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The Hierarchical Modular Structure of HER2+ Breast Cancer Network.

ABSTRACT: HER2-enriched breast cancer is a complex disease characterized by the overexpression of the ERBB2 amplicon. While the effects of this genomic aberration on the pathology have been studied, genome-wide deregulation patterns in this subtype of cancer are also observed. A novel approach to the study of this malignant neoplasy is the use of transcriptional networks. These networks generally exhibit modular structures, which in turn may be associated to biological processes. This modular regulation of biological functions may also exhibit a hierarchical structure, with deeper levels of modular organization accounting for more specific functional regulation. In this work, we identified the most probable (maximum likelihood) model of the hierarchical modular structure of the HER2-enriched transcriptional network as reconstructed from gene expression data, and analyzed the statistical associations of modules and submodules to biological functions. We found modular structures, independent from direct ERBB2 amplicon regulation, involved in different biological functions such as signaling, immunity, and cellular morphology. Higher resolution submodules were identified in more specific functions, such as micro-RNA regulation and the activation of viral-like immune response. We propose the approach presented here as one that may help to unveil mechanisms involved in the development of the pathology.

SUBMITTER: Alcala-Corona SA

PROVIDER: S-EPMC6193406 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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The Hierarchical Modular Structure of HER2+ Breast Cancer Network.

Alcalá-Corona Sergio Antonio SA Espinal-Enríquez Jesús J de Anda-Jáuregui Guillermo G Hernández-Lemus Enrique E

Frontiers in physiology 20181011

HER2-enriched breast cancer is a complex disease characterized by the overexpression of the ERBB2 amplicon. While the effects of this genomic aberration on the pathology have been studied, genome-wide deregulation patterns in this subtype of cancer are also observed. A novel approach to the study of this malignant neoplasy is the use of transcriptional networks. These networks generally exhibit modular structures, which in turn may be associated to biological processes. This modular regulation o ...[more]

PMID: 30364267

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Project description:Virus genomes are prone to extensive gene loss, gain, and exchange and share no universal genes. Therefore, in a broad-scale study of virus evolution, gene and genome network analyses can complement traditional phylogenetics. We performed an exhaustive comparative analysis of the genomes of double-stranded DNA (dsDNA) viruses by using the bipartite network approach and found a robust hierarchical modularity in the dsDNA virosphere. Bipartite networks consist of two classes of nodes, with nodes in one class, in this case genomes, being connected via nodes of the second class, in this case genes. Such a network can be partitioned into modules that combine nodes from both classes. The bipartite network of dsDNA viruses includes 19 modules that form 5 major and 3 minor supermodules. Of these modules, 11 include tailed bacteriophages, reflecting the diversity of this largest group of viruses. The module analysis quantitatively validates and refines previously proposed nontrivial evolutionary relationships. An expansive supermodule combines the large and giant viruses of the putative order "Megavirales" with diverse moderate-sized viruses and related mobile elements. All viruses in this supermodule share a distinct morphogenetic tool kit with a double jelly roll major capsid protein. Herpesviruses and tailed bacteriophages comprise another supermodule, held together by a distinct set of morphogenetic proteins centered on the HK97-like major capsid protein. Together, these two supermodules cover the great majority of currently known dsDNA viruses. We formally identify a set of 14 viral hallmark genes that comprise the hubs of the network and account for most of the intermodule connections. Viruses and related mobile genetic elements are the dominant biological entities on earth, but their evolution is not sufficiently understood and their classification is not adequately developed. The key reason is the characteristic high rate of virus evolution that involves not only sequence change but also extensive gene loss, gain, and exchange. Therefore, in the study of virus evolution on a large scale, traditional phylogenetic approaches have limited applicability and have to be complemented by gene and genome network analyses. We applied state-of-the art methods of such analysis to reveal robust hierarchical modularity in the genomes of double-stranded DNA viruses. Some of the identified modules combine highly diverse viruses infecting bacteria, archaea, and eukaryotes, in support of previous hypotheses on direct evolutionary relationships between viruses from the three domains of cellular life. We formally identify a set of 14 viral hallmark genes that hold together the genomic network.

Project description:BackgroundClinical trials of human epidermal growth factor receptor 2 (HER2)-targeted agents added to standard treatment have been efficacious for HER2-positive (HER2+) advanced breast cancer. To our knowledge, no meta-analysis has evaluated HER2-targeted therapy including trastuzumab emtansine (T-DM1) and pertuzumab for HER2-positive breast caner and ranked the targeted treatments. We performed a network meta-analysis of both direct and indirect comparisons to evaluate the effect of adding HER2-targeted agents to standard treatment and examined side effects.MethodsWe performed a Bayesian-framework network meta-analysis of randomized controlled trials to compare 6 HER2-targeted treatment regimens and 1 naïve standard treatment (NST, without any-targeted drugs) in targeted treatment of HER2+ breast cancer in adults. These treatment regimens were T-DM1, LC (lapatinib), HC (trastuzumab), PEC (pertuzumab), LHC (lapatinib and trastuzumab), and PEHC (pertuzumab and trastuzumab). The main outcomes were overall survival and response rates. We also examined side effects of rash, LVEF (left ventricular ejection fraction), fatigue, and gastrointestinal disorders, and performed subgroup analysis for the different treatment regimens in metastatic or advanced breast cancer.ResultsWe identified 25 articles of 21 trials, with data for 11,276 participants. T-DM1 and PEHC were more efficient drug regimens with regard to overall survival as compared with LHC, LC, HC and PEC. The incidence of treatment-related rash occurs more frequently in the patients who received LC treatment regimen than PEHC and T-DM1 and HC. In subgroup analysis, T-DM1 was associated with increased overall survival as compared with LC and HC. PEHC was associated with increased overall response as compared with LC, HC, and NST.ConclusionsOverall, the regimen of T-DM1 as well as pertuzumab in combination with trastuzumab and docetaxel is efficacious with fewer side effects as compared with other regimens, especially for advanced HER2+ breast cancer.ImpactThis study suggests that both T-DM1 and PEHC therapy are potentially and equally useful treatments for HER2+ breast cancer.

Project description:This systematic review aimed to identify neoadjuvant anti-human epidermal growth factor receptor 2 (HER2) therapies with the best balance between efficacy and safety. A network meta-analysis was applied to estimate the risk ratios along with 95% confidence intervals (CIs) for pathological complete response (pCR) and serious adverse events (SAE). A mixed-effect parametric survival analysis was conducted to assess the disease-free survival (DFS) between treatments. Twenty-one RCTs with eleven regimens of neoadjuvant anti-HER2 therapy (i.e., trastuzumab + chemotherapy (TC), lapatinib + chemotherapy (LC), pertuzumab + chemotherapy (PC), pertuzumab + trastuzumab (PT), trastuzumab emtansine + pertuzumab (T-DM1P), pertuzumab + trastuzumab + chemotherapy (PTC), lapatinib + trastuzumab + chemotherapy (LTC), trastuzumab emtansine + lapatinib + chemotherapy (T-DM1LC), trastuzumab emtansine + pertuzumab + chemotherapy(T-DM1PC), PTC followed by T-DM1P (PTC_T-DM1P), and trastuzumab emtansine (T-DM1)) and chemotherapy alone were included. When compared to TC, only PTC had a significantly higher DFS with a hazard ratio (95% CI) of 0.54 (0.32-0.91). The surface under the cumulative ranking curve (SUCRA) suggested that T-DM1LC (91.9%) was ranked first in achieving pCR, followed by the PTC_T-DM1P (90.5%), PTC (74.8%), and T-DM1PC (73.5%) regimens. For SAEs, LTC, LC, and T-DM1LC presented with the highest risks (SUCRA = 10.7%, 16.8%, and 20.8%), while PT (99.2%), T-DM1P (88%), and T-DM1 (83.9%) were the safest regimens. The T-DM1PC (73.5% vs. 71.6%), T-DM1 (70.5% vs. 83.9%), and PTC_T-DM1P (90.5% vs. 47.3%) regimens offered the optimal balance between pCR and SAE. The T-DM1PC, T-DM1, and PTC_T-DM1P regimens had the optimal balance between efficacy and safety, while DFS was highest for the PTC regimen. However, these results were based on a small number of studies, and additional RCTs assessing the efficacy of regimens with T-DM1 are still needed to confirm these findings.

Project description:BackgroundGlobal profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks.ResultsIn this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells.ConclusionsOur study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.

Project description:To understand the role of HER2-associated signaling network in breast cancer stem cells (BCSC) using radioresistant breast cancer cells and clinical recurrent breast cancers to evaluate HER2-targeted therapy as a tumor eliminating strategy for recurrent HER2(-/low) breast cancers.HER2-expressing BCSCs (HER2(+)/CD44(+)/CD24(-/low)) were isolated from radiation-treated breast cancer MCF7 cells and in vivo irradiated MCF7 xenograft tumors. Tumor aggressiveness and radioresistance were analyzed by gap filling, Matrigel invasion, tumor-sphere formation, and clonogenic survival assays. The HER2/CD44 feature was analyzed in 40 primary and recurrent breast cancer specimens. Protein expression profiling in HER2(+)/CD44(+)/CD24(-/low) versus HER2(-)/CD44(+)/CD24(-/low) BCSCs was conducted with two-dimensional difference gel electrophoresis (2-D DIGE) and high-performance liquid chromatography tandem mass spectrometry (HPLC/MS-MS) analysis and HER2-mediated signaling network was generated by MetaCore program.Compared with HER2-negative BCSCs, HER2(+)/CD44(+)/CD24(-/low) cells showed elevated aldehyde dehydrogenase (ALDH) activity and aggressiveness tested by Matrigel invasion, tumor sphere formation, and in vivo tumorigenesis. The enhanced aggressive phenotype and radioresistance of the HER2(+)/CD44(+)/CD24(-/low) cells were markedly reduced by inhibition of HER2 via siRNA or Herceptin treatments. Clinical breast cancer specimens revealed that cells coexpressing HER2 and CD44 were more frequently detected in recurrent (84.6%) than primary tumors (57.1%). In addition, 2-D DIGE and HPLC/MS-MS of HER2(+)/CD44(+)/CD24(-/low) versus HER2(-)/CD44(+)/CD24(-/low) BCSCs reported a unique HER2-associated protein profile including effectors involved in tumor metastasis, apoptosis, mitochondrial function, and DNA repair. A specific feature of HER2-STAT3 network was identified.This study provides the evidence that HER2-mediated prosurvival signaling network is responsible for the aggressive phenotype of BCSCs that could be targeted to control the therapy-resistant HER2(-/low) breast cancer.

Dataset Information

The Hierarchical Modular Structure of HER2+ Breast Cancer Network.

Publications

The Hierarchical Modular Structure of HER2+ Breast Cancer Network.

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