ROCplot.com – transcriptome-based therapy response prediction

ROCplot.com is an online platform designed to validate predictive biomarkers by linking gene expression data to therapy response in breast, ovarian, colorectal cancer, and glioblastoma patients, as well as in vitro models and user-uploaded datasets. It generates ROC curves, calculates AUC values, and identifies optimal cutoffs to distinguish responders from non-responders.Key features:• ROC analysis across clinical samples, cell lines, and custom datasets• Available cancer types: breast, ovarian, colorectal, glioblastoma, and pan-cancer miRNA• Support for biomarker evaluation in chemotherapy, hormonal therapy, HER2-targeted, and immunotherapy contextsAs the first online ROC analysis tool at the transcriptome level, ROCplot.com is widely used to support biomarker-driven clinical decision-making.

ROCplot.com是一款在线分析平台，旨在通过将基因表达数据与乳腺癌、卵巢癌、结直肠癌、胶质母细胞瘤患者、体外实验模型及用户上传数据集的治疗应答进行关联，实现预测性生物标志物的验证。该平台可生成ROC曲线（Receiver Operating Characteristic curve）、计算曲线下面积（Area Under Curve, AUC）值，并确定最优截断值以区分治疗应答者与非应答者。
核心功能特性：
• 支持临床样本、细胞系及自定义数据集的ROC分析
• 支持的癌症类型包括：乳腺癌、卵巢癌、结直肠癌、胶质母细胞瘤及泛癌microRNA（miRNA）
• 支持在化疗、内分泌治疗、抗HER2靶向治疗及免疫治疗场景下开展生物标志物评估
作为首款面向转录组层面的在线ROC分析工具，ROCplot.com被广泛应用于支撑生物标志物驱动的临床决策制定。