دورية أكاديمية
أعرض في EDS

Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference.

التفاصيل البيبلوغرافية
العنوان: Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference.
المؤلفون: Lynch AR; Carbone Cancer Center, University of Wisconsin-Madison, Madison, United States.; McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, United States., Arp NL; Carbone Cancer Center, University of Wisconsin-Madison, Madison, United States., Zhou AS; Carbone Cancer Center, University of Wisconsin-Madison, Madison, United States.; McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, United States., Weaver BA; Carbone Cancer Center, University of Wisconsin-Madison, Madison, United States.; McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, United States.; Department of Cell and Regenerative Biology, University of Wisconsin, Madison, United States., Burkard ME; Carbone Cancer Center, University of Wisconsin-Madison, Madison, United States.; McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, United States.; Division of Hematology Medical Oncology and Palliative Care, Department of Medicine University of Wisconsin, Madison, United States.
المصدر: ELife [Elife] 2022 Apr 05; Vol. 11. Date of Electronic Publication: 2022 Apr 05.
نوع المنشور: Journal Article; Research Support, N.I.H., Extramural
اللغة: English
بيانات الدورية: Publisher: eLife Sciences Publications, Ltd Country of Publication: England NLM ID: 101579614 Publication Model: Electronic Cited Medium: Internet ISSN: 2050-084X (Electronic) Linking ISSN: 2050084X NLM ISO Abbreviation: Elife Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Cambridge, UK : eLife Sciences Publications, Ltd., 2012-
مواضيع طبية MeSH: Chromosomal Instability*/genetics , Neoplasms*/genetics, Aneuploidy ; Bayes Theorem ; Chromosome Aberrations ; Chromosome Segregation/genetics ; Humans ; Karyotype ; Systems Analysis
مستخلص: Chromosomal instability (CIN)-persistent chromosome gain or loss through abnormal mitotic segregation-is a hallmark of cancer that drives aneuploidy. Intrinsic chromosome mis-segregation rate, a measure of CIN, can inform prognosis and is a promising biomarker for response to anti-microtubule agents. However, existing methodologies to measure this rate are labor intensive, indirect, and confounded by selection against aneuploid cells, which reduces observable diversity. We developed a framework to measure CIN, accounting for karyotype selection, using simulations with various levels of CIN and models of selection. To identify the model parameters that best fit karyotype data from single-cell sequencing, we used approximate Bayesian computation to infer mis-segregation rates and karyotype selection. Experimental validation confirmed the extensive chromosome mis-segregation rates caused by the chemotherapy paclitaxel (18.5 ± 0.5/division). Extending this approach to clinical samples revealed that inferred rates fell within direct observations of cancer cell lines. This work provides the necessary framework to quantify CIN in human tumors and develop it as a predictive biomarker.
Competing Interests: AL, NA, AZ, BW No competing interests declared, MB declares the following: Medical advisory board of Strata Oncology; Research funding from Abbvie, Genentech, Puma, Arcus, Apollomics, Loxo Oncology/Lilly, and Elevation Oncology. I hold patents on microfluidic device for drug testing, and for homologous recombination and super-resolution microscopy technologies. I declare all interests without adjudicating relationship to the published work
(© 2022, Lynch et al.)
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معلومات مُعتمدة: T32 GM008688 United States GM NIGMS NIH HHS; T32 GM081061 United States GM NIGMS NIH HHS; P30 CA014520 United States CA NCI NIH HHS; T32 GM008692 United States GM NIGMS NIH HHS; R01 GM141068 United States GM NIGMS NIH HHS; R01 CA234904 United States CA NCI NIH HHS; T32 GM140935 United States GM NIGMS NIH HHS; F31 CA254247 United States CA NCI NIH HHS; S10 RR025483 United States RR NCRR NIH HHS; T32 HG002760 United States HG NHGRI NIH HHS
فهرسة مساهمة: Keywords: agent-based modeling; aneuploidy; approximate Bayesian computation; cancer biology; computational biology; human; mitosis; single-cell sequencing; systems biology
Local Abstract: [plain-language-summary] DNA contains all the information that cells need to function. The DNA inside cells is housed in structures called chromosomes, and most healthy human cells contain 23 pairs. When a cell divides, all chromosomes are copied so that each new cell gets a complete set. However, sometimes the process of separating chromosomes is faulty, and new cells may get incorrect numbers of chromosomes during cell division. Cancer cells frequently exhibit this behavior, which is called chromosomal instability’, or CIN. Chromosomal instability affects many cancer cells with varying severity. In cancers with high chromosomal instability, the number of chromosomes may change almost every time the cells divide. These cancers are often the most aggressive and difficult to treat. Scientists can estimate chromosomal instability by counting differences in the number of chromosomes across many cells. However, many cells that are missing chromosomes die, resulting in inaccurate measures of chromosomal instability. To find a solution to this problem, Lynch et al. counted chromosomes in human cells with different levels of chromosomal instability and created a computer model to work out the relationship between chromosomal instability and chromosome number. The model could account for both living and dead cells, which gave more accurate results. Lynch et al. then confirmed the accuracy of their approach by using it on a group of cells treated with a chemotherapy drug that causes a known level of chromosomal instability. They also used existing data from breast and bowel cancer, which revealed that levels of chromosomal instability varied between one mistake per three to twenty cell divisions. Lower levels of chromosomal instability can be linked to a better prognosis for cancer patients, but it currently cannot be measured reliably. These results may help to reveal the causes of chromosomal instability and the role it has in cancer. If this method is successfully applied to patient samples, it could also improve our ability to predict how each cancer will progress and may lead to better treatments.
تواريخ الأحداث: Date Created: 20220405 Date Completed: 20220503 Latest Revision: 20240923
رمز التحديث: 20240923
مُعرف محوري في PubMed: PMC9054132
DOI: 10.7554/eLife.69799
PMID: 35380536
قاعدة البيانات: MEDLINE
الوصف
تدمد:2050-084X
DOI:10.7554/eLife.69799