Evidence map›Paper›PMID 37726845›Full record

SynthesisGenome medicine2023

Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome.

Jing Sun, Jianhui Zhao, Fangyuan Jiang, Lijuan Wang, Qian Xiao, Fengyan Han, Jie Chen, Shuai Yuan, Jingsun Wei, Susanna C Larsson and 6 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Genome medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 2 pooled it
53.9field-weighted citation impact, top 1% of its field
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

137 citing papers in PubMed, 2 syntheses or guidelines pooled it, 166 citations in OpenAlex.

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77 more citing papers are in PubMed but not listed here.

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

16 authors at 8 institutions in 4 countries.

Jing SunDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Jianhui ZhaoDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Fangyuan JiangDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Lijuan WangCentre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
Qian XiaoColorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Fengyan HanDepartment of Pathology and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Jie ChenDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Shuai YuanUnit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Jingsun WeiColorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Susanna C LarssonUnit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Honghe ZhangDepartment of Pathology and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Malcolm G DunlopCancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Susan M FarringtonCancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Kefeng Ding *Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Evropi Theodoratou *Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
Xue Li *Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. xueli157@zju.edu.cn.ORCID http://orcid.org/0000-0001-6880-2577
Second Affiliated Hospital of Zhejiang University · CNEdinburgh Cancer Research · GBZhejiang University · CNWomen's Hospital, School of Medicine, Zhejiang University · CNCentre for Global Health Research · CAKarolinska Institutet · SEUniversity of Edinburgh · GBUppsala University · SE

Funding

Cancer Research UK 18927Cancer Research UK 22804Cancer Research UK C31250/A22804Medical Research Council MC_PC_U127527198Medical Research Council MC_U127527198Medical Research Council MC_UU_00007/1Medical Research Council U127527198
6 · The paper itself

Abstract

backgroundThe proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC).

methodsProtein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets.

resultsCollectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC.

conclusionsThis study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

Indexed as

Colorectal NeoplasmsProteomeBiomarkersCalcium-Binding ProteinsExtracellular Matrix ProteinsGenome-Wide Association StudyHumansMatrix Metalloproteinase 2Membrane ProteinsBiomarkersCalcium-Binding ProteinsCHRDL2 protein, humanCLSTN3 protein, humanExtracellular Matrix ProteinsMatrix Metalloproteinase 2Membrane ProteinsProteomeBiomarkerColorectal cancerDrug targetProteinProteome-wide Mendelian randomization

Identifiers

PMID37726845
PMCPMC10508028
OpenAlexW4386864391

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.