Receptor Repertoire Profiling Research Articles

A B cell screen against endogenous retroviruses identifies glycan-reactive IgM that recognizes a broad array of enveloped viruses.

Endogenous retroviruses (ERVs), comprising a substantial portion of the vertebrate genome, are remnants of ancient genetic invaders. ERVs with near-intact coding potential reactivate in B cell-deficient mice. To study how B cells contribute to host anti-ERV immunity, we used an antigen-baiting strategy to enrich B cells reactive to ERV surface antigens. We identified ERV-reactive B-1 cells expressing germline-encoded natural IgM antibodies in naïve mice, the level of which further increases upon innate immune sensor stimulation. B cell receptor repertoire profiling of ERV-reactive B-1 cells revealed increased usage of the Igh VH gene that gives rise to glycan-specific antibodies targeting terminal N-acetylglucosamine moieties on ERV glycoproteins, which further engage the complement pathway to mediate anti-ERV responses. These same antibodies also recognize glycoproteins of other enveloped viruses but not self-proteins. These results reveal an innate antiviral mechanism of germline-encoded antibodies with broad reactivity to enveloped viruses, which constitutes a natural antibody repertoire capable of preventing the emergence of infectious ERVs.

Single-cell T-cell receptor repertoire profiling in dogs

Spontaneous cancers in companion dogs are robust models of human disease. Tracking tumor-specific immune responses in these models requires reagents to perform species-specific single cell T cell receptor sequencing (scTCRseq). scTCRseq and integration with scRNA data have not been demonstrated on companion dogs with cancer. Here, five healthy dogs, two dogs with T cell lymphoma and four dogs with melanoma are selected to demonstrate applicability of scTCRseq in a cancer immunotherapy setting. Single-cell suspensions of PBMCs or lymph node aspirates are profiled using scRNA and dog-specific scTCRseq primers. In total, 77,809 V(D)J-expressing cells are detected, with an average of 3498 (348 - 5,971) unique clonotypes identified per sample. In total, 29/34, 40/40, 22/22 and 9/9 known functional TRAV, TRAJ, TRBV and TRBJ gene segments are observed respectively. Pseudogene or otherwise defective gene segments are also detected supporting re-annotation of several as functional. Healthy dogs exhibit highly diverse repertoires, T cell lymphomas exhibit clonal repertoires, and vaccine-treated melanoma dogs are dominated by a small number of highly abundant clonotypes. scRNA libraries define large clusters of V(D)J-expressing CD8+ and CD4 + T cells. Dominant clonotypes observed in melanoma PBMCs are predominantly CD8 + T cells, with activated phenotypes, suggesting possible anti-tumor T cell populations.

Abstract 80: Toward best practices for B-cell receptor repertoire profiling

Abstract FDA anticipates that immune cell receptor profiling will become crucial to the Agency’s evaluation of the efficacy and safety of emerging cancer immunotherapies and immunomodulatory drugs by advancing precision medicine and providing orthogonal, functional evidence. High-throughput sequencing of B-cell receptor sequencing (BCR) gene rearrangements and downstream analysis empowers researchers to define the B-cell clonal landscape, as well as identify biomarkers for minimal residual disease (MRD). Although this field has made vast strides over the last decade, it lacks standardized assay controls, adequate sensitivity and specificity in gene mapping/alignment, and appropriately qualified reference data sets, materials, and validation methods. Moreover, detailed comparisons of wet-bench analytical methods or bioinformatic procedures have not appeared. The FDA led B-cell receptor sequencing quality control (BCR-SEQC) consortium is establishing protocols for the development of reference materials and data sets for the evaluation of NGS-based BCR repertoire reconstruction. The consortium is also developing materials for performance bench-marking studies. To this end, we performed whole-genome sequencing, RNAseq, and BCR-seq on 50 B-cell lines to determine the clonotype, full-length transcripts, and expression abundance of BCR genes in each cell line. Two batches of reference materials (DNA, RNA, and cells) were generated from each of nine cell lines that were determined unambiguously to be monoclonal in BCR expression of both heavy and light chains. These materials were distributed to ten companies to test up to 15 BCR-seq products. Our benchmarking studies include six widely-used sequencing technologies. The overarching objectives of this research were to elucidate current capabilities and limitations, address fundamental technical needs, provide reference materials and data sets, and establish actionable best practices for reconstructing B cell receptor repertoires from NGS data. Citation Format: Wenming Xiao, BCR-SEQC consortium. Toward best practices for B-cell receptor repertoire profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 80.

Clinical significance of peripheral T-cell receptor repertoire profiling and individualized nomograms in patients with gastrointestinal cancer treated with anti-programmed death 1 antibody.

Immune checkpoint inhibitors (ICIs) have significant clinical benefit for a subset of patients with gastrointestinal cancers (GICs) including esophageal cancer, gastric cancer and colorectal cancer. However, it is difficult to predict which patients will respond favorably to immune checkpoint blockade therapy. Thus, this study was initiated to determine if peripheral T-cell receptor (TCR) repertoire profiling could predict the clinical efficacy of anti-programmed death 1 (PD-1) treatment. Blood samples from 31 patients with GICs were collected before anti-PD-1 antibody treatment initiation. The clinical significance of the combinatorial diversity evenness of the TCR repertoire [the diversity evenness 50 (DE50), with high values corresponding to less clonality and higher TCR diversity] from peripheral blood mononuclear cells (PBMCs) was evaluated in all the enrolled patients. A highly predictive nomogram was set up based on peripheral TCR repertoire profiling. The performance of the nomogram was assessed by receiver operating characteristic (ROC) curve, concordance index (C-index), and calibration curves, and decision curve analysis (DCA) was used to assess its clinical applicability. Compared to non-responders [progression disease (PD)], the DE50 scores were significantly higher in responders [stable disease (SD) and partial response (PR)] (P=0.018). Patients with a high DE50 score showed better progression-free survival (PFS) than those with a low DE50 score (P=0.0022). The multivariable Cox regression demonstrated that high DE50 and low platelet-lymphocyte ratio (PLR) were significant independent predictors for better PFS when treated with anti-PD-1 antibody. Furthermore, a highly predictive nomogram was set up based on peripheral TCR repertoire profiling. The area under the curves (AUCs) of this system at 3-, 6- and 12-month PFS reached 0.825, 0.802, and 0.954, respectively. The nomogram had a C-index of 0.768 [95% confidence interval (CI): 0.658-0.879]. Meanwhile, the calibration curves also demonstrated the reliability and stability of the model. High DE50 scores were predictive of a favorable response and longer PFS to anti-PD-1 treatment in GIC patients. The nomogram based on TCR repertoire profiling was a reliable and practical tool, which could provide risk assessment and clinical decision-making for individualized treatment of patients.

Abstract C007: Improved T-cell and B-cell receptor repertoire profiling and immunophenotyping for biomarker discovery

Abstract T-cell receptor (TCR) and B-cell receptor (BCR) repertoire profiling, also referred to as adaptive immune receptor repertoire (AIRR) profiling, holds great potential for the understanding of disease mechanisms and for the development of new treatments in infectious disease, autoimmunity, and immuno-oncology. This potential could be greatly improved by combining information about receptor clonotypes with immunophenotypes of T- and B- cells. A new technology we developed that combines profiling of all human TCR and BCR variable regions with phenotypic characterization of immune cells using the same workflow could be particularly useful. The TCR and BCR immunophenotyping method proposed involves RT-PCR amplification and sequencing of the CDR3 regions of the TCR and BCR genes, and subsequently determining the expression levels of the most informative T- and B-cell phenotyping genes. Preliminary results show that this method allows for comprehensive profiling of all seven TCR and BCR chains from a single sample, in a highly reproducible manner, directly from micro-samples including cancer tissue, whole blood, sorted cells and more. Bioinformatic analysis of the next-generation sequencing (NGS) data from the TCR and BCR clonotypes profile combined with RNA expression profiling of the same samples results in a richer data set that includes the identification of major immune cell subtypes and their activation status. Data from human cancer tissues and whole blood samples will be presented. Citation Format: Alex Chenchik, Mikhail Makhanov, Tianbing Liu, Dongfang Hu, Khadija Ghias, Lester Kobzik. Improved T-cell and B-cell receptor repertoire profiling and immunophenotyping for biomarker discovery [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C007.

84P T cell receptor repertoire profiles of tumor -infiltrating lymphocytes improves neoantigen prioritization for personalized cancer immunotherapy

84P T cell receptor repertoire profiles of tumor -infiltrating lymphocytes improves neoantigen prioritization for personalized cancer immunotherapy

EP03.03-07 T-Cell Receptor Repertoire Profiling as a Predictive Biomarker for Immunotherapy in Unresectable Stage III Non-small Cell Lung (NSCLC)

EP03.03-07 T-Cell Receptor Repertoire Profiling as a Predictive Biomarker for Immunotherapy in Unresectable Stage III Non-small Cell Lung (NSCLC)

Response to 'comment on rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing' by Davydov A.N.; Bolotin D.A.; Poslavsky S. V. and Chudakov D.M.

Response to 'comment on rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing' by Davydov A.N.; Bolotin D.A.; Poslavsky S. V. and Chudakov D.M.

Comment on 'rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing'.

Transcriptome sequencing has become common in cancer research, resulting in the generation of a substantial volume of RNA sequencing (RNA-Seq) data. The ability to extract immune repertoires from these data is crucial for obtaining information on infiltrating T- and B-lymphocyte clones when dedicated amplicon T-cell/B-cell receptors sequencing (TCR-Seq/BCR-Seq) methods are unavailable. In response to this demand, several dedicated computational methods have been developed, including MiXCR, TRUST and ImRep. In the recent publication in Briefings in Bioinformatics, Peng etal. have conducted an intensive, systematic comparison of the three previously mentioned tools. Although their effort is commendable, we do have a few constructive critiques regarding technical elements of their analysis.

A current and future perspective on T cell receptor repertoire profiling.

T cell receptors (TCR) play a vital role in the immune system's ability to recognize and respond to foreign antigens, relying on the highly polymorphic rearrangement of TCR genes. The recognition of autologous peptides by adaptive immunity may lead to the development and progression of autoimmune diseases. Understanding the specific TCR involved in this process can provide insights into the autoimmune process. RNA-seq (RNA sequencing) is a valuable tool for studying TCR repertoires by providing a comprehensive and quantitative analysis of the RNA transcripts. With the development of RNA technology, transcriptomic data must provide valuable information to model and predict TCR and antigen interaction and, more importantly, identify or predict neoantigens. This review provides an overview of the application and development of bulk RNA-seq and single-cell (SC) RNA-seq to examine the TCR repertoires. Furthermore, discussed here are bioinformatic tools that can be applied to study the structural biology of peptide/TCR/MHC (major histocompatibility complex) and predict antigenic epitopes using advanced artificial intelligence tools.

Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing.

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.

T-cell and B-cell receptor repertoire profiling for biomarker discovery

Abstract T-cell receptor (TCR) and B-cell receptor (BCR) repertoire profiling, also referred to as adaptive immune receptor repertoire (AIRR) profiling, holds great potential for the understanding of disease mechanisms and for the development of new treatments in infectious disease, autoimmunity and immuno-oncology. This potential could be greatly improved by combining information about receptor clonotypes with immunophenotypes of T- and B-cells. We developed a new technology for combined profiling of all human TCR and BCR variable regions and phenotypic characterization of immune cells in the same workflow. The TCR and BCR immunophenotyping method involves RT-PCR amplification and sequencing of the CDR3 regions of the TCR and BCR genes, as well as determining the expression levels of the most informative T- and B-cell phenotyping genes. Results show that this method allows for comprehensive profiling of all seven TCR and BCR chains from a single sample, in a highly reproducible manner, directly from micro-samples including cancer tissue, whole blood, sorted cells and more. Bioinformatic analysis of the next-generation sequencing (NGS) data allows profiling of the TCR and BCR clonotypes and identifcation of major immune cell subtypes and their activation status. Preliminary data from rheumatoid arthritis blood samples and others will be presented.

Predictive value of T cell receptor repertoire profiling for immunosuppressive therapy in severe aplastic anemia

Predictive value of T cell receptor repertoire profiling for immunosuppressive therapy in severe aplastic anemia

Abstract LB172: Improved T-cell and B-cell receptor repertoire profiling and immunophenotyping for biomarker discovery

Abstract T-cell receptor (TCR) and B-cell receptor (BCR) repertoire profiling, also referred to as adaptive immune receptor repertoire (AIRR) profiling, holds great potential for the understanding of disease mechanisms and for the development of new treatments in infectious disease, autoimmunity, and immuno-oncology. This potential could be greatly improved by combining information about receptor clonotypes with immunophenotypes of T- and B- cells. A new technology we developed that combines profiling of all human TCR and BCR variable regions with phenotypic characterization of immune cells using the same workflow could be particularly useful. The TCR and BCR immunophenotyping method proposed involves RT-PCR amplification and sequencing of the CDR3 regions of the TCR and BCR genes, and subsequently determining the expression levels of the most informative T- and B-cell phenotyping genes. Preliminary results show that this method allows for comprehensive profiling of all seven TCR and BCR chains from a single sample, in a highly reproducible manner, directly from micro-samples including cancer tissue, whole blood, sorted cells and more. Bioinformatic analysis of the next-generation sequencing (NGS) data from the TCR and BCR clonotypes profile combined with RNA expression profiling of the same samples results in a richer data set that includes the identification of major immune cell subtypes and their activation status. Data from human cancer tissue and whole blood samples will be presented. Citation Format: Alex Chenchik, Mikhail Makhanov, Tianbing Liu, Dongfang Hu, Paul Diehl, Lester Kobzik. Improved T-cell and B-cell receptor repertoire profiling and immunophenotyping for biomarker discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB172.

Best practices for single-cell analysis across modalities.

Recent advances in single-cell technologies have enabled high-throughput molecular profiling of cells across modalities and locations. Single-cell transcriptomics data can now be complemented by chromatin accessibility, surface protein expression, adaptive immune receptor repertoire profiling and spatial information. The increasing availability of single-cell data across modalities has motivated the development of novel computational methods to help analysts derive biological insights. As the field grows, it becomes increasingly difficult to navigate the vast landscape of tools and analysis steps. Here, we summarize independent benchmarking studies of unimodal and multimodal single-cell analysis across modalities to suggest comprehensive best-practice workflows for the most common analysis steps. Where independent benchmarks are not available, we review and contrast popular methods. Our article serves as an entry point for novices in the field of single-cell (multi-)omic analysis and guides advanced users to the most recent best practices.

Advancing CAR T cell therapy through the use of multidimensional omics data.

Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the treatment of certain haematological malignancies, challenges remain in optimizing CAR designs and cell products, improving response rates, extending the durability of remissions, reducing toxicity and broadening the utility of this therapeutic modality to other cancer types. Data from multidimensional omics analyses, including genomics, epigenomics, transcriptomics, T cell receptor-repertoire profiling, proteomics, metabolomics and/or microbiomics, provide unique opportunities to dissect the complex and dynamic multifactorial phenotypes, processes and responses of CAR T cells as well as to discover novel tumour targets and pathways of resistance. In this Review, we summarize the multidimensional cellular and molecular profiling technologies that have been used to advance our mechanistic understanding of CAR T cell therapies. In addition, we discuss current applications and potential strategies leveraging multi-omics data to identify optimal target antigens and other molecular features that could be exploited to enhance the antitumour activity and minimize the toxicity of CAR T cell therapy. Indeed, fully utilizing multi-omics data will provide new insights into the biology of CAR T cell therapy, further accelerate the development of products with improved efficacy and safety profiles, and enable clinicians to better predict and monitor patient responses.

The use of non-functional clonotypes as a natural calibrator for quantitative bias correction in adaptive immune receptor repertoire profiling.

High-throughput sequencing of adaptive immune receptor repertoires is a valuable tool for receiving insights in adaptive immunity studies. Several powerful TCR/BCR repertoire reconstruction and analysis methods have been developed in the past decade. However, detecting and correcting the discrepancy between real and experimentally observed lymphocyte clone frequencies are still challenging. Here, we discovered a hallmark anomaly in the ratio between read count and clone count-based frequencies of non-functional clonotypes in multiplex PCR-based immune repertoires. Calculating this anomaly, we formulated a quantitative measure of V- and J-genes frequency bias driven by multiplex PCR during library preparation called Over Amplification Rate (OAR). Based on the OAR concept, we developed an original software for multiplex PCR-specific bias evaluation and correction named iROAR: immune Repertoire Over Amplification Removal (https://github.com/smiranast/iROAR). The iROAR algorithm was successfully tested on previously published TCR repertoires obtained using both 5' RACE (Rapid Amplification of cDNA Ends)-based and multiplex PCR-based approaches and compared with a biological spike-in-based method for PCR bias evaluation. The developed approach can increase the accuracy and consistency of repertoires reconstructed by different methods making them more applicable for comparative analysis.

High activation levels maintained in receptor-binding domain-specific memory B cells in people with severe coronavirus disease 2019.

The long-term health consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are still being understood. The molecular and phenotypic properties of SARS-CoV-2 antigen-specific T cells suggest a dysfunctional profile that persists in convalescence in those who were severely ill. By contrast, the antigen-specific memory B-cell (MBC) population has not yet been analyzed to the same degree, but phenotypic analysis suggests differences following recovery from mild or severe coronavirus disease 2019 (COVID-19). Here, we performed single-cell molecular analysis of the SARS-CoV-2 receptor-binding domain (RBD)-specific MBC population in three patients after severe COVID-19 and four patients after mild/moderate COVID-19. We analyzed the transcriptomic and B-cell receptor repertoire profiles at ~2 months and ~4 months after symptom onset. Transcriptomic analysis revealed a higher level of tumor necrosis factor-alpha (TNF-α) signaling via nuclear factor-kappa B in the severe group, involving CD80, FOS, CD83 and TNFAIP3 genes that was maintained over time. We demonstrated the presence of two distinct activated MBCs subsets based on expression of CD80hi TNFAIP3hi and CD11chi CD95hi at the transcriptome level. Both groups revealed an increase in somatic hypermutation over time, indicating progressive evolution of humoral memory. This study revealed distinct molecular signatures of long-term RBD-specific MBCs in convalescence, indicating that the longevity of these cells may differ depending on acute COVID-19 severity.

T Cell Receptor Repertoire Profiling Reveals Breadth of Cellular Responses Against Sars-Cov-2 after Natural Infection and Vaccination in Allogeneic Hematopoietic Stem Cell Transplant Recipients

Background: Allogeneic hematopoietic stem cell transplantation (HSCT) is still associated with significant morbidity and mortality related to infectious complications, with viral infections being the most frequent infectious events. Allogenic HSCT recipients have a higher risk to develop severe forms of COVID-19 compared to the general population. Prevention by vaccination is critically important in allogeneic HSCT recipients but impaired humoral and cellular responses have been reported. To gain further insights into the immune defects leading to impaired immune responses to SARS-CoV-2 in allogeneic HSCT recipients, we performed in the present study high-throughput T cell receptor (TCR) repertoire profiling of cells recovered from allogeneic HSCT recipients or healthy controls (HC) after SARS-CoV2 natural infection or mRNA-based vaccination. Methods: Peripheral blood samples were obtained from allogeneic HSCT recipients after a median of 3 months (range 2-7) after COVID-19 infection (n=11) or 44 days (range 24-166) after vaccination with 3 doses of mRNA-based SARS-CoV-2 vaccines in SARS-CoV2 infection-naive patients (n=13). Median time since HSCT to SARS-CoV-2 infection was 24 months (range 11-79) and to last vaccination was 22.5 months (range 7-174). Healthy controls at 1 to 3 months after SARS-CoV-2 infection (n=10) or vaccination served as controls (n=10). SARS-CoV-2- specific T cell clonotypes were identified by genomic DNA T-cell receptor (TCR) sequencing (immunoSEQ® T-MAP™ COVID, Adaptive). SARS-CoV-2-specific T cell responses were quantified based on IFN-γ release against a range of peptides from the SARS-CoV-2 Spike protein (S) as well as from the membrane glycoprotein (M) and the nucleocapside phosphoprotein (N) using an Enzyme-Linked ImmunoSpot (ELISpot) assay. Results: SARS-CoV-2- specific T cell clonotypes were detectable in both HC and HSCT recipients after COVID-19 infection (Figure 1A). After adjusting for recovered T cell numbers, HSCT recipients displayed significantly reduced SARS-CoV-2-specific T cell clonotypes compared with HC (p=0.0037; Figure 1B). Such a difference was maintained when T cell clonotypes specific for the S protein (p=0.0011) or the N and M proteins (p=0.036) were analyzed. As predicted, HSCT recipients displayed a less diverse TCR repertoire compared with HC as revealed by higher Simpson clonality (p= 0.0079). Interestingly, the Simpson clonality negatively correlated with the number of different SARS-CoV-2-specific T cell clonotypes (r2=0.86, p=4.8e−06; Figure 1C). According to the TCR-seq results, we observed significantly lower numbers of IFN-γ spot forming units after stimulation of PBMCs from HSCT recipients with peptides from both the S protein (p=0.0068) and the M plus N proteins (p=0.0067) compared with HC. Performing the same analysis after SARS-CoV-2 mRNA vaccination, we observed a significant reduction in S-protein-specific T cell clonotypes in allogeneic HSCT recipient compared to HC (p=0.0003; Figure 1D-E). We detected a significantly negative correlation between the Simpson clonality and the number of different S-protein specific T cell clonotypes after vaccination (r2=0.55, p=7.8e-05; Figure 1F). ELISpot analysis of PBMCs recovered after vaccination and stimulated with S-protein peptides revealed significantly lower numbers of IFN-γ spot forming units in HSCT recipients compared with HC (p= 0.019), confirming the results obtained by TCR-seq. Conclusions: Our results indicate that allogeneic HSCT recipients display a defect in cellular SARS-CoV-2-specific responses after COVID-19 infection and vaccination. Such impairment was both quantitative, as revealed by reduced IFN-γ release upon stimulation with SARS-CoV-2 peptides, and qualitative as demonstrated by the reduced breadth of SARS-CoV-2-specific T cell clonotypes. Such impairment was associated with increased T-cell clonality after HSCT, pointing to the reduced diversity of the TCR repertoire as a mechanism leading to impaired cellular responses against SARS-CoV-2 in HSCT recipients. SARS-CoV-2 infection represents an unprecedented opportunity to study the immune responses established in allogeneic HSCT recipients against a new pathogen that either the donor or the HSCT recipient have never been exposed to. Our findings provide insights into our understanding of immune-dysfunction after allogeneic HSCT. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Abstract 5021: Accurate quantification of infiltrating B cell composition and clone diversity in tumor samples

Abstract Tumors harbor a complex ecosystem of malignant, immune, and stromal cells. While malignant cells dictate much of the tumor biology, there is evidence that the tumor microenvironment (TME) also plays a major role in disease etiology. Given the complexity and abundance of the TME cellular composition, investigating the role of immune cell types will yield novel biomarkers for tumor progression and response to therapies. The role of B cells as a prognostic biomarker remains elusive. For instance, infiltrating B cells in CRC have both positive and negative prognostic value. Thus, a scalable approach to quantify B cells and the B-cell receptor (BCR) repertoire could yield novel insights into the role of B cells in tumor biology. To address this, we have developed immune cell quantification (InfiltrateID࣪) and immune receptor repertoire profiling (RepertoireID࣪) methods as part of the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform. We estimate B cell abundance and BCR repertoire by profiling FFPE and PBMC samples using ImmunoID NeXT࣪. In expanding upon InfiltrateID to further estimate B cell abundance, here we regress the bulk RNA-seq readout from a reference signature from purified immune cell types. We also generate orthogonal quantifications of B cell abundance by profiling samples with cytometry by time of flight, single-cell RNA-seq, flow cytometry, and immunohistochemistry (IHC). We compare BCR results from ImmunoID NeXT to a standalone sequencing approach to evaluate the concordance of top clones. We then utilize BCR profiling from ImmunoID NeXT to analyze clonality and isotype composition in tumor samples. We first use InfiltrateID to estimate absolute B cell fractions in over 50 samples. Overall, we observe a high correlation between InfiltrateID results and orthogonal data sets in both PBMC and tumor FFPE samples (R2=0.90). When comparing BCR results from RepertoireID to a standalone BCR sequencing method that profiles IgM and IgG, we identify 475 and 387 of the top 500 clones in IgG and IgM, respectively, with highly concordant abundances across all clones (R2>0.72 and R2>0.82 in IgM and IgG, respectively). Next, we use InfiltrateID to estimate absolute B cell fractions in over 650 samples from 14 tumor types. On average, samples display B cell fractions in agreement with the literature and IHC quantifications, with higher B cell fractions in lung, breast, and cervical tumors. We also observe a range of BCR clonality values across tumor types. Finally, we observe differences in B cell composition and repertoire diversity in tumor samples from patients who underwent checkpoint blockade therapy. We show that InfiltrateID and RepertoireID accurately capture the composition and clone diversity of infiltrating B cells in tumor samples. Citation Format: Fabio Navarro, Eric Levy, Pamela Milani, Qiang Li, Shruti Bhide, Upasana Dutta, Charles W. Abbott, Jose Jacob, Rena McClory, John West, John Lyle, Sean Boyle, Richard O. Chen. Accurate quantification of infiltrating B cell composition and clone diversity in tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5021.