TY - JOUR
T1 - Combined immunohistochemistry of PLK1, p21, and p53 for predicting TP53 status
T2 - An independent prognostic factor of breast cancer
AU - Watanabe, Gou
AU - Ishida, Takanori
AU - Furuta, Akihiko
AU - Takahashi, Shin
AU - Watanabe, Mika
AU - Nakata, Hideaki
AU - Kato, Shunsuke
AU - Ishioka, Chikashi
AU - Ohuchi, Noriaki
N1 - Publisher Copyright:
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
PY - 2015/7/27
Y1 - 2015/7/27
N2 - It is difficult to predict the TP53 status by p53 immunohistochemistry (IHC). We aimed to improve the accuracy of p53 IHC with p53-regulated proteins for predicting the TP53 mutation status. TP53 mutations were detected in 19 of 38 breast cancer patients (50%). Five of 7 cases of protein-truncating mutation of TP53 were completely negative for p53 IHC, whereas 11 of 12 cases of TP53 point mutation were strongly positive for p53 IHC. Therefore, to avoid false negatives, we extracted p53-dependent universally downregulated genes using microarray analysis from 38 breast cancer patients and 2 p53-inducible cell lines. From 9 commonly repressed genes, we evaluated 3 genes, baculoviral IAP repeat-containing 5 (BIRC5), polo-like kinase 1 (PLK1), and BUB1 mitotic checkpoint serine/threonine kinase (BUB1), which were previously identified as p53-dependent repressed genes. PLK1≥Allred total score (TS) 5 showed the highest correlation with TP53 mutation. To decrease false positivity, we evaluated p21 IHC. Although strong staining of p21 was observed in 4 cases (10.5%), all 4 were wild-type TP53. Thus, p53 mutation-like (p53mt-like) IHC was identified by p53 TS7,8 with PLK1≥TS 5 and p21 TS≤6. p53 mt-like IHC correlated with TP53 mutation (predictive value=0.94). In other 157 breast cancer cases, p53 mt-like was an independent prognostic marker in multivariate analysis and a strong prognostic factor. Stratification with p53 mt-like IHC identified patients with a poorer prognosis. In conclusion, we identified reliable IHC conditions to predict the TP53 status of breast cancer patients.
AB - It is difficult to predict the TP53 status by p53 immunohistochemistry (IHC). We aimed to improve the accuracy of p53 IHC with p53-regulated proteins for predicting the TP53 mutation status. TP53 mutations were detected in 19 of 38 breast cancer patients (50%). Five of 7 cases of protein-truncating mutation of TP53 were completely negative for p53 IHC, whereas 11 of 12 cases of TP53 point mutation were strongly positive for p53 IHC. Therefore, to avoid false negatives, we extracted p53-dependent universally downregulated genes using microarray analysis from 38 breast cancer patients and 2 p53-inducible cell lines. From 9 commonly repressed genes, we evaluated 3 genes, baculoviral IAP repeat-containing 5 (BIRC5), polo-like kinase 1 (PLK1), and BUB1 mitotic checkpoint serine/threonine kinase (BUB1), which were previously identified as p53-dependent repressed genes. PLK1≥Allred total score (TS) 5 showed the highest correlation with TP53 mutation. To decrease false positivity, we evaluated p21 IHC. Although strong staining of p21 was observed in 4 cases (10.5%), all 4 were wild-type TP53. Thus, p53 mutation-like (p53mt-like) IHC was identified by p53 TS7,8 with PLK1≥TS 5 and p21 TS≤6. p53 mt-like IHC correlated with TP53 mutation (predictive value=0.94). In other 157 breast cancer cases, p53 mt-like was an independent prognostic marker in multivariate analysis and a strong prognostic factor. Stratification with p53 mt-like IHC identified patients with a poorer prognosis. In conclusion, we identified reliable IHC conditions to predict the TP53 status of breast cancer patients.
KW - breast cancer
KW - p21
KW - p53
KW - PLK1
UR - http://www.scopus.com/inward/record.url?scp=84938054567&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938054567&partnerID=8YFLogxK
U2 - 10.1097/PAS.0000000000000386
DO - 10.1097/PAS.0000000000000386
M3 - Article
C2 - 26171916
AN - SCOPUS:84938054567
SN - 0147-5185
VL - 39
SP - 1026
EP - 1034
JO - American Journal of Surgical Pathology
JF - American Journal of Surgical Pathology
IS - 8
ER -