Evidence map›Paper›PMID 35792657›Full record

ArticleCancer science2022

Novel prognostic model predicts overall survival in colon cancer based on RNA splicing regulation gene expression.

Qiu-Yun Luo, Tian Di, Zhi-Gang Chen, Jian-Hong Peng, Jian Sun, Zeng-Fei Xia, Wen-Tao Pan, Fan Luo, Fei-Teng Lu, Yu-Ting Sun and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 33% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

14 authors at 1 institution in 1 country.

Qiu-Yun LuoCancer Research Institute, The Eighth Affiliated HospitalSun Yat-Sen University, Shenzhen, China.ORCID https://orcid.org/0000-0002-8290-9626
Tian DiState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Zhi-Gang ChenState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.ORCID https://orcid.org/0000-0001-7597-2689
Jian-Hong PengState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Jian SunState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Zeng-Fei XiaState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Wen-Tao PanState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Fan LuoState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Fei-Teng LuState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Yu-Ting SunState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Li-Qiong YangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Lin ZhangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Miao-Zhen QiuState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.ORCID https://orcid.org/0000-0002-4774-6235
Da-Jun YangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Sun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81772587National Natural Science Foundation of China 82003268National Natural Science Foundation of China 82073377Natural Science Foundation of Guangdong Province 2021A1515012439Science and Technology Program of Guangdong 2019B020227002
6 · The paper itself

Abstract

Colon cancer is the third most common cancer and the second leading cause of cancer-related death worldwide. Dysregulated RNA splicing factors have been reported to be associated with tumorigenesis and development in colon cancer. In this study, we interrogated clinical and RNA expression data of colon cancer patients from The Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) database. Genes regulating RNA splicing correlated with survival in colon cancer were identified and a risk score model was constructed using Cox regression analyses. In the risk model, RNA splicing factor peroxisome proliferator-activated receptor-γ coactivator-1α (PPARGC1) is correlated with a good survival outcome, whereas Cdc2-like kinase 1(CLK1), CLK2, and A-kinase anchor protein 8-like (AKAP8L) with a bad survival outcome. The risk model has a good performance for clinical prognostic prediction both in the TCGA cohort and the other two validation cohorts. In the tumor microenvironment (TME) analysis, the immune score was higher in the low-risk group, and TME-related pathway gene expression was also higher in low-risk group. We further verified the mRNA and protein expression levels of these four genes in the adjacent nontumor, tumor, and liver metastasis tissues of colon cancer patients, which were consistent with bioinformatics analysis. In addition, knockdown of AKAP8L can suppress the proliferation and migration of colon cancer cells. Animal studies have also shown that AKAP8L knockdown can inhibit tumor growth in colon cancer in vivo. We established a prognostic risk model for colon cancer based on genes related to RNA splicing regulation and uncovered the role of AKAP8L in promoting colon cancer progression.

Indexed as

Colonic NeoplasmsGene Expression Regulation, NeoplasticA Kinase Anchor ProteinsGene ExpressionHumansPeroxisome Proliferator-Activated ReceptorsPrognosisRNA, MessengerRNA SplicingRNA Splicing FactorsTumor MicroenvironmentA Kinase Anchor ProteinsPeroxisome Proliferator-Activated ReceptorsRNA, MessengerRNA Splicing FactorsAKAP8Lcolon cancerprognosisrisk modelRNA splicing

Identifiers

PMID35792657
PMCPMC9530871
OpenAlexW4283827513

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.