Evidence map›Paper›PMID 37178411›Full record

ArticleCancer reports (Hoboken, N.J.)2023

Identification of m6A-related lncRNAs as prognostic signature within colon tumor immune microenvironment.

Lichao Cao, Shenrui Zhang, Ying Ba, Hezi Zhang

Abstract read
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Article in Cancer reports (Hoboken, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Lichao CaoProvincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.ORCID 0000-0002-6563-1140
Shenrui ZhangResearch and Development Department, Shenzhen Nucleus Gene Technology Co., Ltd., Shenzhen, China.
Ying BaResearch and Development Department, Shenzhen Nucleus Gene Technology Co., Ltd., Shenzhen, China.
Hezi ZhangResearch and Development Department, Shenzhen Nucleus Gene Technology Co., Ltd., Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current study probed prognosis-related potential for m6A-related lncRNAs signatures within colon tumor immune microenvironment (TIM).

methodsAfter downloading transcriptomic datasets for colon cancer (CC) patients from The Cancer Genome Atlas (TCGA), they were divided, in a 1:1 ratio, within training or test datasets. m6A-related lncRNAs were then scrutinized across such dataset using Pearson correlation assessment before generating a m6A-related lncRNAs prognosis-related model using the training dataset. The latter was then validated with the test and the whole dataset. In addition, we compared the differences of TIM and the estimated IC50 of drug response between the high- and low-risk groups.

resultsOverall survival (OS) resulted as linked with 11 m6A-related lncRNAs, while within the developed prognosis-related model, areas-under-curves were as follows: within training dataset, values at 3-, 4-, and 5-years were 0.777, 0.819, and 0.805, accordingly, and for test one, they were 0.697, 0.682, and 0.706, respectively. Finally, the values for the whole dataset were 0.675 (3-year), 0.682 (4-years), and 0.679 (5-years), accordingly. Moreover, CC cases categorized within low-risk cohort demonstrated enhanced OS (p < .0001), lower metastasis (p = 2e-06) and lower T stage (p = .0067), more instability for microsatellite status (p = .012), and downregulation for PD-L1, PD-1, CTLA-4, LAG3, and HAVCR2 (p < .05). In addition, risk scorings were significantly linked to the degree of infiltrative intensity for CD8 and CD4 (memory resting) T-cells, T-regulatory (Tregs), and Mast cells triggering (p < .05). Patients with low infiltrative propensity for CD4 T-cells also had better OS (p = .016). Moreover, six representative drugs were found to be sensitive for treating CC patients.

conclusionA robust m6A-related prognostic model with great performances was developed before exploring the TIM characteristics and its potential therapeutic drugs, which might improve the prognosis and therapeutic efficacy.

Indexed as

Colonic NeoplasmsRNA, Long NoncodingDown-RegulationGene Expression ProfilingHumansPrognosisTumor MicroenvironmentRNA, Long Noncodingcolon cancerlncRNAsN6-methylandenosineprognostic modeltumor immune microenvironment

Identifiers

PMID37178411
PMCPMC10242659

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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.