Jasreet Hundal

Checkpoint Blockade Cancer Immunotherapy Targets Tumour-Specific Mutant Antigens

The immune system influences the fate of developing cancers by not only functioning as a tumour promoter that facilitates cellular transformation, promotes tumour growth and sculpts tumour cell immunogenicity, but also as an extrinsic tumour suppressor that either destroys developing tumours or restrains their expansion. Yet, clinically apparent cancers still arise in immunocompetent individuals in part as a consequence of cancer-induced immunosuppression. In many individuals, immunosuppression is mediated by cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and programmed death-1 (PD-1), two immunomodulatory receptors expressed on T cells. Monoclonal-antibody-based therapies targeting CTLA-4 and/or PD-1 (checkpoint blockade) have yielded significant clinical benefits—including durable responses—to patients with different malignancies. However, little is known about the identity of the tumour antigens that function as the targets of T cells activated by checkpoint blockade immunotherapy and whether these antigens can be used to generate vaccines that are highly tumour-specific. Here we use genomics and bioinformatics approaches to identify tumour-specific mutant proteins as a major class of T-cell rejection antigens following anti-PD-1 and/or anti-CTLA-4 therapy of mice bearing progressively growing sarcomas, and we show that therapeutic synthetic long-peptide vaccines incorporating these mutant epitopes induce tumour rejection comparably to checkpoint blockade immunotherapy. Although mutant tumour-antigen-specific T cells are present in progressively growing tumours, they are reactivated following treatment with anti-PD-1 and/or anti-CTLA-4 and display some overlapping but mostly treatment-specific transcriptional profiles, rendering them capable of mediating tumour rejection. These results reveal that tumour-specific mutant antigens are not only important targets of checkpoint blockade therapy, but they can also be used to develop personalized cancer-specific vaccines and to probe the mechanistic underpinnings of different checkpoint blockade treatments.

Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting

Cancer immunoediting, the process by which the immune system controls tumour outgrowth and shapes tumour immunogenicity, is comprised of three phases: elimination, equilibrium and escape. Although many immune components that participate in this process are known, its underlying mechanisms remain poorly defined. A central tenet of cancer immunoediting is that T-cell recognition of tumour antigens drives the immunological destruction or sculpting of a developing cancer. However, our current understanding of tumour antigens comes largely from analyses of cancers that develop in immunocompetent hosts and thus may have already been edited. Little is known about the antigens expressed in nascent tumour cells, whether they are sufficient to induce protective antitumour immune responses or whether their expression is modulated by the immune system. Here, using massively parallel sequencing, we characterize expressed mutations in highly immunogenic methylcholanthrene-induced sarcomas derived from immunodeficient Rag2−/− mice that phenotypically resemble nascent primary tumour cells. Using class I prediction algorithms, we identify mutant spectrin-β2 as a potential rejection antigen of the d42m1 sarcoma and validate this prediction by conventional antigen expression cloning and detection. We also demonstrate that cancer immunoediting of d42m1 occurs via a T-cell-dependent immunoselection process that promotes outgrowth of pre-existing tumour cell clones lacking highly antigenic mutant spectrin-β2 and other potential strong antigens. These results demonstrate that the strong immunogenicity of an unedited tumour can be ascribed to expression of highly antigenic mutant proteins and show that outgrowth of tumour cells that lack these strong antigens via a T-cell-dependent immunoselection process represents one mechanism of cancer immunoediting.

Association Between Mutation Clearance After Induction Therapy and Outcomes in Acute Myeloid Leukemia

IMPORTANCE Tests that predict outcomes for patients with acute myeloid leukemia (AML) are imprecise, especially for those with intermediate risk AML. OBJECTIVES To determine whether genomic approaches can provide novel prognostic information for adult patients with de novo AML. DESIGN, SETTING, AND PARTICIPANTS Whole-genome or exome sequencing was performed on samples obtained at disease presentation from 71 patients with AML (mean age, 50.8 years) treated with standard induction chemotherapy at a single site starting in March 2002, with follow-up through January 2015. In addition, deep digital sequencing was performed on paired diagnosis and remission samples from 50 patients (including 32 with intermediate-risk AML), approximately 30 days after successful induction therapy. Twenty-five of the 50 were from the cohort of 71 patients, and 25 were new, additional cases. EXPOSURES Whole-genome or exome sequencing and targeted deep sequencing. Risk of identification based on genetic data. MAIN OUTCOMES AND MEASURES Mutation patterns (including clearance of leukemia-associated variants after chemotherapy) and their association with event-free survival and overall survival. RESULTS Analysis of comprehensive genomic data from the 71 patients did not improve outcome assessment over current standard-of-care metrics. In an analysis of 50 patients with both presentation and documented remission samples, 24 (48%) had persistent leukemia-associated mutations in at least 5% of bone marrow cells at remission. The 24 with persistent mutations had significantly reduced event-free and overall survival vs the 26 who cleared all mutations. Patients with intermediate cytogenetic risk profiles had similar findings. [table: see text]. CONCLUSIONS AND RELEVANCE The detection of persistent leukemia-associated mutations in at least 5% of bone marrow cells in day 30 remission samples was associated with a significantly increased risk of relapse, and reduced overall survival. These data suggest that this genomic approach may improve risk stratification for patients with AML.

Genomic impact of transient low-dose decitabine treatment on primary AML cells.

Acute myeloid leukemia (AML) is characterized by dysregulated gene expression and abnormal patterns of DNA methylation; the relationship between these events is unclear. Many AML patients are now being treated with hypomethylating agents, such as decitabine (DAC), although the mechanisms by which it induces remissions remain unknown. The goal of this study was to use a novel stromal coculture assay that can expand primary AML cells to identify the immediate changes induced by DAC with a dose (100nM) that decreases total 5-methylcytosine content and reactivates imprinted genes (without causing myeloid differentiation, which would confound downstream genomic analyses). Using array-based technologies, we found that DAC treatment caused global hypomethylation in all samples (with a preference for regions with higher levels of baseline methylation), yet there was limited correlation between changes in methylation and gene expression. Moreover, the patterns of methylation and gene expression across the samples were primarily determined by the intrinsic properties of the primary cells, rather than DAC treatment. Although DAC induces hypomethylation, we could not identify canonical target genes that are altered by DAC in primary AML cells, suggesting that the mechanism of action of DAC is more complex than previously recognized.

pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens

Cancer immunotherapy has gained significant momentum from recent clinical successes of checkpoint blockade inhibition. Massively parallel sequence analysis suggests a connection between mutational load and response to this class of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies. Here, we present a flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation and expression data (DNA- and RNA-Seq). pVAC-Seq is available at https://github.com/griffithlab/pVAC-Seq.

U2AF1 mutations alter sequence specificity of pre-mRNA binding and splicing.

We previously identified missense mutations in the U2AF1 splicing factor affecting codons S34 (S34F and S34Y) or Q157 (Q157R and Q157P) in 11% of the patients with de novo myelodysplastic syndrome (MDS). Although the role of U2AF1 as an accessory factor in the U2 snRNP is well established, it is not yet clear how these mutations affect splicing or contribute to MDS pathophysiology. We analyzed splice junctions in RNA-seq data generated from transfected CD34+ hematopoietic cells and found significant differences in the abundance of known and novel junctions in samples expressing mutant U2AF1 (S34F). For selected transcripts, splicing alterations detected by RNA-seq were confirmed by analysis of primary de novo MDS patient samples. These effects were not due to impaired U2AF1 (S34F) localization as it co-localized normally with U2AF2 within nuclear speckles. We further found evidence in the RNA-seq data for decreased affinity of U2AF1 (S34F) for uridine (relative to cytidine) at the e-3 position immediately upstream of the splice acceptor site and corroborated this finding using affinity-binding assays. These data suggest that the S34F mutation alters U2AF1 function in the context of specific RNA sequences, leading to aberrant alternative splicing of target genes, some of which may be relevant for MDS pathogenesis.

Temporally Distinct PD-L1 Expression by Tumor and Host Cells Contributes to Immune Escape

PD-L1 induction on tumor cells is IFNγ-dependent and transient, but becomes IFNγ-independent and long-lived on tumorassociated macrophages. Thus, assessing PD-L1 expression on both tumor and host cells may better stratify patients undergoing PD-1/PD-L1 blockade therapy. Antibody blockade of programmed death-1 (PD-1) or its ligand, PD-L1, has led to unprecedented therapeutic responses in certain tumor-bearing individuals, but PD-L1 expressions prognostic value in stratifying cancer patients for such treatment remains unclear. Reports conflict on the significance of correlations between PD-L1 on tumor cells and positive clinical outcomes to PD-1/PD-L1 blockade. We investigated this issue using genomically related, clonal subsets from the same methylcholanthrene-induced sarcoma: a highly immunogenic subset that is spontaneously eliminated in vivo by adaptive immunity and a less immunogenic subset that forms tumors in immunocompetent mice, but is sensitive to PD-1/PD-L1 blockade therapy. Using CRISPR/Cas9-induced loss-of-function approaches and overexpression gain-of-function techniques, we confirmed that PD-L1 on tumor cells is key to promoting tumor escape. In addition, the capacity of PD-L1 to suppress antitumor responses was inversely proportional to tumor cell antigenicity. PD-L1 expression on host cells, particularly tumor-associated macrophages (TAM), was also important for tumor immune escape. We demonstrated that induction of PD-L1 on tumor cells was IFNγ-dependent and transient, but PD-L1 induction on TAMs was of greater magnitude, only partially IFNγ dependent, and was stable over time. Thus, PD-L1 expression on either tumor cells or host immune cells could lead to tumor escape from immune control, indicating that total PD-L1 expression in the immediate tumor microenvironment may represent a more accurate biomarker for predicting response to PD-1/PD-L1 blockade therapy, compared with monitoring PD-L1 expression on tumor cells alone. Cancer Immunol Res; 5(2); 106–17. ©2017 AACR.

Genome Modeling System: A Knowledge Management Platform for Genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Genomic characterization of HER2-positive breast cancer and response to neoadjuvant trastuzumab and chemotherapy-results from the ACOSOG Z1041 (Alliance) trial

Background HER2 (ERBB2) gene amplification and its corresponding overexpression are present in 15-30% of invasive breast cancers. While HER2-targeted agents are effective treatments, resistance remains a major cause of death. The American College of Surgeons Oncology Group Z1041 trial (NCT00513292) was designed to compare the pathologic complete response (pCR) rate of distinct regimens of neoadjuvant chemotherapy and trastuzumab, but ultimately identified no difference. Patients and methods In supplement to tissues from 37 Z1041 cases, 11 similarly treated cases were obtained from a single institution study (NCT00353483). We have extracted genomic DNA from both pre-treatment tumor biopsies and blood of these 48 cases, and performed whole genome (WGS) and exome sequencing. Coincident with these efforts, we have generated RNA-seq profiles from 42 of the tumor biopsies. Among patients in this cohort, 24 (50%) achieved a pCR. Results We have characterized the genomic landscape of HER2-positive breast cancer and investigated associations between genomic features and pCR. Cases assigned to the HER2-enriched subtype by RNA-seq analysis were more likely to achieve a pCR compared to the luminal, basal-like, or normal-like subtypes (19/27 versus 3/15; P = 0.0032). Mutational events led to the generation of putatively active neoantigens, but were overall not associated with pCR. ERBB2 and GRB7 were the genes most commonly observed in fusion events, and genomic copy number analysis of the ERBB2 locus indicated that cases with either no observable or low-level ERBB2 amplification were less likely to achieve a pCR (7/8 versus 17/40; P = 0.048). Moreover, among cases that achieved a pCR, tumors consistently expressed immune signatures that may contribute to therapeutic response. Conclusion The identification of these features suggests that it may be possible to predict, at the time of diagnosis, those HER2-positive breast cancer patients who will not respond to treatment with chemotherapy and trastuzumab. ClinicalTrials.gov identifiers NCT00513292, NCT00353483.Background HER2 ( ERBB2 ) gene amplification and its corresponding overexpression are present in 15-30% of invasive breast cancers. While HER2-targeted agents are effective treatments, resistance remains a major cause of death. The American College of Surgeons Oncology Group Z1041 trial (NCT00513292) was designed to compare the pathologic complete response (pCR) rate of distinct regimens of neoadjuvant chemotherapy and trastuzumab, but ultimately identified no difference [1]. Patients and methods In supplement to tissues from 37 Z1041 cases, 11 similarly treated cases were obtained from a single institution study (NCT00353483). We have extracted genomic DNA from both pre-treatment tumor biopsies and blood of these 48 cases, and performed whole genome (WGS) and exome sequencing. Coincident with these efforts, we have generated RNA-seq profiles from 42 of the tumor biopsies. Among patients in this cohort, 24 (50%) achieved a pCR. Results Here we characterized the genomic landscape of HER2-positive breast cancer and investigated associations between genomic features and pCR. Cases assigned to the HER2-enriched subtype by RNA-seq analysis were more likely to achieve a pCR compared to the luminal, basal-like, or normal-like subtypes (19/27 versus 3/15; P =0.0032). Mutational events led to the generation of putatively active neoantigens, but were overall not associated with pCR. ERBB2 and GRB7 were the genes most commonly observed in fusion events, and genomic copy number analysis of the ERBB2 locus indicated that cases with either no observable or low-level ERBB2 amplification were less likely to achieve a pCR (7/8 versus 17/40; P =0.048). Moreover, among cases that achieved a pCR, tumors consistently expressed immune signatures that may contribute to therapeutic response. Conclusion The identification of these features suggests that it may be possible to predict, at the time of diagnosis, those HER2-positive breast cancer patients who will not respond to treatment with chemotherapy and trastuzumab.

Cancer Immunogenomics: Computational Neoantigen Identification and Vaccine Design

The application of modern high-throughput genomics to the study of cancer genomes has exploded in the past few years, yielding unanticipated insights into the myriad and complex combinations of genomic alterations that lead to the development of cancers. Coincident with these genomic approaches have been computational analyses that are capable of multiplex evaluations of genomic data toward specific therapeutic end points. One such approach is called “immunogenomics” and is now being developed to interpret protein-altering changes in cancer cells in the context of predicted preferential binding of these altered peptides by the patient’s immune molecules, specifically human leukocyte antigen (HLA) class I and II proteins. One goal of immunogenomics is to identify those cancer-specific alterations that are likely to elicit an immune response that is highly specific to the patient’s cancer cells following stimulation by a personalized vaccine. The elements of such an approach are outlined herein and constitute an emerging therapeutic option for cancer patients.