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揭示有前途的乳腺癌生物标志物：结合生物信息学分析和实验验证的综合方法。

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification.

机构信息

Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.

Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.

出版信息

BMC Cancer. 2024 Jan 31;24(1):155. doi: 10.1186/s12885-024-11913-7.

DOI:10.1186/s12885-024-11913-7
PMID:38291367
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10829368/
Abstract

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.

摘要

背景

乳腺癌仍然是全球范围内的重大健康挑战，因此需要识别可靠的生物标志物，以进行早期检测、准确的预后判断和靶向治疗。

材料与方法

对 TCGA 数据库中的乳腺癌 RNA 表达数据进行分析，以鉴定差异表达基因（DEGs）。使用随机森林分析选择前 500 个上调的 DEGs 进行进一步研究，以鉴定重要基因。这些基因基于其作为诊断生物标志物的潜力、在乳腺癌组织中的过表达以及在正常女性组织中的低中位表达进行评估。使用各种验证方法，包括在线工具和定量实时 PCR（qRT-PCR），来验证所鉴定基因作为乳腺癌生物标志物的潜力。

结果

研究在 100 个具有较高重要性评分的基因中确定了 4 个过表达基因（CACNG4、PKMYT1、EPYC 和 CHRNA6）。qRT-PCR 分析证实这些基因在乳腺癌患者中的表达明显高于正常样本。

结论

这些发现表明 CACNG4、PKMYT1、EPYC 和 CHRNA6 可能作为乳腺癌诊断的有价值的生物标志物，而 PKMYT1 可能也具有预后意义。此外，CACNG4、CHRNA6 和 PKMYT1 有望成为潜在的治疗靶点。这些发现有可能推进乳腺癌的诊断方法和治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/f0a38ad6d3a1/12885_2024_11913_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/2b97c084bed1/12885_2024_11913_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/05131f087620/12885_2024_11913_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/21d1467bdcb9/12885_2024_11913_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/51f0e4624185/12885_2024_11913_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/f0a38ad6d3a1/12885_2024_11913_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/2b97c084bed1/12885_2024_11913_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/05131f087620/12885_2024_11913_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/21d1467bdcb9/12885_2024_11913_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/51f0e4624185/12885_2024_11913_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a03f/10829368/f0a38ad6d3a1/12885_2024_11913_Fig5_HTML.jpg

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