Evidence map›Paper›PMID 37821797›Full record

ArticleCellular oncology (Dordrecht, Netherlands)2024

Identifying cancer subtypes based on embryonic and hematopoietic stem cell signatures in pan-cancer.

Jiali Lei, Jiangti Luo, Qian Liu, Xiaosheng Wang

Abstract read
In one paragraph

Article in Cellular oncology (Dordrecht, Netherlands), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

4 authors.

Jiali LeiBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
Jiangti LuoBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
Qian LiuBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
Xiaosheng WangBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China. xiaosheng.wang@cpu.edu.cn.

Funding

China Pharmaceutical University 3150120001
6 · The paper itself

Abstract

purposeCancer cells with stem cell-like properties may contribute to cancer development and therapy resistance. The advancement of multi-omics technology has sparked interest in exploring cancer stemness from a multi-omics perspective. However, there is a limited number of studies that have attempted to subtype cancer by combining different types of stem cell signatures.

methodsIn this study, 10,323 cancer specimens from 33 TCGA cancer types were clustered based on the enrichment scores of six stemness gene sets, representing two types of stem cell backgrounds: embryonic stem cells (ESCs) and hematopoietic stem cells (HSCs).

resultsWe identified four subtypes of pan-cancer, termed StC1, StC2, StC3 and StC4, which displayed distinct molecular and clinical features, including stemness, genome integrity, intratumor heterogeneity, methylation levels, tumor microenvironment, tumor progression, responses to chemotherapy and immunotherapy, and survival prognosis. Importantly, this subtyping method for pan-cancer is reproducible at the protein level.

conclusionOur findings indicate that the ESC signature is an adverse prognostic factor in cancer, while the HSC signature and ratio of HSC/ESC signatures are positive prognostic factors. The subtyping of cancer based on ESC and HSC signatures may provide insights into cancer biology and clinical implications of cancer.

Indexed as

Embryonic Stem CellsHematopoietic Stem CellsNeoplasmsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplastic Stem CellsPrognosisTumor MicroenvironmentBiomarkers, TumorEmbryonic stem cell signatureHematopoietic stem cell signatureMulti-omicsPan-cancerSubtyping

Identifiers

PMID37821797
PMCPMC12973968

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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.