scholarly journals Deep whole genome sequencing identifies recurrent genomic alterations in commonly-used breast cancer cell lines and patient derived xenograft models

2021 ◽  
Author(s):  
Niantao Deng ◽  
Andre Minoche ◽  
Kate Harvey ◽  
Andrei Goga ◽  
Alex Swarbrick
Keyword(s):  
Breast Cancer ◽  
Whole Genome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Cancer Cell Lines ◽  
Whole Genome ◽  
Breast Cancers ◽  
Genomic Alterations ◽  
Pdx Models

Abstract BackgroundBreast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions. ResultsHere we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1 , previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers. ConclusionsOur WGS data provides a comprehensive genome sequencing resource of these models.

scholarly journals Deep Whole Genome Sequencing Identifies Recurrent Genomic Alterations in Commonly-Used Breast Cancer Cell Lines and Patient Derived Xenograft Models

2021 ◽  
Author(s):  
Niantao Deng ◽  
Andre Minoche ◽  
Kate Harvey ◽  
Meng Li ◽  
Juliane Winkler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Whole Genome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Breast Cancer Cell ◽  
Breast Cancer Cell Lines ◽  
Whole Genome ◽  
Breast Cancers ◽  
Pdx Models

Abstract Background: Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions.Results: Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1, previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers. Conclusions: Our WGS data provides a comprehensive genome sequencing resource of these models.

scholarly journals Whole-genome sequencing of phenotypically distinct inflammatory breast cancers reveals similar genomic alterations to non-inflammatory breast cancers

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Xiaotong Li ◽  
Sushant Kumar ◽  
Arif Harmanci ◽  
Shantao Li ◽  
Robert R. Kitchen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Cancer Genome ◽  
Whole Genome ◽  
Breast Cancers ◽  
Genomic Alterations ◽  
Genomic Features ◽  
Clonal Architecture

Abstract Background Inflammatory breast cancer (IBC) has a highly invasive and metastatic phenotype. However, little is known about its genetic drivers. To address this, we report the largest cohort of whole-genome sequencing (WGS) of IBC cases. Methods We performed WGS of 20 IBC samples and paired normal blood DNA to identify genomic alterations. For comparison, we used 23 matched non-IBC samples from the Cancer Genome Atlas Program (TCGA). We also validated our findings using WGS data from the International Cancer Genome Consortium (ICGC) and the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We examined a wide selection of genomic features to search for differences between IBC and conventional breast cancer. These include (i) somatic and germline single-nucleotide variants (SNVs), in both coding and non-coding regions; (ii) the mutational signature and the clonal architecture derived from these SNVs; (iii) copy number and structural variants (CNVs and SVs); and (iv) non-human sequence in the tumors (i.e., exogenous sequences of bacterial origin). Results Overall, IBC has similar genomic characteristics to non-IBC, including specific alterations, overall mutational load and signature, and tumor heterogeneity. In particular, we observed similar mutation frequencies between IBC and non-IBC, for each gene and most cancer-related pathways. Moreover, we found no exogenous sequences of infectious agents specific to IBC samples. Even though we could not find any strongly statistically distinguishing genomic features between the two groups, we did find some suggestive differences in IBC: (i) The MAST2 gene was more frequently mutated (20% IBC vs. 0% non-IBC). (ii) The TGF β pathway was more frequently disrupted by germline SNVs (50% vs. 13%). (iii) Different copy number profiles were observed in several genomic regions harboring cancer genes. (iv) Complex SVs were more frequent. (v) The clonal architecture was simpler, suggesting more homogenous tumor-evolutionary lineages. Conclusions Whole-genome sequencing of IBC manifests a similar genomic architecture to non-IBC. We found no unique genomic alterations shared in just IBCs; however, subtle genomic differences were observed including germline alterations in TGFβ pathway genes and somatic mutations in the MAST2 kinase that could represent potential therapeutic targets.

scholarly journals Analysis of Aneuploidy Spectrum From Whole-Genome Sequencing Provides Rapid Assessment of Clonal Variation Within Established Cancer Cell Lines

2021 ◽  
Vol 20 ◽  
pp. 117693512110492
Author(s):  
Ahmed Ibrahim Samir Khalil ◽  
Anupam Chattopadhyay ◽  
Amartya Sanyal
Keyword(s):  
Whole Genome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Cancer Cell Lines ◽  
Easy Access ◽  
Clonal Variation ◽  
Whole Genome

Background: The revolution in next-generation sequencing (NGS) technology has allowed easy access and sharing of high-throughput sequencing datasets of cancer cell lines and their integrative analyses. However, long-term passaging and culture conditions introduce high levels of genomic and phenotypic diversity in established cell lines resulting in strain differences. Thus, clonal variation in cultured cell lines with respect to the reference standard is a major barrier in systems biology data analyses. Therefore, there is a pressing need for a fast and entry-level assessment of clonal variations within cell lines using their high-throughput sequencing data. Results: We developed a Python-based software, AStra, for de novo estimation of the genome-wide segmental aneuploidy to measure and visually interpret strain-level similarities or differences of cancer cell lines from whole-genome sequencing (WGS). We demonstrated that aneuploidy spectrum can capture the genetic variations in 27 strains of MCF7 breast cancer cell line collected from different laboratories. Performance evaluation of AStra using several cancer sequencing datasets revealed that cancer cell lines exhibit distinct aneuploidy spectra which reflect their previously-reported karyotypic observations. Similarly, AStra successfully identified large-scale DNA copy number variations (CNVs) artificially introduced in simulated WGS datasets. Conclusions: AStra provides an analytical and visualization platform for rapid and easy comparison between different strains or between cell lines based on their aneuploidy spectra solely using the raw BAM files representing mapped reads. We recommend AStra for rapid first-pass quality assessment of cancer cell lines before integrating scientific datasets that employ deep sequencing. AStra is an open-source software and is available at https://github.com/AISKhalil/AStra .

scholarly journals Deep whole-genome sequencing of 3 cancer cell lines on 2 sequencing platforms

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kanika Arora ◽  
Minita Shah ◽  
Molly Johnson ◽  
Rashesh Sanghvi ◽  
Jennifer Shelton ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Cancer Genomics ◽  
Variant Calling ◽  
Cancer Cell Lines ◽  
Whole Genome ◽  
Sequencing Platform ◽  
Sequencing Platforms

AbstractTo test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we performed whole-genome sequencing of 3 common cancer cell lines (COLO-829, HCC-1143 and HCC-1187) along with their matched normal cell lines to great sequencing depths (up to 278x coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, the use of combination of tools improves the accuracy of somatic variant calling. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.

scholarly journals Extracellular Calcium-Sensing Receptor Expression and Its Potential Role in Regulating Parathyroid Hormone-Related Peptide Secretion in Human Breast Cancer Cell Lines*

Endocrinology ◽  
2000 ◽  
Vol 141 (12) ◽  
pp. 4357-4364 ◽  
Author(s):  
Jennifer L. Sanders ◽  
Naibedya Chattopadhyay ◽  
Olga Kifor ◽  
Toru Yamaguchi ◽  
Robert R. Butters ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Human Breast Cancer ◽  
Cancer Cell Lines ◽  
Human Breast Cancer Cell ◽  
Breast Cancer Cell Lines ◽  
Breast Cancers ◽  
Human Breast

Abstract Metastasis of breast cancer to bone occurs with advanced disease and produces substantial morbidity. Secretion of PTH-related peptide (PTHrP) from breast cancer cells is thought to play a key role in osteolytic metastases and is increased by transforming growth factor-β (TGFβ), which is released from resorbed bone. Elevated extracellular calcium (Cao2+) also stimulates PTHrP secretion from various normal and malignant cells, an action that could potentially be mediated by the Cao2+-sensing receptor (CaR) originally cloned from the parathyroid gland. Indeed, we previously showed that both normal breast ductal epithelial cells and primary breast cancers express the CaR. In this study we investigated whether the MCF-7 and MDA-MB-231 human breast cancer cell lines express the CaR and whether CaR agonists modulate PTHrP secretion. Northern blot analysis and RT-PCR revealed bona fide CaR transcripts, and immunocytochemistry and Western analysis with a specific anti-CaR antiserum demonstrated CaR protein expression in both breast cancer cell lines. Furthermore, elevated Cao2+ and the polycationic CaR agonists, neomycin and spermine, stimulated PTHrP secretion dose dependently, with maximal, 2.1- to 2.3-fold stimulation. In addition, pretreatment of MDA-MB-231 cells overnight with TGFβ1 (0.2, 1, or 5 ng/ml) augmented both basal and high Cao2+-stimulated PTHrP secretion. Thus, in PTHrP-secreting breast cancers metastatic to bone, the CaR could potentially participate in a vicious cycle in which PTHrP-induced bone resorption raises the levels of Cao2+ and TGFβ within the bony microenvironment, which then act in concert to evoke further PTHrP release and worsening osteolysis.

scholarly journals New generation breast cancer cell lines developed from patient-derived xenografts

2020 ◽  
Vol 22 (1) ◽  
Author(s):  
Jessica Finlay-Schultz ◽  
Britta M. Jacobsen ◽  
Duncan Riley ◽  
Kiran V. Paul ◽  
Scott Turner ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Breast Cancers ◽  
Luminal A ◽  
New Generation

Abstract Background Breast cancer is a highly heterogeneous disease characterized by multiple histologic and molecular subtypes. While a myriad of breast cancer cell lines have been developed over the past 60 years, estrogen receptor alpha (ER)+ disease and some mutations associated with this subtype remain underrepresented. Here we describe six breast cancer cell lines derived from patient-derived xenografts (PDX) and their general characteristics. Methods Established breast cancer PDX were processed into cell suspensions and placed into standard 2D cell culture; six emerged into long-term passageable cell lines. Cell lines were assessed for protein expression of common luminal, basal, and mesenchymal markers, growth assessed in response to estrogens and endocrine therapies, and RNA-seq and oncogenomics testing performed to compare relative transcript levels and identify putative oncogenic drivers. Results Three cell lines express ER and two are also progesterone receptor (PR) positive; PAM50 subtyping identified one line as luminal A. One of the ER+PR+ lines harbors a D538G mutation in the gene for ER (ESR1), providing a natural model that contains this endocrine-resistant genotype. The third ER+PR−/low cell line has mucinous features, a rare histologic type of breast cancer. The three other lines are ER− and represent two basal-like and a mixed ductal/lobular breast cancer. The cell lines show varied responses to tamoxifen and fulvestrant, and three were demonstrated to regrow tumors in vivo. RNA sequencing confirms all cell lines are human and epithelial. Targeted oncogenomics testing confirmed the noted ESR1 mutation in addition to other mutations (i.e., PIK3CA, BRCA2, CCND1, NF1, TP53, MYC) and amplifications (i.e., FGFR1, FGFR3) frequently found in breast cancers. Conclusions These new generation breast cancer cell lines add to the existing repository of breast cancer models, increase the number of ER+ lines, and provide a resource that can be genetically modified for studying several important clinical breast cancer features.

Simultaneous, quantitative detection of multiple biomarkers in human breast cancers using multicolor nanoparticles

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 619-619
Author(s):  
A. H. Al-Hajj ◽  
M. V. Yezhelyev ◽  
T. Liu ◽  
R. M. O’Regan
Keyword(s):  
Breast Cancer ◽  
Growth Factor ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Growth Factor Receptor ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Breast Cancers ◽  
Human Breast

619 Background: Conventional methods of detecting breast cancer biomarkers are hampered by a lack of adequate quantification and/or an inability to detect multiple targets on small quantities of tissue. We have previously demonstrated that estrogen receptor (ER), progesterone receptor (PR) and HER2/neu (HER2) can be detected and quantified simultaneously using antibodies (Abs) directly conjugated to nanoparticles, called quantum dots (QDs), on single breast cancer sections (ASCO 2005). We have expanded our assay to use multicolored QDs conjugated directly to Abs (QD-Abs) to detect and quantify simultaneously ER, PR, and HER2, along with 3 putative biomarkers, epidermal growth factor receptor (EGFR), mammalian target of Rapamycin (mTOR), and insulin-like growth factor receptor (IGFR), in breast cancer cell lines and human breast cancers. Methods: We used multicolored QDs directly conjugated to primary Abs to detect the 6 proteins in breast cancer cell lines (MCF-7, BT474, MDA-231) and single sections of human breast cancers. The 6 proteins were quantified using spectral separation microscopy, and compared to Western blotting. Results: We detected all 6 proteins simultaneously using QD-Abs in breast cancer cell lines and breast tumors. Using hyper-spectral imaging and wavelength-resolved spectroscopy, we separated all 6 fluorescent signals, and quantified the expression of each protein detected using QD-Abs. Quantification of the biomarkers showed good correlation with Western blotting. Conclusions: These results are proof of principle that 6 proteins can be simultaneously quantified using QD-Abs in single breast cancer sections. The use of multiplex QDs offers a novel method of determining the proteome of an individual breast cancer on single breast cancer sections. With the expanding use of targeted therapies in breast cancer, the ability to detect multiple proteins on small breast cancer specimens using QD-Abs, could allow not only the accurate selection of therapy, but a unique method of determining the activity of specific targeted agents. No significant financial relationships to disclose.

AcornHRD: A novel tool to identify homologous recombination deficiency events in whole genome sequencing data.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15078-e15078
Author(s):  
Kai Liu ◽  
Xueyu Hao ◽  
Mengmeng Zhang ◽  
Mingwei Li ◽  
Wang Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Whole Genome Sequencing ◽  
Cell Line ◽  
Cell Lines ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Wild Type ◽  
Homologous Recombination Deficiency

e15078 Background: Recently, homologous recombination deficiency (HRD) scores are associated with the efficacy of Poly‐(ADP‐Ribose)‐Polymerase (PARP) inhibition and platinum-based chemotherapy in a variety of cancers. Evaluating HRD level in patients with cancers is becoming far more important and influential, so far, there is no standard method to be used in clinical. In this study, we developed an algorithm to detect HRD from next-generation sequencing (NGS) for finding additional patients may potentially benefit from target therapy. Methods: Forty-eight patients were enrolled, including breast cancer, ovarian cancer, prostatic cancer. Fifteen cell lines with breast cancer and endometrial carcinoma were collected from Cobioer biosciences co., LTD. Forty-eight Formalin-fixed, paraffin embedded (FFPE) samples and 15 cell lines were performed by DNA extracting. We developed an HRD score algorithm, termed as AcornHRD algorithm. HRD score was analyzed by whole-genome sequencing, and GATK mutect2 software was used to detect BRCA1/2mutation by deep sequencing. Results: BRCA1/2 deleterious mutations were observed in 20 patients (41.7%). HRD was explained by deficiencies in 17 patients (85.0%) with BRCA mutation, whereas eight HRD-high tumors were non- BRCA related (28.6%). Among BRCA wild-type patients, the corresponding percentage of HRD positive patients in breast cancer, ovarian cancer and prostate cancer were 36.3%, 37.5% and 11.1%, respectively. Similar results were also verified in the cell line datasets. The findings showed that 100% (3/3) BRCA1/2 deficient cell lines are also HRD-high. Furthermore, HRD scores were highly correlated with standard results in the cell line datasets. Conclusions: We here report the NGS-based HRD scores to distinguish similarly well between BRCA mutant and BRCA wild-type cases in a cohort of Chinese population. AcornHRD scores were highly associated with BRCA1/2 deficiency. AcornHRD algorithm can be a useful tool to detect HRD events in clinical settings.

scholarly journals Formin Proteins FHOD1 and INF2 in Triple-Negative Breast Cancer: Association With Basal Markers and Functional Activities

2018 ◽  
Vol 12 ◽  
pp. 117822341879224 ◽  
Author(s):  
Vanina D Heuser ◽  
Naziha Mansuri ◽  
Jasper Mogg ◽  
Samu Kurki ◽  
Heli Repo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Breast Cancers ◽  
Basal Like Breast Cancer

Basal-like breast cancer is an aggressive form of breast cancer with limited treatment options. The subgroup can be identified immunohistochemically, by lack of hormone receptor expression combined with expression of basal markers such as CK5/6 and/or epidermal growth factor receptor (EGFR). In vitro, several regulators of the actin cytoskeleton are essential for efficient invasion of basal-like breast cancer cell lines. Whether these proteins are expressed in vivo determines the applicability of these findings in clinical settings. The actin-regulating formin protein FHOD1 participates in invasion of the triple-negative breast cancer cell line MDA-MB-231. Here, we measure the expression of FHOD1 protein in clinical triple-negative breast cancers by using immunohistochemistry and further characterize the expression of another formin protein, INF2. We report that basal-like breast cancers frequently overexpress formin proteins FHOD1 and INF2. In cell studies using basal-like breast cancer cell lines, we show that knockdown of FHOD1 or INF2 interferes with very similar processes: maintenance of cell shape, migration, invasion, and proliferation. Inhibition of EGFR, PI3K, or mitogen-activated protein kinase activity does not alter the expression of FHOD1 and INF2 in these cell lines. We conclude that the experimental studies on these formins have implications in the clinical behavior of basal-like breast cancer.

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