Dataset Information

Lateral interactions between B7-H3 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis

ABSTRACT: Oncogenic cell-surface membrane proteins contribute to the phenotypic and functional characteristics of cancer stem cells (CSCs). We quantitatively analyzed cell-surface membrane proteins that are in close proximity to CD147 in CSCs using proximity-labeling proteomic approach. Moreover, we compared CSCs to non-CSCs to identify CSC-specific cell-surface membrane proteins that are the nearest neighbors of CD147 and revealed that lateral interaction between CD147 and CD276 (B7H3) concealed within the lipid raft microdomain in CSCs confers resistance to docetaxel, known to treat many types of cancer patients including metastatic breast cancer. Furthermore, we found that co-expression of CD147 and CD276 in patients with HER2+ breast cancer who received chemotherapy had poor disease-free survival (DFS) and Overall survival (OS) rates (p = 0.04 and 0.08, respectively). Subsequent immunohistochemical analysis indicated that co-expression of CD147 and CD276 may be associated with poor response to chemotherapy in an independent HER2+ BC cohort. Altogether, our study suggests that the lateral interaction between CD147 and its proximal partners, such as CD276, may be related to a poor prognostic factor in BC and a predictive marker for the critical phenotypic determinant of breast cancer stemness.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Stem Cell, Cell Culture

DISEASE(S): Breast Cancer

SUBMITTER: Eugene C Yi

LAB HEAD: Eugene C. Yi

PROVIDER: PXD036909 | Pride | 2023-10-24

REPOSITORIES: Pride

ACCESS DATA

Publications

Lateral interactions between CD276 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis.

Seo Yu Ri YR Lee Junghyeon J Ryu Han Suk HS Kim EunHee G EG Kim So Hyun SH Jeong Jieun J Jung Hyeryeon H Jung YeoJin Y Kim Han Byeol HB Jo Yeon Hui YH Kim Yeong Dong YD Jin Min-Sun MS Lee Yong Yook YY Kim Kristine M KM Yi Eugene C EC

Scientific reports 20230830 1

Oncogenic cell-surface membrane proteins contribute to the phenotypic and functional characteristics of cancer stem cells (CSCs). We employed a proximity-labeling proteomic approach to quantitatively analyze the cell-surface membrane proteins in close proximity to CD147 in CSCs. Furthermore, we compared CSCs to non-CSCs to identify CSC-specific cell-surface membrane proteins that are closely interact with CD147 and revealed that lateral interaction between CD147 and CD276 concealed within the li ...[more]

PMID: 37648771

Similar Datasets

Project description:Background: Most asthmatic patients have high serum levels of IgE directed against common environmental allergens such as house dust mite, animal danders and moulds. However the presence of specific IgE against individual allergens alone does not account for asthma. Many individuals are atopic but not asthmatic. Precise knowledge of the serum IgE specificity repertoire in asthmatic and non-asthmatic patients would substantially help in understanding the pathogenesis of the disease and at the same time facilitate the treatment and the implementation of preventive measures. Methods: We developed a microarray immunoassay containing 103 common allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals from families whose members had a documented history of asthma and atopy. The results were analyzed using k-means clustering to investigate whether IgE reactivity profiles correlated with asthma, disease severity and age of onset as well as with other atopic conditions such as rhinitis, conjunctivitis and eczema. We trained an artificial neural network (ANN) using the serum reactivity data to identify individuals as asthmatic and non-asthmatic. Results: Individual sera showed clear differences in the number and the combinations of allergens recognized as well as in the level of specific IgE. While the presence of specific IgE against single allergens correlated poorly with the pathological conditions examined k-means clustering analysis unraveled that a particular profile was significantly associated with asthma (p <1E-8). An ANN-based algorithm, calibrated with the profile reactivity data correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Conclusions: Our analysis demonstrates that asthma may be a higher-order phenomenon related to patterns of response and not attributable to single antibody reactions. This information sheds new light on the risk of developing the disease and can be readily utilized in combination with an ANN-based tool to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile. The study consisted of a total of 872 sera samples: 485 individuals were diagnosed with asthma, 342 were classified as non asthmatic, a remaining 45 were classified as unconfirmed asthma diagnosis. The serum IgE reactivity profiles were analyzed against 103 allergens representative of 11 distinct allergen classes. Quantification of bound IgE: The fluorescence signal was acquired using ProScanArray Express™ version 3.0 software. PMC reading values of individual spots were corrected against the internal negative control to identify signals above background. Duplicate measurements of individual allergens were utilized. The signal collected from the allergens was interpolated with an external calibration curve to obtain the IU/ml value (see supplementary file GSE20020_IU_ml values.txt), and translated into a Class Score by plotting the data in a standard reactivity scale (see Sample data tables). Class Score values: (CLASS 0 (less than 0.35 IU/ml); CLASS 1 (0.35-0.7 IU/ml); CLASS 2 (0.71-3.5 IU/ml); CLASS 3 (3.51-17.5 IU/ml); CLASS 4 (17.51-50 IU/ml); CLASS 5 (50.01-100 IU/ml).

Dataset Information

Lateral interactions between B7-H3 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis

Publications

Lateral interactions between CD276 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure