Abstract We developed a streamlined workflow linking adaptive immune receptor (AIR) profiling to antigen-specific functional screening for cancer-relevant T-cell receptor (TCR) and B-cell receptor (BCR) discovery. Bulk AIR sequencing of DNA and RNA from matched samples quantified clonal expansion while distinguishing transcriptionally activated tumor-infiltrating lymphocytes. Paired TCR chains were obtained using a 96-well plate-based, multiplex single-cell assay for TCR α β chain-pairs together with 36 T-cell marker genes, enabling simultaneous identification of full-length receptor sequences and functional phenotype.Reconstructed paired TCRs were cloned into GFP-reporter Jurkat cells, which were then screened using antigen-binding dextramers and co-cultured with K562 APCs expressing tumor-associated peptides. Reporter activation provided a sensitive readout of antigen recognition and allowed ranking of tumor-specific clonotypes. In proof-of-principle studies, the single-cell assay identified the most abundant TCR-α β clonotype in leukemic T cells (35 wells) and revealed co-expression of NKG7 and CCL5, markers associated with cytotoxic activation in cancer. Functional assays confirmed antigen-responsive signaling in the engineered Jurkat cells.This integrated workflow—from repertoire profiling to TCR-α β chain-pair reconstruction and antigen validation—will enable rapid discovery of tumor-associated clonotypes, characterization of cancer-specific immune responses, and the development of receptor-based cellular immunotherapies. Citation Format: Alex Chenchik, Tianbing Liu, Dongfang Hu, Kitt Paraiso, Lester Kobzik, Khadija Ghias, Paul Diehl. A practical workflow for adaptive immune receptor profiling and screening of antigen-specific clonotypes with applications in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 476.

Antigen-specific T cell populations are of great value for studying immune recognition but tedious to generate by limiting dilution or cloning. Here, we develop a streamlined approach to generate antigen-specific T cell clones directly from peripheral blood using the cloneXplorer, a live-cell analysis and clone isolation platform based on conical microwell arrays. This platform continuously monitors cell proliferation, cytokine secretion, and surface markers in up to 100,000 single cell co-cultures, enabling the identification of rare, functionally defined T cells, which can be recovered for clonal expansion or sequence analysis. We benchmark the platform by performing several key demonstrations. First, we show that this platform can efficiently generate monoclonal cell populations from cell lines and human T cells. Next, we demonstrate that antigen-specificity can be identified at single cell resolution using a co-culture of Jurkat cells expressing NFAT-GFP, CD8, and a T cell receptor and K562 antigen presenting cells (APC) expressing a peptide library. Thereafter, we show that immune activation in mouse and human primary samples can be monitored by time lapse analysis of Interferon gamma (IFN-γ) secretion in individual microwell co-cultures using a fluorescent sandwich assay. Finally, we combine these capabilities in a proof-of-concept demonstration, which uses IFN-γ secretion and the presence of CD8 surface markers as hierarchical gates to isolate and expand antigen-specific T cells from human peripheral blood, and we verify their specificity by tetramer staining. Together, these results showcase potential applications of the cloneXplorer platform in cell line development, and in screening and validating immune receptor interactions with specific antigens.

Abstract Introduction To facilitate the discovery of epitopes or immune therapy targets for researchers without ready access to expensive instrumentation or reagents, we present a cost-effective, simplified workflow for single-cell immune receptor (TCR/BCR) profiling. Methods We use a standard 96-well plate; T- or B-cells are flow-sorted into wells, primers for immune receptor and key marker genes are added, followed by multiplex RT-PCR and next-generation sequencing (NGS). Novel validator barcodes (VBCs) ensure robust clonotype quantification with minimal cross-well contamination. There are two workflow options: one can either 1) flow-sort 96 individual cells onto a plate, or 2) serially dilute ∼10,000 cells (∼100 cells/well in a 96-well plate), which allows for thorough characterization of each receptor in larger cell populations. Results Data analysis with MiXCR software yields full-length receptor chain-pair sequences, clonotype abundance, and gene expression profiles. Single-cell results show 86% of the sorted cells had an associated clonotype, 65% had a TCR-αβ chain pair. Conclusion This sensitive assay is ideal for working with rare or enriched cell populations of a few thousand cells. The single-day workflow, which includes pooling of a 96-well plate into one reaction and profiling multiple plates in one batch, drops assay costs to ∼10 cents/cell. The approach will facilitate applications such as engineering T-cell-based therapies, antibody synthesis, and epitope discovery for cancer or autoimmune diseases. Funding Source N/A Topic Categories Technological Innovations in Immunology (TECH)

Abstract Introduction Despite the critical role of T-cell receptors (TCRs) in adaptive immunity, experimental validation of predicted cognate antigens remains a major challenge. Methods For screening TCR-epitope interaction, we developed Jurkat-NFAT-GFP reporter cells expressing TCRs of interest and co-cultured them with K562 antigen-presenting cells (APCs) expressing peptide libraries in a single-chain trimer (peptide—B2M—HLA-A) format. To enhance HLA surface expression, we introduced a G2C mutation in the G4S linker of the single-chain trimer. TCR activation, cell proliferation, and cytotoxicity were monitored using a novel microwell ELISpot assay, where GFP expression signaled functional TCR—peptide—MHC interactions. Cells from GFP+ wells were isolated using CloneXplorer colony picker for NGS to identify cognate epitopes and TCRs. For proof of concept, a library of ∼100 peptides (cancer-associated and viral peptides) were short-listed using the DETECT algorithm and expressed in K562 cells, and tested against Jurkat cells expressing CMV, MART1, p53, and Flu TCRs. Microarrays were used to establish tens of thousands of Jurkat/K562 co-cultures for each TCR construct. Peptide identity was determined by sequencing isolated cells to match the expected TCR specificity. Results For proof of concept, a library of ∼100 peptides (cancer-associated and viral peptides) were short-listed using the DETECT algorithm and expressed in K562 cells, and tested against Jurkat cells expressing CMV, MART1, p53, and Flu TCRs. Microarrays were used to establish tens of thousands of Jurkat/K562 co-cultures for each TCR construct. Peptide identity was determined by sequencing isolated cells to match the expected TCR specificity. Conclusion This end-to-end platform enables high-throughput discovery to screen 1000s of peptides, and functional characterization of TCR—peptide—MHC interactions. It has broad applications in cancer immunotherapy and vaccine development. Funding Source N/A Topic Categories Technological Innovations in Immunology (TECH)

Abstract We present a streamlined, plate-based single-cell adaptive immune receptor (AIR) profiling technology that enables the discovery and detailed characterization of disease-relevant TCR clonotypes in cancer-associated T cells. Using a scalable 96-well plate workflow, flow-sorted single cells are individually isolated for multiplex RT-PCR of TCR α β chains together with 36 immunophenotyping genes, followed by Illumina NextSeq sequencing. The approach leverages MiXCR and RCEM software pipelines to deliver full-length paired TCR sequences, high-resolution clonotype frequency data, and a profile of key gene expression markers. Applied to longitudinal samples from T-cell large granular lymphocytic leukemia (T-LGL) patients, this method identified both dominant and rare clonotypes--with functional annotation--across multiple timepoints, including a case with a single expanded cytotoxic effector-memory T-cell clone (n=35 wells, with elevated NKG7 and CCL5 levels). High-throughput, “mini-bulk” configurations (approx. 100 cells/well) allow broader repertoire screening of ∼10,000 cells/plate, detecting thousands of unique β chains and α β pairs, and facilitating the identification of rare, disease-associated clonotypes missed by bulk or lower-throughput methods.This rapid, cost-effective (<$0.10/cell), single-day workflow supports large-scale translational studies, providing direct access to paired receptor and phenotypic signatures from a variety of samples without reliance on microfluidics platforms or complex barcoding techniques. The technology significantly expands capacity for immunogenomic discovery and functional immunophenotyping, making it suited for biomarker validation, immunotherapy development, and real-time immune monitoring in cancer research. Citation Format: Alex Chenchik, Tianbing Liu, Dongfang Hu, Kitt Paraiso, Lester Kobzik, Khadija Ghias, Paul Diehl. High-throughput, 96-well plate-based single-cell TCR sequencing for scalable chain-pairing and immunophenotyping of cancer-associated T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6515.

Despite the key role of T-cell receptors (TCRs) in adaptive immune responses, experimental validation of interactions between activated TCRs and cognate antigens remains a holy grail in developing novel molecular and cell-based therapeutics. To facilitate efficient screening of TCR-antigen interactions, we engineered both reporter Jurkat-NFAT-GFP cells to express candidate-activated TCRs, and antigen-presenting K562-HLA cells (APC) expressing a library of predicted peptide epitopes. To detect antigen-activation of Jurkat cells interacting with cognate epitopes, the K562 cells were engineered to express a single-chain variable fragment (scFv) which could bind IL2 released by the activated Jurkat-TCR cells. Jurkat-TCR reporter cells co-cultured with K562-APC cells induce expression of the HLA cognate epitope, which enables them to be labeled with PE anti-IL2 antibody and purified by FACS. The cognate epitope is characterized using NGS. To validate this TCR-epitope library screening system, we constructed and expressed a library of ∼100 cancer-associated epitopes in K562-HLA_A02:01 cells. The K562-HLA-epitope library was then co-cultured with the Jurkat reporter cells expressing MART1 TCR, NY-ESO-1 TCR or, as a control, CMV TCR. After staining with the IL2 antibody and FACS selection, stained APC cells detected specific epitopes with high specificity for cancer-associated and control TCRs. Debbie Deng, Tianbing Liu, Kitt Paraiso, Paul Diehl, Alex Chenchik. Screens to identify TCR-specific epitopes using engineered antigen-presenting cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5495.

Despite the key role of T cell receptors (TCR) in the adaptive immune response, experimental validation of the interaction between activated TCRs and computationally predicted cognate antigens remains the holy grail in the development of novel molecular and cell-based therapeutics. To facilitate high-throughput screening of specific TCR-antigen interactions, we developed a universal artificial cellular system based on Jurkat-NFAT-GFP reporter cells expressing candidate-activated TCRs, and K562-HLA antigen-presenting cells (APC) expressing a library of computationally predicted peptide epitopes. For the detection of antigen-activated Jurkat cells interacting with a cognate epitope, K562 cells were engineered to express a single-chain variable fragment (scFv) that could bind IL2 released by activated Jurkat-TCR cells. When K562 APC expressing HLA-cognate epitopes are co-cultured with Jurkat-TCR reporter cells, K562 cells expressing TCR-specific epitopes are labeled with PE anti-IL2 antibody, purified by FACS, and the cognate epitope is detected by NGS. To validate the TCR-epitope library screening system, we constructed an expression library of 129 cancer-associated epitopes in K562-HLA_A02:01 cells. The K562-HLA-epitope library was co-cultured with Jurkat reporter cells expressing MART1 TCR, NY-ESO-1 TCR, or as a control, CMV TCR. By staining & FACS selection of IL2 antibody-stained APCs, we detected specific epitopes with high specificity for cancer-associated & control TCRs. Technological Innovations in Immunology (TECH)

Different methodologies exist for single-cell CRISPR (scCRISPR) screens, each with its own requirements concerning sgRNA scaffold, sgRNA library vector design, instrumentation, and reagents. This study compares the performance of three distinct scCRISPR protocols: 10X Genomics 3’ scCRISPR, CROP-Seq (using a modified 10X 3’ scCRISPR protocol), and 10X Genomics 5’ scCRISPR. 10X 3’ scCRISPR relies on the CS1 capture sequence inserted in the sgRNA tracr to detect expressed sgRNAs. CROP-Seq protocol requires the sgRNA sequences to be embedded in an expressed mRNA for detection. 10X Genomics 5’ scCRISPR detects sgRNAs without the need for scaffold modifications or inclusion in a mRNA transcript. A modification of the 10X 5’ scCRISPR protocol also allowed us to incorporate sc-targeted RNA-seq, decreasing NGS costs and potentially leading to better transcriptional profiling data. The findings of the study showed that while the CROP-Seq and 10X-CS1 approaches are equally effective for single-cell sgRNA detection and gene expression profiling, the CROP-seq approach was superior in the sgRNA’s ability to induce the expected phenotype. The 10X 5’ scCRISPR protocol proved to be superior to both CROP-Seq and 10X-CS1 in sgRNA detection, and comparable if not better to CROP-seq in gene expression profiling and sgRNA activity. Also, the 5’ scCRISPR targeted RNAseq approach proved to be technically successful, although it did not provide the expected transcriptional profiling improvement. Given the ease of use, the quality of the results, and the lack of need for specialized sgRNA scaffold or library design, 10X 5’ scCRISPR should be the protocol of choice for scCRISPR screens utilizing the 10X Genomics platform. Donato Tedesco, Tianbing Liu, Mikhail Makhanov, Nadya Isachenko, Dongfang Hu, Paul Diehl, Alex Chenchik. Comparison of three single-cell CRISPR-Seq protocols on the 10X Genomics platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2772.

TCR- and BCR-sequencing (TCR/BCR-seq) are two important technologies in studying the immune repertoire of samples such as PBMCs or tumors. In their most common form, these assays combine multiplex PCR of the repertoire using primers targeting regions of the V(D)J and the constant region with next-generation sequencing (NGS). The data produced by this assay provide a slew of information regarding immune repertoire(s) including the presence critical clonotypes, repertoire diversity, variable (V) gene usage, analysis of public clonotypes, etc. One issue that can arise during generation of the TCR/BCR-seq data is sequence bias during the PCR or NGS steps. To combat this, unique molecular identifiers (UMIs) have been used to identify and eliminate sequence bias. However, UMI fragments can be long and very diverse, resulting in the UMI sequences interfering with any of the multitude of primers during multiplex PCR. Here, we introduce Validator Barcodes (VBCs), a set of eight short barcodes (6-9 nucleotides in length). This compact set of barcodes improves PCR efficiency and facilitates PCR primer designs. Also, like UMIs, the VBCs may be used to estimate the number of template molecules (RNA or DNA). Using VBC-labeled primers for TCR and BCR repertoire profiling from PBMCs produces highly comparable results and similarly template values to those obtained through UMI-based assay counts. Overall, VBCs are a useful and simpler alternative to UMIs in assaying TCR and BCR repertoires. ### Competing Interest Statement The authors have declared no competing interest.

Murine disease models can reveal mechanisms and allow testing of drug/vaccine interventions. Current approaches often rely on evaluation after euthanasia, with large numbers of animals needed for time course and dose-response studies. Measuring blood transcriptome biomarkers in small volumes (serially) could provide useful insights and reduce the number of animals needed. We evaluated the utility of repeated (non-lethal) small-volume blood sampling for profiling RNA expression in the same mice at different stages of tuberculosis progression and treatment: 1) before infection (day 0), 2) at the peak of infection (d30 after infection), 3) after 10 weeks of isoniazid (INH) treatment (days 30-99 post-infection), and 4) after partial INH treatment (days 30-70 post-infection) to allow relapse (days 70 – 99 post-infection). We isolated RNA from 100 uL of whole blood for transcriptome profiling using the DriverMap™ assay for quantitation of ∼4700 key mouse genes using a targeted sequencing panel. Blood transcriptome profiling showed abundant up-regulation of immune and inflammatory genes at d30 after infection (e.g. 571DEGs). Additional changes were found after either complete or partial INH treatment (e.g. complete vs d30 after infection: 321DEGs). The data reveal heterogeneity in responses & allow comparisons using each mouse as its own control. Transcriptome profiling using non-terminal, serial blood samples can inform biomarker discovery/monitoring & reduce animal use & costs. Technological Innovations in Immunology (TECH)

Abstract Single-cell immune receptor profiling is a revolutionary approach that allows investigators to combine clonotype repertoire identification with paired-chain information and the phenotype of cells (e.g., cell subtype). Single-cell immune receptor profiling can be performed using a medium-throughput approach (1,000-5,000 cells) using microwell arrays or droplet microfluidics technologies. However, these assays are more complicated to run and require expensive reagents and limited sequencing throughput when compared to bulk immune receptor profiling methods. Here, we describe a low-throughput, single-cell immune profiling strategy using sorted cells in 96-well plates. The plate is pre-aliquoted with either T-cell receptor (TCR) ɑ/β or TCR γ/δ primers along with 30 crucial T-cell markers. We perform multiplex RT-PCR amplification and sequencing of the CDR3 regions. The resulting data provides the abundant clonotype counts along with the chain pairing information for these ɑ/β and γ/δ chains, together with the T-cell subtype information using gene-expression profiles. By analyzing the TCR gene rearrangement at the single-cell level, researchers can better understand T cell development, proliferation, and clonality, which are crucial for studying diseases such as cancer, immunodeficiency, and autoimmunity. Furthermore, single-cell TCR sequencing when combined with RNA sequencing datasets, facilitates the identification of γδ T cells. This method provides a standardized tool for identifying potential γδ T cell-based cancer immunotherapies. The technology's cost-effectiveness and ability to analyze clonotypes and immunophenotypes of cells in a single assay make it a valuable tool for unraveling the immune dynamics in various diseases. Citation Format: Alex Chenchik, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Lester Kobzik, Khadija Ghias, Paul Diehl. Single-cell TCRɑ/β and TCRγ/δ immune receptor profiling and immunophenotyping using a 96-well plate sorted-cell approach [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 3976.

Abstract Microsampling lancet-induced blood drops enables frequent and comprehensive analysis of various metabolites, lipids, cytokines, and proteins. This approach holds promise for monitoring immunotherapy patients using RNA biomarkers, but a suitable method for processing RNA has been lacking. In this study, we employed a targeted RNA-sequencing protocol, the DriverMap™ EXP assay, to process 30 ul of dried blood. We compared the gene expression profile in traditionally collected blood samples with that of blood absorbed onto a Mitra® microsampling device containing an RNA-stabilization reagent. Following endotoxin incubation, RNA was extracted from stimulated and unstimulated blood samples. Targeted PCR amplification of 274 immune/inflammatory genes using the DriverMap targeted RNA-Seq protocol demonstrated robust detection and high correlation (r = 0.94) between the two methods in both unstimulated and endotoxin-stimulated blood. Moreover, differentially expressed genes (DEGs) identified in standard and microsampling methods exhibited substantial overlap with publicly available datasets from similar experiments. Furthermore, we compared whole blood extracted from Tempus™ blood RNA tubes to Mitra microsamples pre- and post-immunization with the Pneumovax® vaccine using the DriverMap EXP genome-wide 19K panel for targeted RNA-sequencing. We observed approximately 90% overlap in the top 10K genes between Tempus and Mitra microsamples. Notably, microsamples stored at 4ºC for over a year exhibited similar expression profiles to more recently drawn whole blood samples. Citation Format: Lester Kobzik, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Khadija Ghias, Paul Diehl, Alex Chenchik. Targeted RNA-seq of dried blood microsamples for convenient RNA biomarker monitoring [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 5643.

Background and Hypothesis: T cell large granular lymphocytic leukemia (T-LGL) is characterized by the clonal expansion of CD8+ cytotoxic T cells. Most cases have a gain of function mutation in either the STAT3 or STAT5B transcription factor gene ,The transformation of single CD8+ T cells results in a distinct rearranged T-cell receptor gene (TCR) clonotype at the time T-LGL presents. The clonality and activating STAT mutations are virtually pathognomonic for the disease. One open question in the field is whether the clonal TCR plays a role in the pathogenesis of T-LGL or the disease process. For example, patients often present with autoimmune manifestations such as rheumatoid arthritis and Sjögren syndrome. Additionally, prominent cytopenias such as anemia and neutropenia may also be autoimmune effects of T-LGL bone marrow infiltration. Here, we present the case of a 67-year-old male with T-LGL and severe neutropenia, hospitalized for two months with recurrent febrile episodes and a perianal abscess. We hypothesize that the unique TCR of the transformed CD8+ T-LGL plays a role in the pathogenesis of disease. Methods: We present patient blood counts and bone marrow aspirate and biopsy. Patient's PBMCs were single-cell sorted for CD3+ T cells and TCR-clonotypes were identified and analyzed by targeted single-cell RNA next generationsequencing. TCR CDR3 sequences were searched in the VDJdb database to find candidate corresponding antigenic T-cell epitopes. Epitope candidates were analyzed with the TCR Model web server to predict epitope binding to the patient's MHC and TCR. In order to identify the patient's precise pp65 epitope variant patient PBMC gDNA was amplified by nested PCR withspecific primers. Tetramers corresponding to the patient's HLA were used to analyze the specificity of T-LGL cells. Cytotoxicity assays were performed with patient CD3+ T cells and pp65-pulsed T2 cells (ATCC CRL-1992). Results: After cloning and sequencing the V-alpha and V-beta regions of the most abundant TCR clonotype of the patient's T-LGL, the VDJdb database predicted the TCR to be specific for CMV pp65 and IE1 epitopes and an autoimmune epitope, BST2. Structural modelling with the TCR model II server predicted epitope binding to the patient's MHC and TCR at high confidence levels. Nested PCR detected the CMV pp65 gene in the patient's PBMCs and CD3-sorted T-cells. Conclusion and Potential Impact: Our data suggest a model for T-LGL pathogenesis where a CMV-reactive T cell immune response plays a role in T-LGL initiation. Reactivation of latent CMV in bone marrow could lead to catastrophic depletion of myeloid cells by cytotoxic T-LGL memory cells resulting in severe neutropenia. A similar paradigmmay be applied to other T-LGL cases, which may present with anemia or other autoimmune disorders, that may have been initiated by CMV or other chronic viral pathogens. Further, the identification of precise TCR sequences and their cognate antigens in T-LGL will guide development of targeted therapies and facilitate the development of clonotype-specific immunotherapeutic agents.

Abstract This study presents a novel approach for performing 10X platform-based targeted single-cell RNA-seq analysis in combination with CRISPR perturbation screens. For the analysis, we constructed a custom sgRNA library focused on a small subset of genes associated with the TNFα response (i.e., NFκB pathway). We compared analysis of two targeted gene expression panels—the first, targeting all protein-coding genes (genome-wide) and the other, targeting a selected set of genes representing key hubs in signaling pathway modules. Narrowing down the analyzed gene set enhanced the efficiency of single-cell RNA-seq by reducing the associated next-generation sequencing (NGS) depth required for readout, and significantly streamlining data analysis. Comparing the analysis of the expression panels targeting all protein-coding genes with the smaller pathway-targeted set, we were able to assess the general flexibility of the novel approach for single-cell CRISPR perturbation screens. We evaluated the specific tradeoffs with regard to the size of the CRISPR library, the size of the panel of genes targeted for expression analysis, and NGS sequencing depth. This flexible, targeted approach not only refines the precision of RNA-seq but also provides a more cost-effective solution for comprehensive genomic analyses. Citation Format: Donato Tedesco, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Nadya Isachenko, Paul Diehl, Alex Chenchik. A flexible and efficient approach for single-cell CRISPR perturbation screens combined with targeted RNA-seq expression analysis [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 2949.

Abstract Synthetic TCR and BCR RNA spike-in controls can be used as universal standards to account for biases caused by PCR and NGS steps of adaptive immune receptor (AIR) repertoire profiling assays. We designed 48 BCR and 39 TCR mRNA synthetic constructs to cover nearly full-length V(D)JC structures, which represent all seven TCR (TRB, TRA, TRG, TRD) and BCR (IGH, IGK, and IGL) hypervariable chains. To identify cross-sample contamination, we spiked in 2 ul of BCR (16x3) and TCR (13x3) triplex isoform pools and detected the presence of the sequence in the sample. Furthermore, we integrated 48 BCR and 39 TCR premixed controls which are mixed in a 16:4:1 ratio into Cellecta’s DriverMap™ Adaptive Immune Receptor Profiling Assay, which employs a gene-specific, multiplex RT-PCR method with unique molecular indices (UMIs). The spike-in controls coupled with UMI-based PCR amplification can help distinguish between control and background sequences. We observed a consistent linear relationship between the concentration of spike-in controls and their molecular counts, with an average sequencing error rate between 0.4%-0.8% per base, which is in line with Illumina sequencing standards. These findings validate the effectiveness of our synthetic spike-in controls in correcting biases in AIR protocols, offering a reliable estimation of error and mutation rates in the DriverMap AIR assay or similar NGS-based immune receptor profiling methods.

Abstract Murine models of tuberculosis (TB) can reveal mechanisms and allow testing of drug/vaccine interventions. Current approaches often rely on the evaluation of lung lesions after euthanasia, with a large number of animals needed for time course and dose-response studies. Measuring blood biomarkers in small volumes obtained serially could provide useful insights and reduce the number of animals needed. We evaluated the utility of small-volume blood samples for profiling T- and B-cell receptor repertoires and transcriptomes in mice (n=16) at different stages of TB progression (early, middle, and advanced—defined by lung histopathology and mycobacterial loads). We isolated RNA from 100 uL of whole blood for TCR/BCR profiling using the Cellecta DriverMap adaptive immune receptor (AIR) assay as well as transcriptome quantitation of ~4700 key mouse genes using a targeted sequencing panel. The results showed substantial changes in clonotype usage and diversity over the course of TB disease, most prominent in the BCR IgH (e.g, top 10 clonotype abundance count in control, early, advanced disease, respectively: 62 + 47, 1792 + 589, 3559 + 286, p < .01, mean + SD, n=3-4). Blood transcriptome profiling showed abundant up-regulation of immune and inflammatory genes (e.g, up-regulated genes vs control: 182 (early), 382 (advanced), q.05 FC1.5). The results support direct testing of non-terminal serial blood samples to characterize disease progression & therapeutic or vaccine interventions.

Abstract Adaptive immune receptor (AIR) repertoire diversity assays are susceptible to biases arising from variations in conditions in the RT-PCR and next-generation sequencing (NGS) steps. We designed synthetic TCR and BCR spike-in controls to mitigate these biases and to serve as universal standards for any PCR-based immune receptor profiling assay. We synthesized 48 BCR constructs representing different IGH, IGK, and IGL genes and 39 TCR constructs for TRB, TRA, TRG, and TRD genes. The spike-in controls were tested as (16 × 3) BCR constructs and (13 × 3) TCR Triplex isoform pools added to multiple samples in the same batch to detect cross-contamination across samples. We successfully discriminated between controls and background sequences by combining a unique molecular identifier (UMI)-based correction strategy with spike-in controls at the data analysis step. We also tested 48 BCR and 39 TCR Premixed Controls by spiking into peripheral blood mononuclear cells (PBMC) RNA samples before reverse transcription using Cellecta’s DriverMap™ Adaptive Immune Receptor Profiling Assay that uses a multiplex RT-PCR approach with gene-specific primers and UMIs. We successfully used it to evaluate assay performance by adding premixed controls at different concentrations. Results showed a linear trend as the number of spike-in molecules increased. Our analysis revealed an average sequencing error rate of 0.4%-0.8% per base, aligning with the reported error rate range of Illumina sequencing. This suggests the reliability of our spike-in controls, which can be used to rectify biases in the AIR protocol and accurately estimate error and mutation rates for the DriverMap AIR assay or any other sequencing-based immune receptor profiling assay. This innovative approach enhances the robustness of immune receptor profiling technology, facilitating more accurate assessments of repertoire diversity. Citation Format: Alex Chenchik, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Khadija Ghias, Paul Diehl. Universal synthetic TCR/BCR spike-in controls to evaluate immune receptor profiling assay and next-generation sequencing performance [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 339.