Search

Abstract Background Laboratory assays are needed for early stage non-small lung cancer (NSCLC) that can link molecular and clinical heterogeneity to predict relapse after surgical resection. We technically validated two miRNA assays for prediction of relapse in NSCLC. Total RNA from seventy-five formalin-fixed and paraffin-embedded (FFPE) specimens was extracted, labeled and hybridized to Affymetrix miRNA arrays using different RNA input amounts, ATP-mix dilutions, array lots and RNA extraction- and labeling methods in a total of 166 hybridizations. Two combinations of RNA extraction- and labeling methods (assays I and II) were applied to a cohort of 68 early stage NSCLC patients. Results RNA input amount and RNA extraction- and labeling methods affected signal intensity and the number of detected probes and probe sets, and caused large variation, whereas different ATP-mix dilutions and array lots did not. Leave-one-out accuracies for prediction of relapse were 63% and 73% for the two assays. Prognosticator calls ("no recurrence" or "recurrence") were consistent, independent on RNA amount, ATP-mix dilution, array lots and RNA extraction method. The calls were not robust to changes in labeling method. Conclusions In this study, we demonstrate that some analytical conditions such as RNA extraction- and labeling methods are important for the variation in assay performance whereas others are not. Thus, careful optimization that address all analytical steps and variables can improve the accuracy of prediction and facilitate the introduction of microRNA arrays in the clinic for prediction of relapse in stage I non-small cell lung cancer (NSCLC).

Abstract Background Quantitative real-time RT-PCR (RT-qPCR) has become a valuable molecular technique in basic and translational biomedical research, and is emerging as an equally valuable clinical tool. Correlation of inter-sample values requires data normalization, which can be accomplished by various means, the most common of which is normalization to internal, stably expressed, reference genes. Recently, such traditionally utilized reference genes as GAPDH and B2M have been found to be regulated in various circumstances in different tissues, emphasizing the need to identify genes independent of factors influencing the tissue, and that are stably expressed within the experimental milieu. In this study, we identified genes for normalization of RT-qPCR data for invasive breast cancer (IBC), with special emphasis on estrogen receptor positive (ER+) IBC, but also examined their applicability to ER- IBC, normal breast tissue and breast cancer cell lines. Methods The reference genes investigated by qRT-PCR were RPLP0, TBP, PUM1, ACTB, GUS-B, ABL1, GAPDH and B2M. Biopsies of 18 surgically-excised tissue specimens (11 ER+ IBCs, 4 ER- IBCs, 3 normal breast tissues) and 3 ER+ cell lines were examined and the data analyzed by descriptive statistics, geNorm and NormFinder. In addition, the expression of selected reference genes in laser capture microdissected ER+ IBC cells were compared with that of whole-tissue. Results A group of 3 genes, TBP, RPLP0 and PUM1, were identified for both the combined group of human tissue samples (ER+ and ER- IBC and normal breast tissue) and for the invasive cancer samples (ER+ and ER- IBC) by GeNorm, where NormFinder consistently identified PUM1 at the single best gene for all sample combinations. Conclusion The reference genes of choice when performing RT-qPCR on normal and malignant breast specimens should be either the collected group of 3 genes (TBP, RPLP0 and PUM1) employed as an average, or PUM1 as a single gene.

Background: We aimed to elucidate the molecular mechanisms of tamoxifen resistance in breast cancer. Methods: We did gene array analyses and identified 366 genes with altered expression in four unique tamoxifen-resistant cell lines versus the parental tamoxifen-sensitive MCF-7/S0.5 cell line. Most of these genes were functionally linked to cell proliferation, death, and control of gene expression, and include FYN, PRKCA, ITPR1, DPYD, DACH1, LYN, GBP1, and PRLR. We also evaluated the subcellular localisation of FYN in primary breast tumours from two cohorts of endocrine-treated ER+ breast cancer patients, one with advanced disease (n=47) and the other with early disease (n=76). Findings: Treatment with FYN-specific small interfering RNA or a SRC family kinase inhibitor reduced cell growth of tamoxifen-resistant cell lines, while exerting no significant effect on MCF-7/S0.5 cells. Moreover, overexpression of FYN in parental tamoxifen-sensitive MCF-7/S0.5 cells resulted in reduced sensitivity to tamoxifen treatment, while knockdown of FYN in the FYN-overexpressing MCF-7/S0.5 cells restored sensitivity to tamoxifen, demonstrating growth-promoting and survival-promoting function of FYN in MCF-7 cells. FYN knockdown in tamoxifen-resistant cells led to reduced phosphorylation of 14-3-3 and Cdc25A, suggesting that FYN, by activation of important cell cycle-associated proteins, could overcome the antiproliferative effects of tamoxifen. Evaluation of the subcellular localisation of FYN in breast cancer patients showed that in those with advanced disease, plasma membrane-associated FYN expression strongly correlated with longer progression-free survival (p< 0.0002). Similarly, in patients with early breast cancer, membrane-associated expression of FYN in the primary breast tumour was significantly associated with increased metastasis-free (p<0.04) and overall survival (p<0.004) independent of tumour size, grade, or lymph node status. Interpretation: Our results indicate that FYN plays an important part in tamoxifen resistance, and its subcellular localisation in breast tumour cells could be an important novel biomarker of response to endocrine therapy in breast cancer. [ABSTRACT FROM AUTHOR]