scholarly journals Comparative gene expression study highlights molecular similarities between triple negative breast cancer tumours and feline mammary carcinomas

2022 ◽  
Author(s):  
Lara Sommerville ◽  
Jane Howard ◽  
Shane Evans ◽  
Pamela Kelly ◽  
Amanda McCann
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Gene Expression Study ◽  
Expression Study ◽  
Mammary Carcinomas

scholarly journals An open-label, pilot study of veliparib and lapatinib in patients with metastatic, triple-negative breast cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Erica M. Stringer-Reasor ◽  
Jori E. May ◽  
Eva Olariu ◽  
Valerie Caterinicchia ◽  
Yufeng Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Dna Repair ◽  
Pilot Study ◽  
Expression Analysis ◽  
Triple Negative Breast Cancer ◽  
Gene Expression Analysis ◽  
Triple Negative ◽  
Egfr Inhibition ◽  
Link Type

Abstract Background Poly (ADP-ribose)-polymerase inhibitors (PARPi) have been approved for cancer patients with germline BRCA1/2 (gBRCA1/2) mutations, and efforts to expand the utility of PARPi beyond BRCA1/2 are ongoing. In preclinical models of triple-negative breast cancer (TNBC) with intact DNA repair, we have previously shown an induced synthetic lethality with combined EGFR inhibition and PARPi. Here, we report the safety and clinical activity of lapatinib and veliparib in patients with metastatic TNBC. Methods A first-in-human, pilot study of lapatinib and veliparib was conducted in metastatic TNBC (NCT02158507). The primary endpoint was safety and tolerability. Secondary endpoints were objective response rates and pharmacokinetic evaluation. Gene expression analysis of pre-treatment tumor biopsies was performed. Key eligibility included TNBC patients with measurable disease and prior anthracycline-based and taxane chemotherapy. Patients with gBRCA1/2 mutations were excluded. Results Twenty patients were enrolled, of which 17 were evaluable for response. The median number of prior therapies in the metastatic setting was 1 (range 0–2). Fifty percent of patients were Caucasian, 45% African–American, and 5% Hispanic. Of evaluable patients, 4 demonstrated a partial response and 2 had stable disease. There were no dose-limiting toxicities. Most AEs were limited to grade 1 or 2 and no drug–drug interactions noted. Exploratory gene expression analysis suggested baseline DNA repair pathway score was lower and baseline immunogenicity was higher in the responders compared to non-responders. Conclusions Lapatinib plus veliparib therapy has a manageable safety profile and promising antitumor activity in advanced TNBC. Further investigation of dual therapy with EGFR inhibition and PARP inhibition is needed. Trial registration ClinicalTrials.gov, NCT02158507. Registered on 12 September 2014

scholarly journals The BIRC Family Genes Expression in Patients with Triple Negative Breast Cancer

2021 ◽  
Vol 22 (4) ◽  
pp. 1820
Author(s):  
Anna Makuch-Kocka ◽  
Janusz Kocki ◽  
Anna Brzozowska ◽  
Jacek Bogucki ◽  
Przemysław Kołodziej ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Data ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Lymphatic Vessels ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Cancer Tissue ◽  
Expression Levels

The BIRC (baculoviral IAP repeat-containing; BIRC) family genes encode for Inhibitor of Apoptosis (IAP) proteins. The dysregulation of the expression levels of the genes in question in cancer tissue as compared to normal tissue suggests that the apoptosis process in cancer cells was disturbed, which may be associated with the development and chemoresistance of triple negative breast cancer (TNBC). In our study, we determined the expression level of eight genes from the BIRC family using the Real-Time PCR method in patients with TNBC and compared the obtained results with clinical data. Additionally, using bioinformatics tools (Ualcan and The Breast Cancer Gene-Expression Miner v4.5 (bc-GenExMiner v4.5)), we compared our data with the data in the Cancer Genome Atlas (TCGA) database. We observed diverse expression pattern among the studied genes in breast cancer tissue. Comparing the expression level of the studied genes with the clinical data, we found that in patients diagnosed with breast cancer under the age of 50, the expression levels of all studied genes were higher compared to patients diagnosed after the age of 50. We observed that in patients with invasion of neoplastic cells into lymphatic vessels and fat tissue, the expression levels of BIRC family genes were lower compared to patients in whom these features were not noted. Statistically significant differences in gene expression were also noted in patients classified into three groups depending on the basis of the Scarff-Bloom and Richardson (SBR) Grading System.

scholarly journals Breast Cancer Type Classification Using Machine Learning

2021 ◽  
Vol 11 (2) ◽  
pp. 61
Author(s):  
Jiande Wu ◽  
Chindo Hicks
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Machine Learning ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Genomic Research ◽  
Support Vector ◽  
Cancer Type ◽  
Classification Models

Background: Breast cancer is a heterogeneous disease defined by molecular types and subtypes. Advances in genomic research have enabled use of precision medicine in clinical management of breast cancer. A critical unmet medical need is distinguishing triple negative breast cancer, the most aggressive and lethal form of breast cancer, from non-triple negative breast cancer. Here we propose use of a machine learning (ML) approach for classification of triple negative breast cancer and non-triple negative breast cancer patients using gene expression data. Methods: We performed analysis of RNA-Sequence data from 110 triple negative and 992 non-triple negative breast cancer tumor samples from The Cancer Genome Atlas to select the features (genes) used in the development and validation of the classification models. We evaluated four different classification models including Support Vector Machines, K-nearest neighbor, Naïve Bayes and Decision tree using features selected at different threshold levels to train the models for classifying the two types of breast cancer. For performance evaluation and validation, the proposed methods were applied to independent gene expression datasets. Results: Among the four ML algorithms evaluated, the Support Vector Machine algorithm was able to classify breast cancer more accurately into triple negative and non-triple negative breast cancer and had less misclassification errors than the other three algorithms evaluated. Conclusions: The prediction results show that ML algorithms are efficient and can be used for classification of breast cancer into triple negative and non-triple negative breast cancer types.

Identification of CCNB2 expression in triple-negative breast cancer based on bioinformatics results

2021 ◽  
Author(s):  
jintao cao ◽  
SHUAI SUN ◽  
RAN LI ◽  
RUI MIN ◽  
XINGYU FAN ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Protein Complex ◽  
Triple Negative ◽  
Expression Profiles ◽  
Pathway Enrichment Analysis ◽  
Analysis Tool ◽  
The Core ◽  
Core Genes

Abstract Background The current epidemiology shows that the incidence of breast cancer is increasing year by year and tends to be younger. Triple-negative breast cancer is the most malignant of breast cancer subtypes. The application of bioinformatics in tumor research is becoming more and more extensive. This study provided research ideas and basis for exploring the potential targets of gene therapy for triple-negative breast cancer (TNBC). Methods We analyzed three gene expression profiles (GSE64790、GSE62931、GSE38959) selected from the Gene Expression Omnibus (GEO) database. The GEO2R online analysis tool was used to screen for differentially expressed genes (DEGs) between TNBC and normal tissues. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to identify the pathways and functional annotation of DEGs. Protein–protein interaction network of these DEGs were visualized by the Metascape gene-list analysis tool so that we could find the protein complex containing the core genes. Subsequently, we investigated the transcriptional data of the core genes in patients with breast cancer from the Oncomine database. Moreover, the online Kaplan–Meier plotter survival analysis tool was used to evaluate the prognostic value of core genes expression in TNBC patients. Finally, immunohistochemistry (IHC) was used to evaluated the expression level and subcellular localization of CCNB2 on TNBC tissues. Results A total of 66 DEGs were identified, including 33 up-regulated genes and 33 down-regulated genes. Among them, a potential protein complex containing five core genes was screened out. The high expression of these core genes was correlated to the poor prognosis of patients suffering breast cancer, especially the overexpression of CCNB2. CCNB2 protein positively expressed in the cytoplasm, and its expression in triple-negative breast cancer tissues was significantly higher than that in adjacent tissues. Conclusions CCNB2 may play a crucial role in the development of TNBC and has the potential as a prognostic biomarker of TNBC.

scholarly journals CBP/β-Catenin/FOXM1 Is a Novel Therapeutic Target in Triple Negative Breast Cancer

Cancers ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 525 ◽  
Author(s):  
Alexander Ring ◽  
Cu Nguyen ◽  
Goar Smbatyan ◽  
Debu Tripathy ◽  
Min Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Drug Resistance ◽  
Triple Negative Breast Cancer ◽  
Therapeutic Target ◽  
Triple Negative ◽  
Creb Binding Protein ◽  
Novel Therapeutic

Background: Triple negative breast cancers (TNBCs) are an aggressive BC subtype, characterized by high rates of drug resistance and a high proportion of cancer stem cells (CSC). CSCs are thought to be responsible for tumor initiation and drug resistance. cAMP-response element-binding (CREB) binding protein (CREBBP or CBP) has been implicated in CSC biology and may provide a novel therapeutic target in TNBC. Methods: RNA Seq pre- and post treatment with the CBP-binding small molecule ICG-001 was used to characterize CBP-driven gene expression in TNBC cells. In vitro and in vivo TNBC models were used to determine the therapeutic effect of CBP inhibition via ICG-001. Tissue microarrays (TMAs) were used to investigate the potential of CBP and associated proteins as biomarkers in TNBC. Results: The CBP/ß-catenin/FOXM1 transcriptional complex drives gene expression in TNBC and is associated with increased CSC numbers, drug resistance and poor survival outcome. Targeting of CBP/β-catenin/FOXM1 with ICG-001 eliminated CSCs and sensitized TNBC tumors to chemotherapy. Immunohistochemistry of TMAs demonstrated a significant correlation between FOXM1 expression and TNBC subtype. Conclusion: CBP/β-catenin/FOXM1 transcriptional activity plays an important role in TNBC drug resistance and CSC phenotype. CBP/β-catenin/FOXM1 provides a molecular target for precision therapy in triple negative breast cancer and could form a rationale for potential clinical trials.

scholarly journals Response to FEC Chemotherapy and Oncolytic HSV-1 Is Associated with Macrophage Polarization and Increased Expression of S100A8/A9 in Triple Negative Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5590
Author(s):  
Alyssa Vito ◽  
Nader El-Sayes ◽  
Omar Salem ◽  
Yonghong Wan ◽  
Karen L. Mossman
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Macrophage Polarization ◽  
Gene Signature ◽  
Immune Checkpoint Blockade ◽  
Differential Gene ◽  
Microarray Analyses ◽  
Tumor Cell Killing

The era of immunotherapy has seen an insurgence of novel therapies driving oncologic research and the clinical management of the disease. We have previously reported that a combination of chemotherapy (FEC) and oncolytic virotherapy (oHSV-1) can be used to sensitize otherwise non-responsive tumors to immune checkpoint blockade and that tumor-infiltrating B cells are required for the efficacy of our therapeutic regimen in a murine model of triple-negative breast cancer. In the studies herein, we have performed gene expression profiling using microarray analyses and have investigated the differential gene expression between tumors treated with FEC + oHSV-1 versus untreated tumors. In this work, we uncovered a therapeutically driven switch of the myeloid phenotype and a gene signature driving increased tumor cell killing.

scholarly journals DNAJC28 expression associates with survival in triple negative breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Overall Survival ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Microarray Data ◽  
Triple Negative ◽  
Breast Cancer Patients ◽  
Primary Tumors ◽  
Significant Gene

We mined published microarray data (1) to understand the most significant gene expression differences in the tumors of triple negative breast cancer patients based on survival following treatment: dead or alive. We observed significant transcriptome-wide differential expression of DnaJ (Hsp40) homolog, subfamily C, member 28, encoded by DNAJC28 when comparing the primary tumors of triple negative breast cancer patients dead or alive. Importantly, DNAJC28 expression was correlated with overall survival in patients with breast cancer. DNAJC28 may be of relevance as a biomarker or as a molecule of interest in understanding the etiology or progression of triple negative breast cancer.

scholarly journals PAX5 expression associates with survival in triple negative breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Microarray Data ◽  
Triple Negative ◽  
Molecular Subtype ◽  
Breast Cancer Patients ◽  
Primary Tumors ◽  
Significant Gene

We mined published microarray data (1) to understand the most significant gene expression differences in the tumors of triple negative breast cancer patients based on survival following treatment: dead or alive. We observed significant transcriptome-wide differential expression of paired box 5, encoded by PAX5 when comparing the primary tumors of triple negative breast cancer patients dead or alive. Importantly, PAX5 expression was significantly correlated with overall survival in basal subtype breast cancer, a molecular subtype sharing significant overlap with triple negative breast cancer. PAX5 may be of relevance as a biomarker or as a molecule of interest in understanding the etiology or progression of triple negative breast cancer.

scholarly journals Prognostic value of CD8 + PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Joe Yeong ◽  
Jeffrey Chun Tatt Lim ◽  
Bernett Lee ◽  
Huihua Li ◽  
Clara Chong Hui Ong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Prognostic Value ◽  
Triple Negative
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