Literature DB >> 12062599

The role of p53 in radiation therapy outcomes for favorable-to-intermediate-risk prostate cancer.

Mark A Ritter1, Kennedy W Gilchrist, Marta Voytovich, Richard J Chappell, Bret M Verhoven.   

Abstract

PURPOSE: Some prostate cancers may have molecular alterations that render them less responsive to radiation therapy; identification of these alterations before treatment might allow improved treatment optimization. This study investigated whether p53, a potential molecular determinant, could predict long-term radiation therapy outcome in a restricted group of relatively favorable-risk prostate cancer patients treated uniformly with irradiation alone. METHODS AND MATERIALS: This study included 53 patients previously treated with radiotherapy for favorable-to-intermediate-risk prostate cancer. These patients were selected for relatively low pretreatment PSAs (< or =21 ng/mL) and Gleason scores (< or =7) to decrease the likelihood of nonlocalized disease, because disease localization was necessary to examine the efficacy of localized radiation therapy. The status of p53 was immunohistochemically assessed in paraffin-embedded pretreatment biopsy specimens, along with appropriate controls. This marker was selected based upon a usable mutation prevalence in early-stage prostate cancer and its potential linkage with radiation response via cell cycle, DNA repair, and cell death pathways. Correlation between p53 mutation and clinical outcome was analyzed in univariate and multivariate fashion and included conventional prognosticators, such as stage, grade, and PSA. Freedom from biochemical failure was determined using American Society for Therapeutic Radiology and Oncology criteria. Limitations of prior studies were potentially avoided by requiring adequate posttreatment follow-up (median follow-up in nonfailing patients of 5.1 years), as well as pretreatment PSA and Gleason scores that suggested localized disease, and uniformity of treatment.
RESULTS: The total group of 53 favorable-to-intermediate-risk patients demonstrated an actuarial biochemical failure rate of 35% at 5 years. Forty percent of all specimens had a greater than 10% labeling index for p53 mutation, and actuarial biochemical control was found to strongly and independently correlate with p53 status. Patients with higher p53 labeling indices demonstrated significantly higher PSA failure rates (p < 0.001). In contrast, p53 status did not correlate with pretreatment PSA, grade, or tumor stage. Similarly, pretreatment PSA (log-rank 0.22), Gleason score (log-rank 0.93), and T stage (log-rank 0.15) were not prognostic for outcome in this group of patients selected for their relatively favorable clinical characteristics.
CONCLUSIONS: (1) p53 status in pretreatment biopsies strongly predicted for long-term biochemical control after radiation therapy in favorable-to-intermediate-risk prostate cancer patients. (2) If validated in other independent clinical data sets, p53 status should be considered as a stratification factor in future clinical trials and could be useful in guiding treatment. Abnormal p53 status might favor surgical management, aggressive dose escalation, or p53-targeted therapy.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 12062599     DOI: 10.1016/s0360-3016(02)02781-5

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  10 in total

1.  mRNA Expression Profiles for Prostate Cancer following Fractionated Irradiation Are Influenced by p53 Status.

Authors:  Charles B Simone; Molykutty John-Aryankalayil; Sanjeewani T Palayoor; Adeola Y Makinde; David Cerna; Michael T Falduto; Scott R Magnuson; C Norman Coleman
Journal:  Transl Oncol       Date:  2013-10-01       Impact factor: 4.243

Review 2.  Molecular staging of prostate cancer in the year 2007.

Authors:  Thorsten Schlomm; Andreas Erbersdobler; Martina Mirlacher; Guido Sauter
Journal:  World J Urol       Date:  2007-03-02       Impact factor: 4.226

3.  Prognostic value of abnormal p53 expression in locally advanced prostate cancer treated with androgen deprivation and radiotherapy: a study based on RTOG 9202.

Authors:  Mingxin Che; Michelle DeSilvio; Alan Pollack; David J Grignon; Varagur Mohan Venkatesan; Gerald E Hanks; Howard M Sandler
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-08-08       Impact factor: 7.038

Review 4.  Tissue biomarkers for prostate cancer radiation therapy.

Authors:  P T Tran; R K Hales; J Zeng; K Aziz; T Salih; R P Gajula; S Chettiar; N Gandhi; A T Wild; R Kumar; J M Herman; D Y Song; T L DeWeese
Journal:  Curr Mol Med       Date:  2012-07-01       Impact factor: 2.222

5.  RNA-seq profiling of a radiation resistant and radiation sensitive prostate cancer cell line highlights opposing regulation of DNA repair and targets for radiosensitization.

Authors:  Arabella Young; Rachael Berry; Adele F Holloway; Nicholas B Blackburn; Joanne L Dickinson; Marketa Skala; Jessica L Phillips; Kate H Brettingham-Moore
Journal:  BMC Cancer       Date:  2014-11-04       Impact factor: 4.430

Review 6.  Mechanistic Insights into Molecular Targeting and Combined Modality Therapy for Aggressive, Localized Prostate Cancer.

Authors:  Alan Dal Pra; Jennifer A Locke; Gerben Borst; Stephane Supiot; Robert G Bristow
Journal:  Front Oncol       Date:  2016-02-16       Impact factor: 6.244

Review 7.  Drivers of Radioresistance in Prostate Cancer.

Authors:  Liam King; Nijole Bernaitis; David Christie; Russ Chess-Williams; Donna Sellers; Catherine McDermott; Wendy Dare; Shailendra Anoopkumar-Dukie
Journal:  J Clin Med       Date:  2022-09-24       Impact factor: 4.964

Review 8.  The role of treatment modality on the utility of predictive tissue biomarkers in clinical prostate cancer: a systematic review.

Authors:  Naveen Kachroo; Vincent J Gnanapragasam
Journal:  J Cancer Res Clin Oncol       Date:  2012-11-28       Impact factor: 4.553

Review 9.  Genomic and Histopathological Tissue Biomarkers That Predict Radiotherapy Response in Localised Prostate Cancer.

Authors:  Anna Wilkins; David Dearnaley; Navita Somaiah
Journal:  Biomed Res Int       Date:  2015-10-04       Impact factor: 3.411

10.  A mathematical model of P53 gene regulatory networks under radiotherapy.

Authors:  J P Qi; S H Shao; Jinli Xie; Y Zhu
Journal:  Biosystems       Date:  2007-03-06       Impact factor: 1.973

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.