A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options

Evaluation of CXCL9 and CXCL10 as circulating biomarkers of human cardiac allograft rejection

BACKGROUND: Cardiac allograft rejection remains a significant clinical problem in the early phase after heart transplantation and requires frequent surveillance with endomyocardial biopsy. However, this is an invasive procedure, which is unpleasant for the patient and carries a certain risk. Therefore, a sensitive non-invasive biomarker of acute rejection would be desirable. METHODS: Endomyocardial tissue samples and serum were obtained in connection with clinical biopsies from twenty consecutive heart transplant patients followed for six months. A rejection episode was observed in 14 patients (11 men and 3 women) and biopsies obtained before, during and after the episode were identified. Endomyocardial RNA, from three patients, matching these three points in time were analysed with DNA microarray. Genes showing up-regulation during rejection followed by normalization after the rejection episode were evaluated further with real-time RT-PCR. Finally, ELISA was performed to investigate whether change in gene-regulation during graft rejection was reflected in altered concentrations of the encoded protein in serum. RESULTS: Three potential cardiac allograft rejection biomarker genes, chemokine (C-X-C motif) ligand 9 (CXCL9), chemokine (C-X-C motif) ligand 10 (CXCL10) and Natriuretic peptide precursor A (NPPA), from the DNA microarray analysis were selected for further evaluation. CXCL9 was significantly upregulated during rejection (p < 0.05) and CXCL10 displayed a similar pattern without reaching statistical significance. Serum levels of CXCL9 and CXCL10 were measured by ELISA in samples from 10 patients before, during and after cardiac rejection. There were no changes in CXCL9 and CXCL10 serum concentrations during cardiac rejection. Both chemokines displayed large individual variations in the selected samples, but the serum levels between the two chemokines correlated (p < 0.001). CONCLUSION: We conclude, that despite a distinct up-regulation of CXCL9 mRNA in human hearts during cardiac allograft rejection, this was not reflected in the serum levels of the encoded protein. Thus, in contrast to previous suggestions, serum CXCL9 does not appear to be a promising serum biomarker for cardiac allograft rejection

The role of FKBP5 in cancer aetiology and chemoresistance

FK506 binding protein 51 (FKBP51, also called FKBP5) belongs to a family of immunophilins, FK506 binding proteins (FKBPs). Members of this family are targets for drugs such as rapamycin and cyclosporine. Although FKBP5 shares characteristics with other FKBPs, it also has unique features, especially its role in the regulation of multiple signalling pathways and in tumourigenesis and chemoresistance. In this review, we will focus on the recently discovered role of FKBP5 in cancer aetiology and response to antineoplastic therapy

Gene expression relationship between prostate cancer cells of Gleason 3, 4 and normal epithelial cells as revealed by cell type-specific transcriptomes

Background: Prostate cancer cells in primary tumors have been typed CD10(-)/CD13(-)/CD24(hi)/CD26(+)/CD38(lo)/CD44(-)/CD104(-). This CD phenotype suggests a lineage relationship between cancer cells and luminal cells. The Gleason grade of tumors is a descriptive of tumor glandular differentiation. Higher Gleason scores are associated with treatment failure. Methods: CD26(+) cancer cells were isolated from Gleason 3+3 (G3) and Gleason 4+4 (G4) tumors by cell sorting, and their gene expression or transcriptome was determined by Affymetrix DNA array analysis. Dataset analysis was used to determine gene expression similarities and differences between G3 and G4 as well as to prostate cancer cell lines and histologically normal prostate luminal cells. Results: The G3 and G4 transcriptomes were compared to those of prostatic cell types of non-cancer, which included luminal, basal, stromal fibromuscular, and endothelial. A principal components analysis of the various transcriptome datasets indicated a closer relationship between luminal and G3 than luminal and G4. Dataset comparison also showed that the cancer transcriptomes differed substantially from those of prostate cancer cell lines. Conclusions: Genes differentially expressed in cancer are potential biomarkers for cancer detection, and those differentially expressed between G3 and G4 are potential biomarkers for disease stratification given that G4 cancer is associated with poor outcomes. Differentially expressed genes likely contribute to the prostate cancer phenotype and constitute the signatures of these particular cancer cell types.National Institutes of Health (NIH)[CA111244]National Institutes of Health (NIH)[CA98699]National Institutes of Health (NIH)[CA85859]National Institutes of Health (NIH)[DK63630][P50-GMO-76547

LNCaP Atlas: Gene expression associated with in vivo progression to castration-recurrent prostate cancer

<p>Abstract</p> <p>Background</p> <p>There is no cure for castration-recurrent prostate cancer (CRPC) and the mechanisms underlying this stage of the disease are unknown.</p> <p>Methods</p> <p>We analyzed the transcriptome of human LNCaP prostate cancer cells as they progress to CRPC <it>in vivo </it>using replicate LongSAGE libraries. We refer to these libraries as the LNCaP atlas and compared these gene expression profiles with current suggested models of CRPC.</p> <p>Results</p> <p>Three million tags were sequenced using <it>in vivo </it>samples at various stages of hormonal progression to reveal 96 novel genes differentially expressed in CRPC. Thirty-one genes encode proteins that are either secreted or are located at the plasma membrane, 21 genes changed levels of expression in response to androgen, and 8 genes have enriched expression in the prostate. Expression of 26, 6, 12, and 15 genes have previously been linked to prostate cancer, Gleason grade, progression, and metastasis, respectively. Expression profiles of genes in CRPC support a role for the transcriptional activity of the androgen receptor (<it>CCNH, CUEDC2, FLNA, PSMA7</it>), steroid synthesis and metabolism (<it>DHCR24, DHRS7</it>, <it>ELOVL5, HSD17B4</it>, <it>OPRK1</it>), neuroendocrine (<it>ENO2, MAOA, OPRK1, S100A10, TRPM8</it>), and proliferation (<it>GAS5</it>, <it>GNB2L1</it>, <it>MT-ND3</it>, <it>NKX3-1</it>, <it>PCGEM1</it>, <it>PTGFR</it>, <it>STEAP1</it>, <it>TMEM30A</it>), but neither supported nor discounted a role for cell survival genes.</p> <p>Conclusions</p> <p>The <it>in vivo </it>gene expression atlas for LNCaP was sequenced and support a role for the androgen receptor in CRPC.</p

Identification of a candidate prognostic gene signature by transcriptome analysis of matched pre-and post-treatment prostatic biopsies from patients with advanced prostate cancer

Background: Although chemotherapy for prostate cancer (PCa) can improve patient survival, some tumours are chemo-resistant. Tumour molecular profiles may help identify the mechanisms of drug action and identify potential prognostic biomarkers. We performed in vivo transcriptome profiling of pre- and post-treatment prostatic biopsies from patients with advanced hormone-naive prostate cancer treated with docetaxel chemotherapy and androgen deprivation therapy (ADT) with an aim to identify the mechanisms of drug action and identify prognostic biomarkers. Methods: RNA sequencing (RNA-Seq) was performed on biopsies from four patients before and ~22 weeks after docetaxel and ADT initiation. Gene fusion products and differentially-regulated genes between treatment pairs were identified using TopHat and pathway enrichment analyses undertaken. Publically available datasets were interrogated to perform survival analyses on the gene signatures identified using cBioportal. Results: A number of genomic rearrangements were identified including the TMPRSS2/ERG fusion and 3 novel gene fusions involving the ETS family of transcription factors in patients, both pre and post chemotherapy. In total, gene expression analyses showed differential expression of at least 2 fold in 575 genes in post-chemotherapy biopsies. Of these, pathway analyses identified a panel of 7 genes (ADAM7, FAM72B, BUB1B, CCNB1, CCNB2, TTK, CDK1), including a cell cycle-related geneset, that were differentially-regulated following treatment with docetaxel and ADT. Using cBioportal to interrogate the MSKCC-Prostate Oncogenome Project dataset we observed a statistically-significant reduction in disease-free survival of patients with tumours exhibiting alterations in gene expression of the above panel of 7 genes (p = 0.015). Conclusions: Here we report on the first “real-time” in vivo RNA-Seq-based transcriptome analysis of clinical PCa from pre- and post-treatment TRUSS-guided biopsies of patients treated with docetaxel chemotherapy plus ADT. We identify a chemotherapy-driven PCa transcriptome profile which includes the down-regulation of important positive regulators of cell cycle progression. A 7 gene signature biomarker panel has also been identified in high-risk prostate cancer patients to be of prognostic value. Future prospective study is warranted to evaluate the clinical value of this panel