Genomic Fabric Remodeling in Prostate Cancer

Prostate cancer is a leading cause of death among men but its genomic characterization and best therapeutic strategy are still under debate. The Genomic Fabric Paradigm (GFP) considers the transcriptome as a multi-dimensional mathematical object subjected to a dynamic set of expres-sion correlations among the genes. Here, GFP is applied to gene expression profiles of three (one primary, and two secondary) cancer nodules and the surrounding normal tissue from a surgically removed prostate tumor. GFP was used to determine the regulation and rewiring of the P53 signaling, apoptosis, prostate cancer and several other pathways involved in survival and pro-liferation of the cancer cells. Genes responsible for the block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy and sustained angiogenesis were found as differently regulated in the three cancer nodules with re-spect to the normal tissue. The analysis indicates that even histo-pathologically equally graded cancer nodules from the same tumor have substantially different transcriptomic organizations, raising legitimate questions about the validity of meta-analyses comparing large populations of healthy and cancer humans. The study suggests that GFP may provide a personalized alternative to the biomarkers’ approach of cancer genomics. Gene expressions were profiled in two equally graded (Gleason score 4+4=8/10) cancer nodules from a surgically removed prostate cancer Please note that [1] multiple yellow strategy was used to hybridize differently labelleld biological replicas with the microarray and then iteratively normalizing the expression data to the intra-array and inter-array median expression until the maximum error of estimate becomes less than 5% [2] Each raw data file contains raw data for two samples as indicated in the corresponding sample description field.

前列腺癌（Prostate cancer）是男性人群的主要致死病因之一，但其基因组特征解析与最优治疗策略仍存在诸多争议。基因组架构范式（Genomic Fabric Paradigm, GFP）将转录组视为一类多维数学对象，其特性由基因间动态变化的表达关联网络所调控。本研究将GFP用于分析1例原发癌结节、2例继发癌结节，以及手术切除的前列腺肿瘤中癌旁正常组织的基因表达谱数据。研究通过GFP解析了P53信号通路、细胞凋亡通路、前列腺癌相关通路及其他数种参与癌细胞存活与增殖的通路的调控模式与重连机制。结果发现，相较于正常组织，3例癌结节中涉及分化阻滞、凋亡逃逸、细胞永生化、抗生长信号不敏感、异常增殖、化疗耐药及持续血管生成的基因均呈现显著差异表达调控。分析结果表明，即便来自同一肿瘤、组织病理学分级一致的癌结节，其转录组架构也存在显著差异，这对比较大量健康与癌症人类人群的荟萃分析（meta-analyses）的有效性提出了合理质疑。本研究提示，GFP或可成为癌症基因组学生物标志物研究方法之外的个性化研究替代方案。本研究对2例分级一致（格里森评分（Gleason score）4+4=8/10）的手术切除前列腺癌癌结节开展了基因表达谱分析。请注意：[1] 研究采用多重黄色标记策略，将不同标记的生物学重复样本与微阵列进行杂交，并通过迭代将表达数据标准化至芯片内与芯片间的中位表达水平，直至最大估计误差低于5%；[2] 每份原始数据文件包含两份样本的原始数据，具体信息详见对应样本描述字段。