Evidence map›Paper›PMID 38999959›Full record

ArticleInternational journal of molecular sciences2024

Comprehensive Analysis of the Function and Prognostic Value of TAS2Rs Family-Related Genes in Colon Cancer.

Suzhen Bi, Jie Zhu, Liting Huang, Wanting Feng, Lulu Peng, Liangqi Leng, Yin Wang, Peipei Shan, Weikaixin Kong, Sujie Zhu

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
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

10 authors.

Suzhen BiInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.ORCID 0009-0003-0043-4546
Jie ZhuInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, 00014 Helsinki, Finland.
Liting HuangInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Wanting FengInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Lulu PengInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Liangqi LengInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Yin WangInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Peipei ShanInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.
Weikaixin KongInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, 00014 Helsinki, Finland.
Sujie ZhuInstitute of Translational Medicine, College of Medicine, Qingdao University, Qingdao 266021, China.

Funding

The National Natural Science Foundation of China No.81903539Youth Innovation Team of Shandong Province Universities 2022KJ145
6 · The paper itself

Abstract

In the realm of colon carcinoma, significant genetic and epigenetic diversity is observed, underscoring the necessity for tailored prognostic features that can guide personalized therapeutic strategies. In this study, we explored the association between the type 2 bitter taste receptor (TAS2Rs) family-related genes and colon cancer using RNA-sequencing and clinical datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Our preliminary analysis identified seven TAS2Rs genes associated with survival using univariate Cox regression analysis, all of which were observed to be overexpressed in colon cancer. Subsequently, based on these seven TAS2Rs prognostic genes, two colon cancer molecular subtypes (Cluster A and Cluster B) were defined. These subtypes exhibited distinct prognostic and immune characteristics, with Cluster A characterized by low immune cell infiltration and less favorable outcomes, while Cluster B was associated with high immune cell infiltration and better prognosis. Finally, we developed a robust scoring system using a gradient boosting machine (GBM) approach, integrated with the gene-pairing method, to predict the prognosis of colon cancer patients. This machine learning model could improve our predictive accuracy for colon cancer outcomes, underscoring its value in the precision oncology framework.

Indexed as

Colonic NeoplasmsGene Expression Regulation, NeoplasticReceptors, G-Protein-CoupledAdultAgedAged, 80 and overCell LineFemaleHumansMaleMiddle AgedNomogramsPrognosisTaste Receptors, Type 2Receptors, G-Protein-CoupledTaste Receptors, Type 2colon cancerimmunotherapymachine learningtype 2 bitter taste receptor

Identifiers

PMID38999959
PMCPMC11241446

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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.