The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer

The Progression and Prospects of the Gene Expression Profiling in Ovarian Epithelial Cancer

Ovarian cancer is one of the most common cancers with a high mortality rate among females worldwide. The understanding of the pathogenesis of the disease is highly important to provide personalized therapy to the patients. Ovarian cancer is as heterogeneous as colon and breast cancer which makes it difficult to treat. The development of gene signature is the only hope in providing targeted therapy to improve the survival of ovarian cancer patients. Malignant epithelial carcinomas are the most common cancers of the ovary with different histological and molecular subtypes and clinical behavior. The development of precursor lesions of ovarian carcinoma in the tubes and endometrium has provided a new dimension to the origin of ovarian cancers. The clinical utility of various gene signatures may not be logical unless validated. Validated gene signatures can aid the clinician in deciding the appropriate line of treatment.

Residual ANTXR1+ myofibroblasts after chemotherapy inhibit anti-tumor immunity via YAP1 signaling pathway

Although cancer-associated fibroblast (CAF) heterogeneity is well-established, the impact of chemotherapy on CAF populations remains poorly understood. Here we address this question in high-grade serous ovarian cancer (HGSOC), in which we previously identified 4 CAF populations. While the global content in stroma increases in HGSOC after chemotherapy, the proportion of FAP+ CAF (also called CAF-S1) decreases. Still, maintenance of high residual CAF-S1 content after chemotherapy is associated with reduced CD8+ T lymphocyte density and poor patient prognosis, emphasizing the importance of CAF-S1 reduction upon treatment. Single cell analysis, spatial transcriptomics and immunohistochemistry reveal that the content in the ECM-producing ANTXR1+ CAF-S1 cluster (ECM-myCAF) is the most affected by chemotherapy. Moreover, functional assays demonstrate that ECM-myCAF isolated from HGSOC reduce CD8+ T-cell cytotoxicity through a Yes Associated Protein 1 (YAP1)-dependent mechanism. Thus, efficient inhibition after treatment of YAP1-signaling pathway in the ECM-myCAF cluster could enhance CD8+ T-cell cytotoxicity. Altogether, these data pave the way for therapy targeting YAP1 in ECM-myCAF in HGSOC.

A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles

Even after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P  =  4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P  =  9.2E-06), respectively. GO analysis of ODFSP's 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP's signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

Recent Advances in Ovarian Cancer: Therapeutic Strategies, Potential Biomarkers, and Technological Improvements

Aggressive and recurrent gynecological cancers are associated with worse prognosis and a lack of effective therapeutic response. Ovarian cancer (OC) patients are often diagnosed in advanced stages, when drug resistance, angiogenesis, relapse, and metastasis impact survival outcomes. Currently, surgical debulking, radiotherapy, and/or chemotherapy remain the mainstream treatment modalities; however, patients suffer unwanted side effects and drug resistance in the absence of targeted therapies. Hence, it is urgent to decipher the complex disease biology and identify potential biomarkers, which could greatly contribute to making an early diagnosis or predicting the response to specific therapies. This review aims to critically discuss the current therapeutic strategies for OC, novel drug-delivery systems, and potential biomarkers in the context of genetics and molecular research. It emphasizes how the understanding of disease biology is related to the advancement of technology, enabling the exploration of novel biomarkers that may be able to provide more accurate diagnosis and prognosis, which would effectively translate into targeted therapies, ultimately improving patients’ overall survival and quality of life.

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

BACKGROUND

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

METHODS

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

CONCLUSION

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

The role of the tumor primary chemosensitivity relative to the success of the medical-surgical management in patients with advanced ovarian carcinomas

In patients with advanced ovarian carcinomas, the first-line treatment has historically relied on debulking surgery and platinum-based chemotherapy. If the major therapeutic/prognostic role of the surgery part is well understood, and integrated in disease-management algorithms, the impact of chemotherapy efficacy has been insufficiently addressed. This review describes the main indicators of the chemosensitivity reported in the literature (pathological response score & biomarkers; genomic alterations; DNA scars; imaging; and circulating tumor markers), and investigates the respective roles of the debulking surgery and tumor primary chemosensitivity relative to the success of the comprehensive medical-surgical treatment. The tumor primary chemosensitivity exhibits a major independent prognostic impact on the feasibility of complete interval debulking surgery after neoadjuvant chemotherapy, risk of subsequent platinum-resistant relapse, efficacy of subsequent maintenance therapies with bevacizumab or PARP inhibitors, progression-free survival, overall and long-term survival. While both the completeness of the surgery and the tumor primary chemosensitivity are undoubtedly major prognostic factors, the impact of the surgery may differ according to the primary chemosensitivity. This assumption raises a potential new concept: in patients with advanced ovarian carcinomas, the maximum tumor debulking should ideally be both biological (induced by systemic treatments) and physical (induced by surgery) for maximizing patient survival. Besides BRCA and HRD biomarkers, future trials and algorithms may integrate indicator(s) of the tumor primary chemosensitivity for guiding more subtly the surgical and medical management in first-line setting. Moreover, such a parameter would help in the development of novel approaches meant to reverse the resistance to chemotherapy and PARP inhibitors.

Gene expression profile association with poor prognosis in epithelial ovarian cancer patients

Ovarian cancer (OC) is the eighth most common type of cancer for women worldwide. The current diagnostic and prognostic routine available for OC management either lack specificity or are very costly. Gene expression profiling has shown to be a very effective tool in exploring new molecular markers for patients with OC, although association of such markers with patient survival and clinical outcome is still elusive. Here, we performed gene expression profiling of different subtypes of OC to evaluate its association with patient overall survival (OS) and aggressive forms of the disease. By global mRNA microarray profiling in a total of 196 epithelial OC patients (161 serous, 15 endometrioid, 11 mucinous, and 9 clear cell carcinomas), we found four candidates-HSPA1A, CD99, RAB3A and POM121L9P, which associated with OS and poor clinicopathological features. The overexpression of all combined was correlated with shorter OS and progression-free survival (PFS). Furthermore, the combination of at least two markers were further associated with advanced grade, chemotherapy resistance, and progressive disease. These results indicate that a panel comprised of a few predictors that associates with a more aggressive form of OC may be clinically relevant, presenting a better performance than one marker alone.

A novel signature predicts recurrence risk and therapeutic response in breast cancer patients

Acetylserotonin O-methyltransferase (ASMT) is a key enzyme in the synthesis of melatonin. Although melatonin has been shown to exhibit anticancer activity and prevents endocrine resistance in breast cancer, the role of ASMT in breast cancer progression remains unclear. In this retrospective study, we analyzed gene expression profiles in 27 data sets on 7244 patients from 11 countries. We found that ASMT expression was significantly reduced in breast cancer tumors relative to healthy tissue. Among breast cancer patients, those with higher levels of ASMT expression had better relapse-free survival outcomes and longer metastasis-free survival times. Following treatment with tamoxifen, patients with greater ASMT expression experienced longer periods before relapse or distance recurrence. Motivated by these results, we devised an ASMT gene signature that can correctly identify low-risk cases with a sensitivity and specificity of 0.997 and 0.916, respectively. This signature was robustly validated using 23 independent breast cancer mRNA array data sets from different platforms (consisting of 5800 patients) and an RNAseq data set from TCGA (comprising 1096 patients). Intriguingly, patients who are classified as high-risk by the signature benefit from adjuvant chemotherapy, and those with grade II tumors who are classified as low-risk exhibit improved overall survival and distance relapse-free outcomes following endocrine therapy. Together, our findings more clearly elucidate the roles of ASMT, provide strategies for improving the efficacy of tamoxifen treatment and help to identify those patients who may maximally benefit from adjuvant or endocrine therapies.

Stiffness increases with myofibroblast content and collagen density in mesenchymal high grade serous ovarian cancer

Women diagnosed with high-grade serous ovarian cancers (HGSOC) are still likely to exhibit a bad prognosis, particularly when suffering from HGSOC of the Mesenchymal molecular subtype (50% cases). These tumors show a desmoplastic reaction with accumulation of extracellular matrix proteins and high content of cancer-associated fibroblasts. Using patient-derived xenograft mouse models of Mesenchymal and Non-Mesenchymal HGSOC, we show here that HGSOC exhibit distinct stiffness depending on their molecular subtype. Indeed, tumor stiffness strongly correlates with tumor growth in Mesenchymal HGSOC, while Non-Mesenchymal tumors remain soft. Moreover, we observe that tumor stiffening is associated with high stromal content, collagen network remodeling, and MAPK/MEK pathway activation. Furthermore, tumor stiffness accompanies a glycolytic metabolic switch in the epithelial compartment, as expected based on Warburg's effect, but also in stromal cells. This effect is restricted to the central part of stiff Mesenchymal tumors. Indeed, stiff Mesenchymal tumors remain softer at the periphery than at the core, with stromal cells secreting high levels of collagens and showing an OXPHOS metabolism. Thus, our study suggests that tumor stiffness could be at the crossroad of three major processes, i.e. matrix remodeling, MEK activation and stromal metabolic switch that might explain at least in part Mesenchymal HGSOC aggressiveness.

Tsukushi is a novel prognostic biomarker and correlates with tumor-infiltrating B cells in non-small cell lung cancer

A recent study has reported that tsukushi (TSKU) may be related to the development of lung cancer. However, few studies focused on if TSKU associated with the prognosis and immune infiltration cells in non-small cell lung cancer (NSCLC). The effect of TSKU expression on prognosis with NSCLC was analyzed in the PrognoScan database and validated in The Cancer Genome Atlas. The composition of tumor infiltrating cells was quantified by methylation and expression data. We combined levels of tumor infiltrating cells with TSKU to evaluate the survival of patients. The analysis of a cohort (GSE31210, N=204) of lung cancer patients demonstrated that high TSKU expression was strongly associated with poor overall survival (P =1.90E-05). The combination of high TSKU expression and low infiltration B cells identified a subtype of patients with poor survival in NSCLC. Besides, the proportion of B cells in NSCLC patients with TSKU hypermethylation were higher than those patients with TSKU hypomethylation (P <0.001). Overall, high TSKU expression combined with low infiltration of B cells may associate with a poor prognosis of NSCLC patients. TSKU might be a potential prognostic biomarker involved in tumor immune infiltration in NSCLC.

The R-enantiomer of ketorolac reduces ovarian cancer tumor burden in vivo

BACKGROUND

Rho-family GTPases, including Ras-related C3 botulinum toxin substrate 1 (Rac1) and cell division control protein 42 (Cdc42), are important modulators of cancer-relevant cell functions and are viewed as promising therapeutic targets. Based on high-throughput screening and cheminformatics we identified the R-enantiomer of an FDA-approved drug (ketorolac) as an inhibitor of Rac1 and Cdc42. The corresponding S-enantiomer is a non-steroidal anti-inflammatory drug (NSAID) with selective activity against cyclooxygenases. We reported previously that R-ketorolac, but not the S-enantiomer, inhibited Rac1 and Cdc42-dependent downstream signaling, growth factor stimulated actin cytoskeleton rearrangements, cell adhesion, migration and invasion in ovarian cancer cell lines and patient-derived tumor cells.

METHODS

In this study we treated mice with R-ketorolac and measured engraftment of tumor cells to the omentum, tumor burden, and target GTPase activity. In order to gain insights into the actions of R-ketorolac, we also performed global RNA-sequencing (RNA-seq) analysis on tumor samples.

RESULTS

Treatment of mice with R-ketorolac decreased omental engraftment of ovarian tumor cells at 18 h post tumor cell injection and tumor burden after 2 weeks of tumor growth. R-ketorolac treatment inhibited tumor Rac1 and Cdc42 activity with little impact on mRNA or protein expression of these GTPase targets. RNA-seq analysis revealed that R-ketorolac decreased expression of genes in the HIF-1 signaling pathway. R-ketorolac treatment also reduced expression of additional genes associated with poor prognosis in ovarian cancer.

CONCLUSION

These findings suggest that R-ketorolac may represent a novel therapeutic approach for ovarian cancer based on its pharmacologic activity as a Rac1 and Cdc42 inhibitor. R-ketorolac modulates relevant pathways and genes associated with disease progression and worse outcome.

Prognostic value of radiological recurrence patterns in ovarian cancer

OBJECTIVE

To study the prognostic value of CT assessed recurrence patterns on survival outcomes in women with epithelial ovarian cancer.

METHODS

CT scans were systematically re-evaluated on predefined anatomical sites for the presence of tumor in all 89 patients diagnosed with epithelial ovarian cancer between January 2008 and December 2013 who underwent cytoreductive surgery at our institution and developed a recurrence. A Cox proportional hazard analysis was used to test the effect of recurrence patterns on survival.

RESULTS

The median survival time for patients grouped as predominantly intraperitoneal (n = 62), hematogenous (n = 13) or lymphatic (n = 14) recurrence was 25.8 (95% CI 18.4-33.2), 27.6 (95% CI 18.5-36.6) and 52.9 months (95% CI 42.1-63.7), respectively. Univariate Cox regression analysis identified the following prognostic factors: lymphatic recurrence pattern (HR 0.42, 95% CI 0.21-0.85), ascites at diagnosis (HR 2.35, 95% CI 1.46-3.79), residual tumor at initial surgery (HR 2.16, 95% CI 1.36-3.44) and FIGO stage (I-IIIB: HR 0.59, 95% CI 0.33-1.06). The median time to recurrence was 19.5 month for patients after complete debulking surgery, 13.1 months for patients with residual disease ≤1 cm and 8.2 months for patients with residual disease >1 cm after surgery (P < 0.001). No differences in recurrence patterns between patients with complete and incomplete surgery were found.

CONCLUSIONS

Prolonged survival rates were found in ovarian cancer patients with a predominantly lymphatic recurrence compared to patients with a predominantly peritoneal or hematogenous recurrence. Completeness of surgery was associated with time to recurrence. Classification of recurrence patterns can help counsel patients on their prognosis at the time of recurrence.

Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study

BACKGROUND

Clustering of gene expression data is widely used to identify novel subtypes of cancer. Plenty of clustering approaches have been proposed, but there is a lack of knowledge regarding their relative merits and how data characteristics influence the performance. We evaluate how cluster analysis choices affect the performance by studying four publicly available human cancer data sets: breast, brain, kidney and stomach cancer. In particular, we focus on how the sample size, distribution of subtypes and sample heterogeneity affect the performance.

RESULTS

In general, increasing the sample size had limited effect on the clustering performance, e.g. for the breast cancer data similar performance was obtained for n = 40 as for n = 330. The relative distribution of the subtypes had a noticeable effect on the ability to identify the disease subtypes and data with disproportionate cluster sizes turned out to be difficult to cluster. Both the choice of clustering method and selection method affected the ability to identify the subtypes, but the relative performance varied between data sets, making it difficult to rank the approaches. For some data sets, the performance was substantially higher when the clustering was based on data from only one sex compared to data from a mixed population. This suggests that homogeneous data are easier to cluster than heterogeneous data and that clustering males and females individually may be beneficial and increase the chance to detect novel subtypes. It was also observed that the performance often differed substantially between females and males.

CONCLUSIONS

The number of samples seems to have a limited effect on the performance while the heterogeneity, at least with respect to sex, is important for the performance. Hence, by analyzing the genders separately, the possible loss caused by having fewer samples could be outweighed by the benefit of a more homogeneous data.

Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy

Heterogeneity in chemotherapeutic response is directly associated with prognosis and disease recurrence in patients with ovarian cancer (OvCa). Despite the significant clinical need, a credible gene signature for predicting response to platinum-based chemotherapy and for guiding the selection of personalized chemotherapy regimens has not yet been identified. The present study used an integrated approach involving both OvCa tumors and cell lines to identify an individualized gene expression signature, denoted as IndividCRS, consisting of 16 robust chemotherapy-responsive genes for predicting intrinsic or acquired chemotherapy response in the meta-discovery dataset. The robust performance of this signature was subsequently validated in 25 independent tumor datasets comprising 2215 patients and one independent cell line dataset, across different technical platforms. The IndividCRS was significantly correlated with the response to platinum therapy and predicted the improved outcome. Moreover, the IndividCRS correlated with homologous recombination deficiency (HRD) and was also capable of discriminating HR-deficient tumors with or without platinum-sensitivity for guiding HRD-targeted clinical trials. Our results reveal the universality and simplicity of the IndividCRS as a promising individualized genomic tool to rapidly monitor response to chemotherapy and predict the outcome of patients with OvCa.

Gene Expression Indicates Altered Immune Modulation and Signaling Pathway Activation in Ovarian Cancer Patients Resistant to Topotecan

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological malignancies. Topotecan remains an essential tool in second-line therapy; even so, most patients develop resistance within a short period of time. We aimed to identify biomarkers of topotecan resistance by using gene expression signatures derived from patient specimens at surgery and available subsequent responses to therapy. Gene expression was collected for 1436 patients and 10,103 genes. Based on disease progression, patients were categorized as responders/nonresponders depending on their progression free survival (PFS) state at 9, 12, 15 and 18 months after surgery. For each gene, the median expression was compared between responders and nonresponders for two treatment regimens (chemotherapy including/excluding topotecan) with Mann-Whitney U test at each of the four different PFS cutoffs. Statistical significance was accepted in the case of p < 0.05 with a fold change (FC) ≥ 1.44. Four genes (EPB41L2, HLA-DQB1, LTF and SFRP1) were consistently overexpressed across multiple PFS cutoff times in initial tumor samples of patients with disease progression following topotecan treatment. A common theme linked to topotecan resistance was altered immune modulation. Genes associated with disease progression after systemic chemotherapy emphasize the role of the initial organization of the tumor microenvironment in therapy resistance. Our results uncover biomarkers with potential utility for patient stratification.

Comparative genomic analysis of collagen gene diversity

Collagen gene family, comprising 30% of the total protein mass in mammals, is the major part of extracellular matrix. To understand the complexity of collagen gene family, detailed sequence, phylogenetic and synteny analyses of 44 collagen genes were performed. According to sequence analysis results, Fibril-associated collagen with interrupted triple helices (FACITs) were identified as the most recently evolved vertebrate-specific collagens while Fibril-forming collagens and Collagen VI, VII, XXVI, and XXVIII were the most ancient collagens, originating at the time of choanoflagellates. Network-forming collagens were entirely conserved from arthopods to homo sapiens, except one gene loss event. Of note, bird specific gene dispensability of COL1A1, COL3A1, COL5A3 and COL11A2 genes was observed in Fibril-forming collagens. According to phylogenetic analysis, gene duplications in collagen family occurred at variable time points during invertebrate to vertebrate evolution. However, majority of gene duplications in FACITs and network-forming collagens occurred at fish time point, suggesting large scale duplications at the root of vertebrate lineage. Lastly, synteny analysis identified 12 conserved blocks containing 27 collagen genes in vertebrate species. Interestingly, dysregulation of seven conserved blocks including block1 (COL11A1), block3 (COL3A1, COL5A2), block5 (COL6A5, COL6A6), block7 (COL1A2), block9 (COL4A1, COL4A2), block11 (COL6A1, COL6A2, COL18A1) and block12 (COL4A5, COL4A6) were also reported in different diseases including cancer. The current study revealed many critical insights into sequence, structural and functional diversity of collagen gene family. In future, by using this information we may be able to establish the clinical and pathological relevance of these conserved collagen blocks in different diseases.

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

RAD-ical New Insights into RAD51 Regulation

The accurate repair of DNA is critical for genome stability and cancer prevention. DNA double-strand breaks are one of the most toxic lesions; however, they can be repaired using homologous recombination. Homologous recombination is a high-fidelity DNA repair pathway that uses a homologous template for repair. One central HR step is RAD51 nucleoprotein filament formation on the single-stranded DNA ends, which is a step required for the homology search and strand invasion steps of HR. RAD51 filament formation is tightly controlled by many positive and negative regulators, which are collectively termed the RAD51 mediators. The RAD51 mediators function to nucleate, elongate, stabilize, and disassemble RAD51 during repair. In model organisms, RAD51 paralogs are RAD51 mediator proteins that structurally resemble RAD51 and promote its HR activity. New functions for the RAD51 paralogs during replication and in RAD51 filament flexibility have recently been uncovered. Mutations in the human RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, XRCC3, and SWSAP1) are found in a subset of breast and ovarian cancers. Despite their discovery three decades ago, few advances have been made in understanding the function of the human RAD51 paralogs. Here, we discuss the current perspective on the in vivo and in vitro function of the RAD51 paralogs, and their relationship with cancer in vertebrate models.

Imaging Mass Spectrometry Reveals Crosstalk between the Fallopian Tube and the Ovary that Drives Primary Metastasis of Ovarian Cancer

High grade serous ovarian cancer (HGSOC) is the fifth leading cause of cancer deaths among women. New evidence suggests that HGSOC arises in the fallopian tube and then colonizes the ovary before spreading into the peritoneal space. Therefore, due to the proximity of this metastasis, an experimental design was optimized using imaging mass spectrometry to capture the spatial composition of small molecules uniquely expressed when fallopian-tube-derived tumor cells were grown in the microenvironment of the ovary as a model of primary metastasis. The observed mass-to-charge ratios (m/z's) that were induced specifically in coculture represent small molecules that may contribute to the metastasis of HGSOC selectively to the ovary. Human fallopian tube epithelial HGSOC and tumorigenic murine oviductal epithelial cells, but not normal cell types, repeatedly induced a signal from the ovary at m/z 170. This signal was identified as norepinephrine, which was confirmed to stimulate invasion of ovarian cancer cells lacking wild-type p53. These molecules may reveal pathways that contribute to metastasis and biological targets for therapeutic intervention to block ovarian metastasis of fallopian-tube-derived HGSOC. The developed mass spectrometry method can be adapted to other mammalian-based model systems for investigation of untargeted metabolomics that facilitate metastasis.

Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells

Four main histological subtypes of ovarian cancer exist: serous (the most frequent), endometrioid, mucinous and clear cell; in each subtype, low and high grade. The large majority of ovarian cancers are diagnosed as high-grade serous ovarian cancers (HGS-OvCas). TP53 is the most frequently mutated gene in HGS-OvCas; about 50% of these tumors displayed defective homologous recombination due to germline and somatic BRCA mutations, epigenetic inactivation of BRCA and abnormalities of DNA repair genes; somatic copy number alterations are frequent in these tumors and some of them are associated with prognosis; defective NOTCH, RAS/MEK, PI3K and FOXM1 pathway signaling is frequent. Other histological subtypes were characterized by a different mutational spectrum: LGS-OvCas have increased frequency of BRAF and RAS mutations; mucinous cancers have mutation in ARID1A, PIK3CA, PTEN, CTNNB1 and RAS. Intensive research was focused to characterize ovarian cancer stem cells, based on positivity for some markers, including CD133, CD44, CD117, CD24, EpCAM, LY6A, ALDH1. Ovarian cancer cells have an intrinsic plasticity, thus explaining that in a single tumor more than one cell subpopulation, may exhibit tumor-initiating capacity. The improvements in our understanding of the molecular and cellular basis of ovarian cancers should lead to more efficacious treatments.