Tumor subclones, where are you?

biorxiv(2022)

引用 0|浏览25
暂无评分
摘要
Introduction Tumor clonal structure is closely related to future progression, which has been mainly investigated via mutation abundance clustering in bulk sample. With limited studies at single-cell resolution, a systematic comparison of the two approaches is still lacking. Methods Here, using bulk and single-cell mutational data from liver and colorectal cancers, we would like to check the possibility of obtaining accurate tumor clonal structures from bulk-level analysis. We checked whether co-mutations determined by single-cell analysis had corresponding bulk variant allele frequency (VAF) peaks. We examined VAF ranges for different groups of co-mutations, and also the possibility of discriminating them. Results While bulk analysis suggested absence of subclonal peaks and possibly neutral evolution in some cases, single-cell analysis identified co-existing subclones. The overlaps of bulk VAF ranges for co-mutations from different subclones made it difficult to separate them, even with other parameter introduced. The difference between mutation cluster and tumor subclone is accountable for the challenge in bulk clonal deconvolution, especially in case of branched evolution as shown in colorectal cancer. Conclusion Complex subclonal structures and dynamic evolution are hidden under the seemingly clonal neutral pattern at bulk level, suggesting single-cell analysis will be needed to avoid under-estimation of tumor heterogeneity. Research Highlights Lay summary Systematic comparison of tumor clonal structure differences between bulk and single-cell mutational analysis is lacking. Here we performed such as study and found that complex subclonal structures and dynamic evolution are hidden under clonal neutral appearance at bulk level in liver and colorectal cancers, suggesting single-cell analysis will be needed to avoid under-estimation of tumor heterogeneity. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
关键词
tumor
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要