[1901] microRNA Profiling in Lung Cancer Diagnosis and Staging.

Charalambos C Solomides, Barry Evans, Peng Li, Vipul Kumar, Rajanikanth Vadigepalli, Stephen C Peiper, Zixuan Wang. Thomas Jefferson University, Philadelphia, PA

Background: Carcinoma of the lung is the leading cause of death among cancers worldwide. With the advent of therapies that have selective efficacy between squamous cell carcinoma (SCC) and adenocarcinoma (AC), the distinction between these two types is critical. Although immunohistochemical markers are used, there are still cases difficult to classify. Different cell types have distinct microRNA (miRNA) expression profiles. Since miRNA can be efficiently extracted from formalin-fixed, paraffin-embedded (FFPE) tissues, we determine the ability of miRNA profiling to distinguish SCC from AC and to classify poorly differentiated variants.
Design: De-identified cases (n=12) were selected from the surgical pathology archive. FFPE blocks for analysis included AC (n=5), SCC (n=4), normal lung from areas adjacent to tumors (n=4), small cell carcinoma (n=1), and two poorly differentiated specimens. Total RNA was extracted from FFPE using Recover All total nucleic acid extraction kit (Ambion). RNA was labeled and hybridized to the microarray according to the manufacturer's procedure. The median of the log2 transformed raw signal intensity data was processed through an invariant normalization workflow to identify “invariant” miRNAs that have similar expression across the samples and “hypervariables” with expression that varies significantly across the samples. The “invariant” miRNA were used to normalize data across all of the samples using quantile normalization and this yielded 34 microRNAs that are differentially expressed.
Results: A panel of 4 miRNAs was identified for differentiating SCC from AC. Expression of miR205 was dramatically increased and miR100, miR150, and miR26b expression was reduced only in SCC but not in AC. Another panel of 16 miRNAs that differentially expressed in normal or cancer specimens were identified Thirteen were significantly down-regulated in lung cancers compared to the corresponding normal lung tissues (p value: 0.0004∼0.058). Expression of 3 miRNAs (miR21, miR210 and miR224) were 3-5-fold increased in the tumor tissues compared to normal lung tissues (p value: 0.0001∼0.1). The altered gene expression profiles correlated with tumor stage independent of cell type.
Conclusions: We identified a panel of miRNAs that are differentially expressed in SCC and AC and another independent panel of miRNAs that correlates with cancer stage. Both panels will be further validated with large cohorts of tumor samples using real-time PCR. This approach shows significant potential for clinical utility in the diagnosis and prognosis of lung cancer.
Category: Special Category - Pan-genomic/Pan-proteomic approaches to Cancer

Monday, February 28, 2011 1:00 PM

Poster Session II # 247, Monday Afternoon

 

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