Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer.

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3, and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.

Multiomic analysis of uterine leiomyomas in self-described Black and White women: molecular insights into health disparities.

BACKGROUND: Black women are at an increased risk of developing uterine leiomyomas and experiencing worse disease prognosis than White women. Epidemiologic and molecular factors have been identified as underlying these disparities, but there remains a paucity of deep, multiomic analysis investigating molecular differences in uterine leiomyomas from Black and White patients. OBJECTIVE: To identify molecular alterations within uterine leiomyoma tissues correlating with patient race by multiomic analyses of uterine leiomyomas collected from cohorts of Black and White women. STUDY DESIGN: We performed multiomic analysis of uterine leiomyomas from Black (42) and White (47) women undergoing hysterectomy for symptomatic uterine leiomyomata. In addition, our analysis included the application of orthogonal methods to evaluate fibroid biomechanical properties, such as second harmonic generation microscopy, uniaxial compression testing, and shear-wave ultrasonography analyses. RESULTS: We found a greater proportion of MED12 mutant uterine leiomyomas from Black women (>35% increase; Mann-Whitney U, P<.001). MED12 mutant tumors exhibited an elevated abundance of extracellular matrix proteins, including several collagen isoforms, involved in the regulation of the core matrisome. Histologic analysis of tissue fibrosis using trichrome staining and secondary harmonic generation microscopy confirmed that MED12 mutant tumors are more fibrotic than MED12 wild-type tumors. Using shear-wave ultrasonography in a prospectively collected cohort, Black patients had fibroids that were firmer than White patients, even when similar in size. In addition, these analyses uncovered ancestry-linked expression quantitative trait loci with altered allele frequencies in African and European populations correlating with differential abundance of several proteins in uterine leiomyomas independently of MED12 mutation status, including tetracoidpeptide repeat protein 38. CONCLUSION: Our study shows that Black women have a higher prevalence of uterine leiomyomas harboring mutations in MED12 and that this mutational status correlates with increased tissue fibrosis compared with wild-type uterine leiomyomas. Our study provides insights into molecular alterations correlating with racial disparities in uterine leiomyomas and improves our understanding of the molecular etiology underlying uterine leiomyoma development within these populations.

Metronomic dosing of ovarian cancer cells with the ATR inhibitor AZD6738 leads to loss of CDC25A expression and resistance to ATRi treatment.

OBJECTIVE: ATR kinase inhibitors promote cell killing by inducing replication stress and through potentiation of genotoxic agents in gynecologic cancer cells. To explore mechanisms of acquired resistance to ATRi in ovarian cancer, we characterized ATRi-resistant ovarian cancer cells generated by metronomic dosing with the clinical ATR inhibitor AZD6738. METHODS: ATRi-resistant ovarian cancer cells (OVCAR3 and OV90) were generated by dosing with AZD6738 and assessed for sensitivity to Chk1i (LY2603618), PARPi (Olaparib) and combination with cisplatin or a CDK4/6 inhibitor (Palbociclib). Models were characterized by diverse methods including silencing CDC25A in OV90 cells and assessing impact on ATRi response. Serum proteomic analysis of ATRi-resistant OV90 xenografts was performed to identify circulating biomarker candidates of ATRi-resistance. RESULTS: AZD6738-resistant cell lines are refractory to LY2603618, but not to Olaparib or combinations with cisplatin. Cell cycle analyses showed ATRi-resistant cells exhibit G1/S arrest following AZD6738 treatment. Accordingly, combination with Palbociclib confers resistance to AZD6738. AZD6738-resistant cells exhibit altered abundances of G1/S phase regulatory proteins, including loss of CDC25A in AZD6738-resistant OV90 cells. Silencing of CDC25A in OV90 cells confers resistance to AZD6738. Serum proteomics from AZD6738-resistant OV90 xenografts identified Vitamin D-Binding Protein (GC), Apolipoprotein E (APOE) and A1 (APOA1) as significantly elevated in AZD6738-resistant backgrounds. CONCLUSIONS: We show that metronomic dosing of ovarian cancer cells with AZD6738 results in resistance to ATR/ Chk1 inhibitors, that loss of CDC25A expression represents a mechanism of resistance to ATRi treatment in ovarian cancer cells and identify several circulating biomarker candidates of CDC25A low, AZD6738-resistant ovarian cancer cells.

Integrated multi-omic analysis of low-grade ovarian serous carcinoma collected from short and long-term survivors.

BACKGROUND: Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors. METHODS: Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed. RESULTS: We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets. CONCLUSIONS: This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

MutEnricher: a flexible toolset for somatic mutation enrichment analysis of tumor whole genomes.

BACKGROUND: Analysis of somatic mutations from tumor whole exomes has fueled discovery of novel cancer driver genes. However, ~ 98% of the genome is non-coding and includes regulatory elements whose normal cellular functions can be disrupted by mutation. Whole genome sequencing (WGS), on the other hand, allows for identification of non-coding somatic variation and expanded estimation of background mutation rates, yet fewer computational tools exist for specific interrogation of this space. RESULTS: We present MutEnricher, a flexible toolset for investigating somatic mutation enrichment in both coding and non-coding genomic regions from WGS data. MutEnricher contains two distinct modules for these purposes that provide customizable options for calculating sample- and feature-specific background mutation rates. Additionally, both MutEnricher modules calculate feature-level and local, or "hotspot," somatic mutation enrichment statistics. CONCLUSIONS: MutEnricher is a flexible software package for investigating somatic mutation enrichment that is implemented in Python, is freely available, can be efficiently parallelized, and is highly configurable to researcher's specific needs. MutEnricher is available online at https://github.com/asoltis/MutEnricher .

Assessment of Statin Interactions With the Human NTCP Transporter Using a Novel Fluorescence Assay.

Sodium taurocholate cotransporting polypeptide (NTCP), which is highly expressed in the sinusoidal membrane of hepatocytes, maintains bile acid homeostasis and participates in the hepatic disposition of a variety of endogenous substances as well as xenobiotics. Manifested by the involvement of organic anion-transporting polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) in the hepatic uptake of statin drugs, sinusoidal membrane transporters play an important role in the pharmacokinetics and pharmacodynamics of these agents. It has been speculated that NTCP may function as an alternative pathway for statin hepatic uptake, complementary to OATP1B1 and OATP1B3. In the current study, we produced stable NTCP-expressing human embryonic kidney 293 (HEK293) cells and developed a fluorescence-based assay using flow cytometry for measuring NTCP transport with chenodeoxycholyl-(Nε-7-nitrobenz-2-oxa-1,3-diazole)-lysine (CDCA-NBD) as the substrate. NTCP-mediated CDCA-NBD transport was time-dependent and exhibited typical Michaelis-Menten kinetics, with a Km of 6.12 µM. Compounds known to interact with NTCP, including chenodeoxycholic acid and taurocholic acid, displayed concentration-dependent inhibition of NTCP-mediated CDCA-NBD transport. We report here a systematic evaluation of the interaction between statins and the NTCP transporter. Utilizing this system, several statins were either found to inhibit NTCP-dependent transport or act as substrates. We find a good correlation between the reported lipophilicity of statins and their ability to inhibit NTCP. The objective was to develop a higher-throughput system to evaluate potential inhibitors such as the statins. The in vitro assays using CDCA-NBD as fluorescent substrate are convenient, rapid, and have utility in screening drug candidates for potential drug-NTCP interactions.

Neuroinflammatory astrocytes generated from cord blood-derived human induced pluripotent stem cells.

BACKGROUND: Astrocytes respond to central nervous system (CNS) injury and disease by transforming to a reactive astrogliosis cell state that can contribute to either CNS dysfunction or repair. Neuroinflammation is a powerful driver of a harmful A1 astrogliosis phenotype associated with in vitro neurotoxicity and histopathology in human neurodegenerative diseases. Here we report a protocol for the rapid development of a human cell culture model of neuroinflammatory astrogliosis using induced pluripotent stem cells (iPSCs). METHODS: Using RNA sequencing and in vitro cell assays, we measured transcriptional and cellular effects of chronic exposure of human iPSC-derived astrocytes to the cytokines TNFα (tumor necrosis factor alpha) or IL-1ß (interleukin-1 beta). RESULTS: We show TNFα and IL-1ß induce pro-inflammatory gene signatures but by widely different magnitudes. TNFα treatment results in 606 differential expressed genes, the suppression of glutamate-uptake, and increased phagocytic activity in astrocyte cultures. In contrast, IL-1ß effects are attenuated to 33 differential expressed genes and no significant effects on glutamate-uptake or increased phagocytic activity. CONCLUSION: Our approach demonstrates a rapid tool for modeling neuroinflammatory human astrocytic responses in nervous system trauma and disease. In particular, we reveal a model for robust TNFα-induced human astrogliosis suitable for the study of neurotoxic A1 astrocytes.

Neonatal mouse cortical but not isogenic human astrocyte feeder layers enhance the functional maturation of induced pluripotent stem cell-derived neurons in culture.

Human induced pluripotent stem (iPS) cell-derived neurons and astrocytes are attractive cellular tools for nervous system disease modeling and drug screening. Optimal utilization of these tools requires differentiation protocols that efficiently generate functional cell phenotypes in vitro. As nervous system function is dependent on networked neuronal activity involving both neuronal and astrocytic synaptic functions, we examined astrocyte effects on the functional maturation of neurons from human iPS cell-derived neural stem cells (NSCs). We first demonstrate human iPS cell-derived NSCs can be rapidly differentiated in culture to either neurons or astrocytes with characteristic cellular, molecular and physiological features. Although differentiated neurons were capable of firing multiple action potentials (APs), few cells developed spontaneous electrical activity in culture. We show spontaneous electrical activity was significantly increased by neuronal differentiation of human NSCs on feeder layers of neonatal mouse cortical astrocytes. In contrast, co-culture on feeder layers of isogenic human iPS cell-derived astrocytes had no positive effect on spontaneous neuronal activity. Spontaneous electrical activity was dependent on glutamate receptor-channel function and occurred without changes in INa , IK , Vm , and AP properties of iPS cell-derived neurons. These data demonstrate co-culture with neonatal mouse cortical astrocytes but not human isogenic iPS cell-derived astrocytes stimulates glutamatergic synaptic transmission between iPS cell-derived neurons in culture. We present RNA-sequencing data for an immature, fetal-like status of our human iPS cell-derived astrocytes as one possible explanation for their failure to enhance synaptic activity in our co-culture system.

Chromaffin cell biology: inferences from The Cancer Genome Atlas.

Pheochromocytomas and paragangliomas (PCC/PGLs) are rare neuroendocrine tumors that are unusually diverse in metabolic profiles, in classes of molecular alterations and across a large number of altered genes. The Cancer Genome Atlas (TCGA) comprehensively profiled the molecular landscape of PCC/PGLs and identified novel genomic alterations and a new molecular classification of PCC/PGLs. In this review, we discuss the significant clinico-molecular findings of this integrated profiling study. We then review the molecular data of the TCGA cohort centering around known markers of sympathoadrenal cell lineage to better understand chromaffin cell biology. This analysis adds a new layer, that of chromaffin cell type, onto the published molecular classifications and in doing so provides inferences about underlying chromaffin cell biology and diversity.

A murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response.

Targeted therapies have demonstrated efficacy against specific subsets of molecularly defined cancers. Although most patients with lung cancer are stratified according to a single oncogenic driver, cancers harbouring identical activating genetic mutations show large variations in their responses to the same targeted therapy. The biology underlying this heterogeneity is not well understood, and the impact of co-existing genetic mutations, especially the loss of tumour suppressors, has not been fully explored. Here we use genetically engineered mouse models to conduct a 'co-clinical' trial that mirrors an ongoing human clinical trial in patients with KRAS-mutant lung cancers. This trial aims to determine if the MEK inhibitor selumetinib (AZD6244) increases the efficacy of docetaxel, a standard of care chemotherapy. Our studies demonstrate that concomitant loss of either p53 (also known as Tp53) or Lkb1 (also known as Stk11), two clinically relevant tumour suppressors, markedly impaired the response of Kras-mutant cancers to docetaxel monotherapy. We observed that the addition of selumetinib provided substantial benefit for mice with lung cancer caused by Kras and Kras and p53 mutations, but mice with Kras and Lkb1 mutations had primary resistance to this combination therapy. Pharmacodynamic studies, including positron-emission tomography (PET) and computed tomography (CT), identified biological markers in mice and patients that provide a rationale for the differential efficacy of these therapies in the different genotypes. These co-clinical results identify predictive genetic biomarkers that should be validated by interrogating samples from patients enrolled on the concurrent clinical trial. These studies also highlight the rationale for synchronous co-clinical trials, not only to anticipate the results of ongoing human clinical trials, but also to generate clinically relevant hypotheses that can inform the analysis and design of human studies.

Characterization of HPV and host genome interactions in primary head and neck cancers.

Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis.

Cafeteria diet-induced obesity causes oxidative damage in white adipose.

Obesity continues to be one of the most prominent public health dilemmas in the world. The complex interaction among the varied causes of obesity makes it a particularly challenging problem to address. While typical high-fat purified diets successfully induce weight gain in rodents, we have described a more robust model of diet-induced obesity based on feeding rats a diet consisting of highly palatable, energy-dense human junk foods - the "cafeteria" diet (CAF, 45-53% kcal from fat). We previously reported that CAF-fed rats became hyperphagic, gained more weight, and developed more severe hyperinsulinemia, hyperglycemia, and glucose intolerance compared to the lard-based 45% kcal from fat high fat diet-fed group. In addition, the CAF diet-fed group displayed a higher degree of inflammation in adipose and liver, mitochondrial dysfunction, and an increased concentration of lipid-derived, pro-inflammatory mediators. Building upon our previous findings, we aimed to determine mechanisms that underlie physiologic findings in the CAF diet. We investigated the effect of CAF diet-induced obesity on adipose tissue specifically using expression arrays and immunohistochemistry. Genomic evidence indicated the CAF diet induced alterations in the white adipose gene transcriptome, with notable suppression of glutathione-related genes and pathways involved in mitigating oxidative stress. Immunohistochemical analysis indicated a doubling in adipose lipid peroxidation marker 4-HNE levels compared to rats that remained lean on control standard chow diet. Our data indicates that the CAF diet drives an increase in oxidative damage in white adipose tissue that may affect tissue homeostasis. Oxidative stress drives activation of inflammatory kinases that can perturb insulin signaling leading to glucose intolerance and diabetes.

SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors.

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors.

ABRA: improved coding indel detection via assembly-based realignment.

MOTIVATION: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. RESULTS: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. AVAILABILITY AND IMPLEMENTATION: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra.

BlackOPs: increasing confidence in variant detection through mappability filtering.

Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin ('mismapping') and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, for a given sample, are expected to be almost completely false positives. We show that these blacklist positions are specific to the alignment algorithm and read length used, and BlackOPs allows users to generate a blacklist specific to their experimental setup. We queried the dbSNP and COSMIC variant databases and found numerous variants indistinguishable from mapping errors. We demonstrate how filtering against blacklist positions reduces the number of potential false variants using an RNA-seq glioblastoma cell line data set. In summary, accounting for mapping-caused variants tuned to experimental setups reduces false positives and, therefore, improves genome characterization by high-throughput sequencing.

Identification of germline population variants misclassified as cancer-associated somatic variants.

Introduction: Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned. Methods: To systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases' Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer. Results: We found 192 of 208 genes in COSMIC's cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants. Conclusion: The direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry.

Genome-Wide Analysis of Exertional Rhabdomyolysis in Sickle Cell Trait Positive African Americans.

Sickle cell trait (SCT), although generally a benign carrier state of hemoglobin S (HbAS), is a risk factor for exertional rhabdomyolysis (ERM), a rare but potentially fatal consequence of highly intense physical exercise, particularly among active-duty military personnel and high-performance athletes. The association between SCT and ERM is poorly understood. The objective of this study was to elucidate the genetic basis of ERM in an SCT-positive African American cohort. SCT-positive African Americans with a personal history of ERM (cases, n = 30) and without history of ERM (controls, n = 53) were enrolled in this study. Whole-genome sequencing was performed on DNA samples isolated from peripheral white blood cells. Participants' demographic, behavioral, and medical history information was obtained. An additional 131 controls were extracted from SCT-positive subjects of African descent from the 1000 Genomes Project. SCT carriers with ERM were characterized by myotoxicity features, significant muscle involvement dominated by muscle weakness, and severe pain and substantial increase in serum creatine kinase, with a mean value of 50,480 U/L. A distinctive feature of the SCT individuals with ERM was exertional collapse, which was reported in 53.3% of the cases in the study cohort. An important factor for the development of ERM was the duration and frequency of strenuous physical activity in the cases compared to the controls. Whole-genome sequencing identified 79,696 protein-coding variants. Genome-wide association analysis revealed that the p.C477R, rs115958260 variant in the SLC44A3 gene was significantly associated with ERM event in SCT-positive African Americans. The study results suggest that a combination of vigorous exercise and a genetic predisposing factor is involved in ERM.

Uncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers.

BACKGROUND: Suicide is a societal and public health concern of global scale. Identifying genetic risk factors for suicide attempt can characterize underlying biology and enable early interventions to prevent deaths. Recent studies have described common genetic variants for suicide-related behaviors. Here, we advance this search for genetic risk by analyzing the association between suicide attempt and uncommon variation exome-wide in a large, ancestrally diverse sample. METHODS: We sequenced whole genomes of 13,584 soldiers from the Army STARRS (Army Study to Assess Risk and Resilience in Servicemembers), including 979 individuals with a history of suicide attempt. Uncommon, nonsilent protein-coding variants were analyzed exome-wide for association with suicide attempt using gene-collapsed and single-variant analyses. RESULTS: We identified 19 genes with variants enriched in individuals with history of suicide attempt, either through gene-collapsed or single-variant analysis (Bonferroni padjusted < .05). These genes were CIB2, MLF1, HERC1, YWHAE, RCN2, VWA5B1, ATAD3A, NACA, EP400, ZNF585A, LYST, RC3H2, PSD3, STARD9, SGMS1, ACTR6, RGS7BP, DIRAS2, and KRTAP10-1. Most genes had variants across multiple genomic ancestry groups. Seventeen of these genes were expressed in healthy brain tissue, with 9 genes expressed at the highest levels in the brain versus other tissues. Brains from individuals deceased from suicide aberrantly expressed RGS7BP (padjusted = .035) in addition to nominally significant genes including YWHAE and ACTR6, all of which have reported associations with other mental disorders. CONCLUSIONS: These results advance the molecular characterization of suicide attempt behavior and support the utility of whole-genome sequencing for complementing the findings of genome-wide association studies in suicide research.