Clinical Implications of Androgen-Positive Triple-Negative Breast Cancer

Brumec, Maša; Sobočan, Monika; Takač, Iztok; Arko, Darja

doi:10.3390/cancers13071642

Cited by 23 publications

(23 citation statements)

References 117 publications

(123 reference statements)

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“…AR could therefore be used as a novel therapeutic target for the LAR subtype. The use of enzalutamide, an androgen receptor inhibitor, is currently being explored in TNBC patients who express the androgen receptor (NCT01889238) [ 30 , 31 , 32 ].…”

Section: Discussionmentioning

confidence: 99%

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Bissanum

Chaichulee

Kamolphiwong

et al. 2021

JPM

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Triple negative breast cancer (TNBC) lacks well-defined molecular targets and is highly heterogenous, making treatment challenging. Using gene expression analysis, TNBC has been classified into four different subtypes: basal-like immune-activated (BLIA), basal-like immune-suppressed (BLIS), mesenchymal (MES), and luminal androgen receptor (LAR). However, there is currently no standardized method for classifying TNBC subtypes. We attempted to define a gene signature for each subtype, and to develop a classification method based on machine learning (ML) for TNBC subtyping. In these experiments, gene expression microarray data for TNBC patients were downloaded from the Gene Expression Omnibus database. Differentially expressed genes unique to 198 known TNBC cases were identified and selected as a training gene set to train in seven different classification models. We produced a training set consisting of 719 DEGs selected from uniquely expressed genes of all four subtypes. The highest average accuracy of classification of the BLIA, BLIS, MES, and LAR subtypes was achieved by the SVM algorithm (accuracy 95–98.8%; AUC 0.99–1.00). For model validation, we used 334 samples of unknown TNBC subtypes, of which 97 (29.04%), 73 (21.86%), 39 (11.68%) and 59 (17.66%) were predicted to be BLIA, BLIS, MES, and LAR, respectively. However, 66 TNBC samples (19.76%) could not be assigned to any subtype. These samples contained only three upregulated genes (EN1, PROM1, and CCL2). Each TNBC subtype had a unique gene expression pattern, which was confirmed by identification of DEGs and pathway analysis. These results indicated that our training gene set was suitable for development of classification models, and that the SVM algorithm could classify TNBC into four unique subtypes. Accurate and consistent classification of the TNBC subtypes is essential for personalized treatment and prognosis of TNBC.

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Section: Discussionmentioning

confidence: 99%

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Bissanum

Chaichulee

Kamolphiwong

et al. 2021

JPM

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Section: Mechanism Of Poly (Adp-ribose) Polymerase Inhibitionmentioning

confidence: 99%

“…AR is expressed in 15%–50% of TNBCs and represents an opportunity for targeted therapy of TNBCs [ 58 ]. A combination of AR inhibitors and PARP1 inhibitors could be a promising target for sporadic positive-AR expression and methylation-mediated BRCA1 dysfunction in patients with TNBC [ 58 , 59 ]. The AR antagonist MDV3100 (enzalutamide) has an antitumor potency greater than first-generation AR inhibitors; it suppresses AR nuclear translocation and decreases DNA binding and coactivator recruitment [ 60 ].…”

Section: Mechanism Of Poly (Adp-ribose) Polymerase Inhibitionmentioning

confidence: 99%

Role of PARP in TNBC: Mechanism of Inhibition, Clinical Applications, and Resistance

2021

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Triple-negative breast cancer is a combative cancer type with a highly inflated histological grade that leads to poor theragnostic value. Gene, protein, and receptor-specific targets have shown effective clinical outcomes in patients with TNBC. Cells are frequently exposed to DNA-damaging agents. DNA damage is repaired by multiple pathways; accumulations of mutations occur due to damage to one or more pathways and lead to alterations in normal cellular mechanisms, which lead to development of tumors. Advances in target-specific cancer therapies have shown significant momentum; most treatment options cause off-target toxicity and side effects on healthy tissues. PARP (poly(ADP-ribose) polymerase) is a major protein and is involved in DNA repair pathways, base excision repair (BER) mechanisms, homologous recombination (HR), and nonhomologous end-joining (NEJ) deficiency-based repair mechanisms. DNA damage repair deficits cause an increased risk of tumor formation. Inhibitors of PARP favorably kill cancer cells in BRCA-mutations. For a few years, PARPi has shown promising activity as a chemotherapeutic agent in BRCA1- or BRCA2-associated breast cancers, and in combination with chemotherapy in triple-negative breast cancer. This review covers the current results of clinical trials testing and future directions for the field of PARP inhibitor development.

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“…AR is expressed in 15–35% of TNBCs [ 138 ], primarily in the luminal androgen receptor (LAR) subtype. These tumours demonstrate a gene expression signature resembling that of endocrine-responsive tumours [ 139 ], are characterised by both AR expression and androgen-dependant growth [ 140 ], and are classically less responsive to conventional cytotoxic chemotherapy. AR-antagonism in this setting, with antiandrogens such as bicalutamide, have been investigated in clinical trials [ 141 ].…”

Section: Androgen Receptor Signallingmentioning

confidence: 99%

Type 1 Nuclear Receptor Activity in Breast Cancer: Translating Preclinical Insights to the Clinic

Kumar

Freelander

Lim

2021

Cancers

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The nuclear receptor (NR) family of transcription factors is intimately associated with the development, progression and treatment of breast cancer. They are used diagnostically and prognostically, and crosstalk between nuclear receptor pathways and growth factor signalling has been demonstrated in all major subtypes of breast cancer. The majority of breast cancers are driven by estrogen receptor α (ER), and anti-estrogenic therapies remain the backbone of treatment, leading to clinically impactful improvements in patient outcomes. This serves as a blueprint for the development of therapies targeting other nuclear receptors. More recently, pivotal findings into modulating the progesterone (PR) and androgen receptors (AR), with accompanying mechanistic insights into NR crosstalk and interactions with other proliferative pathways, have led to clinical trials in all of the major breast cancer subtypes. A growing body of evidence now supports targeting other Type 1 nuclear receptors such as the glucocorticoid receptor (GR), as well as Type 2 NRs such as the vitamin D receptor (VDR). Here, we reviewed the existing preclinical insights into nuclear receptor activity in breast cancer, with a focus on Type 1 NRs. We also discussed the potential to translate these findings into improving patient outcomes.

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Clinical Implications of Androgen-Positive Triple-Negative Breast Cancer

Cited by 23 publications

References 117 publications

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Role of PARP in TNBC: Mechanism of Inhibition, Clinical Applications, and Resistance

Type 1 Nuclear Receptor Activity in Breast Cancer: Translating Preclinical Insights to the Clinic

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