Literature DB >> 33686173

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

Douglas V N P Oliveira1, Kira P Prahm1, Ib J Christensen1, Anker Hansen2, Claus K Høgdall3, Estrid V Høgdall4.   

Abstract

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.

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Year:  2021        PMID: 33686173      PMCID: PMC7940404          DOI: 10.1038/s41598-021-84953-9

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  52 in total

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-12-23       Impact factor: 4.254

9.  Clinical Interest of Combining Transcriptomic and Genomic Signatures in High-Grade Serous Ovarian Cancer.

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10.  Perioperative changes in serum CA125 levels: a prognostic factor for disease-specific survival in patients with ovarian cancer.

Authors:  Nienke Zwakman; Rafli van de Laar; Toon Van Gorp; Petra L M Zusterzeel; Marc P M L Snijders; Isabel Ferreira; Leon F A G Massuger; Roy F P M Kruitwagen
Journal:  J Gynecol Oncol       Date:  2016-09-12       Impact factor: 4.401

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Review 3.  Progesterone Receptor Membrane Component (PGRMC)1 and PGRMC2 and Their Roles in Ovarian and Endometrial Cancer.

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4.  Performance Analysis of Ovarian Cancer Detection and Classification for Microarray Gene Data.

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5.  Identification of New Molecular Biomarkers in Ovarian Cancer Using the Gene Expression Profile.

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Journal:  J Clin Med       Date:  2022-07-04       Impact factor: 4.964

Review 6.  The Therapeutic Potential of Common Herbal and Nano-Based Herbal Formulations against Ovarian Cancer: New Insight into the Current Evidence.

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