基于PIANOS系统的结直肠癌个体化风险分层

IF 14.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Du Cai, Haoning Qi, Qiuxia Yang, Huayu Li, Chenghang Li, Chuling Hu, Baowen Gai, Xu Zhang, Yize Mao, Feng Gao, Xiaojian Wu
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引用次数: 0

摘要

目前,结直肠癌(CRC)的预后生物标志物在不同的队列和平台上缺乏稳定性和普遍性,这对精确的患者分层提出了挑战。在这里,我们引入了一个独立于平台和无归一化的单样本分类器(PIANOS),旨在通过准确地将CRC患者分类为不同的风险组来改进治疗决策。利用562名患者的基因表达数据,采用基于排名的k-Top评分对(k-TSP)算法和重新采样,PIANOS在15个包含3666名结直肠癌患者的队列中进行了严格验证。它有效地区分高风险和低风险患者,优于105种现有模型,并在微阵列和RNA测序等技术上表现出强大的性能。基于pianos的分层被证实为无病生存的独立预测因子。此外,PIANOS区分不同风险类别的治疗反应,高风险患者对贝伐单抗的敏感性增加,低风险患者对化疗和免疫治疗的反应性增强。本研究报告了支持结直肠癌临床决策的重大进展,并为优化患者治疗策略提供了可靠的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Personalized risk stratification in colorectal cancer via PIANOS system

Personalized risk stratification in colorectal cancer via PIANOS system

Current prognostic biomarkers for colorectal cancer (CRC) lack stability and generalizability across different cohorts and platforms, challenging precise patient stratification. Here, we introduce a Platform Independent and Normalization Free Single-sample Classifier (PIANOS), designed to refine treatment decisions by accurately categorizing patients with CRC into distinct risk groups. Developed using gene expression data from 562 patients and employing a rank-based k-Top Scoring Pairs (k-TSP) algorithm alongside resampling, PIANOS was rigorously validated in 15 cohorts comprising 3666 patients with CRC. It effectively differentiates high-risk from low-risk patients, outperforms 105 existing models, and demonstrates robust performance across technologies like microarrays and RNA sequencing. PIANOS-based stratification is validated as an independent predictor of disease-free survival. Moreover, PIANOS discriminates treatment responses across risk categories, with high-risk patients showing increased sensitivity to bevacizumab and low-risk patients exhibiting enhanced responsiveness to chemotherapy and immunotherapy. This study reports significant advancements in supporting clinical decision-making for CRC and provides a reliable framework for optimizing patient treatment strategies.

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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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