Evidence map›Paper›PMID 42724574›Full record

ArticleAmerican journal of cancer research2026

Procyanidin C1 combined with olaparib induces senescence in BRCA1-proficient breast cancer cells.

Chengsi Ren, Chengshi Fu, Xingtong Chen, Renfei Yang, Jinyong He, Anran Gao, Qunshan Su, Xiangyun Teng, Jianhua Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of cancer research, 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.

Chengsi RenMeizhou People's Hospital, Meizhou Academy of Medical Sciences Meizhou, Guangdong, China.
Chengshi FuMedical Laboratory Center, Maoming Hospital of Guangzhou University of Chinese Medicine Maoming, Guangdong, China.
Xingtong ChenMedical Laboratory Center, Maoming Hospital of Guangzhou University of Chinese Medicine Maoming, Guangdong, China.
Renfei YangHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences Hangzhou, Zhejiang, China.
Jinyong HeMedical Laboratory Center, Shunde Hospital of Guangzhou University of Chinese Medicine Foshan, Guangdong, China.
Anran GaoMedical Laboratory Center, Shunde Hospital of Guangzhou University of Chinese Medicine Foshan, Guangdong, China.
Qunshan SuMedical Laboratory Center, Shunde Hospital of Guangzhou University of Chinese Medicine Foshan, Guangdong, China.
Xiangyun TengMedical Laboratory Center, Maoming Hospital of Guangzhou University of Chinese Medicine Maoming, Guangdong, China.
Jianhua XuMedical Laboratory Center, Maoming Hospital of Guangzhou University of Chinese Medicine Maoming, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PARP inhibitors (PARPi) are effective only in BRCA1-mutated tumors, with BRCA1-proficient patients deriving minimal benefit. Here, we demonstrate that PCC1 persistently induces double-strand DNA breaks (DSBs) in BRCA1-proficient breast cancer cells. Critically, PARP inhibition blocks base excision repair (BER), leading to accumulation of DNA damage and direct activation of senescence programs. Compared to monotherapy, the combination of olaparib and PCC1 significantly enhanced cellular senescence and suppressed tumor growth. In sum, we developed a novel therapeutic regimen that extends the utility of PARP inhibitors to BRCA1-proficient breast cancer patients through synergistic co-targeting of DNA damage responses.

Indexed as

BRCA1-proficientbreast cancercellular senescencePARP inhibitorsProcyanidin C1

Identifiers

PMID42724574
PMCPMC13559285

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.