Evidence map›Paper›PMID 37435206›Full record

ArticleJournal of gastrointestinal oncology2023

A risk model constructed using 14 N

Yajun Huai, Liting Lai, Yuanhui Ren, Bowen Yang, Shasha Yu, Shanshan Wang, Jinhong Mei

Abstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Yajun HuaiDepartment of Oncology, First Affiliated Hospital of Nanchang University, Nanchang, China.
Liting LaiDepartment of Oncology, First Affiliated Hospital of Nanchang University, Nanchang, China.
Yuanhui RenInstitute of Molecular Pathology, Nanchang University, Nanchang, China.
Bowen YangInstitute of Molecular Pathology, Nanchang University, Nanchang, China.
Shasha YuNanchang Medical College, School of Basic Medical Sciences, Nanchang, China.
Shanshan WangInstitute of Molecular Pathology, Nanchang University, Nanchang, China.
Jinhong MeiInstitute of Molecular Pathology, Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colorectal cancer (CRC) remains the most common gastrointestinal malignancy. Despite multimodal therapy, its mortality is high due to recurrence and metastasis. This study developed and verified a risk model consisting of 14 N Methods: The gene expression profiles and clinical data of 446 patients with CRC were retrieved from The Cancer Genome Atlas (TCGA). 14 lncRNAs were screened using the Gene Co-expression Network (corFilter =0.5, P<0.001), and univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct the optimal risk model. The predictive performance and clinical applicability of the model were next verified. In addition, we performed Gene Ontology (GO) enrichment analysis to identify potential biological functions and detected the difference in tumor mutational burden (TMB), immune function, and sensitivity to immunotherapy and other drugs between the high- and low-risk groups to evaluate the application of the constructed risk model in depth. Results: The model was found to be an appropriate marker for predicting the prognosis of patients with CRC, independent of other clinical features, and demonstrated good precision and broad clinical applicability. It correlated with pathways in the development of cancer and immune-related functions, and patients in the high-risk group had higher tumor immune dysfunction and escape (TIDE) scores. Furthermore, we found significant differences in the overall survival (OS) between patients in the high- and low-tumor mutation burden (TMB) groups, which may work in conjunction with the constructed model to better predict patients' prognosis. Finally, we identified 12 drugs, including A-443654 and sorafenib, with lower half maximal inhibitory concentration (IC Conclusions: We constructed a risk model based on 14 m

Indexed as

colorectal cancer (CRC)long noncoding RNA (lncRNA)N6-methyladenosine (m6A)prognosticrisk model

Identifiers

PMID37435206
PMCPMC10331747

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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.