Banerjee Sagarika, Wei Zhi, Tan Fei, Peck Kristen N, Shih Natalie, Feldman Michael, Rebbeck Timothy R, Alwine James C, Robertson Erle S
Department of Microbiology, University of Pennsylvania, 201 E Johnson Pavilion, 3610 Hamilton Walk, Philadelphia, PA 19104, USA.
Department of Computer Science, College of Computing Sciences, New Jersey Institute of Technology, GITC 4400, University Heights, Newark, NJ 07102, USA.
Sci Rep. 2015 Oct 15;5:15162. doi: 10.1038/srep15162.
Infectious agents are the third highest human cancer risk factor and may have a greater role in the origin and/or progression of cancers, and related pathogenesis. Thus, knowing the specific viruses and microbial agents associated with a cancer type may provide insights into cause, diagnosis and treatment. We utilized a pan-pathogen array technology to identify the microbial signatures associated with triple negative breast cancer (TNBC). This technology detects low copy number and fragmented genomes extracted from formalin-fixed paraffin embedded archival tissues. The results, validated by PCR and sequencing, define a microbial signature present in TNBC tissue which was underrepresented in normal tissue. Hierarchical clustering analysis displayed two broad microbial signatures, one prevalent in bacteria and parasites and one prevalent in viruses. These signatures demonstrate a new paradigm in our understanding of the link between microorganisms and cancer, as causative or commensal in the tumor microenvironment and provide new diagnostic potential.
感染因子是人类癌症的第三大风险因素,可能在癌症的起源和/或进展以及相关发病机制中发挥更大作用。因此,了解与某一癌症类型相关的特定病毒和微生物因子可能有助于深入了解病因、诊断和治疗。我们利用一种泛病原体阵列技术来识别与三阴性乳腺癌(TNBC)相关的微生物特征。该技术可检测从福尔马林固定石蜡包埋存档组织中提取的低拷贝数和片段化基因组。经PCR和测序验证的结果确定了TNBC组织中存在的一种微生物特征,而该特征在正常组织中含量较低。层次聚类分析显示出两种广泛的微生物特征,一种在细菌和寄生虫中普遍存在,另一种在病毒中普遍存在。这些特征在我们对微生物与癌症之间联系的理解中展现了一种新范式,即微生物在肿瘤微环境中作为致病因素或共生因素,并提供了新的诊断潜力。