BACKGROUND: There is increasing evidence linking development and progression of cancer to an accumulation of mutations at the genomic level. The most frequently mutated gene known to date in sporadic breast cancer appears to be the tumor suppressor gene p53. This study was designed to determine the frequency of p53 gene mutations in primary breast cancer, to correlate the presence of p53 mutations with established clinicopathologic parameters, including the estrogen receptor (ER) and progesterone receptor (PR) status, and to assess the prognostic significance of p53 mutations regarding patient survival. METHODS: We examined the p53 gene in genomic DNA samples from 192 primary breast cancers. Using denaturant gradient gel electrophoresis, the authors analyzed exons 5-9 in all tumors for mutations and performed DNA sequencing in 20 tumors to identify the exact nature of the p53 mutations. RESULTS: p53 gene alterations were identified in 43 of the 192 tumors (22%), the majority localized in exons 5 and 6. DNA sequencing showed mostly missense mutations resulting from G or C substitutions. p53 mutations were found more often in tumors of younger women (P = 0.002), Afro-American women (P = 0.05), and in tumors lacking ER (P = 0.03), PR (P = 0.04), or both (P = 0.06). There were no significant correlations with family history, tumor size, histologic grade or type, nodal status, or disease stage. The overall survival rates showed no significant difference between patients with mutant and wild-type p53 tumors. The same was true when the comparison was limited to node-negative patients or patients with ER-positive or ER-negative tumors. Finally, there was no significant difference in survival between patients with tumors harboring mutations in exons 5 and 6 versus exons 7-9. CONCLUSIONS: The results of this and other studies demonstrate a consistent relationship between ER-positive tumors and wild-type p53 on one hand and ER-negative cancers and p53 mutations on the other. Our data do not support a significant prognostic role for p53 mutations in predicting survival.
BACKGROUND: There is increasing evidence linking development and progression of cancer to an accumulation of mutations at the genomic level. The most frequently mutated gene known to date in sporadic breast cancer appears to be the tumor suppressor gene p53. This study was designed to determine the frequency of p53 gene mutations in primary breast cancer, to correlate the presence of p53 mutations with established clinicopathologic parameters, including the estrogen receptor (ER) and progesterone receptor (PR) status, and to assess the prognostic significance of p53 mutations regarding patient survival. METHODS: We examined the p53 gene in genomic DNA samples from 192 primary breast cancers. Using denaturant gradient gel electrophoresis, the authors analyzed exons 5-9 in all tumors for mutations and performed DNA sequencing in 20 tumors to identify the exact nature of the p53 mutations. RESULTS:p53 gene alterations were identified in 43 of the 192 tumors (22%), the majority localized in exons 5 and 6. DNA sequencing showed mostly missense mutations resulting from G or C substitutions. p53 mutations were found more often in tumors of younger women (P = 0.002), Afro-American women (P = 0.05), and in tumors lacking ER (P = 0.03), PR (P = 0.04), or both (P = 0.06). There were no significant correlations with family history, tumor size, histologic grade or type, nodal status, or disease stage. The overall survival rates showed no significant difference between patients with mutant and wild-type p53tumors. The same was true when the comparison was limited to node-negative patients or patients with ER-positive or ER-negative tumors. Finally, there was no significant difference in survival between patients with tumors harboring mutations in exons 5 and 6 versus exons 7-9. CONCLUSIONS: The results of this and other studies demonstrate a consistent relationship between ER-positive tumors and wild-type p53 on one hand and ER-negative cancers and p53 mutations on the other. Our data do not support a significant prognostic role for p53 mutations in predicting survival.
Authors: T Megha; F Ferrari; A Benvenuto; C Bellan; A V Lalinga; S Lazzi; S Bartolommei; G Cevenini; L Leoncini; P Tosi Journal: J Clin Pathol Date: 2002-06 Impact factor: 3.411
Authors: Sachin Kumar Deshmukh; Sanjeev K Srivastava; Nikhil Tyagi; Aamir Ahmad; Ajay P Singh; Ahmed A L Ghadhban; Donna L Dyess; James E Carter; Kari Dugger; Seema Singh Journal: Carcinogenesis Date: 2017-08-01 Impact factor: 4.944
Authors: G MacGrogan; F Bonichon; I de Mascarel; M Trojani; M Durand; A Avril; J M Coindre Journal: Breast Cancer Res Treat Date: 1995 Impact factor: 4.872
Authors: E Adriaenssens; L Dumont; S Lottin; D Bolle; A Leprêtre; A Delobelle; F Bouali; T Dugimont; J Coll; J J Curgy Journal: Am J Pathol Date: 1998-11 Impact factor: 4.307