Dataset Information

Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines.

ABSTRACT: Transcription factors (TFs) are gene regulatory proteins that are essential for an effective regulation of the transcriptional machinery. Today, it is known that their expression plays an important role in several types of cancer. Computational identification of key players in specific cancer cell lines is still an open challenge in cancer research. In this study, we present a systematic approach which combines colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93, and well-established computational methods in order to compare these cell lines on the level of transcriptional regulation as well as on a pathway level, i.e., the cancer cell-intrinsic pathway repertoire. For this purpose, we firstly applied the Trinity platform to detect signature genes, and then applied analyses of the geneXplain platform to these for detection of upstream transcriptional regulators and their regulatory networks. We created a CRC-specific position weight matrix (PWM) library based on the TRANSFAC database (release 2014.1) to minimize the rate of false predictions in the promoter analyses. Using our proposed workflow, we specifically focused on revealing the similarities and differences in transcriptional regulation between the two CRC cell lines, and report a number of well-known, cancer-associated TFs with significantly enriched binding sites in the promoter regions of the signature genes. We show that, although the signature genes of both cell lines show no overlap, they may still be regulated by common TFs in CRC. Based on our findings, we suggest that canonical Wnt signaling is activated in 1638N-T1, but inhibited in CMT-93 through cross-talks of Wnt signaling with the VDR signaling pathway and/or LXR-related pathways. Furthermore, our findings provide indication of several master regulators being present such as MLK3 and Mapk1 (ERK2) which might be important in cell proliferation, migration, and invasion of 1638N-T1 and CMT-93, respectively. Taken together, we provide new insights into the invasive potential of these cell lines, which can be used for development of effective cancer therapy.

SUBMITTER: Wlochowitz D

PROVIDER: S-EPMC4820448 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines.

Wlochowitz Darius D Haubrock Martin M Arackal Jetcy J Bleckmann Annalen A Wolff Alexander A Beißbarth Tim T Wingender Edgar E Gültas Mehmet M

Frontiers in genetics 20160405

Transcription factors (TFs) are gene regulatory proteins that are essential for an effective regulation of the transcriptional machinery. Today, it is known that their expression plays an important role in several types of cancer. Computational identification of key players in specific cancer cell lines is still an open challenge in cancer research. In this study, we present a systematic approach which combines colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93, and well-established ...[more]

PMID: 27092172

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Project description:BACKGROUND: Cancer cells frequently adopt cellular and molecular alterations and acquire resistance to cytostatic drugs. Chemotherapy with oxaliplatin is among the leading treatments for colorectal cancer with a response rate of 50%, inducing intrastrand cross-links on the DNA. Despite of this drug's efficiency, resistance develops in nearly all metastatic patients. Chemoresistance being of crucial importance for the drug's clinical efficiency this study aimed to contribute to the identification and description of some cellular and molecular alterations induced by prolonged oxaliplatin therapy. Resistance to oxaliplatin was induced in Colo320 (Colo320R) and HT-29 (HT-29R) colorectal adenocarcinoma cell lines by exposing the cells to increasing concentrations of the drug. Alterations in morphology, cytotoxicity, DNA cross-links formation and gene expression profiles were assessed in the parental and resistant variants with microscopy, MTT, alkaline comet and pangenomic microarray assays, respectively. RESULTS: Morphology analysis revealed epithelial-to-mesenchymal transition in the resistant vs parental cells suggesting alterations of the cells' adhesion complexes, through which they acquire increased invasiveness and adherence. Cytotoxicity measurements demonstrated resistance to oxaliplatin in both cell lines; Colo320 being more sensitive than HT-29 to this drug (P?<?0.001). The treatment with oxaliplatin caused major DNA cross-links in both parental cell lines; in Colo320R small amounts of DNA cross-links were still detectable, while in HT-29R not. We identified 441 differentially expressed genes in Colo320R and 613 in HT-29R as compared to their parental counterparts (at least 1.5 -fold up- or down- regulation, p?<?0.05). More disrupted functions and pathways were detected in HT-29R cell line than in Colo320R, involving genes responsible for apoptosis inhibition, cellular proliferation and epithelial-to-mesenchymal transition. Several upstream regulators were detected as activated in HT-29R cell line, but not in Colo320R. CONCLUSIONS: Our findings revealed a more resistant phenotype in HT-29R as compared to Colo320R and different cellular and molecular chemoresistance patterns induced by prolonged treatment with oxaliplatin in cell lines with identical origins (colorectal adenocarcinomas).

Project description:One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically 'coregulated' genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes.

Dataset Information

Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines.

Publications

Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines.

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