Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

Background

Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS).

Methods

We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan.

Results

Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62).

Conclusions

This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

Cell State of Origin Impacts Development of Distinct Endometriosis-Related Ovarian Carcinoma Histotypes

Clear cell ovarian carcinoma (CCOC) and endometrioid ovarian carcinoma (ENOC) are ovarian carcinoma histotypes, which are both thought to arise from ectopic endometrial (or endometrial-like) cells through an endometriosis intermediate. How the same cell type of origin gives rise to two morphologically and biologically different histotypes has been perplexing, particularly given that recurrent genetic mutations are common to both and present in nonmalignant precursors. We used RNA transcription analysis to show that the expression profiles of CCOC and ENOC resemble those of normal endometrium at secretory and proliferative phases of the menstrual cycle, respectively. DNA methylation at the promoter of the estrogen receptor (ER) gene (ESR1) was enriched in CCOC, which could potentially lock the cells in the secretory state. Compared with normal secretory-type endometrium, CCOC was further defined by increased expression of cysteine and glutathione synthesis pathway genes and downregulation of the iron antiporter, suggesting iron addiction and highlighting ferroptosis as a potential therapeutic target. Overall, these findings suggest that while CCOC and ENOC arise from the same cell type, these histotypes likely originate from different cell states. This "cell state of origin" model may help to explain the presence of histologic and molecular cancer subtypes arising in other organs.

SIGNIFICANCE

Two cancer histotypes diverge from a common cell of origin epigenetically locked in different cell states, highlighting the importance of considering cell state to better understand the cell of origin of cancer.

Clinicopathological characteristics, molecular features and novel diagnostic strategies for the detection of malignant transformation of endometriosis (Review)

Endometriosis is a benign gynecological disease that affects women of reproductive age. Although malignant transformation of endometriosis is rare, physicians must be aware of this due to the high incidence of clear cell carcinoma of the ovary (CCC) in Japan. The most prevalent histological subtype of ovarian cancer is CCC (~70%) followed by endometrioid carcinoma (30%). The present review discusses the clinicopathological and molecular features of endometriosis-associated ovarian cancer (EAOC) as well as prospects for novel diagnostic strategies. Papers published between 2000 and 2022 in the PubMed and Google Scholar databases were included. Contents of the endometriotic cyst fluid may be involved in carcinogenesis, although the underlying mechanisms are largely unknown. Some studies have proposed a possible mechanism wherein excessive hemoglobin, heme and iron could cause an imbalance in intracellular redox homeostasis in endometriotic cells. Combined with DNA damage and mutations, the imbalances may induce the development of EAOC. Endometriotic cells evolve to adapt to the prolonged unfavorable oxidative microenvironmental stress. On the other hand, macrophages enhance the antioxidative defense mechanism and protect endometriotic cells against oxidative damage through intercellular crosstalk and signaling pathways. Therefore, changes in redox signaling, energy metabolism and the tumor immune microenvironment could be the key elements in the malignant transformation of certain endometriotic cell clones. Additionally, non-invasive bioimaging (i.e., magnetic resonance relaxometry) and biomarkers (i.e., tissue factor pathway inhibitor 2) may be promising tools for early-stage detection of the disease. In conclusion, the present review summarizes the latest advancements in research on the biological characteristics and early diagnosis of malignant transformation of endometriosis.

Extensive germline-somatic interplay contributes to prostate cancer progression through HNF1B co-option of TMPRSS2-ERG

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

BACKGROUND

Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.

METHODS

Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.

RESULTS

We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.

CONCLUSIONS

CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

A novel subtype to predict prognosis and treatment response with DNA driver methylation-transcription in ovarian cancer

Aims: To identify a novel subtype with DNA driver methylation-transcriptomic multiomics and predict prognosis and therapy response in serous ovarian cancer (SOC). Methods: SOC cohorts with both mRNA and methylation were collected, and DNA driver methylation (DNAme) was identified with the MithSig method. A novel prognostic subtype was developed by integrating the information on DNAme and prognosis-regulated DNAme-associated mRNA by similarity network fusion. Results: 43 overlapped DNAme were identified in three independent cohorts. SOC patients were categorized into three distinct subtypes by integrated multiomics. There were differences in prognosis, tumor microenvironment and response to therapy among the subtypes. Conclusion: This study identified 43 DNAmes and proposes a novel subtype toward personalized chemotherapy and immunotherapy for SOC patients based on multiomics.

Renal oncometabolite L-2-hydroxyglutarate imposes a block in kidney tubulogenesis: Evidence for an epigenetic basis for the L-2HG-induced impairment of differentiation

2-Hydroxyglutarate (2HG) overproducing tumors arise in a number of tissues, including the kidney. The tumorigenesis resulting from overproduced 2HG has been attributed to the ability of 2HG alter gene expression by inhibiting α-ketoglutarate (αKG)-dependent dioxygenases, including Ten-eleven-Translocation (TET) enzymes. Genes that regulate cellular differentiation are reportedly repressed, blocking differentiation of mesenchymal cells into myocytes, and adipocytes. In this report, the expression of the enzyme responsible for L2HG degradation, L-2HG dehydrogenase (L2HGDH), is knocked down, using lentiviral shRNA, as well as siRNA, in primary cultures of normal Renal Proximal Tubule (RPT) cells. The knockdown (KD) results in increased L-2HG levels, decreased demethylation of 5mC in genomic DNA, and increased methylation of H3 Histones. Consequences include reduced tubulogenesis by RPT cells in matrigel, and reduced expression of molecular markers of differentiation, including membrane transporters as well as HNF1α and HNF1β, which regulate their transcription. These results are consistent with the hypothesis that oncometabolite 2HG blocks RPT differentiation by altering the methylation status of chromatin in a manner that impedes the transcriptional events required for normal differentiation. Presumably, similar alterations are responsible for promoting the expansion of renal cancer stem-cells, increasing their propensity for malignant transformation.

XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.

Functional analysis of the 1p34.3 risk locus implicates GNL2 in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of β-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.

A Review of High-Dimensional Mediation Analyses in DNA Methylation Studies

DNA methylation alterations have been widely studied as mediators of environmentally induced disease risks. With new advances in technique, epigenome-wide DNA methylation data (EWAS) have become the new standard for epigenetic studies in human populations. However, to date most epigenetic studies of mediation effects only involve selected (gene-specific) candidate methylation markers. There is an urgent need for appropriate analytical methods for EWAS mediation analysis. In this chapter, we provide an overview of recent advances on high-dimensional mediation analysis, with application to two DNA methylation data.

DNA Methylation Profiles of Ovarian Clear Cell Carcinoma

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC.

METHODS

We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways.

RESULTS

Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10-4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10-6).

CONCLUSIONS

DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways.

IMPACT

This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

DNA methylation-based profiling reveals distinct clusters with survival heterogeneity in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most common type of epigenetically heterogeneous ovarian cancer. Methylation typing has previously been used in many tumour types but not in HGSOC. Methylation typing in HGSOC may promote the development of personalized care. The present study used DNA methylation data from The Cancer Genome Atlas database and identified four unique methylation subtypes of HGSOC. With the poorest prognosis and high frequency of residual tumours, cluster 4 featured hypermethylation of a panel of genes, which indicates that demethylation agents may be tested in this group and that neoadjuvant chemotherapy may be used to reduce the possibility of residual lesions. Cluster 1 and cluster 2 were significantly associated with metastasis genes and metabolic disorders, respectively. Two feature CpG sites, cg24673765 and cg25574024, were obtained through Cox proportional hazards model analysis of the CpG sites. Based on the methylation level of the two CpG sites, the samples were classified into high- and low-risk groups to identify the prognostic information. Similar results were obtained in the validation set. Taken together, these results explain the epigenetic heterogeneity of HGSOC and provide guidance to clinicians for the prognosis of HGSOC based on DNA methylation sites.

An Ovarian Cancer Susceptible Gene Prediction Method Based on Deep Learning Methods

Ovarian cancer (OC) is one of the most fatal diseases among women all around the world. It is highly lethal because it is usually diagnosed at an advanced stage which may reduce the survival rate greatly. Even though most of the patients are treated timely and effectively, the survival rate is still low due to the high recurrence rate of OC. With a large number of genome-wide association analysis (GWAS)-discovered risk regions of OC, expression quantitative trait locus (eQTL) analyses can explore candidate susceptible genes based on these risk loci. However, a large number of OC-related genes remain unknown. In this study, we proposed a novel gene prediction method based on different omics data and deep learning methods to identify OC causal genes. We first employed graph attention network (GAT) to obtain a compact gene feature representation, then a deep neural network (DNN) is utilized to predict OC-related genes. As a result, our model achieved a high AUC of 0.761 and AUPR of 0.788, which proved the accuracy and effectiveness of our proposed method. At last, we conducted a gene-set enrichment analysis to further explore the mechanism of OC. Finally, we predicted 245 novel OC causal genes and 10 top related KEGG pathways.

Identification of a four-gene methylation biomarker panel in high-grade serous ovarian carcinoma

Background The lack of effective biomarkers for the screening and early detection of ovarian cancer (OC) is one of the most pressing problems in oncogynecology. Because epigenetic alterations occur early in the cancer development, they provide great potential to serve as such biomarkers. In our study, we investigated a potential of a four-gene methylation panel (including CDH13, HNF1B, PCDH17 and GATA4 genes) for the early detection of high-grade serous ovarian carcinoma (HGSOC). Methods For methylation detection we used methylation sensitive high-resolution melting analysis and real-time methylation specific analysis. We also investigated the relation between gene hypermethylation and gene relative expression using the 2-ΔΔCt method. Results The sensitivity of the examined panel reached 88.5%. We were able to detect methylation in 85.7% (12/14) of early stage tumors and in 89.4% (42/47) of late stage tumors. The total efficiency of the panel was 94.4% and negative predictive value reached 90.0%. The specificity and positive predictive value achieved 100% rates. Our results showed lower gene expression in the tumor samples in comparison to control samples. The more pronounced downregulation was measured in the group of samples with detected methylation. Conclusions In our study we designed the four-gene panel for HGSOC detection in ovarian tissue with 100% specificity and sensitivity of 88.5%. The next challenge is translation of the findings to the less invasive source for biomarker examination, such as plasma. Our results indicate that combination of examined genes deserve consideration for further testing in clinical molecular diagnosis of HGSOC.

Reference Module-Based Analysis of Ovarian Cancer Transcriptome Identifies Important Modules and Potential Drugs

Ovarian cancer (OVC) is often diagnosed at the advanced stage resulting in a poor overall outcome for the patient. The disease mechanisms, prognosis, and treatment require imperative elucidation. A rank-based module-centric framework was proposed to analyze the key modules related to the development, prognosis, and treatment of OVC. The ovarian cancer cell line microarray dataset GSE43765 from the Gene Expression Omnibus database was used to construct the reference modules by weighted gene correlation network analysis. Twenty-three reference modules were tested for stability and functionally annotated. Furthermore, to demonstrate the utility of reference modules, two more OVC datasets were collected, and their gene expression profiles were projected to the reference modules to generate a module-level expression. An epithelial-mesenchymal transition module was activated in OVC compared to the normal epithelium, and a pluripotency module was activated in ovarian cancer stroma compared to ovarian cancer epithelium. Seven differentially expressed modules were identified in OVC compared to the normal ovarian epithelium, with five up-regulated, and two down-regulated. One module was identified to be predictive of patient overall survival. Four modules were enriched with SNP signals. Based on differentially expressed modules and hub genes, five candidate drugs were screened. The hub genes of those modules merit further investigation. We firstly propose the reference module-based analysis of OVC. The utility of the analysis framework can be extended to transcriptome data of other kinds of diseases.

Acquired Evolution of Mitochondrial Metabolism Regulated by HNF1B in Ovarian Clear Cell Carcinoma

Clear cell carcinoma (CCC) of the ovary exhibits a unique morphology and clinically malignant behavior. The eosinophilic cytoplasm includes abundant glycogen. Although the growth is slow, the prognosis is poor owing to resistance to conventional chemotherapies. CCC often arises in endometriotic cysts and is accompanied by endometriosis. Based on these characteristics, three clinical questions are considered: why does ovarian cancer, especially CCC and endometrioid carcinoma, frequently occur in endometriotic cysts, why do distinct histological subtypes (CCC and endometrioid carcinoma) arise in the endometriotic cyst, and why does ovarian CCC possess unique characteristics? Mutations in AT-rich interacting domain-containing protein 1A and phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit alpha genes may contribute to the carcinogenesis of ovarian CCC, whereas hepatocyte nuclear factor-1-beta (HNF1B) plays crucial roles in sculpting the unique characteristics of ovarian CCC through metabolic alterations. HNF1B increases glutathione synthesis, activates anaerobic glycolysis called the Warburg effect, and suppresses mitochondria. These metabolic changes may be induced in stressful environments. Life has evolved to utilize and control energy; eukaryotes require mitochondria to transform oxygen reduction into useful energy. Because mitochondrial function is suppressed in ovarian CCC, these cancer cells probably acquired further metabolic evolution during the carcinogenic process in order to survive stressful environments.

Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer

PURPOSE

The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes.

METHODS

We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics.

RESULTS

The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive.

CONCLUSIONS

We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling.

Genome-Wide Epigenetic Landscape of Lung Adenocarcinoma Links HOXB9 DNA Methylation to Intrinsic EGFR-TKI Resistance and Heterogeneous Responses

PURPOSE

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs.

PATIENTS AND METHODS

We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations.

RESULTS

A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox (HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019).

CONCLUSION

Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

Hepatocyte nuclear factor 1 beta: A perspective in cancer

Hepatocyte nuclear factor 1 beta (HNF1 β/B) exists as a homeobox transcription factor having a vital role in the embryonic development of organs mainly liver, kidney and pancreas. Initially described as a gene causing maturity‐onset diabetes of the young (MODY), HNF1β expression deregulation and single nucleotide polymorphisms in HNF1β have now been associated with several tumours including endometrial, prostate, ovarian, hepatocellular, renal and colorectal cancers. Its function has been studied either as homodimer or heterodimer with HNF1α. In this review, the role of HNF1B in different cancers will be discussed along with the role of its splice variants, and its emerging role as a potential biomarker in cancer.

A comprehensive analysis of the expression, epigenetic and genetic changes of HNF1B and ECI2 in 122 cases of high-grade serous ovarian carcinoma

High-grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer, with a poor prognosis; however, most studies concerning ovarian carcinoma have focused mainly on clear cell carcinoma. The involvement of hepatocyte nuclear factor 1β (HNF1B) in the carcinogenesis of HGSC has not yet been fully elucidated. To the best of our knowledge, the present study is the first to analyse the expression of the possible downstream target of HNF1B, enoyl-CoA (Δ) isomerase 2 (ECI2), in HGSC. The present study performed a comprehensive analysis of HNF1B mRNA and protein expression, and epigenetic and genetic changes, as well as an analysis of ECI2 mRNA and protein expression in 122 cases of HGSC. HNF1B protein expression was detected in 28/122 cases, and was positively associated with lymphovascular invasion (P=0.025). Protein expression of ECI2 was detected in 115/122 cases, but no associations with clinicopathological variables were revealed. Therefore, ECI2 does not seem to function as a suitable prognostic marker for HGSC. In the sample set, a positive correlation between HNF1B and ECI2 protein expression was detected (P=0.005). HNF1B mRNA was also positively correlated with HNF1B protein expression (P=0.001). HNF1B promoter methylation was detected in 26/67 (38.8%) of cases. A novel pathogenic somatic HNF1B mutation was detected in 1/61 (1.6%) of the analysed HGSC cases. No other correlations between the examined SNPs (rs4430796, rs757210 and rs7405776), HNF1B promoter methylation, HNF1B/ECI2 expression or clinicopathological characteristics were found.

Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers

BACKGROUND

Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.

METHODS

Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.

RESULTS

Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.

CONCLUSIONS

Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.

IMPACT

Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

DNA Methylation in Ovarian Cancer Susceptibility

Simple Summary

It is well established that ovarian cancer “runs in families”, where ovarian and other cancers (commonly breast cancer) occur at early ages at onset and in multiple generations. After decades of genetic studies, rare high-risk genetic mutations in cancer susceptibility genes and over 40 common genetic variants with much smaller risks have been identified. However, based on familial studies, we know that additional heritable genetic risk factors exist. It is possible that epigenetic variation—differences in how DNA is read, and which genes are actively expressed (or not) —also contributes to ovarian cancer susceptibility. This review summarizes the current collection of epidemiological studies that have investigated the role of DNA methylation—one type of epigenetic mechanism—in the risk of ovarian cancer.

Abstract

Epigenetic alterations are somatically acquired over the lifetime and during neoplastic transformation but may also be inherited as widespread ‘constitutional’ alterations in normal tissues that can cause cancer predisposition. Epithelial ovarian cancer (EOC) has an established genetic susceptibility and mounting epidemiological evidence demonstrates that DNA methylation (DNAm) intermediates as well as independently contributes to risk. Targeted studies of known EOC susceptibility genes (CSGs) indicate rare, constitutional BRCA1 promoter methylation increases familial and sporadic EOC risk. Blood-based epigenome-wide association studies (EWAS) for EOC have detected a total of 2846 differentially methylated probes (DMPs) with 71 genes replicated across studies despite significant heterogeneity. While EWAS detect both symptomatic and etiologic DMPs, adjustments and analytic techniques may enrich risk associations, as evidenced by the detection of dysregulated methylation of BNC2—a known CSG identified by genome-wide associations studies (GWAS). Integrative genetic–epigenetic approaches have mapped methylation quantitative trait loci (meQTL) to EOC risk, revealing DNAm variations that are associated with nine GWAS loci and, further, one novel risk locus. Increasing efforts to mapping epigenome variation across populations and cell types will be key to decoding both the genomic and epigenomic causal pathways to EOC.

Translational Theragnosis of Ovarian Cancer: where do we stand?

BACKGROUND

Ovarian cancer is the second most common gynecologic malignancy, accounting for approximately 220,000 deaths annually worldwide. Despite radical surgery and initial high response rates to platinum- and taxane-based chemotherapy, most patients experience a relapse, with a median progression-free survival of only 18 months. Overall survival is approximately 30% at 5 years from the diagnosis. In comparison, patients out from breast cancer are more than 80 % after ten years from the disease discovery. In spite of a large number of published fundamental and applied research, and clinical trials, novel therapies are urgently needed to improve outcomes of the ovarian cancer. The success of new drugs development in ovarian cancer will strongly depend on both fully genomic disease characterization and, then, availability of biomarkers able to identify women likely to benefit from a given new therapy.

METHODS

In this review, the focus is given to describe how complex is the diseases under the simple name of ovarian cancer, in terms of cell tumor types, histotypes, subtypes, and specific gene mutation or differently expressed in the tumor with respect the healthy ovary. The first- and second-line pharmacological treatment clinically used over the last fifty years are also described. Noteworthy achievements in vitro and in vivo tested new drugs are also summarized. Recent literature related to up to date ovarian cancer knowledge, its detection by biomarkers and chemotherapy was searched from several articles on Pubmed, Google Scholar, MEDLINE and various Governmental Agencies till April 2019.

RESULTS

The papers referenced by this review allow a deep analysis of status of the art in the classification of the several types of ovarian cancer, the present knowledge of diagnosis based on biomarkers and imaging techniques, and the therapies developed over the past five decades.

CONCLUSION

This review aims at stimulating more multi-disciplinary efforts to identify a panel of novel and more specific biomarkers to be used to screen patients for a very early diagnosis, to have prognosis and therapy efficacy indications. The desired final goal would be to have available tools allowing to reduce the recurrence rate, increase both the disease progression free interval and of course the overall survival at five years from the diagnosis that today is still very low.

Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

Transcription factors (TFs) are major contributors to cancer risk and somatic development. In preclinical and clinical studies, direct or indirect inhibition of TF-mediated oncogenic gene expression profiles have proven to be effective in many tumor types, highlighting this group of proteins as valuable therapeutic targets. In spite of this, our understanding of TFs in epithelial ovarian cancer (EOC) is relatively limited. EOC is a heterogeneous disease composed of five major histologic subtypes; high-grade serous, low-grade serous, endometrioid, clear cell and mucinous. Each histology is associated with unique clinical etiologies, sensitivity to therapies, and molecular signatures - including diverse transcriptional regulatory programs. While some TFs are shared across EOC subtypes, a set of TFs are expressed in a histotype-specific manner and likely explain part of the histologic diversity of EOC subtypes. Targeting TFs present with unique opportunities for development of novel precision medicine strategies for ovarian cancer. This article reviews the critical TFs in EOC subtypes and highlights the potential of exploiting TFs as biomarkers and therapeutic targets.

Analysis of expression, epigenetic, and genetic changes of HNF1B in 130 kidney tumours

Hepatocyte nuclear factor 1 beta (HNF1B) is a transcription factor which plays a crucial role in nephronogenesis, and its germline mutations have been associated with kidney developmental disorders. However, the effects of HNF1B somatic exonic mutations and its role in the pathogenesis of kidney tumours has not yet been elucidated. Depending on the type of the tumour HNF1B may act as a tumour suppressor or oncogene, although the exact mechanism by which HNF1B participates in the process of cancerogenesis is unknown. Using an immunohistochemical approach, and methylation and mutation analysis, we have investigated the expression, epigenetic, and genetic changes of HNF1B in 130 cases of renal tumours (121 renal cell carcinomas, 9 oncocytomas). In the subset of clear cell renal cell carcinoma (ccRCC), decreased HNF1B expression was associated with a higher tumour grade and higher T stage. The mutation analysis revealed no mutations in the analysed samples. Promoter methylation was detected in two ccRCCs and one oncocytoma. The results of our work on a limited sample set suggest that while in papillary renal cell carcinoma HNF1B functions as an oncogene, in ccRCC and chRCC it may act in a tumour suppressive fashion.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Using genetics to decipher the link between type 2 diabetes and cancer: shared aetiology or downstream consequence?

Recent developments in the field of genetics have accelerated our understanding of the aetiology of complex diseases. Type 2 diabetes mellitus and cancer are no exception, with large-scale genome-wide association studies (GWAS) facilitating exploration of the underlying pathology. Here, we discuss how genetics studies can be used to investigate the relationship between these complex diseases. Observational epidemiological studies consistently report that people with type 2 diabetes have a higher risk of several types of cancer. Indeed, type 2 diabetes and cancer share many common risk factors, such as obesity, ageing, poor diet and low levels of physical activity. However, questions remain regarding the biological mechanisms that link these two diseases. Large-scale GWAS of type 2 diabetes and cancer allow us to consider the evidence for shared genetic architecture. Several shared susceptibility genes have been identified, yet tissue specificity and direction of effect must be taken into account when considering common genetic aetiology. We also consider how GWAS, and associated techniques such as Mendelian randomisation, allow us to dissect the link between the two diseases and address questions such as 'Does type 2 diabetes cause cancer or is the increased risk observed driven by higher adiposity or another associated metabolic feature?' Graphical abstract.

Insights into the multifactorial causation of obesity by integrated genetic and epigenetic analysis

Obesity is a highly heritable multifactorial disease that places an enormous burden on human health. Its increasing prevalence and the concomitant-reduced life expectancy has intensified the search for new analytical methods that can reduce the knowledge gap between genetic susceptibility and functional consequences of the disease pathology. Although the influence of genetics and epigenetics has been studied independently in the past, there is increasing evidence that genetic variants interact with environmental factors through epigenetic regulation. This suggests that a combined analysis of genetic and epigenetic variation may be more effective in characterizing the obesity phenotype. To date, limited genome-wide integrative analyses have been performed. In this review, we provide an overview of the latest findings, advantages, and challenges and discuss future perspectives.

Lung cancer A549 cells suppressed with overexpressed HNF1B or PCDHA13 inhibited PI3K/AKT phosphorylation

BACKGROUND

Lung cancer is the most revenant and deadly tumors around the world. Here we aimed to explore the effects of hepatocyte nuclear factor 1B (HNF1B) and PCDHA13 overexpression on PI3K/AKT phosphorylation and malignant biological behavior in lung cancer A549 cells.

METHODS

HNF1B and PCDHA13 were amplified, and their overexpression plasmids were constructed for transfection. RT-PCR was used to detect the mRNA levels of HNF1B and PCDHA13. Cell proliferation and cell apoptosis were detected by clone formation experiments and flow cytometry, respectively, while cell invasion was studied by Transwell assay. The expression of survivin, PCNA, Caspase-3, Caspase-9, VEGF, and fibronectin was detected using immunoblotting, as was PI3K/AKT phosphorylation.

RESULTS

The level of HNF1B mRNA expression was significantly higher in the pcNDA-HNF1B group than in the control group (P<0.05), and the level of PCDHA13 mRNA expression in the pcNDA-PCDHA13 group was also significantly increased (P<0.05). The clone formation rate and cell invasion count in pcNDA-HNF1B or pcNDA-PCDHA13 transfected groups were significantly reduced in comparison with the control group, which were further validated with the protein expression levels of survivin, PCNA, VEGF, and fibronectin (P<0.05). However, the apoptosis rate, and the cleaved caspase3/caspase3 and cleaved caspase9/caspase9 protein expression ratios were all significantly increased (P<0.05). Cells transfected with pcNDA-HNF1B or pcNDA-PCDHA13 showed decreased levels of PI3K/AKT phosphorylation (P<0.05).

CONCLUSIONS

Overexpression of HNF1B and PCDHA13 inhibits the phosphorylation of PI3K/AKT and hinders the malignant biological behavior of lung cancer A549 cells.

Expression, Epigenetic, and Genetic Changes of HNF1B in Colorectal Lesions: an Analysis of 145 Cases

Hepatocyte nuclear factor 1 beta (HNF1B) is transcription factor which plays a crucial role in the regulation of the development of several organs, but also seems to be implicated in the development of certain tumours, especially the subset of clear cell carcinomas of the ovary and kidney. Depending on the type of the tumour, HNF1B may act as either a tumour suppressor or an oncogene, although the exact mechanism by which HNF1B participates in the process of cancerogenesis is unknown. Using immunohistochemical approach and methylation and mutation analysis, we have investigated the expression, epigenetic, and genetic changes of HNF1B on 40 cases of colorectal adenomas and 105 cases of colorectal carcinomas. The expression of HNF1B was correlated with the benign or malignant behaviour of the lesion, given that carcinomas showed significantly lower levels of expression compared to adenomas. In carcinomas, lower levels of HNF1B expression were associated with recurrence and shortened disease-free survival. The mutation analysis revealed three somatic mutations (two frameshift and one nonsense) in the carcinoma sample set. Promoter methylation was detected in three carcinomas. These results suggest that in colorectal cancer, HNF1B may play a part in the pathogenesis and act in a tumour suppressive fashion.

Precision medicine for ovarian clear cell carcinoma based on gene alterations

Ovarian clear cell carcinoma (OCCC) is a histological subtype of epithelial ovarian carcinoma prevalent in Asians. No clear therapeutic selection based on molecular profile has been implemented for this disease. Oncogenic PIK3CA mutation, which activates the PIK3CA/AKT/mTOR signaling pathway, is a promising druggable alteration in OCCC. Recent studies by our group and others have identified the ARID1A mutation as another alteration linked to therapeutic selection based on synthetic lethality: deleterious ARID1A mutations, resulting in ARID1A deficiency, make OCCC cells sensitive to drugs targeting poly (ADP-ribose) polymerase and EZH2, as well as to glutathione inhibitors. In addition, we recently obtained evidence that ARID1A-deficient OCCC could benefit from gemcitabine treatment. Precision medicine based on gene alteration profiling might improve the prognosis of OCCC patients.

The prospect of discovering new biomarkers for ovarian cancer based on current knowledge of susceptibility loci and genetic variation (Review)

Ovarian cancer is the most lethal gynaecological malignancy. The cancer initially presents with non‑specific symptoms; thus, it is typically not discovered until the patient has reached the late, considerably more lethal, stages of the disease. Research focus is currently on finding novel biomarkers, especially for early detection and stratification of the disease. One promising approach has been to focus on mutations or variations in the genetic code that are associated with the risk of developing ovarian cancer. A certain heritable component is already known regarding genes such as BRCA1/2, TP53, MSH6, BRIP1 and RAD51C, yet these are estimated to only account for ~3.1% of the total risk. Recent advances in sequencing technologies have enabled the investigation of hundreds of thousands of genetic variants in genome‑wide association studies in tens of thousands of patients, which has led to the discovery of 108 (39 loci with P<5.0x10‑8) novel susceptibility loci for ovarian cancer, presented in this review. Using the published variants in a patient cohort screening, together with variants identified in our ongoing whole exome sequencing project, future aims are to ascertain whether certain of the novel variants could be used as biomarkers for early diagnosis and/or treatment decisions.

Molecular Classification of Epithelial Ovarian Cancer Based on Methylation Profiling: Evidence for Survival Heterogeneity

PURPOSE

Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes.

EXPERIMENTAL DESIGN

A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC).

RESULTS

Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10^-7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007).

CONCLUSIONS

DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer.See related commentary by Ishak et al., p. 5729.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

OBJECTIVE

Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

METHODS

Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

RESULTS

At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).

CONCLUSION

While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Tumor-suppressive activity of Hnf1β in Wilms' tumor

Hepatocyte nuclear factor 1β (HNF1β) is a transcription factor belonging to the HNF-1 family and has been implicated in a number of cancers, but its role in Wilms' tumor (nephroblastoma) has not been addressed. Here, we compared its expression between Wilms' tumor patient kidney tissue and adjacent tissue based on the Oncomine database ( www.oncomine.com ). Cell proliferation, apoptosis, migration, and HNF1β expression level were analyzed in Wilms' tumor-derived G401 cells. Using a variety of mouse tissues (lung, heart, kidney, etc.), we found that HNF1β is the highest expression in the kidneys. Oncomine analysis further demonstrated that HNF1β has a lower expression in Wilms' tumor tissue than in paracancerous tissues. Overexpression of HNF1β decreased cell proliferation and migration, but promoted cell apoptosis. Knockdown of HNF1β produced the opposite results. These results indicated that HNF1β may play important roles in kidney development and function, and its activation may negatively regulate Wilms' tumor progression.

Survival Following Chemotherapy in Ovarian Clear Cell Carcinoma Is Not Associated with Pathological Misclassification of Tumor Histotype

PURPOSE

Although ovarian clear cell carcinomas (OCCC) are commonly resistant to platinum-based chemotherapy, good clinical outcomes are observed in a subset of patients. The explanation for this is unknown but may be due to misclassification of high-grade serous ovarian cancer (HGSOC) as OCCC or mixed histology.

EXPERIMENTAL DESIGN

To discover potential biomarkers of survival benefit following platinum-based chemotherapy, we ascertained a cohort of 68 Japanese and Australian patients in whom progression-free survival (PFS) and overall survival (OS) could be assessed. We performed IHC reclassification of tumors, and targeted sequencing and immunohistochemistry of known driver genes. Exome sequencing was performed in 10 patients who had either unusually long survival (N = 5) or had a very short time to progression (N = 5).

RESULTS

The majority of mixed OCCC (N = 6, 85.7%) and a small proportion of pure OCCC (N = 3, 4.9%) were reclassified as likely HGSOC. However, the PFS and OS of patients with misclassified samples were similar to that of patients with pathologically validated OCCC. Absent HNF1B expression was significantly correlated with longer PFS and OS (P = 0.0194 and 0.0395, respectively). Mutations in ARID1A, PIK3CA, PPP2R1A, and TP53 were frequent, but did not explain length of PFS and OS. An exploratory exome analysis of patients with favorable and unfavorable outcomes did not identify novel outcome-associated driver mutations.

CONCLUSIONS

Survival benefit following chemotherapy in OCCC was not associated with pathological misclassification of tumor histotype. HNF1B loss may help identify the subset of patients with OCCC with a more favorable outcome.

Cross-Cancer Pleiotropic Associations with Lung Cancer Risk in African Americans

BACKGROUND

Identifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans.

METHODS

We conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status.

RESULTS

We identified three novel genomic regions significantly associated (FDR-corrected P <0.10) with lung cancer risk (rs336958 on 5q14.3, rs7186207 on 16q22.2, and rs11658063 on 17q12). On chromosome16q22.2, rs7186207 was significantly associated with reduced risk [OR = 0.43; 95% confidence interval (CI), 0.73-0.89], and functional annotation using GTEx showed rs7186207 modifies DHODH gene expression. The minor allele at rs336958 on 5q14.3 was associated with increased lung cancer risk (OR = 1.47; 95% CI, 1.22-1.78), whereas the minor allele at rs11658063 on 17q12 was associated with reduced risk (OR = 0.80; 95% CI, 0.72-0.90).

CONCLUSIONS

We identified novel associations on chromosomes 5q14.3, 16q22.2, and 17q12, which contain HNF1B, DHODH, and HAPLN1 genes, respectively. SNPs within these regions have been previously associated with multiple cancers. This is the first study to examine cross-cancer pleiotropic associations for lung cancer in African Americans.

IMPACT

Our findings demonstrate novel cross-cancer pleiotropic associations with lung cancer risk in African Americans.

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439.

Epigenetic therapy for ovarian cancer: promise and progress

Ovarian cancer is the deadliest gynecologic malignancy, with a 5-year survival rate of approximately 47%, a number that has remained constant over the past two decades. Early diagnosis improves survival, but unfortunately only 15% of ovarian cancers are diagnosed at an early or localized stage. Most ovarian cancers are epithelial in origin and treatment prioritizes surgery and cytoreduction followed by cytotoxic platinum and taxane chemotherapy. While most tumors will initially respond to this treatment, recurrence is likely to occur within a median of 16 months for patients who present with advanced stage disease. New treatment options separate from traditional chemotherapy that take advantage of advances in understanding of the pathophysiology of ovarian cancer are needed to improve outcomes. Recent work has shown that mutations in genes encoding epigenetic regulators are mutated in ovarian cancer, driving tumorigenesis and resistance to treatment. Several of these epigenetic modifiers have emerged as promising drug targets for ovarian cancer therapy. In this article, we delineate epigenetic abnormalities in ovarian cancer, discuss key scientific advances using epigenetic therapies in preclinical ovarian cancer models, and review ongoing clinical trials utilizing epigenetic therapies in ovarian cancer.

Genomics to immunotherapy of ovarian clear cell carcinoma: Unique opportunities for management

Ovarian clear cell carcinoma (OCCC) is distinctive from other histological types of epithelial ovarian cancer, with genetic/epigenetic alterations, a specific immune-related molecular profile, and epidemiologic associations with ethnicity and endometriosis. These findings allow for the exploration of unique and specific treatments for OCCC. Two major mutated genes in OCCC are PIK3CA and ARID1A, which are frequently coexistent with each other. Other genes' alterations also contribute to activation of the PI3K (e.g. PIK3R1 and PTEN) and dysregulation of the chromatin remodeling complex (e.g. ARID1B, and SMARKA4). Although the number of focal copy number variations is small in OCCC, amplification is recurrently detected at chromosome 20q13.2 (including ZNF217), 8q, and 17q. Both expression and methylation profiling highlight the significance of adjustments to oxidative stress and inflammation. In particular, up-regulation of HNF-1β resulting from hypomethylation contributes to the switch from anaerobic to aerobic glucose metabolism. Additionally, up-regulation of HNF-1β activates STAT3 and NF-κB signaling, and leads to immune suppression via production of IL-6 and IL-8. Immune suppression may also be induced by the increased expression of PD-1, Tim-3 and LAG3. Mismatch repair deficient (microsatellite instable) tumors as found in Lynch syndrome also induce immune suppression in some OCCC. In a recent phase II clinical trial in heavily-treated platinum-resistant ovarian cancer, two out of twenty cases with a complete response to the anti-PD-1 antibody, nivolumab, were OCCC subtypes. Thus, the immune-suppressive state resulting from both genetic alterations and the unique tumor microenvironment may be associated with sensitivity to immune checkpoint inhibitors in OCCC. In this review, we highlight recent update and progress in OCCC from both the genomic and immunologic points of view, addressing the future candidate therapeutic options.

A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.

Epigenetics in ovarian cancer

Ovarian cancer is a disease with a poor prognosis and little progress has been made to improve treatment. It is now recognized that there are several histotypes of ovarian cancer, each with distinct epidemiologic and genomic characteristics. Cancer therapy is moving beyond classical chemotherapy to include epigenetic approaches. Epigenetics is the dynamic regulation of gene expression by DNA methylation and histone post translational modification in response to environmental cues. Improvement in technology to study DNA methylation has enabled a more agnostic approach and, with larger samples sets, has begun to unravel how epigenetics contributes to the etiology, response to chemotherapy and prognosis in of ovarian cancer. Investigations into histone modifications in ovarian cancer are more nascent. Much more is needed to be done to fully realize the potential that epigenetics holds for ovarian cancer clinical care.

Cumulative evidence for relationships between multiple variants of HNF1B and the risk of prostate and endometrial cancers

Background

To provide a synopsis of the current understanding of the association between variants of HNF1B and cancer susceptibility, we conducted a comprehensive research synopsis and meta-analysis to evaluate associations between HNF1B variants and prostate and endometrial cancers.

Results

Eighteen studies totaling 34,937 patients and 55,969 controls were eligible for this meta-analysis. Four variants showed a significant association with the risk of individual cancer. Strong significant associations were found between rs4430796 A and the risk of both prostate cancer (OR = 1.247, p = 2.21 × 10^− 77) and endometrial cancer (OR = 1.217, p = 8.98 × 10^− 16); the AA, AG genotypes also showed strong significant associations with the risk of prostate cancer (OR1 = 1.517, p = 4.46 × 10^− 22; OR2 = 1.180, p = 0.002). There was a strong significant association between rs7501939 G and the risk of prostate cancer (OR = 1.201, p = 9.31 × 10^− 31). Strong significant association was found between rs11649743 G (OR = 1.138, p = 1.08 × 10^− 12), rs3760511 C (OR = 1.214, p = 1.57 × 10^− 19) and the prostate cancer risk;the GG, AG genotypes of rs11649743 also showed strong significant associations with the risk of prostate cancer (OR1 = 1.496, p = 3.32 × 10^− 6; OR2 = 1.276, p = 7.82 × 10^− 6). All the cumulative epidemiological evidence of associations was graded as strong.

Conclusions

Our study summarizes the evidence and helps to reveal that common variants of HNF1B are associated with risk of prostate and endometrial cancer.

Transcriptomic Characterization of Endometrioid, Clear Cell, and High-Grade Serous Epithelial Ovarian Carcinoma

Background: Endometrioid carcinoma (EC) and clear cell carcinoma (CC) histotypes of epithelial ovarian cancer are understudied compared with the more common high-grade serous carcinomas (HGSC). We therefore sought to characterize EC and CC transcriptomes in relation to HGSC.Methods: Following bioinformatics processing and gene abundance normalization, differential expression analysis of RNA sequence data collected on fresh-frozen tumors was completed with nonparametric statistical analysis methods (55 ECs, 19 CCs, 112 HGSCs). Association of gene expression with progression-free survival (PFS) was completed with Cox proportional hazards models. Eight additional multi-histotype expression array datasets (N = 852 patients) were used for replication.Results: In the discovery set, tumors generally clustered together by histotype. Thirty-two protein-coding genes were differentially expressed across histotype (P < 1 × 10^-10) and showed similar associations in replication datasets, including MAP2K6, KIAA1324, CDH1, ENTPD5, LAMB1, and DRAM1 Nine genes associated with PFS (P < 0.0001) showed similar associations in replication datasets. In particular, we observed shorter PFS time for CC and EC patients with high gene expression for CCNB2, CORO2A, CSNK1G1, FRMD8, LIN54, LINC00664, PDK1, and PEX6, whereas, the converse was observed for HGSC patients.Conclusions: The results suggest important histotype differences that may aid in the development of treatment options, particularly those for patients with EC or CC.Impact: We present replicated findings on transcriptomic differences and how they relate to clinical outcome for two of the rarer ovarian cancer histotypes of EC and CC, along with comparison with the common histotype of HGSC. Cancer Epidemiol Biomarkers Prev; 27(9); 1101-9. ©2018 AACR.

Glutathione in Ovarian Cancer: A Double-Edged Sword

Glutathione (GSH) has several roles in a cell, such as a reactive oxygen species (ROS) scavenger, an intervenient in xenobiotics metabolism and a reservoir of cysteine. All of these activities are important in the maintenance of normal cells homeostasis but can also constitute an advantage for cancer cells, allowing disease progression and resistance to therapy. Ovarian cancer is the major cause of death from gynaecologic disease and the second most common gynaecologic malignancy worldwide. In over 50 years, the overall survival of patients diagnosed with epithelial ovarian cancer has not changed, regardless of the efforts concerning early detection, radical surgery and new therapeutic approaches. Late diagnosis and resistance to therapy are the main causes of this outcome, and GSH is profoundly associated with chemoresistance to platinum salts, which, together with taxane-based chemotherapy and surgery, are the main therapy strategies in ovarian cancer treatment. Herein, we present some insights into the role of GSH in the poor prognosis of ovarian cancer, and also point out how some strategies underlying the dependence of ovarian cancer cells on GSH can be further used to improve the effectiveness of therapy.

Endometriosis-associated Ovarian Cancers

Endometriosis-associated cancers include clear cell and endometrioid ovarian carcinoma. A history of endometriosis has long been considered to be a risk factor for later development of these malignancies; however, recent molecular genetic evidence has provided unequivocal evidence that these lesions are in fact the precursors for endometriosis-associated cancers. Herein, we will explore the relationship between endometriosis and ovarian carcinomas, similarities between the premalignant lesions and their cancerous counterparts, and the potential role of mutations and the ovarian microenvironment that may contribute to malignant transformation.