High expression of ID family and IGJ genes signature as predictor of low induction treatment response and worst survival in adult Hispanic patients with B-acute lymphoblastic leukemia.

BACKGROUND: B-Acute lymphoblastic leukemia (B-ALL) represents a hematologic malignancy with poor clinical outcome and low survival rates in adult patients. Remission rates in Hispanic population are almost 30% lower and Overall Survival (OS) nearly two years inferior than those reported in other ethnic groups. Only 61% of Colombian adult patients with ALL achieve complete remission (CR), median overall survival is 11.3 months and event-free survival (EFS) is 7.34 months. Identification of prognostic factors is crucial for the application of proper treatment strategies and subsequently for successful outcome. Our goal was to identify a gene expression signature that might correlate with response to therapy and evaluate the utility of these as prognostic tool in hispanic patients. METHODS: We included 43 adult patients newly diagnosed with B-ALL. We used microarray analysis in order to identify genes that distinguish poor from good response to treatment using differential gene expression analysis. The expression profile was validated by real-time PCR (RT-PCT). RESULTS: We identified 442 differentially expressed genes between responders and non-responders to induction treatment. Hierarchical analysis according to the expression of a 7-gene signature revealed 2 subsets of patients that differed in their clinical characteristics and outcome. CONCLUSIONS: Our study suggests that response to induction treatment and clinical outcome of Hispanic patients can be predicted from the onset of the disease and that gene expression profiles can be used to stratify patient risk adequately and accurately. The present study represents the first that shows the gene expression profiling of B-ALL Colombian adults and its relevance for stratification in the early course of disease.

EGF receptor in lung cancer: a successful story of targeted therapy.

Lung cancer research has incorporated molecular medicine into the management of this disease during the last 5 years. Several novel tumorigenesis pathways associated with lung cancer development and proliferation have been discovered and further developed as targets. The idea behind this is to deliver individualized therapy for each patient based on his/her tumor phenotype, which may involve the overexpression or lack of certain proteins, receptors, mutations and other factors. To date, many of these characteristics have been shown to have a potential role as prognostic or predictive biomarkers, with most of the available data being obtained from retrospective analyses, various laboratory platforms, and data sets used for comparison. However, well-designed prospective randomized clinical trials are underway to validate the significance and future role of these novel biomarkers, allowing us to sort out the best personalized management for an individual with lung cancer diagnosis. Nevertheless, one of these features, the EGF receptor (EGFR) gene mutation, has emerged as a prognostic and strongly predictive biomarker when EGFR inhibition is used as a therapy for tumors that harbor the mutation. Our article displays the most recently developed data related to this biomarker and what have we learned based on the analyses of clinical trials that have studied different agents in the clinical arena.