Biology subjects

He, K.-Y.

Publications and source records attributed to He, K.-Y..

3 recordsLinked to original sources

bioRxiv2022

Tumor subclones, where are you?

IntroductionTumor 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. MethodsHere, 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. ResultsWhile 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. ConclusionComplex 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 HighlightsO_LIBulk-level mutation abundance clusters are not equal to tumor subclones. C_LIO_LIDifferent groups of co-mutations could not be discriminated at bulk-level. C_LIO_LISingle-cell mutational analysis can identify rather than infer tumor subclones. C_LIO_LICo-existing tumor subclones may have clonal neutral appearance at bulk-level. C_LI Lay summarySystematic 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.

cancer biology↗

bioRxiv2021

Single-cell and single-variant resolution analysis of clonal evolution in human liver cancer

Genetic heterogeneity of tumor is closely related to clonal evolution, phenotypic diversity and treatment resistance. Such heterogeneity has been characterized in liver cancer at single-cell sub-chromosomal scale, and a more precise single-variant resolution analysis is lacking. Here we employed a strategy to analyze both the single-cell genomic mutations and transcriptomic changes in 5 patients with liver cancer. Target sequencing was done for a total of 480 single cells in a patient-specific manner. DNA copy number status of point mutations was obtained from single-cell mutational profiling. The clonal structures of liver cancers were then uncovered at single-variant resolution, and mutation combinations in single cells enabled reconstruction of their evolutionary history. A common origin but independent evolutionary fate was revealed for primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. The mutational signature suggested early evolutionary process may be related to specific etiology like aristolochic acids. By parallel single-cell RNA-Seq, the transcriptomic phenotype was found to be related with genetic heterogeneity in liver cancer. We reconstructed the single-cell and single-variant resolution clonal evolutionary history of liver cancer, and dissection of both genetic and phenotypic heterogeneity provides knowledge for mechanistic understanding of liver cancer initiation and progression.

genomics↗

bioRxiv2019

Single-cell dissection of a rare human prostate basal cell carcinoma

As a rare subtype of prostate carcinoma, basal cell carcinoma (BCC) has not been studied extensively and thus lacks systematic molecular characterization. Here we applied single-cell genomic amplification and RNA-Seq to a specimen of human prostate BCC (CK34{beta}E12+/P63+/PAP-/PSA-). The mutational landscape was obtained via whole exome sequencing of the amplification mixture of 49 single cells, and the 5 putative driver genes mutated are CASC5, NUTM1, PTPRC, KMT2C and TBX3. The top 3 nucleotide substitutions are C>T, T>C and C>A, similar to common prostate cancer. The distribution of the variant allele frequency values indicated these single cells are from the same tumor clone. The transcriptomes of 69 single cells were obtained, and they were clustered into tumor, stromal and immune cells based on their global transcriptomic profiles. The tumor cells specifically express basal cell markers like KRT5, KRT14 and KRT23, and epithelial markers EPCAM, CDH1 and CD24. The transcription factor (TF) co-variance network analysis showed that the BCC tumor cells have distinct regulatory networks. By comparison with current prostate cancer datasets, we found that some of the bulk samples exhibit basal-cell signatures. Interestingly, at single-cell resolution the gene expression patterns of prostate BCC tumor cells show uniqueness compared with that of common prostate cancer-derived circulating tumor cells. This study, for the first time, discloses the comprehensive mutational and transcriptomic landscapes of prostate BCC, which lays a foundation for the understanding of its tumorigenesis mechanism and provides new insights into prostate cancers in general.

cancer biology↗