MedicalResearch.com Interview with:
Dr. Terry Magnuson PhD
Vice Dean for ResearchDepartment of Genetics, School of Medicine
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina 27599
Medical Research: What is the background for this study? What are the main findings?
Response: Ovarian clear-cell carcinoma is a lethal form of ovarian cancer with limited therapeutic options. Recent patient-derived tumor sequencing studies support a strong genetic basis for the disease, but the roles of gene mutations in cancer causation are still unclear. We observed rapid induction of ovarian clear-cell carcinoma in mice that were genetically engineered to carry mutations in ARID1A and PIK3CA−the two most frequently mutated genes. Comparisons between human and mouse tumors uncovered a downstream role for the Interleukin-6 (IL-6) cytokine-signaling pathway in tumor progression. Thus, ARID1A and PIK3CA mutations cause ovarian clear-cell carcinoma and promote tumor cell growth by acting upon the IL-6 signaling pathway.
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MedicalResearch.com Interview with: Ben Van Calster PhD
Department of Development and Regeneration
KU Leuven, Herestraat Leuven, Belgium
MedicalResearch: What is the background for this study? What are the main findings?
Dr. Van Calster: Ovarian cancer is a very common type of cancer among women, with over 200,000 new cases per year worldwide. It is the most lethal of gynecological malignancies. Research has shown that the referral of patients with ovarian cancer to specialized gynecological oncologists in high volume centers improves survival. However, audits in Europe and the United States also show that only a minority of women with ovarian cancer are appropriately triaged to receive specialist care. In addition, different types of malignancies are not treated in the same way. Hence optimal personalized management of an ovarian tumor hinges on the detailed preoperative diagnosis of its nature. Unfortunately, current prediction models focused on the discrimination between benign and malignant tumors without further specification of the likely type of malignancy.
Various prediction models and rules have been developed to help predict whether an ovarian mass is benign or malignant. A recent systematic review meta-analysis has shown that the IOTA model LR2 and simple rules perform better than any other previous test. However none of these tests give anything other than a dichotomous outcome – i.e. cancer or non-cancer. In practice the position is more nuanced.
The ADNEX model estimates the likelihood that a tumor is benign, borderline malignant, stage I cancer, stage II-IV cancer, or secondary metastatic cancer. This model is the first that is able to differentiate between benign and these four subtypes of malignancy. To do so, ADNEX uses three clinical predictors (age, serum CA-125 level, and type of center), and six ultrasound characteristics of the tumor (maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites). The model is based on data from almost 6,000 women recruited at 24 centers in 10 countries.
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MedicalResearch.com Interview with:Sean C. Dowdy, MD, FACS
Professor and Chair, Division of Gynecologic Surgery
Vice-Chair for Research, Department of Obstetrics and Gynecology
Co-Leader, Women’s Cancer Program
Mayo Clinic College of Medicine
MedicalResearch.com: What are the main findings of the study?Dr. Dowdy: This study was a collaboration between four groups in 3 countries to determine if a genetic “signature” could predict which patients with ovarian cancer benefit from Bevacizumab (a very expensive drug with marginal benefit in patients with ovarian cancer). We hypothesized that while benefit may be marginal in a large group, patients with specific genetic changes could derive significant benefit from it. Using gene expression arrays (analyzing over 18,000 genes) we separated patients into four subgroups as described by The Cancer Genome Atlas (TCGA). We show that patients in the proliferative and mesenchymal groups had a 8-10 month improvement in outcome compared to a 3 month improvement for the other two groups (immunoreactive and differentiated).
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MedicalResearch.com Interview with:Barbara A. Cohn, Ph.D.
Director, Child Health and Development Studies
A Project of the Public Health Institute
Berkeley, CA 94709
MedicalResearch.com: What are the main findings of the study?
Women with irregular menses had a statistically significant 2.4 fold increase in risk of death due to any form ovarian cancer, and a statistically significant 3-fold increase in risk of death due to late stage serous disease. Consistent with these findings, the incidence of late stage disease at diagnosis, and late stage serous cancer was increased about 2-fold in women with irregular menses.
Irregular menses was defined as irregular cycles (variation of 10 days or more) or infrequent cycles (>35 days) or history of annovulatory cycles identified during an in-person interview with women at an average age of 26 years or mentioned in their medical records.
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MedicalResearch.com Interview with:Anil K. Sood MD
Department of Gynecologic Oncology
The University of Texas MD Anderson Cancer Center
Unit 1362, PO Box 301439, Houston, TX, 77030
MedicalResearch.com: What are the main findings of the study?Dr. Sood: For women with newly diagnosed ovarian cancer, high heart rate at diagnosis (tachycardia), venous thromboembolism (VTE) occurring after diagnosis and pulmonary hypertension post-diagnosis are independently related to reduced survival after controlling for tumor stage, grade, and extent of cytoreduction. Women with tachycardia lived an average of 4.0 years after diagnosis compared with 5.9 years for women without tachycardia, a 32% reduction in duration of survival. Patients who experienced VTE lived a median 4.1 years after diagnosis, compared with 6.4 yrs for patients who did not experience VTE.
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