The expression pattern of 19 genes predicts the histology of endometrial carcinoma.
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ABSTRACT:
SUBMITTER: Sung CO
PROVIDER: S-EPMC4044625 | biostudies-literature | 2014 Jun
REPOSITORIES: biostudies-literature
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The expression pattern of 19 genes predicts the histology of endometrial carcinoma.
Sung Chang Ohk CO Sohn Insuk I
Scientific reports 20140604
Cancer diagnosis and classification have traditionally been based on the assessment of morphology by microscopy. However, the histological classification system is challenging and demand for genetic information is increasing in the era of targeted and personalized molecular therapy. Recently accumulated comprehensive genomic data could be used to provide a molecular cancer classification alongside the histological classification. This study identified a 19 gene signature able to classify endomet ...[more]
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Project description:Endometriosis is a chronic disease characterized by the presence of ectopic endometrial tissue outside of the uterus with mixed traits of benign and malignant pathology. In this study we analyzed in endometrial and endometriotic tissues the differential expression of a panel of genes that are involved in preservation of stemness status and consequently considered as markers of stem cell presence. The expression profiles of a panel of 13 genes (SOX2, SOX15, ERAS, SALL4, OCT4, NANOG, UTF1, DPPA2, BMI1, GDF3, ZFP42, KLF4, TCL1) were analyzed by reverse transcription-polymerase chain reaction in human endometriotic (n = 12) and endometrial samples (n = 14). The expression of SALL4 and OCT4 was further analyzed by immunohistochemical methods. Genes UTF1, TCL1, and ZFP42 showed a trend for higher frequency of expression in endometriosis than in endometrium (P < 0.05 for UTF1), whereas GDF3 showed a higher frequency of expression in endometrial samples. Immunohistochemical analysis revealed that SALL4 was expressed in endometriotic samples but not in endometrium samples, despite the expression of the corresponding mRNA in both the sample groups. This study highlights a differential expression of stemness-related genes in ectopic and eutopic endometrium and suggests a possible role of SALL4-positive cells in the pathogenesis of endometriosis.
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Project description:The majority of endometrial carcinomas are classified as Type I endometrioid endometrial carcinomas (EECs) and have a good prognosis. Type II non-endometrioid endometrial carcinomas (NEECs) have a significant worse outcome. Yet, 20 % of the EECs are associated with an unexplained poor outcome. The aim of this study was to determine if L1CAM expression, a recently reported biomarker for aggressive tumor behavior in endometrial carcinoma, was associated with clinicopathological features of EECs. A total of 103 patients diagnosed as EEC at the Radboud University Medical Centre, based on the pathology report were selected. L1CAM status of these tumors was determined, and histologic slides were reviewed by two expert pathologists. L1CAM-positivity was observed in 17 % (18/103). Review of the diagnostic slides revealed that 11 out of these 18 L1CAM-positive tumors (61 %) contained a serous- or mixed carcinoma component that was not initially mentioned in the pathology report. L1CAM-expression was associated with advanced age, poor tumor grade, and lymphovascular space invasion. A worse five year progression free survival rate was observed for patients with L1CAM-positive tumors (55.6 % for the L1CAM-positive group, compared to 83.3 % for the L1CAM-negative group P = 0.01). L1CAM expression carries prognostic value for histologically classified EEC and supports the identification of tumors with a NEEC component.
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Project description:PURPOSE:The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histologic subtypes and predict survival for non-small cell lung cancer. EXPERIMENTAL DESIGN:We analyzed miR expression in 165 adenocarcinoma and 125 squamous cell carcinoma (SQ) tissue samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t tests and F tests and accounted for multiple testing using global permutation tests. We assessed the association of miR expression with tobacco smoking using Spearman correlation coefficients and linear regression models, and with clinical outcome using log-rank tests, Cox proportional hazards, and survival risk prediction models, accounting for demographic and tumor characteristics. RESULTS:MiR expression profiles strongly differed between adenocarcinoma and SQ (P(global) < 0.0001), particularly in the early stages, and included miRs located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Most miRs, including all members of the let-7 family, were downregulated in SQ. Major findings were confirmed by quantitative real time-polymerase chain reaction (qRT-PCR) in EAGLE samples and in an independent set of lung cancer cases. In SQ, the low expression of miRs that are downregulated in the histology comparison was associated with 1.2- to 3.6-fold increased mortality risk. A five-miR signature significantly predicted survival for SQ. CONCLUSIONS:We identified a miR expression profile that strongly differentiated adenocarcinoma from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches.
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Project description:Abstract. Background. Treatment for lung adenocarcinoma (AD) and squamous cell carcinoma (SQ) is similar and shows comparable poor efficacy. We investigated whether microRNA (miR) expression profiles can differentiate histological subtypes, predict survival, and suggest histology-specific targets for treatment. Methods. We analyzed miR expression in 165 AD and 125 SQ tissue samples from the Environmental And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t-tests and F-tests and accounted for multiple testing using global permutation tests. We categorized miR-targeted genes using Gene Ontology. We assessed the association of miR expression with clinical outcome using log-rank tests, Cox proportional hazards and survival risk prediction models, accounting for demographic and tumor characteristics. Findings. MiR expression profiles strongly differed between AD and SQ (global p<0.0001), particularly in the early stages. All members of the let-7 family and other oncosuppressor miRs were down-regulated in SQ, while oncomiRs like miR-21 were up-regulated in AD. The miRs with the strongest expression differences are located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Major findings were confirmed by QRT-PCR in EAGLE samples and in an independent cohort. In SQ, low expression of miRs down-regulated in the histology comparison was associated with 1.2 to 3.6-fold increased mortality risk. A 5-miR signature significantly predicted survival for SQ. Interpretation. We identified a miR expression profile that strongly differentiated AD from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches.
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