ArticleScientific reports2022
MALAT1 as master regulator of biomarkers predictive of pan-cancer multi-drug resistance in the context of recalcitrant NRAS signaling pathway identified using systems-oriented approach.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 8 citations in OpenAlex.
- Phylogenetic Analysis of NEAT1 and MALAT1 Long Non-Coding RNAs Highlights Structure-Function Relationships in Paraspeckle Biology.Molecular biology and evolution · 2026Article
- Systematic identification of pan-cancer single-gene expression biomarkers in drug high-throughput screens.PloS one · 2026Article
- Metastasis-Associated Lung Adenocarcinoma Transcript 1 (ACS omega · 2024Article
- Robust self-supervised learning strategy to tackle the inherent sparsity in single-cell RNA-seq data.Briefings in bioinformatics · 2024Article
- A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer.NAR genomics and bioinformatics · 2024Article
- Deconstructing the role of MALAT1 in MAPK-signaling in melanoma: insights from antisense oligonucleotide treatment.Oncotarget · 2023Article
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2 authors at 1 institution in 1 country.
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Abstract
NRAS, a protein mutated in several cancer types, is involved in key drug resistance mechanisms and is an intractable target. The development of drug resistance is one of the major impediments in targeted therapy. Currently, gene expression data is used as the most predictive molecular profile in pan-cancer drug sensitivity and resistance studies. However, the common regulatory mechanisms that drive drug sensitivity/resistance across cancer types are as yet, not fully understood. We focused on GDSC data on NRAS-mutant pan-cancer cell lines, to pinpoint key signaling targets in direct or indirect associations with NRAS, in order to identify other druggable targets involved in drug resistance. Large-scale gene expression, comparative gene co-expression and protein-protein interaction network analyses were performed on selected drugs inducing drug sensitivity/resistance. We validated our data from cell lines with those obtained from primary tissues from TCGA. From our big data studies validated with independent datasets, protein-coding hub genes FN1, CD44, TIMP1, SNAI2, and SPARC were found significantly enriched in signal transduction, proteolysis, cell adhesion and proteoglycans pathways in cancer as well as the PI3K/Akt-signaling pathway. Further studies of the regulation of these hub/driver genes by lncRNAs revealed several lncRNAs as prominent regulators, with MALAT1 as a possible master regulator. Transcription factor EGR1 may control the transcription rate of MALAT1 transcript. Synergizing these studies, we zeroed in on a pan-cancer regulatory axis comprising EGR1-MALAT1-driver coding genes playing a role. These identified gene regulators are bound to provide new paradigms in pan-cancer targeted therapy, a foundation for precision medicine, through the targeting of these key driver genes in the improvement of multi-drug sensitivity or resistance.
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