scholarly journals Prognostic correlations with the microbiome of breast cancer subtypes

2021 ◽  
Vol 12 (9) ◽  
Author(s):  
Sagarika Banerjee ◽  
Zhi Wei ◽  
Tian Tian ◽  
Dipayan Bose ◽  
Natalie N. C. Shih ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Outcomes ◽  
Clinical Data ◽  
Therapeutic Intervention ◽  
Comprehensive Analysis ◽  
Intervention Strategies ◽  
Tumor Subtype ◽  
Cancer Subtypes ◽  
Disease Outcomes ◽  
Disease Prognosis

AbstractAlterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial signatures, using a pan-pathogen microarray strategy. The signature (includes viruses, bacteria, fungi, and parasites) of each tumor subtype was correlated with clinical data to identify microbes with prognostic potential. The subtypes of BC had specific viromes and microbiomes, with ER+ and TN tumors showing the most and least diverse microbiome, respectively. The specific microbial signatures allowed discrimination between different BC subtypes. Furthermore, we demonstrated correlations between the presence and absence of specific microbes in BC subtypes with the clinical outcomes. This study provides a comprehensive map of the oncobiome of BC subtypes, with insights into disease prognosis that can be critical for precision therapeutic intervention strategies.

scholarly journals Comprehensive Analysis of the Unfolded Protein Response in Breast Cancer Subtypes

2017 ◽  
pp. 1-9 ◽  
Author(s):  
Dadi Jiang ◽  
Brandon Turner ◽  
Jie Song ◽  
Ruijiang Li ◽  
Maximilian Diehn ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Patient Survival ◽  
Gene Signature ◽  
Comprehensive Analysis ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes ◽  
Unfolded Protein ◽  
The Unfolded Protein Response ◽  
Protein Response

Purpose Triple-negative breast cancers (TNBCs) are associated with a worse prognosis and patients with TNBC have fewer therapeutic options than patients with non-TNBC. Recently, the IRE1α-XBP1 branch of the unfolded protein response (UPR) was implicated in TNBC prognosis on the basis of a relatively small patient population, suggesting the diagnostic and therapeutic value of this pathway in TNBCs. In addition, the IRE1α-XBP1 and hypoxia-induced factor 1 α (HIF1α) pathways have been identified as interacting partners in TNBC, suggesting a novel mechanism of regulation. To comprehensively evaluate and validate these findings, we investigated the relative activities and relevance to patient survival of the UPR and HIF1α pathways in different breast cancer subtypes in large populations of patients. Materials and Methods We performed a comprehensive analysis of gene expression and survival data from large cohorts of patients with breast cancer. The patients were stratified based on the average expression of the UPR or HIF1α gene signatures. Results We identified a strong positive association between the XBP1 gene signature and estrogen receptor–positive status or the HIF1α gene signature, as well as the predictive value of the XBP1 gene signature for survival of patients who are estrogen receptor negative, or have TNBC or HER2+. In contrast, another important UPR branch, the ATF4/CHOP pathway, lacks prognostic value in breast cancer in general. Activity of the HIF1α pathway is correlated with patient survival in all the subtypes evaluated. Conclusion These findings clarify the relevance of the UPR pathways in different breast cancer subtypes and underscore the potential therapeutic importance of the IRE1α-XBP1 branch in breast cancer treatment.

Clinical Outcomes and Breast Cancer Subtypes in Patients with Brain Metastases

Onkologie ◽  
2010 ◽  
Vol 33 (4) ◽  
pp. 146-152 ◽  
Author(s):  
Hyuk-Chan Kwon ◽  
Sung Yong Oh ◽  
Sung-Hyun Kim ◽  
Suee Lee ◽  
Kyung A. Kwon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastases ◽  
Clinical Outcomes ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes

Comprehensive analysis of genomic alterations, clinical outcomes, putative functions and potential therapeutic value of MMP11 in human breast cancer

Gene Reports ◽  
2020 ◽  
Vol 21 ◽  
pp. 100852
Author(s):  
Amritha Sathyanarayanan ◽  
Aparna Natarajan ◽  
Oviya Revathi Paramasivam ◽  
Prarthana Gopinath ◽  
Gopisetty Gopal
Keyword(s):  
Breast Cancer ◽  
Clinical Outcomes ◽  
Human Breast Cancer ◽  
Comprehensive Analysis ◽  
Human Breast ◽  
Genomic Alterations ◽  
Therapeutic Value

scholarly journals Current Triple-Negative Breast Cancer Subtypes: Dissecting the Most Aggressive Form of Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Miquel Ensenyat-Mendez ◽  
Pere Llinàs-Arias ◽  
Javier I. J. Orozco ◽  
Sandra Íñiguez-Muñoz ◽  
Matthew P. Salomon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Clinical Outcomes ◽  
Triple Negative Breast Cancer ◽  
High Throughput Sequencing ◽  
Triple Negative ◽  
Growth Factor Receptor ◽  
Her2 Overexpression ◽  
Systematic Classification ◽  
Cancer Subtypes

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease defined by the absence of estrogen receptor (ER) and progesterone receptor (PR) expression, and human epidermal growth factor receptor 2 (HER2) overexpression that lacks targeted treatments, leading to dismal clinical outcomes. Thus, better stratification systems that reflect intrinsic and clinically useful differences between TNBC tumors will sharpen the treatment approaches and improve clinical outcomes. The lack of a rational classification system for TNBC also impacts current and emerging therapeutic alternatives. In the past years, several new methodologies to stratify TNBC have arisen thanks to the implementation of microarray technology, high-throughput sequencing, and bioinformatic methods, exponentially increasing the amount of genomic, epigenomic, transcriptomic, and proteomic information available. Thus, new TNBC subtypes are being characterized with the promise to advance the treatment of this challenging disease. However, the diverse nature of the molecular data, the poor integration between the various methods, and the lack of cost-effective methods for systematic classification have hampered the widespread implementation of these promising developments. However, the advent of artificial intelligence applied to translational oncology promises to bring light into definitive TNBC subtypes. This review provides a comprehensive summary of the available classification strategies. It includes evaluating the overlap between the molecular, immunohistochemical, and clinical characteristics between these approaches and a perspective about the increasing applications of artificial intelligence to identify definitive and clinically relevant TNBC subtypes.

5098 Clinical outcomes and breast cancer subtypes in patients with brain metastases

2009 ◽  
Vol 7 (2) ◽  
pp. 289-290
Author(s):  
H. Kwon ◽  
K.A. Kwon ◽  
S. Lee ◽  
Y.J. Choi ◽  
M. Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastases ◽  
Clinical Outcomes ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes

Identification of new therapeutic leads for triple negative breast cancer subtypes

Planta Medica ◽  
2015 ◽  
Vol 81 (11) ◽  
Author(s):  
AJ Robles ◽  
L Du ◽  
S Cai ◽  
RH Cichewicz ◽  
SL Mooberry
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes ◽  
Therapeutic Leads
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