Single cell DNA sequencing reveals punctuated and gradual clonal evolution in hepatocellular carcinoma

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.

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High-throughput Single-cell CNV Detection Reveals Clonal Evolution During Hepatocellular Carcinoma Recurrence

10.1101/2020.12.09.417626 ◽

2020 ◽

Author(s):

Liang Wu ◽

Yuzhou Wang ◽

Miaomiao Jiang ◽

Biaofeng Zhou ◽

Yunfan Sun ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Single Cell ◽

Clonal Selection ◽

Multiple Displacement Amplification ◽

Clonal Evolution ◽

Primary Tumour ◽

Dna Amplification ◽

Cellular Heterogeneity ◽

Cancer Evolution ◽

Cnv Detection

AbstractSingle-cell genomics provides substantial resources for dissecting cellular heterogeneity and cancer evolution, but classical DNA amplification-based methods are low-throughput and introduce coverage bias during sample preamplification. We developed a single-cell DNA library preparation method without preamplification in nanolitre scale (scDPN). The method has a throughput of up to 1,800 cells per run for copy number variation (CNV) detection. Also, it has a lower level of amplification bias and noise than the multiple displacement amplification (MDA) method and showed high sensitivity and accuracy based on evaluation in cell lines and tumour tissues. We used this approach to profile the tumour clones in paired primary and relapsed tumour samples of hepatocellular carcinoma (HCC). We identified 3 clonal subpopulations with a multitude of aneuploid alterations across the genome. Furthermore, we observed that a minor clone of the primary tumour containing additional alterations in chromosomes 1q, 10q, and 14q developed into the dominant clone in the recurrent tumour, indicating clonal selection during recurrence in HCC. Overall, this approach provides a comprehensive and scalable solution to understand genome heterogeneity and evolution.

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Clonal evolution and heterogeneity in advanced systemic mastocytosis revealed by single-cell DNA sequencing

Blood Advances ◽

10.1182/bloodadvances.2020003980 ◽

2021 ◽

Vol 5 (6) ◽

pp. 1733-1736

Author(s):

Ken-Hong Lim ◽

Jo-Ning Wu ◽

To-Yu Huang ◽

Jie-Yang Jhuang ◽

Yu-Cheng Chang ◽

...

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Systemic Mastocytosis ◽

Clonal Evolution

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Abstract 4696: High-throughput single-cell targeted DNA sequencing using an updated TapestriTMPlatform reveals rare clones and clonal evolution for multiple blood cancers

10.1158/1538-7445.sabcs18-4696 ◽

2019 ◽

Author(s):

Nianzhen Li ◽

Daniel Mendoza ◽

Adam Sciambi ◽

Mani Manivannan ◽

Jacob Ho ◽

...

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

High Throughput ◽

Clonal Evolution ◽

Multiple Blood

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Remarkably stable copy-number profiles in osteosarcoma revealed using single-cell DNA sequencing

10.1101/2021.08.30.458268 ◽

2021 ◽

Author(s):

Sanjana Rajan ◽

Simone Zaccaria ◽

Matthew V. Cannon ◽

Maren Cam ◽

Amy C. Gross ◽

...

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Genomic Instability ◽

Copy Number ◽

Fitness Landscape ◽

Clonal Evolution ◽

Response To Therapy ◽

Tumor Evolution ◽

Sequencing Data ◽

Recurrent Mutations

AbstractOsteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNAs) are the genetic drivers of disease. Models around genomic instability conflict-it is unclear if osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization of the fitness landscape or an early catastrophic event followed by stable maintenance of an abnormal genome. We address this question by investigating SCNAs in 12,019 tumor cells obtained from expanded patient tissues using single-cell DNA sequencing, in ways that were previously impossible with bulk sequencing. Using the CHISEL algorithm, we inferred allele- and haplotype-specific SCNAs from whole-genome single-cell DNA sequencing data. Surprisingly, we found that, despite extensive genomic aberrations, cells within each tumor exhibit remarkably homogeneous SCNA profiles with little sub-clonal diversification. Longitudinal analysis between two pairs of patient samples obtained at distant time points (early detection, relapse) demonstrated remarkable conservation of SCNA profiles over tumor evolution. Phylogenetic analysis suggests that the bulk of SCNAs was acquired early in the oncogenic process, with few new events arising in response to therapy or during adaptation to growth in distant tissues. These data suggest that early catastrophic events, rather than sustained genomic instability, drive formation of these extensively aberrant genomes. Overall, we demonstrate the power of combining single-cell DNA sequencing with an allele- and haplotype-specific SCNA inference algorithm to resolve longstanding questions regarding genetics of tumor initiation and progression, questioning the underlying assumptions of genomic instability inferred from bulk tumor data.

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Clonal Evolution of Acute Myeloid Leukemia Revealed by High-Throughput Single-Cell Genomics

10.1101/2020.02.07.925743 ◽

2020 ◽

Cited By ~ 5

Author(s):

Kiyomi Morita ◽

Feng Wang ◽

Katharina Jahn ◽

Jack Kuipers ◽

Yuanqing Yan ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Dna Sequencing ◽

Single Cell ◽

High Throughput ◽

Myeloid Leukemia ◽

Clonal Evolution ◽

Treatment Resistance ◽

Clonal Diversity ◽

History Of ◽

Acute Myeloid

SummaryOne of the pervasive features of cancer is the diversity of mutations found in malignant cells within the same tumor; a phenomenon called clonal diversity or intratumor heterogeneity. Clonal diversity allows tumors to adapt to the selective pressure of treatment and likely contributes to the development of treatment resistance and cancer recurrence. Thus, the ability to precisely delineate the clonal substructure of a tumor, including the evolutionary history of its development and the co-occurrence of its mutations, is necessary to understand and overcome treatment resistance. However, DNA sequencing of bulk tumor samples cannot accurately resolve complex clonal architectures. Here, we performed high-throughput single-cell DNA sequencing to quantitatively assess the clonal architecture of acute myeloid leukemia (AML). We sequenced a total of 556,951 cells from 77 patients with AML for 19 genes known to be recurrently mutated in AML. The data revealed clonal relationship among AML driver mutations and identified mutations that often co-occurred (e.g., NPM1/FLT3-ITD, DNMT3A/NPM1, SRSF2/IDH2, and WT1/FLT3-ITD) and those that were mutually exclusive (e.g., NRAS/KRAS, FLT3-D835/ITD, and IDH1/IDH2) at single-cell resolution. Reconstruction of the tumor phylogeny uncovered history of tumor development that is characterized by linear and branching clonal evolution patterns with latter involving functional convergence of separately evolved clones. Analysis of longitudinal samples revealed remodeling of clonal architecture in response to therapeutic pressure that is driven by clonal selection. Furthermore, in this AML cohort, higher clonal diversity (≥4 subclones) was associated with significantly worse overall survival. These data portray clonal relationship, architecture, and evolution of AML driver genes with unprecedented resolution, and illuminate the role of clonal diversity in therapeutic resistance, relapse and clinical outcome in AML.

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Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing

Cell Research ◽

10.1038/cr.2018.11 ◽

2018 ◽

Vol 28 (3) ◽

pp. 359-373 ◽

Cited By ~ 32

Author(s):

Meng Duan ◽

Junfeng Hao ◽

Sijia Cui ◽

Daniel L Worthley ◽

Shu Zhang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Single Cell ◽

Genome Sequencing ◽

Clonal Evolution ◽

Cell Genome ◽

Single Cell Genome

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Single-cell DNA sequencing reveals complex mechanisms of resistance to quizartinib

Blood Advances ◽

10.1182/bloodadvances.2020003398 ◽

2021 ◽

Vol 5 (5) ◽

pp. 1437-1441

Author(s):

Cheryl A. C. Peretz ◽

Lisa H. F. McGary ◽

Tanya Kumar ◽

Hunter Jackson ◽

Jose Jacob ◽

...

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Tumor Heterogeneity ◽

Clonal Evolution ◽

Mechanisms Of Resistance ◽

Single Cell Sequencing ◽

Key Points ◽

Complex Mechanisms

Key Points Single-cell sequencing exposes previously unmeasurable complexity of tumor heterogeneity and clonal evolution on quizartinib. Single-cell sequencing reveals on- and off-target mechanisms of resistance to quizartinib, which can preexist therapy.

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