Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures

Prognostic factors of 87 ovarian yolk sac tumor (OYST) patients and molecular characteristics of persistent and recurrent OYST

OBJECTIVE

We aimed to explore the characteristics of OYST, particularly for persistent and recurrent OYST, in order to explore potential treatment options and thereby improve patient outcomes.

METHODS

We retrospectively reviewed the clinical records of all patients with OYST at Fudan university Shanghai Cancer Center from December 3, 2005 to November 27, 2020. Furthermore, and performed whole-exome sequencing on 17 paired OYST (including 8 paired persistent and recurrent OYST) tumor and blood samples to elucidate the aberrant molecular features.

RESULTS

Totally, 87 OYST patients were included between 2007/03/13 and 2020/11/17. With a median follow-up of 73 [3-189] months, 22 patients relapsed or disease persisted. Overall, 17 patients died with a median overall survival of 21 [3-54] months. Univariate and multivariate analysis revealed tumor histology and residual lesions were independently associated with event free survival and overall survival, cycles to AFP normalization were another independent risk factor for overall survival. For the 8 persistent and recurrent OYST: cancer driver genes including ANKRD36, ANKRD62, DNAH8, MUC5B, NUP205, RYR2, STARD9, MUC16, TTN, ARID1A and PIK3CA were frequently mutated; cell cycle, ABC transporters, HR, NHEJ and AMPK signal pathway demonstrated as the most significantly enriched pathways; TMB, DNA MMR gene mutation and MSI were significantly higher. Mutation signature 11, 19 and 30 were the dominant contributors in persistent and recurrent OYST mutation.

CONCLUSION

Persistent and recurrent OYST associated with poor prognosis, and probably susceptible to immune checkpoint blockade therapy. Molecular characteristics contributed to predict the persistence and recurrence of OYST.

A prognostic model based on DNA methylation-related gene expression for predicting overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression.

Methods

Transcriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively.

Results

Three methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications.

Conclusion

Through bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.

Genomic Breakpoints’ Characterization of a Large CHEK2 Duplication in an Italian Family with Hereditary Breast Cancer

CHEK2 (checkpoint kinase 2; MIM# 604373) is a tumor suppressor gene that encodes a serine threonine kinase involved in pathways such as DNA repair, cell cycle arrest, mitosis, and apoptosis. Pathogenic variants in CHEK2 contribute to a moderately increased risk of breast and other cancers. Several variant classes have been reported, either point mutations or large intragenic rearrangements. However, a significant portion of reported variants has an uncertain clinical significance. We report an intragenic CHEK2 duplication, ranging from intron 5 to intron 13, identified in an Italian family with hereditary breast cancer. Using long range PCR, with duplication-specific primers, we were able to ascertain the genomic breakpoint. We also performed a real-time PCR to assess a possible loss-of-function effect. The genomic characterization of large intragenic rearrangements in cancer susceptibility genes is important for the clinical management of the carriers and for a better classification of rare variants. The molecular definition of breakpoints allows for the prediction of the impact of the variant on transcripts and proteins, aiding in its characterization and clinical classification.

Clinical Utility of Germline Genetic Testing in Japanese Men Undergoing Prostate Biopsy

Background

Multiple common variants and also rare variants in monogenic risk genes such as BRCA2 and HOXB13 have been reported to be associated with risk of prostate cancer (PCa); however, the clinical setting in which germline genetic testing could be used for PCa diagnosis remains obscure. Herein, we tested the clinical utility of a 16 common variant–based polygenic risk score (PRS) that has been developed previously for Japanese men and also evaluated the frequency of PCa-associated rare variants in a prospective cohort of Japanese men undergoing prostate biopsy.

Methods

A total of 1336 patients undergoing first prostate biopsy were included. PRS was calculated based on the genotype of 16 common variants, and sequencing of 8 prostate cancer–associated genes was performed by multiplex polymerase chain reaction based target sequencing. PRS was combined with clinical factors in logistic regression models to assess whether addition of PRS improves the prediction of biopsy positivity.

Results

The top PRS decile was associated with an odds ratio of 4.10 (95% confidence interval = 2.46 to 6.86) with reference to the patients at average risk, and the estimated lifetime absolute risk approached 20%. Among the patients with prostate specific antigen 2-10 ng/mL who had prebiopsy magnetic resonance imaging, high PRS had an equivalent impact on biopsy positivity as a positive magnetic resonance imaging finding. Rare variants were detected in 19 (2.37%) and 7 (1.31%) patients with positive and negative biopsies, respectively, with BRCA2 variants being the most prevalent. There was no association between PRS and high-risk rare variants.

Conclusions

Germline genetic testing could be clinically useful in both pre- and post-PSA screening settings.

Identification of CHEK2 germline mutations in BRCA1/2 and PALB2 negative breast and ovarian cancer patients

INTRODUCTION

The CHEK2 gene is known to be an important signal transducer involved in DNA repair, apoptosis, or cell cycle arrest in response to DNA damage. The mutations in this gene have been associated with a wide range of cancers, both sporadic and hereditary. Germline CHEK2 mutations are linked to an increased risk of breast cancer. Therefore, the aim of this study was to identify the prevalence of CHEK2 variants in BRCA1/2 and PALB2 negative early-onset patients with breast cancer and/or ovarian cancer in a Turkish population for the first time.

METHODS

The study included 95 patients with BRCA1/2 and PALB2 negative early-onset breast cancer and/or ovarian cancer and also 60 unaffected women. All the intron/exon boundaries and coding exons of CHEK2 were subjected to mutational analysis by heteroduplex analysis and DNA sequencing.

RESULTS

A total of 16 CHEK2 variants were found in breast cancer patients within the Turkish population. CHEK2 c.1100delC mutation studied in the CHEK2 gene most frequently was not detected in our study. The prevalence of variants of uncertain significance in CHEK2 was found to be 7.3% (n= 7) in BRCA1/2 and PALB2 mutation negative Turkish patients with early-onset breast and/or ovarian cancer.

DISCUSSION/CONCLUSION

The present study may shed light on alternative variations that could be significant for understanding the prevalence and clinical suitability of the CHEK2 gene.

Multiomics subtyping for clinically prognostic cancer subtypes and personalized therapy: A systematic review and meta-analysis

PURPOSE

Multiomics cancer subtyping is becoming increasingly popular for directing state-of-the-art therapeutics. However, these methods have never been systematically assessed for their ability to capture cancer prognosis for identified subtypes, which is essential to effectively treat patients.

METHODS

We systematically searched PubMed, The Cancer Genome Atlas, and Pan-Cancer Atlas for multiomics cancer subtyping studies from 2010 through 2019. Studies comprising at least 50 patients and examining survival were included. Pooled Cox and logistic mixed-effects models were used to compare the ability of multiomics subtyping methods to identify clinically prognostic subtypes, and a structural equation model was used to examine causal paths underlying subtyping method and mortality.

RESULTS

A total of 31 studies comprising 10,848 unique patients across 32 cancers were analyzed. Latent-variable subtyping was significantly associated with overall survival (adjusted hazard ratio, 2.81; 95% CI, 1.16-6.83; P = .023) and vital status (1 year adjusted odds ratio, 4.71; 95% CI, 1.34-16.49; P = .015; 5 year adjusted odds ratio, 7.69; 95% CI, 1.83-32.29; P = .005); latent-variable-identified subtypes had greater associations with mortality across models (adjusted hazard ratio, 1.19; 95% CI, 1.01-1.42; P = .050). Our structural equation model confirmed the path from subtyping method through multiomics subtype (βˆ = 0.66; P = .048) on survival (βˆ = 0.37; P = .008).

CONCLUSION

Multiomics methods have different abilities to define clinically prognostic cancer subtypes, which should be considered before administration of personalized therapy; preliminary evidence suggests that latent-variable methods better identify clinically prognostic biomarkers and subtypes.

Whole-exome sequencing reveals potential germline and somatic mutations in 60 malignant ovarian germ cell tumors†

Malignant ovarian germ cell tumors (MOGCTs) are rare and heterogeneous ovary tumors. We aimed to identify potential germline mutations and somatic mutations in MOGCTs by whole-exome sequencing. The peripheral blood and tumor samples from these patients were used to identify germline mutations and somatic mutations, respectively. For those genes with copy number alterations (deletion and duplication region), functional annotation was performed. Immunohistochemistry was performed to evaluate the expression of mutated genes corresponding to CNA deletion region and duplication region. In peripheral blood, copy number loss and gain were mostly found in yolk sac tumors (YSTs). Moreover, POU5F1 was the most significant mutated gene with mutation frequency >10% in both CNA deletion and duplication region. In addition, strong cytoplasm staining of POU5F1 (corresponding to CNA deletion region and duplication region) was found in two YST and nuclear staining in two dysgerminomas tumor samples. Genes corresponding to CNA deletion region were significantly enriched in the signaling pathway of regulating pluripotency of stem cells. In addition, genes corresponding to CNA duplication region were significantly enriched in the signaling pathways of RIG-I (DExD/H-box helicase 58)-like receptor, Toll-like receptor and nuclear factor (NF)-kappa. Keratin 4 (KRT4), ribosomal protein L14 (RPL14), proprotein convertase subtilisin/kexin type 6 (PCSK6), poly(A)-binding protein cytoplasmic 3 (PABPC3), and sterile alpha and TIR motif containing 1 (SARM1) mutations were detected in both peripheral blood and tumor samples. Identification of potential germline mutations and somatic mutations in MOGCTs may provide a new field in understanding the genetic feature of the rare biological tumor type in the ovary.

A comprehensive analysis of somatic alterations in Chinese ovarian cancer patients

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for the Classification of Germline Sequence Variants in Risk Genes for Hereditary Breast and Ovarian Cancer

More than ten years ago, the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) set up a panel of experts (VUS Task Force) which was tasked with reviewing the classifications of genetic variants reported by individual centres of the GC-HBOC to the central database in Leipzig and reclassifying them, where necessary, based on the most recent data. When it evaluates variants, the VUS Task Force must arrive at a consensus. The resulting classifications are recorded in a central database where they serve as a basis for ensuring the consistent evaluation of previously known and newly identified variants in the different centres of the GC-HBOC. The standardised VUS evaluation by the VUS Task Force is a key element of the recall system which has also been set up by the GC-HBOC. The system will be used to pass on information to families monitored and managed by GC-HBOC centres in the event that previously classified variants are reclassified based on new information. The evaluation algorithm of the VUS Task Force was compiled using internationally established assessment methods (IARC, ACMG, ENIGMA) and is presented here together with the underlying evaluation criteria used to arrive at the classification decision using a flow chart. In addition, the characteristics and special features of specific individual risk genes associated with breast and/or ovarian cancer are discussed in separate subsections. The URLs of relevant databases have also been included together with extensive literature references to provide additional information and cover the scope and dynamism of the current state of knowledge on the evaluation of genetic variants. In future, if criteria are updated based on new information, the update will be published on the website of the GC-HBOC ( https://www.konsortium-familiaerer-brustkrebs.de/ ).

Genetic Predisposition to Breast and Ovarian Cancers: How Many and Which Genes to Test?

Breast and ovarian cancers are some of the most common tumors in females, and the genetic predisposition is emerging as one of the key risk factors in the development of these two malignancies. BRCA1 and BRCA2 are the best-known genes associated with hereditary breast and ovarian cancer. However, recent advances in molecular techniques, Next-Generation Sequencing in particular, have led to the identification of many new genes involved in the predisposition to breast and/or ovarian cancer, with different penetrance estimates. TP53, PTEN, STK11, and CDH1 have been identified as high penetrance genes for the risk of breast/ovarian cancers. Besides them, PALB2, BRIP1, ATM, CHEK2, BARD1, NBN, NF1, RAD51C, RAD51D and mismatch repair genes have been recognized as moderate and low penetrance genes, along with other genes encoding proteins involved in the same pathways, possibly associated with breast/ovarian cancer risk. In this review, we summarize the past and more recent findings in the field of cancer predisposition genes, with insights into the role of the encoded proteins and the associated genetic disorders. Furthermore, we discuss the possible clinical utility of genetic testing in terms of prevention protocols and therapeutic approaches.

Loss of CHEK2 Predicts Progression in Stage pT1 Non-Muscle-Invasive Bladder Cancer (NMIBC)

Downregulation of checkpoint protein kinase 2 (CHEK2), which is involved in DNA repair, is associated with poorer outcome in various tumors. Little is known about the role of CHEK2 in urothelial carcinoma of the bladder (UCB). In the present study, we investigated the prognostic impact of CHEK2 protein expression in stage pT1 UCB. This retrospective, single-center analysis was carried out in a cohort of patients initially diagnosed with a pT1 UCB between 2007 and 2015. Immunohistochemical (IHC) staining of CHEK2 was performed. CHEK2 expression was correlated with recurrence-free survival (RFS), progression-free survival (PFS), and cancer-specific survival (CSS) using Kaplan-Meier analysis and multivariable Cox regression analysis. The analysis included 126 patients (86% male, median age 71 years). Loss of immunohistochemical protein expression of CHEK2 (<10%) was associated with significantly worse PFS (p = 0.041). Likewise, CHEK2 loss identified a subgroup of patients with worse PFS in the high-risk groups with concomitant CIS (p = 0.044), multifocal tumors (p < 0.001) and tumor grading G3 according to WHO1973 (p = 0.009). Multivariable Cox regression analysis revealed both loss of CHEK2 expression (HR: 4.18, 95%-CI: 1.35-12.93; p = 0.013) and multifocal tumors (HR: 4.53, 95%-CI:1.29-15.92; p = 0.018) as the only predictive factors for progression. Loss of IHC expression of CHEK2 in pT1 UCB is an independent predictor for progression to muscle-invasive disease and is also associated with worse PFS. This could help to identify high-risk patients who would benefit from early cystectomy.

HLA-G 3' untranslated region variants +3187G/G, +3196G/G and +3035T define diametrical clinical status and disease outcome in epithelial ovarian cancer

Expression of the non-classical human leukocyte antigen-G (HLA-G) promotes cancer progression in various malignancies including epithelial ovarian cancer (EOC). As single nucleotide polymorphisms (SNPs) in the HLA-G 3' untranslated region (UTR) regulate HLA-G expression, we investigated HLA-G 3'UTR haplotypes arranged by SNPs in healthy controls (n = 75) and primary EOC patients (n = 79) and determined soluble HLA-G (sHLA-G) levels. Results were related to the clinical status and outcome. Although haplotype frequencies were similar in patients and controls, (i) sHLA-G levels were increased in EOC independent of the haplotype, (ii) homozygosity for UTR-1 or UTR-2 genotypes were significantly associated with metastases formation and presence of circulating tumor cells before therapy, whereas (iii) the UTR-5 and UTR-7 haplotypes were significantly associated with a beneficial clinical outcome regarding negative nodal status, early FIGO staging, and improved overall survival. Lastly, (iv) the ambivalent impact on clinical EOC aspects could be deduced to specific SNPs in the HLA-G 3'UTR: +3187G, +3196G and +3035T alleles. Our results give evidence that even if the genetic background of the HLA-G 3'UTR is identical between patients and controls, certain SNPs have the potential to contribute to diametrical clinical status/outcome in EOC.

Developing a genetic signature to predict drug response in ovarian cancer

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

Bioinformatics and Drug Discovery

Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.

Big genomics and clinical data analytics strategies for precision cancer prognosis

The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups. Here, we investigated the predictive performance of PSVM via optimization of the prognostic variable weights, which represent the relative importance of one prognostic variable over the others. In addition, we compared several multivariate prognostic models based on PSVM with classical machine learning techniques such as K-nearest-neighbor, support vector machine, random forest, neural networks and logistic regression. Our results revealed that negative log-rank p-values provides more robust weight values as opposed to the use of other quantities such as hazard ratios, fold change, or a combination of those factors. PSVM, together with the classical machine learning classifiers were combined in an ensemble (multi-test) voting system, which collectively provides a more precise and reproducible patient stratification. The use of the multi-test system approach, rather than the search for the ideal classification/prediction method, might help to address limitations of the individual classification algorithm in specific situation.

Targeting SOD1 induces synthetic lethal killing in BLM- and CHEK2-deficient colorectal cancer cells

Cancer is a major cause of death throughout the world, and there is a large need for better and more personalized approaches to combat the disease. Over the past decade, synthetic lethal approaches have been developed that are designed to exploit the aberrant molecular origins (i.e. defective genes) that underlie tumorigenesis. BLM and CHEK2 are two evolutionarily conserved genes that are somatically altered in a number of tumor types. Both proteins normally function in preserving genome stability through facilitating the accurate repair of DNA double strand breaks. Thus, uncovering synthetic lethal interactors of BLM and CHEK2 will identify novel candidate drug targets and lead chemical compounds. Here we identify an evolutionarily conserved synthetic lethal interaction between SOD1 and both BLM and CHEK2 in two distinct cell models. Using quantitative imaging microscopy, real-time cellular analyses, colony formation and tumor spheroid models we show that SOD1 silencing and inhibition (ATTM and LCS-1 treatments), or the induction of reactive oxygen species (2ME2 treatment) induces selective killing within BLM- and CHEK2-deficient cells relative to controls. We further show that increases in reactive oxygen species follow SOD1 silencing and inhibition that are associated with the persistence of DNA double strand breaks, and increases in apoptosis. Collectively, these data identify SOD1 as a novel candidate drug target in BLM and CHEK2 cancer contexts, and further suggest that 2ME2, ATTM and LCS-1 are lead therapeutic compounds warranting further pre-clinical study.

Mutated Fanconi anemia pathway in non-Fanconi anemia cancers

An extremely high cancer incidence and the hypersensitivity to DNA crosslinking agents associated with Fanconi Anemia (FA) have marked it to be a unique genetic model system to study human cancer etiology and treatment, which has emerged an intense area of investigation in cancer research. However, there is limited information about the relationship between the mutated FA pathway and the cancer development or/and treatment in patients without FA. Here we analyzed the mutation rates of the seventeen FA genes in 68 DNA sequence datasets. We found that the FA pathway is frequently mutated across a variety of human cancers, with a rate mostly in the range of 15 to 35 % in human lung, brain, bladder, ovarian, breast cancers, or others. Furthermore, we found a statistically significant correlation (p < 0.05) between the mutated FA pathway and the development of human bladder cancer that we only further analyzed. Together, our study demonstrates a previously unknown fact that the mutated FA pathway frequently occurs during the development of non-FA human cancers, holding profound implications directly in advancing our understanding of human tumorigenesis as well as tumor sensitivity/resistance to crosslinking drug-relevant chemotherapy.

The BRCA1/2-directed miRNA signature predicts a good prognosis in ovarian cancer patients with wild-type BRCA1/2

Ovarian cancer patients carrying alterations (i.e., germline mutations, somatic mutations, hypermethylations and/or deletions) of BRCA1 or BRCA2 (BRCA1/2) have a better prognosis than BRCA1/2 alteration non-carriers. However, patients with wild-type BRCA1/2 may also have a favorable prognosis as a result of other mechanisms that remain poorly elucidated, such as the deregulation of miRNAs. We therefore sought to identify BRCA1/2-directed miRNA signatures that have prognostic value in ovarian cancer patients with wild-type BRCA1/2 and study how the deregulation of miRNAs impacts the prognosis of patients treated with platinum-based chemotherapy. By analyzing multidimensional datasets of ovarian cancer patients from the TCGA data portal, we identified three miRNAs (hsa-miR-146a, hsa-miR-148a and hsa-miR-545) that target BRCA1/2 and were associated with overall survival and progression-free survival in patients with wild-type BRCA1/2. By analyzing the expression profiles and Gene Ontology functional enrichment, we found that carriers of BRCA1/2 alterations and patients with miRNA deregulation shared a common mechanism, regulation of the DNA repair-related pathways, that affects the prognosis of ovarian cancer patients. Our work highlights that a proportion of patients with wild-type BRCA1/2 ovarian cancers benefit from platinum-based chemotherapy and that the patients who benefit could be predicted from BRCA1/2-directed miRNA signature.

Volasertib Versus Chemotherapy in Platinum-Resistant or -Refractory Ovarian Cancer: A Randomized Phase II Groupe des Investigateurs Nationaux pour l'Etude des Cancers de l'Ovaire Study

PURPOSE

Volasertib is a potent and selective cell-cycle kinase inhibitor that induces mitotic arrest and apoptosis by targeting Polo-like kinase. This phase II trial evaluated volasertib or single-agent chemotherapy in patients with platinum-resistant or -refractory ovarian cancer who experienced failure after treatment with two or three therapy lines.

PATIENTS AND METHODS

Patients were randomly assigned to receive either volasertib 300 mg by intravenous infusion every 3 weeks or an investigator's choice of single-agent, nonplatinum, cytotoxic chemotherapy. The primary end point was 24-week disease control rate. Secondary end points included best overall response, progression-free survival (PFS), safety, quality of life, and exploratory biomarker analyses.

RESULTS

Of the 109 patients receiving treatment, 54 received volasertib and 55 received chemotherapy; demographics were well balanced. The 24-week disease control rates for volasertib and chemotherapy were 30.6% (95% CI, 18.0% to 43.2%) and 43.1% (95% CI, 29.6% to 56.7%), respectively, with partial responses in seven (13.0%) and eight (14.5%) patients, respectively. Median PFS was 13.1 weeks and 20.6 weeks for volasertib and chemotherapy (hazard ratio, 1.01; 95% CI, 0.66 to 1.53). Six patients (11%) receiving volasertib achieved PFS fore more than 1 year, whereas no patient receiving chemotherapy achieved PFS greater than 1 year. No relationship between the expression of the biomarkers tested and their response was determined. Patients treated with volasertib experienced more grade 3 and 4 drug-related hematologic adverse events (AEs) and fewer nonhematologic AEs than did patients receiving chemotherapy. Discontinuation resulting from AEs occurred in seven (13.0%) and 15 (27.3%) patients in the volasertib and chemotherapy arms, respectively. Both arms showed similar effects on quality of life.

CONCLUSION

Single-agent volasertib showed antitumor activity in patients with ovarian cancer. AEs in patients receiving volasertib were mainly hematologic and manageable.

Hereditary ovarian cancer: not only BRCA 1 and 2 genes

More than one-fifth of ovarian tumors have hereditary susceptibility and, in about 65-85% of these cases, the genetic abnormality is a germline mutation in BRCA genes. Nevertheless, several other suppressor genes and oncogenes have been associated with hereditary ovarian cancers, including the mismatch repair (MMR) genes in Lynch syndrome, the tumor suppressor gene, TP53, in the Li-Fraumeni syndrome, and several other genes involved in the double-strand breaks repair system, such as CHEK2, RAD51, BRIP1, and PALB2. The study of genetic discriminators and deregulated pathways involved in hereditary ovarian syndromes is relevant for the future development of molecular diagnostic strategies and targeted therapeutic approaches. The recent development and implementation of next-generation sequencing technologies have provided the opportunity to simultaneously analyze multiple cancer susceptibility genes, reduce the delay and costs, and optimize the molecular diagnosis of hereditary tumors. Particularly, the identification of mutations in ovarian cancer susceptibility genes in healthy women may result in a more personalized cancer risk management with tailored clinical and radiological surveillance, chemopreventive approaches, and/or prophylactic surgeries. On the other hand, for ovarian cancer patients, the identification of mutations may provide potential targets for biologic agents and guide treatment decision-making.

Adverse Drug Events-based Tumor Stratification for Ovarian Cancer Patients Receiving Platinum Therapy

The underlying molecular mechanisms of adverse drug events (ADEs) associated with cancer therapy drugs may overlap with their antineoplastic mechanisms. In a previous study, we developed an ADE-based tumor stratification framework (known as ADEStrata) with a case study of breast cancer patients receiving aromatase inhibitors, and demonstrated that the prediction of per-patient ADE propensity simultaneously identifies high-risk patients experiencing poor outcomes. In this study, we aim to evaluate the ADEStrata framework with a different tumor type and chemotherapy class - ovarian cancer treated with platinum chemotherapeutic drugs. We identified a cohort of ovarian cancer patients receiving cisplatin (a standard platinum therapy) from The Cancer Genome Atlas (TCGA) (n=156). We demonstrated that somatic variant prioritization guided by known ADEs associated with cisplatin could be used to stratify patients treated with cisplatin and uncover tumor subtypes with different clinical outcomes.