Clinicopathological predictors of chemoresponsiveness in epithelial ovarian cancer: a preliminary institutional study

Objective: One-third of women with epithelial ovarian cancer are resistant to standard platinum-based chemotherapy, and insufficient data exist in predicting response to chemotherapy. We describe the clinical and pathological factors of patients with complete and incomplete response to treatment. Method: In this retrospective study, data was reviewed from 75 medical charts of 243 patients with primary epithelial ovarian cancers as a preliminary study. All patients underwent chemotherapy and cytoreductive surgery for primary disease. Fifty-six patients had complete response (CR) to chemotherapy and 19 had incomplete response (IR). Fifty-eight and 17 patients had optimal and suboptimal cytoreductive surgery, respectively. Clinical and pathological factors were compared in patients with complete and incomplete response to treatment, and optimal and suboptimal surgery. Overall survival (OS), cancer-specific survival (CSS), and time to recurrence (TTR) were estimated using the Kaplan-Meier method for patient groups. Results: The majority of patients in both the CR and IR groups were diagnosed at advanced stage ovarian cancer. The CR group had significantly lower preoperative CA125 and was more likely to have optimal chemotherapy. The CR group was also more likely to have lymph nodes removed during cytoreductive surgery. A significantly lower percentage of CR patients died from the disease and had statistically longer disease free survival. Patients who underwent suboptimal surgery had significantly shorter survival, but no difference existed in the time until recurrence between patients with optimal and suboptimal surgery. OS, CSS, and TTR were significantly increased in the CR group and in patients that had optimal surgery. Conclusion: Complete response during treatment and optimal surgery significantly increases OS, CSS, and TTR. Preoperative CA125 and lymph node removal during surgery may be predictive of complete treatment response

Single incision laparo-endoscopic surgery (SILS) is comparable with robotic surgery at a tertiary care center for the management of gynecologic oncology patients

A shift toward minimally invasive surgical techniques has been implemented in the surgical management of gynecologic oncology patients. Over the course of 18 months, we have established a single incision laparo-endoscopic surgery program (SILS), and incorporated it in the management of our patients. We sought to assess the operative and postoperative outcomes of these patients in relation to patients who underwent robotic surgery during that same time period at our institution

A predictive model for serous epithelial ovarian cancer chemo-response using clinical characteristics

One of the prognostic factors most highly associated with ovarian cancer survival is response to initial chemotherapy. Current prediction models of chemo-response built with comprehensive molecular datasets, like The Cancer Genome Atlas (TCGA), could be improved by including clinical and outcomes data designed to study response to treatment. The objective of this study was to create a prediction model of ovarian cancer chemo-response using clinical-pathological features, and to compare its performance with a similar TCGA clinical model

Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes

The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue. Methods: In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform. Results: The prediction model with SNV had an AUC of 1.00 (95% CI 1.00-1.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances. Conclusions: Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage

Methylation Signature Implicated in Immuno-Suppressive Activities in Tubo-Ovarian High-Grade Serous Carcinoma

BACKGROUND: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. METHODS: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. RESULTS: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10-2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17-3.81; P = 2.2 × 10-13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66-2.95; P = 4.1 × 10-8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10-7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10-4) in covariate-adjusted analysis. CONCLUSIONS: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. IMPACT: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-β (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025–51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB

Detection of Somatic Mutations by High-Resolution DNA Melting (HRM) Analysis in Multiple Cancers

Identification of somatic mutations in cancer is a major goal for understanding and monitoring the events related to cancer initiation and progression. High resolution melting (HRM) curve analysis represents a fast, post-PCR high-throughput method for scanning somatic sequence alterations in target genes. The aim of this study was to assess the sensitivity and specificity of HRM analysis for tumor mutation screening in a range of tumor samples, which included 216 frozen pediatric small rounded blue-cell tumors as well as 180 paraffin-embedded tumors from breast, endometrial and ovarian cancers (60 of each). HRM analysis was performed in exons of the following candidate genes known to harbor established commonly observed mutations: PIK3CA, ERBB2, KRAS, TP53, EGFR, BRAF, GATA3, and FGFR3. Bi-directional sequencing analysis was used to determine the accuracy of the HRM analysis. For the 39 mutations observed in frozen samples, the sensitivity and specificity of HRM analysis were 97% and 87%, respectively. There were 67 mutation/variants in the paraffin-embedded samples, and the sensitivity and specificity for the HRM analysis were 88% and 80%, respectively. Paraffin-embedded samples require higher quantity of purified DNA for high performance. In summary, HRM analysis is a promising moderate-throughput screening test for mutations among known candidate genomic regions. Although the overall accuracy appears to be better in frozen specimens, somatic alterations were detected in DNA extracted from paraffin-embedded samples

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