scholarly journals Sweepstake evolution revealed by population-genetic analysis of copy-number alterations in single genomes of breast cancer

2017 ◽  
Vol 4 (9) ◽  
pp. 171060 ◽  
Author(s):  
Mamoru Kato ◽  
Daniel A. Vasco ◽  
Ryuichi Sugino ◽  
Daichi Narushima ◽  
Alexander Krasnitz
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Cancer Cells ◽  
Copy Number ◽  
Population Genetic ◽  
Single Cells ◽  
Genetic Alterations ◽  
Tumour Mass ◽  
Breast Cancers ◽  
Single Cell Sequencing

Single-cell sequencing is a promising technology that can address cancer cell evolution by identifying genetic alterations in individual cells. In a recent study, genome-wide DNA copy numbers of single cells were accurately quantified by single-cell sequencing in breast cancers. Phylogenetic-tree analysis revealed genetically distinct populations, each consisting of homogeneous cells. Bioinformatics methods based on population genetics should be further developed to quantitatively analyse the single-cell sequencing data. We developed a bioinformatics framework that was combined with molecular-evolution theories to analyse copy-number losses. This analysis revealed that most deletions in the breast cancers at the single-cell level were generated by simple stochastic processes. A non-standard type of coalescent theory, the multiple-merger coalescent model, aided by approximate Bayesian computation fit well with the data, allowing us to estimate the population-genetic parameters in addition to false-positive and false-negative rates. The estimated parameters suggest that the cancer cells underwent sweepstake evolution, where only one or very few parental cells produced a descendent cell population. We conclude that breast cancer cells successively substitute in a tumour mass, and the high reproduction of only a portion of cancer cells may confer high adaptability to this cancer.

scholarly journals Variations in Cell Surfaces of Estrogen Treated Breast Cancer Cells Detected by A Combined Instrument for Far-Field and Near-Field Microscopy

2002 ◽  
Vol 24 (2-3) ◽  
pp. 89-100 ◽  
Author(s):  
P. Perner ◽  
A. Rapp ◽  
C. Dressler ◽  
L. Wollweber ◽  
J. Beuthan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Surface Topography ◽  
Breast Cancer Cells ◽  
Light Transmission ◽  
Single Cells ◽  
Near Field ◽  
Far Field ◽  
Breast Cancers ◽  
General Behaviour

The response of single breast cancer cells (cell line T‐47D) to 17β‐estradiol (E2) under different concentrations was studied by using an instrument that allows to combine far‐field light microscopy with high resolution scanning near‐field (AFM/SNOM) microscopy on the same cell. Different concentrations of E2induce clearly different effects as well on cellular shape (in classical bright‐field imaging) as on surface topography (atomic force imaging) and absorbance (near‐field light transmission imaging). The differences range from a polygonal shape at zero via a roughly spherical shape at physiological up to a spindle‐like shape at un‐physiologically high concentrations. The surface topography of untreated control cells was found to be regular and smooth with small overall height modulations. At physiological E2concentrations the surfaces became increasingly jagged as detected by an increase in membrane height. After application of the un‐physiological high E2concentration the cell surface structures appeared to be smoother again with an irregular fine structure. The general behaviour of dose dependent differences was also found in the near‐field light transmission images. In order to quantify the treatment effects, line scans through the normalised topography images were drawn and a rate of co‐localisation between high topography and high transmission areas was calculated. The cell biological aspects of these observations are, so far, not studied in detail but measurements on single cells offer new perspectives to be empirically used in diagnosis and therapy control of breast cancers.

scholarly journals Reconstructing mutational lineages in breast cancer by multi-patient-targeted single cell DNA sequencing

2021 ◽  
Author(s):  
Nicholas Navin ◽  
Jake Leighton ◽  
Min Hu ◽  
Emi Sei ◽  
Funda Meric-Bernstam
Keyword(s):  
Breast Cancer ◽  
Dna Sequencing ◽  
Single Cell ◽  
Copy Number ◽  
Somatic Mutations ◽  
Single Cells ◽  
Tumor Evolution ◽  
Sequencing Method ◽  
Genomic Regions ◽  
Microfluidics Platform

Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells, however most genomic regions characterized in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq sequencing method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this data, we reconstructed mutational lineages and identified early mutational and copy number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggests that MPT can overcome technical obstacles for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.

scholarly journals LINE-1 Retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5’-single cell RNA-Seq

2021 ◽  
Author(s):  
Wilson McKerrow ◽  
Shane A. Evans ◽  
Azucena Rocha ◽  
John Sedivy ◽  
Nicola Neretti ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Early Development ◽  
Immune Cells ◽  
Copy Number ◽  
Single Cells ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Mouse Hippocampus

AbstractLINE-1 retrotransposons are known to be expressed in early development, in tumors and in the germline. Less is known about LINE-1 expression at the single cell level, especially outside the context of cancer. Because LINE-1 elements are present at a high copy number, many transcripts that are not driven by the LINE-1 promoter nevertheless terminate at the LINE-1 3’ UTR. Thus, 3’ targeted single cell RNA-seq datasets are not appropriate for studying LINE-1. However, 5’ targeted single cell datasets provide an opportunity to analyze LINE-1 expression at the single cell level. Most LINE-1 copies are 5’ truncated, and a transcript that contains the LINE-1 5’ UTR as its 5’ end is likely to have been transcribed from its promoter. We developed a method, L1-sc (LINE-1 expression for single cells), to quantify LINE-1 expression in 5’ targeted 10x genomics single cell RNA-seq datasets. Our method confirms that LINE-1 expression is high in cancer cells, but low or absent from immune cells. We also find that LINE-1 expression is elevated in epithelial compared to immune cells outside of the context of cancer and that it is also elevated in neurons compared to glia in the mouse hippocampus.

scholarly journals Targeted transcript quantification in single disseminated cancer cells after whole transcriptome amplification

2019 ◽  
Author(s):  
Franziska C. Durst ◽  
Ana Grujovic ◽  
Iris Ganser ◽  
Martin Hoffmann ◽  
Peter Ugocsai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Single Cell ◽  
Cancer Cells ◽  
Cell Lines ◽  
Single Cells ◽  
Qpcr Assay ◽  
Transcript Expression ◽  
Whole Transcriptome Amplification ◽  
Whole Transcriptome

AbstractGene expression analysis of rare or heterogeneous cell populations such as disseminated cancer cells (DCCs) requires a sensitive method allowing reliable analysis of single cells. Therefore, we developed and explored the feasibility of a quantitative PCR (qPCR) assay to analyze single-cell cDNA pre-amplified using a previously established whole transcriptome amplification (WTA) protocol. We carefully selected and optimized multiple steps of the protocol, e.g. re-amplification of WTA products, quantification of amplified cDNA yields and final qPCR quantification, to identify the most reliable and accurate workflow for quantitation of gene expression of the ERBB2 gene in DCCs. We found that absolute quantification outperforms relative quantification. We then validated the performance of our method on single cells of established breast cancer cell lines displaying distinct levels of HER2 protein. The different protein levels were faithfully reflected by transcript expression across the tested cell lines thereby proving the accuracy of our approach. Finally, we applied our method on patient-derived breast cancer DCCs. Here, we were able to measure ERBB2 expression levels in all HER2-positive DCCs. In addition, we could detect ERBB2 transcript expression even in HER2-negative DCCs, suggesting post-transcriptional mechanisms of HER2 loss in anti-HER2-treated DCCs. In summary, we developed a reliable single-cell qPCR assay applicable to measure distinct levels of ERBB2 in DCCs.

scholarly journals Characterizing the allele- and haplotype-specific copy number landscape of cancer genomes at single-cell resolution with CHISEL

2019 ◽  
Author(s):  
Simone Zaccaria ◽  
Benjamin J. Raphael
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Copy Number ◽  
Single Cells ◽  
Neutral Loss ◽  
Tumor Evolution ◽  
Whole Genome ◽  
Copy Numbers ◽  
Allele Specific ◽  
Total Copy Number

AbstractSingle-cell barcoding technologies have recently been used to perform whole-genome sequencing of thousands of individual cells in parallel. These technologies provide the opportunity to characterize genomic heterogeneity at single-cell resolution, but their extremely low sequencing coverage (<0.05X per cell) has thus far restricted their use to identification of the total copy number of large multi-megabase segments in individual cells. However, total copy numbers do not distinguish between the two homologous chromosomes in humans, and thus provide a limited view of tumor heterogeneity and evolution missing important events such as copy-neutral loss-of-heterozygosity (LOH). We introduce CHISEL, the first method to infer allele- and haplotype-specific copy numbers in single cells and subpopulations of cells by aggregating sparse signal across thousands of individual cells. We applied CHISEL to 10 single-cell sequencing datasets from 2 breast cancer patients, each dataset containing ≈2000 cells. We identified extensive allele-specific copy-number aberrations (CNAs) in these samples including copy-neutral LOH, whole-genome duplications (WGDs), and mirrored-subclonal CNAs in subpopulations of cells. These allele-specific CNAs alter the copy number of genomic regions containing well-known breast cancer genes including TP53, BRCA2, and PTEN but are invisible to total copy number analysis. We utilized CHISEL’s allele- and haplotype-specific copy numbers to derive a more refined reconstruction of tumor evolution: timing allele-specific CNAs before and after WGDs, identifying low-frequency subclones distinguished by unique CNAs, and uncovering evidence of convergent evolution. This reconstruction is supported by orthogonal analysis of somatic single-nucleotide variants (SNVs) obtained by pooling barcoded reads across clones defined by CHISEL.

scholarly journals Novel insights into breast cancer copy number genetic heterogeneity revealed by single-cell genome sequencing

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Timour Baslan ◽  
Jude Kendall ◽  
Konstantin Volyanskyy ◽  
Katherine McNamara ◽  
Hilary Cox ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Genetic Heterogeneity ◽  
Copy Number ◽  
Breast Cancers ◽  
Genomic Location ◽  
Cancer Genomes ◽  
Somatic Alterations ◽  
Cell Genome ◽  
Chromosomal Amplifications

Copy number alterations (CNAs) play an important role in molding the genomes of breast cancers and have been shown to be clinically useful for prognostic and therapeutic purposes. However, our knowledge of intra-tumoral genetic heterogeneity of this important class of somatic alterations is limited. Here, using single-cell sequencing, we comprehensively map out the facets of copy number alteration heterogeneity in a cohort of breast cancer tumors. Ou/var/www/html/elife/12-05-2020/backup/r analyses reveal: genetic heterogeneity of non-tumor cells (i.e. stroma) within the tumor mass; the extent to which copy number heterogeneity impacts breast cancer genomes and the importance of both the genomic location and dosage of sub-clonal events; the pervasive nature of genetic heterogeneity of chromosomal amplifications; and the association of copy number heterogeneity with clinical and biological parameters such as polyploidy and estrogen receptor negative status. Our data highlight the power of single-cell genomics in dissecting, in its many forms, intra-tumoral genetic heterogeneity of CNAs, the magnitude with which CNA heterogeneity affects the genomes of breast cancers, and the potential importance of CNA heterogeneity in phenomena such as therapeutic resistance and disease relapse.

scholarly journals Single Cell Genetic Profiling of Tumors of Breast Cancer Patients Aged 50 Years and Older Reveals Enormous Intratumor Heterogeneity Independent of Individual Prognosis

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3366
Author(s):  
Anna-Sophie Liegmann ◽  
Kerstin Heselmeyer-Haddad ◽  
Annette Lischka ◽  
Daniela Hirsch ◽  
Wei-Dong Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Genome Instability ◽  
Single Cells ◽  
Gene Mutations ◽  
Intratumor Heterogeneity ◽  
Breast Cancer Patients ◽  
Luminal A ◽  
Pik3ca Mutations

Purpose: Older breast cancer patients are underrepresented in cancer research even though the majority (81.4%) of women dying of breast cancer are 55 years and older. Here we study a common phenomenon observed in breast cancer which is a large inter- and intratumor heterogeneity; this poses a tremendous clinical challenge, for example with respect to treatment stratification. To further elucidate genomic instability and tumor heterogeneity in older patients, we analyzed the genetic aberration profiles of 39 breast cancer patients aged 50 years and older (median 67 years) with either short (median 2.4 years) or long survival (median 19 years). The analysis was based on copy number enumeration of eight breast cancer-associated genes using multiplex interphase fluorescence in situ hybridization (miFISH) of single cells, and by targeted next-generation sequencing of 563 cancer-related genes. Results: We detected enormous inter- and intratumor heterogeneity, yet maintenance of common cancer gene mutations and breast cancer specific chromosomal gains and losses. The gain of COX2 was most common (72%), followed by MYC (69%); losses were most prevalent for CDH1 (74%) and TP53 (69%). The degree of intratumor heterogeneity did not correlate with disease outcome. Comparing the miFISH results of diploid with aneuploid tumor samples significant differences were found: aneuploid tumors showed significantly higher average signal numbers, copy number alterations (CNAs) and instability indices. Mutations in PIKC3A were mostly restricted to luminal A tumors. Furthermore, a significant co-occurrence of CNAs of DBC2/MYC, HER2/DBC2 and HER2/TP53 and mutual exclusivity of CNAs of HER2 and PIK3CA mutations and CNAs of CCND1 and PIK3CA mutations were revealed. Conclusion: Our results provide a comprehensive picture of genome instability profiles with a large variety of inter- and intratumor heterogeneity in breast cancer patients aged 50 years and older. In most cases, the distribution of chromosomal aneuploidies was consistent with previous results; however, striking exceptions, such as tumors driven by exclusive loss of chromosomes, were identified.

scholarly journals Transcriptional coregualtor NUPR1 maintains tamoxifen resistance in breast cancer cells

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Lingling Wang ◽  
Jiashen Sun ◽  
Yueyuan Yin ◽  
Yanan Sun ◽  
Jinyi Ma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Critical Role ◽  
Endocrine Resistance ◽  
Autophagic Flux ◽  
Physical Interaction ◽  
Premature Senescence ◽  
Breast Cancers ◽  
Transcriptional Coregulator

AbstractTo support cellular homeostasis and mitigate chemotherapeutic stress, cancer cells must gain a series of adaptive intracellular processes. Here we identify that NUPR1, a tamoxifen (Tam)-induced transcriptional coregulator, is necessary for the maintenance of Tam resistance through physical interaction with ESR1 in breast cancers. Mechanistically, NUPR1 binds to the promoter regions of several genes involved in autophagy process and drug resistance such as BECN1, GREB1, RAB31, PGR, CYP1B1, and regulates their transcription. In Tam-resistant ESR1 breast cancer cells, NUPR1 depletion results in premature senescence in vitro and tumor suppression in vivo. Moreover, enforced-autophagic flux augments cytoplasmic vacuolization in NUPR1-depleted Tam resistant cells, which facilitates the transition from autophagic survival to premature senescence. Collectively, these findings suggest a critical role for NUPR1 as a transcriptional coregulator in enabling endocrine persistence of breast cancers, thus providing a vulnerable diagnostic and/or therapeutic target for endocrine resistance.

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