Re-wiring and gene expression changes of AC025034.1 and ATP2B1 play complex roles in early-to-late breast cancer progression

Abstract Background Elucidating the dynamic topological changes across different stages of breast cancer, called stage re-wiring, could lead to identifying key latent regulatory signatures involved in cancer progression. Such dynamic regulators and their functions are mostly unknown. Here, we reconstructed differential co-expression networks for four stages of breast cancer to assess the dynamic patterns of cancer progression. A new computational approach was applied to identify stage-specific subnetworks for each stage. Next, prognostic traits of genes and the efficiency of stage-related groups were evaluated and validated, using the Log-Rank test, SVM classifier, and sample clustering. Furthermore, by conducting the stepwise VIF-feature selection method, a Cox-PH model was developed to predict patients’ risk. Finally, the re-wiring network for prognostic signatures was reconstructed and assessed across stages to detect gain/loss, positive/negative interactions as well as rewired-hub nodes contributing to dynamic cancer progression. Results After having implemented our new approach, we could identify four stage-specific core biological pathways. We could also detect an essential non-coding RNA, AC025034.1, which is not the only antisense to ATP2B1 (cell proliferation regulator), but also revealed a statistically significant stage-descending pattern; Moreover, AC025034.1 revealed both a dynamic topological pattern across stages and prognostic trait. We also identified a high-performance Overall-Survival-Risk model, including 12 re-wired genes to predict patients’ risk (c-index = 0.89). Finally, breast cancer-specific prognostic biomarkers of LINC01612, AC092142.1, and AC008969.1 were identified. Conclusions In summary new scoring method highlighted stage-specific core pathways for early-to-late progressions. Moreover, detecting the significant re-wired hub nodes indicated stage-associated traits, which reflects the importance of such regulators from different perspectives.

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Overall survival according to tumoral clusterin expression in breast cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e11579 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e11579-e11579

Author(s):

Guillaume Mouillet ◽

Loic Chaigneau ◽

Thierry Michy ◽

Cristian Villanueva ◽

Fernando Bazan ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Cancer Progression ◽

Univariate Analysis ◽

University Hospital ◽

Breast Cancer Cell Lines ◽

Rank Test ◽

Breast Tumorigenesis ◽

Clusterin Expression

e11579 Background: Clusterin (CLU) is a glycoprotein expressed constitutively in many tissues and involved in various physiopathological processes. Despite CLU expression is dysregulated in many types of cancer, the specific role of CLU in tumorigenesis remains unclear. The identification of several forms of the protein, with multiple roles is an explanation for these conflicting results. Cytoplasmic CLU (cCLU) has a role in breast tumorigenesis, cancer progression and is associated with breast cancer cell lines death in vitro. However contradictory data are reported about prognostic value of cCLU on survival and clinical progression. Our objective was to estimate patient’s overall survival (OS) according to the expression of cCLU. Methods: Histological and clinical data of 158 patients diagnosed with breast cancer were retrospectively recorded. Every patients were treated in a single French university hospital between 1993 and 2001. Histological samples had been reviewed to determine hormonal status, HER2 and clusterin expression. Immunohistochemical techniques were based on standards and recommendations applied at the time of analysis. Tumors were defined as cCLU positive (cCLU +) if its expression was superior to 10%. Overall Survival rates along with standard deviations were estimated using the Kaplan-Meier method. Differences in OS according to cCLU expression were tested for significance using the log-rank test. Results: Patients had a median age of 56 years (31 – 82 years). Among the 158 patients analyzed, cCLU was overexpressed in 31 patients (19.62%). The histopathologic and clinical characteristics were not statistically different according to clusterin expression even if a trend favouring less favourable tumoural characteristics were observed in cCLU positive tumour. The median follow-up was 14.1 years (11.3 - 19.3). In univariate analysis, cCLU overexpession were not related to OS (HR = 0.86; CI95%: 0.43 - 1.70). Ten-year OS was 76% (± 4) among patients with cCLU - tumors vs 77% (± 7) in patients with cCLU + tumor (p = 0.66). Conclusions: cCLU expression does not seem to be a pronostic factor of overall survival.

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A new approach for breast abnormality detection based on thermography

Medical Technologies Journal ◽

10.26415/2572-004x-vol2iss3p245-254 ◽

2018 ◽

Vol 2 (3) ◽

pp. 245-254 ◽

Cited By ~ 1

Author(s):

Chebbah Nabil Karim ◽

Ouslim Mohamed ◽

Temmar Ryad

Keyword(s):

Breast Cancer ◽

High Performance ◽

Support Vector ◽

Svm Classifier ◽

Abnormality Detection ◽

Public Database ◽

New Approach ◽

Image Processing Techniques ◽

Breast Abnormality ◽

Processing Techniques

Breast cancer is one of the most common women cancers in the world. In this paper, a new approach based on thermography for the early detection of breast abnormality is proposed. The study involved 80 breast thermograms collected from the PROENG public database which consists of 50 healthy breasts and 30 with some findings. Image processing techniques such as segmentation, texture analysis and mathematical morphology were used to train a support vector machine (SVM) classifier for automatic detection of breast abnormality. After conducting several tests, we obtained very interesting and motivating results. Indeed, our method showed a high performance in terms of sensitivity of 93.3%, a specificity of 90% and an accuracy of 91.25%. The final results let us conclude that infrared thermography with the help of an adequate automatic classification algorithm can be a valuable and reliable complementary tool for radiologist in detecting breast cancer and thereby helping to reduce mortality rates.

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A New Risk Model Predicting Overall Survival Using Preoperative Nutritional and Inflammation Status (NIS) in Patients After Curative Resection of Colorectal Cancer

10.21203/rs.3.rs-467144/v1 ◽

2021 ◽

Author(s):

Tamuro Hayama ◽

Tsuyoshi Ozawa ◽

Mitsuo Tsukamoto ◽

Yoshihisa Fukushima ◽

Ryu Shimada ◽

...

Keyword(s):

Overall Survival ◽

Cancer Progression ◽

Curative Resection ◽

Risk Model ◽

Prognostic Score ◽

Glasgow Prognostic Score ◽

University Hospital ◽

Rank Test ◽

Preoperative Body Mass Index ◽

Neutrophil Lymphocyte Ratio

Abstract It has been shown that nutritional status correlates with survival in patients with various kinds of cancers. Besides, cancer causes inflammation which has been suggested to stimulate cancer progression. Therefore, inflammation status also has shown to reflect prognosis of cancers. In this study, we evaluated several kinds of nutritional and inflammation parameters in preoperative blood samples and constructed new risk model predicting a survival in patients with CRC (colorectal cancers). We retrospectively examined 286 patients with stage I-III CRC who had undergone curative resection in Teikyo University Hospital between 2013 to 2017. The association between overall survival (OS) and preoperative body mass index, albumin (Alb), cholesterol (Chol), and lymphocyte count, white blood cell count (WBC), neutrophil count (Neu), platelet count (Plt), C-reactive protein (CRP) were examined using Kaplan-Meier curve and log rank test. and eventually Alb, Chol, Neu, Plt, and CRP were shown to correlate with OS. Alb, Chol, Neu, Plt, and CRP were shown to correlate with OS. We constructed a new risk model (NIS: nutrition inflammation status) using these factors, and compared its usefulness with known models such as CRP-albumin ratio (CAR), Glasgow prognostic score (GPS), prognostic nutritional index (PNI), and neutrophil lymphocyte ratio (NLR). NIS prepared using nutritional indicators and inflammatory findings was useful as a new model for predicting overall survival in patients undergoing curative resection for CRC, compared with known models.

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Prognosis and Prophylactic Regional Nodal Irradiation in Breast Cancer Patients With the First Isolated Chest Wall Recurrence After Mastectomy

Frontiers in Oncology ◽

10.3389/fonc.2020.600525 ◽

2021 ◽

Vol 10 ◽

Author(s):

Xu-Ran Zhao ◽

Liang Xuan ◽

Jun Yin ◽

Yu Tang ◽

Hui-Ru Sun ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Chest Wall ◽

Risk Model ◽

Rank Test ◽

Breast Cancer Patients ◽

Regional Nodal Irradiation ◽

Failure Patterns ◽

Chest Wall Recurrence ◽

Supraclavicular Fossa

Background and PurposeOptimal radiation target volumes for breast cancer patients with their first isolated chest wall recurrence (ICWR) after mastectomy are controversial. We aimed to analyze the regional failure patterns and to investigate the role of prophylactic regional nodal irradiation (RNI) for ICWR.Materials and MethodsAltogether 205 patients with ICWR after mastectomy were retrospectively analyzed. Post-recurrence progression-free survival (PFS) and overall survival (OS) rates were calculated by Kaplan-Meier method and the differences were compared with Log-rank test. Competing risk model was used to estimate the subsequent regional recurrence (sRR) and locoregional recurrence (sLRR) rates, and the differences were compared with Gray test.ResultsThe 5-year sRR rate was 25.2% with median follow-up of 88.6 months. Of the 52 patients with sRR, 30 (57.7%) recurred in the axilla, 29 (55.8%) in supraclavicular fossa (SC), and five (9.6%) in internal mammary nodes. Surgery plus radiotherapy was independently associated with better sLRR and PFS rates (p<0.001). The ICWR interval of ≤ 4 years was associated with unfavorable sRR (p=0.062), sLRR (p=0.014), PFS (p=0.001), and OS (p=0.005). Among the 157 patients who received radiotherapy after ICWR, chest wall plus RNI significantly improved PFS (p=0.004) and OS (p=0.021) compared with chest wall irradiation alone. In the 166 patients whose ICWR interval was ≤ 4 years, chest wall plus RNI provided the best PFS (p<0.001) and OS (p=0.022) compared with chest wall irradiation alone or no radiotherapy.ConclusionPatients with ICWR have a high-risk of sRR in SC and axilla. Chest wall plus RNI is recommended.

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Intelligent CAD System for Automatic Detection of Mitotic Cells from Breast Cancer Histology Slide Images Based on Teaching-Learning-Based Optimization

Computational Biology Journal ◽

10.1155/2014/970898 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 8

Author(s):

Ramin Nateghi ◽

Habibollah Danyali ◽

Mohammad Sadegh Helfroush ◽

Ashkan Tashk

Keyword(s):

Breast Cancer ◽

High Performance ◽

False Positives ◽

Support Vector ◽

Svm Classifier ◽

Computer Assisted ◽

Cad System ◽

Teaching Learning Based Optimization ◽

Teaching Learning ◽

Mitotic Cells

This paper introduces a computer-assisted diagnosis (CAD) system for automatic mitosis detection from breast cancer histopathology slide images. In this system, a new approach for reducing the number of false positives is proposed based on Teaching-Learning-Based optimization (TLBO). The proposed CAD system is implemented on the histopathology slide images acquired by Aperio XT scanner (scanner A). In TLBO algorithm, the number of false positives (falsely detected nonmitosis candidates as mitosis ones) is defined as a cost function and, by minimizing it, many of nonmitosis candidates will be removed. Then some color and texture (textural) features such as those derived from cooccurrence and run-length matrices are extracted from the remaining candidates and finally mitotic cells are classified using a specific support vector machine (SVM) classifier. The simulation results have proven the claims about the high performance and efficiency of the proposed CAD system.

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Core-Fucosylated Tetra-Antennary N-Glycan Containing A Single N-Acetyllactosamine Branch Is Associated with Poor Survival Outcome in Breast Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms20102528 ◽

2019 ◽

Vol 20 (10) ◽

pp. 2528 ◽

Cited By ~ 4

Author(s):

Harmin Herrera ◽

Tinslee Dilday ◽

Allison Uber ◽

Danielle Scott ◽

Joelle N. Zambrano ◽

...

Keyword(s):

Breast Cancer ◽

Clinical Outcomes ◽

Cancer Progression ◽

High Performance ◽

Recurrent Disease ◽

Imaging Mass Spectrometry ◽

Tissue Imaging ◽

Poor Survival ◽

Maldi Ims ◽

Poor Survival Outcome

(1) Glycoproteins account for ~80% of proteins located at the cell surface and in the extracellular matrix. A growing body of evidence indicates that α-L-fucose protein modifications contribute to breast cancer progression and metastatic disease. (2) Using a combination of techniques, including matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) based in cell and on tissue imaging and glycan sequencing using exoglycosidase analysis coupled to hydrophilic interaction ultra-high performance liquid chromatography (HILIC UPLC), we establish that a core-fucosylated tetra-antennary glycan containing a single N-acetyllactosamine (F(6)A4G4Lac1) is associated with poor clinical outcomes in breast cancer, including lymph node metastasis, recurrent disease, and reduced survival. (3) This study is the first to identify a single N-glycan, F(6)A4G4Lac1, as having a correlation with poor clinical outcomes in breast cancer.

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Nanosized zinc, epigenetic changes and its relationship with DMBA induced breast cancer in rats

Reviews in Analytical Chemistry ◽

10.1515/revac-2020-0104 ◽

2020 ◽

Vol 39 (1) ◽

pp. 200-208

Author(s):

Barbara Bobrowska-Korczak ◽

Kamila Domanska ◽

Dorota Skrajnowska ◽

Robert Wrzesien ◽

Joanna Giebultowicz ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Progression ◽

High Performance ◽

Control Diet ◽

Modified Nucleosides ◽

Synergistic Activity ◽

Sprague Dawley ◽

Neoplastic Process ◽

Inflammatory Infiltrates ◽

The Impact

Abstract The aim of the research was to compare the impact of nano- and micro-sized-zinc on the kinetics of changes in the level of 3-methyladenine, 7-methylguanine, 7-methylguanosine, O-methylguanosine, 1-methyladenosine, N6-methyl-2’-deoxyguanosine in urine of rats with breast cancer. Female Sprague-Dawley rats divided into 3 groups were used in the study. Animals were fed only a control diet or diets supplemented with the nano and micro-sized zinc particles. To induce the mammary cancer (adenocarcinoma), rats were treated with 7,12-dimethylbenz[a]anthracene (DMBA). Modified nucleosides were determined by a validated high performance liquid chromatography coupled to mass spectrometry method. In the first stage of investigations a synergistic activity of nanosized Zn with DMBA on the growth of the neoplastic process was found. During that time a statistically significant increase in the levels of all six examined markers in the rats’ urine was observed. However, as the experiment continued, the supplementation with nanosized zinc caused inhibition of tumour growth, being followed by regression and remission of tumours, as well as, a statistically significant systematic reduction of the levels of methyl derivatives in the urine. Biopsy images indicated grade 1 tumours with multiple inflammatory infiltrates in the group treated with zinc nanoparticles, whereas, in the other groups, moderately-differentiated grade 2 adenocarcinoma was identified. It was found that the biological activity of zinc depends on the size of applied particles, as the treatment with zinc microparticles has not had much effect on cancer progression.

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Identification and Validation of a Five-Gene Signature Associated With Overall Survival in Breast Cancer Patients

Frontiers in Oncology ◽

10.3389/fonc.2021.660242 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaolong Wang ◽

Chen Li ◽

Tong Chen ◽

Wenhao Li ◽

Hanwen Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Cancer Progression ◽

Molecular Mechanisms ◽

Risk Model ◽

Expression Profiles ◽

External Validation ◽

Gene Signature ◽

Breast Cancer Patients ◽

Study Gene Expression

BackgroundRecent years, the global prevalence of breast cancer (BC) was still high and the underlying molecular mechanisms remained largely unknown. The investigation of prognosis-related biomarkers had become an urgent demand.ResultsIn this study, gene expression profiles and clinical information of breast cancer patients were downloaded from the TCGA database. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1, and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the TCGA entire cohort and an independent external validation cohort. To explore the biological functions of the selected genes, in vitro assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression.ConclusionsWe established a predictive five-gene signature, which could be helpful for a personalized management in breast cancer patients.

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