Delineation of tumor, stromal and immune transcriptomes at the infiltrating interface of muscle invasive bladder cancer

项目摘要 肿瘤侵入膀胱粘膜下肌层的存在定义了从膀胱癌到膀胱癌的进展。 非致死性至致死性膀胱癌;然而，这一过程在分子水平上还没有得到很好的理解。基因组 和转录组学分析的肌肉浸润性膀胱癌（MIBC）最近确定的突变和基因 与已建立的MIBC相关的表达谱。虽然膀胱癌的一个重大进展 领域，这些分析不能确定个体肿瘤中激活的独特转录程序， 基质和免疫群体在MIBC的侵入界面。这主要是由于限制 浸润性肿瘤和相邻/混合的基质和浸润性免疫细胞的精确空间收集。作为 因此，早期的转录组学研究，甚至最近的研究使用单细胞RNAseq依赖于异质性， 大块肿瘤，包括非侵入性以及正常间质和免疫成分，空间距离 入侵边境。这种异质性使得精确地去卷积基因表达变得困难 肿瘤细胞、间质和浸润免疫细胞在直接侵袭性微环境中的独特特征， 环境我们假设不同的基因网络在个体肿瘤、间质和 在MIBC的侵入界面的免疫群体。RNAseq分析和生物信息学分析应该 揭示了来自个体群体的丰富和独特的转录组学特征。这项研究将 通过识别不同细胞群体的细胞和分子特征， 侵袭性进展。这些发现可能会导致对候选基因网络的检查， 作为生物学功能、潜在生物标志物鉴定和所需新治疗靶点的基础 适用于诊断为肌肉浸润性疾病或复发的膀胱癌患者。

Project Summary The presence of tumor invasion into the submucosal muscle of the bladder defines the progression from nonlethal to lethal bladder cancer; however, this process is not well understood at the molecular level. Genomic and transcriptomic profiling of muscle invasive bladder cancer (MIBC) has recently identified mutations and gene expression profiles associated with established MIBC. Although a major advancement in the bladder cancer field, these analyses were unable to determine the unique transcriptional programs activated in individual tumor, stromal and immune populations at the invasive interface of MIBC. This was primarily due to the limitations of accurate spatial collection of infiltrating tumor and adjacent/intermingled stroma and infiltrating immune cells. As a result, earlier transcriptomic studies and even recent studies using single cell RNAseq relied on heterogeneous bulk tumor, which includes both noninvasive as well as normal stroma and immune components spatially distant from the invasive border. This heterogeneity makes it difficult to accurately de-convolute gene expression signatures unique to tumor cells, stroma and infiltrating immune cells in the immediate invasive micro- environment. We hypothesize that distinct gene networks are activated in individual tumor, stromal and immune populations at the invasive interface of MIBC. RNAseq profiling and bioinformatic analysis should reveal enriched and distinct transcriptomic signatures from the individual populations. This research would provide positive impact by identifying cellular and molecular signatures of distinct cellular populations driving invasive progression. These findings could then lead to examination of candidate gene networks that will serve as the basis for biological function, potential biomarker identification and new therapeutic targets that are needed for bladder cancer patients who have been diagnosed with or have relapsed with muscle invasive disease.