Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer

Motivation: B-cell receptor (BCR) repertoire profiling is an important tool for understanding the biology of diverse immunologic processes. Current methods for analyzing adaptive immune receptor repertoires depend upon PCR amplification of VDJ rearrangements followed by long read amplicon sequencing spanning the VDJ junctions. While this approach has proven to be effective, it is frequently not feasible due to cost or limited sample material. Additionally, there are many existing datasets where short-read RNA sequencing data are available but PCR amplified BCR data are not. Results: We present here V'DJer, an assembly-based method that reconstructs adaptive immune receptor repertoires from short-read RNA sequencing data. This method captures expressed BCR loci from a standard RNA-seq assay. We applied this method to 473 Melanoma samples from The Cancer Genome Atlas and demonstrate V'DJer's ability to accurately reconstruct BCR repertoires from short read mRNA-seq data

Prognostic value of B cells in cutaneous melanoma

Background: Measures of the adaptive immune response have prognostic and predictive associations in melanoma and other cancer types. Specifically, intratumoral T cell density and function have considerable prognostic and predictive value in skin cutaneous melanoma (SKCM). Less is known about the significance of tumor-infiltrating B cells in SKCM. Our goal was to understand the prognostic and predictive value of B cell phenotypic subsets in SKCM using RNA sequencing. Methods: We used our previously published algorithm, V'DJer, to assemble B cell receptor (BCR) repertoires and estimate diversity from short-read RNA sequencing (RNA-seq). We applied machine learning-based cellular phenotype classifiers to measure relative similarity of bulk tumor sample gene expression profiles and different B cell phenotypes. We assessed these aspects of B cell biology in 473 SKCM from the Cancer Genome Atlas Project (TCGA) as well as in RNA-seq data corresponding to tumor samples procured from patients who received CTLA-4 and PD-1 inhibitors for metastatic SKCM. Results: We found that the BCR repertoire was associated with different clinical factors, such as tumor tissue site and sex. However, increased clonality of the BCR repertoire was favorably prognostic in SKCM and was prognostic even after first conditioning on various clinical factors. Mutation burden was not correlated with any BCR measurement, and no specific mutation had an altered BCR repertoire. Lack of an assembled BCR in pre-treatment tumor tissues was associated with a lack of anti-tumor response to a CTLA-4 inhibitor in metastatic SKCM. Conclusions: These findings suggest an important prognostic and predictive role for B cell characteristics in SKCM. This has implications for melanoma immunobiology and potential development of immunogenomics features to predict survival and response to immunotherapy

Molecular and clinical characterization of a claudin-low subtype of gastric cancer

Purpose Claudin-low molecular subtypes have been identified in breast and bladder cancers and are characterized by low expression of claudins, enrichment for epithelial-to-mesenchymal transition (EMT), and tumor-initiating cell (TIC) features. We evaluated whether the claudin-low subtype also exists in gastric cancer. Materials and Methods Four hundred fifteen tumors from The Cancer Genome Atlas (TCGA) gastric cancer mRNA data set were clustered on the claudin, EMT, and TIC gene sets to identify claudin-low tumors. We derived a 24-gene predictor that classifies gastric cancer into claudin-low and non-claudin-low subtypes. This predictor was validated with the Asian Cancer Research Group(ACRG)data set. We characterized molecular and clinical features of claudin-low tumors. Results We identified 46 tumors that had consensus enrichment for claudin-low features in TCGA data set. Claudin-low tumors were most commonly diffuse histologic type (82%) and originally classified as TCGA genomically stable(GS)subtype (78%). Compared with GS subtype, claudin-low subtype had significant activation in Rho family of GTPases signaling, which appears to play a key role in its EMT and TIC properties. In the ACRG data set, 28 of 300 samples were classified as claudin-low tumors by the 24-gene predictor and were phenotypically similar to the initially derived claudin-low tumors. Clinically, claudin-low subtype had the worst overall survival. Of note, the hazard ratios that compared claudin-low versus GS subtype were 2.10 (95% CI, 1.07 to 4.11) in TCGA and 2.32 (95% CI, 1.18 to 4.55) in the ACRG cohorts, with adjustment for age and pathologic stage. Conclusion We identified a gastric claudin-low subtype that carries a poor prognosis likely related to therapeutic resistance as a result of its EMT and TIC phenotypes

Machine-learning prediction of tumor antigen immunogenicity in the selection of therapeutic epitopes

Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and select for potential epitope targets. These algorithms do not predict for epitope immunogenicity using approaches modeled from tumor-specific antigen data. Here, we describe peptide-intrinsic biochemical features associated with neoantigen and minor histocompatibility mismatch antigen immunogenicity and present a gradient boosting algorithm for predicting tumor antigen immunogenicity. This algorithm was validated in two murine tumor models and demonstrated the capacity to select for therapeutically active antigens. Immune correlates of neoantigen immunogenicity were studied in a pan-cancer data set from The Cancer Genome Atlas and demonstrated an association between expression of immunogenic neoantigens and immunity in colon and lung adenocarcinomas. Lastly, we present evidence for expression of an out-of-frame neoantigen that was capable of driving antitumor cytotoxic T-cell responses. With the growing clinical importance of tumor vaccine therapies, our approach may allow for better selection of therapeutically relevant tumor-specific antigens, including nonclas-sic out-of-frame antigens capable of driving antitumor immunity

CD30-redirected chimeric antigen receptor T cells target CD30+ and CD30- embryonal carcinoma via antigen-dependent and fas/fasl interactions

Tumor antigen heterogeneity limits success of chimeric antigen receptor (CAR) T-cell therapies. Embryonal carcinomas (EC) and mixed testicular germ cell tumors (TGCT) containing EC, which are the most aggressive TGCT subtypes, are useful for dissecting this issue as ECs express the CD30 antigen but also containCD30-/dim cells.Wefound that CD30- redirected CAR T cells (CD30.CAR T cells) exhibit antitumor activity in vitro against the human EC cell lines Tera-1, Tera-2, and NCCIT and putative EC stem cells identified by Hoechst dye staining. Cytolytic activity of CD30.CAR T cells was complemented by their sustained proliferation and proinflammatory cytokine production. CD30.CAR T cells also demonstrated antitumor activity in an in vivo xenograft NOD/SCID/gcnull (NSG)mousemodel of metastatic EC.Weobserved that CD30. CAR T cells, while targeting CD30+ EC tumor cells through the CAR (i.e., antigen-dependent targeting), also eliminated surrounding CD30- EC cells in an antigen-independent manner, via a cell-cell contact-dependent Fas/FasL interaction. In addition, ectopic Fas (CD95)expression inCD30+ Fas-ECwas sufficient to improve CD30.CAR T-cell antitumor activity. Overall, these data suggest that CD30.CAR T cells might be useful as an immunotherapy for ECs. Additionally, Fas/FasL interaction between tumor cells and CAR T cells can be exploited to reduce tumor escapedue to heterogeneous antigen expression or to improve CAR T-cell antitumor activity

Tumor neoantigen heterogeneity impacts bystander immune inhibition of pancreatic cancer growth

The immunogenic clonal-fraction threshold in heterogeneous solid-tumor required to induce effective bystander-killing of non-immunogenic subclones is unknown. Pancreatic cancer poses crucial challenges for immune therapeutic interventions due to low mutational-burden and consequent lack of neoantigens. Here, we designed a model to incorporate artificial-neoantigens into genes-of -interest in cancer-cells and to test their potential to actuate bystander-killing. By precisely controlling a neoantigen's abundance in the tumor, we studied the impact of neoantigen frequency on immune-response and immune-escape. Our results showed single, strong, widely-expressed neoantigen could lead to robust antitumor response when over 80% of cancer cells express the neoantigen. Further, immunological assays demonstrated T-cell responses against non-target self-antigen on KRAS-oncoprotein, when we inoculated animals with a high frequency of tumor-cells expressing test-neoantigen. Using nanoparticle-based gene-therapy, we successfully altered tumor-microenvironment by perturbing interleukin-12 and interleukin-10 gene-expression. The subsequent microenvironment-remodeling reduced the neoantigen frequency threshold at which bioluminescent signal intensity for tumor-burden decreased 1.5-log-fold, marking robust tumor-growth inhibition, from 83% to 29%. Our results thus suggest bystander killing is inefficient in immunologically-cold tumors like pancreatic-cancer and requires high neoantigen abundance. However, bystander killing mediated antitumor response can be rescued by adjuvant-immune therapy

A High-Avidity T-cell Receptor Redirects Natural Killer T-cell Specificity and Outcompetes the Endogenous Invariant T-cell Receptor

T-cell receptor (TCR) gene transfer redirects T cells to target intracellular antigens. However, the potential autoreactivity generated by TCR mispairing and occurrence of graft-versus-host disease in the allogenic setting due to the retention of native TCRs remain major concerns. Natural killer T cells (NKT) have shown promise as a platform for adoptive T-cell therapy in cancer patients. Here, we showed their utility for TCR gene transfer. We successfully engineered and expanded NKTs expressing a functional TCR (TCR NKTs), showing HLA-restricted antitumor activity in xenogeneic mouse models in the absence of graft-versus-mouse reactions. We found that TCR NKTs downregulated the invariant TCR (iTCR), leading to iTCR+TCR+ and iTCR-TCR+ populations. In-depth analyses of these subsets revealed that in iTCR-TCR+ NKTs, the iTCR, although expressed at the mRNA and protein levels, was retained in the cytoplasm. This effect resulted from a competition for binding to CD3 molecules for cell-surface expression by the transgenic TCR. Overall, our results highlight the feasibility and advantages of using NKTs for TCR expression for adoptive cell immunotherapies. NKT-low intrinsic alloreactivity that associated with the observed iTCR displacement by the engineered TCR represents ideal characteristics for “off-the-shelf” products without further TCR gene editing

B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors

Neoadjuvant pazopanib and molecular analysis of tissue response in renal cell carcinoma

BACKGROUND. Surgery remains the frontline therapy for patients with localized clear cell renal cell carcinoma (ccRCC); however, 20%–40% recur. Angiogenesis inhibitors have improved survival in metastatic patients and may result in responses in the neoadjuvant setting. The impact of these agents on the tumor genetic heterogeneity or the immune milieu is largely unknown. This phase II study was designed to evaluate safety, response, and effect on tumor tissue of neoadjuvant pazopanib. METHODS. ccRCC patients with localized disease received pazopanib (800 mg daily; median 8 weeks), followed by nephrectomy. Five tumors were examined for mutations by whole exome sequencing from samples collected before therapy and at nephrectomy. These samples underwent RNA sequencing; 17 samples were available for posttreatment assessment. RESULTS. Twenty-one patients were enrolled. The overall response rate was 8 of 21 (38%). No patients with progressive disease. At 1-year, response-free survival and overall survival was 83% and 89%, respectively. The most frequent grade 3 toxicity was hypertension (33%, 7 of 21). Sequencing revealed strong concordance between pre- and posttreatment samples within individual tumors, suggesting tumors harbor stable core profiles. However, a reduction in private mutations followed treatment, suggesting a selective process favoring enrichment of driver mutations. CONCLUSION. Neoadjuvant pazopanib is safe and active in ccRCC. Future genomic analyses may enable the segregation of driver and passenger mutations. Furthermore, tumor infiltrating immune cells persist during therapy, suggesting that pazopanib can be combined with immune checkpoint inhibitors without dampening the immune response. FUNDING. Support was provided by Novartis and GlaxoSmithKline as part of an investigator-initiated study

STING agonist promotes CAR T cell trafficking and persistence in breast cancer

CAR T therapy targeting solid tumors is restrained by limited infiltration and persistence of those cells in the tumor microenvironment (TME). Here, we developed approaches to enhance the activity of CAR T cells using an orthotopic model of locally advanced breast cancer. CAR T cells generated from Th/Tc17 cells given with the STING agonists DMXAA or cGAMP greatly enhanced tumor control, which was associated with enhanced CAR T cell persistence in the TME. Using single-cell RNA sequencing, we demonstrate that DMXAA promoted CAR T cell trafficking and persistence, supported by the generation of a chemokine milieu that promoted CAR T cell recruitment and modulation of the immunosuppressive TME through alterations in the balance of immune-stimulatory and suppressive myeloid cells. However, sustained tumor regression was accomplished only with the addition of anti-PD-1 and anti-GR-1 mAb to Th/Tc17 CAR T cell therapy given with STING agonists. This study provides new approaches to enhance adoptive T cell therapy in solid tumors