Immunohistochemical Expression of Melatonin Receptor MT1 and Glucose Transporter GLUT1 in Human Breast Cancer

Background: Breast cancer is a heterogeneous disease and is the leading cause of cancer-related deaths among women. Even after diagnosis, the prognosis cannot be concluded since patients can develop resistance to therapy, which favors tumor growth, invasion and metastasis. In recent years, research has focused on identifying significant markers that can be used to determine the prognosis. Melatonin can act through G protein– coupled MT1 receptor, which controls selected protein kinases, influences the levels of transcription factor phosphorylation, specific genes expression, proliferation, angiogenesis, cell differentiation, migration, and indirectly controls the transport of glucose in cancer cells. It is known that glucose enters the cells by glucose transporters, such as GLUT1 which shows wide tissue distribution and appears to be altered in human breast carcinoma. High GLUT1 expression is associated with increased malignant potential, invasiveness and poor prognosis in some cancers including breast cancer. Objective: The aim of this study was to evaluate the expression of MT1 receptor and GLUT1 in breast tumors and correlate with molecular subtypes and prognostic characteristics. Method: Protein expression was performed by an immunohistochemical procedure with specific antibodies and positive and negative controls. Results: We found that MT1 high expression was associated with good prognosis subtype (Luminal A), while GLUT1 high expression was related to poor prognosis subtype (triple-negative). In addition, we found high expression of MT1 in ER+ and the inverse in GLUT1 expression. GLUT1 is also highly expressed in tumor ≥20mm. Conclusion: These results indicate MT1 and GLUT1 as potential targets for breast cancer subtypes and prognosis.

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Mammographic tumour appearance is related to clinicopathological factors and surrogate molecular breast cancer subtype

Scientific Reports ◽

10.1038/s41598-020-77053-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Li Sturesdotter ◽

Malte Sandsveden ◽

Kristin Johnson ◽

Anna-Maria Larsson ◽

Sophia Zackrisson ◽

...

Keyword(s):

Breast Cancer ◽

Molecular Subtype ◽

Histological Grade ◽

Breast Cancer Subtype ◽

Growth Factor Receptor ◽

Good Prognosis ◽

Clinicopathological Factors ◽

Luminal A ◽

Cancer Subtypes ◽

Epidermal Growth

AbstractMammographic tumour appearance may provide prognostic useful information. For example, spiculation indicates invasiveness, but also better survival compared to tumours with other appearances. We aimed to study the relationship between mammographic tumour appearance and established clinicopathological factors, including surrogate molecular breast cancer subtypes, in the large Malmö Diet and Cancer Study. A total of 1116 women with invasive breast cancer, diagnosed between 1991 and 2014, were included. Mammographic tumour appearance in relation to status for oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2, histological grade, Ki67 and molecular subtype was analysed using various regression models. All models were adjusted for relevant confounders, including breast density, which can affect mammographic appearance. The results consistently showed that spiculated tumours are indicative of favourable characteristics, as they are more likely to be ER and PR positive, and more often exhibit lower histological grade and lower Ki67 expression. Furthermore, spiculated tumours tend to be of luminal A-like subtype, which is associated with a good prognosis. The establishment of associations between mammographic tumour appearance and clinicopathological factors may aid in characterizing breast cancer at an earlier stage. This could contribute to more individualized breast cancer treatment in the future.

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High Expression of Pseudogene PTTG3P Indicates a Poor Prognosis in Human Breast Cancer

Molecular Therapy — Oncolytics ◽

10.1016/j.omto.2019.03.006 ◽

2019 ◽

Vol 14 ◽

pp. 15-26 ◽

Cited By ~ 16

Author(s):

Weiyang Lou ◽

Bisha Ding ◽

Weimin Fan

Keyword(s):

Breast Cancer ◽

Human Breast Cancer ◽

Poor Prognosis ◽

High Expression ◽

Human Breast

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High expression levels of egfl7 correlate with low endothelial cell activation in peritumoral vessels of human breast cancer

Oncology Letters ◽

10.3892/ol.2016.4791 ◽

2016 ◽

Vol 12 (2) ◽

pp. 1422-1428 ◽

Cited By ~ 7

Author(s):

Diane Pannier ◽

Géraldine Philippin-Lauridant ◽

Marie-Christine Baranzelli ◽

Delphine Bertin ◽

Emilie Bogart ◽

...

Keyword(s):

Breast Cancer ◽

Endothelial Cell ◽

Human Breast Cancer ◽

Cell Activation ◽

High Expression ◽

Human Breast ◽

Endothelial Cell Activation ◽

Expression Levels ◽

Peritumoral Vessels

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The association of women’s birth size with risk of molecular breast cancer subtypes: a cohort study

BMC Cancer ◽

10.1186/s12885-021-08027-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Marie S. Sandvei ◽

Signe Opdahl ◽

Marit Valla ◽

Pagona Lagiou ◽

Ellen Veronika Vesterfjell ◽

...

Keyword(s):

Breast Cancer ◽

Birth Weight ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Head Circumference ◽

Birth Length ◽

Birth Size ◽

Luminal A ◽

Cancer Subtypes ◽

Luminal B

Abstract Background Because birth size appears to be positively associated with breast cancer risk, we have studied whether this risk may differ according to molecular breast cancer subtypes. Methods A cohort of 22,931 women born 1920–1966 were followed up for breast cancer occurrence from 1961 to 2012, and 870 were diagnosed during follow-up. Archival diagnostic material from 537 patients was available to determine molecular breast cancer subtype, specified as Luminal A, Luminal B (human epidermal growth factor receptor 2 (HER2)-), Luminal B (HER2+), HER2 type, and Triple negative (TN) breast cancer. Information on the women’s birth weight, birth length and head circumference at birth was used to estimate hazard ratios (HR) with 95% confidence intervals (CI) for each molecular subtype, applying Cox regression, and stratified by maternal height. Results Birth length (per 2 cm increments) was positively associated with Luminal A (HR = 1.2, 95% CI, 1.0–1.3), Luminal B (HER2+) (HR = 1.3, 95% CI, 1.0–1.7), and TN breast cancer (HR = 1.4, 95% CI, 1.0–1.9). No clear association was found for birth weight and head circumference. The positive associations of birth length were restricted to women whose mothers were relatively tall (above population median). Conclusion We found a positive association of birth length with risk of Luminal A, Luminal B (HER2+) and TN breast cancer that appears to be restricted to women whose mothers were relatively tall. This may support the hypothesis that breast cancer risk is influenced by determinants of longitudinal growth and that this finding deserves further scrutiny.

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Comprehensive immunohistochemical analysis of RET, BCAR1, and BCAR3 expression in patients with Luminal A and B breast cancer subtypes

Breast Cancer Research and Treatment ◽

10.1007/s10549-021-06452-9 ◽

2022 ◽

Author(s):

Ana Carolina Pavanelli ◽

Flavia Rotea Mangone ◽

Piriya Yoganathan ◽

Simone Aparecida Bessa ◽

Suely Nonogaki ◽

...

Keyword(s):

Breast Cancer ◽

Immunohistochemical Analysis ◽

Breast Cancer Subtypes ◽

Luminal A ◽

Cancer Subtypes

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High expression of UBD correlates with epirubicin resistance and indicates poor prognosis in triple-negative breast cancer

OncoTargets and Therapy ◽

10.2147/ott.s81214 ◽

2015 ◽

pp. 1643 ◽

Cited By ~ 1

Author(s):

Xiaodong Xie ◽

TAO HAN ◽

Yaling Han ◽

Wanqing Xie ◽

Ranran Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Poor Prognosis ◽

Triple Negative ◽

High Expression

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Low KIBRA Expression Is Associated with Poor Prognosis in Patients with Triple-Negative Breast Cancer

Medicina ◽

10.3390/medicina57080837 ◽

2021 ◽

Vol 57 (8) ◽

pp. 837

Author(s):

So-Woon Kim ◽

Jinah Chu ◽

Sung-Im Do ◽

Kiyong Na

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Poor Prognosis ◽

Triple Negative ◽

Histological Grade ◽

Growth Factor Receptor ◽

Hippo Signaling ◽

Luminal A ◽

Luminal B ◽

Epidermal Growth

Background and Objectives: Kidney and brain protein (KIBRA) is a protein encoded by the WW and C2 domain containing 1 (WWC1) gene and is involved in the Hippo signaling pathway. Recent studies have revealed the prognostic value of KIBRA expression; however, its role in breast cancer remains unclear. The aim of this study was to examine KIBRA expression in relation to the clinical and pathological characteristics of patients with breast cancer and to disease outcomes. Materials and Methods: We analyzed the expression of KIBRA and its correlation with event-free survival (EFS) outcomes in resected samples from 486 patients with breast cancer. Results: KIBRA expression was significantly different among the molecular subgroups (low KIBRA expression: luminal A, 46.7% versus 50.0%, p = 0.641; luminal B, 32.7% versus 71.7%, p < 0.001; human epidermal growth factor receptor 2 (HER2)-enriched, 64.9% versus 45.5%. p = 0.001; triple-negative, 73.6% versus 43.8%, p < 0.001). Low KIBRA expression was also associated with high nuclear grade (60.4% versus 37.8%, p < 0.001), high histologic grade (58.7% versus 37.0%, p < 0.001), and estrogen receptor (ER) negativity (54.2% versus 23.6%, p < 0.001). Low KIBRA expression was significantly associated with poor EFS (p = 0.041; hazard ratio (HR) 1.658; 95% confidence interval (CI), 1.015–2.709). Low KIBRA expression was an independent indicator of poor prognosis (p = 0.001; HR = 3.952; 95% CI = 1.542–10.133) in triple-negative breast cancer (TNBC). Conclusion: Low KIBRA expression was associated with higher histological grade, ER negativity and poor EFS of breast cancer. In particular, our data highlight KIBRA expression status as a potential prognostic marker for TNBC.

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Identification of key genes unique to the luminal A and basal-like breast cancer subtypes via bioinformatic analysis

10.21203/rs.3.rs-28637/v1 ◽

2020 ◽

Author(s):

Rong Jia ◽

Zhongxian Li ◽

Wei Liang ◽

Yucheng Ji ◽

Yujie Weng ◽

...

Keyword(s):

Breast Cancer ◽

Differentially Expressed Genes ◽

Survival Data ◽

Breast Cancer Subtypes ◽

Differentially Expressed ◽

Expression Data ◽

Luminal A ◽

Cancer Subtypes ◽

Protein Protein Interaction ◽

Basal Like Breast Cancer

Abstract Background Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field. Methods We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype. Results We identified 1,114 differentially expressed genes in luminal A breast cancer and 1,042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7 , KIF18A , STIL , and CKS2 in basal-like breast cancer statistically correlated with poor prognosis. Conclusions NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

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