The Lymphoma Epidemiology of Outcomes cohort study: Design, baseline characteristics, and early outcomes.

To address the current and long-term unmet health needs of the growing population of non-Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18-99). Participants came from 49 US states and included 538 Black/African-Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population-based SEER data (2015-2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population-based SEER rates for indolent B-cell (follicular and marginal zone) and T-cell lymphomas, but were 10%-15% higher than SEER rates for aggressive B-cell subtypes (diffuse large B-cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Genes associated with bowel metastases in ovarian cancer.

OBJECTIVE: This study is designed to identify genes and pathways that could promote metastasis to the bowel in high-grade serous ovarian cancer (OC) and evaluate their associations with clinical outcomes. METHODS: We performed RNA sequencing of OC primary tumors (PTs) and their corresponding bowel metastases (n = 21 discovery set; n = 18 replication set). Differentially expressed genes (DEGs) were those expressed at least 2-fold higher in bowel metastases (BMets) than PTs in at least 30% of patients (P < .05) with no increased expression in paired benign bowel tissue and were validated with quantitative reverse transcription PCR. Using an independent OC cohort (n = 333), associations between DEGs in PTs and surgical and clinical outcomes were performed. Immunohistochemistry and mouse xenograft studies were performed to confirm the role of LRRC15 in promoting metastasis. RESULTS: Among 27 DEGs in the discovery set, 21 were confirmed in the replication set: SFRP2, Col11A1, LRRC15, ADAM12, ADAMTS12, MFAP5, LUM, PLPP4, FAP, POSTN, GRP, MMP11, MMP13, C1QTNF3, EPYC, DIO2, KCNA1, NETO1, NTM, MYH13, and PVALB. Higher expression of more than half of the genes in the PT was associated with an increased requirement for bowel resection at primary surgery and an inability to achieve complete cytoreduction. Increased expression of LRRC15 in BMets was confirmed by immunohistochemistry and knockdown of LRRC15 significantly inhibited tumor progression in mice. CONCLUSIONS: We identified 21 genes that are overexpressed in bowel metastases among patients with OC. Our findings will help select potential molecular targets for the prevention and treatment of malignant bowel obstruction in OC.

Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level allele-specific expression.

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.

Germline genetic variation in JAK2 as a prognostic marker in castration-resistant prostate cancer.

OBJECTIVES: To evaluate the prognostic significance of germline variation in candidate genes in patients with castration-resistant prostate cancer (CRPC). METHODS: Germline DNA was extracted from peripheral blood mononuclear cells of patients with CRPC enrolled in a clinically annotated registry. Fourteen candidate genes implicated in either initiation or progression of prostate cancer were tagged using single nucleotide polymorphisms (SNPs) from HapMap with a minor allele frequency of >5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP-level results the per allele hazard ratios (HRs) and 95% confidence intervals (CIs) under the additive allele model were estimated using Cox regression, adjusted for age at CRPC and Gleason score (GS). RESULTS: A total of 240 patients with CRPC were genotyped (14 genes; 84 SNPs). The median (range) age of the cohort was 69 (43-93) years. The GS distribution was 55% with GS ≥8, 32% with GS = 7 and 13% with GS <7 or unknown. The median (interquartile range) time from castration resistance to death for the cohort was 2.67 (1.6-4.07) years (144 deaths). At the gene level, a single gene, JAK2 was associated with OS (P < 0.01), and 11 of 18 JAK2 SNPs were individually associated with OS after adjustment for age and GS. A multivariate model consisting of age, GS, rs2149556 (HR 0.67; 95% CI 0.38-1.18) and rs4372063 (HR 2.17; 95% CI 1.25-3.76) was constructed to predict survival in patients with CRPC (concordance of 0.69, P < 3.2 × 10-9 ). CONCLUSIONS: Germline variation in the JAK2 gene was associated with survival in patients with CRPC and warrants further validation as a potential prognostic biomarker.

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21.

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e(-8)) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e(-11)). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer predisposition locus.

Mutational landscape of candidate genes in familial prostate cancer.

BACKGROUND: Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. METHODS: Here, we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). RESULTS: Overall, 4,856 candidate gene SNVs were identified, including 1,052 missense and 10 nonsense variants. Twenty missense variants were shared by all three family members in each family in which they were observed. Additionally, 15 missense variants were shared by two of three family members and predicted to be deleterious by five different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and one nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. CONCLUSIONS: Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility.

Farnesyltransferase inhibitor tipifarnib inhibits Rheb prenylation and stabilizes Bax in acute myelogenous leukemia cells.

Although farnesyltransferase inhibitors have shown promising activity in relapsed lymphoma and sporadic activity in acute myelogenous leukemia, their mechanism of cytotoxicity is incompletely understood, making development of predictive biomarkers difficult. In the present study, we examined the action of tipifarnib in human acute myelogenous leukemia cell lines and clinical samples. In contrast to the Ras/MEK/ERK pathway-mediated Bim upregulation that is responsible for tipifarnib-induced killing of malignant lymphoid cells, inhibition of Rheb-induced mTOR signaling followed by dose-dependent upregulation of Bax and Puma occurred in acute myelogenous leukemia cell lines undergoing tipifarnib-induced apoptosis. Similar Bax and Puma upregulation occurred in serial bone marrow samples harvested from a subset of acute myelogenous leukemia patients during tipifarnib treatment. Expression of FTI-resistant Rheb M184L, like knockdown of Bax or Puma, diminished tipifarnib-induced killing. Further analysis demonstrated that increased Bax and Puma levels reflect protein stabilization rather than increased gene expression. In U937 cells selected for tipifarnib resistance, neither inhibition of signaling downstream of Rheb nor Bax and Puma stabilization occurred. Collectively, these results not only identify a pathway downstream from Rheb that contributes to tipifarnib cytotoxicity in human acute myelogenous leukemia cells, but also demonstrate that FTI-induced killing of lymphoid versus myeloid cells reflects distinct biochemical mechanisms downstream of different farnesylated substrates. (ClinicalTrials.gov identifier NCT00602771).

Evaluating Lab-Based Eligibility Criteria by Race/Ethnicity in Clinical Trials of Diffuse Large B-Cell Lymphoma.

Underrepresentation of racial and ethnic subgroups in cancer clinical trials remains a persistent challenge. Restrictive clinical trial eligibility criteria have been shown to exacerbate this problem. We previously identified that up to 24% of patients treated with standard immunochemotherapy (IC) would have been excluded from recent first-line trials in diffuse large B-cell lymphoma (DLBCL) based on 5 lab-based criteria. These ineligible patients had worse clinical outcomes and increased deaths related to lymphoma progression suggesting the potential exclusion of patients who could have benefited most from the novel therapies being evaluated. Utilizing data from the prospectively enrolled Lymphoma Epidemiology Outcomes (LEO) Cohort study, with demographics broadly similar to the U.S. patients diagnosed with lymphoma, we evaluated the impact of laboratory eligibility criteria from recent first-line DLBCL trials across various racial and ethnic backgrounds. There were significant differences in the baseline lab values by race/ethnicity with Black/African American (AA) patients having the lowest mean hemoglobin and highest creatinine clearance. Based on recent clinical trial eligibility criteria, AA and Hispanic patients had higher rates of lab-based ineligibility compared to Non-Hispanic Whites. The largest gap in the clinical outcomes between eligible (ref) and non-eligible patients was noted within AA patients with an overall survival hazard ratio based on POLARIX clinical trial criteria of 4.09, 95% CI: 1.83-9.14. A thoughtful approach to the utility of each criterion and cut offs for eligibility needs to be evaluated in the context of its differential impact across various racial/ethnic groups.

Family-based association analysis of 42 hereditary prostate cancer families identifies the Apolipoprotein L3 region on chromosome 22q12 as a risk locus.

Multiple genome-wide scans for hereditary prostate cancer (HPC) have identified susceptibility loci on nearly every chromosome. However, few results have been replicated with statistical significance. One exception is chromosome 22q, for which five independent linkage studies yielded strong evidence for a susceptibility locus in HPC families. Previously, we refined this region to a 2.53 Mb interval, using recombination mapping in 42 linked pedigrees. We now refine this locus to a 15 kb interval, spanning Apolipoprotein L3 (APOL3), using family-based association analyses of 150 total prostate cancer (PC) cases from two independent family collections with 506 unrelated population controls. Analysis of the two independent sets of PC cases highlighted single nucleotide polymorphisms (SNPs) within the APOL3 locus showing the strongest associations with HPC risk, with the most robust results observed when all 150 cases were combined. Analysis of 15 tagSNPs across the 5' end of the locus identified six SNPs with P-values < or =2 × 10(-4). The two independent sets of HPC cases highlight the same 15 kb interval at the 5' end of the APOL3 gene and provide strong evidence that SNPs within this 15 kb interval, or in strong linkage disequilibrium with it, contribute to HPC risk. Further analyses of this locus in an independent population-based, case-control study revealed an association between an SNP within the APOL3 locus and PC risk, which was not confirmed in the Cancer Genetic Markers of Susceptibility data set. This study further characterizes the 22q locus in HPC risk and suggests that the role of this region in sporadic PC warrants additional studies.

Estimation of genotype relative risks from pedigree data by retrospective likelihoods.

Pedigrees collected for linkage studies are a valuable resource that could be used to estimate genetic relative risks (RRs) for genetic variants recently discovered in case-control genome wide association studies. To estimate RRs from highly ascertained pedigrees, a pedigree "retrospective likelihood" can be used, which adjusts for ascertainment by conditioning on the phenotypes of pedigree members. We explore a variety of approaches to compute the retrospective likelihood, and illustrate a Newton-Raphson method that is computationally efficient particularly for single nucleotide polymorphisms (SNPs) modeled as log-additive effect of alleles on the RR. We also illustrate, by simulations, that a naïve "composite likelihood" method that can lead to biased RR estimates, mainly by not conditioning on the ascertainment process-or as we propose-the disease status of all pedigree members. Applications of the retrospective likelihood to pedigrees collected for a prostate cancer linkage study and recently reported risk-SNPs illustrate the utility of our methods, with results showing that the RRs estimated from the highly ascertained pedigrees are consistent with odds ratios estimated in case-control studies. We also evaluate the potential impact of residual correlations of disease risk among family members due to shared unmeasured risk factors (genetic or environmental) by allowing for a random baseline risk parameter. When modeling only the affected family members in our data, there was little evidence for heterogeneity in baseline risks across families.

Two-stage Study of Familial Prostate Cancer by Whole-exome Sequencing and Custom Capture Identifies 10 Novel Genes Associated with the Risk of Prostate Cancer.

BACKGROUND: Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. OBJECTIVE: To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. DESIGN, SETTING, AND PARTICIPANTS: A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. RESULTS AND LIMITATIONS: Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. CONCLUSIONS: Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. PATIENT SUMMARY: Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.

Human colon cancer profiles show differential microRNA expression depending on mismatch repair status and are characteristic of undifferentiated proliferative states.

BACKGROUND: Colon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression. METHODS: To identify miRNAs that are differentially expressed in tumors and tumor subtypes, we carried out highly sensitive expression profiling of 735 miRNAs on samples obtained from a statistically powerful set of tumors (n = 80) and normal colon tissue (n = 28) and validated a subset of this data by qRT-PCR. RESULTS: Tumor specimens showed highly significant and large fold change differential expression of the levels of 39 miRNAs including miR-135b, miR-96, miR-182, miR-183, miR-1, and miR-133a, relative to normal colon tissue. Significant differences were also seen in 6 miRNAs including miR-31 and miR-592, in the direct comparison of tumors that were deficient or proficient for mismatch repair. Examination of the genomic regions containing differentially expressed miRNAs revealed that they were also differentially methylated in colon cancer at a far greater rate than would be expected by chance. A network of interactions between these miRNAs and genes associated with colon cancer provided evidence for the role of these miRNAs as oncogenes by attenuation of tumor suppressor genes. CONCLUSION: Colon tumors show differential expression of miRNAs depending on mismatch repair status. miRNA expression in colon tumors has an epigenetic component and altered expression that may reflect a reversion to regulatory programs characteristic of undifferentiated proliferative developmental states.

Serum Proteomics on the Basis of Discovery of Predictive Biomarkers of Response to Androgen Deprivation Therapy in Advanced Prostate Cancer.

BACKGROUND: We investigated the serum proteome of hormone-sensitive prostate cancer patients to determine candidate biomarkers associated with androgen deprivation therapy (ADT) efficacy. PATIENTS AND METHODS: Serum proteomes generated using isobaric mass tags for relative and absolute quantitation were analyzed using reverse-phase liquid chromatography coupled to tandem mass spectrometry. The advanced hormone-sensitive prostate cancer cohorts studied were: (1) untreated "paired" pre-ADT and 4-month post-ADT hormone-sensitive patients (n = 15); (2) "early ADT failure" patients (n = 10) in whom ADT treatment failed within a short period of time; and (3) "late ADT failure" patients (n = 10) in whom ADT treatment failed after a prolonged response time. Differential abundance was assessed, and ingenuity pathway analysis (IPA) was used to identify interaction networks in selected candidates from these comparisons. RESULTS: Between "post-ADT" and combined "early" and "late" ADT failure groups 149 differentially detected candidates were observed, and between "early" and "late" ADT failure groups 98 candidates were observed; 47 candidates were common in both comparisons. IPA network enrichment analysis of the 47 candidates identified 3 interaction networks (P < .01) including 17-ß-estradiol, nuclear factor kappa-light-chain enhancer of activated B cells complex, and P38 mitogen-activated protein kinases as pathways with potential markers of response to ADT. CONCLUSION: A global proteomic analysis identified pathways with markers of ADT response, which will need validation in independent data sets.

An expanded variant list and assembly annotation identifies multiple novel coding and noncoding genes for prostate cancer risk using a normal prostate tissue eQTL data set.

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci.

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Targeted sequencing of 36 known or putative colorectal cancer susceptibility genes.

BACKGROUND: Mutations in several genes predispose to colorectal cancer. Genetic testing for hereditary colorectal cancer syndromes was previously limited to single gene tests; thus, only a very limited number of genes were tested, and rarely those infrequently mutated in colorectal cancer. Next-generation sequencing technologies have made it possible to sequencing panels of genes known and suspected to influence colorectal cancer susceptibility. METHODS: Targeted sequencing of 36 known or putative CRC susceptibility genes was conducted for 1231 CRC cases from five subsets: (1) Familial Colorectal Cancer Type X (n = 153); (2) CRC unselected by tumor immunohistochemical or microsatellite stability testing (n = 548); (3) young onset (age <50 years) (n = 333); (4) proficient mismatch repair (MMR) in cases diagnosed at ≥50 years (n = 68); and (5) deficient MMR CRCs with no germline mutations in MLH1, MSH2, MSH6, or PMS2 (n = 129). Ninety-three unaffected controls were also sequenced. RESULTS: Overall, 29 nonsense, 43 frame-shift, 13 splice site, six initiator codon variants, one stop codon, 12 exonic deletions, 658 missense, and 17 indels were identified. Missense variants were reviewed by genetic counselors to determine pathogenicity; 13 were pathogenic, 61 were not pathogenic, and 584 were variants of uncertain significance. Overall, we identified 92 cases with pathogenic mutations in APC,MLH1,MSH2,MSH6, or multiple pathogenic MUTYH mutations (7.5%). Four cases with intact MMR protein expression by immunohistochemistry carried pathogenic MMR mutations. CONCLUSIONS: Results across case subsets may help prioritize genes for inclusion in clinical gene panel tests and underscore the issue of variants of uncertain significance both in well-characterized genes and those for which limited experience has accumulated.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes.

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Loss of HSulf-1 promotes altered lipid metabolism in ovarian cancer.

BACKGROUND: Loss of the endosulfatase HSulf-1 is common in ovarian cancer, upregulates heparin binding growth factor signaling and potentiates tumorigenesis and angiogenesis. However, metabolic differences between isogenic cells with and without HSulf-1 have not been characterized upon HSulf-1 suppression in vitro. Since growth factor signaling is closely tied to metabolic alterations, we determined the extent to which HSulf-1 loss affects cancer cell metabolism. RESULTS: Ingenuity pathway analysis of gene expression in HSulf-1 shRNA-silenced cells (Sh1 and Sh2 cells) compared to non-targeted control shRNA cells (NTC cells) and subsequent Kyoto Encyclopedia of Genes and Genomics (KEGG) database analysis showed altered metabolic pathways with changes in the lipid metabolism as one of the major pathways altered inSh1 and 2 cells. Untargeted global metabolomic profiling in these isogenic cell lines identified approximately 338 metabolites using GC/MS and LC/MS/MS platforms. Knockdown of HSulf-1 in OV202 cells induced significant changes in 156 metabolites associated with several metabolic pathways including amino acid, lipids, and nucleotides. Loss of HSulf-1 promoted overall fatty acid synthesis leading to enhance the metabolite levels of long chain, branched, and essential fatty acids along with sphingolipids. Furthermore, HSulf-1 loss induced the expression of lipogenic genes including FASN, SREBF1, PPARγ, and PLA2G3 stimulated lipid droplet accumulation. Conversely, re-expression of HSulf-1 in Sh1 cells reduced the lipid droplet formation. Additionally, HSulf-1 also enhanced CPT1A and fatty acid oxidation and augmented the protein expression of key lipolytic enzymes such as MAGL, DAGLA, HSL, and ASCL1. Overall, these findings suggest that loss of HSulf-1 by concomitantly enhancing fatty acid synthesis and oxidation confers a lipogenic phenotype leading to the metabolic alterations associated with the progression of ovarian cancer. CONCLUSIONS: Taken together, these findings demonstrate that loss of HSulf-1 potentially contributes to the metabolic alterations associated with the progression of ovarian pathogenesis, specifically impacting the lipogenic phenotype of ovarian cancer cells that can be therapeutically targeted.

Erratum to: Loss of HSulf-1 promotes altered lipid metabolism in ovarian cancer.

[This corrects the article DOI: 10.1186/2049-3002-2-13.].

Identification of novel variants in colorectal cancer families by high-throughput exome sequencing.

BACKGROUND: Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants. METHODS: We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign. RESULTS: We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively. CONCLUSIONS: Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility. IMPACT: Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk.