Dataset Information

Low PR in ER(+)/HER2(-) breast cancer: high rates of TP53 mutation and high SUV.

ABSTRACT: On the basis of TP53 mutations and standardized uptake values (SUVs) from 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET), we sought to enhance our knowledge of the biology underlying low progesterone receptor (PR) expression in estrogen receptor (ER)-positive/human epidermal growth factor receptor-2 (HER2)-negative tumors. This study included 272 patients surgically treated for ER-positive, HER2-negative breast cancer and who had undergone TP53 gene sequencing. Of these, 229 patients also underwent 18F-FDG PET or PET/CT. Mutational analysis of exons 5-9 of the TP53 gene was conducted using PCR amplification and direct sequencing. The SUVs were measured using 18F-FDG-PET scan images. Twenty-eight (10.3%) tumors had a somatic TP53 mutation. The TP53 mutation rate was significantly higher in low-PR tumors than in high-PR tumors (17.1% vs 7.9%, P = 0.039). Low-PR tumors had significantly higher median SUVs than high-PR tumors (P = 0.046). The multivariable analysis revealed that SUV and age remained independent variables associated with low PR expression. An adverse impact of low PR expression on recurrence-free survival was observed in the multivariable Cox regression hazard model. We provide clinical evidence that genetic alteration of the TP53 gene and dysregulated glucose metabolism partly involve low PR expression in ER-positive and HER2-negative breast cancer.

SUBMITTER: Ahn SG

PROVIDER: S-EPMC6347277 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Low PR in ER(+)/HER2(-) breast cancer: high rates of TP53 mutation and high SUV.

Ahn Sung Gwe SG Yoon Chang Ik CI Lee Jae Hoon JH Lee Hye Sun HS Park So Eun SE Cha Yoon Jin YJ Cha Chihwan C Bae Soong June SJ Lee Kyung-A KA Jeong Joon J

Endocrine-related cancer 20190201 2

On the basis of TP53 mutations and standardized uptake values (SUVs) from 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET), we sought to enhance our knowledge of the biology underlying low progesterone receptor (PR) expression in estrogen receptor (ER)-positive/human epidermal growth factor receptor-2 (HER2)-negative tumors. This study included 272 patients surgically treated for ER-positive, HER2-negative breast cancer and who had undergone TP53 gene sequencing. Of these, 229 p ...[more]

PMID: 30407916

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Project description:Background: Extensive amounts of archived formalin fixed paraffin embedded (FFPE) human tumor tissues are the ultimate resource to investigate signaling network underlying tumorigenesis in human. Yet, their usage is severely limited for lacking of suitable protein techniques. In this study, a quantitative, objective, absolute, and high throughput immunoblot method, quantitative dot blot (QDB), was explored to address this issue by investigating the putative relationship between estrogen receptor (ER)/progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2) pathways in breast cancer tumorigenesis. Methods: In this descriptive observational retrospective study, ER, PR, Her2, and Ki67 protein levels were measured absolutely and quantitatively in 852 FFPE breast cancer tissues using the QDB method. ER, PR, and Her2 levels were charted on the X, Y, and Z-axes to observe samples distribution in a 3D scatterplot. Results: A "seesaw" relationship between ER/PR and Her2 pathways was observed in ER-PR-Her2 space, characterized by the expression levels of these 3 proteins. Specimens with strong expressions of ER/PR proteins were found spreading along the ER/PR floor while those with strong Her2 expression were found wrapping around the Her2 axis. Those lacking strong expressions of all 3 proteins were found accumulating at the intersection of the ER, PR, and Her2 axes. Few specimens floated in the ER-PR-Her2 space to suggest the lack of co-expression of all 3 proteins simultaneously. Ki67 levels were found to be significantly reduced in specimens spreading in the ER-PR space. Conclusions: The unique distribution of specimens in ER-PR-Her2 space prior to any clinical intervention provided visual support of bidirectional talk between ER/PR and Her2 pathways in breast cancer specimens. Clinical interventions to suppress these 2 pathways alternatively warrant further exploration for breast cancer patients accordingly. Our study also demonstrated that the QDB method is an effective tool to analyze archived FFPE cancer specimens in biomedical research.

Project description:Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65-70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa?=?0.76), followed by human epidermal growth factor receptor 2 (Kappa?=?0.69) and progesterone receptor (Kappa?=?0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96-98%), but yielded many false positives (positive predictive value?=?30-32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.

Dataset Information

Low PR in ER(+)/HER2(-) breast cancer: high rates of TP53 mutation and high SUV.

Publications

Low PR in ER(+)/HER2(-) breast cancer: high rates of TP53 mutation and high SUV.

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