Evidence map›Paper›PMID 38807223›Full record

ArticleJournal of translational medicine2024

Generalizable transcriptome-based tumor malignant level evaluation and molecular subtyping towards precision oncology.

Dingxue Hu, Ziteng Zhang, Xiaoyi Liu, Youchun Wu, Yunyun An, Wanqiu Wang, Mengqi Yang, Yuqi Pan, Kun Qiao, Changzheng Du and 8 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 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. 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

18 authors.

Dingxue Hu *Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Ziteng Zhang *Hepato-Biliary Surgery Division, The Second Affiliated Hospital, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518100, China.
Xiaoyi Liu *Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Youchun Wu *Hepato-Biliary Surgery Division, The Second Affiliated Hospital, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518100, China.
Yunyun AnInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Wanqiu WangInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Mengqi YangInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Yuqi PanInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Kun QiaoThoracic Surgical Department, Shenzhen Third People's Hospital, The Second Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518100, China.
Changzheng DuInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
Yu ZhaoMolecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, 518107, China.
Yan LiDepartment of Biology, Southern University of Science and Technology, Shenzhen, 518055, China.
Jianqiang BaoDivision of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China.
Tao QinGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat- Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
Yue PanGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat- Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
Zhaohua XiaThoracic Surgical Department, Shenzhen Third People's Hospital, The Second Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518100, China. daoren_000113@126.com.
Xin ZhaoHepato-Biliary Surgery Division, The Second Affiliated Hospital, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518100, China. drzhaoxin@126.com.
Kun SunInstitute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China. sunkun@szbl.ac.cn.ORCID 0000-0002-9883-1616

Funding

National Key R&D Program of China 2022YFA0912700
6 · The paper itself

Abstract

In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients' prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients' survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

Indexed as

Gene Expression Regulation, NeoplasticNeoplasmsPrecision MedicineTranscriptomeCarcinoma, HepatocellularGene Expression ProfilingHumansLiver NeoplasmsMedical OncologyMutationPrognosisTumor MicroenvironmentHepatocellular carcinomaOncogeneSurvival analysisTumor suppressor

Identifiers

PMID38807223
PMCPMC11134716

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LicenceCC BY
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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.