Dataset Information

Distinct TP63 Isoform-Driven Transcriptional Signatures Predict Tumor Progression and Clinical Outcomes.

ABSTRACT: TP63 is required to maintain stem cell pluripotency and suppresses the metastatic potential of cancer cells through multiple mechanisms. These functions are differentially regulated by individual isoforms, necessitating a deeper understanding of how the distinct transcriptional programs controlled by these isoforms affect cancer progression and outcomes. In this study, we conducted a pan-cancer analysis of The Cancer Genome Atlas to identify transcriptional networks regulated by TAp63 and ?Np63 using transcriptomes derived from epidermal cells of TAp63-/- and ?Np63-/- mice. Analysis of 17 cancer developmental and 27 cancer progression signatures revealed a consistent tumor suppressive pattern for TAp63. In contrast, we identified pleiotropic roles for ?Np63 in tumor development and found that its regulation of Lef1 was crucial for its oncogenic role. ?Np63 performed a distinctive role as suppressor of tumor progression by cooperating with TAp63 to modulate key biological pathways, principally cell-cycle regulation, extracellular matrix remodeling, epithelial-to-mesenchymal transition, and the enrichment of pluripotent stem cells. Importantly, these TAp63 and ?Np63 signatures prognosticated progression and survival, even within specific stages, in bladder and renal carcinomas as well as low-grade gliomas. These data describe a novel approach for understanding transcriptional activities of TP63 isoforms across a large number of cancer types, potentially enabling identification of patient subsets most likely to benefit from therapies predicated on manipulating specific TP63 isoforms.Significance: Transcriptomic analyses of patient samples and murine knockout models highlight the prognostic role of several critical mechanisms of tumor suppression that are regulated by TP63. Cancer Res; 78(2); 451-62. ©2017 AACR.

SUBMITTER: Abbas HA

PROVIDER: S-EPMC5771893 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Distinct TP63 Isoform-Driven Transcriptional Signatures Predict Tumor Progression and Clinical Outcomes.

Abbas Hussein A HA Bui Ngoc Hoang Bao NHB Rajapakshe Kimal K Wong Justin J Gunaratne Preethi P Tsai Kenneth Y KY Coarfa Cristian C Flores Elsa R ER

Cancer research 20171127 2

TP63 is required to maintain stem cell pluripotency and suppresses the metastatic potential of cancer cells through multiple mechanisms. These functions are differentially regulated by individual isoforms, necessitating a deeper understanding of how the distinct transcriptional programs controlled by these isoforms affect cancer progression and outcomes. In this study, we conducted a pan-cancer analysis of The Cancer Genome Atlas to identify transcriptional networks regulated by TAp63 and ΔNp63 ...[more]

PMID: 29180475

Similar Datasets

Project description:An emerging cellular immunotherapy for cancer is based on the cytolytic activity of natural killer (NK) cells against a wide range of tumors. Although in vitro activation, or "priming," of NK cells by exposure to pro-inflammatory cytokines, such as interleukin (IL)-2, has been extensively studied, the biological consequences of NK cell activation in response to target cell interactions have not been thoroughly characterized. We investigated the consequences of co-incubation with K562, CTV-1, Daudi RPMI-8226, and MCF-7 tumor cell lines on the phenotype, cytokine expression profile, and transcriptome of human NK cells. We observe the downregulation of several activation receptors including CD16, CD62L, C-X-C chemokine receptor (CXCR)-4, natural killer group 2 member D (NKG2D), DNAX accessory molecule (DNAM)-1, and NKp46 following tumor-priming. Although this NK cell phenotype is typically associated with NK cell dysfunction in cancer, we reveal the upregulation of NK cell activation markers, such as CD69 and CD25; secretion of pro-inflammatory cytokines, including macrophage inflammatory proteins (MIP-1) α /β and IL-1β/6/8; and overexpression of numerous genes associated with enhanced NK cell cytotoxicity and immunomodulatory functions, such as FAS, TNFSF10, MAPK11, TNF, and IFNG. Thus, it appears that tumor-mediated ligation of receptors on NK cells may induce a primed state which may or may not lead to full triggering of the lytic or cytokine secreting machinery. Key signaling molecules exclusively affected by tumor-priming include MAP2K3, MARCKSL1, STAT5A, and TNFAIP3, which are specifically associated with NK cell cytotoxicity against tumor targets. Collectively, these findings help define the phenotypic and transcriptional signature of NK cells following their encounters with tumor cells, independent of cytokine stimulation, and provide insight into tumor-specific NK cell responses to inform the transition toward harnessing the therapeutic potential of NK cells in cancer.

Project description:Over the last two decades, tumor-derived RNA expression signatures have been developed for the two most commonly diagnosed tumors worldwide, namely prostate and breast tumors, in order to improve both outcome prediction and treatment decision-making. In this context, molecular signatures gained by main components of the tumor microenvironment, such as cancer-associated fibroblasts (CAFs), have been explored as prognostic and therapeutic tools. Nevertheless, a deeper understanding of the significance of CAFs-related gene signatures in breast and prostate cancers still remains to be disclosed. RNA sequencing technology (RNA-seq) was employed to profile and compare the transcriptome of CAFs isolated from patients affected by breast and prostate tumors. The differentially expressed genes (DEGs) characterizing breast and prostate CAFs were intersected with data from public datasets derived from bulk RNA-seq profiles of breast and prostate tumor patients. Pathway enrichment analyses allowed us to appreciate the biological significance of the DEGs. K-means clustering was applied to construct CAFs-related gene signatures specific for breast and prostate cancer and to stratify independent cohorts of patients into high and low gene expression clusters. Kaplan-Meier survival curves and log-rank tests were employed to predict differences in the outcome parameters of the clusters of patients. Decision-tree analysis was used to validate the clustering results and boosting calculations were then employed to improve the results obtained by the decision-tree algorithm. Data obtained in breast CAFs allowed us to assess a signature that includes 8 genes (ITGA11, THBS1, FN1, EMP1, ITGA2, FYN, SPP1, and EMP2) belonging to pro-metastatic signaling routes, such as the focal adhesion pathway. Survival analyses indicated that the cluster of breast cancer patients showing a high expression of the aforementioned genes displays worse clinical outcomes. Next, we identified a prostate CAFs-related signature that includes 11 genes (IL13RA2, GDF7, IL33, CXCL1, TNFRSF19, CXCL6, LIFR, CXCL5, IL7, TSLP, and TNFSF15) associated with immune responses. A low expression of these genes was predictive of poor survival rates in prostate cancer patients. The results obtained were significantly validated through a two-step approach, based on unsupervised (clustering) and supervised (classification) learning techniques, showing a high prediction accuracy (≥ 90%) in independent RNA-seq cohorts. We identified a huge heterogeneity in the transcriptional profile of CAFs derived from breast and prostate tumors. Of note, the two novel CAFs-related gene signatures might be considered as reliable prognostic indicators and valuable biomarkers for a better management of breast and prostate cancer patients.

Dataset Information

Distinct TP63 Isoform-Driven Transcriptional Signatures Predict Tumor Progression and Clinical Outcomes.

Publications

Distinct TP63 Isoform-Driven Transcriptional Signatures Predict Tumor Progression and Clinical Outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets