ArticleJournal of personalized medicine2022
Personalized Prescription of Chemotherapy Based on Assessment of mRNA Expression of BRCA1, RRM1, ERCC1, TOP1, TOP2α, TUBβ3, TYMS, and GSTP1 Genes in Tumors Compared to Standard Chemotherapy in the Treatment of Non-Small-Cell Lung Cancer
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Review
- ERCC1/NGFR affects prognosis in basal-like breast cancer.European journal of medical research · 2025Article
- Genetic signatures ofOncology research · 2025Article
- Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.Cancer science · 2025Article
- Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Objectives: A growing body of evidence suggests the important role of chemosensitive gene expression in the prognosis of patients with lung cancer. However, studies on combined gene expression assessments for personalized prescriptions of chemotherapy regimens in patients have not yet been conducted. The aim of this work was to conduct a prospective study on the appointment of personalized chemotherapy in patients with non-small-cell lung cancer. Materials and methods: The present study analyzed 85 patients with lung cancer (stage IIB-IIIB). Within this group, 48 patients received individualized chemotherapy, and 37 patients received classical chemotherapy. In the individualized chemotherapy group, the mRNA expression levels of ERCC1, RRM1, TUBB3, TYMS, TOP1, TOP2α, BRCA1, and GSTP1 in lung tissues were measured by quantitative real-time PCR (qPCR), and an individual chemotherapy regimen was developed for each patient according to the results. Patients in the classical chemotherapy group received the vinorelbine/carboplatin regimen. Survival analyses were performed using the Kaplan−Meier method. Prognostic factors of metastasis-free survival (MFS) and overall survival (OS) of patients were identified via Cox’s proportional hazards regression model. Results: MFS and OS were significantly better in the personalized chemotherapy group compared to the classic chemotherapy group (MFS, 46.22 vs. 22.9 months, p = 0.05; OS, 58.6 vs. 26.9 months, p < 0.0001). Importantly, the best metastasis-free survival rates in the group with personalized ACT were achieved in patients treated with the paclitaxel/carboplatin regimen. Based on an assessment of chemosensitivity gene expression in the tumors, the classical chemotherapy strategy also increased the risk of death (HR = 14.82; 95% CI: 3.33−65.86; p < 0.000) but not metastasis (HR = 1.95; 95% CI: 0.96−3.98; p = 0.06) compared to the group of patients with chemotherapy. Conclusions: The use of combined ERCC1, RRM1, TUBB3, TYMS, TOP1, TOP2α, BRCA1, and GSTP1 gene expression results for personalized chemotherapy can improve treatment efficacy and reduce unnecessary toxicity.
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