Characterization of fusion genes in common and rare epithelial ovarian cancer histologic subtypes

Integrated mutational landscape analysis of poorly differentiated high-grade neuroendocrine carcinoma of the uterine cervix

High-grade neuroendocrine cervical cancers (NETc) are exceedingly rare, highly aggressive tumors. We analyzed 64 NETc tumor samples by whole-exome sequencing (WES). Human papillomavirus DNA was detected in 65.6% (42/64) of the tumors. Recurrent mutations were identified in PIK3CA, KMT2D/MLL2, K-RAS, ARID1A, NOTCH2, and RPL10. The top mutated genes included RB1, ARID1A, PTEN, KMT2D/MLL2, and WDFY3, a gene not yet implicated in NETc. Somatic CNV analysis identified two copy number gains (3q27.1 and 19q13.12) and five copy number losses (1p36.21/5q31.3/6p22.2/9q21.11/11p15.5). Also, gene fusions affecting the ACLY-CRHR1 and PVT1-MYC genes were identified in one of the eight samples subjected to RNA sequencing. To resolve evolutionary history, multiregion WES in NETc admixed with adenocarcinoma cells was performed (i.e., mixed-NETc). Phylogenetic analysis of mixed-NETc demonstrated that adenocarcinoma and neuroendocrine elements derive from a common precursor with mutations typical of adenocarcinomas. Over one-third (22/64) of NETc demonstrated a mutator phenotype of C > T at CpG consistent with deficiencies in MBD4, a member of the base excision repair (BER) pathway. Mutations in the PI3K/AMPK pathways were identified in 49/64 samples. We used two patient-derived-xenografts (PDX) (i.e., NET19 and NET21) to evaluate the activity of pan-HER (afatinib), PIK3CA (copanlisib), and ATR (elimusertib) inhibitors, alone and in combination. PDXs harboring alterations in the ERBB2/PI3K/AKT/mTOR/ATR pathway were sensitive to afatinib, copanlisib, and elimusertib (P < 0.001 vs. controls). However, combinations of copanlisib/afatinib and copanlisib/elimusertib were significantly more effective in controlling NETc tumor growth. These findings define the genetic landscape of NETc and suggest that a large subset of these highly lethal malignancies might benefit from existing targeted therapies.

Prognostic Model for High-Grade Neuroendocrine Carcinoma of the Lung Incorporating Genomic Profiling and Poly (ADP-ribose) Polymerase-1 Expression

PURPOSE

High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model.

MATERIALS AND METHODS

We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102). Clinical and genetic data were used to develop an integrated Cox hazards model.

RESULTS

Strong PARP1 IHC expression (intensity 3) was observed in 153 of 191 (80.1%) patients, and the mean PARP1 H-score was 285 (range, 5-300). To develop an integrated Cox hazard model, our data set included information from 357 gene mutations and 19 clinical profiles. When the targeted mutation profiles were combined with clinical profiles, 12 genes (ATRX, CCND2, EXT2, FGFR2, FOXO1, IL21R, MAF, TGM7, TNFAIP3, TP53, TSHR, and DDR2) were identified as prognostic factors for survival. The integrated Cox hazard model, which combines mutation profiles with a baseline model, outperformed the baseline model (incremental area under the curve 0.84 v 0.78; P = 8.79e-12). The integrated model stratified patients into high- and low-risk groups with significantly different disease-free and overall survival (integrated model: hazard ratio, 7.14 [95% CI, 4.07 to 12.54]; P < .01; baseline model: 4.38 [2.56 to 7.51]; P < .01).

CONCLUSION

We introduced a new prognostic model for HGNEC that combines genetic and clinical data. The integrated Cox hazard model outperformed the baseline model in predicting the survival of patients with HGNEC.

A comprehensive molecular analysis of 113 primary ovarian clear cell carcinomas reveals common therapeutically significant aberrations

BACKGROUND

Molecular aberrations occurring in primary ovarian clear cell carcinoma (OCCC) can be of diagnostic, predictive, and prognostic significance. However, a complex molecular study including genomic and transcriptomic analysis of large number of OCCC has been lacking.

METHODS

113 pathologically confirmed primary OCCCs were analyzed using capture DNA NGS (100 cases; 727 solid cancer related genes) and RNA-Seq (105 cases; 147 genes) in order to describe spectra and frequency of genomic and transcriptomic alterations, as well as their prognostic and predictive significance.

RESULTS

The most frequent mutations were detected in genes ARID1A, PIK3CA, TERTp, KRAS, TP53, ATM, PPP2R1A, NF1, PTEN, and POLE (51,47,27,18,13,10,7,6,6, and 4%, respectively). TMB-High cases were detected in 9% of cases. Cases with POLE^mut and/or MSI-High had better relapse-free survival. RNA-Seq revealed gene fusions in 14/105 (13%) cases, and heterogeneous expression pattern. The majority of gene fusions affected tyrosine kinase receptors (6/14; four of those were MET fusions) or DNA repair genes (2/14). Based on the mRNA expression pattern, a cluster of 12 OCCCs characterized by overexpression of tyrosine kinase receptors (TKRs) AKT3, CTNNB1, DDR2, JAK2, KIT, or PDGFRA (p < 0.00001) was identified.

CONCLUSIONS

The current work has elucidated the complex genomic and transcriptomic molecular hallmarks of primary OCCCs. Our results confirmed the favorable outcomes of POLE^mut and MSI-High OCCC. Moreover, the molecular landscape of OCCC revealed several potential therapeutical targets. Molecular testing can provide the potential for targeted therapy in patients with recurrent or metastatic tumors.

Immunotherapeutic Approaches in Ovarian Cancer

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes

PURPOSE

To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes.

EXPERIMENTAL DESIGN

We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival.

RESULTS

We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy.

CONCLUSIONS

Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

Into the future: A pilot study combining imaging with molecular profiling to predict resectability in ovarian cancer

OBJECTIVE

We sought to determine the predictive value of combining tumor molecular subtype and computerized tomography (CT) imaging for surgical outcomes after primary cytoreductive surgery in advanced stage high-grade serous ovarian cancer (HGSOC) patients.

METHODS

We identified 129 HGSOC patients who underwent pre-operative CT imaging and post-operative tumor mRNA profiling. A continuous CT-score indicative of overall disease burden was defined based on six imaging measurements of anatomic involvement. Molecular subtypes were derived from mRNA profiling of chemo-naïve tumors and classified as mesenchymal (MES) subtype (36%) or non-MES subtype (64%). Fischer exact tests and multivariate logistic regression examined residual disease and surgical complexity.

RESULTS

Women with higher CT-scores were more likely to have MES subtype tumors (p = 0.014). MES subtypes and a high CT-score were independently predictive of macroscopic disease and high surgical complexity. In multivariate models adjusting for age, stage and American Society of Anesthesiologists (ASA) score, patients with a MES subtype and high CT-score had significantly elevated risk of macroscopic disease (OR = 26.7, 95% CI = [6.42, 187]) and were more likely to undergo high complexity surgery (OR = 9.53, 95% CI = [2.76, 40.6], compared to patients with non-MES tumor and low CT-score.

CONCLUSION

Preoperative CT imaging combined with tumor molecular subtyping can identify a subset of women unlikely to have resectable disease and likely to require high complexity surgery. Along with other clinical factors, these may refine predictive scores for resection and assist treatment planning. Investigating methods for pre-surgical molecular subtyping is an important next step.

RNA biomarkers from proximal liquid biopsy for diagnosis of ovarian cancer

BACKGROUND

Most ovarian cancer patients are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers that are sensitive for early stage disease are lacking. This medical need justifies the search for novel approaches using utero-tubal lavage as a proximal liquid biopsy.

METHODS

In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing.

RESULTS

We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor-derived signal.

CONCLUSION

This is a proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study.

IMPACT

Proximal liquid biopsy from the gynecologic tract is a promising source for mRNA and miRNA biomarkers for diagnosis of early-stage ovarian cancer.

The Role of Omics Approaches to Characterize Molecular Mechanisms of Rare Ovarian Cancers: Recent Advances and Future Perspectives

Rare ovarian cancers are ovarian cancers with an annual incidence of less than 6 cases per 100,000 women. They generally have a poor prognosis due to being delayed diagnosis and treatment. Exploration of molecular mechanisms in these cancers has been challenging due to their rarity and research efforts being fragmented across the world. Omics approaches can provide detailed molecular snapshots of the underlying mechanisms of these cancers. Omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, can identify potential candidate biomarkers for diagnosis, prognosis, and screening of rare gynecological cancers and can aid in identifying therapeutic targets. The integration of multiple omics techniques using approaches such as proteogenomics can provide a detailed understanding of the molecular mechanisms of carcinogenesis and cancer progression. Further, omics approaches can provide clues towards developing immunotherapies, cancer recurrence, and drug resistance in tumors; and form a platform for personalized medicine. The current review focuses on the application of omics approaches and integrative biology to gain a better understanding of rare ovarian cancers.

Systematic analysis of the relationship between ovarian cancer prognosis and alternative splicing

Background

Ovarian cancer(OC) is the gynecological tumor with the highest mortality rate, effective biomarkers are of great significance in improving its prognosis. In recent years, there have been many studies on alternative splicing (AS) events, and the role of AS events in tumor has become a focus of attention.

Methods

Data were downloaded from the TCGA database and Univariate Cox regression analysis was performed to determine AS events associated with OC prognosis.Eight prognostic models of OC were constructed in R package, and the accuracy of the models were evaluated by the time-dependent receiver operating characteristic (ROC) curves.Eight types of survival curves were drawn to evaluate the differences between the high and low risk groups.Independent prognostic factors of OC were analyzed by single factor independent analysis and multi-factor independent prognostic analysis.Again, Univariate Cox regression analysis was used to analyze the relationship between splicing factors(SF) and AS events, and Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis were performed on OS-related SFs to understand the pathways.

Results

Univariate Cox regression analysis showed that among the 15,278 genes, there were 31,286 overall survival (OS) related AS events, among which 1524 AS events were significantly correlated with OS. The area under the time-dependent receiver operating characteristic curve (AUC) of AT and ME were the largest and the RI was the smallest,which were 0.757 and 0.68 respectively. The constructed models have good value for the prognosis assessment of OC patients. Among the eight survival curves, AP was the most significant difference between the high and low risk groups, with a P value of 1.61e − 1.The results of single factor independent analysis and multi-factor independent prognostic analysis showed that risk score calculated by the model and age could be used as independent risk factors.According to univariate COX regression analysis,109 SFs were correlated with AS events and adjusted in two ways: positive and negative.

Conclusions

SFs and AS events can directly or indirectly affect the prognosis of OC patients. It is very important to find effective prognostic markers to improve the survival rate of OC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00866-1.

Advances in understanding the molecular pathology of gynecological malignancies: the role and potential of RNA sequencing

For many years technological limitations restricted the progress of identifying the underlying genetic causes of gynecologicalcancers. However, during the past decade, high-throughput next-generation sequencing technologies have revolutionized cancer research. RNA sequencing has arisen as a very useful technique in expanding our understanding of genome changes in cancer. Cancer is characterized by the accumulation of genetic alterations affecting genes, including substitutions, insertions, deletions, translocations, gene fusions, and alternative splicing. If these aberrant genes become transcribed, aberrations can be detected by RNA sequencing, which will also provide information on the transcript abundance revealing the expression levels of the aberrant genes. RNA sequencing is considered the technique of choice when studying gene expression and identifying new RNA species. This is due to the quantitative and qualitative improvement that it has brought to transcriptome analysis, offering a resolution that allows research into different layers of transcriptome complexity. It has also been successful in identifying biomarkers, fusion genes, tumor suppressors, and uncovering new targets responsible for drug resistance in gynecological cancers. To illustrate that we here review the role of RNA sequencing in studies that enhanced our understanding of the molecular pathology of gynecological cancers.

Frequent POLE-driven hypermutation in ovarian endometrioid cancer revealed by mutational signatures in RNA sequencing

BACKGROUND

DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT > TAT and TCG > TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC.

METHODS

Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n = 195), The Cancer Genome Atlas (TCGA) OC tumors (n = 419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n = 84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10.

RESULTS

In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P = 5e-04). These six tumors had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P = .008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations.

CONCLUSIONS

From the largest cohort of RNA-seq from endometrioid OC to date (n = 53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

Identification of Novel Fusion Transcripts in High Grade Serous Ovarian Cancer

Fusion genes are structural chromosomal rearrangements resulting in the exchange of DNA sequences between genes. This results in the formation of a new combined gene. They have been implicated in carcinogenesis in a number of different cancers, though they have been understudied in high grade serous ovarian cancer. This study used high throughput tools to compare the transcriptome of high grade serous ovarian cancer and normal fallopian tubes in the interest of identifying unique fusion transcripts within each group. Indeed, we found that there were significantly more fusion transcripts in the cancer samples relative to the normal fallopian tubes. Following this, the role of fusion transcripts in chemo-response and overall survival was investigated. This led to the identification of fusion transcripts significantly associated with overall survival. Validation was performed with different analytical platforms and different algorithms to find fusion transcripts.

Analysis in epithelial ovarian cancer identifies KANSL1 as a biomarker and target gene for immune response and HDAC inhibition

OBJECTIVE

There is an immunoreactive subtype of ovarian cancer with a favorable prognosis, but the majority of ovarian cancers have limited immune reactivity. The reason for this is poorly understood. This study aimed to approach this question by identifying prognostically relevant genes whose prognostic mRNA expression levels correlated with a genomic event.

METHODS

Expression microarray and 5-year survival data on 170 ovarian tumors and aCGH data on 45 ovarian cancer cell lines were used to identify amplified/deleted genes associated with prognosis. Three immune-response genes were identified mapping to epigenetically modified chromosome 6p21.3. Genes were searched for roles in epigenetic modification, identifying KANSL1. Genome-wide association studies were searched to identify genetic variants in KANSL1 associated with altered immune profile. Sensitivity to HDAC inhibition in cell lines with KANSL1 amplification/rearrangement was studied.

RESULTS

Expression of 196 genes was statistically significantly associated with survival, and expression levels correlated with copy number variations for 82 of them. Among these, 3 immune-response genes (HCP5, PSMB8, PSMB9) clustered together at epigenetically modified chromosome 6p21.3 and their expression was inversely correlated to epigenetic modification gene KANSL1. KANSL1 is amplified/rearranged in ovarian cancer, associated with lymphocyte profile, a biomarker for response to HDAC inhibition, and may drive expression of immune-response genes.

CONCLUSION

This study identifies 82 genes with prognostic relevance and genomic alteration in ovarian cancer. Among these, immune-response genes have correlated expression which is associated with 5-year survival. KANSL1 may be a master gene altering immune-response gene expression at 6p21.3 and drive response to HDAC inhibitors. Future research should investigate KANSL1 and determine whether targeting it alters the immune profile of ovarian cancer and improves survival, HDAC inhibition, and/or immunotherapy response.

MET Alterations Are a Recurring and Actionable Resistance Mechanism in ALK-Positive Lung Cancer

PURPOSE

Most ALK-positive lung cancers will develop ALK-independent resistance after treatment with next-generation ALK inhibitors. MET amplification has been described in patients progressing on ALK inhibitors, but frequency of this event has not been comprehensively assessed.

EXPERIMENTAL DESIGN

We performed FISH and/or next-generation sequencing on 207 posttreatment tissue (n = 101) or plasma (n = 106) specimens from patients with ALK-positive lung cancer to detect MET genetic alterations. We evaluated ALK inhibitor sensitivity in cell lines with MET alterations and assessed antitumor activity of ALK/MET blockade in ALK-positive cell lines and 2 patients with MET-driven resistance.

RESULTS

MET amplification was detected in 15% of tumor biopsies from patients relapsing on next-generation ALK inhibitors, including 12% and 22% of biopsies from patients progressing on second-generation inhibitors or lorlatinib, respectively. Patients treated with a second-generation ALK inhibitor in the first-line setting were more likely to develop MET amplification than those who had received next-generation ALK inhibitors after crizotinib (P = 0.019). Two tumor specimens harbored an identical ST7-MET rearrangement, one of which had concurrent MET amplification. Expressing ST7-MET in the sensitive H3122 ALK-positive cell line induced resistance to ALK inhibitors that was reversed with dual ALK/MET inhibition. MET inhibition resensitized a patient-derived cell line harboring both ST7-MET and MET amplification to ALK inhibitors. Two patients with ALK-positive lung cancer and acquired MET alterations achieved rapid responses to ALK/MET combination therapy.

CONCLUSIONS

Treatment with next-generation ALK inhibitors, particularly in the first-line setting, may lead to MET-driven resistance. Patients with acquired MET alterations may derive clinical benefit from therapies that target both ALK and MET.

NSCLC Mutated Isoforms of CCDC6 Affect the Intracellular Distribution of the Wild Type Protein Promoting Cisplatinum Resistance and PARP Inhibitors Sensitivity in Lung Cancer Cells

CCDC6 is implicated in cell cycle checkpoints and DNA damage repair by homologous recombination (HR). In NSCLC, CCDC6 is barely expressed in about 30% of patients and CCDC6 gene rearrangements with RET and ROS kinases are detected in about 1% of patients. Recently, CCDC6 point-mutations naming E227K, S351Y, N394Y, and T462A have been identified in primary NSCLC. In this work, we analyze the effects exerted by the CCDC6 mutated isoforms on lung cancer cells. By pull-down experiments and immunofluorescence, we evaluated the biochemical and morphological effects of CCDC6 lung-mutants on the CCDC6 wild type protein. By using two HR-reporter assays, we analyzed the effect of CCDC6 lung-mutants in perturbing CCDC6 physiology in the HR process. Finally, by cell-titer assay, we evaluated the response to the treatment with different drugs in lung cancer cells expressing CCDC6 mutants. This work shows that the CCDC6 mutated and truncated isoforms, identified so far in NSCLC, affected the intracellular distribution of the wild type protein and impaired the CCDC6 function in the HR process, ultimately inducing cisplatinum resistance and PARP-inhibitors sensitivity in lung cancer cells. The identification of selected molecular alterations involving CCDC6 gene product might define predictive biomarkers for personalized treatment in NSCLC.

Molecular signatures of X chromosome inactivation and associations with clinical outcomes in epithelial ovarian cancer

X chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women's cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10-10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of residual disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.

Identification of recurrent fusion genes across multiple cancer types

Chromosome changes are one of the hallmarks of human malignancies. Chromosomal rearrangement is frequent in human cancers. One of the consequences of chromosomal rearrangement is gene fusions in the cancer genome. We have previously identified a panel of fusion genes in aggressive prostate cancers. In this study, we showed that 6 of these fusion genes are present in 7 different types of human malignancies with variable frequencies. Among them, the CCNH-C5orf30 and TRMT11-GRIK2 gene fusions were found in breast cancer, colon cancer, non-small cell lung cancer, esophageal adenocarcinoma, glioblastoma multiforme, ovarian cancer and liver cancer, with frequencies ranging from 12.9% to 85%. In contrast, four other gene fusions (mTOR-TP53BP1, TMEM135-CCDC67, KDM4-AC011523.2 and LRRC59-FLJ60017) are less frequent. Both TRMT11-GRIK2 and CCNH-C5orf30 are also frequently present in lymph node metastatic cancer samples from the breast, colon and ovary. Thus, detecting these fusion transcripts may have significant biological and clinical implications in cancer patient management.

Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival

Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I and II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.

Identification of novel cyclin gene fusion transcripts in endometrioid ovarian carcinomas

Formation of fusion genes is pathogenetically crucial in many solid tumors. They are particularly characteristic of several mesenchymal tumors, but may also be found in epithelial neoplasms. Ovarian carcinomas, too, may harbor fusion genes but only few of these were found to be recurrent with a rate ranging from 0.5 to 5%. Because most attempts to find specific and recurrent fusion transcripts in ovarian carcinomas focused exclusively on high‐grade serous carcinomas, the situation in the other carcinoma subgroups remains largely uninvestigated as far as fusion genes are concerned. We performed transcriptome sequencing on a series of 34 samples from ovarian tumors that included borderline, clear cell, mucinous, endometrioid, low‐grade and high‐grade serous carcinomas in search of fusion genes typical of these subtypes. We found a total of 24 novel fusion transcripts. The PCMTDI‐CCNL2 fusion transcript, which involves a member of the cyclin family, was found recurrently involved but only in endometrioid carcinomas (4 of 18 tumors; 22%). We also found three additional fusion transcripts involving genes belonging to the cyclin family: ANXA5‐CCNA2 and PDE4D‐CCNB1 were detected in two endometrioid carcinomas, whereas CCNY‐NRG4 was identified in a clear cell carcinoma. The recurrent involvement of CCNL2 in four fusions and of three other genes of the cyclin family in three additional transcripts hints that deregulation of cyclin genes is important in the pathogenesis of ovarian carcinomas in general but of endometrioid carcinomas particularly.

What's new?

Chimeric genes formed by fusion of previously separate genes are associated with many malignant tumors, but rare in ovarian cancer. Here the authors performed transcriptome sequencing of different types of ovarian tumors and identify novel fusion genes, involving cyclin genes, the master regulators of the cell cycle. As most of these fusions were found in ovarian cancer of the endometroid type, which represent about 10% of all ovarian cancers, the data point to a novel role of cyclin deregulation in this specific cancer subtype.

Assessment of data transformations for model-based clustering of RNA-Seq data

Quality control, global biases, normalization, and analysis methods for RNA-Seq data are quite different than those for microarray-based studies. The assumption of normality is reasonable for microarray based gene expression data; however, RNA-Seq data tend to follow an over-dispersed Poisson or negative binomial distribution. Little research has been done to assess how data transformations impact Gaussian model-based clustering with respect to clustering performance and accuracy in estimating the correct number of clusters in RNA-Seq data. In this article, we investigate Gaussian model-based clustering performance and accuracy in estimating the correct number of clusters by applying four data transformations (i.e., naïve, logarithmic, Blom, and variance stabilizing transformation) to simulated RNA-Seq data. To do so, an extensive simulation study was carried out in which the scenarios varied in terms of: how genes were selected to be included in the clustering analyses, size of the clusters, and number of clusters. Following the application of the different transformations to the simulated data, Gaussian model-based clustering was carried out. To assess clustering performance for each of the data transformations, the adjusted rand index, clustering error rate, and concordance index were utilized. As expected, our results showed that clustering performance was gained in scenarios where data transformations were applied to make the data appear "more" Gaussian in distribution.