Literature DB >> 18386191

A quantitative overview of radiosensitivity of human tumor cells across histological type and TP53 status.

Jerry R Williams1, Yonggang Zhang, Haoming Zhou, Daila S Gridley, Cameron J Koch, James Russell, James S Slater, John B Little.   

Abstract

PURPOSE: We have previously shown in a limited number of tumor cell lines derived from only two histological types that clonogenic survival patterns fall into radiosensitivity groups, each group associating with a specific genotype. We now establish a global, quantitative description of human tumor cells based on genotype-dependent radiosensitivity across histological types.
METHODS: We measure clonogenic radiosensitivity in 39 human tumor cell lines that vary in histological type (colorectal, glioblastoma, prostate, bladder, teratoma, breast, melanoma and liver) and expression of several genes purported to influence radiosensitivity: ATM (ataxia telangiectasia mutated), TP53 (tumor protein 53), CDKN1A (cyclin-dependent kinase N1A), 14-3-3sigma (an isoform of the 14-3-3 gene) and DNA mismatch repair genes . For each survival curve we use the linear-quadratic model and a linear-linear model to extract multiple coefficients and seek correlation across histological types.
RESULTS: Under one-parameter analysis, survival rate at circa 2 Gy, cell lines segregate into two major, statistically-significant groups that correlate with TP53 status (wildtype versus mutant). Under two-parameter analysis, cell lines segregate into four radiosensitivity groups based on correlations between response at lower doses (ca. 2 Gy) and a component of response to higher doses (>4 Gy).
CONCLUSIONS: Intrinsic radiosensitivity of 39 human tumor cell lines segregate into distinct genotype-dependent radiosensitivity groups that associate with mutATM, wtTP53, mutTP53, and an unidentified factor in some glioblastoma cells. Genotype-dependent radiosensitivity underlies histology-dependent variation in radiosensitivity. Our analysis establishes a quantitative overview of radiosensitivity that can predict possible response of human tumors to radiotherapy protocols.

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Year:  2008        PMID: 18386191     DOI: 10.1080/09553000801953342

Source DB:  PubMed          Journal:  Int J Radiat Biol        ISSN: 0955-3002            Impact factor:   2.694


  20 in total

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