Evidence map›Paper›PMID 38872418›Full record

ArticleCancer medicine2024

Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer.

Mohita Mahajan, Angshuman Sarkar, Sukanta Mondal

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mohita MahajanDepartment of Biological Sciences, Birla Institute of Technology and Science Pilani, K.K. Birla Goa campus, Goa, India.ORCID 0009-0001-1546-492X
Angshuman SarkarDepartment of Biological Sciences, Birla Institute of Technology and Science Pilani, K.K. Birla Goa campus, Goa, India.
Sukanta MondalDepartment of Biological Sciences, Birla Institute of Technology and Science Pilani, K.K. Birla Goa campus, Goa, India.ORCID 0000-0002-5050-2346

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCross-talk among biological pathways is essential for normal biological function and plays a significant role in cancer progression. Through integrated network analysis, this study explores the significance of pathway cross-talk in colorectal cancer (CRC) development at both the pathway and gene levels.

methodsIn this study, we integrated the gene expression data with domain knowledge to construct state-dependent pathway cross-talk networks. The significance of the genes involved in pathway cross-talk was assessed by analyzing their association with cancer hallmarks, disease-gene relation, genetic alterations, and survival analysis. We also analyzed the gene regulatory network to identify the dysregulated genes and their role in CRC progression.

resultsCross-talk was observed between immune-related pathways and pathways associated with cell communication and signaling. The PTPRC gene was identified as a mediator, facilitating interactions within the immune system and other signaling pathways. The rewired interactions of ITGA7 were identified as influential in the epithelial-mesenchymal transition in CRC. This study also highlighted the crucial link between cell communication and vascular smooth muscle contraction pathway in CRC progression. The survival analysis of identified gene clusters showed their significant prognostic value in distinguishing high-risk from low-risk CRC groups, and L1000CDS2 revealed seven potential drug molecules in CRC. Nine dysregulated genes (CTNNB1, EP300, JUN, MYC, NFKB1, RELA, SP1, STAT1, and TP53) emerge as transcription factors acting as common regulators across various pathways.

conclusionsThis study highlights the crucial role of pathway cross-talk in CRC progression and identified the potential prognostic biomarkers and potential drug molecules.

Indexed as

Biomarkers, TumorColorectal NeoplasmsGene Expression Regulation, NeoplasticGene Regulatory NetworksComputational BiologyGene Expression ProfilingHumansPrognosisSignal TransductionSurvival AnalysisTranscriptomeBiomarkers, Tumorgene co‐expression networkgene regulatory networkKEGG pathwayspathway cross‐talkprognostic biomarkersreactome pathways

Identifiers

PMID38872418
PMCPMC11176588

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.