Evidence map›Paper›PMID 33819921›Full record

ArticleAging2021

Tumor infiltrating lymphocyte signature is associated with single nucleotide polymorphisms and predicts survival in esophageal squamous cell carcinoma patients.

Chen Suo, Huiyao Chen, Franciszek Binczyk, Renjia Zhao, Jiahui Fan, Xiaorong Yang, Ziyu Yuan, David Kreil, Paweł Łabaj, Tiejun Zhang and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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.

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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

15 authors.

Chen SuoDepartment of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Huiyao ChenDepartment of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Franciszek BinczykSilesian University of Technology, Data Mining Division, Gliwice, Poland.
Renjia ZhaoDepartment of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Jiahui FanState Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Xiaorong YangClinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China.
Ziyu YuanFudan University Taizhou Institute of Health Sciences, Taizhou, China.
David KreilIMBT Bioinformatics Research, Boku University Vienn, Vienna, Austria.
Paweł ŁabajMalopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
Tiejun ZhangDepartment of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Ming LuClinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China.
Li JinFudan University Taizhou Institute of Health Sciences, Taizhou, China.
Joanna PolańskaSilesian University of Technology, Data Mining Division, Gliwice, Poland.
Xingdong ChenFudan University Taizhou Institute of Health Sciences, Taizhou, China.
Weimin YeDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEsophageal cancer is the sixth leading cause of cancer-related death worldwide, and is associated with a poor prognosis. Stromal tumor infiltrating lymphocytes (sTIL) and certain single nucleotide polymorphisms (SNPs) have been found to be predictive of patient survival. In this study, we explored the association between SNPs and sTIL regarding the predictability of disease-free survival in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND

methodsWe collected 969 pathologically confirmed ESCC patients from 2010 to 2013 and genotyped 101 SNPs from 59 genes. The number of sTIL for each patient was determined using an automatic algorithm. A Kruskal-Wallis test was used to determine the association between genotype and sTIL. The genotypes and clinical factors related to survival were analyzed using a Kaplan-Meier curve, Cox proportional hazards model, and log-rank test.

resultsThe median age of the patients was 67 (42-85 years), there was a median follow-up of 851.5 days and 586 patients died. The univariable analysis showed that 10 of the 101 SNPs were associated with sTIL. Six SNPs were also associated with disease-free survival. A multivariable analysis revealed that sTIL, rs1801131, rs25487, and rs8030672 were independent prognostic markers for ESCC patients. The model combining SNPs, clinical characteristics and sTIL outperformed the model with clinical characteristics alone for predicting outcomes in ESCC patients.

conclusionWe discovered 10 SNPs associated with sTIL in ESCC and we built a model of sTIL, SNPs and clinical characteristics with improved prediction of survival in ESCC patients.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorDisease-Free SurvivalEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaFemaleGenotypeHumansLymphocytes, Tumor-InfiltratingMaleMiddle AgedPolymorphism, Single NucleotidePrognosisBiomarkers, Tumoresophageal squamous cell cancersingle nucleotide polymorphismsurvivaltumor infiltrating lymphocytes

Identifiers

PMID33819921
PMCPMC8064198

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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.