👤 Tomasz Tyszkiewicz

Transcriptome of papillary thyroid cancer (PTC) is well characterized and correlates with some prognostic and genotypic factors, but data addressing the interaction between PTC and tumor microenvironment (TME) are scarce. Therefore, in the present study, we aimed to assess the impact of TME on gene expression profile in PTC. We evaluated the gene expression profile in PTC and normal thyroid cells isolated by laser capture microdissection and in whole tissue slides corresponding to the entire tumor. We included 26 microdissected samples for gene expression analysis (HG-U133 PLUS 2.0, Affymetrix, currently Thermo Fisher Scientific USA): 15 PTC samples, 11 samples of normal thyrocytes, and 30 whole slides (15 PTC and 15 normal thyroid). Transcripts were divided into three groups: differentially expressed both in microdissected and whole slides, transcripts differently expressed in microdissected samples and not changed in whole slides, and transcripts differentially expressed in whole slides and not changed in microdissected samples. Eleven genes were selected for validation in an independent set of samples; among them, four genes differentiated only microdissected PTC and normal cells. Two genes (PTCSC and CTGF) were confirmed. One gene (FOS) was not confirmed by the validation, whereas EGR1 was also significant in whole slide analysis. The other seven genes (TFF3, FN1, MPPED2, MET, KCNJ2, TACSTD2, and GALE) showed differentiated expression in microdissected thyrocytes and in whole tumor slides. Most of identified genes were related to the tumor-microenvironment interaction and confirmed the crosstalk between TME and cancer cells. Show less

Several studies have shown the prognostic and predictive potential of molecular markers in combined therapy for lung cancer. Most of them referred, however, to operable early stage NSCLC. The aim of the present study is to correlate the expression of multiple mRNA markers in bronchoscopy obtained cancer specimens with clinical outcome of advanced lung cancer. Bronchoscopy cancer specimens were taken from 123 patients with radiological diagnosis of advanced lung tumor. Out of 123 patients 50 were diagnosed with squamous cell cancer, 17 with adenocarcinoma, 12 with NOS, 32 with SCLC and one with large cell neuroendocrinal cancer. In 11 patients other tumours were diagnosed. The group was heterogeneous with respect to clinical stage, performance of the patients and treatment. Quantitative real time PCR was carried out by ABI 7900 HT machine, with Universal Probe Library (Roche) fluorescent probes. The genes selected for the analysis were ERCC1, EGFR, BRCA1, CSF1, CA9, DUSP6, STAT1, ERBB3, MMD, FN1, and CDKN1B. More than 50 ng of RNA (the amount considered sufficient for the analysis) was isolated in 82 out of 112 lung cancer specimens (73%), including 60/80 (75.0%) of NSCLC specimens and 22/32 (68,7%) of SCLC samples. The highest Cohen's κ coefficient for discrimination between small cell, squamous cell and adenocarcinoma was found for CDKN1B, CSF and EGFR1 (κ = 0.177, p = 0.0041). A multivariate Cox regression model has shown a significant impact of clinical stage (p<0.001, RR = 4.19), ERCC1 (p = 0.01, RR = 0.43) and CA9 (p = 0.03, RR = 2.11) expression on overall survival in a group of 60 patients with NSCLC. These results show the feasibility of multiple gene expression analysis in bronchoscopy obtained cancer specimens as prognostic markers in radiotherapy and chemotherapy for advanced lung cancer. A limiting factor was relatively high proportion of samples from which sufficient amount of RNA could not be isolated. Show less