Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

We assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a Single Sample Classifier (SSC) using penalized logistic regression based on the most robust and replicable schema. We demonstrate that a tumor-intrinsic two subtype schema is most robust, replicable, and clinically relevant. We developed purity independent subtyping of tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX. Keywords: Expression profiling by array Analysis of gene expression in pancreatic adenocarcinoma (PDAC). For primary PDAC tumors, data include 16 flash frozen (FF), 1 formalin-fixed and paraffin embedded (FFPE) and 16 fine-needle aspiration (FNA) ; for patient derived xenograft (PDX), data include 18 FF and 7 FFPE samples.

本研究结合两项临床试验的结果，并通过对公开表达数据开展荟萃分析，对三种主流亚型分类方案进行评估，以考察亚型稳健性的统计学标准与整体临床相关性。随后，我们基于最具稳健性与可重复性的分类方案，采用惩罚逻辑回归构建了单样本分类器（Single Sample Classifier, SSC）。研究证实，肿瘤内在型双亚型分类方案具备最优的稳健性、可重复性及临床相关性。我们进一步开发了肿瘤纯度独立分型工具（Purity Independent Subtyping of Tumors, PurIST）——一款可在多种平台与样本类型中展现出稳健且高可重复性性能的单样本分类器。研究表明，PurIST分型与患者预后存在显著关联，且对FOLIFIRNOX的治疗响应具有重要指导意义。
关键词：基于芯片的表达谱分析；胰腺腺癌（pancreatic adenocarcinoma, PDAC）基因表达分析。
针对原发性胰腺腺癌肿瘤样本，数据集包含16份快速冷冻（FF）样本、1份福尔马林固定石蜡包埋（FFPE）样本及16份细针抽吸活检（FNA）样本；针对患者来源异种移植瘤（PDX）样本，数据集包含18份FF样本与7份FFPE样本。