Evidence map›Paper›PMID 38125666›Full record

ReviewHealth information science and systems2024

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine.

Shumin Ren, Jiakun Li, Julián Dorado, Alejandro Sierra, Humbert González-Díaz, Aliuska Duardo, Bairong Shen

Open access · greenAbstract readReview
In one paragraph

Review in Health information science and systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Overdiagnosis and Overtreatment in Prostate Cancer.Diseases (Basel, Switzerland) · 2025
    Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. 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

7 authors at 2 institutions in 2 countries.

Shumin RenDepartment of Urology and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041 China.
Jiakun LiDepartment of Urology and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041 China.
Julián DoradoDepartment of Computer Science and Information Technology, University of A Coruña, 15071 A Coruña, Spain.
Alejandro SierraDepartment of Computer Science and Information Technology, University of A Coruña, 15071 A Coruña, Spain.
Humbert González-DíazDepartment of Computer Science and Information Technology, University of A Coruña, 15071 A Coruña, Spain.
Aliuska DuardoDepartment of Computer Science and Information Technology, University of A Coruña, 15071 A Coruña, Spain.
Bairong ShenDepartment of Urology and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041 China.ORCID 0000-0003-2899-1531
Universidade da Coruña · ESSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Indexed as

Intelligent medicineMulti-omicsProstate cancerSystems medicineTranslational informatics

Identifiers

PMID38125666
PMCPMC10728428
OpenAlexW4389869348

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.