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利用 DawnRank 整合外显子组测序和 mRNA 测序,鉴定了参与固有免疫的基因,这些基因是印度队列中乳腺癌的驱动因素。

Integration of exome-seq and mRNA-seq using DawnRank, identified genes involved in innate immunity as drivers of breast cancer in the Indian cohort.

机构信息

Institute of Bioinformatics and Applied Biotechnology, Bengaluru, Karnataka, India.

Human Genetics, Children's Hospital of Philadelphia, Philadelphia, USA.

出版信息

PeerJ. 2023 Oct 2;11:e16033. doi: 10.7717/peerj.16033. eCollection 2023.

Abstract

Genetic heterogeneity influences the prognosis and therapy of breast cancer. The cause of disease progression varies and can be addressed individually. To identify the mutations and their impact on disease progression at an individual level, we sequenced exome and transcriptome from matched normal-tumor samples. We utilised DawnRank to prioritise driver genes and identify specific mutations in Indian patients. Mutations in the C3 and HLA genes were identified as drivers of disease progression, indicating the involvement of the innate immune system. We performed immune profiling on 16 matched normal/tumor samples using CIBERSORTx. We identified CD8+ve T cells, M2 macrophages, and neutrophils to be enriched in luminal A and T cells CD4naïve, natural killer (NK) cells activated, T follicular helper (Tfh) cells, dendritic cells activated, and neutrophils in triple-negative breast cancer (TNBC) subtypes. Weighted gene co-expression network analysis (WGCNA) revealed activation of T cell-mediated response in ER positive samples and Interleukin and Interferons in ER negative samples. WGCNA analysis also identified unique pathways for each individual, suggesting that rare mutations/expression signatures can be used to design personalised treatment.

摘要

遗传异质性影响乳腺癌的预后和治疗。疾病进展的原因各不相同,可以进行个体化治疗。为了在个体水平上识别突变及其对疾病进展的影响,我们对匹配的正常-肿瘤样本进行了外显子组和转录组测序。我们利用 DawnRank 来优先考虑驱动基因,并在印度患者中识别特定的突变。C3 和 HLA 基因的突变被确定为疾病进展的驱动因素,表明先天免疫系统的参与。我们使用 CIBERSORTx 对 16 对匹配的正常/肿瘤样本进行了免疫谱分析。我们发现,在腔 A 和 T 细胞 CD4naïve、自然杀伤 (NK) 细胞激活、滤泡辅助 T (Tfh) 细胞、树突状细胞激活和三阴性乳腺癌 (TNBC) 亚型中的中性粒细胞中,CD8+ve T 细胞、M2 巨噬细胞和中性粒细胞丰富。加权基因共表达网络分析 (WGCNA) 显示,在 ER 阳性样本中 T 细胞介导的反应和 ER 阴性样本中的白细胞介素和干扰素被激活。WGCNA 分析还为每个个体识别出独特的途径,表明罕见的突变/表达特征可用于设计个性化治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c9e3/10552747/45aa9758a992/peerj-11-16033-g001.jpg

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