Evidence map›Paper›PMID 37422541›Full record

ArticleJournal of cancer research and clinical oncology2023

Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity.

Yuting Zhang, Yinghui Ye, Anping Xu, Yulou Luo, Yutian Sun, Wei Zhang, Ling Ji

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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 4 institutions in 1 country.

Yuting Zhang *Department of Breast Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, 510000, China.
Yinghui Ye *Department of Laboratory Medicine, Peking University Shenzhen Hospital, Shenzhen, 518000, China.
Anping Xu *Department of Laboratory Medicine, Peking University Shenzhen Hospital, Shenzhen, 518000, China.
Yulou LuoDepartment of Breast Surgery, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, 830000, China.
Yutian SunDepartment of Medical Oncology, School of Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, 610000, China.
Wei ZhangDepartment of Breast Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, 510000, China. zhangwei@jnu.edu.cn.
Ling JiDepartment of Laboratory Medicine, Peking University Shenzhen Hospital, Shenzhen, 518000, China. 1120303921@qq.com.
Peking University Shenzhen Hospital · CNFirst Affiliated Hospital of Jinan University · CNUniversity of Electronic Science and Technology of China · CNXinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA).

methodsWe used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis.

resultsWe developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment.

conclusionMultidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA.

Indexed as

Breast NeoplasmsCysteineBreastFemaleHumansNomogramsPrognosisTumor MicroenvironmentCysteineBreast cancerCysteine metabolismDisulfidptosisImmune infiltrationPrognosisSingle-cell analysis

Identifiers

PMID37422541
PMCPMC11796888
OpenAlexW4383618723

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.