MTFAP: a Comprehensive Platform for Predicting and Analyzing Master Transcription Factors

Overview

Journal Sci Rep

Specialty Science

Date 2024 Dec 31

PMID 39738650

Authors

Jianyuan Zhou

Haojie Yu

Chunhui Lou

Min Yang

Yanshang Li

Qian Yang

Shuhan Li

Chunwang Ji

Song Li

Shuang Wang

Haotian Cao

Xuecang Li

Lian Liu

Affiliations

Soon will be listed here.

Abstract

Master transcription factors (MTFs) activate gene expression in pluripotent embryonic stem cells (ESCs) by binding to enhancers and super-enhancers, which precisely control ESC fate. Compelling evidence reveals a strong correlation between the operation of MTFs and the initiation and progression of cancer. Nevertheless, the challenge of identifying MTFs imposes a barrier for researchers. Therefore, we developed a master transcription factors prediction and analysis web resource (MTFAP). MTFAP is a comprehensive web tool designed to predict and analyze MTFs with different data types. To enhance user experience and facilitate exploration of interest MTFs, MTFAP offers search and browse functionalities. Furthermore, we have developed a Docker file to empower users with the capability to conduct localized analyses Additionally, MTFAP extends support for further analysis and data visualization for the MTFs identified by Coltron and CRCmapper. The platform is freely available at http://www.xiejjlab.bio/MTFAP/.

References

Jiang Y, Jiang Y, Li C, Zhang Y, Dakle P, Kaur H . TP63, SOX2, and KLF5 Establish a Core Regulatory Circuitry That Controls Epigenetic and Transcription Patterns in Esophageal Squamous Cell Carcinoma Cell Lines. Gastroenterology. 2020; 159(4):1311-1327.e19. DOI: 10.1053/j.gastro.2020.06.050. View

Boyer L, Lee T, Cole M, Johnstone S, Levine S, Zucker J . Core transcriptional regulatory circuitry in human embryonic stem cells. Cell. 2005; 122(6):947-56. PMC: 3006442. DOI: 10.1016/j.cell.2005.08.020. View

Newman A, Liu C, Green M, Gentles A, Feng W, Xu Y . Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015; 12(5):453-7. PMC: 4739640. DOI: 10.1038/nmeth.3337. View

Corces M, Granja J, Shams S, Louie B, Seoane J, Zhou W . The chromatin accessibility landscape of primary human cancers. Science. 2018; 362(6413). PMC: 6408149. DOI: 10.1126/science.aav1898. View

Balhoff J, Carbon S, Ebert D, Gaudet P, Harris N, Mi H . The Gene Ontology knowledgebase in 2023. Genetics. 2023; 224(1). PMC: 10158837. DOI: 10.1093/genetics/iyad031. View

Saint-Andre V, Federation A, Lin C, Abraham B, Reddy J, Lee T . Models of human core transcriptional regulatory circuitries. Genome Res. 2016; 26(3):385-96. PMC: 4772020. DOI: 10.1101/gr.197590.115. View

Ott C, Federation A, Schwartz L, Kasar S, Klitgaard J, Lenci R . Enhancer Architecture and Essential Core Regulatory Circuitry of Chronic Lymphocytic Leukemia. Cancer Cell. 2018; 34(6):982-995.e7. PMC: 6298230. DOI: 10.1016/j.ccell.2018.11.001. View

Schmeier S, Alam T, Essack M, Bajic V . TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactions. Nucleic Acids Res. 2016; 45(D1):D145-D150. PMC: 5210517. DOI: 10.1093/nar/gkw1007. View

Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z . GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017; 45(W1):W98-W102. PMC: 5570223. DOI: 10.1093/nar/gkx247. View

10.

Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z . clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (Camb). 2021; 2(3):100141. PMC: 8454663. DOI: 10.1016/j.xinn.2021.100141. View

11.

Li H, Ning S, Ghandi M, Kryukov G, Gopal S, Deik A . The landscape of cancer cell line metabolism. Nat Med. 2019; 25(5):850-860. PMC: 6629041. DOI: 10.1038/s41591-019-0404-8. View

12.

Lee K, Yeo S, Gong J, Koo O, Sohn I, Lee W . PRRX1 is a master transcription factor of stromal fibroblasts for myofibroblastic lineage progression. Nat Commun. 2022; 13(1):2793. PMC: 9120014. DOI: 10.1038/s41467-022-30484-4. View

13.

McFarland J, Ho Z, Kugener G, Dempster J, Montgomery P, Bryan J . Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration. Nat Commun. 2018; 9(1):4610. PMC: 6214982. DOI: 10.1038/s41467-018-06916-5. View

14.

Chen Y, Xu L, Lin R, Muschen M, Koeffler H . Core transcriptional regulatory circuitries in cancer. Oncogene. 2020; 39(43):6633-6646. PMC: 7581508. DOI: 10.1038/s41388-020-01459-w. View

15.

Shen W, Chen S, Gan Z, Zhang Y, Yue T, Chen M . AnimalTFDB 4.0: a comprehensive animal transcription factor database updated with variation and expression annotations. Nucleic Acids Res. 2022; 51(D1):D39-D45. PMC: 9825474. DOI: 10.1093/nar/gkac907. View

16.

Caicedo H, Hashimoto D, Caicedo J, Pentland A, Pisano G . Overcoming barriers to early disease intervention. Nat Biotechnol. 2020; 38(6):669-673. DOI: 10.1038/s41587-020-0550-z. View

17.

Blum A, Wang P, Zenklusen J . SnapShot: TCGA-Analyzed Tumors. Cell. 2018; 173(2):530. DOI: 10.1016/j.cell.2018.03.059. View

18.

Okuda S, Yamada T, Hamajima M, Itoh M, Katayama T, Bork P . KEGG Atlas mapping for global analysis of metabolic pathways. Nucleic Acids Res. 2008; 36(Web Server issue):W423-6. PMC: 2447737. DOI: 10.1093/nar/gkn282. View

19.

Whyte W, Orlando D, Hnisz D, Abraham B, Lin C, Kagey M . Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell. 2013; 153(2):307-19. PMC: 3653129. DOI: 10.1016/j.cell.2013.03.035. View

20.

Duttke S, Chang M, Heinz S, Benner C . Identification and dynamic quantification of regulatory elements using total RNA. Genome Res. 2019; 29(11):1836-1846. PMC: 6836739. DOI: 10.1101/gr.253492.119. View