Unique Genomic Alterations and Microbial Profiles Identified in Patients With Gastric Cancer of African, European, and Asian Ancestry: A Novel Path for Precision Oncology.

OBJECTIVE: Here, we characterize differences in the genetic and microbial profiles of GC in patients of African (AFR), European, and Asian ancestry. BACKGROUND: Gastric cancer (GC) is a heterogeneous disease with clinicopathologic variations due to a complex interplay of environmental and biological factors, which may affect disparities in oncologic outcomes.. METHODS: We identified 1042 patients with GC with next-generation sequencing data from an institutional Integrated Mutation Profiling of Actionable Cancer Targets assay and the Cancer Genomic Atlas group. Genetic ancestry was inferred from markers captured by the Integrated Mutation Profiling of Actionable Cancer Targets and the Cancer Genomic Atlas whole exome sequencing panels. Tumor microbial profiles were inferred from sequencing data using a validated microbiome bioinformatics pipeline. Genomic alterations and microbial profiles were compared among patients with GC of different ancestries. RESULTS: We assessed 8023 genomic alterations. The most frequently altered genes were TP53 , ARID1A , KRAS , ERBB2 , and CDH1 . Patients of AFR ancestry had a significantly higher rate of CCNE1 alterations and a lower rate of KRAS alterations ( P < 0.05), and patients of East Asian ancestry had a significantly lower rate of PI3K pathway alterations ( P < 0.05) compared with other ancestries. Microbial diversity and enrichment did not differ significantly across ancestry groups ( P > 0.05). CONCLUSIONS: Distinct patterns of genomic alterations and variations in microbial profiles were identified in patients with GC of AFR, European, and Asian ancestry. Our findings of variation in the prevalence of clinically actionable tumor alterations among ancestry groups suggest that precision medicine can mitigate oncologic disparities.

Local Therapy for Oligoprogression or Consolidation in High Mutational Burden Stage 4 Colorectal Cancer Treated With PD-1 or PD-L1 Blockade.

BACKGROUND: Immune checkpoint blockade (ICI) of programmed cell death protein 1 (PD-1) or PD-1 ligand (PD-L1) can induce durable responses in patients who have colorectal cancer (CRC) with a high tumor mutational burden (TMB). Two recurring clinical dilemmas show how to manage oligoprogressive disease and stable disease after ICI. METHODS: A cohort study was conducted to analyze patients with metastatic CRC who underwent PD-1 or PD-L1 blockade. Tumors were mismatch repair (MMR) deficient or had more than 25 mutations per megabase. Patients were identified who had local therapy (surgery, ablation, or radiotherapy) for one to three sites of progressive disease (PD) or surgery to consolidate SD. The study evaluated clinical and biologic factors associated with patient selection, outcomes, and pathologic response rates. RESULTS: From 2014 to 2020, treatment was administered to 111 patients with ICI. Of these 111 patients, 19 (17%) survived fewer than 6 months, whereas to date, 50 have not had progression of disease. The remaining 42 patients experienced PD, and 16 (38%) were treated with local therapy for oligoprogression. Selection for local therapy was associated with response to ICI. The 2-year progression-free survival (PFS) after local therapy was 62%. Finally, 6 of the 50 patients without PD had consolidation of SD, and 5 had complete or near complete pathologic responses. CONCLUSIONS: Oligoprogression, a frequent pattern of failure after ICI, can be managed effectively with local therapy. In contrast, it may not be necessary to consolidate SD for selected patients. Further research is essential to define management algorithms better and to explore heterogeneity in response patterns.

TP53 mutations identify high-risk events for peripheral T-cell lymphoma treated with CHOP-based chemotherapy.

Nodal peripheral T-cell lymphomas (PTCL), the most common PTCLs, are generally treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP)-based curative-intent chemotherapy. Recent molecular data have assisted in prognosticating these PTCLs, but most reports lack detailed baseline clinical characteristics and treatment courses. We retrospectively evaluated cases of PTCL treated with CHOP-based chemotherapy that had tumors sequenced by the Memorial Sloan Kettering Integrated Mutational Profiling of Actionable Cancer Targets next-generation sequencing panel to identify variables correlating with inferior survival. We identified 132 patients who met these criteria. Clinical factors correlating with an increased risk of progression (by multivariate analysis) included advanced-stage disease and bone marrow involvement. The only somatic genetic aberrancies correlating with inferior progression-free survival (PFS) were TP53 mutations and TP53/17p deletions. PFS remained inferior when stratifying by TP53 mutation status, with a median PFS of 4.5 months for PTCL with a TP53 mutation (n = 21) vs 10.5 months for PTCL without a TP53 mutation (n = 111). No TP53 aberrancy correlated with inferior overall survival (OS). Although rare (n = 9), CDKN2A-deleted PTCL correlated with inferior OS, with a median of 17.6 months vs 56.7 months for patients without CDKN2A deletions. This retrospective study suggests that patients with PTCL with TP53 mutations experience inferior PFS when treated with curative-intent chemotherapy, warranting prospective confirmation.

Phase II Trial of Imatinib Plus Binimetinib in Patients With Treatment-Naive Advanced Gastrointestinal Stromal Tumor.

PURPOSE: Dual targeting of the gastrointestinal stromal tumor (GIST) lineage-specific master regulators, ETV1 and KIT, by MEK and KIT inhibitors were synergistic preclinically and may enhance clinical efficacy. This trial was designed to test the efficacy and safety of imatinib plus binimetinib in first-line treatment of GIST. METHODS: In this trial (NCT01991379), treatment-naive adult patients with confirmed advanced GISTs received imatinib (400 mg once daily) plus binimetinib (30 mg twice daily), 28-day cycles. The primary end point was RECIST1.1 best objective response rate (ORR; complete response plus partial response [PR]). The study was designed to detect a 20% improvement in the ORR over imatinib alone (unacceptable rate of 45%; acceptable rate of 65%), using an exact binomial test, one-sided type I error of 0.08 and type II error of 0.1, and a planned sample size of 44 patients. Confirmed PR or complete response in > 24 patients are considered positive. Secondary end points included Choi and European Organisation for Research and Treatment of Cancer Response Rate, progression-free survival (PFS), overall survival (OS), pathologic responses, and toxicity. RESULTS: Between September 15, 2014, and November 15, 2020, 29 of 42 evaluable patients with advanced GIST had confirmed RECIST1.1 PR. The best ORR was 69.0% (two-sided 95% CI, 52.9 to 82.4). Thirty-nine of 41 (95.1%) had Choi PR approximately 8 weeks. Median PFS was 29.9 months (95% CI, 24.2 to not estimable); median OS was not reached (95% CI, 50.4 to not estimable). Five of eight patients with locally advanced disease underwent surgery after treatment and achieved significant pathologic response (≥ 90% treatment effect). There were no unexpected toxicities. Grade 3 and 4 toxicity included asymptomatic creatinine phosphokinase elevation (79.1%), hypophosphatemia (14.0%), neutrophil decrease (9.3%), maculopapular rash (7.0%), and anemia (7.0%). CONCLUSION: The study met the primary end point. The combination of imatinib and binimetinib is effective with manageable toxicity and warrants further evaluation in direct comparison with imatinib in frontline treatment of GIST.

Prevalence and Landscape of Actionable Genomic Alterations in Renal Cell Carcinoma.

PURPOSE: We report our experience with next-generation sequencing to characterize the landscape of actionable genomic alterations in renal cell carcinoma (RCC). EXPERIMENTAL DESIGN: A query of our institutional clinical sequencing database (MSK-IMPACT) was performed that included tumor samples from 38,468 individuals across all cancer types. Somatic variations were annotated using a precision knowledge database (OncoKB) and the available clinical data stratified by level of evidence. Alterations associated with response to immune-checkpoint blockade (ICB) were analyzed separately; these included DNA mismatch repair (MMR) gene alterations, tumor mutational burden (TMB), and microsatellite instability (MSI). Data from The Cancer Genome Atlas (TCGA) consortium as well as public data from several clinical trials in metastatic RCC were used for validation purposes. Multiregional sequencing data from the TRAcking Cancer Evolution through Therapy (TRACERx) RENAL cohort were used to assess the clonality of somatic mutations. RESULTS: Of the 753 individuals with RCC identified in the MSK-IMPACT cohort, 115 showed evidence of targetable alterations, which represented a prevalence of 15.3% [95% confidence interval (CI), 12.7%-17.8%). When stratified by levels of evidence, the alterations identified corresponded to levels 2 (11.3%), 3A (5.2%), and 3B (83.5%). A low prevalence was recapitulated in the TCGA cohort at 9.1% (95% CI, 6.9%-11.2%). Copy-number variations predominated in papillary RCC tumors, largely due to amplifications in the MET gene. Notably, higher rates of actionability were found in individuals with metastatic disease (stage IV) compared with those with localized disease (OR, 2.50; 95% CI, 1.16-6.16; Fisher's P = 0.01). On the other hand, the prevalence of alterations associated with response to ICB therapy was found to be approximately 5% in both the MSK-IMPACT and TCGA cohorts and no associations with disease stage were identified (OR, 1.35; 95% CI, 0.46-5.40; P = 0.8). Finally, multiregional sequencing revealed that the vast majority of actionable mutations occurred later during tumor evolution and were only present subclonally in RCC tumors. CONCLUSIONS: RCC harbors a low prevalence of clinically actionable alterations compared with other tumors and the evidence supporting their clinical use is limited. These aberrations were found to be more common in advanced disease and seem to occur later during tumor evolution. Our study provides new insights on the role of targeted therapies for RCC and highlights the need for additional research to improve treatment selection using genomic profiling.

Linked Entity Attribute Pair (LEAP): A Harmonization Framework for Data Pooling.

PURPOSE: As data-sharing projects become increasingly frequent, so does the need to map data elements between multiple classification systems. A generic, robust, shareable architecture will result in increased efficiency and transparency of the mapping process, while upholding the integrity of the data. MATERIALS AND METHODS: The American Association for Cancer Research's Genomics Evidence Neoplasia Information Exchange (GENIE) collects clinical and genomic data for precision cancer medicine. As part of its commitment to open science, GENIE has partnered with the National Cancer Institute's Genomic Data Commons (GDC) as a secondary repository. After initial efforts to submit data from GENIE to GDC failed, we realized the need for a solution to allow for the iterative mapping of data elements between dynamic classification systems. We developed the Linked Entity Attribute Pair (LEAP) database framework to store and manage the term mappings used to submit data from GENIE to GDC. RESULTS: After creating and populating the LEAP framework, we identified 195 mappings from GENIE to GDC requiring remediation and observed a 28% reduction in effort to resolve these issues, as well as a reduction in inadvertent errors. These results led to a decrease in the time to map between OncoTree, the cancer type ontology used by GENIE, and International Classification of Disease for Oncology, 3rd Edition, used by GDC, from several months to less than 1 week. CONCLUSION: The LEAP framework provides a streamlined mapping process among various classification systems and allows for reusability so that efforts to create or adjust mappings are straightforward. The ability of the framework to track changes over time streamlines the process to map data elements across various dynamic classification systems.

Comprehensive Molecular Characterization of Salivary Duct Carcinoma Reveals Actionable Targets and Similarity to Apocrine Breast Cancer.

PURPOSE: Salivary duct carcinoma (SDC) is an aggressive salivary malignancy, which is resistant to chemotherapy and has high mortality rates. We investigated the molecular landscape of SDC, focusing on genetic alterations and gene expression profiles. EXPERIMENTAL DESIGN: We performed whole-exome sequencing, RNA sequencing, and immunohistochemical analyses in 16 SDC tumors and examined selected alterations via targeted sequencing of 410 genes in a second cohort of 15 SDCs. RESULTS: SDCs harbored a higher mutational burden than many other salivary carcinomas (1.7 mutations/Mb). The most frequent genetic alterations were mutations in TP53 (55%), HRAS (23%), PIK3CA (23%), and amplification of ERBB2 (35%). Most (74%) tumors had alterations in either MAPK (BRAF/HRAS/NF1) genes or ERBB2 Potentially targetable alterations based on supportive clinical evidence were present in 61% of tumors. Androgen receptor (AR) was overexpressed in 75%; several potential resistance mechanisms to androgen deprivation therapy (ADT) were identified, including the AR-V7 splice variant (present in 50%, often at low ratios compared with full-length AR) and FOXA1 mutations (10%). Consensus clustering and pathway analyses in transcriptome data revealed striking similarities between SDC and molecular apocrine breast cancer. CONCLUSIONS: This study illuminates the landscape of genetic alterations and gene expression programs in SDC, identifying numerous molecular targets and potential determinants of response to AR antagonism. This has relevance for emerging clinical studies of ADT and other targeted therapies in SDC. The similarities between SDC and apocrine breast cancer indicate that clinical data in breast cancer may generate useful hypotheses for SDC. Clin Cancer Res; 22(18); 4623-33. ©2016 AACR.