MOLECULAR BIOLOGY LAB

Esophageal cancer is the eighth most common cancer in the World. Majority of the cases reported worldwide are generally Esophageal squamous cell carcinoma (ESCC) and it is followed by esophageal adenocarcinoma (EAC). Overall, the incidence rates are two-fold higher in poor socioeconomic geographic regions, with the highest rates occurring in Asia. Despite advancement in therapy, the overall 5-year survival rate of esophageal cancer still remains less than 30%. ESCC is a multifactorial disease, which arises due to several genetic and environmental factors. Major risk factors for ESCC are alcohol, tobacco, vitamin deficiency, ageing and low socioeconomic status. There are also several predisposing factors for ESCC such as tylosis, lye ingestion, achalasia, and Plummer-Vinson syndrome.

Some of the commonly used markers for ESCC are squamous cell carcinoma antigen (SCC), carcinoembryonic antigen (CEA), and cytokeratin 19-fragment (CYFRA 21-1). CCND1 offers hope as a prognostic marker for lymph node metastasis, HGF as a prognostic marker, and EpCAM for an adjuvant immunotherapeutic intervention.

However, there is not even a single molecule, which can be considered as an ideal biomarker possessing characteristics like high sensitivity, specificity and higher prevalence to classify them as diagnostic markers. Lack of an ideal biomarker for early detection leaves surgical resection as the best available method for control and management of ESCC. Understanding molecular pathophysiology to study ESCC in a more comprehensive way paves a path to identify various biomarkers for determination of disease prognosis or predict the efficacy of the treatment in ESCC patients.

Several techniques including differential display analysis has recently been used to analyze ESCC gene expression profile, but this approach more closely averages the genomic view and it also has a drawback that every interesting band must be individually cloned and sequenced. Microarrays have been employed as a useful, high-throughput technology for detecting complex genetic changes in ESCC. High throughput analysis of several thousands of genes simultaneously has transformed microarray into a single powerful analytical tool. Several studies on gene expression profiling of ESCC using cDNA microarray / oligonucleotide microarray have been investigated however, none of these studies have carried out an analysis to explore gene expression profiling on a whole genome scale.

The ongoing study will enable us to explore the possibility of potential biomarkers and to better understand the molecular pathophysiology of ESCC with reference to the complete genome, which will offer better opportunities to identify diagnostic markers, therapeutic targets, or prognostic indicators for this disease. Microarray analysis from this study will possibly give us the information about up and down-regulated genes in this disease. The data generated from this study could detect genetic changes that would help subdivide this disease into subgroups with distinct molecular profiles, which would correlate with clinical profiles.