Evidence map›Paper›PMID 41930321›Full record

ReviewMedComm2026

Multiomics Research Strategies in Cancer: A Growing and Innovative Field.

Zhenhua Du, Xiaomei Liu, Zhi Lv, Bengang Wang, Yu Xia, Wala Abduljabbar Mohammed Al-Duais, Lirong Yan, Fuqiang Zhang, Yanke Li

Abstract readReview
In one paragraph

Review in MedComm, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Zhenhua DuDepartment of Gynaecology and Obstetrics Shengjing Hospital of China Medical University Shenyang China.
Xiaomei LiuDepartment of Gynaecology and Obstetrics Shengjing Hospital of China Medical University Shenyang China.
Zhi LvDepartment of Anorectal Surgery First Hospital of China Medical University Shenyang China.
Bengang WangDepartment of Hepatobiliary Surgery First Hospital of China Medical University Shenyang China.
Yu XiaDepartment of Gynaecology and Obstetrics Shengjing Hospital of China Medical University Shenyang China.
Wala Abduljabbar Mohammed Al-DuaisDepartment of Gynaecology and Obstetrics Shengjing Hospital of China Medical University Shenyang China.
Lirong YanThe First Laboratory of Cancer Institute First Hospital of China Medical University Shenyang China.
Fuqiang ZhangDepartment of Anorectal Surgery First Hospital of China Medical University Shenyang China.
Yanke LiDepartment of Anorectal Surgery First Hospital of China Medical University Shenyang China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a highly complex and heterogeneous disease involving multiple pathophysiological events. Despite significant advances in modern medicine, the molecular mechanisms of cancer are still largely unknown. Omics methods have opened new avenues for identifying cancer biomarkers and elucidating disease pathogenesis. However, single-omics approaches only provide a limited understanding of biological mechanisms. The comprehensive analysis of multiomics data will provide useful insights for the pathogenesis, identification of therapeutic targets, and discovery of biomarkers in cancer. Here, we reviewed the disease signatures of cancer. We then reviewed the current state of multiomics biomarkers research in cancer. To further delineate the upstream pathogenic changes and downstream molecular effects of cancer, we also discuss the current strategies for integrating multiomics data using deep learning approaches. In addition, single-cell and spatial omics are being used to guide treatment strategies, risk assessment, and early diagnosis, as well as their potential impact on precision medicine. Despite the relative youth of the field, the development of single-cell and spatial omics promises to provide a powerful tool for elucidating the pathogenesis of cancer.

Indexed as

biomarkerscancerdeep learningmultiomicsprecision medicinesingle‐cell omicsspatial omics

Identifiers

PMID41930321
PMCPMC13042694

What OpenQuestion holds

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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.