scholarly journals miRNA-135b Contributes to Triple Negative Breast Cancer Molecular Heterogeneity: Different Expression Profile in Basal-like Versus non-Basal-like Phenotypes

2018 ◽  
Vol 15 (6) ◽  
pp. 536-548 ◽  
Author(s):  
Paolo Uva ◽  
Paolo Cossu-Rocca ◽  
Federica Loi ◽  
Giovanna Pira ◽  
Luciano Murgia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Expression Profile ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Heterogeneity

scholarly journals Molecular heterogeneity in adjacent cells in triple-negative breast cancer

2015 ◽  
pp. 231 ◽  
Author(s):  
Eugene P. Frenkel ◽  
Michael Huebschman ◽  
Nancy Lane ◽  
Judith Devlin ◽  
Huaying Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Heterogeneity

Abstract 3698: Unraveling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis

2018 ◽  
Author(s):  
Yacine Bareche ◽  
David Venet ◽  
Philippe Aftimos ◽  
Michail Ignatiadis ◽  
Martine Piccart ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Heterogeneity

scholarly journals SIK2 Restricts Autophagic Flux To Support Triple-Negative Breast Cancer Survival

2016 ◽  
Vol 36 (24) ◽  
pp. 3048-3057 ◽  
Author(s):  
Kimberly E. Maxfield ◽  
Jennifer Macion ◽  
Hariprasad Vankayalapati ◽  
Angelique W. Whitehurst
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Large Scale ◽  
Triple Negative ◽  
Cancer Survival ◽  
Treatment Options ◽  
Autophagic Flux ◽  
Molecular Heterogeneity ◽  
Loss Of Function

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with multiple, distinct molecular subtypes that exhibit unique transcriptional programs and clinical progression trajectories. Despite knowledge of the molecular heterogeneity of the disease, most patients are limited to generic, indiscriminate treatment options: cytotoxic chemotherapy, surgery, and radiation. To identify new intervention targets in TNBC, we used large-scale, loss-of-function screening to identify molecular vulnerabilities among different oncogenomic backgrounds. This strategy returned salt inducible kinase 2 (SIK2) as essential for TNBC survival. Genetic or pharmacological inhibition of SIK2 leads to increased autophagic flux in both normal-immortalized and tumor-derived cell lines. However, this activity causes cell death selectively in breast cancer cells and is biased toward the claudin-low subtype. Depletion of ATG5, which is essential for autophagic vesicle formation, rescued the loss of viability following SIK2 inhibition. Importantly, we find that SIK2 is essential for TNBC tumor growth in vivo . Taken together, these findings indicate that claudin-low tumor cells rely on SIK2 to restrain maladaptive autophagic activation. Inhibition of SIK2 therefore presents itself as an intervention opportunity to reactivate this tumor suppressor mechanism.

scholarly journals Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis

2018 ◽  
Vol 29 (4) ◽  
pp. 895-902 ◽  
Author(s):  
Y. Bareche ◽  
D. Venet ◽  
M. Ignatiadis ◽  
P. Aftimos ◽  
M. Piccart ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Heterogeneity

NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
NandiniA Sahasrabuddhe ◽  
Aruna Korlimarla ◽  
Madhura Kulkarni ◽  
Vinay Kusuma ◽  
JyothiS Prabhu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Heterogeneity ◽  
Cancer Genes ◽  
Breast Cancer Patients

scholarly journals Expression profile of CADM1 and CADM4 in triple negative breast cancer with primary systemic therapy

2018 ◽  
Author(s):  
Yasuyuki Kanke ◽  
Motonobu Saito ◽  
Noriko Abe ◽  
Katsuharu Saito ◽  
Akiteru Goto ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Expression Profile ◽  
Triple Negative Breast Cancer ◽  
Systemic Therapy ◽  
Triple Negative ◽  
Primary Systemic Therapy

scholarly journals Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

2020 ◽  
Author(s):  
Yiqun Han ◽  
Jiayu Wang ◽  
Binghe Xu
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prediction Model ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Gene Set Enrichment Analysis ◽  
Molecular Heterogeneity ◽  
Mtorc1 Signaling

Abstract Background: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC).Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. The molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, the machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of genes were undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of robust model, and a nomogram was constructed with the independent predictors for pCR rate.Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response.Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.

scholarly journals Modeling Heterogeneity of Triple-Negative Breast Cancer Uncovers a Novel Combinatorial Treatment Overcoming Primary Drug Resistance

2020 ◽  
Author(s):  
Fabienne Lamballe ◽  
Fahmida Ahmad ◽  
Yaron Vinik ◽  
Olivier Castellanet ◽  
Fabrice Daian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mouse Model ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Tumor Regression ◽  
Breast Cancer Subtype ◽  
Mitotic Catastrophe ◽  
Molecular Heterogeneity ◽  
Primary Drug Resistance ◽  
Druggable Targets

AbstractTriple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterized by a remarkable molecular heterogeneity. Currently, there are no effective druggable targets and advanced preclinical models of the human disease. Here, we generated a unique mouse model (MMTV-R26Met mice) of mammary tumors driven by a subtle increase in the expression of the wild-type MET receptor. MMTV-R26Met mice develop spontaneous, exclusive TNBC tumors, recapitulating primary resistance to treatment of patients. Proteomic profiling of MMTV-R26Met tumors and machine learning approach showed that the model faithfully recapitulates inter-tumoral heterogeneity of human TNBC. Further signaling network analysis highlighted potential druggable targets, of which co-targeting of WEE1 and BCL-XL synergistically killed TNBC cells and efficiently induced tumor regression. Mechanistically, BCL-XL inhibition exacerbates the dependency of TNBC cells on WEE1 function, leading to Histone H3 and phosphoS33RPA32 upregulation, RRM2 downregulation, cell cycle perturbation, mitotic catastrophe and apoptosis. Our study introduces a unique, powerful mouse model for studying TNBC formation and evolution, its heterogeneity, and for identifying efficient therapeutic targets.

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