Genetic Heterogeneity, Tumor Microenvironment and Immunotherapy in Triple-Negative Breast Cancer

Quercetin exerts anti-tumor immune mechanism by regulating IL-6/JAK2/STAT3 signaling pathway to deplete Treg cells

Breast cancer is still the leading cause of death among women worldwide. Due to the lack of effective drug targets, triple-negative breast cancer has a worse prognosis and higher mortality compared with other types of breast cancer, and chemotherapy is still the main treatment for triple-negative breast cancer at present. Quercetin (QUE) is a flavonoid compound found in a variety of fruits and vegetables. The mechanism of QUE has been extensively studied, such as prostate cancer, colon cancer, ovarian cancer, etc. However, the anti-tumor immune mechanism of QUE in triple-negative breast cancer remains unclear. Therefore, we assessed the anti-tumor immune effects of QUE on triple-negative breast cancer using both 4T1 cells and a xenograft mouse model of 4T1 cells. In vitro, we examined the inhibitory effects of QUE on 4T1 cells and its molecular mechanisms through MTT, Transwell, ELISA, and Western blotting. In vivo, by establishing a xenograft mouse model, we utilized flow cytometry, immunohistochemistry, ELISA, and Western blotting to evaluate the anti-tumor immune effects of QUE on triple-negative breast cancer. The results indicate that QUE inhibits the proliferation, migration, and invasion of 4T1 cells, concurrently significantly suppressing the IL-6/JAK2/STAT3 signaling pathway. Furthermore, it depletes Treg cell content in 4T1 xenograft mice, thereby improving the tumor immune microenvironment and promoting the cytotoxicity of relevant tumor immune cells. These findings suggest that QUE may serve as a potential adjuvant for immune therapy in triple-negative breast cancer.

Neoantigens and cancer-testis antigens as promising vaccine candidates for triple-negative breast cancer: Delivery strategies and clinical trials

Immunotherapy is gaining prominence as a promising strategy for treating triple-negative breast cancer (TNBC). Neoantigens (neoAgs) and cancer-testis antigens (CTAs) are tumor-specific targets originating from somatic mutations and epigenetic changes in cancer cells. These antigens hold great promise for personalized cancer vaccines, as supported by preclinical and early clinical evidence in TNBC. This review delves into the potential of neoAgs and CTAs as vaccine candidates, emphasizing diverse strategies and delivery approaches. It also highlights the current status of vaccination modalities undergoing clinical trials in TNBC therapy. A comprehensive understanding of neoAgs, CTAs, vaccination strategies, and innovative delivery methods is crucial for optimizing neoAg-based immunotherapies in clinical practice.

Association Between Polymorphisms in DNA Damage Repair Pathway Genes and Female Breast Cancer Risk

Breast cancer risk have been discussed to be associated with polymorphisms in genes as well as abnormal DNA damage repair function. This study aims to assess the relationship between genes single nucleotide polymorphisms (SNPs) related to DNA damage repair and female breast cancer risk in Chinese population. A case-control study containing 400 patients and 400 healthy controls was conducted. Genotype was identified using the sequence MassARRAY method and expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was analyzed by immunohistochemistry assay. The results revealed that ATR rs13091637 decreased breast cancer risk influenced by ER, PR (CT/TT vs. CC: adjusted odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.04-2.27, p = 0.032; CT/TT vs. CC: adjusted OR = 1.63, 95%CI: 1.14-2.35, p = 0.008) expression. Stratified analysis revealed that PALB2 rs16940342 increased breast cancer risk in response to menstrual status (AG/GG vs. AA: adjusted OR = 1.72, 95%CI: 1.13-2.62, p = 0.011) and age of menarche (AG/GG vs. AA: adjusted OR = 1.54, 95%CI: 1.03-2.31, p = 0.037), whereas ATM rs611646 and Ku70 rs132793 were associated with reduced breast cancer risk influenced by menarche (GA/AA vs. GG: adjusted OR = 0.50, 95%CI: 0.30-0.95, p = 0.033). In a summary, PALB2 rs16940342, ATR rs13091637, ATM rs611646, and Ku70 rs132793 were associated with breast cancer risk.

Pharmacological Mechanism of Mume Fructus in the Treatment of Triple-Negative Breast Cancer Based on Network Pharmacology

Our study aims to find the relevant mechanism of Mume Fructus in the treatment of triple-negative breast cancer (TNBC) by network pharmacology analysis and experimental validation. The effective compounds of Mume Fructus and TNBC-related target genes were imported into Cytoscape to construct a Mume Fructus-effective compounds-disease target network. The common targets of Mume Fructus and TNBC were determined by drawing Venn diagrams. Then, the intersection targets were transferred to the STRING database to construct a protein-protein interaction (PPI) network. To investigate the mechanism of Mume Fructus in treatment of TNBC, breast cancer cell (MDA-MB-231) was treated with Mume Fructus and/or transfected with small interference RNA-PKM2(siPKM2). CCK-8 assay, cell clonal formation assay, transwell, flow cytometry, qRT-PCR, and western blotting were performed. Eight effective compounds and 145 target genes were obtained, and the Mume Fructus- effective compounds-disease target network was constructed. Then through the analysis of the PPI network, we obtained 10 hub genes including JUN, MAPK1, RELA, AKT1, FOS, ESR1, IL6, MAPK8, RXRA, and MYC. KEGG enrichment analysis showed that JUN, MAPK1, RELA, FOS, ESR1, IL6, MAPK8, and RXRA were enriched in the Th17 cell differentiation signaling pathway. Loss of PKM2 and Mume Fructus both inhibited the malignant phenotype of MDA-MB-231 cells. And siPKM2 further aggravated the Mume Fructus inhibition of malignancy of breast cancer cells. Network pharmacology analysis suggests that Mume Fructus has multiple therapeutic targets for TNBC and may play a therapeutic role by modulating the immune microenvironment of breast cancer.

Identification of hub genes and diagnostic efficacy for triple-negative breast cancer through WGCNA and Mendelian randomization

OBJECTIVE

Triple-negative breast cancer (TNBC) represents a particularly aggressive form of breast cancer with a poor prognosis due to a lack of targeted treatments resulting from limited a understanding of the underlying mechanisms. The aim of this study was the identification of hub genes for TNBC and assess their clinical applicability in predicting the disease.

METHODS

This study employed a combination of weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) to identify new susceptible modules and central genes in TNBC. The potential functional roles of the central genes were investigated using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Furthermore, a predictive model and ROC curve were developed to assess the diagnostic performance of the identified central genes. The correlation between CCNB1 and immune cells proportion was also investigated. At last, a Mendelian randomization (MR) analysis utilizing Genome-Wide Association Study (GWAS) data was analyzed to establish the causal effect of CCNB1 level on TNBC.

RESULTS

WGCNA was applied to determine gene co-expression maps and identify the most relevant module. Through a screening process, 1585 candidate hub genes were subsequently identified with WGCNA and DEGs. GO and KEGG function enrichment analysis indicated that these core genes were related to various biological processes, such as organelle fission, chromosome segregation, nuclear division, mitotic cell cycle phase transition, the cell cycle, amyotrophic lateral sclerosis, and motor proteins. Using STRING and Cytoscape, the top five genes with high degrees were identified as CDC2, CCNB1, CCNA2, TOP2A, and CCNB2. The nomogram model demonstrated good performance in predicting TNBC risk and was proven effective in diagnosis, as evidenced by the receiver operating characteristic (ROC) curve. Further investigation revealed a causal association between CCNB1 and immune cell infiltrates in TNBC. Survival analysis revealed high expression of the CCNB1 gene leads to poorer prognosis in TNBC patients. Additionally, analysis using inverse variance weighting revealed that CCNB1 was linked to a 2.8% higher risk of TNBC (OR: 1.028, 95% CI 1.002-1.055, p = 0.032).

CONCLUSION

We established a co-expression network using the WGCNA methodology to detect pivotal genes associated with TNBC. This finding holds promise for advancing the creation of pre-symptomatic diagnostic tools and deepening our comprehension of the pathogenic mechanisms involved in TNBC risk genes.

Clinical efficacy of tumor organoid-guided cancer therapy for locally advanced unresectable or metastatic breast cancer

Patient-derived organoids (PDOs) may facilitate treatment selection. This retrospective cohort study evaluated the feasibility and clinical benefit of using PDOs to guide personalized treatment in metastatic breast cancer (MBC). Patients diagnosed with MBC were recruited between January 2019 and August 2022. PDOs were established and the efficacy of customized drug panels was determined by measuring cell mortality after drug exposure. Patients receiving organoid-guided treatment (OGT) were matched 1:2 by nearest neighbor propensity scores with patients receiving treatment of physician's choice (TPC). The primary outcome was progression-free survival. Secondary outcomes included objective response rate and disease control rate. Targeted gene sequencing and pathway enrichment analysis were performed. Forty-six PDOs (46 of 51, 90.2%) were generated from 45 MBC patients. PDO drug screening showed an accuracy of 78.4% (95% CI 64.9%-91.9%) in predicting clinical responses. Thirty-six OGT patients were matched to 69 TPC patients. OGT was associated with prolonged median progression-free survival (11.0 months vs. 5.0 months; hazard ratio 0.53 [95% CI 0.33-0.85]; p = .01) and improved disease control (88.9% vs. 63.8%; odd ratio 4.26 [1.44-18.62]) compared with TPC. The objective response rate of both groups was similar. Pathway enrichment analysis in hormone receptor-positive, human epidermal growth factor receptor 2-negative patients demonstrated differentially modulated pathways implicated in DNA repair and transcriptional regulation in those with reduced response to capecitabine/gemcitabine, and pathways associated with cell cycle regulation in those with reduced response to palbociclib. Our study shows that PDO-based functional precision medicine is a feasible and effective strategy for MBC treatment optimization and customization.

Diagnostic potential of NRG1 in benign nerve sheath tumors and its influence on the PI3K-Akt signaling and tumor immunity

OBJECTIVE

Benign nerve sheath tumors (BNSTs) present diagnostic challenges due to their heterogeneous nature. This study aimed to determine the significance of NRG1 as a novel diagnostic biomarker in BNST, emphasizing its involvement in the PI3K-Akt pathway and tumor immune regulation.

METHODS

Differential genes related to BNST were identified from the GEO database. Gene co-expression networks, protein-protein interaction networks, and LASSO regression were utilized to pinpoint key genes. The CIBERSORT algorithm assessed immune cell infiltration differences, and functional enrichment analyses explored BNST signaling pathways. Clinical samples helped establish PDX models, and in vitro cell lines to validate NRG1's role via the PI3K-Akt pathway.

RESULTS

Nine hundred eighty-two genes were upregulated, and 375 downregulated in BNST samples. WGCNA revealed the brown module with the most significant difference. Top hub genes included NRG1, which was also determined as a pivotal gene in disease characterization. Immune infiltration showed significant variances in neutrophils and M2 macrophages, with NRG1 playing a central role. Functional analyses confirmed NRG1's involvement in key pathways. Validation experiments using PDX models and cell lines further solidified NRG1's role in BNST.

CONCLUSION

NRG1 emerges as a potential diagnostic biomarker for BNST, influencing the PI3K-Akt pathway, and shaping the tumor immune microenvironment.

An Update on the Application of CRISPR Technology in Clinical Practice

The CRISPR/Cas system, an innovative gene-editing tool, is emerging as a promising technique for genome modifications. This straightforward technique was created based on the prokaryotic adaptive immune defense mechanism and employed in the studies on human diseases that proved enormous therapeutic potential. A genetically unique patient mutation in the process of gene therapy can be corrected by the CRISPR method to treat diseases that traditional methods were unable to cure. However, introduction of CRISPR/Cas9 into the clinic will be challenging because we still need to improve the technology's effectiveness, precision, and applications. In this review, we first describe the function and applications of the CRISPR-Cas9 system. We next delineate how this technology could be utilized for gene therapy of various human disorders, including cancer and infectious diseases and highlight the promising examples in the field. Finally, we document current challenges and the potential solutions to overcome these obstacles for the effective use of CRISPR-Cas9 in clinical practice.

Evaluation of blood supply and metabolism in tumor, axillary lymph node and normal breast tissue with F-18 FDG PET/CT in breast cancer: comparison with pathological prognostic factors

BACKGROUND AND PURPOSE

Perfusion parameters obtained in F-18 FDG PET/CT performed for staging purposes in breast cancers may provide additional information about tumor biology as well as glucose metabolism. The aim of this study was to evaluate throughout F-18 FDG PET/CT the relationship between blood flow and glucose metabolism and histological parameters of the primary tumor, normal mammary gland, and axillary lymph nodes in breast cancer patients.

MATERIALS AND METHODS

Sixty six female patients (mean age 51 y ± 12,81) were prospectively included to this study. We performed dynamic blood flow (f) study that started with 296-444 MBq (8-12 mCi) F-18 FDG injection and lasted for 10 minutes, and glucose metabolism (m) imaging one hour later. On each frame, mean activity concentration (AC) values (Bq/mL) were recorded on a spherical volume of interest (VOI) having a volume of ~ 1 cm3 on the hottest voxel of primary tumor (T), across normal breast gland (NG) and ipsilaterally axillary lymph nodes (iLN). Correlations among PET parameters and estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (c-erbB2) and Ki67 index were analyzed.

RESULTS

T volume (TV) ranged from 1.1 to 85.28 cm3 [median (IR): 6.44 (11.78)]. There were positive correlations between c-erbB2 and TACf and between c-erbB2 and iLNACf (p = 0.045, r = + 0.248; p = 0.050, r = + 0.242). In the ER positive (ERP) patients, TV and TACm were significantly lower than those of ER negative (ERN) (respectively p = 0.044 and p = 0.041). In patients with two positive Ki-67 indices, iLN-SUVmax was significantly higher than one-positive patients (p = 0.020). There was a negative correlation between NGACm and histological grade of tumor (p = 0.005, r = - 0.365).

CONCLUSIONS

Breast cancer shows differences in progression, metastasis and survival due to its diversity in terms of molecular, biological and angiogenesis. High glucose metabolism in breast cancers is associated with tumor aggressiveness. Being able to examine tumor tissue characteristics such as blood flow and glucose metabolism with a single diagnostic technique and to reveal its relationship with histological parameters can provide a reliable pretherapeutic evaluation in breast cancers.

Molecular Characterization and Establishment of a Prognostic Model Based on Primary Immunodeficiency Features in Association with RNA Modifications in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms in TNBC. The gene expression data of breast cancer patients were obtained from the TCGA and METABRIC databases. Gene set variation analysis (GSVA) revealed specific upregulation or abnormal expression of immunodeficiency pathways in TNBC patients. Multi-omics data showed significant differential expression of Primary Immunodeficiency Genes (PIDGs) in TNBC patients, who are prone to genomic-level variations. Consensus clustering was used in two datasets to classify patients into two distinct molecular subtypes based on PIDGs expression patterns, with each displaying different biological features and immune landscapes. To further explore the prognostic characteristics of PIDGs-regulated molecules, we constructed a four-gene prognostic PIDG score model and a nomogram using least absolute shrinkage and selection operator (LASSO) regression analysis in combination with clinicopathological parameters. The PIDG score was closely associated with the immune therapy and drug sensitivity of TNBC patients, providing potential guidance for clinical treatment. Particularly noteworthy is the close association of this scoring with RNA modifications; patients with different scores also exhibited different mutation landscapes. This study offers new insights for the clinical treatment of TNBC and for identifying novel prognostic markers and therapeutic targets in TNBC.

Components of the tumor immune microenvironment based on m-IHC correlate with prognosis and subtype of triple-negative breast cancer

BACKGROUND AND AIM

The spatial distribution and interactions of cells in the tumor immune microenvironment (TIME) might be related to the different responses of triple-negative breast cancer (TNBC) to immunomodulators. The potential of multiplex IHC (m-IHC) in evaluating the TIME has been reported, but the efficacy is insufficient. We aimed to research whether m-IHC results could be used to reflect the TIME, and thus to predict prognosis and complement the TNBC subtyping system.

METHODS

The clinical, imaging, and prognosis data for 86 TNBC patients were retrospectively reviewed. CD3, CD4, CD8, Foxp3, PD-L1, and Pan-CK markers were stained by m-IHC. Particular cell spatial distributions and interactions in the TIME were evaluated with the HALO multispectral analysis platform. Then, we calculated the prognostic value of components of the TIME and their correlations with TNBC transcriptomic subtypes and MRI radiomic features reflecting TNBC subtypes.

RESULTS

The components of the TIME score were established by m-IHC and demonstrated positive prognostic value for TNBC (p = 0.0047, 0.039, <0.0001 for DMFS, RFS, and OS). The score was calculated from several indicators, including Treg% in the tumor core (TC) or stromal area (SA), PD-L1+ cell% in the SA, CD3 + cell% in the TC, and PD-L1+ /CD8+ cells in the invasive margin and SA. According to the TNBC subtyping system, a few TIME indicators were significantly different in different subtypes and significantly correlated with MRI radiomic features reflecting TNBC subtypes.

CONCLUSION

We demonstrated that the m-IHC-based quantitative score and indicators related to the spatial distribution and interactions of cells in the TIME can aid in the accurate diagnosis of TNBC in terms of prognosis and classification.

A review of biological targets and therapeutic approaches in the management of triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a heterogeneous, aggressive phenotype of breast cancer with associated chemoresistance. The development of chemo- or radioresistance could be attributed to diverse tumor microenvironments, overexpression of membrane proteins (transporters), epigenetic changes, and alteration of the cell signaling pathways/genes associated with the development of cancer stem cells (CSCs).

AIM OF REVIEW

Due to the diverse and heterogeneous nature of TNBC, therapeutic response to the existing modalities offers limited scope and thus results in reccurance after therapy. To establish landmark therapeutic efficacy, a number of novel therapeutic modalities have been proposed. In addition, reversal of the resistance that developed during treatment may be altered by employing appropriate therapeutic modalities. This review aims to discuss the plethora of investigations carried out, which will help readers understand and make an appropriate choice of therapy directed toward complete elimination of TNBC.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This manuscript addresses the major contributory factors from the tumor microenvironment that are responsible for the development of chemoresistance and poor prognosis. The associated cellular events and molecular mechanism-based therapeutic interventions have been explained in detail. Inhibition of ABC transporters, cell signaling pathways associated with CSCs, and epigenetic modification offers promising results in this regard. TNBC progression, invasion, metastasis and recurrence can also be inhibited by blocking multiple cell signaling pathways, targeting specific receptors/epigenetic targets, disrupting bioenergetics and generating reactive oxygen species (ROS).

Advances in Doxorubicin-based nano-drug delivery system in triple negative breast cancer

Triple positive breast cancer (TPBC) is one of the most aggressive breast cancer. Due to the unique cell phenotype, aggressiveness, metastatic potential and lack of receptors or targets, chemotherapy is the choice of treatment for TNBC. Doxorubicin (DOX), one of the representative agents of anthracycline chemotherapy, has better efficacy in patients with metastatic TNBC (mTNBC). DOX in anthracycline-based chemotherapy regimens have higher response rates. Nano-drug delivery systems possess unique targeting and ability of co-load, deliver and release chemotherapeutic drugs, active gene fragments and immune enhancing factors to effectively inhibit or kill tumor cells. Therefore, advances in nano-drug delivery systems for DOX therapy have attracted a considerable amount of attention from researchers. In this article, we have reviewed the progress of nano-drug delivery systems (e.g., Nanoparticles, Liposomes, Micelles, Nanogels, Dendrimers, Exosomes, etc.) applied to DOX in the treatment of TNBC. We also summarize the current progress of clinical trials of DOX combined with immune checkpoint inhibitors (ICIS) for the treatment of TNBC. The merits, demerits and future development of nanomedicine delivery systems in the treatment of TNBC are also envisioned, with the aim of providing a new class of safe and efficient thoughts for the treatment of TNBC.

Implications of tumor-infiltrating lymphocytes in early-stage triple-negative breast cancer: clinical oncologist perspectives

Breast cancer (BC) is the most common neoplasm in women worldwide and one of the leading causes of female death. The triple-negative subtype, characterized by the absence of hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2), tends to occur in younger patients, be more aggressive and less differentiated. Furthermore, this subtype is considered the most immunogenic and associated with higher levels of tumor cell infiltration, mainly lymphocytes. Tumor-infiltrating lymphocytes (TILs) play a crucial role in the interaction of the host's immune system and cancer cells. The microenvironment is critical in tumor development and progression. Assessment of infiltrating lymphocytes can provide valuable information about the immune response and, given the lack of biomarkers to guide treatment decisions and predict outcomes in triple-negative tumors and can be considered as a potential biomarker. Some evidence suggests that higher levels of these lymphocytes are associated with better responses to systemic treatment, longer progression-free survival and overall survival (OS). However, treatment escalation or de-escalation strategies for triple-negative BC (TNBC) currently do not consider the presence or density of TILs for therapeutic decisions. TILs appear to be useful predictive and prognostic indicators. Further clinical studies are needed to confirm these relationships and integrate TILs as a biomarker consistently into clinical practice. This article summarizes key concepts relating to the role of the immune infiltrate in BC, along with the current status and future prospects regarding TILs as a predictive and prognostic biomarker.

A Review of the Advancements in Targeted Therapies for Breast Cancer

Breast cancer, the second-most common and lethal disease in women, poses a severe danger to global health. Breast cancer rates continue to climb despite advances in medical technology. Predictions indicate that by 2040, there will be more than three million new cases yearly. Targeted medicines have experienced a profound transformation in treating breast cancer, allowing for individualized strategies that lessen side effects and improve patient outcomes. This thorough analysis gives a rigorous investigation of current developments in breast cancer-targeted treatments. It carefully examines several subtypes, including hormone receptor-positive (HR+), HER2-positive (HER2+), and triple-negative breast cancer (TNBC), recognizing the illness' fundamental variety. It offers specialized treatment plans catered to each subtype's particular traits. The review also examines how precise genetic abnormalities like BRCA1/2 and PIK3CA mutations and molecular profiling facilitate therapy selection. Monoclonal antibodies and small molecule inhibitors are some of the targeted medicines examined in the study. It explains how each of these treatments works and supports its findings with data from clinical trials. It also considers potential new medications and addresses persistent problems, such as resistance mechanisms, chances for combining therapies, and cutting-edge patient classification techniques. This study seeks to give healthcare professionals, researchers, and patients a thorough overview of the recent advancements in breast cancer-targeted therapy by drawing on the opinions of top authorities in the area. The coordinated effort aims to create customized, efficient therapies, eventually bolstering the battle against this powerful illness.

Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity

PURPOSE

The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA).

METHODS

We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis.

RESULTS

We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment.

CONCLUSION

Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA.

A pH/GSH/Glucose Responsive Nanozyme for Tumor Cascade Amplified Starvation and Chemodynamic Theranostics

Nanozymes have brought enormous opportunities for disease theranostics. Here, a self-enhanced catalytic nanocrystal based on a bismuth-manganese core-shell nanoflower containing glucose oxide (GOx), termed BDS-GOx@MnOx, was designed for 4T1 tumor theranostics in vitro and in vivo. The BDS-GOx@MnOx nanozymes enable enhanced starvation treatment (ST) and chemotherapy (CDT) with high efficacy and exhibit sensitive tumor microenvironment (TME) responsive character for tumor therapy as well as for tumor-enhanced computer tomography (CT) and magnetic resonance (MR) diagnostic imaging. The characters and mechanism of the BDS-GOx@MnOx nanozymes have also been systematically studied and revealed.

Deregulated miRNA Expression in Triple-Negative Breast Cancer of Ancestral Genomic-Characterized Latina Patients

Among patients with triple-negative breast cancer (TNBC), several studies have suggested that deregulated microRNA (miRNA) expression may be associated with a more aggressive phenotype. Although tumor molecular signatures may be race- and/or ethnicity-specific, there is limited information on the molecular profiles in women with TNBC of Hispanic and Latin American ancestry. We simultaneously profiled TNBC biopsies for the genome-wide copy number and miRNA global expression from 28 Latina women and identified a panel of 28 miRNAs associated with copy number alterations (CNAs). Four selected miRNAs (miR-141-3p, miR-150-5p, miR-182-5p, and miR-661) were validated in a subset of tumor and adjacent non-tumor tissue samples, with miR-182-5p being the most discriminatory among tissue groups (AUC value > 0.8). MiR-141-3p up-regulation was associated with increased cancer recurrence; miR-661 down-regulation with larger tumor size; and down-regulation of miR-150-5p with larger tumor size, high p53 expression, increased cancer recurrence, presence of distant metastasis, and deceased status. This study reinforces the importance of integration analysis of CNAs and miRNAs in TNBC, allowing for the identification of interactions among molecular mechanisms. Additionally, this study emphasizes the significance of considering the patients ancestral background when examining TNBC, as it can influence the relationship between intrinsic tumor molecular characteristics and clinical manifestations of the disease.

ER Negative Breast Cancer and miRNA: There Is More to Decipher Than What the Pathologist Can See!

Breast cancer (BC), the most prevalent cancer in women, is a heterogenous disease. Despite advancements in BC diagnosis, prognosis, and therapeutics, survival rates have drastically decreased in the metastatic setting. Therefore, BC still remains a medical challenge. The evolution of high-throughput technology has highlighted gaps in the classification system of BCs. Of particular interest is the notorious triple negative BC, which was recounted as being heterogenous itself and it overlaps with distinct subtypes, namely molecular apocrine (MA) and luminal androgen (LAR) BCs. These subtypes are, even today, still misdiagnosed and poorly treated. As such, researchers and clinicians have been looking for ways through which to refine BC classification in order to properly understand the initiation, development, progression, and the responses to the treatment of BCs. One tool is biomarkers and, specifically, microRNA (miRNA), which are highly reported as associated with BC carcinogenesis. In this review, the diverse roles of miRNA in estrogen receptor negative (ER-) and androgen receptor positive (AR+) BC are depicted. While highlighting their oncogenic and tumor suppressor functions in tumor progression, we will discuss their diagnostic, prognostic, and predictive biomarker potentials, as well as their drug sensitivity/resistance activity. The association of several miRNAs in the KEGG-reported pathways that are related to ER-BC carcinogenesis is presented. The identification and verification of accurate miRNA panels is a cornerstone for tackling BC classification setbacks, as is also the deciphering of the carcinogenesis regulators of ER - AR + BC.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

XMR: an explainable multimodal neural network for drug response prediction

Introduction: Existing large-scale preclinical cancer drug response databases provide us with a great opportunity to identify and predict potentially effective drugs to combat cancers. Deep learning models built on these databases have been developed and applied to tackle the cancer drug-response prediction task. Their prediction has been demonstrated to significantly outperform traditional machine learning methods. However, due to the "black box" characteristic, biologically faithful explanations are hardly derived from these deep learning models. Interpretable deep learning models that rely on visible neural networks (VNNs) have been proposed to provide biological justification for the predicted outcomes. However, their performance does not meet the expectation to be applied in clinical practice. Methods: In this paper, we develop an XMR model, an eXplainable Multimodal neural network for drug Response prediction. XMR is a new compact multimodal neural network consisting of two sub-networks: a visible neural network for learning genomic features and a graph neural network (GNN) for learning drugs' structural features. Both sub-networks are integrated into a multimodal fusion layer to model the drug response for the given gene mutations and the drug's molecular structures. Furthermore, a pruning approach is applied to provide better interpretations of the XMR model. We use five pathway hierarchies (cell cycle, DNA repair, diseases, signal transduction, and metabolism), which are obtained from the Reactome Pathway Database, as the architecture of VNN for our XMR model to predict drug responses of triple negative breast cancer. Results: We find that our model outperforms other state-of-the-art interpretable deep learning models in terms of predictive performance. In addition, our model can provide biological insights into explaining drug responses for triple-negative breast cancer. Discussion: Overall, combining both VNN and GNN in a multimodal fusion layer, XMR captures key genomic and molecular features and offers reasonable interpretability in biology, thereby better predicting drug responses in cancer patients. Our model would also benefit personalized cancer therapy in the future.

Biomarkers derived from CmP signal network in triple negative breast cancers

Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer-related death in women, accounting for approximately 30% of all new cancer cases. The prognosis of breast cancer heavily depends on the stage of diagnosis, with early detection resulting in higher survival rates. Various risk factors, including family history, alcohol consumption and hormone exposure, contribute to breast cancer development. Triple-negative breast cancer (TNBC), characterized by the absence of certain receptors, is particularly aggressive and heterogeneous. Cerebral cavernous malformations (CCMs), abnormal dilations of small blood vessels in the brain, is contributed by mutated genes like CCM1, CCM2, and CCM3 through the perturbed formation of the CCM signaling complex (CSC). The CSC-non-classic membrane progesterone receptors (mPRs)-progesterone (PRG) (CmP)/CSC-mPRs-PRG-classic nuclear progesterone receptors (nPRs) (CmPn) signaling network, which integrates the CSC with mPRs and nPRs, plays a role in breast cancer tumorigenesis. Understanding these pathways can provide insights into potential treatments. This paper focuses on the emerging field of CmPn/CmP signal networks, which involve PRG, its receptors (nPRs and mPRs), and the CSC. These networks play a role in tumorigenesis, particularly in TNBCs. Aims to deliver a thorough examination of the CmP/CmPn pathways concerning TNBCs, this paper provides a comprehensive overview of these pathways, explores their applications and highlights their significance in the context of TNBCs.

The covert symphony: cellular and molecular accomplices in breast cancer metastasis

Breast cancer has emerged as the most commonly diagnosed cancer and primary cause of cancer-related deaths among women worldwide. Although significant progress has been made in targeting the primary tumor, the effectiveness of systemic treatments to prevent metastasis remains limited. Metastatic disease continues to be the predominant factor leading to fatality in the majority of breast cancer patients. The existence of a prolonged latency period between initial treatment and eventual recurrence in certain patients indicates that tumors can both adapt to and interact with the systemic environment of the host, facilitating and sustaining the progression of the disease. In order to identify potential therapeutic interventions for metastasis, it will be crucial to gain a comprehensive framework surrounding the mechanisms driving the growth, survival, and spread of tumor cells, as well as their interaction with supporting cells of the microenvironment. This review aims to consolidate recent discoveries concerning critical aspects of breast cancer metastasis, encompassing the intricate network of cells, molecules, and physical factors that contribute to metastasis, as well as the molecular mechanisms governing cancer dormancy.

The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity

Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.