Evidence map›Paper›PMID 38352751›Full record

ArticleHeliyon2024

A robust primary liver cancer subtype related to prognosis and drug response based on a multiple combined classifying strategy.

Jielian Deng, Guichuan Lai, Cong Zhang, Kangjie Li, Wenyan Zhu, Biao Xie, Xiaoni Zhong

Abstract read
In one paragraph

Article in Heliyon, 2024. 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. 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

7 authors.

Jielian DengDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Guichuan LaiDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Cong ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Kangjie LiDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Wenyan ZhuChongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, China.
Biao XieDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Xiaoni ZhongDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recurrence or resistance to treatment of primary liver cancer (PLL) is significantly related to the heterogeneity present within the tumor. In this study, we integrated prognosis risk score, mRNAsi index, and immune characteristics clustering to classify patients. The four subtypes obtained from the combined classification are associated with PLC's prognosis and drug response. In these subtypes, we observed mRNAsiH_ICCA subtype, the intersection between high mRNAsi and immune characteristics clustering A, had the worst prognosis. Specifically, immune characteristics clustering B (ICC_B) had high drug sensitivity in most drugs regardless of the value of mRNAsi. On the other hand, patients with low mRNAsi responded better to ten drugs including KU-55933 and NU7441, while patients with high mRNAsi might benefit from drugs like Leflunomide. By matching the specific characteristics of each combined subtype with the drug-induced cell line expression profile, we identified a group of potential therapeutic drugs that might regulate the expression of disease signature genes. We developed a feasible multiple combined typing strategy, hoping to guide therapeutic selection and promote the development of precision medicine.

Indexed as

Cancer molecular markersCancer stem cellsCombined classifyingDrug sensitivityGenotypingImmune microenvironmentPrognostic markers

Identifiers

PMID38352751
PMCPMC10861988

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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.