Evidence map›Paper›PMID 41908092›Full record

ReviewOncoTargets and therapy2026

Research Advances on Targets and Mechanisms in Cancers Complicated by Cardiovascular Diseases.

Jianing Li, Peili Wang

Abstract readReview
In one paragraph

Review in OncoTargets and therapy, 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

2 authors.

Jianing LiGraduate School, Heilongjiang University of Chinese Medicine, Harbin, People's Republic of China.
Peili WangXiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Cancers complicated by cardiovascular diseases (CVDs) are increasingly becoming major limiting factors affecting patients' long-term quality of life and clinical outcomes. Systematic identification of therapeutic targets and their clinical development status is crucial for optimizing treatment strategies. Therefore, this study aimed to establish a target-based analytical framework to systematically map the distribution, developmental stage, maturity, and mechanistic characteristics of clinical trials investigating tumors co-occurring with CVD, thereby identifying potential therapeutic targets. Patients and Methods: We analyzed clinical trial data on treatments for cancers complicated by CVDs. A total of 58 clinical trials were included and examined across multiple dimensions, including target distribution, development stage, and disease relevance. Results: Forty-five therapeutic targets were identified, with coagulation Factor X, thrombin, and serpin family C member 1 (SERPINC1) emerging as high-frequency core targets. Most studies focused on coagulation, inflammation, and endothelial pathways. Significant variations were observed in completion status and research phase across different targets, with some demonstrating dual therapeutic and cardiovascular regulatory potentials. Conclusion: Coagulation and endothelium-related targets emerged as key links between cancer progression and cardiovascular complications. SERPINC1 and 3-hydroxy-3-methylglutaryl-CoA reductase showed potential for synergistic therapy. This study provides a comprehensive overview of targeted therapies for tumors with concomitant CVD, revealing key pathways and under-explored mechanisms. It offers data-driven insights and directional guidance for precision treatment design.

Indexed as

cancercardiovascular complicationcardiovascular diseaseclinical trialtherapeutic target

Identifiers

PMID41908092
PMCPMC13021555

What OpenQuestion holds

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Registered trials

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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.