A Gene Signature Predicting for Survival in Suboptimally Debulked Patients with Ovarian Cancer

Abstract

Despite the existence of morphologically indistinguishable disease, patients with advanced ovarian tumors display a broad range of survival end points. We hypothesize that gene expression profiling can identify a prognostic signature accounting for these distinct clinical outcomes. To resolve survival-associated loci, gene expression profiling was completed for an extensive set of 185 (90 optimal/95 suboptimal) primary ovarian tumors using the Affymetrix human U133A microarray. Cox regression analysis identified probe sets associated with survival in optimally and suboptimally debulked tumor sets at a P value of <0.01. Leave-one-out cross-validation was applied to each tumor cohort and confirmed by a permutation test. External validation was conducted by applying the gene signature to a publicly available array database of expression profiles of advanced stage suboptimally debulked tumors. The prognostic signature successfully classified the tumors according to survival for suboptimally (P = 0.0179) but not optimally debulked (P = 0.144) patients. The suboptimal gene signature was validated using the independent set of tumors (odds ratio, 8.75; P = 0.0146).

Gene expression signature-based approach identifies a pro-resolving mechanism of action for histone deacetylase inhibitors

“…The selective FPR2 antagonist WRW 4 was purchased from Calbiochem, Nottingham, UK. The PKC inhibitor (PKC [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] ) and the protein phosphatase 2 inhibitor (okadaic acid) were purchased from Tocris Bioscience, Bristol, UK.…”

“…Novel approaches include the use of gene expression data for class discovery, 34 to generate prognosis predictors in cancer 35,36 and, more recently, to find 'connections' between drug-disease or drug-drug pairs using the CMap. 9 Drug repositioning strategies, which aim to identify if drugs used for one disease could be applied to another, can benefit from this new approach.…”

Identification of an ovarian clear cell carcinoma gene signature that reflects inherent disease biology and the carcinogenic processes

“…Ovarian cancer is the fifth most common form of cancer in women (Bonome et al, 2008), and it has the worst prognosis of all gynecological malignancies in the United States, Europe and Japan (Takemoto et al, 2004;Takano et al, 2006). Epithelial ovarian cancers are thought to develop from deregulation of cells within the ovarian surface epithelia and differentiate into four major histological subtypes: serous (OS), mucinous (OM), endometrioid (OE) adenocarcinomas and ovarian clear cell carcinomas (OCCCs) during malignant transformation.…”

Coordination of Nutrient Availability and Utilization by MAX- and MLX-Centered Transcription Networks

“…3) (Basso et al 2005;Detwiller et al 2005;Sanchez-Carbayo et al 2006;Tomlins et al 2007). TXNIP mRNA levels are also generally lower in (Roessler et al 2010) Ovarian serous cystadenocarcinoma (TCGA) Chronic lymphocytic leukemia (Haslinger et al 2004) Thyroid gland oncocytic adenoma (Giordano et al 2006) Ovarian carcinoma (Bonome et al 2008) Cutaneous melanoma (Talantov et al 2005) Tongue squamous cell carcinoma (Talbot et al 2005) Colon adenocarcinoma ( 1.55E-7…”