Ulaganathan Kayalvili, Puranam Kaushik, Mukta Srinivasulu, Hanumanth Surekha Rani
Department of Genetics, Osmania University, Hyderabad, Telangana, 500007, India.
Department of Surgical Oncology, MNJ Institute of Oncology and RCC, Hyderabad, Telangana, India.
J Cancer Res Clin Oncol. 2023 Nov;149(15):13645-13664. doi: 10.1007/s00432-023-05195-y. Epub 2023 Jul 30.
In this study, we aimed at profiling of luminal B breast cancer specific gene expression pattern in Indian women using mRNA-seq and validation based on TCGA expression data.
RNA isolated from luminal B tumor and adjacent normal tissues was used for library construction and sequencing. Reference-based assemblies of these reads were used for differential gene expression analysis using DeSeq2. The DEGs were evaluated using TCGA expression data. Kaplan-Meier survival method was used to evaluate association between genes showing luminal B specific differential expression pattern and breast cancer prognosis and statistical significance was assessed using log-rank test. Alternate splicing analysis was done using rmats.
Differential expression analysis identified 2371 differentially expressed genes (DEGs) in luminal B breast tumors in comparison with adjacent normal tissues of Indian Women. Of them, 1692 DEGs were validated using TCGA luminal B paired samples. Integration of this data with the DEGs obtained by comparative analysis of unpaired luminal B with luminal A unpaired samples from TCGA resulted in 291 DEGs showing luminal B specific expression pattern. Further, 26 genes of prognostic value were identified. Differential splicing analysis between luminal B tumors and adjacent normal tissues in our cohort led to the identification of 687 genes showing significant differential alternate splicing events.
This study profiled gene expression pattern of luminal B tumors of Indian women and identified 26 key genes of prognostic value for luminal B breast cancer. This study also profiled differential alternate splicing and identified important alternate splicing events in luminal B breast cancer.
在本研究中，我们旨在利用mRNA测序分析印度女性腔面B型乳腺癌特异性基因表达模式，并基于TCGA表达数据进行验证。
从腔面B型肿瘤及其相邻正常组织中分离出的RNA用于文库构建和测序。这些 reads 的基于参考的组装用于使用DeSeq2进行差异基因表达分析。使用TCGA表达数据评估差异表达基因（DEGs）。采用Kaplan-Meier生存法评估显示腔面B型特异性差异表达模式的基因与乳腺癌预后之间的关联，并使用对数秩检验评估统计学意义。使用rmats进行可变剪接分析。
差异表达分析确定了印度女性腔面B型乳腺肿瘤与相邻正常组织相比有2371个差异表达基因（DEGs）。其中，1692个DEGs使用TCGA腔面B型配对样本进行了验证。将该数据与通过对TCGA中未配对的腔面B型与未配对的腔面A型样本进行比较分析获得的DEGs整合，得到291个显示腔面B型特异性表达模式的DEGs。此外，还鉴定出26个具有预后价值的基因。我们队列中腔面B型肿瘤与相邻正常组织之间的差异剪接分析导致鉴定出687个显示显著差异可变剪接事件的基因。
本研究分析了印度女性腔面B型肿瘤的基因表达模式，鉴定出26个对腔面B型乳腺癌具有预后价值的关键基因。本研究还分析了差异可变剪接，并鉴定出腔面B型乳腺癌中重要的可变剪接事件。
