BMC Genomics: Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer

Fang-Han HsuErchin SerpedinTzu-Hung HsiaoAlexander JR BishopEdward R Dougherty & Yidong Chen


Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after a few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA) research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses a large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms.

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