Genetic Ancestry Correlates with Somatic Differences in a Real-World Clinical Cancer Sequencing Cohort

An elevated rate of whole-genome duplications in cancers from Black patients

In the United States, Black individuals have higher rates of cancer mortality than any other racial group. Here, we examine chromosome copy number changes in cancers from more than 1800 self-reported Black patients. We find that tumors from self-reported Black patients are significantly more likely to exhibit whole-genome duplications (WGDs), a genomic event that enhances metastasis and aggressive disease, compared to tumors from self-reported white patients. This increase in WGD frequency is observed across multiple cancer types, including breast, endometrial, and lung cancer, and is associated with shorter patient survival. We further demonstrate that combustion byproducts are capable of inducing WGDs in cell culture, and cancers from self-reported Black patients exhibit mutational signatures consistent with exposure to these carcinogens. In total, these findings identify a type of genomic alteration that is associated with environmental exposures and that may influence racial disparities in cancer outcomes.

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.

Single-nucleus chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry

Single-nucleus analysis allows robust cell-type classification and helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Here, using samples from 92 women of several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells, and macrophages. In addition to the known cell identity genes FOXA1 (luminal hormone sensing), EHF and ELF5 (LASP), TP63 and KRT14 (basal-myoepithelial), epithelial subtypes displayed several uncharacterized markers and inferred gene regulatory networks. By integrating breast epithelial cell gene expression signatures with spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.

Ancestry-associated co-alteration landscape of KRAS and EGFR-altered non-squamous NSCLC

Racial/ethnic disparities mar NSCLC care and treatment outcomes. While socioeconomic factors and access to healthcare are important drivers of NSCLC disparities, a deeper understanding of genetic ancestry-associated genomic landscapes can better inform the biology and the treatment actionability for these tumors. We present a comprehensive ancestry-based prevalence and co-alteration landscape of genomic alterations and immunotherapy-associated biomarkers in patients with KRAS and EGFR-altered non-squamous (non-Sq) NSCLC. KRAS was the most frequently altered oncogene in European (EUR) and African (AFR), while EGFR alterations predominated in East Asian (EAS), South Asian (SAS), and Admixed American (AMR) groups, consistent with prior studies. As expected, STK11 and KEAP1 alterations co-occurred with KRAS alterations while showing mutual exclusivity with EGFR alterations. EAS and AMR KRAS-altered non-Sq NSCLC showed lower rates of co-occurring STK11 and KEAP1 alterations relative to other ancestry groups. Ancestry-specific co-alterations included the co-occurrence of KRAS and GNAS alterations in AMR, KRAS, and ARID1A alterations in SAS, and the mutual exclusivity of KRAS and NF1 alterations in the EUR and AFR ancestries. Contrastingly, EGFR-altered tumors exhibited a more conserved co-alteration landscape across ancestries. AFR exhibited the highest tumor mutational burden, with potential therapeutic implications for these tumors.

Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer

The KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, a detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3,918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1,450 patients with NSCLC. This comprehensive analysis included detailed covariates such as age at diagnosis, sex, clinical stage, cancer histology, and smoking status. We report that SIRE is significantly associated with KRAS mutations, modified by sex, with SIRE-Asian patients showing lower rates of KRAS mutation, transversion substitution, and the allele-specific subtype KRASG12C compared to SIRE-White patients after adjusting for potential confounders. Moreover, GIA was found to correlate with KRAS mutations, where patients with a higher proportion of European ancestry had an increased risk of KRAS mutations, especially more transition substitutions and KRASG12D. Notably, among SIRE-White patients, an increase in European ancestry was linked to a higher likelihood of KRAS mutations, whereas an increase in admixed American ancestry was associated with a reduced likelihood, suggesting that quantitative GIA offers additional information beyond SIRE. The association of SIRE, GIA, and their interplay with KRAS driver mutations in NSCLC highlights the importance of incorporating both into population-based cancer research, aiming to refine clinical decision-making processes and mitigate health disparities.

Association of ESR1 Germline Variants with TP53 Somatic Variants in Breast Tumors in a Genome-wide Study

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

SIGNIFICANCE

Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data

Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole-genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a data set of 39,787 solid tumors sequenced using a clinically targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivaling the performance of WGS-based methods. GDD-ENS can also guide diagnoses of rare type and cancers of unknown primary and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows could provide clinically relevant tumor-type predictions to guide treatment decisions in real time.

SIGNIFICANCE

We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

Basket Trials: Past, Present, and Future

Large-scale tumor molecular profiling has revealed that diverse cancer histologies are driven by common pathways with unifying biomarkers that can be exploited therapeutically. Disease-agnostic basket trials have been increasingly utilized to test biomarker-driven therapies across cancer types. These trials have led to drug approvals and improved the lives of patients while simultaneously advancing our understanding of cancer biology. This review focuses on the practicalities of implementing basket trials, with an emphasis on molecularly targeted trials. We examine the biologic subtleties of genomic biomarker and patient selection, discuss previous successes in drug development facilitated by basket trials, describe certain novel targets and drugs, and emphasize practical considerations for participant recruitment and study design. This review also highlights strategies for aiding patient access to basket trials. As basket trials become more common, steps to ensure equitable implementation of these studies will be critical for molecularly targeted drug development.

Pan-Cancer Comparative and Integrative Analyses of Driver Alterations Using Japanese and International Genomic Databases

Using 48,627 samples from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), we present a pan-cancer landscape of driver alterations and their clinical actionability in Japanese patients. Comparison with White patients in Genomics Evidence Neoplasia Information Exchange (GENIE) demonstrates high TP53 mutation frequencies in Asian patients across multiple cancer types. Integration of C-CAT, GENIE, and The Cancer Genome Atlas data reveals many cooccurring and mutually exclusive relationships between driver mutations. At pathway level, mutations in epigenetic regulators frequently cooccur with PI3K pathway molecules. Furthermore, we found significant cooccurring mutations within the epigenetic pathway. Accumulation of mutations in epigenetic regulators causes increased proliferation-related transcriptomic signatures. Loss-of-function of many epigenetic drivers inhibits cell proliferation in their wild-type cell lines, but this effect is attenuated in those harboring mutations of not only the same but also different epigenetic drivers. Our analyses dissect various genetic properties and provide valuable resources for precision medicine in cancer.

SIGNIFICANCE

We present a genetic landscape of 26 principal cancer types/subtypes, including Asian-prevalent ones, in Japanese patients. Multicohort data integration unveils numerous cooccurring and exclusive relationships between driver mutations, identifying cooccurrence of multiple mutations in epigenetic regulators, which coordinately cause transcriptional and phenotypic changes. These findings provide insights into epigenetic regulator-driven oncogenesis. This article is featured in Selected Articles from This Issue, p. 695.

Spectrum of somatic mutational features of colorectal tumors in ancestrally diverse populations

Ancestrally diverse and admixed populations, including the Hispanic/Latino/a/x/e community, are underrepresented in cancer genetic and genomic studies. Leveraging the Latino Colorectal Cancer Consortium, we analyzed whole exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer (128 Latino, 469 non-Latino) to map somatic mutational features by ethnicity and genetic ancestry. Global proportions of African, East Asian, European, and Native American ancestries were estimated using ADMIXTURE. Associations between global genetic ancestry and somatic mutational features across genes were examined using logistic regression. TP53 , APC , and KRAS were the most recurrently mutated genes. Compared to non-Latino individuals, tumors from Latino individuals had fewer KRAS (OR=0.64, 95%CI=0.41-0.97, p=0.037) and PIK3CA mutations (OR=0.55, 95%CI=0.31-0.98, p=0.043). Genetic ancestry was associated with presence of somatic mutations in 39 genes (FDR-adjusted LRT p<0.05). Among these genes, a 10% increase in African ancestry was associated with significantly higher odds of mutation in KNCN (OR=1.34, 95%CI=1.09-1.66, p=5.74×10 -3 ) and TMEM184B (OR=1.53, 95%CI=1.10-2.12, p=0.011). Among RMGs, we found evidence of association between genetic ancestry and mutation status in CDC27 (LRT p=0.0084) and between SMAD2 mutation status and AFR ancestry (OR=1.14, 95%CI=1.00-1.30, p=0.046). Ancestry was not associated with tumor mutational burden. Individuals with above-average Native American ancestry had a lower frequency of microsatellite instable (MSI-H) vs microsatellite stable tumors (OR=0.45, 95%CI=0.21-0.99, p=0.048). Our findings provide new knowledge about the relationship between ancestral haplotypes and somatic mutational profiles that may be useful in developing precision medicine approaches and provide additional insight into genomic contributions to cancer disparities.

Significance

Our data in ancestrally diverse populations adds essential information to characterize mutational features in the colorectal cancer genome. These results will help enhance equity in the development of precision medicine strategies.

A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

Quantifying the Expanding Landscape of Clinical Actionability for Patients with Cancer

There is a continuing debate about the proportion of cancer patients that benefit from precision oncology, attributable in part to conflicting views as to which molecular alterations are clinically actionable. To quantify the expansion of clinical actionability since 2017, we annotated 47,271 solid tumors sequenced with the MSK-IMPACT clinical assay using two temporally distinct versions of the OncoKB knowledge base deployed 5 years apart. Between 2017 and 2022, we observed an increase from 8.9% to 31.6% in the fraction of tumors harboring a standard care (level 1 or 2) predictive biomarker of therapy response and an almost halving of tumors carrying nonactionable drivers (44.2% to 22.8%). In tumors with limited or no clinical actionability, TP53 (43.2%), KRAS (19.2%), and CDKN2A (12.2%) were the most frequently altered genes.

SIGNIFICANCE

Although clear progress has been made in expanding the availability of precision oncology-based treatment paradigms, our results suggest a continued unmet need for innovative therapeutic strategies, particularly for cancers with currently undruggable oncogenic drivers. See related commentary by Horak and Fröhling, p. 18. This article is featured in Selected Articles from This Issue, p. 5.

Obesity shapes selection for driver mutations in cancer

Obesity is a leading risk factor for cancer, but whether obesity is linked to specific genomic subtypes of cancer is unknown. Here, we examined the relationship between obesity and tumor genotype in two large clinicogenomic corpora. Obesity was associated with specific driver mutations in lung adenocarcinoma, endometrial carcinoma, and cancers of unknown primary, independent of clinical covariates and genetic ancestry. Obesity is therefore a putative driver of etiologic heterogeneity across cancers.

TERT Promoter Mutations Frequency Across Race, Sex, and Cancer Type

BACKGROUND

Telomerase reverse transcriptase (TERT) gene promoter mutations have been explored, as biomarkers of improved survival for patients with cancer receiving immune checkpoint inhibitors. We sought to investigate their prevalence by race and sex across different cancer types to inform patient selection in clinical trials.

RESULTS

In this observational study, 31 925 patients with cancer underwent next-generation sequencing of their tumors with 88% (27 970) patients self-reported being Whites, 7.1% (2273) Asians, and 5.3% (1682) Blacks. Examining the distribution of TERT promoter mutations by race, White patients with melanoma harbored more TERT promoter mutations than Asian and Black patients (OR = 25.83; 95%CI, 6.84-217.42; P < .001). In contrast, Asian patients with head and neck cancer (HNC) harbored more TERT promoter mutations compared to White patients (OR = 2.47; 95%CI, 1.39-4.37; P = .004). In addition, the distribution of TERT promoter mutations differed by sex. Males were enriched for TERT gene promoter mutations compared to females with melanoma (OR = 1.82; 95%CI, 1.53-2.16; P < .001), cancer of unknown primary (OR = 1.96; 95%CI, 1.43-2.69; P < .001), hepatobiliary (OR = 3.89; 95%CI, 2.65-5.69; P < .001), and thyroid cancers (OR = 1.42; 95%CI, 1.10-1.84; P = .0087), while females were more enriched for TERT promoter mutations compared to males for HNC (OR = 0.56; 95%CI, 0.39-0.81; P = .0021).

CONCLUSIONS

The prevalence of TERT gene promoter mutations varies among patients with cancer based on race and sex. These findings inform our understanding of cancer biology and can assist in the design of future clinical trials that leverage drugs targeting TERT promoter dependencies.

Precision Oncology: 2023 in Review

SUMMARY

This article presents a review of recent major advances in precision oncology and the future implications of these advances, specifying the iterative progress achieved from the end of 2022 through 2023. We discuss the different classes of precision oncology drugs and associated biomarkers as well as the improvements in clinical trial design that have enabled the efficient testing of these drugs.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Molecular Characterization of Endometrial Carcinomas in Black and White Patients Reveals Disparate Drivers with Therapeutic Implications

Although the incidence of endometrial carcinoma (EC) is similar in Black and White women, racial disparities are stark, with the highest mortality rates observed among Black patients. Here, analysis of 1,882 prospectively sequenced ECs using a clinical FDA-authorized tumor-normal panel revealed a significantly higher prevalence of high-risk histologic and molecular EC subtypes in self-identified Black (n = 259) compared with White (n = 1,623) patients. Clinically actionable alterations, including high tumor mutational burden/microsatellite instability, which confer benefit from immunotherapy, were less frequent in ECs from Black than from White patients. Ultramutated POLE molecular subtype ECs associated with favorable outcomes were rare in Black patients. Results were confirmed by genetic ancestry analysis. CCNE1 gene amplification, which is associated with aggressive clinical behavior, was more prevalent in carcinosarcomas occurring in Black than in White patients. ECs from Black and White patients display important differences in their histologic types, molecular subtypes, driver genetic alterations, and therapeutic targets.

SIGNIFICANCE

Our comprehensive analysis of prospectively clinically sequenced ECs revealed significant differences in their histologic and molecular composition and in the presence of therapeutic targets in Black versus White patients. These findings emphasize the importance of incorporating diverse populations into molecular studies and clinical trials to address EC disparities. This article is featured in Selected Articles from This Issue, p. 2293.

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.

Deep Learning Model for Tumor Type Prediction using Targeted Clinical Genomic Sequencing Data

Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a dataset of 39,787 solid tumors sequenced using a clinical targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivalling performance of WGS-based methods. GDD-ENS can also guide diagnoses on rare type and cancers of unknown primary, and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows has enabled clinically-relevant tumor type predictions to guide treatment decisions in real time.

Germline Pathogenic Variants and Genetic Counseling by Ancestry in Patients With Epithelial Ovarian Cancer

PURPOSE

To evaluate rates of germline pathogenic/likely pathogenic variants (PVs) and genetic counseling by ancestry in patients with epithelial ovarian cancer (EOC).

METHODS

Patients with pathologically confirmed EOC who underwent clinical tumor-normal sequencing from January 1, 2015, to December 31, 2020, inclusive of germline analysis of ≥76 genes were included. Patients with newly identified PVs were referred for Clinical Genetics Service (CGS) counseling. Ancestry groups were defined using self-reported race/ethnicity and Ashkenazi Jewish (AJ) heritage. Genetic ancestry was inferred computationally using validated algorithms. Logistic regression models were built.

RESULTS

Of 1,266 patients, self-reported ancestry (AJ, 17%; Asian, 10%; Black/African American, 5.4%; Hispanic, 6.2%; non-Hispanic White, 57%; other, 0.16%; unknown, 4.0%) correlated with genetic ancestry (AJ ancestry, 18%; admixed, 10%; African, 4%; East Asian [EAS], 6%; European, 56%; Native American, 0.2%; South Asian [SAS], 4%; unknown, 2%). Germline PVs were observed in 313 (25%) patients, including 195 (15%) with PVs in EOC-associated genes. Those with PVs were younger at diagnosis (59 v 62 years; P < .001) and more likely to have high-grade serous ovarian cancer (83% v 72%; P = .009). PV prevalence varied between ancestry groups (P < .001), with highest rates in the AJ (39.9%) and Asian (26.5%) groups and similar rates (>10%) across other ancestry groups. Use of genetic ancestry demonstrated similar findings and further characterized high rates of PV in EAS/SAS groups. Younger age, high-grade serous histology, and self-reported AJ or Asian ancestry were associated with PV in an EOC-associated gene. Rates of CGS counseling for newly identified PVs were high (80%) across ancestry groups.

CONCLUSION

Rates of PV, particularly in EOC-associated genes, were high regardless of ancestry, with similar rates of counseling between groups, emphasizing the importance of universal genetic testing in all patients with EOC.

Lesion-based indicators predict long-term outcomes of pheochromocytoma and paraganglioma- SIZEPASS

Aim

We seek a simple and reliable tool to predict malignant behavior of pheochromocytoma and paraganglioma (PPGL).

Methods

This single-center prospective cohort study assessed size of primary PPGLs on preoperative cross-sectional imaging and prospectively scored specimens using the Pheochromocytoma of the Adrenal Gland Scaled Score (PASS). Multiplication of PASS points with maximum lesion diameter (in mm) yielded the SIZEPASS criterion. Local recurrence, metastasis or death from disease were surrogates defining malignancy.

Results

76 consecutive PPGL patients, whereof 58 with pheochromocytoma and 51 female, were diagnosed at a mean age of 52.0 ± 15.2 years. 11 lesions (14.5%) exhibited malignant features at a median follow-up (FU) of 49 months (range 4-172 mo). Median FU of the remaining cohort was 139 months (range 120-226 mo). SIZEPASS classified malignancy with an area under the curve (AUC) of 0.97 (95%CI 0.93-1.01; p<0.0001). Across PPGL, SIZEPASS >1000 outperformed all known predictors of malignancy, with sensitivity 91%, specificity 94%, and accuracy 93%, and an odds ratio of 72 fold (95%CI 9-571; P<0.001). It retained an accuracy >90% in cohorts defined by location (adrenal, extra-adrenal) or mutation status.

Conclusions

The SIZEPASS>1000 criterion is a lesion-based, clinically available, simple and effective tool to predict malignant behavior of PPGLs independently of age, sex, location or mutation status.

Associations Between Cancer Predisposition Mutations and Clonal Hematopoiesis in Patients With Solid Tumors

PURPOSE

Clonal hematopoiesis (CH), the expansion of clones in the hematopoietic system, has been linked to different internal and external features such as aging, genetic ancestry, smoking, and oncologic treatment. However, the interplay between mutations in known cancer predisposition genes and CH has not been thoroughly examined in patients with solid tumors.

METHODS

We used prospective tumor-blood paired sequencing data from 46,906 patients who underwent Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) testing to interrogate the associations between CH and rare pathogenic or likely pathogenic (P/LP) germline variants.

RESULTS

We observed an enrichment of CH-positive patients among those carrying P/LP germline mutations and identified a significant association between P/LP germline variants in ATM and CH. Germline and CH comutation patterns in ATM, TP53, and CHEK2 suggested biallelic inactivation as a potential mediator of clonal expansion. Moreover, we observed that CH-PPM1D mutations, similar to somatic tumor-associated PPM1D mutations, were depleted in patients with P/LP germline mutations in the DNA damage response (DDR) genes ATM, CHEK2, and TP53. Patients with solid tumors and harboring P/LP germline mutations, CH mutations, and mosaicism chromosomal alterations might be at an increased risk of developing secondary leukemia while germline variants in TP53 were identified as an independent risk factor (hazard ratio, 36; P < .001) for secondary leukemias.

CONCLUSION

Our results suggest a close relationship between inherited variants and CH mutations within the DDR genes in patients with solid tumors. Associations identified in this study might translate into enhanced clinical surveillance for CH and associated comorbidities in patients with cancer harboring these germline mutations.

Outcomes in breast cancer-does ethnicity matter?

Ethnic or racial differences in breast cancer (BC) survival outcomes have been reported, but current data are largely restricted to comparisons between African Americans and non-Hispanic whites. Most analyses have traditionally been based on self-reported race which may not always be accurate, or are oversimplified in their classification. With increasing globalization, quantification of the genetic ancestry from genomic data may offer a solution to infer the complex makeup from admixture of races. Focusing on the larger and the latest studies, we will discuss recent findings on the differing host and tumor biology that may be driving these disparities, in addition to the extrinsic environmental or lifestyle factors. Socioeconomic disparities with lower cancer literacy may lead to late presentation, poorer adherence to treatment, and other lifestyle factors such as unhealthy diet, obesity, and inadequate physical activity. These hardships may also result in greater allostatic load, which is in turn associated with aggressive BC features in disadvantaged populations. Epigenetic reprogramming may mediate the effects of the environment or lifestyle factors on gene expression, with ensuing differences in BC characteristics and outcome. There is increasing evidence that germline genetics can influence somatic gene alterations or expression, as well as modulate the tumor or immune microenvironment. Although the precise mechanisms remain elusive, this may account for the varying distribution of different BC subtypes across ethnicities. These gaps in our knowledge highlight the need to interrogate the multiomics landscape of BC in diverse populations, ideally in large-scale collaborative settings with standardized methodology for the comparisons to be statistically robust. Together with improving BC awareness and access to good quality health care, a holistic approach with insights of the biological underpinnings is much needed to eradicate ethnic disparities in BC outcomes.

Understanding inequities in precision oncology diagnostics

Advances in molecular diagnostics have enabled the identification of targetable driver pathogenic variants, forming the basis of precision oncology care. However, the adoption of new technologies, such as next-generation sequencing (NGS) panels, can exacerbate healthcare disparities. Here, we summarize data on use patterns of advanced biomarker testing, highlight the disparities in both accessing NGS testing and using this data to match patients to appropriate personalized therapies and propose multidisciplinary strategies to address inequities looking forward.

Inferring genetic ancestry from cancer sequencing data

Genetic ancestry is an important biological determinant of cancer health disparities that is not captured by self-identified race and ethnicity (SIRE). Belleau et al. recently developed a systematic computational approach to infer genetic ancestry from cancer-derived molecular data from different genomic and transcriptomic profiling assays, creating opportunities to interrogate population-scale data sets.

NBN Pathogenic Germline Variants are Associated with Pan-Cancer Susceptibility and In Vitro DNA Damage Response Defects

PURPOSE

To explore the role of NBN as a pan-cancer susceptibility gene.

EXPERIMENTAL DESIGN

Matched germline and somatic DNA samples from 34,046 patients were sequenced using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets and presumed pathogenic germline variants (PGV) identified. Allele-specific and gene-centered analysis of enrichment was conducted and a validation cohort of 26,407 pan-cancer patients was analyzed. Functional studies utilized cellular models with analysis of protein expression, MRN complex formation/localization, and viability assessment following treatment with γ-irradiation.

RESULTS

We identified 83 carriers of 32 NBN PGVs (0.25% of the studied series), 40% of which (33/83) carried the Slavic founder p.K219fs. The frequency of PGVs varied across cancer types. Patients harboring NBN PGVs demonstrated increased loss of the wild-type allele in their tumors [OR = 2.7; confidence interval (CI): 1.4-5.5; P = 0.0024; pan-cancer], including lung and pancreatic tumors compared with breast and colorectal cancers. p.K219fs was enriched across all tumor types (OR = 2.22; CI: 1.3-3.6; P = 0.0018). Gene-centered analysis revealed enrichment of PGVs in cases compared with controls in the European population (OR = 1.9; CI: 1.3-2.7; P = 0.0004), a finding confirmed in the replication cohort (OR = 1.8; CI: 1.2-2.6; P = 0.003). Two novel truncating variants, p.L19* and p.N71fs, produced a 45 kDa fragment generated by alternative translation initiation that maintained binding to MRE11. Cells expressing these fragments showed higher sensitivity to γ-irradiation and lower levels of radiation-induced KAP1 phosphorylation.

CONCLUSIONS

Burden analyses, biallelic inactivation, and functional evidence support the role of NBN as contributing to a broad cancer spectrum. Further studies in large pan-cancer series and the assessment of epistatic and environmental interactions are warranted to further define these associations.

Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms

Genetic ancestry-oriented cancer research requires the ability to perform accurate and robust genetic ancestry inference from existing cancer-derived data, including whole-exome sequencing, transcriptome sequencing, and targeted gene panels, very often in the absence of matching cancer-free genomic data. Here we examined the feasibility and accuracy of computational inference of genetic ancestry relying exclusively on cancer-derived data. A data synthesis framework was developed to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. The data synthesis framework is applicable to multiple profiling platforms, making it possible to assess the performance of inference specifically for a given molecular profile and separately for each continental-level ancestry; this ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. The inference procedure was demonstrated to be accurate and robust in a wide range of sequencing depths. Testing of the approach in four representative cancer types and across three molecular profiling modalities showed that continental-level ancestry of patients can be inferred with high accuracy, as quantified by its agreement with the gold standard of deriving ancestry from matching cancer-free molecular data. This study demonstrates that vast amounts of existing cancer-derived molecular data are potentially amenable to ancestry-oriented studies of the disease without requiring matching cancer-free genomes or patient self-reported ancestry.

SIGNIFICANCE

The development of a computational approach that enables accurate and robust ancestry inference from cancer-derived molecular profiles without matching cancer-free data provides a valuable methodology for genetic ancestry-oriented cancer research.