Dataset Information

The relevance of the intrinsic subtype to the clinicopathological features and biomarkers in Japanese breast cancer patients.

ABSTRACT:

Background

Breast cancer is a disease rich in diversity, and it can be categorized into the immunohistochemical intrinsic subtypes : ER/PR + and HER2-, ER/PR + and HER2+, HER2 type, basal-like and unclassified.

Methods

In this study, in addition to the clinicopathological features potentially associated with the intrinsic subtypes, protein expression and genetic mutations of key molecules associated with breast cancer prognosis and treatment sensitivity were analyzed. The distribution of subtypes in the patient population and the differences in marker distribution across the subtypes were investigated.

Results

The immunohistochemical features of 471 consecutive surgical cases of women with primary breast cancer, treated in a single institution, were examined. There were 306 patients who were ER/PR + HER2- (65%); 41 who were ER/PR + HER2+ (8.7%); 59 with HER2 type (12.5%); 37 with basal-like (7.9%); and 28 patients whose breast cancer was unclassified (5.9%). There were no significant differences between the subtypes regarding age, menopausal status, disease stage, lymphatic invasion, blood vessel invasion and lymph node metastasis. Statistically significant differences were found for histological type and grade. Regarding protein expression and genetic mutation, significant differences were found in the distribution within each subtype for six out of 12 molecules investigated.

Conclusions

This study revealed that subtypes differ not only in their clinical pathological profiles, such as histological types and histological grades, but also in molecular expression. The molecular expression patterns observed for each intrinsic subtype may help the selection of an optimal treatment strategy.

SUBMITTER: Tamaki M

PROVIDER: S-EPMC3913623 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Publications

The relevance of the intrinsic subtype to the clinicopathological features and biomarkers in Japanese breast cancer patients.

Tamaki Masako M Kamio Takako T Kameoka Shingo S Kojimahara Noriko N Nishikawa Toshio T

World journal of surgical oncology 20131118

<h4>Background</h4>Breast cancer is a disease rich in diversity, and it can be categorized into the immunohistochemical intrinsic subtypes : ER/PR + and HER2-, ER/PR + and HER2+, HER2 type, basal-like and unclassified.<h4>Methods</h4>In this study, in addition to the clinicopathological features potentially associated with the intrinsic subtypes, protein expression and genetic mutations of key molecules associated with breast cancer prognosis and treatment sensitivity were analyzed. The distribu ...[more]

PMID: 24245483

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Project description:BackgroundThe prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.Methods and findingsThe microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.ConclusionsThe CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

Dataset Information

The relevance of the intrinsic subtype to the clinicopathological features and biomarkers in Japanese breast cancer patients.

Background

Methods

Results

Conclusions

Publications

The relevance of the intrinsic subtype to the clinicopathological features and biomarkers in Japanese breast cancer patients.

Similar Datasets

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