Misregulation of ELK1, AP1, and E12 Transcription Factor Networks Is Associated with Melanoma Progression.

Komudi Singh,Fayaz Seifuddin,Clare M Waterman,Yun-Ching Chen,Robert Fischer,Vijender Chaitankar,Ilker Tunc,Mehdi Pirooznia,Michelle Baird

doi:10.3390/cancers12020458

Abstract

Melanoma is among the most malignant cutaneous cancers and when metastasized results in dramatically high mortality. Despite advances in high-throughput gene expression profiling in cancer transcriptomic studies, our understanding of mechanisms driving melanoma progression is still limited. We present here an in-depth bioinformatic analysis of the melanoma RNAseq, chromatin immunoprecipitation (ChIP)seq, and single-cell (sc)RNA seq data to understand cancer progression. Specifically, we have performed a consensus network analysis of RNA-seq data from clinically re-grouped melanoma samples to identify gene co-expression networks that are conserved in early (stage 1) and late (stage 4/invasive) stage melanoma. Overlaying the fold-change information on co-expression networks revealed several coordinately up or down-regulated subnetworks that may play a critical role in melanoma progression. Furthermore, by incorporating histone lysine-27 acetylation information and highly expressed genes identified from the single-cell RNA data from melanoma patient samples, we present a comprehensive list of pathways, putative protein-protein interactions (PPIs) and transcription factor (TF) networks that are driving cancer progression. From this analysis, we have identified Elk1, AP1 and E12 TF networks that coordinately change expression in late melanoma when compared to early melanoma, implicating these TFs in melanoma progression. Additionally, the sumoylation-associated interactome is upregulated in invasive melanoma. Together, this bioinformatic analysis potentially implicates a combination of TF networks and PPIs in melanoma progression, which if confirmed in the experimental systems, could be used as targets for drug intervention in melanoma.

Highlights

Melanocytes are a population of cells that arise from the neural crest lineage and are found in the skin, the middle layer of the eye, the inner ear, the meninges, bones and the heart [1,2]
We present here a comprehensive bioinformatic analysis of the melanoma RNA-seq data that incorporates (a) clinical information to stratify the samples into stages of melanoma cancer (b) subnetwork analysis on clusters of correlated genes (c) overlays genes associated with superenhancers from chromatin immunoprecipitation (ChIP) seq data
While these samples were sufficient to create robust correlated clusters, future studies on larger cohort of staged melanoma samples will be needed to test if similar transcription factor (TF) and protein-protein interactions (PPIs) subnetworks are identified to further substantiate the findings from this study

Summary

Introduction

Melanocytes are a population of cells that arise from the neural crest lineage and are found in the skin, the middle layer of the eye, the inner ear, the meninges, bones and the heart [1,2]. In the skin, these cells are present in the most bottom layer of the skin epidermis and in the hair follicles, and are primarily responsible for the production of the pigment melanin, which is synthesized and stored in lysosome-like organelles called melanosomes [3]. The majority of cutaneous melanomas arise as a result of the proliferation of melanocytes, referred to as melanocytic naevi. Increasing occurrences of these melanocytic naevi raises the chance for melanoma development [6]

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