scholarly journals k-core genes underpin structural features of breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rodrigo Dorantes-Gilardi ◽  
Diana García-Cortés ◽  
Enrique Hernández-Lemus ◽  
Jesús Espinal-Enríquez
Keyword(s):  
Breast Cancer ◽  
Expression Patterns ◽  
Structural Features ◽  
Structure And Function ◽  
Luminal A ◽  
Luminal B ◽  
The Core ◽  
Gene Pairs ◽  
And Function ◽  
Core Genes

AbstractGene co-expression networks (GCNs) have been developed as relevant analytical tools for the study of the gene expression patterns behind complex phenotypes. Determining the association between structure and function in GCNs is a current challenge in biomedical research. Several structural differences between GCNs of breast cancer and healthy phenotypes have been reported. In a previous study, using co-expression multilayer networks, we have shown that there are abrupt differences in the connectivity patterns of the GCN of basal-like breast cancer between top co-expressed gene-pairs and the remaining gene-pairs. Here, we compared the top-100,000 interactions networks for the four breast cancer phenotypes (Luminal-A, Luminal-B, Her2+ and Basal), in terms of structural properties. For this purpose, we used the graph-theoretical k-core of a network (maximal sub-network with nodes of degree at least k). We developed a comprehensive analysis of the network k-core ($$k=30$$ k = 30 ) structures in cancer, and its relationship with biological functions. We found that in the Top-100,000-edges networks, the majority of interactions in breast cancer networks are intra-chromosome, meanwhile inter-chromosome interactions serve as connecting bridges between clusters. Moreover, core genes in the healthy network are strongly associated with processes such as metabolism and cell cycle. In breast cancer, only the core of Luminal A is related to those processes, and genes in its core are over-expressed. The intersection of the core nodes in all subtypes of cancer is composed only by genes in the chr8q24.3 region. This region has been observed to be highly amplified in several cancers before, and its appearance in the intersection of the four breast cancer k-cores, may suggest that local co-expression is a conserved phenomenon in cancer. Considering the many intricacies associated with these phenomena and the vast amount of research in epigenomic regulation which is currently undergoing, there is a need for further research on the epigenomic effects on the structure and function of gene co-expression networks in cancer.

scholarly journals Integrative Analysis Reveals Subtype-Specific Regulatory Determinants in Triple Negative Breast Cancer

Cancers ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 507 ◽  
Author(s):  
Shujun Huang ◽  
Wayne Xu ◽  
Pingzhao Hu ◽  
Ted M. Lakowski
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Binding Sites ◽  
Triple Negative ◽  
Expression Patterns ◽  
Lasso Regression ◽  
Luminal A ◽  
Luminal B ◽  
Number Variation ◽  
Yin And Yang

Different breast cancer (BC) subtypes have unique gene expression patterns, but their regulatory mechanisms have yet to be fully elucidated. We hypothesized that the top upregulated (Yin) and downregulated (Yang) genes determine the fate of cancer cells. To reveal the regulatory determinants of these Yin and Yang genes in different BC subtypes, we developed a lasso regression model integrating DNA methylation (DM), copy number variation (CNV) and microRNA (miRNA) expression of 391 BC patients, coupled with miRNA–target interactions and transcription factor (TF) binding sites. A total of 25, 20, 15 and 24 key regulators were identified for luminal A, luminal B, Her2-enriched, and triple negative (TN) subtypes, respectively. Many of the 24 TN regulators were found to regulate the PPARA and FOXM1 pathways. The Yin Yang gene expression mean ratio (YMR) and combined risk score (CRS) signatures built with either the targets of or the TN regulators were associated with the BC patients’ survival. Previously, we identified FOXM1 and PPARA as the top Yin and Yang pathways in TN, respectively. These two pathways and their regulators could be further explored experimentally, which might help to identify potential therapeutic targets for TN.

scholarly journals Reparameterization of PAM50 expression identifies novel breast tumor dimensions and leads to discovery of a breast cancer susceptibility locus at 12q15

2017 ◽  
Author(s):  
Michael J Madsen ◽  
Stacey Knight ◽  
Carol Sweeney ◽  
Rachel Factor ◽  
Mohamed Salama ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Susceptibility ◽  
Expression Patterns ◽  
Breast Tumors ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Tumor Characteristics ◽  
Intrinsic Subtypes ◽  
Luminal A ◽  
Luminal B

AbstractIt is well-known that breast tumors exhibit different expression patterns that can be used to assign intrinsic subtypes – the PAM50 assay, for example, categorizes tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like – yet tumors are often more complex than categorization can describe. We used 911 sporadic breast tumors to reparameterize expression from the PAM50 genes to five orthogonal tumor dimensions using principal components (PC). Three dimensions captured intrinsic subtype, two dimensions were novel, and all replicated in 945 TCGA tumors. By definition dimensions are independent, an important attribute for inclusion in downstream studies exploring effects of tumor diversity. One application where tumor subtyping has failed to provide impact is susceptibility genetics. Germline genetic heterogeneity reduces power for gene-finding. The identification of heritable tumor characteristics has potential to increase homogeneity. We compared 238 breast tumors from high-risk pedigrees not attributable to BRCA1 or BRCA2 to 911 sporadic breast tumors. Two PC dimensions were significantly enriched in the pedigrees (intrinsic subtypes were not). We performed proof-of-concept gene-mapping in one enriched pedigree and identified a 0.5 Mb genomewide significant region at 12q15 that segregated to the 8 breast cancer cases with the most extreme PC tumors through 32 meioses (p=2.6×10−8). In conclusion, our study: suggests a new approach to describe tumor diversity; supports the hypothesis that tumor characteristics are heritable providing new avenues for germline studies; and proposes a new breast cancer locus. Reparameterization of expression patterns may similarly inform other studies attempting to model the effects of tumor heterogeneity.

scholarly journals Gene Co-Expression in Breast Cancer: A Matter of Distance

2021 ◽  
Vol 11 ◽  
Author(s):  
Alfredo González-Espinoza ◽  
Jose Zamora-Fuentes ◽  
Enrique Hernández-Lemus ◽  
Jesús Espinal-Enríquez
Keyword(s):  
Breast Cancer ◽  
Pearson Correlation ◽  
Expression Patterns ◽  
Null Model ◽  
Gene Clusters ◽  
Chromosome Location ◽  
Luminal A ◽  
Long Distance ◽  
Cancer Subtypes ◽  
Luminal B

Gene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed us to compare and analyze complex phenotypes such as breast cancer (BrCa) and their control counterparts. Global co-expression patterns have revealed, for instance, that the highest gene-gene co-expression interactions often occur between genes from the same chromosome (cis-), meanwhile inter-chromosome (trans-) interactions are scarce and have lower correlation values. Furthermore, strength of cis- correlations have been shown to decay with the chromosome distance of gene couples. Despite this loss of long-distance co-expression has been clearly identified, it has been observed only in a small fraction of the whole co-expression landscape, namely the most significant interactions. For that reason, an approach that takes into account the whole interaction set results appealing. In this work, we developed a hybrid method to analyze whole-chromosome Pearson correlation matrices for the four BrCa subtypes (Luminal A, Luminal B, HER2+ and Basal), as well as adjacent normal breast tissue derived matrices. We implemented a systematic method for clustering gene couples, by using eigenvalue spectral decomposition and the k–medoids algorithm, allowing us to determine a number of clusters without removing any interaction. With this method we compared, for each chromosome in the five phenotypes: a) Whether or not the gene-gene co-expression decays with the distance in the breast cancer subtypes b) the chromosome location of cis- clusters of gene couples, and c) whether or not the loss of long-distance co-expression is observed in the whole range of interactions. We found that in the correlation matrix for the control phenotype, positive and negative Pearson correlations deviate from a random null model independently of the distance between couples. Conversely, for all BrCa subtypes, in all chromosomes, positive correlations decay with distance, and negative correlations do not differ from the null model. We also found that BrCa clusters are distance-dependent, meanwhile for the control phenotype, chromosome location does not determine the clustering. To our knowledge, this is the first time that a dependence on distance is reported for gene clusters in breast cancer. Since this method uses the whole cis- interaction geneset, combination with other -omics approaches may provide further evidence to understand in a more integrative fashion, the mechanisms that disrupt gene regulation in cancer.

AGE FEATURES OF MOLECULAR-BIOLOGICAL SUBTYPES OF BREAST CANCER

2020 ◽  
Vol 17 (2) ◽  
pp. 187-192
Author(s):  
E.A. Novikova ◽  
◽  
O.V. Kostromina ◽  
D.V. Mikhailov ◽  
S.L. Leontiev ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Hormone Receptors ◽  
Age Groups ◽  
Luminal A ◽  
Ki 67 ◽  
Luminal B ◽  
Age Related ◽  
Age Features ◽  
Immunohistochemical Studies ◽  
Triple Negative Subtype

Aim. The aim of the study was to determine the presence of peculiarities of the age structure in patients with various surrogate molecular biological subtypes of breast cancer. Materials and research methods. This work analyzes the age-related characteristics of the occurrence of molecular biological subtypes in 499 patients with invasive breast cancer. All cases were divided into 5 molecular biological subtypes based on immunohistochemical studies of hormone receptors, Her2, Ki-67. The average age of the patients was 53.4±0.39 years, the predominant group was patients from 50 to 60 years (37.2% of the total). Research results. In patients under 40 years old, the triple negative subtype prevailed (44.8%). Luminal A subtype prevailed in the groups 51-60 years old (more than 41.4%) and over 60 years old (39.7%). Luminal B (Her2-) subtype was equally found in all age groups.

scholarly journals Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer

2021 ◽  
Vol 22 (2) ◽  
pp. 636
Author(s):  
Hsing-Ju Wu ◽  
Pei-Yi Chu
Keyword(s):  
Breast Cancer ◽  
Normal Breast ◽  
New Drugs ◽  
Cancer Type ◽  
Luminal A ◽  
Luminal B ◽  
Therapeutic Implications ◽  
Whole Cells ◽  
Diagnosis And Prognosis ◽  
Novel Biomarkers

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

scholarly journals Inflammatory Breast Cancer: Clinical Characteristics and Influence of Molecular Subtypes on Treatment Response

2021 ◽  
Vol 107 (1_suppl) ◽  
pp. 12-12
Author(s):  
D Aissaoui ◽  
M Bohli ◽  
R Ben Amor ◽  
J Yahyaoui ◽  
A Hamdoun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Treatment Response ◽  
Inflammatory Breast Cancer ◽  
Hormone Receptor ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Luminal A ◽  
Her2 Positive ◽  
Luminal B ◽  
Significant Difference

Introduction: Inflammatory Breast Cancer (IBC) is a rare and very aggressive breast cancer with poor prognosis. The prevalence is different from a country to another. In Tunisia, it is about 5 to 7% of breast cancer. The aim of this study is to describe the epidemiological and histopathological features of patients with inflammatory breast cancer and to evaluate the treatment response according to the molecular subtypes. Methods: This retrospective review identified 31 patients with no metastatic IBC treated in our radiotherapy department between December 2019 and November 2020. IBC was confirmed using the clinical criteria. Baseline clinic-pathological and treatment information was retrieved from medical records. Statistical analysis was performed with IBM SPSS V.20. Results: Median age was 51.3 years [27-68]. 48% of tumors were grade 3. The average tumor size was 36mm [10-90]. The histological type was ductal carcinoma in 97%. Vascular invasion was noted in 24 patients (77%). Thirty patients were classified as stage IIIB and one patient was IIIC. 74% were hormone receptor positive and 45% were HER2 positive. Luminal B was the predominant subtype (52%) followed by Her2 positive (32%), Luminal A (23%), and triple negative (3%) All patients had chemotherapy: neoadjuvant for 26 patients (84%) and adjuvant for 5 patients (16%). Nine patients (29%) had tumor pathological complete response (pCR). Partial response was observed in 18 patients (58%). Lymph node pCR was noted in 16% of cases (n=5). Endocrine therapy and trastuzumab were given to 76% and 45% of patients, respectively. The influence of the molecular subtype was not statistically significant on the response to neoadjuvant treatment. The highest rate of pCR were 43% for Her2positive, then 27%, 21% and 9% for Luminal B, Luminal A and Triple negative, respectively (p=0.2). Conclusion: Our study showed a high percentage of hormone receptor and Her2+ (74% and 45% respectively) in IBC. Luminal B was the most frequent subtype. Anthracycline-based chemotherapy and trastuzumab improved the pCR rate: 44% for Her2positive. Triple negative showed poorer pCR than other breast cancer subtype without a significant difference. A larger study is warranted to confirm our findings.

scholarly journals Prognostic Relevance of Neutrophil to Lymphocyte Ratio (NLR) in Luminal Breast Cancer: A Retrospective Analysis in the Neoadjuvant Setting

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1685
Author(s):  
Antonino Grassadonia ◽  
Vincenzo Graziano ◽  
Laura Iezzi ◽  
Patrizia Vici ◽  
Maddalena Barba ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Disease Free Survival ◽  
Post Treatment ◽  
Neutrophil To Lymphocyte Ratio ◽  
Luminal Breast Cancer ◽  
Luminal A ◽  
Luminal B ◽  
Lymphocyte Ratio ◽  
Cell Counts ◽  
Pre Treatment

The neutrophil to lymphocyte ratio (NLR) is a promising predictive and prognostic factor in breast cancer. We investigated its ability to predict disease-free survival (DFS) and overall survival (OS) in patients with luminal A- or luminal B-HER2-negative breast cancer who received neoadjuvant chemotherapy (NACT). Pre-treatment complete blood cell counts from 168 consecutive patients with luminal breast cancer were evaluated to assess NLR. The study population was stratified into NLRlow or NLRhigh according to a cut-off value established by receiving operator curve (ROC) analysis. Data on additional pre- and post-treatment clinical-pathological characteristics were also collected. Kaplan–Meier curves, log-rank tests, and Cox proportional hazards models were used for statistical analyses. Patients with pre-treatment NLRlow showed a significantly shorter DFS (HR: 6.97, 95% CI: 1.65–10.55, p = 0.002) and OS (HR: 7.79, 95% CI: 1.25–15.07, p = 0.021) compared to those with NLRhigh. Non-ductal histology, luminal B subtype, and post-treatment Ki67 ≥ 14% were also associated with worse DFS (p = 0.016, p = 0.002, and p = 0.001, respectively). In a multivariate analysis, luminal B subtype, post-treatment Ki67 ≥ 14%, and NLRlow remained independent prognostic factors for DFS, while only post-treatment Ki67 ≥ 14% and NLRlow affected OS. The present study provides evidence that pre-treatment NLRlow helps identify women at higher risk of recurrence and death among patients affected by luminal breast cancer treated with NACT.

scholarly journals Clinicopathologic Profile of Breast Cancer in Germline ATM and CHEK2 Mutation Carriers

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 616
Author(s):  
Angela Toss ◽  
Elena Tenedini ◽  
Claudia Piombino ◽  
Marta Venturelli ◽  
Isabella Marchi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Rate ◽  
Luminal A ◽  
Clinicopathologic Characteristics ◽  
Luminal B ◽  
Chek2 Mutation ◽  
Mutation Carriers ◽  
Clinicopathologic Profile ◽  
Contralateral Mastectomy

The most common breast cancer (BC) susceptibility genes beyond BRCA1/2 are ATM and CHEK2. For the purpose of exploring the clinicopathologic characteristics of BC developed by ATM or CHEK2 mutation carriers, we reviewed the archive of our Family Cancer Clinic. Since 2018, 1185 multi-gene panel tests have been performed. Nineteen ATM and 17 CHEK2 mutation carriers affected by 46 different BCs were identified. A high rate of bilateral tumors was observed in ATM (26.3%) and CHEK2 mutation carriers (41.2%). While 64.3% of CHEK2 tumors were luminal A-like, 56.2% of ATM tumors were luminal B-like/HER2-negative. Moreover, 21.4% of CHEK2-related invasive tumors showed a lobular histotype. About a quarter of all ATM-related BCs and a third of CHEK2 BCs were in situ carcinomas and more than half of ATM and CHEK2-related BCs were diagnosed at stage I-II. Finally, 63.2% of ATM mutation carriers and 64.7% of CHEK2 mutation carriers presented a positive BC family history. The biological and clinical characteristics of ATM and CHEK2-related tumors may help improve diagnosis, prognostication and targeted therapeutic approaches. Contralateral mastectomy should be considered and discussed with ATM and CHEK2 mutation carriers at the first diagnosis of BC.

scholarly journals Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis

Breast Care ◽  
2021 ◽  
pp. 1-8
Author(s):  
Hans-Jonas Meyer ◽  
Andreas Wienke ◽  
Alexey Surov
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Diffusion Weighted Imaging ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Luminal A ◽  
Diagnose Breast Cancer ◽  
Luminal B ◽  
Diffusion Weighted ◽  
Adc Values

Background: Magnetic resonance imaging can be used to diagnose breast cancer (BC).Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Objectives: This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients. Method: The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included. Results: The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10–3 mm2/s (95% CI 0.94–1.04), luminal B: 0.97 × 10–3 mm2/s (95% CI 0.89–1.05), Her2-enriched: 1.02 × 10–3 mm2/s (95% CI 0.95–1.08), and triple-negative: 0.99 × 10–3 mm2/s (95% CI 0.91–1.07). Conclusions: ADC values cannot be used to discriminate between molecular subtypes of BC.

Sign in / Sign up

Export Citation Format

Share Document