Restricted myeloperoxidase epitopes drive the adaptive immune response in MPO-ANCA vasculitis

BACKGROUND

Treatment of autoimmune diseases has relied on broad immunosuppression. Knowledge of specific interactions between human leukocyte antigen (HLA), the autoantigen, and effector immune cells, provides the foundation for antigen-specific therapies. These studies investigated the role of HLA, specific myeloperoxidase (MPO) epitopes, CD4+ T cells, and ANCA specificity in shaping the immune response in patients with anti-neutrophil cytoplasmic autoantibody (ANCA) vasculitis.

METHODS

HLA sequence-based typing identified enriched alleles in our patient population (HLA-DPB1*04:01 and HLA-DRB4*01:01), while in silico and in vitro binding studies confirmed binding between HLA and specific MPO epitopes. Class II tetramers with MPO peptides were utilized to detect autoreactive CD4+ T cells. TCR sequencing was performed to determine the clonality of T cell populations. Longitudinal peptide ELISAs assessed the temporal nature of anti-MPO447-461 antibodies. Solvent accessibility combined with chemical modification determined the buried regions of MPO.

RESULTS

We identified a restricted region of MPO that was recognized by both CD4+ T cells and ANCA. The autoreactive T cell population contained CD4+CD25intermediateCD45RO+ memory T cells and secreted IL-17A. T cell receptor (TCR) sequencing demonstrated that autoreactive CD4+ T cells had significantly less TCR diversity when compared to naïve and memory T cells, indicating clonal expansion. The anti-MPO447-461 autoantibody response was detectable at onset of disease in some patients and correlated with disease activity in others. This region of MPO that is targeted by both T cells and antibodies is not accessible to solvent or chemical modification, indicating these epitopes are buried.

CONCLUSIONS

These observations reveal interactions between restricted MPO epitopes and the adaptive immune system within ANCA vasculitis that may inform new antigen-specific therapies in autoimmune disease while providing insight into immunopathogenesis.

Using RNA Sequencing to Characterize the Tumor Microenvironment

RNA sequencing (RNA-seq) is an integral tool in immunogenomics, allowing for interrogation of the transcriptome of a tumor and its microenvironment. Analytical methods to deconstruct the genomics data can then be applied to infer gene expression patterns associated with the presence of various immunocyte populations. High quality RNA-seq is possible from formalin-fixed, paraffin-embedded (FFPE), fresh-frozen, and fresh tissue, with a wide variety of sequencing library preparation methods, sequencing platforms, and downstream bioinformatics analyses currently available. Selection of an appropriate library preparation method is largely determined by tissue type, quality of RNA, and quantity of RNA. Downstream of sequencing, many analyses can be applied to the data, including differential gene expression analysis, immune gene signature analysis, gene pathway analysis, T/B-cell receptor inference, HLA inference, and viral transcript quantification. In this chapter, we will describe our workflow for RNA-seq from bulk tissue to evaluable data, including extraction of RNA, library preparation methods, sequencing of libraries, alignment and quality assurance of data, and initial downstream analyses of RNA-seq data to extract relevant immunogenomics features. Systems biology methods that draw additional insights by integrating these features are covered further in Chapters 28 - 30 .

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.

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 nonclassic out-of-frame antigens capable of driving antitumor immunity.

The Transcription Factor Bhlhe40 Programs Mitochondrial Regulation of Resident CD8+ T Cell Fitness and Functionality

Tissue-resident memory CD8⁺ T (Trm) cells share core residency gene programs with tumor-infiltrating lymphocytes (TILs). However, the transcriptional, metabolic, and epigenetic regulation of Trm cell and TIL development and function is largely undefined. Here, we found that the transcription factor Bhlhe40 was specifically required for Trm cell and TIL development and polyfunctionality. Local PD-1 signaling inhibited TIL Bhlhe40 expression, and Bhlhe40 was critical for TIL reinvigoration following anti-PD-L1 blockade. Mechanistically, Bhlhe40 sustained Trm cell and TIL mitochondrial fitness and a functional epigenetic state. Building on these findings, we identified an epigenetic and metabolic regimen that promoted Trm cell and TIL gene signatures associated with tissue residency and polyfunctionality. This regimen empowered the anti-tumor activity of CD8⁺ T cells and possessed therapeutic potential even at an advanced tumor stage in mouse models. Our results provide mechanistic insights into the local regulation of Trm cell and TIL function.

Alternative tumour-specific antigens

The study of tumour-specific antigens (TSAs) as targets for antitumour therapies has accelerated within the past decade. The most commonly studied class of TSAs are those derived from non-synonymous single-nucleotide variants (SNVs), or SNV neoantigens. However, to increase the repertoire of available therapeutic TSA targets, 'alternative TSAs', defined here as high-specificity tumour antigens arising from non-SNV genomic sources, have recently been evaluated. Among these alternative TSAs are antigens derived from mutational frameshifts, splice variants, gene fusions, endogenous retroelements and other processes. Unlike the patient-specific nature of SNV neoantigens, some alternative TSAs may have the advantage of being widely shared by multiple tumours, allowing for universal, off-the-shelf therapies. In this Opinion article, we will outline the biology, available computational tools, preclinical and/or clinical studies and relevant cancers for each alternative TSA class, as well as discuss both current challenges preventing the therapeutic application of alternative TSAs and potential solutions to aid in their clinical translation.

Abstract 1184: Comprehensive analysis with interactive exploration of immune response signatures in 10,000 tumor samples

In recent years, analysis of cancer genomics data using methods of immunogenomics has yielded valuable insight into how cancer cells interact with immune cells in the tumor microenvironment. A recent analysis of the multiple molecular platforms by The Cancer Genome Atlas (TCGA) of over 10,000 tumors comprising 33 cancer types identified six immune subtypes, spanning multiple tumor types, that are characterized by differences in: macrophage vs. lymphocyte signatures; Th1:Th2 cell ratio; extent of intratumoral heterogeneity; aneuploidy; extent of neoantigen load; signatures of cell proliferation; expression of immunomodulatory genes; and disease outcome [1]. Particular driver mutations correlate with variation in leukocyte levels across all cancers or with the fraction of individual immune cell types. Intracellular and extracellular networks (involving transcription, microRNAs, copy number and epigenetic processes) are predicted to play a role in establishing the observed tumor-immune cell interactions, both across and within immune subtypes. Additionally, machine learning methods have been applied to H&E images to extract information on which tissue regions contain tumor infiltrating lymphocytes (TILs), yielding TIL maps of whole slide images from digital pathology[2]. Spatial patterns of TILs are associated with a variety of genomic alterations, including cancer subtypes.

The CRI iAtlas (www.cri-iatlas.org) is a cloud-based platform for data exploration and discovery, allowing researchers to study TCGA immune response characterizations, and the relationships among them in individual tumor types, tumor subtypes, and immune subtypes. iAtlas supports the adaptive exploration of correlations within the cellularity of the tumor microenvironment, immune expression signatures, tumor mutation burden, cancer driver mutations, adaptive cell clonality, patient survival, and expression of key immunomodulators. iAtlas was launched in April 2018, and has since been expanded to include new capabilities such as (1) user-defined loading of cohorts, (2) a tool for classifying expression data into immune subtypes, (3) integration of TIL mapping from digital pathology images, and (4) addition of annotated genomics datasets from immunotherapy clinical trials as comparative data sources. As the resource evolves, we expect that the CRI iAtlas will help to accelerate discovery and improve patient outcomes by providing researchers greater access to immunogenomics data to better understand the immunological characteristics of the tumor microenvironment and its potential impact on patient responses to immunotherapy.

[1] Thorsson, V, et al., The Immune Landscape of Cancer; Immunity 48, p812 - 830.e14 (2018)

[2] Saltz, J et al. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images; Cell Reports 23 pp.181-193.e7 (2018)

Citation Format: Vesteinn Thorsson, David L. Gibbs, Mary L. Disis, Elizabeth G. Demicco, Alexander J. Lazar, Jonathan S. Serody, James A. Eddy, Ilya Shmulevich, Justin Guinney, Benjamin G. Vincent. Comprehensive analysis with interactive exploration of immune response signatures in 10,000 tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1184.

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.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0647-5) contains supplementary material, which is available to authorized users.

Emerging Nano-/Microapproaches for Cancer Immunotherapy

Cancer immunotherapy has achieved remarkable clinical efficacy through recent advances such as chimeric antigen receptor-T cell (CAR-T) therapy, immune checkpoint blockade (ICB) therapy, and neoantigen vaccines. However, application of immunotherapy in a clinical setting has been limited by low durable response rates and immune-related adverse events. The rapid development of nano-/microtechnologies in the past decade provides potential strategies to improve cancer immunotherapy. Advances of nano-/microparticles such as virus-like size, high surface to volume ratio, and modifiable surfaces for precise targeting of specific cell types can be exploited in the design of cancer vaccines and delivery of immunomodulators. Here, the emerging nano-/microapproaches in the field of cancer vaccines, immune checkpoint blockade, and adoptive or indirect immunotherapies are summarized. How nano-/microparticles improve the efficacy of these therapies, relevant immunological mechanisms, and how nano-/microparticle methods are able to accelerate the clinical translation of cancer immunotherapy are explored.

Abstract GS1-05: Apobec3 induced mutagenesis sensitizes murine models of triple negative breast cancer to immunotherapy by activating B-cells and CD4+ T-cells

Immune checkpoint inhibitor (ICI) therapies have led to remarkable clinical responses in cancers such as melanoma and non-small cell lung cancer. In breast cancer, current immunotherapy trials have placed an emphasis on triple negative breast cancers (TNBC), where early results suggest response rates of 10-20%. Thus, it is critical to identify predictive biomarkers to enhance patient selection for immunotherapy. With this goal in mind, we simulated a clinical trial employing anti-PD1 and anti-CTLA therapies in immune-intact genetically engineered mouse models (GEMMs) of TNBC. Testing of ICI therapies on 8 different GEMMs demonstrated that each model was resistant. Whole exome sequencing showed that each model also harbored a low mutation burden. Given that mutation load is predictive of immunotherapy response in other cancer types, and that Apobec3B activity is associated with higher tumor mutation burden (TMB) in breast cancer, we created two different tumor lines with overexpression of murine Apobec3.

In contrast to the parental lines, the Apobec3 overexpressing lines showed an elevated tumor mutation burden and new mutations were consistent with the Apobec mutation signature. These TNBC lines with new mutations resulting from Apobec3 activity were exquisitely sensitive to anti-PD1/anti-CTLA4 combination therapy; as assessed by reduction in tumor volume and extended overall survival. To identify features that predict response, we examined resistant and sensitive tumors at pretreatment, at 1 week of treatment, and at end stage by flow cytometry and mRNA-seq. Gene expression profiling identified multiple immune signatures as predictive of response to ICI therapy; specifically CD8+ T-effector memory cells, CD4+ T-cells, and activated B-Cells. Similarly, gene expression analysis showed that these cell types increased at 1 week of therapy in sensitive models but not in resistant models. Flow cytometry confirmed these predictions.

Next, we used an antibody based approach to separately deplete CD4+ T-Cells, CD8+ T-cells, or B-cells in Apobec3 mutagenized murine tumors receiving aPD1/aCTLA4 combination therapy. In each case, depletion of these populations significantly reduced the therapeutic response. However, mice receiving combination immunotherapy and depleted for CD8+ T-cells still exhibited a significant extension in overall survival compared to non-treated controls. In contrast, the CD4+ T-cell depleted mice and B-cell depleted mice exhibited no ICI therapeutic benefit.

Together, these data point to key immune biomarkers of response to anti-PD1/anti-CTLA4 therapy; we have further developed a genomic predictor of ICI response using our murine models and will test this on a human TNBC data set. Lastly, this GEMM system provides a rich RNA-seq resource, and new immune-activated models for TNBC, which uncovered a key role for B-cells and CD4+ T-cells in response to ICI therapies.

Citation Format: Hollern DP, Xu N, Mott KR, He X, Carey-Ewend K, Marron DS, Ford J, Parker JS, Vincent BG, Serody JS, Perou CM. Apobec3 induced mutagenesis sensitizes murine models of triple negative breast cancer to immunotherapy by activating B-cells and CD4+ T-cells [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS1-05.

Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.

Endogenous retrovirus expression is associated with response to immune checkpoint blockade in clear cell renal cell carcinoma

Although a subset of clear cell renal cell carcinoma (ccRCC) patients respond to immune checkpoint blockade (ICB), predictors of response remain uncertain. We investigated whether abnormal expression of endogenous retroviruses (ERVs) in tumors is associated with local immune checkpoint activation (ICA) and response to ICB. Twenty potentially immunogenic ERVs (πERVs) were identified in ccRCC in The Cancer Genome Atlas data set, and tumors were stratified into 3 groups based on their expression levels. πERV-high ccRCC tumors showed increased immune infiltration, checkpoint pathway upregulation, and higher CD8+ T cell fraction in infiltrating leukocytes compared with πERV-low ccRCC tumors. Similar results were observed in ER+/HER2- breast, colon, and head and neck squamous cell cancers. ERV expression correlated with expression of genes associated with histone methylation and chromatin regulation, and πERV-high ccRCC was enriched in BAP1 mutant tumors. ERV3-2 expression correlated with ICA in 11 solid cancers, including the 4 named above. In a small retrospective cohort of 24 metastatic ccRCC patients treated with single-agent PD-1/PD-L1 blockade, ERV3-2 expression in tumors was significantly higher in responders compared with nonresponders. Thus, abnormal expression of πERVs is associated with ICA in several solid cancers, including ccRCC, and ERV3-2 expression is associated with response to ICB in ccRCC.

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 contain CD30^-/dim cells. We found 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/γcnull (NSG) mouse model of metastatic EC. We observed 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 in CD30⁺ Fas^- EC was 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 escape due to heterogeneous antigen expression or to improve CAR T-cell antitumor activity. Cancer Immunol Res; 6(10); 1274-87. ©2018 AACR.

Abstract 4055: Genomic and immune characterization of triple-negative breast cancer brain metastases

Introduction: Triple negative breast cancer (TNBC) is an aggressive subset of BC with high metastatic potential. Once metastatic, half of patients (pts) with TNBC will develop brain metastases (BM), commonly with progressive extracranial disease. While TNBC BM are routinely treated with radiotherapy, survival is generally less than one year. There are no approved systemic therapies to treat TNBC BM. Both the blood brain barrier and paucity of data on the biologic underpinnings and immune response of BCBM contribute to inadequate therapies for this disease. We sought to characterize the genomic and immune landscape of TNBC BM to foster the development of effective brain permeable anti-cancer agents.

Experimental Procedures: A clinically-annotated BCBM biobank of archival brain metastases and primary BC that eventually metastasize to the brain was created under IRB approval (LCCC1419). DNA (tumor/normal) and RNA (tumor only) was extracted. Following library preparation, whole exome (WES) and RNA sequencing (RNASeq) was performed. Common mutations were determined from WES as those co-identified by two variant callers (Strelka, Cadabra), while immune gene signature expression, molecular subtype identification, and B and T cell receptor repertoires were inferred from RNAseq data.

Results: Of the 26 enrolled pts, median age at BCBM diagnosis was 52 years (35-72); 23% were African American and 57% Caucasian. Additional non-brain metastatic sites included bone (23%), liver (20%), and lung (35%); 23% had a solitary BCBM. 35% of pts received chemotherapy after BCBM diagnosis, while 92% received radiation to the brain (21% WBRT, 5% SRS, 25% SRS plus WBRT and resection). The median survival from BCBM was 6 months. 40 (93%) of the tissues (21 primaries, 22 BCBM) were characterized as basal-like by PAM50; 1 HER2-enriched and 2 Luminal A. 34 genes were mutated in ≥20% of BCBMs, while only 8 were mutated in at least 25% of primaries. Commonly mutated BCBM genes included TP53, ATM and MYH9; in primaries only TP53. Many immune gene signatures were lower in BCBM compared to primary BC including B cell, dendritic cell, regulatory T cell, and IgG cluster (p<0.05). A signature of responsiveness to PD1 inhibition in melanoma was higher in BCBM compared with primary BC (p<0.05). Globally, the BCBM T cell receptor repertoires showed higher diversity (TCR evenness, p=0.006) and lower read count (TCR total read count, p=0.0267) compared to primary BC.

Conclusions: TNBC BM compared to primary BC that metastasize to the brain had more significantly mutated genes, lower immune gene signature expression, higher PD1 inhibition response signature expression, and T cell receptor repertoire features less characteristic of an active antigen-specific response. Given that checkpoint inhibitors are showing response in non-BCBM (i.e. lung and melanoma), these findings indicate that immunotherapy to treat patients with TNBC BM is worthy of exploration.

Citation Format: Benjamin G. Vincent, Maria Sambade, Shengjie Chai, Marni B. Siegel, Luz Cuaboy, Alan Hoyle, Joel Parker, Charles M. Perou, Carey K. Anders. Genomic and immune characterization of triple-negative breast cancer brain metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4055.

Abstract 3609: Differential gene expression is associated with response to chemoradiation and relapse-free and overall survival in rectal adenocarcinoma

Background: Neoadjuvant chemoradiation is a standard therapy for stage II-III rectal adenocarcinoma, and the degree of pathologic response observed upon resection informs prognosis. However, there is a need to identify novel biomarkers of response to chemoradiation and survival after chemoradiation, particularly using modern next-generation sequencing methods.

Methods: We prospectively collected pretreatment endoscopic tumor biopsies from 43 patients with stage II-IV rectal adenocarcinoma prior to neoadjuvant chemoradiation with concurrent fluoropyrimidine. Tumor samples were fresh frozen, and subsequently RNA was extracted, paired end libraries for mRNA sequencing (RNASeq) were prepared using TruSeq RNA Access library prep kits (Illumina), and samples were sequenced on Illumina HiSeq. Differentially expressed genes were determined using DESeq2 and Ingenuity pathway analysis (Qiagen) was performed. Additionally, the association between “claudin-low”-like gene sets established in breast and bladder cancers and clinical outcomes was determined.

Results: Among the 36 patients with adequate RNA quality, 7 had a pathologic complete response (pCR) and 29 did not, with 22 differentially expressed genes with false discovery rate (FDR) <0.1 between the two cohorts, including EME2 (2.0-fold change, FDR p-value 0.00627). At 5 years of follow-up, 11 patients had known relapse and 11 were known to be relapse-free, with 33 differentially expressed genes with FDR<0.1 between the two cohorts. Pathway analysis demonstrated that p53 signaling and Wnt/β-catenin signaling pathways were associated with relapse, while dendritic cell maturation and Toll-like receptor signaling pathways were associated with relapse-free survival. Rectal cancers with greater expression of a “claudin-low”-like signature had significantly inferior relapse-free survival (HR 1.79, 95% CI 1.07-3.00) and overall survival (HR 1.91, 95% CI 1.17-3.12) on univariate Cox proportional hazards model.

Conclusions: There are multiple differentially expressed genes associated with response to neoadjuvant chemoradiation in rectal adenocarcinoma. EME2, which forms an endonuclease that cleaves stalled replication forks, was one of the most differentially expressed genes overexpressed in patients with pathologic complete response and thus is a rational target for further investigation. Extension of “claudin-low” gene expression signatures to rectal cancers may serve as a new prognostic biomarker. Further investigation into the association of gene expression subtypes and responses to neoadjuvant chemoradiation is warranted.

Citation Format: Michael S. Lee, Cheryl Carlson, Benjamin F. Calvo, Bert H. O'Neil, Dante S. Bortone, Benjamin G. Vincent. Differential gene expression is associated with response to chemoradiation and relapse-free and overall survival in rectal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3609.

A Dual Immunotherapy Nanoparticle Improves T-Cell Activation and Cancer Immunotherapy

Combination immunotherapy has recently emerged as a powerful cancer treatment strategy. A promising treatment approach utilizes coadministration of antagonistic antibodies to block checkpoint inhibitor receptors, such as antiprogrammed cell death-1 (aPD1), alongside agonistic antibodies to activate costimulatory receptors, such as antitumor necrosis factor receptor superfamily member 4 (aOX40). Optimal T-cell activation is achieved when both immunomodulatory agents simultaneously engage T-cells and promote synergistic proactivation signaling. However, standard administration of these therapeutics as free antibodies results in suboptimal T-cell binding events, with only a subset of the T-cells binding to both aPD1 and aOX40. Here, it is shown that precise spatiotemporal codelivery of aPD1 and aOX40 using nanoparticles (NP) (dual immunotherapy nanoparticles, DINP) results in improved T-cell activation, enhanced therapeutic efficacy, and increased immunological memory. It is demonstrated that DINP elicits higher rates of T-cell activation in vitro than free antibodies. Importantly, it is demonstrated in two tumor models that combination immunotherapy administered in the form of DINP is more effective than the same regimen administered as free antibodies. This work demonstrates a novel strategy to improve combination immunotherapy using nanotechnology.

Molecular Subtype-Specific Immunocompetent Models of High-Grade Urothelial Carcinoma Reveal Differential Neoantigen Expression and Response to Immunotherapy

High-grade urothelial cancer contains intrinsic molecular subtypes that exhibit differences in underlying tumor biology and can be divided into luminal-like and basal-like subtypes. We describe here the first subtype-specific murine models of bladder cancer and show that Upk3a-Cre^ERT2; Trp53^L/L; Pten^L/L; Rosa26^LSL-Luc (UPPL, luminal-like) and BBN (basal-like) tumors are more faithful to human bladder cancer than the widely used MB49 cells. Following engraftment into immunocompetent C57BL/6 mice, BBN tumors were more responsive to PD-1 inhibition than UPPL tumors. Responding tumors within the BBN model showed differences in immune microenvironment composition, including increased ratios of CD8⁺:CD4⁺ and memory:regulatory T cells. Finally, we predicted and confirmed immunogenicity of tumor neoantigens in each model. These UPPL and BBN models will be a valuable resource for future studies examining bladder cancer biology and immunotherapy.Significance: This work establishes human-relevant mouse models of bladder cancer. Cancer Res; 78(14); 3954-68. ©2018 AACR.

The Immune Landscape of Cancer

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing.

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.