Computational single-cell methods for predicting cancer risk.

IF 3.8 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Andrew E Teschendorff
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引用次数: 0

Abstract

Despite recent biotechnological breakthroughs, cancer risk prediction remains a formidable computational and experimental challenge. Addressing it is critical in order to improve prevention, early detection and survival rates. Here, I briefly summarize some key emerging theoretical and computational challenges as well as recent computational advances that promise to help realize the goals of cancer-risk prediction. The focus is on computational strategies based on single-cell data, in particular on bottom-up network modeling approaches that aim to estimate cancer stemness and dedifferentiation at single-cell resolution from a systems-biological perspective. I will describe two promising methods, a tissue and cell-lineage independent one based on the concept of diffusion network entropy, and a tissue and cell-lineage specific one that uses transcription factor regulons. Application of these tools to single-cell and single-nucleus RNA-seq data from stages prior to invasive cancer reveal that they can successfully delineate the heterogeneous inter-cellular cancer-risk landscape, identifying those cells that are more likely to turn cancerous. Bottom-up systems biological modeling of single-cell omic data is a novel computational analysis paradigm that promises to facilitate the development of preventive, early detection and cancer-risk prediction strategies.

预测癌症风险的单细胞计算方法。
尽管最近在生物技术方面取得了突破,但癌症风险预测仍然是一项艰巨的计算和实验挑战。要提高预防、早期检测和存活率,解决这一问题至关重要。在此,我简要总结了一些新出现的关键理论和计算挑战,以及有望帮助实现癌症风险预测目标的最新计算进展。重点是基于单细胞数据的计算策略,特别是自下而上的网络建模方法,这些方法旨在从系统生物学的角度以单细胞分辨率估算癌症干性和去分化。我将介绍两种很有前景的方法,一种是基于扩散网络熵概念的独立于组织和细胞系的方法,另一种是利用转录因子调控子的组织和细胞系特异性方法。将这些工具应用于侵袭性癌症前各阶段的单细胞和单核 RNA-seq 数据显示,它们可以成功地勾勒出细胞间的异质性癌症风险图谱,识别出那些更有可能转变成癌症的细胞。对单细胞奥米克数据进行自下而上的系统生物学建模是一种新的计算分析范式,有望促进预防、早期检测和癌症风险预测策略的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biochemical Society transactions
Biochemical Society transactions 生物-生化与分子生物学
CiteScore
7.80
自引率
0.00%
发文量
351
审稿时长
3-6 weeks
期刊介绍: Biochemical Society Transactions is the reviews journal of the Biochemical Society. Publishing concise reviews written by experts in the field, providing a timely snapshot of the latest developments across all areas of the molecular and cellular biosciences. Elevating our authors’ ideas and expertise, each review includes a perspectives section where authors offer comment on the latest advances, a glimpse of future challenges and highlighting the importance of associated research areas in far broader contexts.
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