Project description:The basaloid carcinoma (pure) and the (mixed) basalod variant of lung squamous cell carcinoma (SCC) have a dismal prognosis but their underlying specific molecular characteristics remain obscure and no therapy has proven to be efficient. In order to assess their molecular specificity among other lung squamous cell carcinomas we analysed DNA copy number aberrations and mRNA expression pangenomic profiles of 93 SCC, including 42 basaloid samples (24 pure, 18 mixed).
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.
Project description:The human genome encodes two proteins closely related to transketolase (TKT), transketolase-like protein 1 and 2 (TKTL1 and TKTL2). TKTL1 shares 61% amino acid sequence identity with TKT. More and more evidence suggests a role for TKTL1 in proliferation or cell cycle regulation. Indeed, TKTL1 is overexpressed in various cancers and is correlated with poor prognosis in colon, urothelial, gastric, and lung cancers as well as in ocular adnexa carcinomas, rectum carcinomas, and laryngeal squamous cell carcinomas. Increased TKTL1 levels also correlate with esophageal squamous cell carcinoma metastasis and increased resistance against cisplatin chemotherapy in nasopharyngeal carcinomas. Moreover, TKTL1 overexpression promotes cell proliferation and enhanced tumor growth; in contrast, TKTL1 down regulation attenuates the proliferation of various types of cancer cells. However, the cellular functions and regulatory machineries of TKTL1 are still largely unknown. Through this proteomic analysis, we defined the protein-protein interaction map for the TKTL1 and uncovered the novel regulating function of TKTL1 in regulating TKT transketolase activity.
Project description:Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is about 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. Conventional prognostic markers are unable to determine which patients with completely resected disease within each stage group are likely to relapse. To identify a gene signature associated with recurrent squamous cell carcinoma (SCC) of lung, we analyzed primary tumour gene expression for a total of fifty-one SCCs (stage I-III) on 22,323 element microarrays, comparing expression profiles for individuals who remained disease-free for a minimum of 36 months with those from individuals whose disease recurred within 18 months of complete resection. Cox proportional hazards modeling with leave-one-out cross-validation identified a 70-gene capable of predicting the likelihood of tumor recurrence and a 79-gene signature predictive for overall survival. These two signatures were pooled to generate a 111-gene classifier which achieved an overall predictive accuracy for disease recurrence of 72% (77% sensitivity, 67% specificity) in an independent set of fifty-eight stage I-III SCCs. This classifier also predicted differences in survival (log-rank P=0.0008, hazard ratio (HR), 3.8 [95% confidence interval, 1.6-8.7]), and was superior to conventional prognostic markers such as TNM stage or N stage in predicting patient outcome. Genome-wide profiling has revealed a distinct gene expression profile for recurrent lung SCC which may be clinically useful as a prognostic tool. Expression profiling using 22K element microarrays of 51 primary lung squamous cell carcinomas.