Genomic heterogeneity and copy number variant burden are associated with poor recurrence-free survival and 11q loss in human papillomavirus-positive squamous cell carcinoma of the oropharynx.

BACKGROUND: Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States. Favorable treatment outcomes have led to increased interest in treatment de-escalation to reduce treatment morbidity as well as the development of prognostic markers to identify appropriately low-risk patients. Intratumoral genomic heterogeneity and copy number alteration burden have been demonstrated to be predictive of poor outcomes in many other cancers; therefore, we sought to determine whether intratumor heterogeneity and genomic instability are associated with poor outcomes in HPV+ OPSCC. METHODS: Tumor heterogeneity estimates were made based on targeted exome sequencing of 45 patients with HPV+ OPSCC tumors. Analysis of an additional cohort of HPV+ OPSCC tumors lacking matched normal sequencing allowed copy number analysis of 99 patient tumors. RESULTS: High intratumorally genomic heterogeneity and high numbers of copy number alterations were strongly associated with worse recurrence-free survival. Tumors with higher heterogeneity and frequent copy number alterations were associated with loss of distal 11q, which encodes key genes related to double-strand break repair, including ATM and MRE11A. CONCLUSIONS: Both intratumor genomic heterogeneity and high-burden copy number alterations are strongly associated with poor recurrence-free survival in patients with HPV+ OPSCC. The drivers of genomic instability and heterogeneity in these tumors remains to be elucidated. However, 11q loss and defective DNA double-strand break repair have been associated with genomic instability in other solid tumors. Copy number alteration burden and intratumoral heterogeneity represent promising avenues for risk stratification of patients with HPV+OPSCC.

Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing.

BACKGROUND: Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human "molecular tumor boards" (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. MATERIALS AND METHODS: One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. RESULTS: Using a WfG-curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker-selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. CONCLUSION: These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up-to-date availability of clinical trials. IMPLICATIONS FOR PRACTICE: The results of this study demonstrate that the interpretation and actionability of somatic next-generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost-effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data.

LCCC 1025: a phase II study of everolimus, trastuzumab, and vinorelbine to treat progressive HER2-positive breast cancer brain metastases.

PURPOSE: HER2 + breast cancer (BC) is an aggressive subtype with high rates of brain metastases (BCBM). Two-thirds of HER2 + BCBM demonstrate activation of the PI3K/mTOR pathway driving resistance to anti-HER2 therapy. This phase II study evaluated everolimus (E), a brain-permeable mTOR inhibitor, trastuzumab (T), and vinorelbine (V) in patients with HER2 + BCBM. PATIENTS AND METHODS: Eligible patients had progressive HER2 + BCBM. The primary endpoint was intracranial response rate (RR); secondary objectives were CNS clinical benefit rate (CBR), extracranial RR, time to progression (TTP), overall survival (OS), and targeted sequencing of tumors from enrolled patients. A two-stage design distinguished intracranial RR of 5% versus 20%. RESULTS: 32 patients were evaluable for toxicity, 26 for efficacy. Intracranial RR was 4% (1 PR). CNS CBR at 6 mos was 27%; at 3 mos 65%. Median intracranial TTP was 3.9 mos (95% CI 2.2-5). OS was 12.2 mos (95% CI 0.6-20.2). Grade 3-4 toxicities included neutropenia (41%), anemia (16%), and stomatitis (16%). Mutations in TP53 and PIK3CA were common in BCBM. Mutations in the PI3K/mTOR pathway were not associated with response. ERBB2 amplification was higher in BCBM compared to primary BC; ERBB2 amplification in the primary BC trended toward worse OS. CONCLUSION: While intracranial RR to ETV was low in HER2 + BCBM patients, one-third achieved CNS CBR; TTP/OS was similar to historical control. No new toxicity signals were observed. Further analysis of the genomic underpinnings of BCBM to identify tractable prognostic and/or predictive biomarkers is warranted. CLINICAL TRIAL: (NCT01305941).

Comprehensive Analysis of the Immunogenomics of Triple-Negative Breast Cancer Brain Metastases From LCCC1419.

Background: Triple negative breast cancer (TNBC) is an aggressive variant of breast cancer that lacks the expression of estrogen and progesterone receptors (ER and PR) and HER2. Nearly 50% of patients with advanced TNBC will develop brain metastases (BrM), commonly with progressive extracranial disease. Immunotherapy has shown promise in the treatment of advanced TNBC; however, the immune contexture of BrM remains largely unknown. We conducted a comprehensive analysis of TNBC BrM and matched primary tumors to characterize the genomic and immune landscape of TNBC BrM to inform the development of immunotherapy strategies in this aggressive disease. Methods: Whole-exome sequencing (WES) and RNA sequencing were conducted on formalin-fixed, paraffin-embedded samples of BrM and primary tumors of patients with clinical TNBC (n = 25, n = 9 matched pairs) from the LCCC1419 biobank at UNC-Chapel Hill. Matched blood was analyzed by DNA sequencing as a comparison for tumor WES for the identification of somatic variants. A comprehensive genomics assessment, including mutational and copy number alteration analyses, neoantigen prediction, and transcriptomic analysis of the tumor immune microenvironment were performed. Results: Primary and BrM tissues were confirmed as TNBC (23/25 primaries, 16/17 BrM) by immunohistochemistry and of the basal intrinsic subtype (13/15 primaries and 16/19 BrM) by PAM50. Compared to primary tumors, BrM demonstrated a higher tumor mutational burden. TP53 was the most frequently mutated gene and was altered in 50% of the samples. Neoantigen prediction showed elevated cancer testis antigen- and endogenous retrovirus-derived MHC class I-binding peptides in both primary tumors and BrM and predicted that single-nucleotide variant (SNV)-derived peptides were significantly higher in BrM. BrM demonstrated a reduced immune gene signature expression, although a signature associated with fibroblast-associated wound healing was elevated in BrM. Metrics of T and B cell receptor diversity were also reduced in BrM. Conclusions: BrM harbored higher mutational burden and SNV-derived neoantigen expression along with reduced immune gene signature expression relative to primary TNBC. Immune signatures correlated with improved survival, including T cell signatures. Further research will expand these findings to other breast cancer subtypes in the same biobank. Exploration of immunomodulatory approaches including vaccine applications and immune checkpoint inhibition to enhance anti-tumor immunity in TNBC BrM is warranted.

UNMASC: tumor-only variant calling with unmatched normal controls.

Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the appropriate number of controls is a crucial step to identifying somatic variants. Our approach utilizes public databases for canonical somatic variants as well as germline variants and leverages information gathered about nearby positions in the normal controls. Drawing from our cohort of targeted capture panel sequencing of tumor and normal samples with varying tumortypes and demographics, these served as a benchmark for our tumor-only variant calling pipeline to observe the relationship between our ability to correctly classify variants against a number of unmatched normals. With our benchmarked samples, approximately ten normal controls were needed to maintain 94% sensitivity, 99% specificity and 76% positive predictive value, far outperforming comparable methods. Our approach, called UNMASC, also serves as a supplement to traditional tumor with matched normal variant calling workflows and can potentially extend to other concerns arising from analyzing next generation sequencing data.

Integrated RNA and DNA sequencing reveals early drivers of metastatic breast cancer.

Breast cancer metastasis remains a clinical challenge, even within a single patient across multiple sites of the disease. Genome-wide comparisons of both the DNA and gene expression of primary tumors and metastases in multiple patients could help elucidate the underlying mechanisms that cause breast cancer metastasis. To address this issue, we performed DNA exome and RNA sequencing of matched primary tumors and multiple metastases from 16 patients, totaling 83 distinct specimens. We identified tumor-specific drivers by integrating known protein-protein network information with RNA expression and somatic DNA alterations and found that genetic drivers were predominantly established in the primary tumor and maintained through metastatic spreading. In addition, our analyses revealed that most genetic drivers were DNA copy number changes, the TP53 mutation was a recurrent founding mutation regardless of subtype, and that multiclonal seeding of metastases was frequent and occurred in multiple subtypes. Genetic drivers unique to metastasis were identified as somatic mutations in the estrogen and androgen receptor genes. These results highlight the complexity of metastatic spreading, be it monoclonal or multiclonal, and suggest that most metastatic drivers are established in the primary tumor, despite the substantial heterogeneity seen in the metastases.

The Prognostic Significance of Low-Frequency Somatic Mutations in Metastatic Cutaneous Melanoma.

Background: Little is known about the prognostic significance of somatically mutated genes in metastatic melanoma (MM). We have employed a combined clinical and bioinformatics approach on tumor samples from cutaneous melanoma (SKCM) as part of The Cancer Genome Atlas project (TCGA) to identify mutated genes with potential clinical relevance. Methods: After limiting our DNA sequencing analysis to MM samples (n = 356) and to the CANCER CENSUS gene list, we filtered out mutations with low functional significance (snpEFF). We performed Cox analysis on 53 genes that were mutated in ≥3% of samples, and had ≥50% difference in incidence of mutations in deceased subjects versus alive subjects. Results: Four genes were potentially prognostic [RAC1, FGFR1, CARD11, CIITA; false discovery rate (FDR) < 0.2]. We identified 18 additional genes (e.g., SPEN, PDGFRB, GNAS, MAP2K1, EGFR, TSC2) that were less likely to have prognostic value (FDR < 0.4). Most somatic mutations in these 22 genes were infrequent (< 10%), associated with high somatic mutation burden, and were evenly distributed across all exons, except for RAC1 and MAP2K1. Mutations in only 9 of these 22 genes were also identified by RNA sequencing in >75% of the samples that exhibited corresponding DNA mutations. The low frequency, UV signature type and RNA expression of the 22 genes in MM samples were confirmed in a separate multi-institution validation cohort (n = 413). An underpowered analysis within a subset of this validation cohort with available patient follow-up (n = 224) showed that somatic mutations in SPEN and RAC1 reached borderline prognostic significance [log-rank favorable (p = 0.09) and adverse (p = 0.07), respectively]. Somatic mutations in SPEN, and to a lesser extent RAC1, were not associated with definite gene copy number or RNA expression alterations. High (>2+) nuclear plus cytoplasmic expression intensity for SPEN was associated with longer melanoma-specific overall survival (OS) compared to lower (≤ 2+) nuclear intensity (p = 0.048). We conclude that expressed somatic mutations in infrequently mutated genes beyond the well-characterized ones (e.g., BRAF, RAS, CDKN2A, PTEN, TP53), such as RAC1 and SPEN, may have prognostic significance in MM.

Germline Analysis from Tumor-Germline Sequencing Dyads to Identify Clinically Actionable Secondary Findings.

PURPOSE: To evaluate germline variants in hereditary cancer susceptibility genes among unselected cancer patients undergoing tumor-germline sequencing. EXPERIMENTAL DESIGN: Germline sequence data from 439 individuals undergoing tumor-germline dyad sequencing through the LCCC1108/UNCseq™ (NCT01457196) study were analyzed for genetic variants in 36 hereditary cancer susceptibility genes. These variants were analyzed as an exploratory research study to determine whether pathogenic variants exist within the germline of patients undergoing tumor-germline sequencing. Patients were unselected with respect to indicators of hereditary cancer predisposition. RESULTS: Variants indicative of hereditary cancer predisposition were identified in 19 (4.3%) patients. For about half (10/19), these findings represent new diagnostic information with potentially important implications for the patient and their family. The others were previously identified through clinical genetic evaluation secondary to suspicion of a hereditary cancer predisposition. Genes with pathogenic variants included ATM, BRCA1, BRCA2, CDKN2A, and CHEK2 In contrast, a substantial proportion of patients (178, 40.5%) had Variants of Uncertain Significance (VUS), 24 of which had VUS in genes pertinent to the presenting cancer. Another 143 had VUS in other hereditary cancer genes, and 11 had VUS in both pertinent and nonpertinent genes. CONCLUSIONS: Germline analysis in tumor-germline sequencing dyads will occasionally reveal significant germline findings that were clinically occult, which could be beneficial for patients and their families. However, given the low yield for unexpected germline variation and the large proportion of patients with VUS results, analysis and return of germline results should adhere to guidelines for secondary findings rather than diagnostic hereditary cancer testing. Clin Cancer Res; 22(16); 4087-94. ©2016 AACRSee related commentary by Mandelker, p. 3987.