Evidence map›Paper›PMID 41283923›Full record

ArticleDiscover oncology2025

Multi-omics analysis reveals different cholesterol metabolism subtypes in colorectal cancer.

Yu Sun, Deyang Kong, Huiru Zhang, Jialiang Fan, Shuaibing Lu, Wenjing Yang, Renshen Xiang, Qi Zhang, Wei Pei, Lin Feng and 1 more

Abstract read
In one paragraph

Article in Discover oncology, 2025. 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. 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

11 authors.

Yu SunDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Deyang KongDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Huiru ZhangDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Jialiang FanState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 100021.
Shuaibing LuDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Wenjing YangDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Renshen XiangDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Qi ZhangDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Wei PeiDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China.
Lin FengState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 100021. fenglin@cicams.ac.cn.ORCID http://orcid.org/0000-0003-0951-713X
Haizeng ZhangDepartment of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China. haizengzhang@cicams.ac.cn.ORCID http://orcid.org/0000-0003-1433-3482

Funding

the CAMS Innovation Fund for Medical Sciences 2021-I2M-1-018the CAMS Innovation Fund for Medical Sciences 2021-I2M-1-021the National Key R&D Program of China 2022YFF0710603
6 · The paper itself

Abstract

backgroundCholesterol metabolism (CM) plays a critical role in the progression of colorectal cancer (CRC), yet its molecular and immunological implications remain incompletely understood. Therefore, we aimed to identify CRC subtypes according to CM-related genes and reveal their distinct characteristics.

methodsBased on CM-related genes, we applied unsupervised clustering to classify CRC into two subtypes using transcriptomic data from TCGA and comprehensively compared their transcriptomic, genomic and clinical characteristics. We utilized single-cell RNA sequencing data and classified the samples into two subtypes and investigated the distinctions in the tumor microenvironment (TME) between these subtypes.

resultsTwo distinct CM subtypes were identified: Subtype A, characterized by cholesterol esterification and storage, was associated with inflammatory activation and cellular senescence. This subtype exhibited a poor prognosis and reduced predicted response to chemotherapy and immunotherapy. Tumor cells in Subtype A exhibited characteristics of epithelial-mesenchymal transition and angiogenesis. The TME in Subtype A contained higher infiltration of myeloid cells, fibroblasts, and pericytes, with dominant immunosuppressive tumor-associated macrophages (TAMs), especially TAM_SPP1, which interacted closely with Fibro_IL32, promoting immune exclusion. In contrast, Subtype B was marked by enhanced cholesterol catabolism and regulation. Tumor cells in this subtype displayed features of proliferation and stem-like properties. It showed a more active immune microenvironment with increased plasma cell infiltration and fewer immunosuppressive TAMs. Finally, we constructed a prognostic signature and validated its performance across multiple datasets.

conclusionsThese findings provide comprehensive insights into CM subtypes in CRC, highlighting their clinical significance and potential therapeutic implications.

Indexed as

Cholesterol metabolismColorectal cancerPrognosisTumor microenvironment

Identifiers

PMID41283923
PMCPMC12644335

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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.