Breast Cancer: Multiple Subtypes within a Tumor?

Basic and applied research progress of TRAIL in hematologic malignancies

Hematological malignancies encompass a diverse range of blood-related cancers characterized by abnormal blood cell production. These cancers, classified by the World Health Organization based on lineage, cell origin, and progression, provide a more comprehensive framework for understanding cancer biology. This classification has significantly advanced cancer research, particularly in genetic analyses for diagnosis and treatment. Despite recent clinical improvements, challenges, such as relapse, resistance, and high mortality, remain unresolved. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), a protein that induces apoptosis in cancer cells without affecting normal cells, has emerged as a promising therapeutic target. However, its clinical efficacy is limited by factors, such as tumor heterogeneity and resistance to TRAIL signaling. This review examines the mechanisms of TRAIL in hematological malignancies, factors contributing to resistance, and the current state of preclinical and clinical research, highlighting potential strategies to enhance TRAIL-based therapies in blood cancers.

A coagulation-related long non-coding RNA signature to predict prognosis and immune features of breast cancer

Breast cancer (BC) remains one of the most common malignancies among women worldwide, with persistently poor prognosis despite advancements in diagnostics and therapies. Long non-coding RNAs (lncRNAs) and coagulation-related genes (CRGs) are increasingly recognized for their roles in prognosis and immune modulation. Using transcriptomic data from 1,045 BC patients in TCGA, we identified CRG-associated lncRNAs via coexpression analysis (Pearson |R|> 0.4, p < 0.001) and constructed a prognostic model through univariate Cox analysis, LASSO regression with tenfold cross-validation (λ = 0.05), and multivariate Cox analysis. The model stratified patients into high- and low-risk groups with distinct overall survival (HR = 3.21, p < 0.001) and demonstrated robust predictive accuracy (AUC = 0.795 at 1 year). Functional enrichment revealed immune-related pathways (e.g., cytokine signaling, PD-L1 regulation), and high-risk patients exhibited elevated tumor mutational burden (TMB) and PD-L1 expression, suggesting enhanced immunotherapy responsiveness. Drug sensitivity analysis identified 5 targeted agents (e.g., BIBW2992) with differential efficacy between risk groups. This CRG-lncRNA signature provides a novel tool for prognosis prediction and personalized immunotherapy in BC, illuminating crosstalk between coagulation and immune pathways.

Current Status of Breast Cancer Immunotherapy and Prognosis-Related Markers

Breast cancer, being the most common type of cancer globally, stands out as the primary malignant tumor affecting females. With the advent of breast cancer immunotherapy, inhibitors targeting immune checkpoints such as anti-PD-1 (Programmed cell death protein 1) / PD-L1 (Programmed cell death-Ligand 1) and CTLA-4 (Cytotoxic T Lymphocyte-Associated Antigen-4) have demonstrated promising outcomes for breast cancer patients across all molecular subtypes, particularly those with advanced breast cancer and triple-negative breast cancer (TNBC). Our current focus lies in accurately predicting the prognosis of breast cancer patients and the effectiveness of immunotherapy. This article provides a review of emerging biomarkers for breast cancer, encompassing immune-related markers, metabolic indicators, and potential prognosis-related markers. The primary emphasis of the article is to review immune-related tumor biomarkers in breast cancer. Our goal is to summarize relevant studies capable of forecasting breast cancer prognosis and immunotherapy effectiveness. Lastly, we delve into the future directions of breast cancer immunotherapy development.

Cu/Au-doped nanopolymers with multiple catalytic activities for NIR II laser-promoted nanocatalytic tumor therapy

Breast cancer remains a significant global health concern owing to the limitations of conventional therapies, such as side effects, drug resistance, and high costs. Nanocatalytic therapy has emerged as a promising alternative due to its tumor specificity, spatiotemporal controllability, and noninvasiveness. However, its effectiveness is limited by endogenous antioxidants like glutathione (GSH) and the low catalytic activity of nanocatalysts. Herein, an Cu/Au-doped polypyrrole nanocatalyst, Cu-AuPP, with multiple catalytic activities is developed by sequentially polymerizing pyrrole monomers using CuCl2 and HAuCl4, followed by PEGylation. The obtained Cu-AuPP catalyzes the production of hydroxyl radicals (·OH) and facilitates the oxidation of GSH to GSSG via redox reactions mediated by multivalent Cu ions, leading to oxidative damage, mitochondrial dysfunction, and tumor cell apoptosis. Upon 1064 nm laser irradiation, these catalytic activities were enhanced by elevated temperature and electron-hole separation mediated by Au nanoclusters, resulting in more intense oxidative damage to tumor cells. Collectively, the developed Cu-AuPP nanocatalytic medicine capable of simultaneously catalyzing GSH depletion and ·OH production via several improved catalytic mechanisms, has significant promise for the treatment of malignant tumors.

α-chaconine increases the sensitivity of HER2+ breast cancer cells to trastuzumab by targeting acetylcholinesterase

BACKGROUND

Trastuzumab (TRZ) is the first drug used to treat HER2-positive breast cancer, but some patients become resistant to it because of the PI3K/Akt pathway and other pathways that counteract it. TRZ, in conjunction with other therapeutic agents, is needed to overcome resistance. α-chaconine (CHA), a glycoalkaloid from the Solanaceae family, can suppress lung cancer cell proliferation in vitro by inhibiting PI3K/Akt signaling, one of the key regulatory pathways in TRZ resistance.

METHODS

This study used integrative bioinformatics analysis to screen for possible targets of CHA that can help fight breast cancer that is resistant to TRZ. In vitro experiments were used to confirm the target genes using TRZ-resistant HCC-1954 (HCC-TRZ) cells for cytotoxicity, gene expression studies, and enzymatic assay.

RESULTS

We identified several potential target genes of CHA, including EGFR, VEGF, ACHE, and ADORA. We generated HCC1954-TRZ cells, which showed an increase in cell viability after sequential treatment of the parental HCC1954 cells with TRZ. Further experiments showed the high sensitivity of HCC-TRZ toward TRZ when TRZ was combined with CHA. The combination of CHA and TRZ significantly increased the mRNA expression levels of various genes compared to a single TRZ treatment. Additionally, CHA alone and combined with CHA-TRZ inhibited acetylcholinesterase (AChE) activity in HCC-TRZ cells.

CONCLUSION

CHA increased the sensitivity of HCC-TRZ cells to TRZ by targeting several potential target genes and AChE activity. This study highlights the potential of using CHA in combination with TRZ to overcome TRZ resistance in HER2+ breast cancer cells.

Molecular Subtypes and Mechanisms of Breast Cancer: Precision Medicine Approaches for Targeted Therapies

Breast cancer remains one of the most prevalent diseases worldwide, primarily affecting women. Its heterogeneous nature poses a significant challenge in the development of effective and targeted treatments. Molecular characterization has enabled breast cancer to be classified into four main subtypes: luminal A, luminal B, HER2-positive, and triple-negative breast cancer, based on hormone receptor expression and HER2 status. A deeper understanding of these molecular markers and their associated signaling pathways, such as MAPK and PI3K/AKT, is essential for improving prognosis and optimizing treatment strategies. Currently, several therapeutic agents are utilized in neoadjuvant and adjuvant therapies, often in combination with surgical interventions. However, emerging evidence highlights the growing challenge of drug resistance, which significantly limits the efficacy of existing treatments. Addressing this issue may require innovative approaches, including combination therapies and precision medicine strategies, tailored to the molecular profile of each patient. Therefore, a comprehensive understanding of the pathophysiologic mechanisms driving breast cancer progression and resistance is crucial for the development of advanced targeted therapies with greater precision and efficacy. This review aims to explore recent advancements in molecular research related to breast cancer subtypes and provide a critical analysis of current therapeutic approaches within the framework of precision medicine.

The role of C1orf50 in breast cancer progression and prognosis

Although the prognosis of breast cancer has significantly improved compared to other types of cancer, there are still some patients who expire due to recurrence or metastasis. Therefore, it is necessary to develop a method to identify patients with poor prognosis at the early stages of cancer. In the process of discovering new prognostic markers from genes of unknown function, we found that the expression of C1orf50 determines the prognosis of breast cancer patients, especially for those with Luminal A breast cancer. This study aims to elucidate the molecular role of C1orf50 in breast cancer progression. Bioinformatic analyses of the breast cancer dataset of TCGA, and in vitro analyses, reveal the molecular pathways influenced by C1orf50 expression. C1orf50 knockdown suppressed the cell cycle of breast cancer cells and weakened their ability to maintain the undifferentiated state and self-renewal capacity. Interestingly, upregulation of C1orf50 increased sensitivity to CDK4/6 inhibition. In addition, C1orf50 was found to be more abundant in breast cancer cells than in normal breast epithelium, suggesting C1orf50's involvement in breast cancer pathogenesis. Furthermore, the mRNA expression level of C1orf50 was positively correlated with the expression of PD-L1 and its related factors. These results suggest that C1orf50 promotes breast cancer progression through cell cycle upregulation, maintenance of cancer stemness, and immune evasion mechanisms. Our study uncovers the biological functions of C1orf50 in Luminal breast cancer progression, a finding not previously reported in any type of cancer.

Enhanced preoperative prediction of breast lesion pathology, prognostic biomarkers, and molecular subtypes using multiple models diffusion-weighted MR imaging

This study aims to comprehensively evaluate the clinical utility of five diffusion models, including conventional mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential (SEM), and continuous-time random-walk (CTRW), for preoperatively predicting of breast lesion pathology, prognostic biomarkers, and molecular subtypes. We retrospectively analyzed 132 patients with pathologically verified breast lesions (41 benign and 91 malignant) who underwent a full protocol preoperative breast MRI protocol, including a diffusion-weighted imaging (DWI) sequence with nine b values (0 to 2000 s/mm2) on a 3.0T MR scanner. The diffusion parameters from each model-Mono (ADC), IVIM (D, D*, f), DKI (MD, MK), SEM (DDC, α) and CTRW (Dm, α, β)-were quantitatively calculated and compared between benign and malignant breast lesions, as well as across different prognostic biomarker statuses in breast cancer, using Mann-Whitney U-tests. For molecular subtypes comparisons, we employed the Kruskal-Wallis test followed by Bonferroni. All parameters, except IVIM-D*, significantly differentiated benign from malignant lesions. Notably, IVIM-D and DKI-MK values were significantly different between estrogen receptor (ER)-positive and ER-negative tumors. Progesterone receptor (PR)-positive cancers exhibited lower Mono-ADC, IVIM-D, DKI-MD, SEM-DDC, CTRW-Dm, and CTRW-α values, alongside higher DKI-MK value compared to PR-negative cancers (p < 0.05). Significant differences in IVIM-D, IVIM-D*, and DKI-MK values were observed between human epidermal growth factor receptor 2 (HER2)-negative and HER2-positive tumors. Furthermore, higher SEM-α and CTRW-β values, along with lower DKI-MD and SEM-DDC values, were noted in the high Ki-67 expression group compared to the low Ki-67 group (p < 0.05). All five diffusion models proved valuable for breast cancer diagnosis, with the CTRW model exhibiting the highest diagnostic performance, although the difference was not statistically significant. The diffusion parameters derived from these models can effectively assist in distinguishing prognostic factors and molecular subtypes of breast cancer.

Complex Role of Circulating Triglycerides in Breast Cancer Onset and Survival: Insights From Two-Sample Mendelian Randomization Study

BACKGROUND

Reducing the incidence of breast cancer and improving its prognosis have become significant challenges for the global public health sector. We aimed to investigate the role of circulating triglycerides in the occurrence and survival of patients with breast cancer, while focusing on the possible differential effects by molecular subtypes of breast cancer.

METHODS

We used a Mendelian randomization approach to analyze publicly accessible genome-wide association study data, including triglyceride levels, breast cancer risk, and survival prognosis. We performed a two-sample causality inference analysis using the inverse-variance weighted method. We used both Mendelian randomization-Egger regression and weighted median methods for model verification. Heterogeneity was evaluated using Cochran's Q test, and sensitivity analyses were performed using the leave-one-out method, Mendelian randomization-Egger intercept test, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier test.

RESULTS

The results revealed a negative causal relationship between triglyceride levels and overall breast cancer risk (odds ratio [OR] = 0.94, confidence interval [CI] = 0.89-0.99, p = 0.011), luminal A breast cancer risk (OR = 0.93, CI = 0.87-0.99, p = 0.014), and human epidermal growth factor receptor 2 (HER2)-enriched breast cancer risk (OR = 0.84, CI = 0.73-0.96, p = 0.010). However, no statistically significant correlations were observed for the luminal B, luminal B HER2-negative, and triple-negative subtypes. Furthermore, triglyceride levels showed a positive causal relationship with the risk of survival prognosis in patients with estrogen receptor-negative breast cancer (OR = 1.33, CI = 1.00-1.76, p = 0.047). However, no statistically significant impact was observed on the survival of patients with overall breast cancer or patients with estrogen receptor-positive, HER2-positive, and HER2-negative breast cancer.

CONCLUSIONS

The potentially complex role of circulating triglycerides in the incidence and survival of patients with breast cancer provides a new perspective on the heterogeneity of the effects of triglycerides on breast cancer, thereby promoting the development of precise medical strategies. Moreover, our findings contribute to an increased understanding of overall health among patients and clinicians alike.

hERG activators exhibit antitumor effects in breast cancer through calcineurin and β-catenin-mediated signaling pathways

Background

Breast cancer remains a leading cause of mortality among women worldwide, with existing therapeutic options often accompanied by significant side effects and a persistent risk of disease recurrence. This highlights the need for novel drug candidates with new mechanisms of action by targeting alternative signaling pathways. While hERG channel is notoriously regarded as an off-target due to drug-induced cardiotoxicity, its therapeutic potential as a drug target remains largely unexplored.

Methods

This study investigated the role of hERG in breast cancer progression and its impact on patient survival. The anti-proliferative, anti-migratory, anti-invasive and pro-apoptotic effects of hERG activators were evaluated using the Cell Counting Kit-8, wound healing assay, transwell assay and cell apoptosis assay, respectively. Western blotting, Ca2+ imaging and immunofluorescence assays were employed to study their antitumor mechanisms of actions.

Results

We identified two novel hERG activators, SDUY429 and SDUY436, which effectively inhibited the proliferation and migration of MDA-MB-231 and MCF-7 cells. In addition, SDUY436 demonstrated significant anti-invasive and pro-apoptotic effects in MDA-MB-231 cells. Mechanistically, the anti-proliferative activity of hERG activators were mediated through calcineurin activation via enhanced calcium ion influx, which facilitated the nuclear translocation of nuclear factor of activated T cells (NFAT) and upregulated p21Waf/Cip expression. Furthermore, both SDUY429 and SDUY436 remarkably suppressed the migration and invasion of MDA-MB-231 cells by downregulating the protein kinase B (AKT)/glycogen synthase kinase-3 beta (GSK3β)/β-catenin signaling pathway. The observed reduction in phospho-AKT-Ser473 (pAKTS473) expression resulted in the decreased levels of phospho-GSK3β-Ser9 (pGSK3βS9), thereby limiting the nuclear localization of β-catenin, which led to the inhibition of cell migration and invasion. Notably, combining SDUY429 or SDUY436 with the AKT inhibitor MK-2206 produced synergistic anti-proliferative effects.

Conclusion

These findings suggest that hERG activators hold promise as new potential therapeutic agents for the treatment of breast cancer, paving the way for future investigations into their clinical applications.

The mechanism underlying metastasis in triple-negative breast cancer: focusing on the interplay between ferroptosis, epithelial-mesenchymal transition, and non-coding RNAs

Triple-negative breast cancer (TNBC) is a type of breast cancer with lack the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). It is the most aggressive breast cancer and the most difficult to treat due to its poor response to treatments and extremely invasive characteristics. The typical treatment for TNBC frequently results in relapse because of the lack of particular treatment choices. It is urgent to focus on identifying a workable and effective target for the treatment of TNBC. Cancer metastasis is significantly influenced by epithelial-mesenchymal transition (EMT). Ferroptosis is an iron-dependent cell death form, and changes its key factor to affect the proliferation and metastasis of TNBC. Several reports have established associations between EMT and ferroptosis in TNBC metastasis. Furthermore, non-coding RNA (ncRNA), which has been previously described, can also control cancer cell death and metastasis. Thus, in this review, we summarize the correlation and pathways among the ferroptosis, EMT, and ncRNAs in TNBC metastasis. Also, aim to find out a novel strategy for TNBC treatment through the ncRNA-ferroptosis-EMT axis.

ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer

BACKGROUND

HER2-positive breast cancer (BC) is a subtype of breast cancer. Increased ERBB3 expression has been implicated as a potential cause of resistance to other HER-targeted therapies. Our study aimed to screen and validate prognostic markers associated with ERBB3 expression by bioinformatics and affecting the prognosis of HER2 staging.

METHODS

Analyzing differences in ERBB3-related groups. ERBB3 expression-related differentially expressed genes (DEGs) were identified and intersected with survival status-related DEGs to obtain intersected genes. Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. Furthermore, we delve into the immunological traits, correlations, and expression patterns of signature genes by conducting a comprehensive analysis that encompasses immune infiltration analysis, correlation analysis, and differential expression analysis.

RESULTS

Significant variability in ERBB3 expression and prognosis in high and low ERBB3 expression groups. Twenty-five candidate DEGs were identified by intersecting ERBB3-related DEGs with survival-related DEGs. Utilizing three distinct machine learning algorithms, we identified three signature genes-PBX1, IGHM, and CXCL13-that exhibited significant diagnostic value within the diagnostic model. In addition, the risk model had better prognostic and predictive effects, and the immune infiltration analysis showed that IGHM, CXCL13 might affect the proliferation of BC cells through immune cells. Functional studies demonstrated that interference with PBX1 inhibited the proliferation, migration, and epithelial-mesenchymal transition process of HER2-positive BC cells.

CONCLUSION

PBX1, IGHM and CXCL13 are associated with the expression level of the ERBB3 and are prognostic markers for HER2-positive in BC, which may play an important role in the development and progression of BC.

Prognostic model based on tumor stemness genes for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive disease with a poor prognosis and lack of effective treatment. In this study, TNBCs were analyzed from the perspective of tumor stemness based on scRNA-seq data. The analysis showed that tumor cells of TNBC were divided into 4 subtypes, with subtype 2 having the highest stemness score. A prognostic model of 7 tumor stemness-related genes (AP2S1, CHML, FABP7, FADS2, PAXX, SDC1 and TOP2A) was developed based on marker genes of this subtype and TCGA data, and the predictive power of this feature was well validated in different clinical subgroups. TNBC patients in the low TS group had a better prognosis. In addition, drug sensitivity analysis showed that patients in the high TS (tumor stemness) score group were more sensitive to PD-L1 inhibitors and the chemotherapeutic agents. In conclusion, our study developed a prognostic model based on TNBC tumor stemness cell marker genes, which has a good ability to predict the prognosis of TNBC patients and the effect of response to drug therapy.

Identification and validation of KIF20A for predicting prognosis and treatment outcomes in patients with breast cancer

Breast cancer is a leading cause of cancer-related deaths among women globally. It is imperative to explore novel biomarkers to predict breast cancer treatment response as well as progression. Here, we collected six breast cancer samples and paired normal tissues for high-throughput sequencing. By differential expression analysis, we found 1687 DEGs and identified the top 10 hub genes, including TOP2A, CDK1, BUB1B, KIF11, CCNA2, BUB1, CCNB1, KIF20A, DLGAP5 and CDC20. Univariate and multivariate Cox analyses on the METABRIC database and GSE96058 dataset demonstrated that KIF20A was an independent prognostic predictor for overall survival. KIF20A was positively correlated with cell cycle phases, including the cell cycle process, cycle G2 M phase transition and cell cycle DNA replication initiation. Single-cell analyses revealed that KIF20A was enriched in fibroblasts and endothelial within breast cancer stroma. Meanwhile, multidrug resistance (MDR) genes ABCB1, ABCC1 and ABCG2 were co-expressed with KIF20A in fibroblasts and endothelial cells within the stroma. MTABRIC database confirmed that high expression of KIF20A was positively correlated with treatment efficacy in patients with breast cancer. In conclusion, KIF20A could be served as a predictive biomarker for breast cancer prognosis and treatment outcomes. KIF20A may play a significant role by regulating cell cycle progression and modulating stromal progression in breast cancer. Our findings provided novel molecular insights that can guide personalized treatment strategies in breast cancer.

Comparing core needle biopsy and surgical excision in breast cancer diagnosis: implications for clinical practice from a retrospective cohort study

BACKGROUND

Preoperative ultrasound-guided core needle biopsy (CNB) is currently the standard procedure for managing breast illnesses. However, the differences in outcomes between CNB and surgical excision (SE) have not been thoroughly assessed. This study aimed to explore the disparities in pathological outcomes between these two procedures, using a large sample dataset.

METHODS

This retrospective study consecutively included patients who underwent CNB and SE at Shenzhen People's Hospital from May 2016 to June 2023. Immunohistochemistry (IHC) was utilized to determine the status of estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor-2 (HER2), and Ki-67. Patients presenting with HER2 IHC 2+ underwent additional fluorescence in situ hybridization (FISH) examination. The cutoff value for high Ki-67 expression was established at 14%. Molecular subtypes were classified into four groups (Luminal A, Luminal B, Triple-negative, and HER2-positive) and five groups [Luminal A, Luminal B+ (HER2-positive), Luminal B- (HER2-negative), Triple-negative, and HER2-positive], based on different criteria.

RESULTS

A total of 4,209 patients were included in this study. Post-surgical confirmation revealed 2,410 cases as benign and 1,799 as malignant. Among the malignant cases, 334 were excluded due to either not having undergone direct surgery or having incomplete IHC results. The remaining 1,465 cases underwent IHC testing. CNB demonstrated a 97% concordance rate (CR) in diagnosing benign cases. The CRs for diagnosing invasive breast cancer (IBC) and carcinoma in situ (CIS) were 92% and 54%, respectively. ER, PgR, HER2, and Ki-67 exhibited CRs of 94%, 91%, 98%, and 84%, respectively. In the four-group classification, the overall diagnostic CR was 82%, with CRs for Luminal A, Luminal B, HER2-positive, and triple-negative breast cancer (TNBC) being 84%, 82%, 78%, and 85%, respectively. Under the five-group classification, the overall diagnostic CR was also 82%, with CRs for Luminal A, Luminal B+, Luminal B-, HER2-positive, and TNBC being 86%, 85%, 94%, 88%, and 92%, respectively.

CONCLUSIONS

This study demonstrates that CNB is highly accurate in differentiating benign from malignant breast lesions, particularly showing significant consistency in the diagnosis of molecular subtypes, providing a reliable reference for clinical diagnosis.

TBL2 Promotes Tumorigenesis via PRMT5/WDR77-Mediated AKT Activation in Breast Cancer

Breast cancer (BC) is a common malignancy that affects women worldwide. Although transducing beta-like 2 (TBL2), a member of the WD40 repeat protein family, has been implicated in various intracellular signaling pathways, its precise function in BC remains unclear. The expression of TBL2 is analyzed using real-time PCR, western blotting, and immunohistochemistry in BC patient specimens. Kaplan-Meier survival analysis is employed to assess its prognostic significance. Proteomic analysis, immunoprecipitation tests, and protein immunoblotting are employed to examine the impact of TBL2 on AKT phosphorylation activation. The findings reveal selective overexpression of TBL2 in BC, correlating significantly with various clinicopathological characteristics and poor survival outcomes in patients with BC. Through in vivo and in vitro experiments, it is observed that TBL2 suppression inhibits BC cell proliferation, while TBL2 overexpression has the opposite effect. Mechanistically, TBL2 is identified as a scaffolding protein that promotes PRMT5 and WDR77 interaction. This interaction enhances the methyltransferase activity of PRMT5, leading to increased AKT phosphorylation activation and promotion of breast cancer cell proliferation. In conclusion, this study uncovers a novel function of TBL2 in the activation of AKT by PRMT5 and suggests TBL2 as a potential therapeutic target for BC treatment.

Ubiquitin-Activating Enzyme E1 (UBA1) as a Prognostic Biomarker and Therapeutic Target in Breast Cancer: Insights into Immune Infiltration and Functional Implications

Ubiquitin-Activating Enzyme E1 (UBA1), an E1 enzyme involved in the activation of ubiquitin enzymes, has been involved in the onset and progression of different cancers in humans. Nevertheless, the precise contribution of UBA1 in breast cancer (BC) is still poorly characterized. In this study, a thorough investigation was carried out to elucidate the significance of UBA1 and validate its functionality in BC. Through the analysis of mRNA sequencing data of BC patients, the mRNA expression of UBA1 was observed to be notably enhanced in cancer tissues relative to controls, and high UBA1 expression was linked to worse overall survival (OS), disease-specific survival (DSS), and progress-free survival (PFS). Moreover, UBA1 exhibited potential as an independent prognostic and diagnostic biomarker for individuals with BC. Additionally, functional enrichment analysis revealed the involvement of UBA1 in inflammation-linked pathways, like the TNF-α signaling pathway, the IL-6 signaling pathway, and various immune-related biological processes. Notably, single-sample gene set enrichment analysis (ssGSEA) aided in the identification of a negative link between UBA1 expression and the levels of infiltrating mast cells, Th1 cells, iDC cells, B cells, DC cells, Tem cells, Cytotoxic cells, T cells, CD8T cells, and pDC cells. Finally, this study demonstrated that silencing UBA1 significantly impeded the growth and development of BC cell lines. These findings highlight UBA1 as a potential prognostic biomarker linked to immune infiltration in BC, thereby depicting its potential as a new therapeutic target for individuals with BC.

TTK promotes HER2 + breast cancer cell migration, apoptosis, and resistance to targeted therapy by modulating the Akt/mTOR axis

BACKGROUND

HER2 + breast cancer is a malignant neoplasm with a high degree of aggressiveness and therapeutic challenge. In recent years, studies have indicated a strong correlation between TTK and various tumors, though its role in HER2 + BRCA remains unclear.

OBJECTIVES

Studying the biological function of the TTK gene in HER2 + BRCA and its resistance to targeted therapy it provides new ideas for targeted drug research.

METHODS

TTK was knocked down by small interfering RNA transfection, and its biological function in HER2 + BRCA cells was verified, and its mechanism of action was verified by RT-PCR and Western blot.

RESULTS

The study demonstrated that TTK promoted cell proliferation and migration by activating the Akt/mTOR pathway in HER2 + breast cancer and enhanced the drug sensitivity of BRCA cell lines SKBR3 and BT474 to pyrotinib, in addition, knockdown of TTK induced apoptosis and arrested cells in G1 phase.

CONCLUSION

Which implies that TTK is an oncogene in HER2 + BRCA and is a valuable research target.

Recent advancements in small interfering RNA based therapeutic approach on breast cancer

Breast cancer (BC) is the most common and malignant tumor diagnosed in women, with 2.9 million cases in 2023 and the fifth highest cancer-causing mortality worldwide. Recent developments in targeted therapy options for BC have demonstrated the promising potential of small interfering RNA (siRNA)-based cancer therapeutic approaches. As BC continues to be a global burden, siRNA therapy emerges as a potential treatment strategy to regulate disease-related genes in other types of cancers, including BC. siRNAs are tiny RNA molecules that, by preventing their expression, can specifically silence genes linked to the development of cancer. In order to increase the stability and effectiveness of siRNA delivery to BC cells, minimize off-target effects, and improve treatment efficacy, advanced delivery technologies such as lipid nanoparticles and nanocarriers have been created. Additionally, combination therapies, such as siRNAs that target multiple pathways are used in conjunction with conventional chemotherapy agents, have shown synergistic effects in various preclinical studies, opening up new treatment options for breast cancer that are personalized and precision medicine-oriented. Targeting important genes linked to BC growth, metastasis, and chemo-resistance has been reported in BC research using siRNA-based therapies. This study reviews recent reports on therapeutic approaches to siRNA for advanced treatment of BC. Furthermore, this review evaluates the role and mechanisms of siRNA in BC and demonstrates the potential of exploiting siRNA as a novel target for BC therapy.

Non-metabolic enzyme function of pyruvate kinase M2 in breast cancer

Breast cancer (BC) is a prevalent malignant tumor in women, and its incidence has been steadily increasing in recent years. Compared with other types of cancer, it has the highest mortality and morbidity rates in women. So, it is crucial to investigate the underlying mechanisms of BC development and identify specific therapeutic targets. Pyruvate kinase M2 (PKM2), an important metabolic enzyme in glycolysis, has been found to be highly expressed in BC. It can also move to the nucleus and interact with various transcription factors and proteins, including hypoxia-inducible factor-1α (HIF-1α), signal transducer and activator of transcription 3 (STAT3), β-catenin, cellular-myelocytomatosis oncogene (c-Myc), nuclear factor kappa-light-chain enhancer of activated B cells (NF-κB), and mammalian sterile 20-like kinase 1 (MST1). This interaction leads to non-metabolic functions that control the cell cycle, proliferation, apoptosis, migration, invasion, angiogenesis, and tumor microenvironment in BC. This review provides an overview of the latest advancements in understanding the interactions between PKM2 and different transcription factors and proteins that influence the initiation and progression of BC. It also examined how natural drugs and noncoding RNAs affect various biological processes in BC cells through the regulation of the non-metabolic enzyme functions of PKM2. The findings provide valuable insights for improving the prognosis and developing targeted therapies for BC in the coming years.

Leveraging State-of-the-Art AI Algorithms in Personalized Oncology: From Transcriptomics to Treatment

BACKGROUND

Continuous breakthroughs in computational algorithms have positioned AI-based models as some of the most sophisticated technologies in the healthcare system. AI shows dynamic contributions in advancing various medical fields involving data interpretation and monitoring, imaging screening and diagnosis, and treatment response and survival prediction. Despite advances in clinical oncology, more effort must be employed to tailor therapeutic plans based on each patient's unique transcriptomic profile within the precision/personalized oncology frame. Furthermore, the standard analysis method is not compatible with the comprehensive deciphering of significant data streams, thus precluding the prediction of accurate treatment options.

METHODOLOGY

We proposed a novel approach that includes obtaining different tumour tissues and preparing RNA samples for comprehensive transcriptomic interpretation using specifically trained, programmed, and optimized AI-based models for extracting large data volumes, refining, and analyzing them. Next, the transcriptomic results will be scanned against an expansive drug library to predict the response of each target to the tested drugs. The obtained target-drug combination/s will be then validated using in vitro and in vivo experimental models. Finally, the best treatment combination option/s will be introduced to the patient. We also provided a comprehensive review discussing AI models' recent innovations and implementations to aid in molecular diagnosis and treatment planning.

RESULTS

The expected transcriptomic analysis generated by the AI-based algorithms will provide an inclusive genomic profile for each patient, containing statistical and bioinformatics analyses, identification of the dysregulated pathways, detection of the targeted genes, and recognition of molecular biomarkers. Subjecting these results to the prediction and pairing AI-based processes will result in statistical graphs presenting each target's likely response rate to various treatment options. Different in vitro and in vivo investigations will further validate the selection of the target drug/s pairs.

CONCLUSIONS

Leveraging AI models will provide more rigorous manipulation of large-scale datasets on specific cancer care paths. Such a strategy would shape treatment according to each patient's demand, thus fortifying the avenue of personalized/precision medicine. Undoubtedly, this will assist in improving the oncology domain and alleviate the burden of clinicians in the coming decade.

A validated UPLC-MS/MS method for quantification of pyrotinib and population pharmacokinetic study of pyrotinib in HER2-positive breast cancer patients

Objective

Pyrotinb has been approved for the treatment of HER2-positive advanced or metastatic breast cancer in China. However, the plasma concentration of pyrotinb in different patients varies greatly, and in the course of treatment, if patients have intolerable adverse reactions, the drug dosage will be reduced or even stopped. This study set out to establish an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for the determination of pyrotinb in human plasma, analyze the population pharmacokinetics (PPK) of pyrotinib and assess the influence of patient variables on PK of pyrotinib in patients with HER2 positive breast cancer.

Method

An UPLC-MS/MS method was developed to measure pyrotinib in human plasma. Utilizing a gradient elution procedure and a Kinetex C18 column (2.1 mm × 100 mm, 1.7 μm), sample separation was accomplished in 5.5 min. Pyrotinb extraction via protein precipitation was used as a sample pre-treatment technique. In total, 50 patients provided 158 plasma samples, which were identified and used in the PPK investigation. The non-linear mixed-effects modeling (NONMEM) approach was used to assess the plasma concentrations and covariates information. For the final PPK model evaluation, external evaluation, non-parametric bootstrap, visual predictive check (VPC), and goodness-of-fit (GOF) were used.

Results

The UPLC-MS/MS method for determining plasma concentration of pyrotinib in patients had good selectivity and linearity in the range of 1-1,000 ng/mL. Pyrotinib concentration profile in HER2-positive breast cancer patients was well described by a single-compartment PPK model with first-order absorption and elimination. The formulas for the final estimated values of overall parameters of CL/F and Vd/F and Ka are respectively: C L / F L / h = 88.8 × e TP / 67.2 × 0.376 , V / F L = 3940 , K A h - 1 = 0.357 F I X E D . No dosage adjustment was advised, despite the possibility that the total protein levels could have a substantial impact on the apparent distribution volume of pyrotinib with limited magnitude.

Conclusion

In this study, an UPLC-MS/MS method was established to determine the concentration of pyrotinib in human plasma. A population pharmacokinetic model of pyrotinib in HER2 positive breast cancer patients suggested that low serum total protein reduced the clearance rate of pyrotinib in patients. Clinical medical staff should pay attention to the liver function of patients with abnormal serum total protein and be alert to the occurrence of adverse drug reactions.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Enhancing RNA detection and breast cancer subtyping with a universal 3D-hybridization chain reaction system

Breast cancer, a globally prevalent malignancy, is characterized by pronounced heterogeneity. Accurate subtyping requires the simultaneous detection of different biomarkers, which is crucial for personalized treatment strategies. However, existing methodologies are hindered by limited versatility and sensing performance. To overcome these hurdles, this study presents a universal 3D-Hybridization Chain Reaction (3D-HCR) system for RNA detection and subtype-specific diagnosis of breast cancer. The system integrated a universal trigger for HCR, thereby circumventing the need for complex sequence design and enabling the analysis of various RNA targets. Leveraging the spatial-confinement effect offered by DNA nanocarriers, this system exhibited superior amplification efficiency, achieving detection limits of 3.83 pM and 4.96 pM for PD-L1 mRNA and miR-21, respectively. Importantly, the system could differentiate between triple-negative breast cancer and estrogen receptor-positive breast cancer in both living cells and clinical tissues. These findings underscore the potential of the universal 3D-HCR system as a promising tool in clinical diagnostics. With its proven proficiency in breast cancer diagnostics and versatility in RNA analysis, this system holds the promise of broadening the horizons of precision medicine.

CircCFL1 Promotes TNBC Stemness and Immunoescape via Deacetylation-Mediated c-Myc Deubiquitylation to Facilitate Mutant TP53 Transcription

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. TP53, which has a mutation rate of ≈70%-80% in TNBC patients, plays oncogenic roles when mutated. However, whether circRNAs can exert their effects on TNBC through regulating mutant TP53 has not been well evaluated. In this study, circCFL1, which is highly expressed in TNBC cells and tissues and has prognostic potential is identified. Functionally, circCFL1 promoted the proliferation, metastasis and stemness of TNBC cells. Mechanistically, circCFL1 acted as a scaffold to enhance the interaction between HDAC1 and c-Myc, further promoting the stability of c-Myc via deacetylation-mediated inhibition of K48-linked ubiquitylation. Stably expressed c-Myc further enhanced the expression of mutp53 in TNBC cells with TP53 mutations by directly binding to the promoter of TP53, which promoted the stemness of TNBC cells via activation of the p-AKT/WIP/YAP/TAZ pathway. Moreover, circCFL1 can facilitate the immune escape of TNBC cells by promoting the expression of PD-L1 and suppressing the antitumor immunity of CD8+ T cells. In conclusion, the results revealed that circCFL1 plays an oncogenic role by promoting the HDAC1/c-Myc/mutp53 axis, which can serve as a potential diagnostic biomarker and therapeutic target for TNBC patients with TP53 mutations.

Identification of TAT as a Biomarker Involved in Cell Cycle and DNA Repair in Breast Cancer

Breast cancer (BC) is the most frequently diagnosed cancer and the primary cause of cancer-related mortality in women. Treatment of triple-negative breast cancer (TNBC) remains particularly challenging due to its resistance to chemotherapy and poor prognosis. Extensive research efforts in BC screening and therapy have improved clinical outcomes for BC patients. Therefore, identifying reliable biomarkers for TNBC is of great clinical importance. Here, we found that tyrosine aminotransferase (TAT) expression was significantly reduced in BC and strongly correlated with the poor prognosis of BC patients, which distinguished BC patients from normal individuals, indicating that TAT is a valuable biomarker for early BC diagnosis. Mechanistically, we uncovered that methylation of the TAT promoter was significantly increased by DNA methyltransferase 3 (DNMT3A/3B). In addition, reduced TAT contributes to DNA replication and cell cycle activation by regulating homologous recombination repair and mismatch repair to ensure genomic stability, which may be one of the reasons for TNBC resistance to chemotherapy. Furthermore, we demonstrated that Diazinon increases TAT expression as an inhibitor of DNMT3A/3B and inhibits the growth of BC by blocking downstream pathways. Taken together, we revealed that TAT is silenced by DNMT3A/3B in BC, especially in TNBC, which promotes the proliferation of tumor cells by supporting DNA replication, activating cell cycle, and enhancing DNA damage repair. These results provide fresh insights and a theoretical foundation for the clinical diagnosis and treatment of BC.

A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients

Background

We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients.

Methods

The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram.

Results

A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system.

Conclusion

The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

Prognostic significance of the novel immunonutritional marker of cholesterol-to-lymphocyte ratio in patients with non-metastatic breast cancer

BACKGROUND

Although there is a strong correlation between the novel cholesterol-to-lymphocyte ratio (CLR) and tumor survival, its prognostic significance in breast cancer (BC) is unknown. After analyzing the relationship between CLR and the overall survival (OS) of patients with BC, we created a predictive model.

METHODS

Following retrospective enrollment, 1316 patients with BC were randomized into two cohorts: validation (n = 392) and training (n = 924). Distinct factors within the training dataset were identified for OS by univariate and multivariate Cox analyses; two-tailed P-value < 0.05 were considered to indicate statistical significance. On this premise, we developed novel signals for survival prediction and utilized the calibration curve, receiver operating characteristic curves, and concordance index (C-index) to validate their efficacy across both datasets.

RESULTS

Patients with BC were categorized into two categories with differing prognoses based on the CLR score [hazard ratio = 0.492; 95% confidence interval (CI): 0.286-0.846, P = 0.009]. A prediction nomogram was created based on multivariate analysis, which showed that N stage, postoperative pathological categorization, and CLR score were all independently correlated with OS. In the training [C-index = 0.831 (95% CI: 0.788-0.874)] and validation [C-index = 0.775 (95% CI: 0.694-0.856)] cohorts, the nomogram demonstrated favorable performance in predicting OS. In both the training and validation cohorts, it outperformed the traditional staging system [C-index = 0.702 (95% CI: 0.623-0.782)] and [C-index = 0.709 (95% CI: 0.570-0.847)]. The accurate prediction by the signature was further demonstrated by the time-dependent receiver operating characteristic curves.

CONCLUSIONS

The novel immunonutritional marker CLR could function as a simplified, cost-effective, easily accessible, non-invasive, and readily promotive prognostic indicator for patients with early-stage BC and demonstrates superior predictive power than the traditional staging system.

Heterogeneous Evolution of Breast Cancer Cells-An Endogenous Molecular-Cellular Network Study

Breast cancer heterogeneity presents a significant challenge in clinical therapy, such as over-treatment and drug resistance. These challenges are largely due to its obscure normal epithelial origins, evolutionary stability, and transitions on the cancer subtypes. This study aims to elucidate the cellular emergence and maintenance of heterogeneous breast cancer via quantitative bio-process modeling, with potential benefit to therapeutic strategies for the disease. An endogenous molecular-cellular hypothesis posits that both pathological and physiological states are phenotypes evolved from and shaped by interactions among a number of conserved modules and cellular factors within a biological network. We hereby developed a model of core endogenous network for breast cancer in accordance with the theory, quantifying its intrinsic dynamic properties with dynamic modeling. The model spontaneously generates cell states that align with molecular classifications at both the molecular and modular level, replicating four widely recognized molecular subtypes of the cancer and validating against data extracted from the TCGA database. Further analysis shows that topologically, a singular progression gateway from normal breast cells to cancerous states is identified as the Luminal A-type breast cancer. Activated positive feedback loops are found to stabilize cellular states, while negative feedback loops facilitate state transitions. Overall, more routes are revealed on the cellular transition between stable states, and a traceable count explains the origin of breast cancer heterogeneity. Ultimately, the research intended to strength the search for therapeutic targets.

Harnessing virus flexibility to selectively capture and profile rare circulating target cells for precise cancer subtyping

The effective isolation of rare target cells, such as circulating tumor cells, from whole blood is still challenging due to the lack of a capturing surface with strong target-binding affinity and non-target-cell resistance. Here we present a solution leveraging the flexibility of bacterial virus (phage) nanofibers with their sidewalls displaying target circulating tumor cell-specific aptamers and their ends tethered to magnetic beads. Such flexible phages, with low stiffness and Young's modulus, can twist and adapt to recognize the cell receptors, energetically enhancing target cell capturing and entropically discouraging non-target cells (white blood cells) adsorption. The magnetic beads with flexible phages can isolate and count target cells with significant increase in cell affinity and reduction in non-target cell absorption compared to magnetic beads having rigid phages. This differentiates breast cancer patients and healthy donors, with impressive area under the curve (0.991) at the optimal detection threshold (>4 target cells mL-1). Immunostaining of captured circulating tumor cells precisely determines breast cancer subtypes with a diagnostic accuracy of 91.07%. Our study reveals the power of viral mechanical attributes in designing surfaces with superior target binding and non-target anti-fouling.

Stability of Radiomic Features against Variations in Lesion Segmentations Computed on Apparent Diffusion Coefficient Maps of Breast Lesions

Diffusion-weighted imaging (DWI) combined with radiomics can aid in the differentiation of breast lesions. Segmentation characteristics, however, might influence radiomic features. To evaluate feature stability, we implemented a standardized pipeline featuring shifts and shape variations of the underlying segmentations. A total of 103 patients were retrospectively included in this IRB-approved study after multiparametric diagnostic breast 3T MRI with a spin-echo diffusion-weighted sequence with echoplanar readout (b-values: 50, 750 and 1500 s/mm2). Lesion segmentations underwent shifts and shape variations, with >100 radiomic features extracted from apparent diffusion coefficient (ADC) maps for each variation. These features were then compared and ranked based on their stability, measured by the Overall Concordance Correlation Coefficient (OCCC) and Dynamic Range (DR). Results showed variation in feature robustness to segmentation changes. The most stable features, excluding shape-related features, were FO (Mean, Median, RootMeanSquared), GLDM (DependenceNonUniformity), GLRLM (RunLengthNonUniformity), and GLSZM (SizeZoneNonUniformity), which all had OCCC and DR > 0.95 for both shifting and resizing the segmentation. Perimeter, MajorAxisLength, MaximumDiameter, PixelSurface, MeshSurface, and MinorAxisLength were the most stable features in the Shape category with OCCC and DR > 0.95 for resizing. Considering the variability in radiomic feature stability against segmentation variations is relevant when interpreting radiomic analysis of breast DWI data.

Systematic analysis of PANoptosis-related genes identifies XIAP as a functional oncogene in breast cancer

BACKGROUND

Breast cancer (BC) is the most prevalent malignant disease affecting women globally. PANoptosis, a novel form of cell death combining features of pyroptosis, apoptosis, and necroptosis, has recently gained attention. However, its precise function in BC and the predictive values of PANoptosis-related genes remain unclear.

METHODS

We used the expression data and clinical information of BC tissues or normal breast tissues from public databases, and then successfully developed and verified a BC PANoptosis-related risk model through a combination of univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and Kaplan-Meier (KM) analysis. A nomogram was constructed to estimate survival probability, and its accuracy was assessed using calibration curves.

RESULTS

Among 37 PANoptosis-related genes, we identified 4 differentially expressed genes related to overall survival (OS). Next, a risk model incorporating these four PANoptosis-related genes was established. Patients were stratified into low/high-risk groups based on the median risk score, with the low-risk group showing better prognoses and higher levels of immune infiltration. Utilizing the risk score and clinical features, we developed a nomogram to predict 1-, 3- and 5-year survival probability. X-linked inhibitor of apoptosis protein (XIAP) emerged as a potentially risky factor with the highest hazard ratio. In vitro experiments demonstrated that XIAP inhibition enhances the antitumor effect of doxorubicin through the PANoptosis pathway.

CONCLUSION

PANoptosis holds an important role in BC prognosis and treatment.

The G Protein Estrogen Receptor (GPER) is involved in the resistance to the CDK4/6 inhibitor palbociclib in breast cancer

BACKGROUND

The cyclin D1-cyclin dependent kinases (CDK)4/6 inhibitor palbociclib in combination with endocrine therapy shows remarkable efficacy in the management of estrogen receptor (ER)-positive and HER2-negative advanced breast cancer (BC). Nevertheless, resistance to palbociclib frequently arises, highlighting the need to identify new targets toward more comprehensive therapeutic strategies in BC patients.

METHODS

BC cell lines resistant to palbociclib were generated and used as a model system. Gene silencing techniques and overexpression experiments, real-time PCR, immunoblotting and chromatin immunoprecipitation studies as well as cell viability, colony and 3D spheroid formation assays served to evaluate the involvement of the G protein-coupled estrogen receptor (GPER) in the resistance to palbociclib in BC cells. Molecular docking simulations were also performed to investigate the potential interaction of palbociclib with GPER. Furthermore, BC cells co-cultured with cancer-associated fibroblasts (CAFs) isolated from mammary carcinoma, were used to investigate whether GPER signaling may contribute to functional cell interactions within the tumor microenvironment toward palbociclib resistance. Finally, by bioinformatics analyses and k-means clustering on clinical and expression data of large cohorts of BC patients, the clinical significance of novel mediators of palbociclib resistance was explored.

RESULTS

Dissecting the molecular events that characterize ER-positive BC cells resistant to palbociclib, the down-regulation of ERα along with the up-regulation of GPER were found. To evaluate the molecular events involved in the up-regulation of GPER, we determined that the epidermal growth factor receptor (EGFR) interacts with the promoter region of GPER and stimulates its expression toward BC cells resistance to palbociclib treatment. Adding further cues to these data, we ascertained that palbociclib does induce pro-inflammatory transcriptional events via GPER signaling in CAFs. Of note, by performing co-culture assays we demonstrated that GPER contributes to the reduced sensitivity to palbociclib also facilitating the functional interaction between BC cells and main components of the tumor microenvironment named CAFs.

CONCLUSIONS

Overall, our results provide novel insights on the molecular events through which GPER may contribute to palbociclib resistance in BC cells. Additional investigations are warranted in order to assess whether targeting the GPER-mediated interactions between BC cells and CAFs may be useful in more comprehensive therapeutic approaches of BC resistant to palbociclib.

Flexible Regularized Estimation in High-Dimensional Mixed Membership Models

Mixed membership models are an extension of finite mixture models, where each observation can partially belong to more than one mixture component. A probabilistic framework for mixed membership models of high-dimensional continuous data is proposed with a focus on scalability and interpretability. The novel probabilistic representation of mixed membership is based on convex combinations of dependent multivariate Gaussian random vectors. In this setting, scalability is ensured through approximations of a tensor covariance structure through multivariate eigen-approximations with adaptive regularization imposed through shrinkage priors. Conditional weak posterior consistency is established on an unconstrained model, allowing for a simple posterior sampling scheme while keeping many of the desired theoretical properties of our model. The model is motivated by two biomedical case studies: a case study on functional brain imaging of children with autism spectrum disorder (ASD) and a case study on gene expression data from breast cancer tissue. These applications highlight how the typical assumption made in cluster analysis, that each observation comes from one homogeneous subgroup, may often be restrictive in several applications, leading to unnatural interpretations of data features.

Clinical significance of the CXCL8/CXCR1/R2 signalling axis in patients with invasive breast cancer

The C-X-C motif chemokine ligand 8 (CXCL8)-C-X-C chemokine receptor (CXCR)1/2 signalling axis is among numerous mechanisms which stimulate the immune system to defend against tumour growth and influence the tumour microenvironment to promote tumour growth. This pathway plays an important role in the development of a number of cancers including breast cancer (BC). The aim of the present study was to analyse the levels of the chemokine CXCL8 and its receptors, CXCR1 and CXCR2, in the serum of female patients with invasive BC and to assess the expression of these parameters at the mRNA level, considering molecular subtypes and degrees of cancer malignancy. The study group consisted of 62 patients with histopathologically confirmed invasive BC. The control group consisted of 18 patients with histopathologically confirmed fibroadenoma, a benign breast tumour. The levels of CXCL8, CXCR1 and CXCR2 were determined by sandwich ELISA using the CLOUD-CLONE ELISA kit. CXCL8, CXCR1 and CXCR2 transcript levels were analysed using reverse transcription-quantitative PCR. Results showed that serum CXCL8 levels in female patients with invasive BC were significantly higher compared with those in the control group (P<0.05). In addition, significantly elevated CXCR1 levels were observed in luminal B human epidermal growth factor receptor 2+ carcinoma compared with those in the control group. Analysis of CXCL8 in the serum of female patients with BC showed a statistically significant difference between clinical stage G1 and G2 (P<0.05), G2 and G3 (P<0.01), and G1 and G3 (P<0.0001). On the other hand, the analysis of CXCR1 and CXCR2 levels in the serum of the patients revealed a statistically significant difference between G2 and G3 (P<0.05). The current study showed that abnormalities in the immune response involving the CXCL8-CXCR1/2 signalling axis in patients with invasive BC are involved in the development of these tumours. Moreover, the demonstrated severity of changes occurring at protein level may suggest the potential usefulness of their determination as potential diagnostic markers in the clinic.

Diagnostic performance of ultrasound-based artificial intelligence for predicting key molecular markers in breast cancer: A systematic review and meta-analysis

BACKGROUND

Breast cancer (BC) diagnosis and treatment rely heavily on molecular markers such as HER2, Ki67, PR, and ER. Currently, these markers are identified by invasive methods.

OBJECTIVE

This meta-analysis investigates the diagnostic accuracy of ultrasound-based radiomics as a novel approach to predicting these markers.

METHODS

A comprehensive search of PubMed, EMBASE, and Web of Science databases was conducted to identify studies evaluating ultrasound-based radiomics in BC. Inclusion criteria encompassed research on HER2, Ki67, PR, and ER as key molecular markers. Quality assessment using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) was performed. The data extraction step was performed systematically.

RESULTS

Our meta-analysis quantifies the diagnostic accuracy of ultrasound-based radiomics with a sensitivity and specificity of 0.76 and 0.78 for predicting HER2, 0.80, and 0.76 for Ki67 biomarkers. Studies did not provide sufficient data for quantitative PR and ER prediction analysis. The overall quality of studies based on the RQS tool was moderate. The QUADAS-2 evaluation showed that the studies had an unclear risk of bias regarding the flow and timing domain.

CONCLUSION

Our analysis indicated that AI models have a promising accuracy for predicting key molecular biomarkers' status in BC patients. We performed the quantitative analysis for HER2 and Ki67 biomarkers which yielded a moderate to high accuracy. However, studies did not provide adequate data for meta-analysis of ER and PR prediction accuracy of developed models. The overall quality of the studies was acceptable. In future research, studies need to report the results thoroughly. Also, we suggest more prospective studies from different centers.

High expression of CCNB2 is an independent predictive poor prognostic biomarker and correlates with immune infiltrates in breast carcinoma

Background

Cyclin B2 (CCNB2) is associated with cell cycle progression, acting as a cell cycle checkpoint in progression of G2/M transition. In many cancer patients, it has been observed that overexpression of CCNB2 enhances tumor invasiveness and leads to adverse prognosis. However, the association of CCNB2 with the tumor microenvironment remains unclear. Therefore, it is necessary to clarify the associations of CCNB2 with the immune status and prognosis of breast carcinoma (BRCA).

Methods

Gene expression and clinical data for BRCA were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, followed by association analyses of CCNB2 expression with prognosis, immune cell infiltration, and immune checkpoints. This study further performed drug sensitivity analysis and constructed a prognostic nomogram for CCNB2.

Results

3619 differentially expressed genes were identified in BRCA, including CCNB2 that emerged as a key gene in the network. High CCNB2 expression correlated with poor prognosis. Functional analysis demonstrated enrichment of CCNB2 co-expressed genes with the cell cycle, cancer progression, cell energy, and immune pathways. Microsatellite instability and tumor mutation burden analyses indicated CCNB2 as a candidate immunotherapy target. Tumor-infiltrating myeloid-derived suppressor cells, regulatory T cells, and T helper 2 cells were associated with CCNB2-related tumor progression and metastasis. CCNB2 expression positively correlated with immune checkpoints, indicating that high CCNB2 expression might facilitate tumor immune escape. Tumors with high CCNB2 expression showed sensitivity to phosphoinositide 3-kinase-protein kinase B-mammalian target of rapamycin and cyclin-dependent kinase (CDK) 4/6 inhibitors, and the nomogram had good prognostic predictive ability for patients with BRCA.

Conclusions

CCNB2 may play a crucial role in tumorigenesis and serve as an independent prognostic biomarker associated with tumor microenvironment, tumor immune infiltration and immunotherapy in BRCA.

Comparing the HER2 Status of the Primary Tumor to That of Disseminated Tumor Cells in Early Breast Cancer

Breast cancer remains a leading cause of cancer mortality in women globally. Despite advancements in systemic therapy, the risk of distant recurrence persists even after such treatment and may be linked to disseminated tumor cells (DTCs). Variability in molecular characteristics between primary tumors (PTs) and distant metastases underscores the need to comprehensively understand metastatic pathways. This retrospective study investigated discrepancies between HER2 expression in PTs and DTCs and their implications for survival outcomes in 201 early breast cancer (EBC) patients. We found a significant association between HER2 expression in PTs and DTCs when classifying tumors as HER2-high/low/negative. Patients whose HER2 status was discordant between PTs and DTCs exhibited worse distant disease-free survival than those with concordant status. Multivariate analysis confirmed the HER2 status of DTCs as an independent prognostic factor for distant DFS. These findings emphasize the importance of assessing HER2 expression in DTCs and its potential implications for tailored therapy strategies in EBC. Furthermore, prospective trials are needed to validate these findings and explore targeted therapies based on the molecular characteristics of DTCs.

Cancer-associated fibroblast-derived gene signature discriminates distinct prognoses by integrated single-cell and bulk RNA-seq analyses in breast cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are one of the most predominant cellular subpopulations in the tumor stroma and play an integral role in cancer occurrence and progression. However, the prognostic role of CAFs in breast cancer remains poorly understood.

METHODS

We identified a number of CAF-related biomarkers in breast cancer by combining single-cell and bulk RNA-seq analyses. Based on univariate Cox regression as well as Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a novel CAF-associated prognostic model was developed. Breast cancer patients were grouped according to the median risk score and further analyzed for outcome, clinical characteristic, pathway activity, genomic feature, immune landscape, and drug sensitivity.

RESULTS

A total of 341 CAF-related biomarkers were identified from single-cell and bulk RNA-seq analyses. We eventually screened eight candidate prognostic genes, including CERCAM, EMP1, SDC1, PRKG1, XG, TNN, WLS, and PDLIM4, and constructed the novel CAF-related prognostic model. Grouped by the median risk score, high-risk patients showed a significantly worse prognosis and exhibited distinct pathway activities such as uncontrolled cell cycle progression, angiogenesis, and activation of glycolysis. In addition, the combined risk score and tumor mutation burden significantly improved the ability to predict patient prognosis. Importantly, patients in the high-risk group had a higher infiltration of M2 macrophages and a lower infiltration of CD8+ T cells and activated NK cells. Finally, we calculated the IC50 for a range of anticancer drugs and personalized the treatment regimen for each patient.

CONCLUSION

Integrating single-cell and bulk RNA-seq analyses, we identified a list of compositive CAF-associated biomarkers and developed a novel CAF-related prognostic model for breast cancer. This robust CAF-derived gene signature acts as an excellent predictor of patient outcomes and treatment responses in breast cancer.

Analysis on status quo and related factors of delays in diagnosis and treatment of breast cancer in Ningxia Hui Autonomous Region

This study aimed to explore factors contributing to the delays in the diagnosis and treatment of breast cancer (BC) in Ningxia Hui Autonomous Region. We conducted a cohort analysis of 1012 patients with BC diagnosed at the General Hospital of Ningxia Medical University between January 2018 and December 2019. Sociodemographic data were collected through questionnaires, and clinical data were gathered and analyzed from relevant databases. Furthermore, observations were made regarding delays in the diagnosis and treatment of BC, followed by an analysis of the correlations between patient delay and both sociological factors within the population and clinical factors specific to patients with BC. Subsequently, the factors associated with patient delay and system delay were examined using Cox regression analysis, along with the inclusion of neoadjuvant therapy. In the prevention and treatment of BC in Ningxia, the patient delay rate was 33.20%, the diagnosis delay rate was 17.89%, the treatment delay rate was 0.0099% and the system delay rate was 41.60%. There was a higher proportion of patient delay and system delay in aged patients (age ≥ 61 years) with rural registered permanent residence (RPR), multiple clinical symptoms (such as nipple spillage, axillary abnormalities, etc), a T4 tumor size classification, and the initial use of neoadjuvant therapy. Besides, significant positive correlations were observed between patient delay and system delay time with BC stage. Patients aged 51 to 60 and those with molecular types (Limanal1B: ki-67 > 14%, Limanal1B: HER-2 positive) were prone to patient delay, whereas molecular characteristics influenced system delay, unrelated to sociodemographic factors. The study identifies significant age, residency, and tumor molecular subtype correlations with diagnostic and treatment delays in Ningxia's patients with BC, predominantly affecting women aged 41 to 60, especially urban dwellers. These findings underscore the need for targeted interventions to reduce delays and improve BC care in this region.

Extrachromosomal circular DNA (eccDNA): from carcinogenesis to drug resistance

Extrachromosomal circular DNA (eccDNA) is a circular form of DNA that exists outside of the chromosome. Although it has only been a few decades since its discovery, in recent years, it has been found to have a close relationship with cancer, which has attracted widespread attention from researchers. Thus far, under the persistent research of researchers from all over the world, eccDNA has been found to play an important role in a variety of tumors, including breast cancer, lung cancer, ovarian cancer, etc. Herein, we review the sources of eccDNA, classifications, and the mechanisms responsible for their biogenesis. In addition, we introduce the relationship between eccDNA and various cancers and the role of eccDNA in the generation and evolution of cancer. Finally, we summarize the research significance and importance of eccDNA in cancer, and highlight new prospects for the application of eccDNA in the future detection and treatment of cancer.

SF3A2 promotes progression and cisplatin resistance in triple-negative breast cancer via alternative splicing of MKRN1

Triple-negative breast cancer (TNBC) is the deadliest subtype of breast cancer owing to the lack of effective therapeutic targets. Splicing factor 3a subunit 2 (SF3A2), a poorly defined splicing factor, was notably elevated in TNBC tissues and promoted TNBC progression, as confirmed by cell proliferation, colony formation, transwell migration, and invasion assays. Mechanistic investigations revealed that E3 ubiquitin-protein ligase UBR5 promoted the ubiquitination-dependent degradation of SF3A2, which in turn regulated UBR5, thus forming a feedback loop to balance these two oncoproteins. Moreover, SF3A2 accelerated TNBC progression by, at least in part, specifically regulating the alternative splicing of makorin ring finger protein 1 (MKRN1) and promoting the expression of the dominant and oncogenic isoform, MKRN1-T1. Furthermore, SF3A2 participated in the regulation of both extrinsic and intrinsic apoptosis, leading to cisplatin resistance in TNBC cells. Collectively, these findings reveal a previously unknown role of SF3A2 in TNBC progression and cisplatin resistance, highlighting SF3A2 as a potential therapeutic target for patients with TNBC.

Analysis of differentially expressed proteins in lymph fluids related to lymphatic metastasis in a breast cancer rabbit model guided by contrast‑enhanced ultrasound

The aim of the present study was to identify differentially expressed proteins in the lymph fluid of rabbits with breast cancer lymphatic metastasis compared with healthy rabbits and to analyze and verify these proteins using proteomics technologies. In the process of breast cancer metastasis, the composition of the lymph fluid will also change. Rabbits with breast cancer lymph node metastasis and normal rabbits were selected for analysis. Lymph fluid was extracted under the guidance of percutaneous contrast-enhanced ultrasound. Label-free quantitative proteomics was used to detect and compare differences between the rabbit cancer model and healthy rabbits and differential protein expression results were obtained. Bioinformatics analysis was performed using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis software, selecting the most significantly differentially expressed proteins. Finally, parallel reaction monitoring technology was applied for validation. A total of 547 significantly differentially expressed proteins were found in the present study, which included 371 upregulated proteins and 176 downregulated proteins. The aforementioned genes were mainly involved in various cellular and metabolic pathways, including upregulated proteins, such as biliverdin reductase A and isocitrate dehydrogenase 2 and downregulated proteins, such as pyridoxal kinase. The upregulated proteins protein disulfide-isomerase 3, protein kinase cAMP-dependent type I regulatory subunit α and ATP-binding cassette sub-family C member 4 participated in immune regulation, endocrine regulation and anti-tumor drug resistance regulation, respectively. Compared with healthy rabbits, rabbits with breast cancer metastasis differentially expressed of a number of different proteins in their lymph, which participate in the pathophysiological process of tumor occurrence and metastasis. Through further research, these differential proteins can be used as predictive indicators of breast cancer metastasis and new therapeutic targets.

The Utility of the Cachexia Index and the Modified Glasgow Score in Young Patients With Breast Cancer

Background Breast cancer is the most common cancer in women. Body composition and inflammatory markers are increasingly important for predicting cancer prognosis. The Cancer Cachexia Index (CXI) and the modified Glasgow Prognostic Score (GPS) are two new markers evaluating prognosis in cancer. In this study, we evaluated the utility of the CXI and the modified GPS in young patients with breast cancer. Methods Eighty patients diagnosed between 2012 and 2023 were included in the study. The following information was recorded: patient features, pathological subtype, estrogen receptor and human epidermal growth factor receptor-2 (HER-2) status, disease stage, therapies, disease recurrence, and last control or death date. The CXI and the modified GPS were calculated using clinical data, including skeletal muscle index, albumin, C-reactive protein, and neutrophil-to-lymphocyte ratio. Results There were no differences in overall survival with respect to the CXI in the study population (p=0.96). Only stage 4 patients showed statistically significant survival differences according to the CXI (p=0.046). Although the median survival time was not reached for the modified GPS groups, there was a statistical overall survival difference favoring the negative group (p=0.017). No significant differences were observed in disease-free survival due to the CXI (p=0.128). In multivariate analysis, no factors, including the modified GPS and the CXI, influenced overall survival. There was a significant effect of the modified GPS and body mass index on recurrence (p=0.037; p=0.034). The CXI had a non-significant marginal p-value (p=0.074). Conclusion Our study showed that the modified GPS may be related to disease-free survival and overall survival, whereas the CXI has a more prominent prognostic effect on overall survival in advanced-stage breast cancers. In early-stage and young patients, optimization of risk scores is lacking.

Role of ferroptosis and ferroptosis-related long non'coding RNA in breast cancer

Ferroptosis, a therapeutic strategy for tumours, is a regulated cell death characterised by the increased accumulation of iron-dependent lipid peroxides (LPO). Tumour-associated long non-coding RNAs (lncRNAs), when combined with traditional anti-cancer medicines or radiotherapy, can improve efficacy and decrease mortality in cancer. Investigating the role of ferroptosis-related lncRNAs may help strategise new therapeutic options for breast cancer (BC). Herein, we briefly discuss the genes and pathways of ferroptosis involved in iron and reactive oxygen species (ROS) metabolism, including the XC-/GSH/GPX4 system, ACSL4/LPCAT3/15-LOX and FSP1/CoQ10/NAD(P)H pathways, and investigate the correlation between ferroptosis and LncRNA in BC to determine possible biomarkers related to ferroptosis.

PIK3CA mutation-driven immune signature as a prognostic marker for evaluating the tumor immune microenvironment and therapeutic response in breast cancer

PURPOSE

Gene mutations drive tumor immune microenvironment (TIME) heterogeneity, in turn affecting prognosis and immunotherapy efficacy. PIK3CA is the most frequently mutated gene in breast cancer (BC), yet its relevance to BC prognosis remains controversial. Herein, we sought to determine the impact of PIK3CA mutation-driven immune genes (PDIGs) on BC prognosis in relation to TIME heterogeneity.

METHODS

PIK3CA mutation characteristics were compared and verified between the TCGA-BRCA dataset and a patient cohort from our hospital. PIK3CA mutation-driven differentially expressed genes were identified for consensus clustering and weighted gene co-expression network analysis to select the modules most relevant to the immune subtype. Thereafter, the two were intersected to obtain PDIGs. Univariate Cox, LASSO, and multivariate Cox regression analyses were sequentially performed on PDIGs to obtain a PIK3CA mutation-driven immune signature (PDIS), which was then validated using the Gene Expression Omnibus (GEO) database. Differences in functional enrichment, mutation landscape, immune infiltration, checkpoint gene expression, and drug response were compared between different risk groups.

RESULTS

PIK3CA mutation frequencies in the TCGA and validation cohorts were 34.49% and 40.83%, respectively. PIK3CA mutants were significantly associated with ER, PR, and molecular BC subtypes in our hospital cohort. The PDIS allowed for effective risk stratification and exhibited prognostic power in TCGA and GEO sets. The low-risk patients exhibited greater immune infiltration, higher expression of common immune checkpoint factors, and lower scores for tumor immune dysfunction and exclusion.

CONCLUSION

The PDIS can be used as an effective prognostic model for predicting immunotherapy response to guide clinical decision-making.

Cerebrospinal Fluid Testing in Leptomeningeal Progression of HER2-Negative Breast Cancer Reveals HER2 Positivity, Leading to HER2-Targeted Therapy: A Case Report

The treatment of breast cancer is largely determined by protein expression assays of estrogen receptor, progesterone receptor, and Her2/neu (HER2) status. These prognostic markers may vary due to tumor heterogeneityor the evolution of prognostic markers throughout the course of treatment. This report presents a case of a patient who initially presented with HER2-negative breast cancer and had rapidly progressed on numerous lines of treatment. An analysis of cerebrospinal fluid via next-generation sequencing and biopsy of metastasis to the liver identified HER2-positive cancer, which allowed for the use of trastuzumab deruxtecan, a HER2-targeted therapy. This led to an excellent clinical response with improvement in performance status and quality of life. This case report demonstrates the importance of continuing to follow a patient's cancer pathology to open the doors for other opportunities for treatment. Cancer has the potential to evolve and there is a benefit of obtaining rebiopsies to ensure the correct targeted therapies are provided to the patient.

Precision targeting of CuET overload to disrupt mitochondrial unfolded protein response by integrated liposome

Mitochondria in breast cancer play a critical role in survival and adaptation to dynamic environments. Thus, targeting mitochondria emerges as a promising therapeutic strategy for breast cancer. However, the adaptive unfolded protein response in mitochondria (UPRmt) due to mitochondrial unspecific distribution might contribute to diminished therapeutic outcomes. Herein, mitochondrial targeting liposome agents (CTPP-Lipid) are constructed and adopted for delivering the copper ion (CuET-DSF), which is especially sensitive for mitochondria-abundant breast tumors. In brief, the CTPP-Lipid@CuET achieves the goal of Cu2+ overloading by mitochondria targeting delivery. This rapidly increases ROS production, disrupts mitochondrial structure, and avoids the adaptive UPRmt formation, finally leading to apoptosis of breast cancer cells. In general, the Cu2+ overloading at mitochondria by CTPP-Lipid@CuET is a potential strategy for antitumor therapy, providing new insights into breast tumor therapy.

Phytocompounds-based therapeutic approach: Investigating curcumin and green tea extracts on MCF-7 breast cancer cell line

BACKGROUND

Breast cancer (BC) has transcended lung cancer as the most common cancer in the world. Due to the disease's aggressiveness, rapid growth, and heterogeneity, it is crucial to investigate different therapeutic approaches for treatment. According to the World Health Organization (WHO), Plant-based therapeutics continue to be utilized as safe/non-toxic complementary or alternative treatments for cancer, even in developed countries, regardless of how cutting-edge conventional therapies are. Despite their low bioavailability, curcumin (CUR) and green tea (GT) represent safer therapeutic options. Due to their potent molecular-modulating properties on various cancer-related molecules and signaling pathways, they are considered gold-standard therapeutic agents and have been incorporated into the development of one or more therapeutic strategies of BC treatment.

METHODS

We investigated the modulatory role of CUR and GT extracts on significant multi molecular targets in MCF-7 BC cell line to assess their potential as BC multi-targeting agents. We analyzed the phytocompounds in GT leaves using High-performance liquid chromatography (HPLC) and Gas chromatography-mass spectrometry (GC-MS) techniques. The mRNA expression levels of Raf-1, Telomerase, Tumor necrosis factor alpha (TNF-α) and Interleukin-8 (IL-8) genes in MCF-7 cells were quantified using quantitative real-time PCR (qRT-PCR). The cytotoxicity of the extracts was assessed by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the released Lactate dehydrogenase (LDH), a valuable marker for identifying the programmed necrosis (necroptosis). Additionally, the concentrations of the necroptosis-related proinflammatory cytokines (TNF-α and IL-8) were measured using enzyme-linked immunosorbent assay (ELISA).

RESULTS

In contrast to the GT, the results showed the anticancer and cytotoxic properties of CUR against MCF-7 cells, with a relatively higher level of released LDH. The CUR extract downregulated the oncogenic Raf-1, suppressed the Telomerase and upregulated the TNF-α and IL-8 genes. Results from the ELISA showed a notable increase in IL-8 and TNF-α cytokines levels after CUR treatment, which culminated after 72 h.

CONCLUSIONS

Among both extracts, only CUR effectively modulated the understudy molecular targets, achieving multi-targeting anticancer activity against MCF-7 cells. Moreover, the applied dosage significantly increased levels of the proinflammatory cytokines, which represent a component of the cytokines-targeting-based therapeutic strategy. However, further investigations are recommended to validate this therapeutic approach.