Prediction and characterization of diffuse large B-cell lymphoma cell-of-origin subtypes using targeted sequencing.

The aim of the present study was to determine cell of origin (COO) from a platform using a DNA-based method, COO DNA classifier (COODC). A targeted exome-sequencing platform that applies the mutational profile of a sample was used to classify COO subtype. Two major mutational signatures associated with COO were identified: Catalogue of Somatic Mutations in Cancer (COSMIC) signature 23 enriched in activated B cell (ABC) and COSMIC signature 3, which suggested increased frequency in germinal center B cell (GCB). Differential mutation signatures linked oncogenesis to mutational processes during B-cell activation, confirming the putative origin of GCB and ABC subtypes. Integrating COO with comprehensive genomic profiling enabled identification of features associated with COO and demonstrated the feasibility of determining COO without RNA.

Lay abstract To determine subtypes of diffuse large B-cell lymphoma (DLBCL), a cancer with poor survival, we aimed to identify DLBCL subtypes using DNA mutation-based tools. A targeted gene-sequencing platform, which measures the number and types of DNA mutations in a sample, was used to categorize DLBCL subtypes. Two major patterns of mutations associated with subtypes were identified: Catalogue of Somatic Mutations in Cancer (COSMIC) signature 23 and COSMIC signature 3. Differences in how the subtypes developed suggest a link between tumor developments and B cells being activated normally, confirming where the DLBCL subtypes came from. Combining this information with comprehensive genomic profiling, which determines all of the genes that a person has, allowed identification of features that are associated with DLBCL subtypes and showed that a DLBCL subtype can be determined without using RNA.

The Molecular Landscape of Gastric Cancers for Novel Targeted Therapies from Real-World Genomic Profiling.

BACKGROUND: Panel-based comprehensive genomic profiling is used in clinical practice worldwide; however, large real-world datasets of patients with advanced gastric cancer are not well known. OBJECTIVE: We investigated what differences exist in clinically relevant alterations for molecularly defined or age-stratified subgroups. METHODS: This was a collaborative biomarker study of a real-world dataset from comprehensive genomic profiling testing (Foundation Medicine, Inc.). Hybrid capture was carried out on at least 324 cancer-related genes and select introns from 31 genes frequently rearranged in cancer. Overall, 4634 patients were available for analyses and were stratified by age (≥ 40/< 40 years), microsatellite instability status, tumor mutational burden status (high 10 ≥ /low < 10 Muts/Mb), Epstein-Barr virus status, and select gene alterations. We analyzed the frequency of alterations with a chi-square test with Yate's correction. RESULTS: Genes with frequent alterations included TP53 (60.1%), ARID1A (19.6%), CDKN2A (18.2%), KRAS (16.6%), and CDH1 (15.8%). Differences in comprehensive genomic profiling were observed according to molecularly defined or age-stratified subgroups. Druggable genomic alterations were detected in 31.4% of patients; ATM (4.4%), BRAF V600E (0.4%), BRCA1 (1.5%), BRCA2 (2.9%), ERBB2 amplification (9.2%), IDH1 (0.2%), KRAS G12C (0.7%), microsatellite instability-high (4.8%), NTRK1/2/3 fusion (0.13%), PIK3CA mutation (11.4%), and tumor mutational burden-high (9.4%). CDH1 alterations and MET amplification were significantly more frequent in patients aged < 40 years (27.7 and 6.2%) than in those aged ≥ 40 years (14.7 and 4.0%). CONCLUSIONS: Real-world datasets from clinical panel testing revealed the genomic landscape in gastric cancer by subgroup. These findings provide insights for the current therapeutic strategies and future development of treatments in gastric cancer.

Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis.

BACKGROUND: Men of African ancestry experience the greatest burden of prostate cancer globally, but they are under-represented in genomic and precision medicine studies. Therefore, we sought to characterise the genomic landscape, comprehensive genomic profiling (CGP) utilisation patterns, and treatment patterns across ancestries in a large, diverse, advanced prostate cancer cohort, to determine the impact of genomics on ancestral disparities. METHODS: In this large-scale retrospective analysis, the CGP-based genomic landscape was evaluated in biopsy sections from 11 741 patients with prostate cancer, with ancestry inferred using a single nucleotide polymorphism-based approach. Admixture-derived ancestry fractions for each patient were also interrogated. Independently, clinical and treatment information was retrospectively reviewed for 1234 patients in a de-identified US-based clinicogenomic database. Prevalence of gene alterations, including actionable gene alterations, was assessed across ancestries (n=11 741). Furthermore, real-world treatment patterns and overall survival was assessed in the subset of patients with linked clincogenomic information (n=1234). FINDINGS: The CGP cohort included 1422 (12%) men of African ancestry and 9244 (79%) men of European ancestry; the clinicogenomic database cohort included 130 (11%) men of African ancestry and 1017 (82%) men of European ancestry. Men of African ancestry received more lines of therapy before CGP than men of European ancestry (median of two lines [IQR 0-8] vs one line [0-10], p=0·029). In genomic analyses, ancestry-specific mutational landscapes were observed, but the prevalence of alterations in AR, the DNA damage response pathway, and other actionable genes were similar across ancestries. Similar genomic landscapes were observed in analyses that accounted for admixture-derived ancestry fractions. After undergoing CGP, men of African ancestry were less likely to receive a clinical study drug compared with men of European ancestry (12 [10%] of 118 vs 246 [26%] of 938, p=0·0005). INTERPRETATION: Similar rates of gene alterations with therapy implications suggest that differences in actionable genes (including AR and DNA damage response pathway genes) might not be a main driver of disparities across ancestries in advanced prostate cancer. Later CGP utilisation and a lower rate of clinical trial enrolment observed in men of African ancestry could affect genomics, outcomes, and disparities. FUNDING: American Society for Radiation Oncology, Department of Defense, Flatiron Health, Foundation Medicine, Prostate Cancer Foundation, and Sylvester Comprehensive Cancer Center.

Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation.

Small cell lung cancer (SCLC) is a recalcitrant neuroendocrine carcinoma with dismal survival outcomes. A major barrier in the field has been the relative paucity of human tumors studied. Here we provide an integrated analysis of 3,600 "real-world" SCLC cases. This large cohort allowed us to identify new recurrent alterations and genetic subtypes, including STK11-mutant tumors (1.7%) and TP53/RB1 wild-type tumors (5.5%), as well as rare cases that were human papillomavirus-positive. In our cohort, gene amplifications on 4q12 are associated with increased overall survival, whereas CCNE1 amplification is associated with decreased overall survival. We also identify more frequent alterations in the PTEN pathway in brain metastases. Finally, profiling cases of SCLC containing oncogenic drivers typically associated with NSCLC demonstrates that SCLC transformation may occur across multiple distinct molecular cohorts of NSCLC. These novel and unsuspected genetic features of SCLC may help personalize treatment approaches for this fatal form of cancer. SIGNIFICANCE: Minimal changes in therapy and survival outcomes have occurred in SCLC for the past four decades. The identification of new genetic subtypes and novel recurrent mutations as well as an improved understanding of the mechanisms of transformation to SCLC from NSCLC may guide the development of personalized therapies for subsets of patients with SCLC. This article is highlighted in the In This Issue feature, p. 1501.

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response.

PURPOSE: Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection. METHODS: We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data. RESULTS: CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit. CONCLUSION: Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

The Molecular Landscape of Pancreatobiliary Cancers for Novel Targeted Therapies From Real-World Genomic Profiling.

BACKGROUND: Chemotherapies have limited efficacy in pancreatic cancer (PC) and biliary tract cancer (BTC), underscoring the need for new regimens. Recently, tumor-agnostic approaches have been developed for some targeted therapies in advanced solid tumors; however, the frequency of alterations by clinical and genomic background is unclear in PC and BTC. METHODS: To assess the frequencies of druggable gene alterations and investigate new potential therapeutic targetable genomic alterations, advanced PC and BTC patients were tested with comprehensive genomic profiling at Foundation Medicine during the course of clinical care. RESULTS: A total of 16 913 PC patients and 3031 BTC patients were available for analyses, and frequencies of genomic alterations were stratified by age (≥40 years or <40 years), microsatellite instability status, tumor mutational burden status (high ≥10 or low <10 Muts/Mb), and select genomic alterations. Alterations in BRCA2, BRAF, ERBB2, CDK12, PIK3CA, FGFR2, EGFR, and other potential targets were seen across cohorts, with enrichment observed within particular subsets such as in PC patients lacking a KRAS mutation. In BTC patients, the rate of ERBB2 amplification was statistically significantly higher in the tumor mutational burden-high population (23.3% vs 13.7%). Interestingly, CDK12 rearrangement was observed in BTC patients with ERBB2 amplification tumors. In patients younger than 40 years, FGFR2 rearrangement (4%) was observed in PC: GATA6 amplification (11.1%) and rearrangement of BRAF (2.8%)FGFR2 (5.6%) was observed in BTC patients. CONCLUSIONS: We identified an appreciable frequency of immunotherapy biomarkers and targetable gene alterations in both PC and BTC, with notable frequencies in PC samples lacking KRAS mutations and children or adolescent and young adult populations, that should encourage comprehensive genomic profiling testing.

Genomic Profiling of Combined Hepatocellular Cholangiocarcinoma Reveals Genomics Similar to Either Hepatocellular Carcinoma or Cholangiocarcinoma.

PURPOSE: Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare, aggressive primary liver carcinoma, with morphologic features of both hepatocellular carcinomas (HCC) and liver cholangiocarcinomas (CCA). METHODS: The genomic profiles of 4,975 CCA, 1,470 HCC, and 73 cHCC-CCA cases arising from comprehensive genomic profiling in the course of clinical care were reviewed for genomic alterations (GA), tumor mutational burden, microsatellite instability status, genomic loss of heterozygosity, chromosomal aneuploidy, genomic ancestry, and hepatitis B virus status. RESULTS: In cHCC-CCA, GA were most common in TP53 (65.8%), TERT (49.3%), and PTEN (9.6%), and 24.6% cHCC-CCA harbored potentially targetable GA. Other GA were predominantly associated with either HCC or CCA, including, but not limited to, TERT, FGFR2, IDH1, and presence of hepatitis B virus. On the basis of these features, a machine learning (ML) model was trained to classify a cHCC-CCA case as CCA-like or HCC-like. Of cHCC-CCA cases, 16% (12/73) were ML-classified as CCA-like and 58% (42/73) cHCC-CCA were ML-classified as HCC-like. The ML model classified more than 70% of cHCC-CCA as CCA-like or HCC-like on the basis of genomic profiles, without additional clinico-pathologic input. CONCLUSION: These findings demonstrate the use of ML for classification as based on a targeted exome panel used during routine clinical care. Classification of cHCC-CCA by genomic features alone creates insights into the biology of the disease and warrants further investigation for relevance to clinical care.

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non-small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. SIGNIFICANCE: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected "Goldilocks" relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development.This article is highlighted in the In This Issue feature, p. 211.