Evidence map›Paper›PMID 41934581›Full record

ArticleDiscover oncology2026

Integration of machine learning-based screening approaches and single-cell sequencing technique to identify cancer stemness genes associated with radiotherapy resistance in lung adenocarcinoma.

Xiao-Jia Cui, Bai-Xia Yang, Da-Ming Hang, Ye Tian, Guo-Mei Tai

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

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiao-Jia CuiThe Second Affiliated Hospital of Soochow University, Soochow, 215000, Jiangsu, PR China.
Bai-Xia YangTumor Hospital Affiliated to Nantong University, Nantong, 226361, Jiangsu, PR China.
Da-Ming HangTumor Hospital Affiliated to Nantong University, Nantong, 226361, Jiangsu, PR China.
Ye TianThe Second Affiliated Hospital of Soochow University, Soochow, 215000, Jiangsu, PR China. dryetian@126.com.
Guo-Mei TaiTumor Hospital Affiliated to Nantong University, Nantong, 226361, Jiangsu, PR China. guomeitai@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRadiotherapy resistance in lung adenocarcinoma (LUAD) complicates treatment and worsens outcomes. Growing evidence indicates that cancer stemness contributes to radioresistance and poor prognosis. This study aimed to develop a prognostic model based on radioresistant stemness genes and to identify candidate therapeutics.

methodsMachine-learning methods were used to identify key radioresistant stemness genes (RRSKGs) and construct a prognostic risk score, the Radioresistant Stemness Risk Prognostic Score (RRSRPS). Its prognostic value was evaluated by Cox regression. PLK1 was prioritized for mechanistic analysis. Single-cell RNA sequencing and immune deconvolution characterized PLK1’s cellular distribution and associations with immune infiltration. Molecular docking and flow cytometry examined the relationship between cisplatin and PLK1. Clonogenic assays and xenograft models assessed whether cisplatin enhances radiosensitivity.

resultsRRSRPS was an independent prognostic factor. PLK1 was identified as the target through screening. Knockdown of PLK1 significantly suppressed cell viability and enhanced radiosensitivity, increasing apoptosis by 40.06 ± 1.524% versus control. Mechanistic studies showed PLK1 acts via the JAK-STAT3 pathway, confirmed by rescue experiments. Drug sensitivity analysis and molecular docking identified cisplatin as a specific PLK1 inhibitor. Clonogenic and in vivo assays demonstrated that cisplatin combined with radiotherapy synergistically inhibited tumor growth, reducing tumor volume by 697 ± 41.81 mm³ compared to control.

conclusionsRRSRPS is a robust, independent prognostic indicator in LUAD. Cisplatin increases radiosensitivity, potentially via PLK1-related mechanisms, offering a feasible precision-medicine strategy for patients with radioresistant disease.

Indexed as

Cancer stem cellsLung adenocarcinomaMachine learningRadiotherapy resistanceSingle cell sequencing

Identifiers

PMID41934581
PMCPMC13199540

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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.