Evidence map›Paper›PMID 39494300›Full record

ArticlePeerJ2024

Prognostic and therapeutic potential of gene profiles related to tertiary lymphoid structures in colorectal cancer.

Jinglu Yu, Yabin Gong, Xiaowei Huang, Yufang Bao

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Jinglu YuPuDong Traditional Chinese Medicine Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, Pudong New Area, China.
Yabin GongDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiaowei HuangDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yufang BaoPuDong Traditional Chinese Medicine Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, Pudong New Area, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of tertiary lymphoid structures (TLS) in oncology is gaining interest, particularly in colorectal carcinoma, yet a thorough analysis remains elusive. This study pioneered a novel TLS quantification system for prognostic and therapeutic response prediction in colorectal carcinoma, alongside a comprehensive depiction of the TLS landscape. Utilizing single-cell sequencing, we established a TLS score within the Tumor Immune Microenvironment (TIME). Analysis of tertiary lymphoid structure-related genes (TLSRGs) in 1,184 patients with colon adenocarcinoma/rectum adenocarcinoma (COADREAD) from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases led to the identification of two distinct molecular subtypes. Differentially expressed genes (DEGs) further segregated these patients into gene subtypes. A TLS score was formulated using gene set variation analysis (GSVA) and its efficacy in predicting immunotherapy outcomes was validated in two independent cohorts. High-scoring patients exhibited a 'hot' immune phenotype, correlating with enhanced immunotherapy efficacy. Key genes in our model, including

Indexed as

Colorectal NeoplasmsTertiary Lymphoid StructuresTumor MicroenvironmentAdenocarcinomaBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyMaleMiddle AgedPrognosisBiomarkers, TumorColon adenocarcinoma/rectum adenocarcinomaTertiary lymphoid structuresTherapeutic potential

Identifiers

PMID39494300
PMCPMC11531753

What OpenQuestion holds

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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.