Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer

Analysis of Genetic Ancestry from NGS Data Using EthSEQ

Next-generation sequencing (NGS) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Identification and stratification of an individual's ancestry is fundamental for the correct interpretation of genetic and genomic profiling. EthSEQ provides an easy and effective computational workflow to determine the ancestry of individuals, exploiting single nucleotide polymorphism genotypes computed from NGS data of whole-exome and targeted sequencing experiments. Genotypes are determined by EthSEQ from sequencing alignment files (BAM files) or can be provided as input in Variant Call Format (VCF) or CoreArray Genomic Data Structure (GDS) format. Ancestry is determined and assigned to individuals by EthSEQ exploiting a reference model and a standard or multi-step refinement approach based on Principal Component Analysis (PCA). A complete and detailed set of textual and graphical output files are generated by EthSEQ as result. EthSEQ is easy to use and can be integrated into any NGS-based processing pipeline also exploiting multi-core capabilities. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Perform ancestry analysis using a pre-computed reference model Alternate Protocol: Perform ancestry analysis using a user-specified GDS file as reference model Basic Protocol 2: Perform ancestry analysis using multi-step refinement Support Protocol 1: Create a reference model from multiple VCF genotype data files Support Protocol 2: Create VCF genotype data files from a BAM file.

Non-CpG sites preference in G:C > A:T transition of TP53 in gastric cancer of Eastern Europe (Poland, Romania and Hungary) compared to East Asian countries (China and Japan)

AIM

Mutation spectrum of TP53 in gastric cancer (GC) has been investigated world-widely, but a comparison of mutation spectrum among GCs from various regions in the world are still sparsely documented. In order to identify the difference of TP53 mutation spectrum in GCs in Eastern Europe and in East Asia, we sequenced TP53 in GCs from Eastern Europe, Lujiang (China), and Yokohama, Kanagawa (Japan) and identified the feature of TP53 mutations of GC in these regions.

SUBJECTS AND METHOD

In total, 689 tissue samples of GC were analyzed: 288 samples from East European populations (25 from Hungary, 71 from Poland and 192 from Romania), 268 from Yokohama, Kanagawa, Japan and 133 from Lujiang, Anhui province, China. DNA was extracted from FFPE tissue of Chinese, East European cases; and from frozen tissue of Japanese GCs. PCR products were direct-sequenced by Sanger method, and in ambiguous cases, PCR product was cloned and up to 8 clones were sequenced. We used No. NC_000017.11(hg38) as the reference sequence of TP53. Mutation patterns were categorized into nine groups: six base substitutions, insertion, deletion and deletion-insertion. Within G:C > A:T mutations the mutations in CpG and non-CpG sites were divided. The Cancer Genome Atlas data (TCGA, ver.R20, July, 2019) having somatic mutation list of GCs from Whites, Asians, and other ethnicities were used as a reference for our data.

RESULTS

The most frequent base substitutions were G:C > A:T transition in all the areas investigated. The G:C > A:T transition in non-CpG sites were prominent in East European GCs, compared with Asian ones. Mutation pattern from TCGA data revealed the same trend between GCs from White (TCGA category) vs Asian countries. Chinese and Japanese GCs showed higher ratio of G:C > A:T transition in CpG sites and A:T > G:C mutation was more prevalent in Asian countries.

CONCLUSION

The divergence in mutation spectrum of GC in different areas in the world may reflect various pathogeneses and etiologies of GC, region to region. Diversified mutation spectrum in GC in Eastern Europe may suggest GC in Europe has different carcinogenic pathway of those from Asia.

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.

Efficacy and adverse reaction management of oncolytic viral intervention combined with chemotherapy in patients with liver metastasis of gastrointestinal malignancy

Background

The liver is a key target organ for colorectal and gastric cancer metastasis. One of the challenges in the treatment of colorectal and gastric cancers is the management of liver metastasis. This study aimed to investigate the efficacy, adverse effects, and coping strategies of oncolytic virus injection in patients with liver metastases of gastrointestinal malignancies.

Methods

We prospectively analyzed patients treated at Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine from June 2021 to October 2022. 47 patients with gastrointestinal cancer liver metastasis were included in the study. The data, including clinical manifestations, imaging, tumor markers, postoperative adverse reactions, psychological intervention, dietary guidance, and adverse reaction management were evaluated.

Results

Oncolytic virus injection was successful in all patients, and no drug injection-related deaths occurred. The adverse effects, such as fever, pain, bone marrow suppression, nausea, and vomiting, were mild and resolved subsequently. Based on the comprehensive intervention of nursing procedures, the postoperative adverse reactions of patients were effectively alleviated and treated. None of the 47 patients had any puncture point infections, and the pain caused by the invasive operation was relieved quickly. After 2 courses of oncolytic virus injection, postoperative liver MRI showed 5 partial remissions, 30 stable diseases, and 12 progressive diseases in target organs.

Conclusion

Interventions based on nursing procedures can ensure the smooth treatment of recombinant human adenovirus type 5 in patients with liver metastases of gastrointestinal malignant tumors. This is of great importance for clinical treatment and significantly reduces patient complications and improves the patient's quality of life.

MicroRNAs within the Basal-like signature of Quadruple Negative Breast Cancer impact overall survival in African Americans

We previously found that QNBC tumors are more frequent in African Americans compared to TNBC tumors. To characterize this subtype further, we sought to determine the miRNA-mRNA profile in QNBC patients based on race. Both miRNA and mRNA expression data were analyzed from TCGA and validated using datasets from the METABRIC, TCGA proteomic, and survival analysis by KMPLOT. miRNA-mRNAs which include FOXA1 and MYC (mir-17/20a targets); GATA3 and CCNG2 (mir-135b targets); CDKN2A, CDK6, and B7-H3 (mir-29c targets); and RUNX3, KLF5, IL1-β, and CTNNB1 (mir-375 targets) were correlated with basal-like and immune subtypes in QNBC patients and associated with a worse survival. Thus, QNBC tumors have an altered gene signature implicated in racial disparity and poor survival.

Genetic variants in African-American and Hispanic patients with breast cancer

Breast cancer is a disease with significant health disparity affecting mortality in minority women. The present study examined the genetic makeup of breast cancers in African-American and Hispanic/Latinx patients to determine specific genetic mutations associated with breast cancer in the minority population from South Los Angeles, United States. Whole-exome sequencing was performed on DNA extracted from breast cancer tumor biopsies collected from 13 African-American and 15 Hispanic women and 8 matched-normal samples for each ethnic category. The results were analyzed using Ensemble Variant Effect Predictor and Mutation Significance. Additionally, a comparative analysis with The Cancer Genome Atlas data was provided. Our data revealed somatic mutations in genes such as SET domain containing (lysine methyltransferase) 8, serine protease 1 and AT-rich interaction domain 1B (ARID1B) and known breast cancer genes, such as BRCA1/2, TP53 and the DNA damage response genes across all ethnicities. Additionally, Hispanic patients had BRCA1 associated RING domain 1B (BARD1) variants, while African-American patients had higher numbers of nonsynonymous variants in the RAD51 paralog B (RAD51B), ARID1B and X-ray repair cross complementing 3 (XRCC3) genes. In addition, our patients exhibited mutational signature enrichment that indicated DNA homologous recombination repair deficiencies. Therefore, African-American and Hispanic breast cancer samples showed considerable overlap in breast cancer genetic mutations. However, there are differences in specific genetic variants in TP53, BRCA1/2, BARD1 or ARID1B, which will require further study of their role in tumorigenesis.

Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors

Germline genetic variants modulate human immune response. We present analytical pipelines for assessing the contribution of hosts' genetic background to the immune landscape of solid tumors using harmonized data from more than 9,000 patients in The Cancer Genome Atlas (TCGA). These include protocols for heritability, genome-wide association studies (GWAS), colocalization, and rare variant analyses. These workflows are developed around the structure of TCGA but can be adapted to explore other repositories or in the context of cancer immunotherapy. For complete details on the use and execution of this protocol, please refer to Sayaman et al. (2021).

Ethnic and racial-specific differences in levels of centrosome-associated mitotic kinases, proliferative and epithelial-to-mesenchymal markers in breast cancers

Molecular epidemiology evidence indicates racial and ethnic differences in the aggressiveness and survival of breast cancer. Hispanics/Latinas (H/Ls) and non-Hispanic Black women (NHB) are at higher risk of breast cancer (BC)-related death relative to non-Hispanic white (NHW) women in part because they are diagnosed with hormone receptor-negative (HR) subtype and at higher stages. Since the cell cycle is one of the most commonly deregulated cellular processes in cancer, we propose that the mitotic kinases TTK (or Mps1), TBK1, and Nek2 could be novel targets to prevent breast cancer progression among NHBs and H/Ls. In this study, we calculated levels of TTK, p-TBK1, epithelial (E-cadherin), mesenchymal (Vimentin), and proliferation (Ki67) markers through immunohistochemical (IHC) staining of breast cancer tissue microarrays (TMAs) that includes samples from 6 regions in the Southeast of the United States and Puerto Rico -regions enriched with NHB and H/L breast cancer patients. IHC analysis showed that TTK, Ki67, and Vimentin were significantly expressed in triple-negative (TNBC) tumors relative to other subtypes, while E-cadherin showed decreased expression. TTK correlated with all of the clinical variables but p-TBK1 did not correlate with any of them. TCGA analysis revealed that the mRNA levels of multiple mitotic kinases, including TTK, Nek2, Plk1, Bub1, and Aurora kinases A and B, and transcription factors that are known to control the expression of these kinases (e.g. FoxM1 and E2F1-3) were upregulated in NHBs versus NHWs and correlated with higher aneuploidy indexes in NHB, suggesting that these mitotic kinases may be future novel targets for breast cancer treatment in NHB women.

An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.

African Ancestry-Associated Gene Expression Profiles in Triple-Negative Breast Cancer Underlie Altered Tumor Biology and Clinical Outcome in Women of African Descent

Women of sub-Saharan African descent have disproportionately higher incidence of triple-negative breast cancer (TNBC) and TNBC-specific mortality across all populations. Population studies show racial differences in TNBC biology, including higher prevalence of basal-like and quadruple-negative subtypes in African Americans (AA). However, previous investigations relied on self-reported race (SRR) of primarily U.S. populations. Due to heterogeneous genetic admixture and biological consequences of social determinants, the true association of African ancestry with TNBC biology is unclear. To address this, we conducted RNA sequencing on an international cohort of AAs, as well as West and East Africans with TNBC. Using comprehensive genetic ancestry estimation in this African-enriched cohort, we found expression of 613 genes associated with African ancestry and 2,000+ associated with regional African ancestry. A subset of African-associated genes also showed differences in normal breast tissue. Pathway enrichment and deconvolution of tumor cellular composition revealed that tumor-associated immunologic profiles are distinct in patients of African descent.

SIGNIFICANCE

Our comprehensive ancestry quantification process revealed that ancestry-associated gene expression profiles in TNBC include population-level distinctions in immunologic landscapes. These differences may explain some differences in race-group clinical outcomes. This study shows the first definitive link between African ancestry and the TNBC immunologic landscape, from an African-enriched international multiethnic cohort. See related commentary by Hamilton et al., p. 2496. This article is highlighted in the In This Issue feature, p. 2483.

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

Accurate ancestry inference is critical for identifying genetic contributors of cancer disparities among populations. Although methods to infer genetic ancestry have historically relied upon genome-wide markers, the adaptation to targeted clinical sequencing panels presents an opportunity to incorporate ancestry inference into routine diagnostic workflows. We show that global ancestral contributions and admixture of continental populations can be quantitatively inferred using markers captured by the MSK-IMPACT clinical panel. In a pan-cancer cohort of 45,157 patients, we observed differences by ancestry in the frequency of somatic alterations, recapitulating known associations and revealing novel associations. Despite the comparable overall prevalence of driver alterations by ancestry group, the proportion of patients with clinically actionable alterations was lower for African (30%) compared with European (33%) ancestry. Although this result is largely explained by population-specific cancer subtype differences, it reveals an inequity in the degree to which different populations are served by existing precision oncology interventions.

SIGNIFICANCE

We performed a comprehensive analysis of ancestral associations with somatic mutations in a real-world pan-cancer cohort, including >5,000 non-European individuals. Using an FDA-authorized tumor sequencing panel and an FDA-recognized oncology knowledge base, we detected differences in the prevalence of clinically actionable alterations, potentially contributing to health care disparities affecting underrepresented populations. This article is highlighted in the In This Issue feature, p. 2483.

Disparities in cancer genetics care by race/ethnicity among pan-cancer patients with pathogenic germline variants

BACKGROUND

Germline risk assessment is increasing as part of cancer care; however, disparities in subsequent genetic counseling are unknown.

METHODS

Pan-cancer patients were prospectively consented to tumor-normal sequencing via custom next generation sequencing panel (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) inclusive of germline analysis of ≥76 genes from January 2015 through December 2019 (97.5% research nonbillable) with protocol for genetics referral. Rates of pathogenic/likely pathogenic germline variants (PVs) and downstream counseling were compared across ancestry groups (mutually exclusive groups based on self-reported race/ethnicity and Ashkenazi Jewish [AJ] heritage) using nonparametric tests and multivariable logistic regression models.

RESULTS

Among 15,775 patients (59.6%, non-Hispanic [NH]-White; 15.7%, AJ; 20.5%, non-White [6.9%, Asian; 6.8%, Black/African American (AA); 6.7%, Hispanic; 0.1%, Other], and 4.2%, unknown), 2663 (17%) had a PV. Non-White patients had a lower PV rate (n = 433, 13.4%) compared to NH-Whites (n = 1451, 15.4%) and AJ patients (n = 683, 27.6%), p < .01, with differences in mostly moderate and low/recessive/uncertain penetrance variants. Among 2239 patients with new PV, 1652 (73.8%) completed recommended genetic counseling. Non-White patients had lower rates of genetic counseling (67.7%) than NH-White (73.7%) and AJ patients (78.8%), p < .01, with lower rates occurring in Black/AA (63%) compared to NH-White patients, even after adjustment for confounders (odds ratio, 0.60; 95% confidence interval, 0.37-0.97; p = .036). Non-White, particularly Black/AA and Asian, probands had a trend toward lower rates and numbers of at-risk family members being seen for counseling/genetic testing.

CONCLUSIONS

Despite minimizing barriers to genetic testing, non-White patients were less likely to receive recommended cancer genetics follow-up, with potential implications for oncologic care, cancer risk reduction, and at-risk family members.

LAY SUMMARY

Genetic testing is becoming an important part of cancer care, and we wanted to see if genetics care was different between individuals of different backgrounds. We studied 15,775 diverse patients with cancer who had genetic testing using a test called MSK-IMPACT that was covered by research funding. Clinically important genetic findings were high in all groups. However, Black patients were less likely to get recommended counseling compared to White patients. Even after removing many roadblocks, non-White and especially Black patients were less likely to get recommended genetics care, which may affect their cancer treatments and families.

Solving the puzzle of what makes immunotherapies work

The rapid adoption of immune checkpoint blockade (ICB) therapies has led to a need to understand the mechanistic drivers of efficacy and the identification of novel biomarkers that enrich for patients who benefit from ICB therapy. Here, we provide a perspective on emerging biomarker candidates, their underlying biological mechanisms, and how they may fit into the current landscape of ICB biomarkers. We discuss new frameworks to identify and evaluate biomarker candidates and review the opportunities and challenges of utilizing biomarker-derived models to facilitate the development of new immunotherapies.

Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors

The immune checkpoint inhibitor (ICI) pembrolizumab is US FDA approved for treatment of solid tumors with high tumor mutational burden (TMB-high; ≥10 variants/Mb). However, the extent to which TMB-high generalizes as an accurate biomarker in diverse patient populations is largely unknown. Using two clinical cohorts, we investigated the interplay between genetic ancestry, TMB, and tumor-only versus tumor-normal paired sequencing in solid tumors. TMB estimates from tumor-only panels substantially overclassified individuals into the clinically important TMB-high group due to germline contamination, and this bias was particularly pronounced in patients with Asian/African ancestry. Among patients with non-small cell lung cancer treated with ICIs, those misclassified as TMB-high from tumor-only panels did not associate with improved outcomes. TMB-high was significantly associated with improved outcomes only in European ancestries and merits validation in non-European ancestry populations. Ancestry-aware tumor-only TMB calibration and ancestry-diverse biomarker studies are critical to ensure that existing disparities are not exacerbated in precision medicine.

Pyroptosis: a novel signature to predict prognosis and immunotherapy response in gliomas

Gliomas are the most common primary brain tumors and are highly malignant with a poor prognosis. Pyroptosis, an inflammatory form of programmed cell death, promotes the inflammatory cell death of cancer. Studies have demonstrated that pyroptosis can promote the inflammatory cell death (ICD) of cancer, thus affecting the prognosis of cancer patients. Therefore, genes that control pyroptosis could be a promising candidate bio-indicator in tumor therapy. The function of pyroptosis-related genes (PRGs) in gliomas was investigated based on the Chinese Glioma Genome Atlas (CGGA), the Cancer Genome Atlas (TCGA) and the Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. In this study, using the non-negative matrix factorization (NMF) clustering method, 26 PRGs from the RNA sequencing data were divided into two subgroups. The LASSO and Cox regression was used to develop a 4-gene (BAX, Caspase-4, Caspase-8, PLCG1) risk signature, and all glioma patients in the CGGA, TCGA and Rembrandt cohorts were divided into low- and high-risk groups. The results demonstrate that the gene risk signature related to clinical features can be used as an independent prognostic indicator in glioma patients. Moreover, the high-risk subtype had rich immune infiltration and high expression of immune checkpoint genes in the tumor immune microenvironment (TIME). The analysis of the Submap algorithm shows that patients in the high-risk group could benefit more from anti-PD1 treatment. The risk characteristics associated with pyroptosis proposed in this study play an essential role in TIME and can potentially predict the prognosis and immunotherapeutic response of glioma patients.

Analysis of germline-driven ancestry-associated gene expression in cancers

Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort.

For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021).

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Protocol for obtaining controlled access TCGA datasets

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Protocols for quality control analysis and genotype imputation of TCGA germline data

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Statistical analysis for determining ancestry-associated SNPs

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Determination of ancestry-associated germline genetic variation driving mRNA expression

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Characterization of genetic predisposition to molecular subtypes of breast cancer in Brazilian patients

Introduction

BRCA1 and BRCA2 germline pathogenic variants (GPVs) account for most of the 5-10% of breast cancer (BC) that is attributable to inherited genetic variants. BRCA1 GPVs are associated with the triple negative subtype, whereas BRCA2 GPVs are likely to result in higher grade, estrogen-receptor positive BCs. The contribution of other genes of high and moderate risk for BC has not been well defined and risk estimates to specific BC subtypes is lacking, especially for an admixed population like Brazilian.

Objective

The aim of this study is to evaluate the value of a multigene panel in detecting germline mutations in cancer-predisposing genes for Brazilian BC patients and its relation with molecular subtypes and the predominant molecular ancestry.

Patients and methods

A total of 321 unrelated BC patients who fulfilled NCCN criteria for BRCA1/2 testing between 2016-2018 were investigated with a 94-genes panel. Molecular subtypes were retrieved from medical records and ancestry-specific variants were obtained from off-target reads obtained from the sequencing data.

Results

We detected 83 GPVs in 81 patients (positivity rate of 25.2%). Among GPVs, 47% (39/83) were identified in high-risk BC genes (BRCA1/2, PALB2 and TP53) and 18% (15/83) in moderate-penetrance genes (ATM, CHEK2 and RAD51C). The remainder of the GPVs (35% - 29/83), were identified in lower-risk genes. As for the molecular subtypes, triple negative BC had a mutation frequency of 31.6% (25/79), with predominance in BRCA1 (12.6%; 10/79). Among the luminal subtypes, except Luminal B HER2-positive, 18.7% (29/155) had GPV with BRCA1/2 genes contributing 7.1% (11/155) and non-BRCA1/2 genes, 12.9% (20/155). For Luminal B HER2-positive subtype, 40% (16/40) had GPVs, with a predominance of ATM gene (15% - 6/40) and BRCA2 with only 2.5% (1/40). Finally, HER2-enriched subtype presented a mutation rate of 30.8% (4/13) with contribution of BRCA2 of 7.5% (1/13) and non-BRCA1/2 of 23% (3/13). Variants of uncertain significance (VUS) were identified in 77.6% (249/321) of the patients and the number of VUS was increased in patients with Asian and Native American ancestry.

Conclusion

The multigene panel contributed to identify GPVs in genes other than BRCA1/2, increasing the positivity of the genetic test from 9.6% (BRCA1/2) to 25.2% and, considering only the most clinically relevant BC predisposing genes, to 16.2%. These results indicate that women with clinical criteria for hereditary BC may benefit from a multigene panel testing, as it allows identifying GPVs in genes that directly impact the clinical management of these patients and family members.

Analysis of KIR gene variants in The Cancer Genome Atlas and UK Biobank using KIRCLE

BACKGROUND

Natural killer (NK) cells represent a critical component of the innate immune system's response against cancer and viral infections, among other diseases. To distinguish healthy host cells from infected or tumor cells, killer immunoglobulin receptors (KIR) on NK cells bind and recognize Human Leukocyte Antigen (HLA) complexes on their target cells. However, NK cells exhibit great diversity in their mechanism of activation, and the outcomes of their activation are not yet understood fully. Just like the HLAs they bind, KIR receptors exhibit high allelic diversity in the human population. Here we provide a method to identify KIR allele variants from whole exome sequencing data and uncover novel associations between these variants and various molecular and clinical correlates.

RESULTS

In order to better understand KIRs, we have developed KIRCLE, a novel method for genotyping individual KIR genes from whole exome sequencing data, and used it to analyze approximately sixty-thousand patient samples in The Cancer Genome Atlas (TCGA) and UK Biobank. We were able to assess population frequencies for different KIR alleles and demonstrate that, similar to HLA alleles, individuals' KIR alleles correlate strongly with their ethnicities. In addition, we observed associations between different KIR alleles and HLA alleles, including HLA-B*53 with KIR3DL2*013 (Fisher's exact FDR = 7.64e-51). Finally, we showcased statistically significant associations between KIR alleles and various clinical correlates, including peptic ulcer disease (Fisher's exact FDR = 0.0429) and age of onset of atopy (Mann-Whitney U FDR = 0.0751).

CONCLUSIONS

We show that KIRCLE is able to infer KIR variants accurately and consistently, and we demonstrate its utility using data from approximately sixty-thousand individuals from TCGA and UK Biobank to discover novel molecular and clinical correlations with KIR germline variants. Peptic ulcer disease and atopy are just two diseases in which NK cells may play a role beyond their "classical" realm of anti-tumor and anti-viral responses. This tool may be used both as a benchmark for future KIR-variant-inference algorithms, and to better understand the immunogenomics of and disease processes involving KIRs.

Persistent ethnicity-associated disparity in anti-tumor effectiveness of immune checkpoint inhibitors despite equal access

We reviewed response to immune checkpoint inhibitors (ICI) of 207 patients with diagnoses of lung or head and neck cancer treated with chemotherapy/ICI combination therapy and ICI monotherapy between 2015 and 2020 at one of three clinical pavilions associated with the Dan L. Duncan Comprehensive Cancer Center at Baylor College of Medicine. Two of these pavilions (Harris Health System and the Michael E. DeBakey Veterans Affairs Medical Center) serve large minority populations and provide equal access to care regardless of means. 174 patients had a diagnosis of lung cancer (non-small cell or small cell) and 33 had a diagnosis of head and neck squamous cell carcinoma (HNSCC). 38% self-identified as Black, 45% as non-Hispanic White, and 18% as Hispanic. The objective response rate (ORR) was similar for lung cancer (35.057%) and HNSCC patients (30.3%) (p=0.894). The ORR for Hispanic and Black patients was lower compared to non-Hispanic White patients (H 27.0%, B 32.5%, W 38.7%; H vs. W p=0.209; B vs. W p=0.398). When considering only patients treated with ICI monotherapy, the ORR for Hispanic patients dropped further to 20.7% while the ORR of Black and non-Hispanic White patients remained about the same (B 29.3% and W 35.9%, H vs. W p=0.133; B vs. W p=0.419). Immune related adverse events were the lowest in the Hispanic population occurring in only 30% of patients compared to 40% of patients in the Black cohort and 50% of the non-Hispanic White cohorts.

DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse

We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc ^Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

Dissecting the Interplay Between Genetic Ancestry and Neighborhood Socioeconomic Status on Triple Negative Breast Cancer

OBJECTIVE

To investigate the impact of global and local genetic ancestry and neighborhood socioeconomic status (nSES), on breast cancer (BC) subtype, and gene expression.

SUMMARY OF BACKGROUND DATA

Higher rates of aggressive BC subtypes (TNBC) and worse overall BC survival are seen in black women [Hispanic (HB) and non-Hispanic (NHB)] and women from low nSES. However, the complex relationship between genetic ancestry, nSES, and BC subtype etiology remains unknown.

METHODS

Genomic analysis was performed on the peripheral blood from a cohort of 308 stage I-IV non-Hispanic White (NHW), Hispanic White (HW), HB and NHB women with BC. Patient and tumor characteristics were collected. Global and local ancestral estimates were calculated. Multinomial logistic regression was performed to determine associations between age, stage, genetic ancestry, and nSES on rates of TNBC compared to ER+/HER2-, ER+/HER2+, and ER-/HER2+ disease.

RESULTS

Among 308 women, we identified a significant association between increasing West African (WA) ancestry and odds of TNBC (OR 1.06,95%CI 1.001-1.126, P=0.046) as well as an inverse relationship between higher nSES and TNBC (OR 0.343,95%CI 0.151-0.781, P=0.011). WA ancestry remained significantly associated with TNBC when adjusting for patient age and tumor stage, but not when adjusting for nSES (OR 1.049, 95%CI-0.987-1.116, P=0.120). Local ancestry analysis revealed nSES-independent enriched WA ancestral segment centered at chr2:42004914 (P=3.70×10-5) in patients with TNBC.

CONCLUSIONS

In this translational epidemiologic study of genetic ancestry and nSES on BC subtype, we discovered associations between increasing WA ancestry, low nSES, and higher rates of TNBC compared to other BC subtypes. Moreover, on admixture mapping, specific chromosomal segments were associated with WA ancestry and TNBC, independent of nSES. However, on multinomial logistic regression adjusting for WA ancestry, women from low nSES were more likely to have TNBC, independent of genetic ancestry. These findings highlight the complex nature of TNBC and the importance of studying potential gene-environment interactions as drivers of TNBC.

Adaptive stress response genes associated with breast cancer subtypes and survival outcomes reveal race-related differences

Aggressive breast cancer variants, like triple negative and inflammatory breast cancer, contribute to disparities in survival and clinical outcomes among African American (AA) patients compared to White (W) patients. We previously identified the dominant role of anti-apoptotic protein XIAP in regulating tumor cell adaptive stress response (ASR) that promotes a hyperproliferative, drug resistant phenotype. Using The Cancer Genome Atlas (TCGA), we identified 46–88 ASR genes that are differentially expressed (2-fold-change and adjusted p-value < 0.05) depending on PAM50 breast cancer subtype. On average, 20% of all 226 ASR genes exhibited race-related differential expression. These genes were functionally relevant in cell cycle, DNA damage response, signal transduction, and regulation of cell death-related processes. Moreover, 23% of the differentially expressed ASR genes were associated with AA and/or W breast cancer patient survival. These identified genes represent potential therapeutic targets to improve breast cancer outcomes and mitigate associated health disparities.

Targeting STT3A produces an anti-tumor effect in lung adenocarcinoma by blocking the MAPK and PI3K/AKT signaling pathway

Background

Glycosylation is crucial for the stability and biological functions of proteins. The aberrant glycosylation of critical proteins plays an important role in multiple cancers, including lung adenocarcinoma (LUAD). STT3 oligosaccharyltransferase complex catalytic subunit A (STT3A) is a major isoform of N-linked glycosyltransferase that catalyzes the glycosylation of various proteins. However, the functions of STT3A in LUAD are still unclear.

Methods

The expression profiles of STT3A were initially analyzed in public data sets and then validated by quantitative real-time polymerase chain reaction, Western blot and immunohistochemistry assays in clinical LUAD samples. The overall survival (OS) between patients with high and low STT3A expression was compared using a Kaplan-Meier curve with a log-rank analysis. STT3A was knocked-out using CRISPR/Cas9 and inhibited by NGI-1. Cell Counting Kit-8, colony formation assay, wound-healing, transwell assay, and flow cytometry were performed to assess the cellular functions of STT3A in vitro. A mice xenograft model was established to investigate the effects of STT3A on tumor growth in vivo. Further, the downstream signaling pathways of STT3A were screened by mass spectrometry with a bioinformatics analysis, and the activation of the target pathways were subsequently validated by Western blot.

Results

The expression of STT3A was frequently upregulated in LUAD tissues than normal lung tissues. The high expression of STT3A was significantly associated with poor OS in LUAD patients. The knockout or inhibition of STT3A suppressed proliferation, migration, and invasion, and arrested the cell cycle of LUAD cell lines in vitro. Similarly, the knockout or inhibition of STT3A suppressed tumor growth in vivo. In terms of molecular mechanism, STT3A may promote LUAD progression by activating the mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-kinase and protein kinase B (PI3K/AKT) pathways and regulating the epithelial-mesenchymal transition.

Conclusions

STT3A promotes LUAD progression via the MAPK and PI3K/AKT signaling pathways and could serve as a novel prognostic biomarker and potential therapeutic target for LUAD patients.

HPV51-associated Leiomyosarcoma: A Novel Class of TP53/RB1-Wildtype Tumor With Predilection for the Female Lower Reproductive Tract

Inactivating mutations in tumor suppressor genes TP53 and RB1 are considered central drivers in leiomyosarcomas (LMSs). In high-risk human papillomavirus (HPV)-related tumors, a similar functional outcome is achieved through oncoproteins E6 and E7, which inactivate the p53 and RB1 proteins, respectively. Here, we hypothesized that HPV infection could provide an alternative mechanism for tumorigenesis in a subset of TP53/RB1-wildtype LMS. We evaluated tumor samples from 2585 consecutive unique patients carrying a diagnosis of gynecologic or soft tissue LMS. Tumor DNA and available RNA were analyzed by hybrid-capture-based next-generation sequencing/comprehensive genomic profiling of 406 genes and transcripts (FoundationOneHeme). Of the initial 2585 cases, we excluded 16 based on the presence of molecular alterations that are considered defining for sarcomas other than LMS. In the remaining 2569 cases, we searched for LMS that were TP53/RB1-wildtype (n=486 of 2569; 18.9%). We also searched LMS tumors for HPV sequences that we then classified into genotypes by de novo assembly of nonhuman sequencing reads followed by alignment to the RefSeq database. Among TP53/RB1-wildtype LMS, we identified 18 unique cases harboring HPV sequences. Surprisingly, most (n=11) were HPV51-positive, and these 11 represented all HPV51-positive tumors in our entire LMS database (n=11 of 2569; 0.4%). The absence of genomic alterations in TP53 or RB1 in HPV51-positive LMS represented a marked difference from HPV51-negative LMS (n=2558; 0% vs. 72% [P<0.00001], 0% vs. 53% [P=0.0002]). In addition, compared with HPV51-negative LMS, HPV51-positive LMS were significantly enriched for genomic alterations in ATRX (55% vs. 24%, P=0.027) and TSC1 (18% vs. 0.6%, P=0.0047). All HPV51-positive LMS were in women; median age was 54 years at surgery (range: 23 to 74 y). All known primary sites were from the gynecologic tract or adjacent anogenital area, including 5 cases of vaginal primary site. Histology was heterogeneous, with evaluable cases showing predominant epithelioid (n=5) and spindle (n=5) morphology. In situ hybridization confirmed the presence of high-risk HPV E6/E7 mRNA in tumor cells in three of three evaluable cases harboring HPV51 genomic sequences. Overall, in our pan-LMS analysis, HPV reads were identified in a subset of TP53/RB1-wildtype LMS. For all HPV51-associated LMS, the striking absence of any detectable TP53 or RB1 mutations and predilection for the female lower reproductive tract supports our hypothesis that high-risk HPV can be an alternative tumorigenic mechanism in this distinct class of LMS.

Mutational signatures and processes in hepatobiliary cancers

The evolutionary history of hepatobiliary cancers is embedded in their genomes. By analysing their catalogue of somatic mutations and the DNA sequence context in which they occur, it is possible to infer the mechanisms underpinning tumorigenesis. These mutational signatures reflect the exogenous and endogenous origins of genetic damage as well as the capacity of hepatobiliary cells to repair and replicate DNA. Genomic analysis of thousands of patients with hepatobiliary cancers has highlighted the diversity of mutagenic processes active in these malignancies, highlighting a prominent source of the inter-cancer-type, inter-patient, intertumour and intratumoural heterogeneity that is observed clinically. However, a substantial proportion of mutational signatures detected in hepatocellular carcinoma and biliary tract cancer remain of unknown cause, emphasizing the important contribution of processes yet to be identified. Exploiting mutational signatures to retrospectively understand hepatobiliary carcinogenesis could advance preventative management of these aggressive tumours as well as potentially predict treatment response and guide the development of therapies targeting tumour evolution.

Improvements Achieved by Multiple Imputation for Single-Cell RNA-Seq Data in Clustering Analysis and Differential Expression Analysis

In a single-cell RNA-seq (scRNA-seq) data set, a high proportion of missing values (or an excessive number of zeroes) are frequently observed. For the related follow-up tasks, such as clustering analysis and differential expression analysis, a data set without missing values is generally required. Many imputation approaches have been proposed for this purpose. Multiple imputation (MI) is a well-established approach to address possible biases in a follow-up analysis result based on one-time imputed data. There is a lack of investigation on this in the analysis of scRNA-seq data. In this study, we have investigated how to efficiently apply the MI approach to the clustering analysis and the differential expression analysis of scRNA-seq data. We proposed an MI procedure for clustering analysis and an MI procedure for differential expression analysis. To demonstrate the improvements achieved by MI in clustering analysis and differential expression analysis of scRNA-seq data, we analyzed three well-known scRNA-seq data sets. scIGANs, an scRNA-seq imputation method based on the generative adversarial networks (GANs), has been recently proposed for scRNA-seq data imputation. Multiple randomly imputed data sets can be conveniently generated by this method. We implemented our MI procedures based on scIGANs. We demonstrated that MI yielded improved performances on the clustering analysis and differential expression analysis results. Our applications to experimental scRNA-seq data illustrated the advantages of MI over one-time imputation of missing values in scRNA-seq data.

How inclusive are cell lines in preclinical engineered cancer models?

Diverse factors contribute to significant and dire disparities in cancer risk and treatment outcomes. To address this, there was a call for inclusion of sex as a biological variable, which resulted in more instances of careful inclusion of sex in preclinical studies of cancer. Another variable in cancer treatment is genetic ancestry. Although this is considered explicitly in clinical research, it is considerably neglected in preclinical studies. Preclinical research can use several 3D in vitro model systems, such as spheroids/organoids, xenografts, or other bioengineered systems that combine biomaterials and cellular material. Ultimately, the cellular base for all of these in vitro model systems is derived from human cell lines or patient samples, to investigate mechanisms of cancer and screen novel therapeutics, all of which aim to maximize successful outcomes in clinical trials. This in itself offers an opportunity to potentiate effective treatments for many groups of people, when diverse variables like genetic ancestry are consciously included into study design. This Perspective highlights the need for conscious inclusion of genetic ancestry in preclinical cancer tissue engineering, especially when it pertains to determining therapeutic outcomes.

Summary: Genetic determinants, like ancestry, impact cancer risk and therapeutic outcomes. Hence, this is an important variable to consider at the very initial stages of biomedical research at the bench.

The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients

Purposes

Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches.

Patients and Methods

We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes.

Results

PAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors.

Conclusions

This is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America.

Clinical Trial Registration

ClinicalTrials.gov (Identifier: NCT02326857).

A novel risk score model based on five angiogenesis-related long non-coding RNAs for bladder urothelial carcinoma

Background

Tumour angiogenesis is an independent risk factor for bladder urothelial carcinoma (BUC) progression, but viable and promising antiangiogenic targets are understudied. Emerging evidence suggests that long non-coding RNAs (lncRNAs) play prominent role in the tumour microenvironment and tumour angiogenesis.

Methods

The clinical data of BUC patients were obtained from TCGA database and clinical specimens of 138 BUC patients. Univariate and multivariate COX regression analyses were used to identify survival-related ARLNRs (sARLNRs) from The Molecular Signatures Database v4.0. Fisher’s exact probability method was used to detect the correlations between sARLNRs levels and clinicopathological characteristics. A chain of experiments including FACS, qPCR, immunohistochemistry, tube formation, migration and invasion assays, combining with co-culture models, were utilized to validate the clinical significance and angiogenetic correlation of sARLNRs.

Results

Five sARLNRs were employed to establish an angiogenesis-related risk score model, by which patients in the low-risk group obtained better overall survival than those in the high-risk group. The expression of AC005625.1 and AC008760.1 was significantly related to ECs percentage, tumour size and muscle invasion status. Besides, AC005625.1 and AC008760.1 expressed lower in BUC cell lines and tumour tissues than that in normal urothelial cells and adjacent normal tissues, with much lower levels in more advanced T stages. A prominently higher proportion of ECs was detected in tumour tissues with lower expression of AC005625.1 and AC008760.1. In the co-culture models, we found that knockdown of AC005625.1 and AC008760.1 in BUC cells increased the tube formation, migration and invasion abilities of HUVEC. The expression levels of CD31, VEGF-A, VIMENTIN and N-CADHERIN were also enhanced in HUVEC cells co-cultured with siR-AC005625.1 and siR-AC008760.1-treated T24 cells.

Conclusion

In the study, we identify five sARLNRs and validate their clinical significance, angiogenesis correlation and prognosis-predictive values in BUC. These findings may provide a new perspective and some promising antiangiogenic targets for clinical diagnosis and treatment strategies of BUC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02575-1.

Associations of Genetic Ancestry with Terminal Duct Lobular Unit Involution among Healthy Women

Reduced age-related terminal duct lobular unit (TDLU) involution has been linked to increased breast cancer risk and triple-negative breast cancer (TNBC). Associations of TDLU involution levels with race and ethnicity remain incompletely explored. Herein, we examined associations between genetic ancestry and TDLU involution in normal breast tissue donated by 2,014 healthy women in the US. Women of African ancestry were more likely than European women to have increased TDLU counts (odds ratio [OR]trend=1.36; 95% CI = 1.07-1.74), acini counts/TDLU (OR = 1.47; 95% CI = 1.06-2.03), and median TDLU span (ORtrend=1.44; 95% CI = 1.08-1.91), indicating lower involution; whereas East Asian descendants were associated with decreased TDLU counts (ORtrend=0.52; 95% CI = 0.35-0.78) after controlling for potential confounders. These associations are consistent with the racial variations in incidence rates of TNBC in the US and suggest opportunities for future work examining whether TDLU involution may mediate the racial differences in subtype-specific breast cancer risk.

Differences in somatic TP53 mutation type in breast tumors by race and receptor status

PURPOSE

Somatic driver mutations in TP53 are associated with triple-negative breast cancer (TNBC) and poorer outcomes. Breast cancers in women of African ancestry (AA) are more likely to be TNBC and have somatic TP53 mutations than cancers in non-Hispanic White (NHW) women. Missense driver mutations in TP53 have varied functional impact including loss-of-function (LOF) or gain-of-function (GOF) activity, and dominant negative (DNE) effects. We aimed to determine if there were differences in somatic TP53 mutation types by patient ancestry or TNBC status.

METHODS

We identified breast cancer datasets with somatic TP53 mutation data, ancestry, age, and hormone receptor status. Mutations were classified for functional impact using published data and type of mutation. We assessed differences using Fisher's exact test.

RESULTS

From 96 breast cancer studies, we identified 2964 women with somatic TP53 mutations: 715 (24.1%) Asian, 258 (8.7%) AA, 1931 (65.2%) NHW, and 60 (2%) Latina. The distribution of TP53 mutation type was similar by ancestry. However, 35.8% of tumors from NHW individuals had GOF mutations compared to 29% from AA individuals (p = 0.04). Mutations with DNE activity were positively associated with TNBC (OR 1.37, p = 0.03) and estrogen receptor (ER) negative status (OR 1.38; p = 0.005).

CONCLUSIONS

Somatic TP53 mutation types did not differ by ancestry overall, but GOF mutations were more common in NHW women than AA women. ER-negative and TNBC tumors are less likely to have DNE+ TP53 mutations which could reflect biological processes. Larger cohorts and functional studies are needed to further elucidate these findings.

Tumor molecular differences associated with outcome disparities of Black patients with head and neck cancer

BACKGROUND

Numerous studies of head and neck squamous cell carcinoma (HNSCC) have demonstrated disparate outcomes by race and ethnicity. Beyond known associations with socioeconomic variables, whether these are also associated with differences in tumor molecular composition has thus far been poorly explored.

METHODS

We downloaded clinical and multiplatform molecular data from The Cancer Genome Atlas and other published studies. These were compared between non-Hispanic Black (n = 43) and White (n = 354) patients with non-HPV-related tumors, using multivariable models. Publicly available validation cohorts were used.

RESULTS

Black patients had poorer progression-free survival than White patients. Tumors of Black patients had greater copy number aberrations, and increased SFRP1 methylation and miRNA-mediated PRG4 silencing associated with poor survival. PI3K/AkT/mTOR pathway proteins were differentially expressed.

CONCLUSIONS

There are molecular differences between tumors of Black and White patients that may partially account for differences in survival. These may inform targeted treatment decisions to achieve equitable outcomes.

The Genomics of Colorectal Cancer in Populations with African and European Ancestry

Blacks have a higher incidence of colorectal cancer (CRC) and worse survival rates when compared to Whites. Comprehensive genomic profiling was performed in 46,140 colorectal adenocarcinoma cases. Ancestry-informative markers identified 5,301 patients of African descent (AFR) and 33,770 patients of European descent (EUR). AFR were younger, had fewer MSI-H tumors, and had significantly more frequent alterations in KRAS, APC, and PIK3CA. AFR had increased frequency of KRAS mutations specifically KRAS G12D and KRAS G13. There were no differences in rates of actionable kinase driver alterations (HER2, MET, NTRK, ALK, ROS1, RET). In patients with young onset CRC (&lt;50 years), AFR and EUR had similar frequency of MSI-H and TMB-H tumors, and strikingly different trends in APC mutations by age, as well as differences in MAPK pathway alterations. These findings inform treatment decisions, impact prognosis, and underscore the need for model systems representative of our diverse US population.

Race-associated molecular changes in gynecologic malignancies

The difference in cancer morbidity and mortality between individuals of different racial groups is complex. Health disparities provide a framework to explore potential connections between poor outcomes and individuals of different racial backgrounds. This study identifies genomic changes in African-American patients with gynecologic malignancies, a population with well-established disparities in outcomes. Our data explore whether social health disparities might mediate interactions between the environment and tumor epigenomes and genomes that can be identified. Using The Cancer Genetic Ancestry Atlas, which encodes data from The Cancer Genome Atlas by ancestry and allows for systematic analyses of sequencing data by racial group, we performed large-scale, comparative analyses to identify novel targets with alterations in methylation, transcript, and microRNA expression between tumors from women of European American or African American racial groups across all gynecologic malignancies. We identify novel discrete genomic changes in these complex malignancies and suggest a framework for identifying novel therapeutic targets for future investigation.

Haplotypes of single cancer driver genes and their local ancestry in a highly admixed long-lived population of Northeast Brazil

Admixed populations have not been examined in detail in cancer genetic studies. Here, we inferred the local ancestry of cancer-associated single nucleotide polymorphisms (SNPs) and haplotypes of a highly admixed Brazilian population. SNP array was used to genotype 73 unrelated individuals aged 80-102 years. Local ancestry inference was performed by merging genotyped regions with phase three data from the 1000 Genomes Project Consortium using RFmix. The average ancestry tract length was 9.12-81.71 megabases. Strong linkage disequilibrium was detected in 48 haplotypes containing 35 SNPs in 10 cancer driver genes. All together, 19 risk and eight protective alleles were identified in 23 out of 48 haplotypes. Homozygous individuals were mainly of European ancestry, whereas heterozygotes had at least one Native American and one African ancestry tract. Native-American ancestry for homozygous individuals with risk alleles for HNF1B, CDH1, and BRCA1 was inferred for the first time. Results indicated that analysis of SNP polymorphism in the present admixed population has a high potential to identify new ancestry-associated alleles and haplotypes that modify cancer susceptibility differentially in distinct human populations. Future case-control studies with populations with a complex history of admixture could help elucidate ancestry-associated biological differences in cancer incidence and therapeutic outcomes.

Age influences on the molecular presentation of tumours

Cancer is often called a disease of aging. There are numerous ways in which cancer epidemiology and behaviour change with the age of the patient. The molecular bases for these relationships remain largely underexplored. To characterise them, we analyse age-associations in the nuclear and mitochondrial somatic mutational landscape of 20,033 tumours across 35 tumour-types. Age influences both the number of mutations in a tumour (0.077 mutations per megabase per year) and their evolutionary timing. Specific mutational signatures are associated with age, reflecting differences in exogenous and endogenous oncogenic processes such as a greater influence of tobacco use in the tumours of younger patients, but higher activity of DNA damage repair signatures in those of older patients. We find that known cancer driver genes such as CDKN2A and CREBBP are mutated in age-associated frequencies, and these alter the transcriptome and predict for clinical outcomes. These effects are most striking in brain cancers where alterations like SUFU loss and ATRX mutation are age-dependent prognostic biomarkers. Using three cancer datasets, we show that age shapes the somatic mutational landscape of cancer, with clinical implications.

Understanding how genetic ancestry may influence cancer development

Of the multifactorial determinants that lead to cancer health disparities among race groups, quantified genetic ancestry has begun to expand our knowledge beyond self-reported race. However, it is essential to study these biological determinants in the context of social determinants to truly improve clinical tools and achieve equitable survival outcomes.

Controls for Phylogeny and Robust Analysis in Pareto Task Inference

Understanding the tradeoffs faced by organisms is a major goal of evolutionary biology. One of the main approaches for identifying these tradeoffs is Pareto task inference (ParTI). Two recent papers claim that results obtained in ParTI studies are spurious due to phylogenetic dependence (Mikami T, Iwasaki W. 2021. The flipping t-ratio test: phylogenetically informed assessment of the Pareto theory for phenotypic evolution. Methods Ecol Evol. 12(4):696-706) or hypothetical p-hacking and population-structure concerns (Sun M, Zhang J. 2021. Rampant false detection of adaptive phenotypic optimization by ParTI-based Pareto front inference. Mol Biol Evol. 38(4):1653-1664). Here, we show that these claims are baseless. We present a new method to control for phylogenetic dependence, called SibSwap, and show that published ParTI inference is robust to phylogenetic dependence. We show how researchers avoided p-hacking by testing for the robustness of preprocessing choices. We also provide new methods to control for population structure and detail the experimental tests of ParTI in systems ranging from ammonites to cancer gene expression. The methods presented here may help to improve future ParTI studies.

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

OUP accepted manuscript

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.

OUP accepted manuscript

Background

Materials and Methods

Results

Conclusions

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer

Background and Aims

Individuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown.

Methods

Multiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences.

Results

We demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called “master transcriptional regulators” (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups.

Conclusion

Our study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

Landscape and Clonal Dominance of Co-occurring Genomic Alterations in Non-Small-Cell Lung Cancer Harboring MET Exon 14 Skipping

MET exon 14 skipping alterations (METex14) comprise a diverse set of actionable oncogene drivers in non–small-cell lung cancer (NSCLC). Recent studies have established the efficacy of tyrosine kinase inhibitors for this patient population. The landscape of co-occurring genetic alterations in METex14 NSCLC and their potential impact to therapeutic sensitivities has not yet been fully described.

Comprehensive Analysis of the Effects of Genetic Ancestry and Genetic Characteristics on the Clinical Evolution of Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC), a kind of malignant cancer, is associated with increasing morbidity and mortality. Patients with different genetic ancestries may respond differently to clinical treatment. The limited understanding of the influence of genetic ancestry and genetic characteristics on OSCC impedes the development of precision medicine. To provide a reference for clinical treatment, this study comprehensively analyzed multigenomic differences in OSCC patients with different genetic ancestries and their impact on prognosis. An analysis of data from OSCC patients with different genetic ancestries in The Cancer Genome Atlas (TCGA) showed that the overall survival (OS) of African (AFR) patients was lower than that of primarily European (EUR) patients, and differences were also observed in the tumor-stroma ratio (TSR) and tumor-infiltrating lymphocytes (TILs), which are associated with prognosis. FAT1 is a key mutant gene in OSCC, and it has inconsistent effects on clinical evolution for patients with diverse genetic characteristics. PIKfyve and CAPN9 showed a significant difference in mutation frequency between EUR and AFR; PIKfyve was related to Ki-67 expression, suggesting that it could promote tumor proliferation, and CAPN9 was related to the expression of Bcl-2, promoting tumor cell apoptosis. A variant methylation locus, cg20469139, was correlated with the levels of PD-L1 and Caspase-7 and modulated tumor cell apoptosis. A novel ceRNA model was constructed based on genetic ancestries, and it could accurately evaluate patient prognosis. More importantly, although T cell dysfunction scores could determine the potential of tumor immune escape, the efficacy was obviously affected by patients' genetic ancestries. To provide patients with more precise, personalized therapy and to further improve their quality of life and 5-year survival rate, the influence of genetic ancestry should be fully considered when selecting treatments.

Analytical protocol to identify local ancestry-associated molecular features in cancer

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the "local" ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).