Evidence map›Paper›PMID 30917936›Full record

ArticleEBioMedicine2019

A robust panel based on tumour microenvironment genes for prognostic prediction and tailoring therapies in stage I-III colon cancer.

Rui Zhou, Dongqiang Zeng, Jingwen Zhang, Huiying Sun, Jianhua Wu, Nailin Li, Li Liang, Min Shi, Jianping Bin, Yulin Liao and 2 more

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
10.6field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 68 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

12 authors at 3 institutions in 2 countries.

Rui ZhouDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Dongqiang ZengDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Jingwen ZhangDepartment of Medicine Ultrasonics, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Huiying SunDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Jianhua WuDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Nailin LiDepartment of Medicine-Solna, Clinical Pharmacology Group, Karolinska University Hospital-Solna, Karolinska Institutet, Stockholm, Sweden.
Li LiangDepartment of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China; Department of Pathology, Southern Medical University, Guangzhou, Guangdong, PR China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Guangzhou, Guangdong, PR China.
Min ShiDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Jianping BinDepartment of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Yulin LiaoDepartment of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Na HuangDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China.
Wangjun LiaoDepartment of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, PR China. Electronic address: nfyyliaowj@163.com.
Nanfang Hospital · CNKarolinska University Hospital · SEKey Laboratory of Guangdong Province · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumour microenvironment (TME) is critical for the regulation of cancer development as well as therapy. The objective of the current study was the development of a robust prognostic model based on TME-relevant genes.

methodsFive public microarray datasets providing clinical information were obtained. The least absolute shrinkage and selection operator regression method was used to reduce the dimensionality of robust prognostic genes identified via the bootstrap method.

findingsWe established a prognostic panel, designated as tumour microenvironment risk score (TMRS), consisting of 100 genes. With specific risk score formulae, the TMRS panel possesses a strong ability to predict relapse-free survival and overall survival through both univariate and multivariate analyses. Compared with the TNM stage, the TMRS panel showed much higher predictive accuracy. Further analysis revealed that patients with higher TMRS scores exhibited no therapeutic benefits from adjuvant chemotherapy, probably due to the activation of stromal relevant pathways and infiltration of stromal cells. Besides colon cancer, the TMRS panel was also revealed to be a reliable tool for prognostic prediction and chemotherapeutic decision-making in gastric cancer. Its value in predicting immunotherapy outcomes was also confirmed in two other cohorts consisting of metastatic urothelial carcinoma patients and melanoma patients.

interpretationOur TMRS panel may be an effective tool for survival prediction and treatment guidance in patients with stage I-III colon cancer. FUND: This work was supported by the National Natural Science Foundation of China (No. 81772580) and Guangzhou Planed Project of Science and Technology (No. 201803010070).

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorColonic NeoplasmsComputational BiologyDatabases, GeneticFemaleGene Expression ProfilingHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasmsNeoplasm StagingPrognosisBiomarkers, TumorAdjuvant chemotherapyColon cancerImmunotherapyPrognosisTMRS

Identifiers

PMID30917936
PMCPMC6491960
OpenAlexW2937818441

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LicenceCC BY-NC-ND
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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.