peripheral blood is a mixture of many components, including plasma and blood cells, readily available from the human body, primarily from finger tips, earlobes, and elbow meridians. Plasma components include metabolites, waste products, hormones, ions, proteins, etc., and blood cells include red blood cells, white blood cells, platelets, etc. Peripheral blood is often used clinically for routine, biochemical and serum immunological tests to diagnose or identify certain diseases. Morphological examination and cytological examination of peripheral blood are of great significance for the diagnosis of various blood diseases.

Gene expression of a single cell type is a good biomarker. In order to obtain the gene expression levels of individual cell subsets in peripheral blood, conventional methods require the prior isolation of subsets of a given cell type. Recently, a method called single cell RNA-sequencing (scRNA-seq) may also obtain gene expression information of single cells. Single cell RNA sequencing generates gene expression data for each single cell by using expensive equipment and reagents, and such expensive techniques are generally used only in research and are not suitable for wide clinical application.

Some methods can directly measure genes characteristic of a selected single cell subpopulation in a cell mixture sample without isolating the target cell subpopulation. It also avoids the use of expensive equipment for single cell RNA-seq. See patent document CN103764848B (

application date

2012, 7, 23, publication date 2014, 4, 30); and US9589099B2 (application date 2012, 7, 20, published 2017, 3, 7). This new assay is called "Direct Leukocyte Subpopulation Transcript Abundance" assay (Direct Leucozyphation Abstract, or simply Direct LS-TA assay). These methods provide a technique for directly measuring the abundance of transcripts of subpopulations of white blood cells without prior isolation of the cells, with great advantages in measurement speed and cost.

Immunology is an important research aspect of biology. Through immunological research, the immune system of human bodies and animal bodies is further known, and more substances, means and methods are provided for preventing and treating diseases. Immunology has been greatly developed in recent years, and various vaccines are emerging continuously. Vaccine prevention of disease or vaccine treatment of disease is currently a faster developing aspect. However, the effectiveness of the vaccine after use is uncertain, and it is an important issue to obtain the effectiveness of the vaccine or confirm the effectiveness of the vaccine in time.

Infectious diseases are a significant enemy of humans and animals. Vaccination is a good method of controlling infection. Vaccines allow the body to prime the adaptive (also known as adaptive or specific) immune system prior to infection to produce antibodies against the pathogen. In individuals who have been vaccinated, the pathogen will be rapidly controlled and the symptoms of infection will be greatly reduced or even asymptomatic. Common examples include vaccination against hepatitis and influenza viruses. Since influenza virus strains frequently change, annual vaccination with different influenza virus strains is common in many places. COVID-19 is now a new pandemic infection and vaccine development is underway.

In the case of vaccination against influenza virus, not all vaccinated vaccinees are protected from subsequent infection, nor are each vaccinee antibody-producing, and such poorly protected (low antibody-producing) people are called non-responders (NR). On the other hand, the vaccinated Responder (R) will produce antibodies against the antigen. Antibody production is measured as the Antibody Titer (Antibody Titer) against a particular antigen and needs to be measured in blood samples 28 days after inoculation. Generally, the responder rate after influenza vaccination is less than 50% of the vaccinees. In addition, the acquired immune system takes a long time to produce antibodies against the neoantigen, so the results of antibody titers are generally analyzed 28 days after vaccination. Tests with the presence of antibodies as a biological marker confirm that the test requires at least 28 days after inoculation to obtain results.

Therefore, the vaccine needs to be matched with effective detection to really prevent and treat diseases in time. Rapid and early detection of vaccination efficacy is an urgent problem to be solved in vaccine use.

Therefore, there is a need for a new simple and rapid peripheral blood analysis method that can be performed early after prophylactic or therapeutic vaccination to evaluate the effectiveness of vaccination and the effect of immunotherapy.

Disclosure of Invention

In general, the present application provides an analysis method and corresponding kit and application, which can directly evaluate the expression of B lymphocyte genes by directly measuring the Transcript Abundance (TA) of a gene (cell-type information) characteristic of a specific B lymphocyte type in various cell mixture samples (e.g., peripheral blood), thereby avoiding the prior isolation of B lymphocytes and also avoiding the need for single cell RNA sequencing using expensive equipment, and biomarker parameters obtained by the method are used to predict the effectiveness of vaccination and the effect of immunotherapy (e.g., cancer immunotherapy), thereby facilitating early or rapid determination.

In particular, one aspect of the present application provides a method of peripheral blood sample analysis comprising determining in a peripheral blood sample the abundance of transcripts of at least one B lymphocyte target gene and the abundance of transcripts of at least one B lymphocyte reference gene; the B lymphocyte target gene is selected from at least one of TNFRSF17, TNFRSF13B, TXDC 5 and JCHAIN, and the B lymphocyte reference gene is selected from TNFRSF13C and FCRLA. The present application also provides the use of a reagent composition for determining the abundance of a gene transcript selected from TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, in the preparation of a kit for a method of analysis of a peripheral blood sample, and a B lymphocyte reference gene selected from TNFRSF13C and FCRLA.

Other genes may also be selected for the above-described reference and target genes without departing from the spirit and nature of the present invention.

In one embodiment, the above method may comprise the steps of:

a) collecting the peripheral blood sample;

b) determining transcript abundance of the at least one B lymphocyte target gene of the peripheral blood sample to obtain a first amount;

c) determining transcript abundance of the at least one B lymphocyte reference gene of the peripheral blood sample to obtain a second amount;

d) calculating a biomarker parameter, i.e. a relative value of the first amount and the second amount.

In one embodiment, the peripheral blood sample is a peripheral blood sample before or after vaccination. For example, the peripheral blood sample may be a sample 5-12 days after vaccination.

In one embodiment, the method further comprises comparing the biomarker parameter of the peripheral blood sample to a threshold value. The comparison may be used, for example, to predict antibody production resulting from the vaccination and/or the effect of cancer immunotherapy.

In one embodiment, the peripheral blood sample comprises a first peripheral blood sample taken prior to vaccination, and a second peripheral blood sample taken after vaccination (e.g., 5-12 days after vaccination); the biomarker parameters comprise a first biomarker parameter obtained from the first peripheral blood sample and a second biomarker parameter obtained from the second peripheral blood sample. In further embodiments, the method may further comprise calculating a change value for the first and second biomarker parameters. The change value can be used, for example, to predict antibody production and/or the effect of immunotherapy (e.g., cancer immunotherapy) resulting from the vaccination.

In one embodiment, the calculation and comparison of the biomarker parameters may be performed by, for example, a calculator system, such as by a computer.

In one embodiment, the vaccine is a prophylactic vaccine or a therapeutic vaccine. For example, it may be a vaccine for preventing infectious diseases or a vaccine for treating cancer.

In one embodiment, the vaccine is an existing vaccine already on the market, but also a new vaccine.

In another aspect, the present application provides a kit comprising reagent components for quantifying transcript abundance of a gene, which may be selected from at least one of TNFRSF17, TNFRSF13B, TXNDC5, JCHAIN, and at least one of TNFRSF13C and FCRLA. Other genes may be selected without departing from the spirit and nature of the invention.

In one embodiment, the kit contains at least one of the primers having the following sequences:

in another aspect, the present application provides a reagent composition or kit for determining the abundance of a gene transcript for predicting the effectiveness of vaccination and/or the effect of immunotherapy, wherein the gene is selected from at least one of TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, and at least one of TNFRSF13C and FCRLA. In a further aspect, the present application provides the use of a reagent composition for quantifying the abundance of a gene transcript, wherein the gene is selected from at least one of TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, and at least one of TNFRSF13C and FCRLA, in the manufacture of a kit or medicament for predicting the effectiveness of vaccination and/or the effectiveness of immunotherapy.

In a specific embodiment, the reagent component comprises a primer, and the sequence of the primer is shown as any one of SEQ ID NOs: 1-14.

In a specific embodiment, said genes are obtained from a peripheral blood sample, preferably from B lymphocytes of said peripheral blood sample. In one embodiment, the peripheral blood sample may be obtained at least once, e.g., once, twice, or multiple times.

In one embodiment, the abundance of transcripts of reference and target genes of B lymphocytes in peripheral blood can be determined using the method disclosed in CN 103764848B.

In one embodiment, the methods of the invention are used to analyze the immune response elicited by vaccination, thereby evaluating the effectiveness of the vaccine or for the assessment of the efficacy of immunotherapy (e.g., cancer immunotherapy).

The effectiveness of the traditional vaccine or the prognosis evaluation of the immunotherapy mostly adopts an antibody titration confirmation method, and the evaluation can be carried out only after the generation of the antibody, and generally needs 28 days later. This traditional approach suffers from the biological time limit limitations imposed by antibody production, and is too long to be validated for treatment of acute infectious diseases and rapidly progressing diseases, among others. In contrast, the methods of the present application significantly shorten the time for confirmation of vaccine effectiveness or prognostic evaluation of immunotherapy. For example, the screening of the present invention results in specific target and reference B lymphocyte genes, and the analysis of transcripts of these specific genes can greatly advance the time for confirmation of vaccine effectiveness or prognostic evaluation of immunotherapy, for example, up to 28 days, for example, three weeks, for example, two weeks, for example, one week, or even several days, or less after vaccine administration.

Brief description of the drawings

The invention will be further described with reference to the accompanying drawings, in which:

FIG. 1 shows the correlation of the results of biomarker detection using "Direct B Lymphocyte LS-TA" assay, "Direct B Lymphocyte LS-TA", with the expression of target genes detected in isolated and purified B lymphocytes by conventional methods. The X-axis in fig. 1 shows the assay of TNFRSF17 gene expression in isolated and purified B lymphocytes, using RPL32 as the conventional housekeeping gene, where the X-axis is the gold standard. As shown in the Y-axis of FIG. 1, the results of detection of the biomarkers obtained by using "direct B lymphocytes LS-TA" in PBMC (TNFRSF17: relative value of TNFRSF13C) showed a good correlation with the expression of the target gene detected in the isolated and purified B lymphocytes by the conventional method (correlation coefficient, R > 0.9).

FIG. 2 shows a first embodiment of the method for evaluating the effect of using a vaccine according to the present invention. This scheme requires only one sample.

FIG. 3 shows a second embodiment of the method for evaluating the effectiveness of a vaccine according to the present invention. This protocol requires two samples before and after vaccination.

Figure 4A shows PBMC data at day 7 for raw values of the "direct B lymphocyte LS-TA" biomarker parameters for TNFRSF17 for NR and R subjects. Shown in fig. 4B as MoM values after conversion.

FIG. 5A shows the ability of "direct B lymphocyte LS-TA" to predict early stage after vaccination by ROC analysis (receiver operating characteristic curve) of TNFRSF17 values of "direct B lymphocyte LS-TA" from a day 7 PBMC sample. The area under the curve (AUC) was 0.85, indicating that this biomarker parameter has good predictive power.

Figure 5B shows that ROC analysis was performed similarly on the data set GSE59635 from another influenza vaccination experiment, which also reached 0.73 AUC.

FIG. 6A shows the increase in "direct B lymphocyte-LS-TA" of TNFRSF 17.

Fig. 6B shows the same data as fig. 6A converted to a MoM representation. In the NR group, the biomarker parameters (D7-D0) were increased in increments ranging from-1.01 to 0.67 with a median increment of 0.066. In contrast, the R group had higher incremental changes ranging from-0.13 to 3.39 with a median increment of 1.11, and the incremental changes between the NR and R groups were significantly different (paired tests, p value < 0.01).

FIG. 7A shows that ROC analysis was performed to determine the ability of detecting the increase in TNFRSF17 between day 0 and day 7 using "direct B lymphocytes LS-TA" to discriminate between the R and NR groups. The resolution of the incremental values was also high AUC (AUC 0.85) comparable to that of "direct B lymphocyte LS-TA" TNFRSF17 on day 7 alone.

FIG. 7B shows that the AUC for the increment of "direct B lymphocyte LS-TA" of TNFRSF17 (D7-D0) was 0.7 in the data set GSE59635 PBMC samples.

Fig. 8A and 8B in data set GSE136163, results for whole blood samples from yellow fever inoculators were used. Of these, 2 vaccinees were assigned NR as their neutralizing antibody (nab) titers did not exceed a 4-fold increase. The median change of "direct B lymphocyte LS-TA" of TNFRSF17 in the NR group (D7-D0) was negative (-0.28). In contrast, D7-D0 "direct B lymphocyte LS-TA" of TNFRSF17 of the R group was amplified more (median 0.38).

FIG. 8C shows that ROC analysis was performed, and the AUC of "direct B lymphocyte-LS-TA" TNFRSF17 was 0.82 on day 7 alone.

FIG. 8D shows the AUC of the increase in "direct B lymphocyte-LS-TA" TNFRSF17 at day 0 and day 7 to be 0.88.

Fig. 9A shows: the increase in biomarkers in the NR and R groups from D0 to D7 when using TXNDC5 gene data in the data set GSE 59635. The difference between the two groups (NR and R) was significant (paired test, p value < 0.01).

FIG. 9B shows the analysis of the increased ROC of TXNDC5 detected by "direct B lymphocytes LS-TA", which has an AUC of 0.77.

Figure 9C shows that the "direct B lymphocyte LS-TA" assay of TNFRSF13B versus TNFRSF13C using data set GSE59635, taken alone on day seven samples, determined that responders (group R) had a higher biomarker parameter (p value < 0.05).

Figure 9D shows ROC analysis, demonstrating that this index is effective in discriminating between the two groups (AUC 0.81).

Figure 10A shows that group R has higher TNFRSF17 than group NR: increment of "direct B lymphocytes LS-TA" for FCRLA (paired test, p value < 0.001).

FIG. 10B shows the AUC for the increment of "direct B lymphocyte LS-TA" (TNFRSF13C, FCRLA) in the ROC analysis to be 0.82.

Figure 11A shows that the "direct B lymphocyte LS-TA" biomarker parameters were lower in patients with long survival before vaccination (P value < 0.05). Figure 11B shows that ROC analysis indicates that this assay has some predictive power (AUC 0.63).

FIG. 12A shows the results of survival analysis (survival analysis). Survival curves (survival curves) were calculated for three groups of patients using Cox regression, dividing patients into three groups based on the "direct B lymphocyte LS-TA" biomarker parameters prior to vaccine injection, using a range of quantiles into three groups of (a) low (indicators below 25 percentile), (B) intermediate (25 percentile-75 percentile), and (c) high (above 75 percentile). The survival curves of the three groups are obviously different. The worst survival probability is the group with a high "direct B lymphocyte LS-TA" index, most patients die within almost one year (p-value < 0.01).

Figure 12B shows that the survival curves are more significantly different (p value <0.001) when comparing only the two groups with low (below 25 percentile) and high (above 75 percentile) biomarker parameter indices to each other. The worst survival probability is the group with a high "direct B lymphocyte LS-TA" index, and the risk of death (also called risk rate or risk ratio) is almost three times higher than the group with a lower biomarker parameter index (risk probability 2.95, confidence interval 1.6-5.6).

FIG. 13A shows a meta-analysis Forest map (Forest Plot) of the seventh day expression of biomarkers (JCHAIN/TNFRSF13C) in the NR and R groups.

FIG. 13B shows meta-analyzed forest profiles of the increase in biomarker (JCHAIN/TNFRSF13C) from day 0 to day 7 in the NR and R groups.

Detailed description of the preferred embodiments

The traditional method of determining gene expression of specific cells in peripheral blood is to first isolate a specific cell subset and then determine its gene expression level. The cell expression level obtained by the traditional method is used as a gold standard. The present application provides methods for directly determining gene expression of specific cells (e.g., B lymphocytes) in a peripheral blood sample (e.g., Peripheral Blood Mononuclear Cells (PBMCs)) without the need to purify the specific cells from other blood cells. Comparison of the gold standard derived from the traditional methods with the specific cellular gene expression levels derived from the novel methods herein and their correlation allows the utility of the novel methods to be determined.

Using the methods of the present application, Transcript Abundance (TA) of a single cell type (e.g., B lymphocytes) can be determined directly in a cell mixture sample of peripheral blood (e.g., PBMCs) without the need for subpopulation isolation. It applies to a group of genes called B-cell information genes. The relative values of the two B cell informative genes (target gene and stably expressed reference gene) obtained in PBMC were used as new biomarker parameters to represent target gene expression in purified B lymphocytes. This method of directly determining the TA of a leukocyte subset in a peripheral blood sample by eliminating the cumbersome process of cell isolation is called the direct LS-TA method. For example, the method can be applied to gene expression data sets collected in influenza vaccination trials to make early predictions of seroconversion.

The present application provides novel, readily analyzable peripheral blood biomarkers that can be readily incorporated into routine clinical laboratory examinations, or used in routine clinical studies. The peripheral blood biomarkers can predict early seroconversion status after influenza vaccination (e.g., antibody production after vaccination can be predicted at day 7, etc.). Since the route of adaptive immunity is common to vaccination against influenza and COVID-19, these biomarkers can also be used to predict seroconversion of the new COVID-19 vaccine. Direct B lymphocyte LS-TA would be a useful test for performing personalized vaccination.

Terms and definitions

The term "peripheral blood sample" has the usual meaning in the field of medical testing, mainly referring to blood samples taken from the point of the finger, the earlobe, the arm veins, etc. For example, the sample may be a Whole Blood sample (WB) or a mixture of types of monocytes in Peripheral Blood (PBMC).

The term "directly measuring" means measuring without isolating specific cells (e.g., B lymphocytes) therein. That is, a direct measurement is performed from a blood sample without isolating specific cells to be measured (e.g., B lymphocytes).

The term "gene expression level" refers to the level of gene expression of a cell (e.g., a B lymphocyte) measured by RNA, specifically mRNA, which is the level of the amount of mRNA. In other words, the mRNA level of a gene of a cell (e.g., B lymphocyte) in a sample is measured. Technically, it is also referred to as Transcript Abundance (TA).

The term "vaccine" refers to a biological product, which is prepared by artificial attenuation, inactivation, lysis, gene recombination, purification and other methods aiming at pathogenic microorganisms of diseases or proteins (polypeptides, peptides), polysaccharides or nucleic acids thereof, can induce the organism to generate corresponding protective immune substances for preventing and controlling the occurrence and prevalence of corresponding diseases, or can regulate and control specific immune response of certain harmful factors (such as smoking) and physiological states (such as contraception) in the organism, thereby achieving the purposes of treating or eliminating the harmful factors and avoiding fertility.

Functionally, a vaccine is a substance that stimulates the body to mount an immune response, serving to destroy a specific infectious organism, a specific cell, and to perform a preventive or therapeutic action. The vaccine component comprises an active component and an auxiliary component.

As used herein, "vaccine" includes vaccine active ingredients, as well as compositions or formulations incorporating other substances, i.e., single ingredients or compositions or formulations suitable for use in stimulating an immune response in humans and animals. Vaccines refer to substances in any of the above cases. Simply, an immune response stimulant, or a substance that induces a beneficial immune response.

The term "cancer" refers to a disease in which oncogene expression or cancer cell proliferation occurs or a solid tumor occurs. Any cancer that is clinically diagnosed by histology, immunology, or protein assay is within the meaning of the word.

The term "cancer immunotherapy", also known as cancer immunotherapy, is a new generation of cancer treatment (Wikipedia: ("cancer immunotherapy" 2020)), which exploits the body's immune function to attack tumor cells. There are different treatment regimes to stimulate the body's immune potency. Most commonly, PD-1 or PD-L1 inhibitors have been used with great success in the treatment of large bowel cancer. Cancer vaccine (cancer vaccine) is a new therapeutic approach. The cancer vaccine herein does not mean a preventive vaccine that is administered before an individual does not develop cancer, such as Hepatitis B Virus (HBV) vaccine that can prevent liver cancer and Human Papilloma Virus (HPV) vaccine that can prevent cervical cancer, but means an antigen against which cancer cells possess some characteristics after cancer has developed, and against which an immune response can be generated by stimulating self-body. Different treatment regimens use different candidate antigens. An example herein is the treatment of prostate cancer using vaccination with a Personalized Peptide Vaccine (PPV) (Araki et al 2015).

The term "cell mixture sample" is a mixture of cells from an individual (e.g., a human). Typically, the cell mixture sample may be from peripheral blood, e.g. may be a peripheral blood sample without any treatment.

The term "characteristic genes" refers to genes specifically expressed by a particular cell type (e.g., B-lymphocytes), and the activity of the characteristic genes can be determined by measuring the abundance of transcripts. The characteristic gene may include a target gene and a reference gene. Since the target specific cell used in the present patent application is a B cell, the B cell characteristic gene may also be referred to as a B cell information gene. In this patent application, characteristic genes and informative genes may be used interchangeably.

The terms "biomarker" and "biomarker" (biomarker) refer to the amount of mrna in gene expression of a particular cell (e.g., a B lymphocyte), including relative and absolute amounts, that can be used to record biomarker status. In the present patent application, biomarkers and biological indicators may be used interchangeably.

The term "Leukocyte Subpopulation (LS)" includes B lymphocyte Subpopulation. White blood cells include multiple types of cells. Peripheral blood is typically a specimen of a mixture of types of cells, containing various subpopulations of white blood cells, such as neutrophils (neutrophiles), lymphocytes (lymphocytes) and monocytes (monocytes), among others.

The term "Transcript Abundance (TA)" refers to the amount of gene expression (gene expression level) obtained by measuring a sample. Transcript refers to the product after gene transcription (gene transcription), typically RNA. For example, a gene encoded by a protein will produce messenger RNA (mRNA).

The term "Direct B lymphocyte subpopulation transcript abundance" detection ("Direct B lymphocyte leukocyte abundance" assay, "Direct B lymphocyte LS-TA" detection) is a novel biomarker parameter detection scheme, and the average gene expression of a target cell subpopulation can be directly evaluated from a mixture sample without the need to separate and purify the target cell type subpopulation in the mixture sample. The target cell subpopulation in the present discussion is the B lymphocytes in the peripheral blood. This assay is therefore termed the "direct B lymphocyte subpopulation transcript abundance" assay. The calculation of "direct B lymphocyte LS-TA" requires the use of a target gene characteristic of a cell subset and a reference gene characteristic of a cell subset.

In some embodiments, the direct B lymphocyte LS-TA value can be calculated by using the ratio of a target gene characteristic of a cell subpopulation and a reference gene characteristic of the cell subpopulation, e.g., a target gene of "direct B lymphocyte LS-TA" ═ the target gene in PBMC)/(the corresponding reference gene in PBMC). In other embodiments, log (ratio) is used to calculate direct B lymphocyte LS-TA values. For example, log ("direct B lymphocyte-LS-TA" TNFRSF17) ═ log (TNFRSF17 in PBMC) -log (TNFRSF13C in PBMC).

The term "cell subset characteristic target gene" means that in a multicellular mixed sample (e.g., WB, PBMC), most of the transcripts are derived from the gene of a specified target cell subset, i.e., are produced by the cell subset. For example, genes derived from B lymphocytes in the following examples.

The term "cell subset characteristic reference gene" refers to a gene, which is derived from a given target cell subset and is stably expressed in a target cell in a majority of transcripts in a mixed multi-cell sample (e.g., WB, PBMC).

The inventors of the present application propose to directly measure gene expression of specific cells (e.g., B lymphocytes) from various peripheral blood samples, and unexpectedly found that these gene expression are of great value in predicting vaccination and cancer immunotherapy efficacy.

The methods described herein further comprise comparing the biomarker parameter of a peripheral blood sample to a threshold value. In some embodiments, the comparison is used to predict antibody production and/or the effect of immunotherapy resulting from vaccination.

The term "critical value" can be defined using several methods. (1) The critical value may be defined as a value outside the reference interval of the control group. The reference interval for the control group is typically taken to be the middle 95% distribution of the control group. Values outside this range may be used as thresholds to define abnormally low or abnormally high results. (2) The cut-off value may also be preferably defined from a ROC chart, as shown in FIG. 5A. The value of the label at each point on the ROC curve represents a potential cut-off value, and the Y-axis and X-axis show the relative sensitivity and specificity, respectively, using this cut-off value. Thus, when 0.6 was used as the cutoff for day 7 direct LS-TA values for the ratio of TNFRSF17 to TNFRSF13C, it predicted a sensitivity of the vaccination response of-0.8 and a specificity of-0.85 (FIG. 5A). (3) If no control group is available, the percentile value of the direct LS-TA data distribution in the patient group can be used as the cutoff value, as shown in example 7 and FIG. 12. For example, a cutoff value (fig. 9B) was defined by the 75th percentile value of the direct LS-TA values for TNFRSF17 to FCRLA ratio, and cancer patients with direct LS-TA above this cutoff value (solid line in fig. 9B) had a poor response to cancer vaccine therapy and a shorter survival time than other patients.

Data set list for use with the present invention:

Gene expression data sets for peripheral blood and specific single cell types

To identify genes characteristic of a single cell type that can predict a vaccination response, the following gene expression data sets obtained from peripheral blood samples were used.

These data sets were obtained from "gene expression integration" (GEO) maintained by the national institutes of health, USA. The detailed information is available under its login number. The blood sample types obtained included Whole Blood (WB) and Peripheral Blood Mononuclear Cells (PBMCs). Certain cell types that are further isolated and purified, such as isolated and purified B lymphocytes (e.g., GSE45764) or T lymphocytes, are also included in certain data sets.

The standard definition of responders (R) after vaccination is based on the antibody titer in serum against a particular antigen, e.g. a significant increase in Hemagglutination Inhibition (HI) antibody levels (also known as HI titers) after influenza vaccination, indicating that the vaccinee is responsive to the vaccine. The standard is determined by Hemagglutination Inhibition (HI) assay on the sera of subjects before and twenty-eight days after inoculation. The european commission on human pharmaceutical products (CHMP) defines seroconversion/significant increase (seroconversion/significant increase) as: (1) HI titers were at least 1:40 after vaccination and (b) increased at least 4-fold (Committee for Medicinal Products for Human use.1997; Mo et al.2017). The case where the subject after vaccination does not meet these criteria is defined as "non-responder (NR)".

In addition to influenza vaccines, in data set GSE136163, vaccinees received yellow fever vaccination. As with the definition of responders used in other studies, a 4-fold increase in neutralizing antibody (nab) titers post-vaccination was used herein to define responders in this dataset (Casey et al.2019). Two subjects in this data were defined as NR.

In the present specification and claims, the words "comprise," "comprises," and "comprising" mean "including but not limited to," and are not intended to exclude other moieties, additives, components, or steps.

It should be understood that features, characteristics, components or steps described in a particular aspect, embodiment or example of the present application may be applied to any other aspect, embodiment or example described herein unless incompatible therewith.

The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The following examples are illustrative only and are not intended to limit the scope of the embodiments of the present application or the scope of the appended claims. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Examples

Example 1

Biological index parameter of Direct B Lymphocyte transcript abundance (Direct B Lymphocyte LS-TA for short)

A biological index parameter is calculated by using the TA relative values of the B lymphocyte target gene (for example, TNFRSF17) and the B lymphocyte characteristic reference gene (for example, TNFRSF13C) in the cell mixture sample to estimate the gene expression level of the separated and purified B lymphocyte.

In data set GSE45764, multiple isolated and purified B lymphocyte samples and PBMC samples were collected from 5 inoculators on different days, respectively. The degree to which the relative values of the two specified B lymphocyte signature genes in a PBMC cell mixture sample correlate with the expression of the target gene (gold standard) in a purified B lymphocyte sample provides a performance assessment for the "direct B lymphocyte LS-TA" protocol.

In this embodiment, reference is made to fig. 1. The designated target gene is TNFRSF 17. The designated B lymphocyte reference gene is TNFRSF 13C. "direct B lymphocyte LS-TA" is indicated on the Y axis.

For this example, conventional housekeeping genes were used only to normalize gene expression results for isolated and purified B lymphocyte samples. Conventional housekeeping genes include RPL31, RPL32, ACTB, GAPDH, and UBC. The selection of conventional housekeeping genes is described in Eisenberg and Levanon2013, and is also available on websites such as https:// www.tau.ac.il/. about eliis/HKG/. The X-axis of figure 1 shows the gene expression (gold standard) of assayed TNFRSF17 in isolated and purified B lymphocytes using RPL32 as the conventional housekeeping gene. Conventional housekeeping genes are used only by the manufacturer for calibration gold standards and validation purposes, and not in the kits of the invention or embodiments thereof.

As shown in the Y-axis of FIG. 1, the results of the "direct B lymphocyte LS-TA" biomarker of the present invention measured in the sample of PBMC cell mixture (relative value of TNFRSF17: TNFRSF13C) correlated well with the expression of the target gene (gold standard) detected in the isolated and purified B lymphocytes by the conventional method (correlation coefficient, R > 0.9). The results demonstrate that this "direct B lymphocyte LS-TA" biomarker parameter enables assessment of target gene (TNFRSF17) expression in purified B lymphocytes; and single cell type gene expression assays are defined that can be obtained directly from a sample of a multicellular mixture, including PBMCs or WB, without the need for prior isolation of B lymphocytes.

The remaining "direct B lymphocyte LS-TA" biomarkers consisting of B lymphocyte target genes (including TNFRSF13B, TXNDC5, JCHAIN) and B lymphocyte reference genes (including TNFRSF13C, FCRLA) also correlated well with their respective gold standards (correlation coefficient, R > 0.8).

In the examples that follow, the "direct B lymphocyte-LS-TA" marker will be used to predict antibody production status after vaccination. Two schemes are used here, the first scheme requiring only one sample and the implementation flow is shown in fig. 2. The second protocol required two samples before and after vaccination and the procedure is shown in FIG. 3.

Example 2

"direct B lymphocyte LS-TA" seventh day after Vaccination enables prediction of antibody production response

In data set GSE29617 Transcript Abundance (TA) of the two designated B lymphocyte signature genes TNFRSF17 and TNFRSF13C had been logarithmically transformed. Thus, log (TNFRSF17) minus log (TNFRSF13C) yields the biomarker parameters (log values) required for the present application. The biomarker parameter represents the gene expression level of the B lymphocyte gene TNFRSF17 in a cell mixture sample of PBMCs. Because this biomarker is obtained without prior isolation of B lymphocytes, it is labeled "direct B lymphocyte transcript abundance" ("direct B lymphocyte-LS-TA") in the figure.

Thus, the "direct B lymphocyte-LS-TA" biomarker parameter of the B lymphocyte target gene TNFRSF17, calculated using the ratio of the cell subset characteristic target gene and the cell subset characteristic reference gene, can be expressed as:

("direct B lymphocyte-LS-TA" TNFRSF17) ═ TNFRSF17 in PBMC)/(TNFRSF 13 in PBMC 13C)

The biomarker parameters may also be logarithmically transformed, i.e. also expressed as:

log ("direct B lymphocyte-LS-TA" TNFRSF17) ═ log (TNFRSF17 in PBMC) -log (TNFRSF13C in PBMC)

Since measurements with different assay detection methods yield results in different units, a method is needed to normalize the results obtained from multiple different detection methods. The median relative to the normal control group (MoM) is a common standard technique. In this example, the data before inoculation (day 0) was used to define the median of the normal control group. The results for all individuals (including NR and R) were then expressed as multiples of this normal median. This data representation is called the fold of median (MoM) in the control group. It is commonly used in detection methods that have not been standardized by large-scale assays, such as cytokine assays for determining the risk of adverse outcome following SARS-CoV infection (Tang et al 2005). The benefit of using MoM is that it removes the unit limit of data so that the results from different detection schemes can be compared.

Comparison of "direct B lymphocyte LS-TA" of TNFRSF17 gene in peripheral blood mononuclear cell mixed sample (PBMC) of R and NR groups 7 days after vaccination:

the PBMC data at day 7 was used to obtain the "direct B lymphocyte LS-TA" biomarker parameters for TNFRSF17 in NR and R subjects. Shown in fig. 4A and 4B as the original values and the MoM values after conversion. The results confirmed that there was a significant difference between the R and NR groups (Wilcoxon test, p value < 0.01).

The ability of "direct B lymphocyte LS-TA" to make an early prediction of vaccination effectiveness was determined by ROC analysis (receiver operating characteristics curve) of TNFRSF17 values for "direct B lymphocyte LS-TA" from day 7 PBMC samples (fig. 5A). The area under the curve (AUC) was 0.85, indicating that the biomarker parameter has good predictive power.

Similarly, ROC analysis was performed on the data set GSE59635 from another influenza vaccination experiment, which also reached an AUC of 0.73 (fig. 5B).

Example 3

Comparison of incremental Change values of "direct B lymphocyte-LS-TA" TNFRSF17 at day 0 and day 7 in the R and NR groups

The data set (GSE29617) was used to calculate the increment of "direct B lymphocyte-LS-TA" on day 0 and day 7, and the increment change value (delta, δ) obtained by subtracting the two values using the data "direct B lymphocyte-LS-TA" TNFRSF17 value on day 7 and the "direct B lymphocyte-LS-TA" TNFRSF17 value on day 0 (baseline, pre-inoculation) was used to predict the subsequent antibody production status. That is, the present embodiment executes the flow of fig. 3.

Since both values have been logarithmically transformed, the reduction represents the log of the fold change after vaccination. It is shown as the following equation:

the increment of "direct B lymphocyte-LS-TA" in TNFRSF17 gene after vaccination was "direct B lymphocyte-LS-TA" TNFRSF17 at day 7-direct B lymphocyte-LS-TA "TNFRSF 17 at day 0

The increment of "direct B lymphocyte-LS-TA" of TNFRSF17 is shown in FIG. 6A. The same data is converted to a MoM representation as shown in fig. 6B. In the NR group, the biomarker parameters (D7-D0) were increased in increments ranging from-1.01 to 0.67 with a median increment of 0.066. In contrast, the R group had higher incremental changes ranging from-0.13 to 3.39 with a median increment of 1.11, and the incremental changes between the NR and R groups were significantly different (paired tests, p value < 0.01).

ROC analysis was performed to determine the ability of the increment of "direct B lymphocyte-LS-TA" TNFRSF17 to distinguish between the R and NR groups from day 0 to day 7 (fig. 7A). The ability to resolve incremental values was also high AUC (AUC 0.85), comparable to that of "direct B lymphocyte-LS-TA" TNFRSF17 on day 7 alone (AUC 0.85, compare fig. 5A).

Similarly, the increase in "direct B lymphocyte-LS-TA" of TNFRSF17 in the data set GSE59635 PBMC samples (D7-D0) also provided useful information with an AUC of 0.7 (FIG. 7B).

Example 4

D7-D0 changes in "direct B lymphocyte-LS-TA" of TNFRSF17 in whole blood samples, and the ability to effectively distinguish between the two R and NR groups in other vaccinations

In data set GSE136163, whole blood samples for yellow fever inoculators were used. 2 vaccinees were assigned NR as their neutralizing antibody (nab) titers did not exceed a 4-fold increase. The median change of "direct B lymphocyte-LS-TA" of TNFRSF17 in the NR group (D7-D0) was negative (-0.28). In contrast, D7-D0 "direct B lymphocyte-LS-TA" of TNFRSF17 of the R group was amplified more (median 0.38). The data are shown in fig. 8A and 8B.

ROC analysis was performed and the AUC for "direct B lymphocyte-LS-TA" TNFRSF17 on day 7 alone was 0.82 (fig. 8C), while the AUC for the increase in "direct B lymphocyte-LS-TA" TNFRSF17 on day 0 and day 7 was higher, 0.88 (fig. 8D).

Example 5

Results of Using two additional "direct B lymphocyte LS-TA" with target genes characteristic of B lymphocytes

In addition to TNFRSF17, the TXDDC 5 and TNFRSF13B genes are two additional target genes that can be used for "direct B lymphocyte-LS-TA". In this example, the relative expression of TXNDC5 and TNFRSF13B relative to TNFRSF13C was used as a biomarker.

In data set GSE59635, data for the TXNDC5 gene was included. And is therefore analyzed with this one data set. Fig. 9A shows the increase in biomarkers from D0 to D7 in the NR and R groups. The difference between the two groups (NR and R) was significant (paired test, p value < 0.01). And the increased ROC of "direct B lymphocyte-LS-TA" TXNDC5 was analyzed, with AUC of 0.77 (fig. 9B).

Similarly using data set GSE59635, the seventh day samples alone were tested for "direct B lymphocyte-LS-TA" of TNFRSF13B versus TNFRSF13C, and it was determined that responders (group R) had higher biomarker parameters (figure 9C, p value < 0.05). ROC analysis showed that this index was able to effectively distinguish between the two R and NR groups (fig. 9D, AUC 0.81).

Example 6

Results of "direct B lymphocyte-LS-TA" Using another B lymphocyte characteristic reference Gene FCRLA

In addition to TNFRSF13C, FCRLA may also be used as another B lymphocyte reference gene. FIGS. 10A and 10B show the results and resolution performance of "direct B lymphocyte-LS-TA" using TNFRSF17 and FCRLA.

Figure 10A shows that group R has higher TNFRSF17 than group NR: increment of "direct B lymphocytes-LS-TA" for FCRLA (paired assay, p value < 0.001). FIG. 10B shows the AUC for the increment of "direct B lymphocyte-LS-TA" (TNFRSF13C, FCRLA) in ROC analysis to be 0.82 (FIG. 10B).

Example 7

"direct B lymphocyte-LS-TA" prior to cancer vaccine (PPV) vaccination is able to predict prognosis and survival probability of prostate patients

The GSE53922 database contains data on PMBC gene expression, prognosis and survival time (OS) for a multi-type monocyte sample of peripheral blood prior to 112 cancer vaccinations in prostate patients. Patients were divided into two groups, the first group being patients who survived less than one year (365 days) after treatment. The other group is patients with better treatment effect and survival more than one year after treatment. The patient's pre-PPV vaccination "direct B lymphocyte-LS-TA" biomarker parameters were then compared in both groups. In this example, the relative values of the two genes TNFRSF17 and FCRLA in a PBMC sample were used to calculate the "direct B lymphocyte-LS-TA" results.

FIGS. 11A and 11B show that the group of patients with better therapeutic effect had a lower "direct B lymphocyte-LS-TA" biomarker parameter prior to vaccination. Figure 11A shows that the "direct B lymphocyte-LS-TA" biomarker parameters were lower in patients with long survival before vaccination (P value < 0.05). ROC analysis indicated that the assay had some predictive power (AUC 0.63).

Fig. 12A is a survival analysis (survival analysis) using Cox regression (Cox regression) to calculate survival curves (survival curve) for three groups of patients, which were divided into three groups based on the "direct B lymphocyte-LS-TA" biomarker prior to vaccine injection, using a range of quantiles into three groups of (a) low (index below 25 percent), (B) middle (25 percent-75 percent), and (c) high (above 75 percent). The survival curves of the three groups are obviously different. The worst survival probability was for the group with a high "direct B lymphocyte-LS-TA" index before vaccination, most patients died almost within one year (p-value < 0.01).

In addition, the difference in survival curves was more pronounced when only the two groups with low index (below 25 percentile) and high index (above 75 percentile) were compared to each other (fig. 12B, p value < 0.001). The worst survival probability is the group with a high "direct B lymphocyte-LS-TA" index, and the risk of death (Hazard ratio) is almost three times higher than the group with a lower index (Hazard ratio 2.95, confidence interval 1.6 to 5.6).

The above results show that if prostate patients already had some B lymphocyte activity (i.e. the group with a high "LS-TA" index) before the PPV cancer vaccination, it is not much helpful to them to be vaccinated against cancer, i.e. the cancer vaccine has little value to them. Conversely, if the patient had no (or only low) B lymphocyte activity (i.e., a group with a low "LS-TA" index) prior to PPV cancer vaccination, the chance that the PPV vaccine will be helpful to them is higher, resulting in a greatly increased probability of survival for the prognosis of this group.

Example 8

Results of "direct B lymphocyte LS-TA" Using JCHAIN Gene as target Gene characteristic of B lymphocyte

In addition to the target genes characteristic of B lymphocytes already mentioned above, the JCHAIN gene is also a target gene that can be used for "direct B lymphocytes-LS-TA". In this example, meta-analysis (meta-analysis) of influenza vaccinees was performed using the relative expression of JCHAIN relative to TNFRSF13C as a biomarker.

In meta-analysis (see fig. 13), 7 data sets GSE59654, GSE59635, GSE59743, GSE101709, GSE101710, GSE29617, GSE29614 were used. The meta-analysis included 65 NR and 79R influenza vaccinees altogether. FIG. 13A shows the meta-Forest map (Forest Plot) of the expression of the biomarker on day 7 (JCHAIN/TNFRSF13C) in the NR and R groups, while FIG. 13B shows the meta-Forest map of the increase in the biomarker from day 0 to day 7 in the NR and R groups. Meta-analysis of these two expression indices differed significantly between the two groups (NR and R), giving a normalized Mean Difference (SMD) greater than zero, and the confidence interval was confirmed to be greater than zero, regardless of whether a fixed effect model and a random effect model were used. For example, fig. 13A shows that the JCHAIN gene of the R group had a higher "direct B lymphocyte LS-TA" than the NR group at day seven after the vaccine injection, and SMD was 0.75 (95% confidence region 0.39-1.11).

Example 9

General purpose laboratory procedures and kit compositions for quantifying B lymphocyte gene transcript abundance

In other embodiments, one skilled in the art will know how to design primers to determine transcript abundance of these B lymphocyte message genes.

Examples of primers that may be used for quantitative PCR (qPCR) are provided herein for reference. They can be used in the presence of SYBR Green in the qPCR reaction to obtain threshold Cycle (CT) data that can be used to determine delta-CT, delta-delta CT or efficiency corrected delta-CT as biomarker parameters by relative quantitation assays. Transcript abundance of RNA in blood samples was quantified (Dorak 2007). Other methods of quantification may also be practiced.

General laboratory procedure: first, RNA is extracted from various blood samples using Trizol or similar reagents. Commercial kits are also available for column-based RNA extraction. The RNA is then reverse transcribed into cDNA by reverse transcriptase. Specific genes are quantified by user-selected methods including qPCR, RNA sequencing, DNA microarray (gene chip), branched DNA detection (branched chain DNA, bDNA assay, US8426578B2, US7927798B2), nano-reporter probes detection (US 8415102B2), digital PCR (US10465238B2), or hybridization.

The present application teaches that cDNA samples using this method can be used for the assay of TA for both target genes of B lymphocytes (e.g., TNFRSF17, TNFRSF13B, TXNDC5 or JCHAIN) and reference genes of B lymphocytes (e.g., TNFRSF13C, FCRLA, CD79A, CD79B or MS4A1), for example, the primers listed below can be used. Biomarker parameters were calculated from delta-CT, delta-delta CT or efficiency corrected delta-CT of qPCR results for such B lymphocyte informative gene pairs. This "direct B lymphocyte-LS-TA" analysis produces biomarker parameters that provide an indication of the level of B lymphocyte gene expression in various cell mixture samples (e.g., PBMCs, WBs) in blood without prior isolation of the B lymphocytes.

A list of examples of primers used for qPCR analysis in the "direct B lymphocyte-LS-TA" assay, see Table below.

Reference to the literature

[1]CN103764848B.

[2]US9589099B2.

[3]Araki,Hiromitsu,Xiaoliang Pang,Nobukazu Komatsu,Mikiko Soejima,Nawoe Miyata,Mari Takaki,Shigeru Muta,et al.2015.“Haptoglobin Promoter Polymorphism Rs5472 as a Prognostic Biomarker for Peptide Vaccine Efficacy in Castration-Resistant Prostate Cancer Patients.”Cancer Immunology,Immunotherapy:CII 64(12):1565–73.https://doi.org/10.1007/s00262-015-1756-7.

[4]Casey,Rebecca M.,Jennifer B.Harris,Steve Ahuka-Mundeke,Meredith G.Dixon,Gabriel M.Kizito,Pierre M.Nsele,Grace Umutesi,et al.2019.“Immunogenicity of Fractional-Dose Vaccine during a Yellow Fever Outbreak-Final Report.”The New England Journal of Medicine 381(5):444–54.https://doi.org/10.1056/NEJMoa1710430.

[5]Committee for Medicinal Products for Human Use.1997.“Note for Guidance on Harmonisation of Requirements for Influenza Vaccines.”European Agency for the Evaluation of Medicinal Products,Brussels,Belgium(1997).https://www.ema.europa.eu/en/documents/scientific-guideline/note-guidance-harmonisation-requirements-influenza-vaccines_en.pdf.

[6]Dorak,M.Tevfik.2007.Real-Time PCR.Garland Science.

[7]Eisenberg,Eli,and Erez Y.Levanon.2013.“Human Housekeeping Genes,Revisited.”Trends in Genetics,Human Genetics,29(10):569–74.https://doi.org/10.1016/j.tig.2013.05.010.

[8]Henn,Alicia D.,Shuang Wu,Xing Qiu,Melissa Ruda,Michael Stover,Hongmei Yang,Zhiping Liu,et al.2013.“High-Resolution Temporal Response Patterns to Influenza Vaccine Reveal a Distinct Human Plasma Cell Gene Signature.”Scientific Reports 3(1):2327.https://doi.org/10.1038/srep02327.

[9]Mo,Zhaojun,Yi Nong,Shuzhen Liu,Ming Shao,Xueyan Liao,Kerry Go,and Nathalie Lavis.2017.“Immunogenicity and Safety of a Trivalent Inactivated Influenza Vaccine Produced in Shenzhen,China.”Human Vaccines&Immunotherapeutics 13(6):1272–78.https://doi.org/10.1080/21645515.2017.1285475.

[10]Nakaya,Helder I.,Jens Wrammert,Eva K.Lee,Luigi Racioppi,Stephanie Marie-Kunze,W.Nicholas Haining,Anthony R.Means,et al.2011.“Systems Biology of Vaccination for Seasonal Influenza in Humans.”Nature Immunology 12(8):786–95.https://doi.org/10.1038/ni.2067.

[11]Tang,Nelson Leung-Sang,Paul Kay-Sheung Chan,Chun-Kwok Wong,Ka-Fai To,Alan Ka-Lun Wu,Ying-Man Sung,David Shu-Cheong Hui,Joseph Jao-Yiu Sung,and Christopher Wai-Kei Lam.2005.“Early Enhanced Expression of Interferon-Inducible Protein-10(CXCL-10)and Other Chemokines Predicts Adverse Outcome in Severe Acute Respiratory Syndrome.”Clinical Chemistry 51(12):2333–40.https://doi.org/10.1373/clinchem.2005.054460.

[12]Thakar,Juilee,Subhasis Mohanty,A.Phillip West,Samit R.Joshi,Ikuyo Ueda,Jean Wilson,Hailong Meng,et al.2015.“Aging-Dependent Alterations in Gene Expression and a Mitochondrial Signature of Responsiveness to Human Influenza Vaccination.”Aging 7(1):38–52.https://doi.org/10.18632/aging.100720.

[13] "cancer immunotherapy" 2020.In Wikipedia, free encyclopedia. https:// zh.wikipedia.org/w/index. phititle ═ E7% 99% 8C% E7% 97% 87% E5% 85% 8D% E7% 96% AB% E7% 97% E6% B3% 95& oldid ═ 61685761.

[14]US8426578B2.

[15]US7927798B2.

[16]US8415102B2.

[17]US10465238B2.

[18]Huang,D.,Liu,A.,Leung,K.S.,&Tang,N.(2021).Direct Measurement of B Lymphocyte Gene Expression Biomarkers in Peripheral Blood Transcriptomics Enables Early Prediction of Vaccine Seroconversion.Genes,12(7),971.https://doi.org/10.3390/genes12070971.

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Claims

1. A peripheral blood sample analysis method comprising determining in a peripheral blood sample the transcript abundance of at least one B lymphocyte target gene selected from the group consisting of TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN and the transcript abundance of at least one B lymphocyte reference gene selected from the group consisting of TNFRSF13C and FCRLA.

2. Use of a reagent composition for determining gene transcript abundance in the manufacture of a kit for use in a method of peripheral blood sample analysis, wherein said method comprises determining transcript abundance of at least one B lymphocyte target gene selected from TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN and transcript abundance of at least one B lymphocyte reference gene selected from TNFRSF13C and FCRLA in a peripheral blood sample.

3. The method of claim 1 or the use of claim 2, wherein the method comprises the steps of:

a) collecting a peripheral blood sample;

b) determining transcript abundance of at least one B lymphocyte target gene of said peripheral blood sample to obtain a first amount;

c) determining transcript abundance of at least one B lymphocyte reference gene of said peripheral blood sample to obtain a second amount;

d) calculating a biomarker parameter, said parameter being the relative value of said first amount and said second amount.

4. The method of claim 1 or the use of claim 2, wherein the peripheral blood sample is a peripheral blood sample obtained prior to vaccination; or a peripheral blood sample taken after vaccination, preferably a peripheral blood sample taken 5-12 days after vaccination.

5. The method or use according to claim 4, wherein the method further comprises comparing the relative value to a cut-off value, preferably the comparison is used to predict antibody production and/or the effect of immunotherapy as a result of vaccination.

6. The method of claim 1 or the use of claim 2, wherein the peripheral blood sample comprises a first peripheral blood sample taken prior to vaccination and a second peripheral blood sample taken after vaccination; the biomarker parameters comprise a first biomarker parameter obtained from the first peripheral blood sample and a second biomarker parameter obtained from the second peripheral blood sample.

7. The method or use according to claim 6, wherein the method further comprises calculating a change value of the first and second biomarker parameters, preferably the change value is used to predict antibody production and/or the effect of immunotherapy as a result of vaccination.

8. The method or use according to any one of claims 4-7, wherein the vaccine is a prophylactic vaccine or a therapeutic vaccine, preferably the vaccine is a vaccine for the prevention of infectious diseases or a vaccine for the treatment of cancer.

9. A kit comprising reagent components for quantifying transcript abundance of a gene selected from at least one of TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, and at least one of TNFRSF13C and FCRLA.

10. Use of a reagent composition for quantifying the abundance of a gene transcript, wherein the gene is selected from at least one of TNFRSF17, TNFRSF13B, TXNDC5 and JCHAIN, and at least one of TNFRSF13C and FCRLA, in the manufacture of a kit or medicament for predicting the effectiveness of vaccination and/or the effectiveness of immunotherapy.

11. The kit of claim 9 or the use of claim 10, wherein the reagent components comprise primers having a sequence as set forth in any one of SEQ ID NOs 1-14; and preferably, said genes are obtained from a peripheral blood sample, more preferably from B lymphocytes of said peripheral blood sample.