A Bayesian approach to determine the composition of heterogeneous cancer tissue. 2018

Ashish Katiyar, and Anwoy Mohanty, and Jianping Hua, and Sima Chao, and Rosana Lopes, and Aniruddha Datta, and Michael L Bittner
Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843-3128, USA. ashish.katiyar13@tamu.edu.

Cancer Tissue Heterogeneity is an important consideration in cancer research as it can give insights into the causes and progression of cancer. It is known to play a significant role in cancer cell survival, growth and metastasis. Determining the compositional breakup of a heterogeneous cancer tissue can also help address the therapeutic challenges posed by heterogeneity. This necessitates a low cost, scalable algorithm to address the challenge of accurate estimation of the composition of a heterogeneous cancer tissue. In this paper, we propose an algorithm to tackle this problem by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework. The algorithm is analyzed and validated using synthetic data and experimental data. The experimental data is obtained from mixtures of three separate human cancer cell lines, HCT116 (Colorectal carcinoma), A2058 (Melanoma) and SW480 (Colorectal carcinoma). The algorithm provides a low cost framework to determine the composition of heterogeneous cancer tissue which is a crucial aspect in cancer research.

UI MeSH Term Description Entries
D009369 Neoplasms New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms. Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D011336 Probability The study of chance processes or the relative frequency characterizing a chance process. Probabilities
D002452 Cell Count The number of CELLS of a specific kind, usually measured per unit volume or area of sample. Cell Density,Cell Number,Cell Counts,Cell Densities,Cell Numbers,Count, Cell,Counts, Cell,Densities, Cell,Density, Cell,Number, Cell,Numbers, Cell
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000077341 Lapatinib A quinazoline derivative that inhibits EPIDERMAL GROWTH FACTOR RECEPTOR and HER2 (RECEPTOR, ERBB-2) tyrosine kinases. It is used for the treatment of advanced or metastatic breast cancer, where tumors overexpress HER2. GW 282974X,GW 572016,GW-282974X,GW-572016,GW282974X,GW572016,Lapatinib Ditosylate,N-(3-chloro-4-(((3-fluorobenzyl)oxy)phenyl)-6-(5-(((2-methylsulfonyl)ethyl)amino)methyl) -2-furyl)-4-quinazolinamine,Tykerb
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D000970 Antineoplastic Agents Substances that inhibit or prevent the proliferation of NEOPLASMS. Anticancer Agent,Antineoplastic,Antineoplastic Agent,Antineoplastic Drug,Antitumor Agent,Antitumor Drug,Cancer Chemotherapy Agent,Cancer Chemotherapy Drug,Anticancer Agents,Antineoplastic Drugs,Antineoplastics,Antitumor Agents,Antitumor Drugs,Cancer Chemotherapy Agents,Cancer Chemotherapy Drugs,Chemotherapeutic Anticancer Agents,Chemotherapeutic Anticancer Drug,Agent, Anticancer,Agent, Antineoplastic,Agent, Antitumor,Agent, Cancer Chemotherapy,Agents, Anticancer,Agents, Antineoplastic,Agents, Antitumor,Agents, Cancer Chemotherapy,Agents, Chemotherapeutic Anticancer,Chemotherapy Agent, Cancer,Chemotherapy Agents, Cancer,Chemotherapy Drug, Cancer,Chemotherapy Drugs, Cancer,Drug, Antineoplastic,Drug, Antitumor,Drug, Cancer Chemotherapy,Drug, Chemotherapeutic Anticancer,Drugs, Antineoplastic,Drugs, Antitumor,Drugs, Cancer Chemotherapy
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D045744 Cell Line, Tumor A cell line derived from cultured tumor cells. Tumor Cell Line,Cell Lines, Tumor,Line, Tumor Cell,Lines, Tumor Cell,Tumor Cell Lines

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