Breast cancer metastasis: markers and models

Tumor and α-SMA-expressing stromal cells in pancreatic neuroendocrine tumors have a distinct RNA profile depending on tumor grade

Alpha-smooth muscle actin (α-SMA) expression in the stroma is linked to the presence of cancer-associated fibroblasts and is known to correlate with worse outcomes in various tumors. In this study, using a GeoMx digital spatial profiling approach, we characterized the gene expression of the tumor and α-SMA-expressing stromal cell compartments in pancreatic neuroendocrine tumors (PanNETs). The profiling was performed on tissues from eight retrospective cases (three grade 1, four grade 2, and one grade 3). Selected regions of interest were segmented geometrically based on tissue morphology and fluorescent signals from synaptophysin and α-SMA markers. The α-SMA-expressing stromal-cell-associated genes were involved in pathways of extracellular matrix modification, whereas, in tumor cells, the gene expression profiles were associated with pathways involved in cell proliferation. The comparison of gene expression profiles across all three PanNET grades revealed that the differences between grades are not only present at the level of the tumor but also in the α-SMA-expressing stromal cells. Furthermore, the tumor cells from regions with a rich presence of adjacent α-SMA-expressing stromal cells revealed an upregulation of matrix metalloproteinase-9 (MMP9) expression in grade 3 tumors. This study provides an in-depth characterization of gene expression profiles in α-SMA-expressing stromal and tumor cells, and outlines potential crosstalk mechanisms.

MLLT6/ATF2 Axis Restrains Breast Cancer Progression by Driving DDIT3/4 Expression

Epigenetic deregulation is strongly associated with tumor progression. The identification of natural tumor suppressors to overcome cancer metastasis is urgent for cancer therapy. We investigate whether myeloid/lymphoid or mixed-lineage leukemia translocated (MLLT) family members contribute to breast cancer progression and found that high MLLT6 expression predicted a better prognosis and that gradually decreased MLLT6 expression was accompanied by breast cancer malignancy. MLLT6 was downregulated by hypoxia-induced enrichment of DNMT1 at the MLLT6 promoter. The results of in vitro functional experiments indicated that MLLT6 depletion promoted colony formation and cell migration, probably by hampering apoptosis. RNA profiling revealed that the apoptotic pathway was downregulated following stable knockdown of MLLT6. DNA damage-inducible transcript 3/4 (DDIT3/4) were among the top 10 downregulated genes and may have expression patterns similar to that of MLLT6. Restoring DDIT3/4 expression in cells with MLLT6 depletion blocked colony formation and cell migration and attenuated the successful colonization of breast cancer cells in vivo. We also determined that the transcription factor activating transcription factor 2 is a binding partner of MLLT6 and participates in the MLLT6/ATF2 axis, which was reinforced by inhibition of AKT signaling, in turn inducing DDIT3/4 expression by establishing an active chromatin structure at the DDIT3/4 gene promoters. As MLLT6 promotes breast cancer cell apoptosis by inducing DDIT3/4 expression during metastasis, it could be a novel tumor suppressor. Implications: Control of MLLT6 expression via inhibition of PI3K/AKT kinase activity is a potential therapeutic approach for the management of metastatic breast cancer.

Identification potential biomarkers for diagnosis, and progress of breast cancer by using high-pressure photon ionization time-of-flight mass spectrometry

BACKGROUND

In this study, exhaled breath testing has been considered a promising method for the detection and monitoring of breast cancer (BC).

METHODS

A high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform was used to detect volatile organic compounds (VOCs) in breath samples. Then, machine learning (ML) models were constructed on VOCs for the diagnosis of BC and its progression monitoring. Ultimately, 1981 women with useable breath samples were included in the study, of whom 937 (47.3 %) had been diagnosed with BC. VOC panels were used for ML model construction for BC detection and progression monitoring.

RESULTS

On the blinded testing cohort, this VOC-based model successfully differentiated patients with and without BC with sensitivity, specificity, and area under receiver operator characteristic curve (AUC) values of 85.9 %, 90.4 %, and 0.946. The corresponding AUC values when differentiating between patients with and without lymph node metastasis (LNM) or between patients with tumor-node-metastasis (TNM) stage 0/I/II or III/IV disease were 0.840 and 0.708, respectively. While developed VOC-based models exhibited poor performance when attempting to differentiate between patients based on pathological patterns (Ductal carcinoma in situ (DCIS) vs Invasive BC (IBC)) or molecular subtypes (Luminal vs Human epidermal growth factor receptor 2 (HER2+) vs Triple-negative BC (TNBC)) of BC.

CONCLUSION

Collectively, the HPPI-TOFMS-based breathomics approaches may offer value for the detection and progression monitoring of BC. Additional research is necessary to explore the fundamental mechanisms of the identified VOCs.

Asymmetric crowders and membrane morphology at the nexus of intracellular trafficking and oncology

A definitive understanding of the interplay between protein binding/migration and membrane curvature evolution is emerging but needs further study. The mechanisms defining such phenomena are critical to intracellular transport and trafficking of proteins. Among trafficking modalities, exosomes have drawn attention in cancer research as these nano-sized naturally occurring vehicles are implicated in intercellular communication in the tumor microenvironment, suppressing anti-tumor immunity and preparing the metastatic niche for progression. A significant question in the field is how the release and composition of tumor exosomes are regulated. In this perspective article, we explore how physical factors such as geometry and tissue mechanics regulate cell cortical tension to influence exosome production by co-opting the biophysics as well as the signaling dynamics of intracellular trafficking pathways and how these exosomes contribute to the suppression of anti-tumor immunity and promote metastasis. We describe a multiscale modeling approach whose impact goes beyond the fundamental investigation of specific cellular processes toward actual clinical translation. Exosomal mechanisms are critical to developing and approving liquid biopsy technologies, poised to transform future non-invasive, longitudinal profiling of evolving tumors and resistance to cancer therapies to bring us one step closer to the promise of personalized medicine.

Exploration of Curvature and Stiffness Dual-Regulated Breast Cancer Cell Motility by a Motor-Clutch Model and Cell Traction Force Characterization

The migration of breast cancer cells is the main cause of death and significantly regulated by physical factors of the extracellular matrix (ECM). To be specific, the curvature and stiffness of the ECM were discovered to effectively guide cell migration in velocity and direction. However, it is not clear what the extent of effect is when these dual-physical factors regulate cell migration. Moreover, the mechanobiology mechanism of breast cancer cell migration in the molecular level and analysis of cell traction force (CTF) are also important, but there is a lack of systematic investigation. Therefore, we employed a microfluidic platform to construct hydrogel microspheres with an independently adjustable curvature and stiffness as a three-dimensional substrate for breast cancer cell migration. We found that the cell migration velocity was negatively correlated to curvature and positively correlated to stiffness. In addition, curvature was investigated to influence the focal adhesion expression as well as the assignment of F-actin at the molecular level. Further, with the help of a motor-clutch mathematical model and hydrogel microsphere stress sensors, it was concluded that cells perceived physical factors (curvature and stiffness) to cause changes in CTF, which ultimately regulated cell motility. In summary, we employed a theoretical model (motor-clutch) and experimental strategy (stress sensors) to understand the mechanism of curvature and stiffness regulating breast cancer cell motility. These results provide evidence of force driven cancer cell migration by ECM physical factors and explain the mechanism from the perspective of mechanobiology.

Epinephrine promotes breast cancer metastasis through a ubiquitin-specific peptidase 22-mediated lipolysis circuit

Chronic stress-induced epinephrine (EPI) accelerates breast cancer progression and metastasis, but the molecular mechanisms remain unclear. Herein, we found a strong positive correlation between circulating EPI levels and the tumoral expression of ubiquitin-specific peptidase 22 (USP22) in patients with breast cancer. USP22 facilitated EPI-induced breast cancer progression and metastasis by enhancing adipose triglyceride lipase (ATGL)-mediated lipolysis. Targeted USP22 deletion decreased ATGL expression and lipolysis, subsequently inhibiting EPI-mediated breast cancer lung metastasis. USP22 acts as a bona fide deubiquitinase for the Atgl gene transcription factor FOXO1, and EPI architects a lipolysis signaling pathway to stabilize USP22 through AKT-mediated phosphorylation. Notably, USP22 phosphorylation levels are positively associated with EPI and with downstream pathways involving both FOXO1 and ATGL in breast cancers. Pharmacological USP22 inhibition synergized with β-blockers in treating preclinical xenograft breast cancer models. This study reveals a molecular pathway behind EPI's tumor-promoting effects and provides a strong rationale for combining USP22 inhibition with β-blockers to treat aggressive breast cancer.

ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions

INTRODUCTION

Breast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis.

OBJECTIVES

Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models.

RESULTS

ARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10-29). ARTEMIS demonstrated satisfactory discrimination ability across four independent populations, with pooled AUC3-year = 0.844 (95% CI: 0.805-0.883), AUC5-year = 0.816 (95% CI: 0.775-0.857), and C-index = 0.803 (95% CI: 0.776-0.830). Meanwhile, ARTEMIS had well calibration performance with pooled E/O ratio 1.060 (95% CI: 1.038-1.083) and 1.090 (95% CI: 1.057-1.122) for 3- and 5-year survival prediction, respectively. Additionally, ARTEMIS is a clinical instrument with acceptable cost-effectiveness for detecting breast cancer patients at high risk of mortality (Pt = 0.4: NB3-year = 19‰, NB5-year = 62‰; NR3-year = 69.21%, NR5-year = 56.01%). ARTEMIS has superior performance compared to existing models in terms of accuracy, extrapolation, and sample size, as indicated by the systematic review. ARTEMIS is implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/ARTEMIS/.

CONCLUSION

ARTEMIS is an efficient and practical tool for breast cancer prognostic prediction.

Harnessing the evolving CRISPR/Cas9 for precision oncology

The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 system, a groundbreaking innovation in genetic engineering, has revolutionized our approach to surmounting complex diseases, culminating in CASGEVY™ approved for sickle cell anemia. Derived from a microbial immune defense mechanism, CRISPR/Cas9, characterized as precision, maneuverability and universality in gene editing, has been harnessed as a versatile tool for precisely manipulating DNA in mammals. In the process of applying it to practice, the consecutive exploitation of novel orthologs and variants never ceases. It's conducive to understanding the essentialities of diseases, particularly cancer, which is crucial for diagnosis, prevention, and treatment. CRISPR/Cas9 is used not only to investigate tumorous genes functioning but also to model disparate cancers, providing valuable insights into tumor biology, resistance, and immune evasion. Upon cancer therapy, CRISPR/Cas9 is instrumental in developing individual and precise cancer therapies that can selectively activate or deactivate genes within tumor cells, aiming to cripple tumor growth and invasion and sensitize cancer cells to treatments. Furthermore, it facilitates the development of innovative treatments, enhancing the targeting efficiency of reprogrammed immune cells, exemplified by advancements in CAR-T regimen. Beyond therapy, it is a potent tool for screening susceptible genes, offering the possibility of intervening before the tumor initiative or progresses. However, despite its vast potential, the application of CRISPR/Cas9 in cancer research and therapy is accompanied by significant efficacy, efficiency, technical, and safety considerations. Escalating technology innovations are warranted to address these issues. The CRISPR/Cas9 system is revolutionizing cancer research and treatment, opening up new avenues for advancements in our understanding and management of cancers. The integration of this evolving technology into clinical practice promises a new era of precision oncology, with targeted, personalized, and potentially curative therapies for cancer patients.

Surface-enhanced Raman scattering-based identification of breast cancer progression using extracellular vesicles-derived integrin α6β4

Detection of progression is of great importance to breast cancer treatment and can benefit patients. Limited by current detection technologies and biomarkers, early breast cancer progression diagnosis remains challenging. Researchers have found blood extracellular vesicles (EVs)-derived integrin α6β4 directly facilitate progression in breast cancer, enabling cancer detection. However, EVs size and heterogeneity hinder protein detection, masked by abundant background EVs. Hence, novel tools for efficient detection of EVs with high selectivity and low interference are significantly desired. Here, a new silver-coated gold nanorods SERS probe, termed as Au@Ag@IDA-B/4MSTP, based on DNA aptamer was established for the detection of integrin α6β4 derived from EVs. Validation of the Au@Ag@IDA-B/4MSTP probes using cell-culture-derived EVs revealed a LOD of 23 particles/μL for EVs detection. This tool was further confirmed to mimic the real state of cancer with subcutaneous tumor model and lung metastasis model in mice. With 10 μL of blood plasma and simple Raman analysis process, the test achieved 85.7 % sensitivity and 83.3 % specificity. Moreover, our method achieves a simplified approach that expedites the detection process. These results demonstrate the good detection performance of Au@Ag@IDA-B/4MSTP probes for EVs integrin α6β4, and suggest that this non-invasive approach could be a promising tool for early detection of breast cancer progression.

Did the Coronavirus Disease 2019 (COVID-19) Pandemic Cause a Delay in the Diagnosis of Breast Cancer Patients?

Introduction The coronavirus disease 2019 (COVID-19) outbreak, first reported in Wuhan, China, in December 2019, quickly hit the world in just one month, causing a global public health emergency. We aimed to investigate whether the COVID-19 pandemic caused a delay in the hospital admissions of breast cancer patients and diagnosis of breast cancer, thus increasing the tumor size and the stage of the disease. Materials and methods Included in the study were patients who underwent breast cancer surgery between 01/03/2019 and 01/03/2020 (pre-COVID-19, first period) and between 01/03/2020 and 01/03/2021 (post-COVID-19, second period). Three hundred and seventy patients with enough details were included, and details were analyzed retrospectively. Tumor characteristics of pre-COVID-19 breast cancer patients were compared with the tumor characteristics of post-COVID-19 breast cancer patients. Demographics, preoperative diagnosis, tumor properties, surgical procedure (breast-conserving surgery, modified radical mastectomy, simple mastectomy, skin-sparing mastectomy), tumor size, total lymph node number, metastatic lymph node number, locally advanced disease, metastatic disease, and neoadjuvant therapy were evaluated. Results The mean tumor size increased significantly in the post-COVID-19 primary surgery group (p=0.005). There is no significant relationship between the pre-COVID-19 and post-COVID-19 period and pT in the neoadjuvant received group (p>0.05). The presence of pT2+pT3+pT4 was statistically significantly higher in the post-COVID-19 primary surgery group (p=0.001). The mean value of metastatic lymph nodes dissected between pre-COVID-19 and post-COVID-19 primary surgery groups increased significantly (p=0.010). Pericapsular extension was higher in the post-primary surgery group (p=0.002). Conclusion During the COVID-19 outbreak, breast cancer patients have difficulty accessing healthcare services and hesitate to apply to hospitals to fear contracting the COVID-19 disease. This situation has led to delays in diagnosing breast cancer patients, increased tumor size and pT grade, increased number of metastatic lymph nodes, pericapsular extension, and the resulting disease often appearing in advanced sizes and stages.

SHG Fiberscopy Assessment of Collagen Morphology and Its Potential for Breast Cancer Optical Histology

OBJECTIVE

This study is to investigate the feasibility of our recently developed nonlinear fiberscope for label-free in situ breast tumor detection and lymph node status assessment based on second harmonic generation (SHG) imaging of fibrillar collagen matrix with histological details. The long-term goal is to improve the current biopsy-based cancer paradigm with reduced sampling errors.

METHODS

In this pilot study we undertook retrospective SHG imaging study of ex vivo invasive ductal carcinoma human biopsy tissue samples, and carried out quantitative image analysis to search for collagen structural signatures that are associated with the malignance of breast cancer.

RESULTS

SHG fiberscopy image-based quantitative assessment of collagen fiber morphology reveals that: 1) cancerous tissues contain generally less extracellular collagen fibers compared with tumor-adjacent normal tissues, and 2) collagen fibers in lymph node positive biopsies are more aligned than lymph node negative counterparts.

CONCLUSION/SIGNIFICANCE

The results demonstrate the promising potential of our SHG fiberscope for in situ breast tumor detection and lymph node involvement assessment and for offering real-time guidance during ongoing tissue biopsy.

Exosomal lncRNAs as regulators of breast cancer chemoresistance and metastasis and their potential use as biomarkers

Breast cancer is the most common cancer in women and the leading cause of female deaths by cancer in the world worldwide. Hence, understanding the molecular mechanisms associated with breast cancer development and progression, including drug resistance and breast cancer metastasis, is essential for achieving the best management of breast cancer patients. Cancer-related long noncoding RNAs have been shown to be involved in the regulation of each stage of breast cancer progression. Additionally, exosomes are extracellular microvesicles that are central to intercellular communication and play an important role in tumorigenesis. Exosomes can be released from primary tumor cells into the bloodstream and transmit cellular signals to distant body sites. In this work, we review the findings regarding the cellular mechanisms regulated by exosomal lncRNAs that are essentials to chemoresistance development and metastasis of breast cancer. Likewise, we evaluate the outcomes of the potential clinical use of exosomal lncRNAs as breast cancer biomarkers to achieve personalized management of the patients. This finding highlights the importance of transcriptomic analysis of exosomal lncRNAs to understand the breast cancer tumorigenesis as well as to improve the clinical tests available for this disease.

Unveiling the cancer risk nexus of the steatotic liver

Steatotic liver, characterized by the accumulation of fat in the liver, poses significant health risks including metabolic dysfunction-associated steatotic liver disease (MASLD) and an elevated risk of primary liver cancer. Emerging evidence indicates a robust association between steatotic liver and increased susceptibility to extrahepatic primary cancers and their metastases. The deposition of fat induces dynamic changes in hepatic microenvironments, thereby fostering inflammation and immune responses that enhance liver metastasis from extrahepatic primary cancers. This review explores the impact of steatotic liver on hepatic carcinogenesis and metastasis from extrahepatic cancers, with a specific focus on hepatocyte-derived factors and the immune microenvironment. By emphasizing novel conclusions, this article underscores the timely relevance of understanding these intricate connections.

Characterisation of Canine and Feline Breast Tumours, Their Metastases, and Corresponding Primary Cell Lines Using LA-REIMS and DESI-MS Imaging

Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours' characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer.

AI models predicting breast cancer distant metastasis using LightGBM with clinical blood markers and ultrasound maximum diameter

Breast cancer metastasis significantly impacts women's health globally. This study aimed to construct predictive models using clinical blood markers and ultrasound data to predict distant metastasis in breast cancer patients, ensuring clinical applicability, cost-effectiveness, relative non-invasiveness, and accessibility of these models. Analysis was conducted on data from 416 patients across two centers, focusing on clinical blood markers (tumor markers, liver and kidney function indicators, blood lipid markers, cardiovascular biomarkers) and maximum lesion diameter from ultrasound. Feature reduction was performed using Spearman correlation and LASSO regression. Two models were built using LightGBM: a clinical model (using clinical blood markers) and a combined model (incorporating clinical blood markers and ultrasound features), validated in training, internal test, and external validation (test1) cohorts. Feature importance analysis was conducted for both models, followed by univariate and multivariate regression analyses of these features. The AUC values of the clinical model in the training, internal test, and external validation (test1) cohorts were 0.950, 0.795, and 0.883, respectively. The combined model showed AUC values of 0.955, 0.835, and 0.918 in the training, internal test, and external validation (test1) cohorts, respectively. Clinical utility curve analysis indicated the combined model's superior net benefit in identifying breast cancer with distant metastasis across all cohorts. This suggests the combined model's superior discriminatory ability and strong generalization performance. Creatine kinase isoenzyme (CK-MB), CEA, CA153, albumin, creatine kinase, and maximum lesion diameter from ultrasound played significant roles in model prediction. CA153, CK-MB, lipoprotein (a), and maximum lesion diameter from ultrasound positively correlated with breast cancer distant metastasis, while indirect bilirubin and magnesium ions showed negative correlations. This study successfully utilized clinical blood markers and ultrasound data to develop AI models for predicting distant metastasis in breast cancer. The combined model, incorporating clinical blood markers and ultrasound features, exhibited higher accuracy, suggesting its potential clinical utility in predicting and identifying breast cancer distant metastasis. These findings highlight the potential prospects of developing cost-effective and accessible predictive tools in clinical oncology.

Neutrophil extracellular traps modulate chemotherapy efficacy and its adverse side effects

Neutrophils, major regulator of innate immunity have recently emerged as key components of the tumor microenvironment. The role of neutrophils in cancer has been linked to their ability to form neutrophil extracellular traps (NETs), structures composed of decondensed DNA decorated with enzymes that are released into the extracellular space. Here, we discuss the pivotal roles of NETs, in influencing responses to chemotherapy and its severe adverse effect. Highlighting recent insights, we discuss the dual nature of NETs in the context of chemotherapy treatment, examining their potential to either counteract or enhance treatment outcomes. Strategic targeting of NETs emerges as a promising avenue for determining combination therapies that could help counteracting resistance or enhancing chemotherapy efficacy as well as limiting complications due to this type of treatment.

In Vivo PET Detection of Lung Micrometastasis in Mice by Targeting Endothelial VCAM-1 Using a Dual-Contrast PET/MRI Probe

Current clinical diagnostic imaging methods for lung metastases are sensitive only to large tumours (1-2 mm cross-sectional diameter), and early detection can dramatically improve treatment. We have previously demonstrated that an antibody-targeted MRI contrast agent based on microparticles of iron oxide (MPIO; 1 μm diameter) enables the imaging of endothelial vascular cell adhesion molecule-1 (VCAM-1). Using a mouse model of lung metastasis, upregulation of endothelial VCAM-1 expression was demonstrated in micrometastasis-associated vessels but not in normal lung tissue, and binding of VCAM-MPIO to these vessels was evident histologically. Owing to the lack of proton MRI signals in the lungs, we modified the VCAM-MPIO to include zirconium-89 (89Zr, t1/2 = 78.4 h) in order to allow the in vivo detection of lung metastases by positron emission tomography (PET). Using this new agent (89Zr-DFO-VCAM-MPIO), it was possible to detect the presence of micrometastases within the lung in vivo from ca. 140 μm in diameter. Histological analysis combined with autoradiography confirmed the specific binding of the agent to the VCAM-1 expressing vasculature at the sites of pulmonary micrometastases. By retaining the original VCAM-MPIO as the basis for this new molecular contrast agent, we have created a dual-modality (PET/MRI) agent for the concurrent detection of lung and brain micrometastases.

VHL suppresses UBE3B-mediated breast tumor growth and metastasis

Protein homeostasis is predominantly governed through post-translational modification (PTM). UBE3B, identified as an oncoprotein, exhibits elevated protein levels in breast cancer. However, the impact of PTM on UBE3B remains unexplored. In this study, we show that VHL is a bona fide E3 ligase for UBE3B. Mechanistically, VHL directly binds to UBE3B, facilitating its lysine 48 (K48)-linked polyubiquitination at K286 and K427 in a prolyl hydroxylase (PHD)-independent manner. Consequently, this promotes the proteasomal degradation of UBE3B. The K286/427R mutation of UBE3B dramatically abolishes the inhibitory effect of VHL on breast tumor growth and lung metastasis. Additionally, the protein levels of UBE3B and VHL exhibit a negative correlation in breast cancer tissues. These findings delineate an important layer of UBE3B regulation by VHL.

Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study

Objective

This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients.

Methods

Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models.

Results

The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase.

Conclusion

This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

PI 3-Kinase and the Histone Methyl-Transferase KMT2D Collaborate to Induce Arp2/3-Dependent Migration of Mammary Epithelial Cells

Breast cancer develops upon sequential acquisition of driver mutations in mammary epithelial cells; however, how these mutations collaborate to transform normal cells remains unclear in most cases. We aimed to reconstitute this process in a particular case. To this end, we combined the activated form of the PI 3-kinase harboring the H1047R mutation with the inactivation of the histone lysine methyl-transferase KMT2D in the non-tumorigenic human mammary epithelial cell line MCF10A. We found that PI 3-kinase activation promoted cell-cycle progression, especially when growth signals were limiting, as well as cell migration, both in a collective monolayer and as single cells. Furthermore, we showed that KMT2D inactivation had relatively little influence on these processes, except for single-cell migration, which KMT2D inactivation promoted in synergy with PI 3-kinase activation. The combination of these two genetic alterations induced expression of the ARPC5L gene that encodes a subunit of the Arp2/3 complex. ARPC5L depletion fully abolished the enhanced migration persistence exhibited by double-mutant cells. Our reconstitution approach in MCF10A has thus revealed both the cell function and the single-cell migration, and the underlying Arp2/3-dependent mechanism, which are synergistically regulated when KMT2D inactivation is combined with the activation of the PI 3-kinase.

The emerging role and mechanism of HMGA2 in breast cancer

High mobility group AT-hook 2 (HMGA2) is a member of the non-histone chromosomal high mobility group (HMG) protein family, which participate in embryonic development and other biological processes. HMGA2 overexpression is associated with breast cancer (BC) cell growth, proliferation, metastasis, and drug resistance. Furthermore, HMGA2 expression is positively associated with poor prognosis of patients with BC, and inhibiting HMGA2 signaling can stimulate BC cell progression and metastasis. In this review, we focus on HMGA2 expression changes in BC tissues and multiple BC cell lines. Wnt/β-catenin, STAT3, CNN6, and TRAIL-R2 proteins are upstream mediators of HMGA2 that can induce BC invasion and metastasis. Moreover, microRNAs (miRNAs) can suppress BC cell growth, invasion, and metastasis by inhibiting HMGA2 expression. Furthermore, long noncoding RNAs (LncRNAs) and circular RNAs (CircRNAs) mainly regulate HMGA2 mRNA and protein expression levels by sponging miRNAs, thereby promoting BC development. Additionally, certain small molecule inhibitors can suppress BC drug resistance by reducing HMGA2 expression. Finally, we summarize findings demonstrating that HMGA2 siRNA and HMGA2 siRNA-loaded nanoliposomes can suppress BC progression and metastasis.

Glyoxalase System in Breast and Ovarian Cancers: Role of MEK/ERK/SMAD1 Pathway

The glyoxalase system, comprising GLO1 and GLO2 enzymes, is integral in detoxifying methylglyoxal (MGO) generated during glycolysis, with dysregulation implicated in various cancer types. The MEK/ERK/SMAD1 signaling pathway, crucial in cellular processes, influences tumorigenesis, metastasis, and angiogenesis. Altered GLO1 expression in cancer showcases its complex role in cellular adaptation and cancer aggressiveness. GLO2 exhibits context-dependent functions, contributing to both proapoptotic and antiapoptotic effects in different cancer scenarios. Research highlights the interconnected nature of these systems, particularly in ovarian cancer and breast cancer. The glyoxalase system's involvement in drug resistance and its impact on the MEK/ERK/SMAD1 signaling cascade underscore their clinical significance. Furthermore, this review delves into the urgent need for effective biomarkers, exemplified in ovarian cancer, where the RAGE-ligand pathway emerges as a potential diagnostic tool. While therapeutic strategies targeting these pathways hold promise, this review emphasizes the challenges posed by context-dependent effects and intricate crosstalk within the cellular milieu. Insights into the molecular intricacies of these pathways offer a foundation for developing innovative therapeutic approaches, providing hope for enhanced cancer diagnostics and tailored treatment strategies.

TAZ is involved in breast cancer cell migration via regulating actin dynamics

Background

Cancer metastasis is dependent on cell migration. Several mechanisms, including epithelial-to-mesenchymal transition (EMT) and actin fiber formation, could be involved in cancer cell migration. As a downstream effector of the Hippo signaling pathway, transcriptional coactivator with PDZ-binding motif (TAZ) is recognized as a key mediator of the metastatic ability of breast cancer cells. We aimed to examine whether TAZ affects the migration of breast cancer cells through the regulation of EMT or actin cytoskeleton.

Methods

MCF-7 and MDA-MB-231 cells were treated with siRNA to attenuate TAZ abundance. Transwell migration assay and scratch wound healing assay were performed to study the effects of TAZ knockdown on cancer cell migration. Fluorescence microscopy was conducted to examine the vinculin and phalloidin. Semiquantitative immunoblotting and quantitative real-time PCR were performed to study the expression of small GTPases and kinases. Changes in the expression of genes associated with cell migration were examined through next-generation sequencing.

Results

TAZ-siRNA treatment reduced TAZ abundance in MCF-7 and MDA-MB-231 breast cancer cells, which was associated with a significant decrease in cell migration. TAZ knockdown increased the expression of fibronectin, but it did not exhibit the typical pattern of EMT progression. TGF-β treatment in MDA-MB-231 cells resulted in a reduction in TAZ and an increase in fibronectin levels. However, it paradoxically promoted cell migration, suggesting that EMT is unlikely to be involved in the decreased migration of breast cancer cells in response to TAZ suppression. RhoA, a small Rho GTPase protein, was significantly reduced in response to TAZ knockdown. This caused a decrease in the expression of the Rho-dependent downstream pathway, i.e., LIM kinase 1 (LIMK1), phosphorylated LIMK1/2, and phosphorylated cofilin, leading to actin depolymerization. Furthermore, myosin light chain kinase (MLCK) and phosphorylated MLC2 were significantly decreased in MDA-MB-231 cells with TAZ knockdown, inhibiting the assembly of stress fibers and focal adhesions.

Conclusion

TAZ knockdown inhibits the migration of breast cancer cells by regulating the intracellular actin cytoskeletal organization. This is achieved, in part, by reducing the abundance of RhoA and Rho-dependent downstream kinase proteins, which results in actin depolymerization and the disassembly of stress fibers and focal adhesions.

Dual FGFR-targeting and pH-activatable ruthenium-peptide conjugates for targeted therapy of breast cancer

Dysregulation of Fibroblast Growth Factor Receptors (FGFRs) signaling has been associated with breast cancer, yet employing FGFR-targeted delivery systems to improve the efficacy of cytotoxic agents is still sparsely exploited. Herein, we report four new bi-functional ruthenium-peptide conjugates (RuPCs) with FGFR-targeting and pH-dependent releasing abilities, envisioning the selective delivery of cytotoxic Ru complexes to FGFR(+)-breast cancer cells, and controlled activation at the acidic tumoral microenvironment. The antiproliferative potential of the RuPCs and free Ru complexes was evaluated in four breast cancer cell lines with different FGFR expression levels (SKBR-3, MDA-MB-134-VI, MCF-7, and MDA-MB-231) and in human dermal fibroblasts (HDF), at pH 6.8 and pH 7.4 aimed at mimicking the tumor microenvironment and normal tissues/bloodstream pHs, respectively. The RuPCs showed higher cytotoxicity in cells with higher level of FGFR expression at acidic pH. Additionally, RuPCs showed up to 6-fold higher activity in the FGFR(+) breast cancer lines compared to the normal cell line. The release profile of Ru complexes from RuPCs corroborates the antiproliferative effects observed. Remarkably, the cytotoxicity and releasing ability of RuPCs were shown to be strongly dependent on the conjugation of the peptide position in the Ru complex. Complementary molecular dynamic simulations and computational calculations were performed to help interpret these findings at the molecular level. In summary, we identified a lead bi-functional RuPC that holds strong potential as a FGFR-targeted chemotherapeutic agent.

Ezetimibe inhibits the migration and invasion of triple-negative breast cancer cells by targeting TGFβ2 and EMT

The important role of cholesterol in tumor metastasis has been widely studied in recent years. Ezetimibe is currently the only selective cholesterol uptake inhibitor on the market. Here, we explored the effect of ezetimibe on breast cancer metastasis by studying its impact on breast cancer cell migration, invasion, and epithelial-mesenchymal transition (EMT). Differential gene expression analysis and validation were also carried out to compare ezetimibe-treated and untreated breast cancer cells. Finally, breast cancer cells overexpressing TGFβ2 were constructed, and the effect of TGFβ2 on the migration and invasion of ezetimibe-treated breast cancer cells was examined. Our results show that ezetimibe treatment of breast cancer cells inhibited cell migration, invasion, and EMT, and it significantly suppressed the expression of TGFβ2. Overexpression of TGFβ2 reversed the inhibitory effect of ezetimibe on the migration and invasion of breast cancer cells. Taken together, our results suggest that ezetimibe might be a potential candidate for the treatment of breast cancer metastasis.

MCT4 and CD147 colocalize with MMP14 in invadopodia and support matrix degradation and invasion by breast cancer cells

Expression levels of the lactate-H+ cotransporter MCT4 (also known as SLC16A3) and its chaperone CD147 (also known as basigin) are upregulated in breast cancers, correlating with decreased patient survival. Here, we test the hypothesis that MCT4 and CD147 favor breast cancer invasion through interdependent effects on extracellular matrix (ECM) degradation. MCT4 and CD147 expression and membrane localization were found to be strongly reciprocally interdependent in MDA-MB-231 breast cancer cells. Overexpression of MCT4 and/or CD147 increased, and their knockdown decreased, migration, invasion and the degradation of fluorescently labeled gelatin. Overexpression of both proteins led to increases in gelatin degradation and appearance of the matrix metalloproteinase (MMP)-generated collagen-I cleavage product reC1M, and these increases were greater than those observed upon overexpression of each protein alone, suggesting a concerted role in ECM degradation. MCT4 and CD147 colocalized with invadopodia markers at the plasma membrane. They also colocalized with MMP14 and the lysosomal marker LAMP1, as well as partially with the autophagosome marker LC3, in F-actin-decorated intracellular vesicles. We conclude that MCT4 and CD147 reciprocally regulate each other and interdependently support migration and invasiveness of MDA-MB-231 breast cancer cells. Mechanistically, this involves MCT4-CD147-dependent stimulation of ECM degradation and specifically of MMP-mediated collagen-I degradation. We suggest that the MCT4-CD147 complex is co-delivered to invadopodia with MMP14.

Free energy calculations for membrane morphological transformations and insights to physical biology and oncology

In this chapter, we aim to bridge basic molecular and cellular principles surrounding membrane curvature generation with rewiring of cellular signals in cancer through multiscale models. We describe a general framework that integrates signaling with other cellular functions like trafficking, cell-cell and cell-matrix adhesion, and motility. The guiding question in our approach is: how does a physical change in cell membrane configuration caused by external stimuli (including those by the extracellular microenvironment) alter trafficking, signaling and subsequent cell fate? We answer this question by constructing a modeling framework based on stochastic spatial continuum models of cell membrane deformations. We apply this framework to explore the link between trafficking, signaling in the tumor microenvironment, and cell fate. At each stage, we aim to connect the results of our predictions with cellular experiments.

The Influence of Tumor-Specific Markers in Breast Cancer on Other Blood Parameters

BACKGROUND

Breast cancer is the most frequently diagnosed cancer among women, responsible for the highest number of cancer-related deaths worldwide. There is limited data available related to serum tumor markers in breast cancer and other blood parameters or other glandular laboratory parameters. This study aims to evaluate the correlation of tumor-specific markers for breast cancer with other blood parameters and how these correlations could impact clinical management.

MATERIAL AND METHOD

This retrospective study represents a data analysis from 1 January 2020 to 31 May 2023, in the County Hospital of Timisoara, Romania. We reviewed all the cases where, in the laboratory analyses, the serum tumor specific biomarkers for breast cancer were analyzed.

RESULTS

A statistical analysis was performed in order to identify a possible relationship between CA 15-3 and the various biomarkers and blood parameters included in the present study. Values were classified according to reference ranges. The tests revealed no statistically significant associations between CA 15-3 values and the levels of CA125 (χ2(1) = 1.852, p = 0.174), CEA (χ2(1) = 1.139, p = 0.286), AFP (Fisher's exact test, p = 0.341), fT4 (Fisher's exact test, p = 0.310), TSH (Fisher's exact test, p = 0.177), or PTH (Fisher's exact test, p = 0.650).

CONCLUSION

The findings indicate a lack of strong correlation between CA 15-3 and CA125, CEA, AFP, thyroid function markers, or PTH within this cohort.

Perioperative Ketamine and Cancer Recurrence: A Comprehensive Review

Cancer is a significant global health threat and a leading cause of death worldwide. Effective early-stage interventions, particularly surgery, can potentially cure many solid tumors. However, the risk of postoperative cancer recurrence remains high. Recent research highlights the influence of perioperative anesthetic and analgesic choices on the fate of residual cancer cells, potentially affecting recurrence risks. Among these agents, ketamine-a well-known anesthetic and analgesic-has garnered interest due to its antitumor properties, mainly through inhibiting the N-methyl-D-aspartate (NMDA) receptor found in various cancer tissues. Additionally, ketamine's potential immunomodulatory effects, given the expression of NMDA receptors on immune cells, suggest that it plays a significant role during the perioperative period. This review synthesizes current evidence on ketamine's impact on cancer cell biology, inflammation, immune modulation, and the role of the gut microbiota, proposing ketamine as a promising agent for enhancing oncological outcomes.

Molecular perspectives on systemic priming and concomitant immunity in colorectal carcinoma

The progression of metastasis, a complex systemic disease, is facilitated by interactions between tumor cells and their isolated microenvironments. Over the past few decades, researchers have investigated the metastatic spread of cancer extensively, identifying multiple stages in the process, such as intravasation, extravasation, tumor latency, and the development of micrometastasis and macrometastasis. The premetastatic niche is established in target organs by the accumulation of aberrant immune cells and extracellular matrix proteins. The "seed and soil" idea, which has become widely known and accepted, is being used to this day to guide cancer studies. Changes in the local and systemic immune systems have a major impact on whether an infection spreads or not. The belief that the immune response may play a role in slowing tumor growth and may be beneficial against the metastatic disease underpins the responsiveness shown in the immunological landscape of metastasis. Various hypotheses on the phylogenesis of metastases have been proposed in the past. The primary tumor's secreting factors shape the intratumoral microenvironment and the immune landscape, allowing this progress to be made. Therefore, it is evident that among disseminated tumor cells, there are distinct phenotypes that either carry budding for metastasis or have the ability to obtain this potential or in systemic priming through contact with substantial metastatic niches that have implications for medicinal chemistry. Concurrent immunity signals that the main tumor induces an immune response that may not be strong enough to eradicate the tumor. Immunotherapy's success with some cancer patients shows that it is possible to effectively destroy even advanced-stage tumors by modifying the microenvironment and tumor-immune cell interactions. This review focuses on the metastasome in colorectal carcinoma and the therapeutic implications of site-specific metastasis, systemic priming, tumor spread, and the relationship between the immune system and metastasis.

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics

INTRODUCTION

Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment.

CONTENT

In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack.

SUMMARY AND OUTLOOK

We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Recent progress of CDK4/6 inhibitors' current practice in breast cancer

Dysregulated cellular proliferation represents a hallmark feature across all cancers. Aberrant activation of the cyclin-dependent kinase 4 and 6 (CDK4/6) pathway, independent of mitogenic signaling, engenders uncontrolled breast cancer cell proliferation. Consequently, the advent of CDK4/6 inhibition has constituted a pivotal milestone in the realm of targeted breast cancer therapy. The combination of CDK4/6 inhibitors (CDK4/6i) with endocrine therapy (ET) has emerged as the foremost therapeutic modality for patients afflicted with hormone receptor-positive (HR + )/HER2-negative (HER2-) advanced breast cancer. At present, the Food and Drug Administration (FDA) has sanctioned various CDK4/6i for employment as the primary treatment regimen in HR + /HER2- breast cancer. This therapeutic approach has demonstrated a substantial extension of progression-free survival (PFS), often amounting to several months, when administered alongside endocrine therapy. Within this comprehensive review, we systematically evaluate the utilization strategies of CDK4/6i across various subpopulations of breast cancer and explore potential therapeutic avenues following disease progression during application of CDK4/6i therapy.

Peroxiredoxin 3 regulates breast cancer progression via ERK-mediated MMP-1 expression

Peroxiredoxin 3 (PRDX3), a mitochondrial hydrogen peroxide scavenger, is known to be upregulated during tumorigenesis and cancer progression. In this study, we provide evidence for the first time that PRDX3 could regulate cellular signaling pathways associated with Matrix Metalloproteinase-1 (MMP-1) expression and activity in breast cancer progression. We show that shRNA-mediated gene silencing of PRDX3 inhibits cell migration and invasion in two triple-negative breast cancer cell lines. Reciprocal experiments show that PRDX3 overexpression promotes invasion and migration of the cancer cells, processes which are important in the metastatic cascade. Notably, this phenomenon may be attributed to the activation of MMP-1, which is observed to be upregulated by PRDX3 in the breast cancer cells. Moreover, immunohistochemical staining of breast cancer tissues revealed a positive correlation between PRDX3 and MMP-1 expression in both epithelial and stromal parts of the tissues. Further pathway reporter array and luciferase assay demonstrated that activation of ERK signaling is responsible for the transcriptional activation of MMP-1 in PRDX3-overexpressed cells. These findings suggest that PRDX3 could mediate cancer spread via ERK-mediated activation of MMP-1. Targeted inhibition of ERK signaling may be able to inhibit tumor metastasis in triple-negative breast cancer.

The ways Fusobacterium nucleatum translocate to breast tissue and contribute to breast cancer development

Breast cancer is among the most prevalent malignancies in women worldwide. Epidemiological findings suggested that periodontal diseases may be associated with breast cancer, among which Fusobacterium nucleatum is considered an important cross-participant. In this work, we comprehensively summarize the known mechanisms of how F. nucleatum translocates to, colonizes in mammary tumors, and promotes the carcinogenesis. Specifically, F. nucleatum translocates to mammary tissue through the mammary-intestinal axis, direct nipple contact, and hematogenous transmission. Subsequently, F. nucleatum takes advantage of fusobacterium autotransporter protein 2 to colonize breast cancer and uses virulence factors fusobacterium adhesin A and lipopolysaccharide to promote proliferation. Moreover, the upregulated matrix metalloproteinase-9 induced by F. nucleatum does not only trigger the inflammatory response but also facilitates the tumor-promoting microenvironment. Aside from the pro-inflammatory effect, F. nucleatum may also be engaged in tumor immune evasion, which is achieved through the action of virulence factors on immune checkpoint receptors highly expressed on T cells, natural killer cells, and tumor-infiltrating lymphocytes. Taking breast cancer as an example, more relevant research studies may expand our current knowledge of how oral microbes affect systemic health. Hopefully, exploring these mechanisms in depth could provide new strategies for safer and more effective biologic and targeted therapies targeted at breast cancer.

A Preliminary Investigation into Search and Matching for Tumor Discrimination in World Health Organization Breast Taxonomy Using Deep Networks

Breast cancer is one of the most common cancers affecting women worldwide. It includes a group of malignant neoplasms with a variety of biological, clinical, and histopathologic characteristics. There are more than 35 different histologic forms of breast lesions that can be classified and diagnosed histologically according to cell morphology, growth, and architecture patterns. Recently, deep learning, in the field of artificial intelligence, has drawn a lot of attention for the computerized representation of medical images. Searchable digital atlases can provide pathologists with patch-matching tools, allowing them to search among evidently diagnosed and treated archival cases, a technology that may be regarded as computational second opinion. In this study, we indexed and analyzed the World Health Organization breast taxonomy (Classification of Tumors fifth ed.) spanning 35 tumor types. We visualized all tumor types using deep features extracted from a state-of-the-art deep-learning model, pretrained on millions of diagnostic histopathology images from the Cancer Genome Atlas repository. Furthermore, we tested the concept of a digital "atlas" as a reference for search and matching with rare test cases. The patch similarity search within the World Health Organization breast taxonomy data reached >88% accuracy when validating through "majority vote" and >91% accuracy when validating using top n tumor types. These results show for the first time that complex relationships among common and rare breast lesions can be investigated using an indexed digital archive.

Health-related quality of life (HRQoL) after different axillary treatments in women with breast cancer: a 1-year longitudinal cohort study

PURPOSE

As life expectancy continues to rise, post-treatment health-related quality of life (HRQoL) of breast cancer patients becomes increasingly important. This study examined the one-year longitudinal relation between axillary treatments and physical, psychosocial, and sexual wellbeing and arm symptoms.

METHODS

Women diagnosed with breast cancer who received different axillary treatments being axilla preserving surgery (APS) with or without axillary radiotherapy or full axillary lymph node dissection (ALND) with or without axillary radiotherapy were included. HRQoL was assessed at baseline, 6- and 12-months postoperatively using the BREAST-Q and the European Organization for Research and Treatment of Cancer QoL Questionnaire Breast Cancer Module (EORTC QLQ-BR23). Mixed regression models were constructed to assess the impact of axillary treatment on HRQoL. HRQoL at baseline was compared to HRQoL at 6- and at 12-months postoperatively.

RESULTS

In total, 552 patients were included in the mixed regressions models. Except for ALND with axillary radiotherapy, no significant differences in physical and psychosocial wellbeing were found. Physical wellbeing decreased significantly between baseline and 6- and 12-months postoperatively (p < 0.001, p = 0.035) and psychosocial wellbeing decreased significantly between baseline and 12 months postoperatively (p = 0.028) for ALND with axillary radiotherapy compared to APS alone. Arm symptoms increased significantly between baseline and 6 months and between baseline and 12 months postoperatively for APS with radiotherapy (12.71, 13.73) and for ALND with radiotherapy (13.93, 16.14), with the lowest increase in arm symptoms for ALND without radiotherapy (6.85, 7.66), compared to APS alone (p < 0.05).

CONCLUSION

Physical and psychosocial wellbeing decreased significantly for ALND with radiotherapy compared to APS alone. Shared decision making and expectation management pre-treatment could be strengthened by discussing arm symptoms per axillary treatment with the patient.

Kv3.4 regulates cell migration and invasion through TGF-β-induced epithelial-mesenchymal transition in A549 cells

Epithelial-mesenchymal transition (EMT) is the process by which epithelial cells acquire mesenchymal characteristics. This process induces cell migration and invasion, which are closely related to cancer metastasis and malignancy. EMT consists of various intermediate states that express both epithelial and mesenchymal traits, called partial EMT. Recently, several studies have focused on the roles of voltage-gated potassium (Kv) channels associated with EMT in cancer cell migration and invasion. In this study, we demonstrate the relationship between Kv3.4 and EMT and confirm the effects of cell migration and invasion. With TGF-β treatment, EMT was induced and Kv3.4 was also increased in A549 cells, human lung carcinoma cells. The knockdown of Kv3.4 blocked the EMT progression reducing cell migration and invasion. However, the Kv3.4 overexpressed cells acquired mesenchymal characteristics and increased cell migration and invasion. The overexpression of Kv3.4 also has a synergistic effect with TGF-β in promoting cell migration. Therefore, we conclude that Kv3.4 regulates cancer migration and invasion through TGF-β-induced EMT and these results provide insights into the understanding of cancer metastasis.

Exploring Biomarkers in Breast Cancer: Hallmarks of Diagnosis, Treatment, and Follow-Up in Clinical Practice

Breast cancer is a prevalent malignancy in the present day, particularly affecting women as one of the most common forms of cancer. A significant portion of patients initially present with localized disease, for which curative treatments are pursued. Conversely, another substantial segment is diagnosed with metastatic disease, which has a worse prognosis. Recent years have witnessed a profound transformation in the prognosis for this latter group, primarily due to the discovery of various biomarkers and the emergence of targeted therapies. These biomarkers, encompassing serological, histological, and genetic indicators, have demonstrated their value across multiple aspects of breast cancer management. They play crucial roles in initial diagnosis, aiding in the detection of relapses during follow-up, guiding the application of targeted treatments, and offering valuable insights for prognostic stratification, especially for highly aggressive tumor types. Molecular markers have now become the keystone of metastatic breast cancer diagnosis, given the diverse array of chemotherapy options and treatment modalities available. These markers signify a transformative shift in the arsenal of therapeutic options against breast cancer. Their diagnostic precision enables the categorization of tumors with elevated risks of recurrence, increased aggressiveness, and heightened mortality. Furthermore, the existence of therapies tailored to target specific molecular anomalies triggers a cascade of changes in tumor behavior. Therefore, the primary objective of this article is to offer a comprehensive review of the clinical, diagnostic, prognostic, and therapeutic utility of the principal biomarkers currently in use, as well as of their clinical impact on metastatic breast cancer. In doing so, our goal is to contribute to a more profound comprehension of this complex disease and, ultimately, to enhance patient outcomes through more precise and effective treatment strategies.

Radiomics signatures for predicting the Ki-67 level and HER-2 status based on bone metastasis from primary breast cancer

This study explores the potential of radiomics to predict the proliferation marker protein Ki-67 levels and human epidermal growth factor receptor 2 (HER-2) status based on MRI images of patients with spinal metastasis from primary breast cancer. A total of 110 patients with pathologically confirmed spinal metastases from primary breast cancer were enrolled between Dec. 2017 and Dec. 2021. All patients underwent T1-weighted contrast-enhanced MRI scans. The PyRadiomics package was used to extract features from the MRI images based on the intraclass correlation coefficient and least absolute shrinkage and selection operator. The most predictive features were used to develop the radiomics signature. The Chi-Square test, Fisher's exact test, Student's t-test, and Mann-Whitney U test were used to evaluate the clinical and pathological characteristics between the high- and low-level Ki-67 groups and the HER-2 positive/negative groups. The radiomics models were compared using receiver operating characteristic curve analysis. The area under the receiver operating characteristic curve (AUC), sensitivity (SEN), and specificity (SPE) were generated as comparison metrics. From the spinal MRI scans, five and two features were identified as the most predictive for the Ki-67 level and HER-2 status, respectively. The developed radiomics signatures generated good prediction performance for the Ki-67 level in the training (AUC = 0.812, 95% CI: 0.710-0.914, SEN = 0.667, SPE = 0.846) and validation (AUC = 0.799, 95% CI: 0.652-0.947, SEN = 0.722, SPE = 0.833) cohorts. Good prediction performance for the HER-2 status was also achieved in the training (AUC = 0.796, 95% CI: 0.686-0.906, SEN = 0.720, SPE = 0.776) and validation (AUC = 0.705, 95% CI: 0.506-0.904, SEN = 0.733, SPE = 0.762) cohorts. The results of this study provide a better understanding of the potential clinical implications of spinal MRI-based radiomics on the prediction of Ki-67 levels and HER-2 status in breast cancer.

Anoikis-related mRNA-lncRNA and DNA methylation profiles for overall survival prediction in breast cancer patients

As a type of programmed cell death, anoikis resistance plays an essential role in tumor metastasis, allowing cancer cells to survive in the systemic circulation and as a key pathway for regulating critical biological processes. We conducted an exploratory analysis to improve risk stratification and optimize adjuvant treatment choices for patients with breast cancer, and identify multigene features in mRNA and lncRNA transcriptome profiles associated with anoikis. First, the variance selection method filters low information content genes in RNA sequence and then extracts the mRNA and lncRNA expression data base on annotation files. Then, the top ten key mRNAs are screened out through the PPI network. Pearson analysis has been employed to identify lncRNAs related to anoikis, and the prognosis-related lncRNAs are selected using Univariate Cox regression and machine learning. Finally, we identified a group of RNAs (including ten mRNAs and six lncRNAs) and integrated the expression data of 16 genes to construct a risk-scoring system for BRCA prognosis and drug sensitivity analysis. The risk score's validity has been evaluated with the ROC curve, Kaplan-Meier survival curve analysis and decision curve analysis (DCA). For the methylation data, we have obtained 169 anoikis-related prognostic methylation sites, integrated these sites with 16 RNA features and further used the deep learning model to evaluate and predict the survival risk of patients. The developed anoikis feature is demonstrated a consistency index (C-index) of 0.778, indicating its potential to predict the survival probability of breast cancer patients using deep learning methods.

Leader cells mechanically respond to aligned collagen architecture to direct collective migration

Leader cells direct collective migration through sensing cues in their microenvironment to determine migration direction. The mechanism by which leader cells sense the mechanical cue of organized matrix architecture culminating in a mechanical response is not well defined. In this study, we investigated the effect of organized collagen matrix fibers on leader cell mechanics and demonstrate that leader cells protrude along aligned fibers resulting in an elongated phenotype of the entire cluster. Further, leader cells show increased mechanical interactions with their nearby matrix compared to follower cells, as evidenced by increased traction forces, increased and larger focal adhesions, and increased expression of integrin-α2. Together our results demonstrate changes in mechanical matrix cues drives changes in leader cell mechanoresponse that is required for directional collective migration. Our findings provide new insights into two fundamental components of carcinogenesis, namely invasion and metastasis.

Integrating biocomputational techniques for Breast cancer drug discovery via the HER-2, BCRA, VEGF and ER protein targets

Computational modelling remains an indispensable technique in drug discovery. With myriad of high computing resources, and improved modelling algorithms, there has been a high-speed in the drug development cycle with promising success rate compared to the traditional route. For example, lapatinib; a well-known anticancer drug with clinical applications was discovered with computational drug design techniques. Similarly, molecular modelling has been applied to various disease areas ranging from cancer to neurodegenerative diseases. The techniques ranges from high-throughput virtual screening, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) to molecular dynamics simulation. This review focuses on the application of computational modelling tools in the identification of drug candidates for Breast cancer. First, we begin with a succinct overview of molecular modelling in the drug discovery process. Next, we take note of special efforts on the developments and applications of combining these techniques with particular emphasis on possible breast cancer therapeutic targets such as estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), breast cancer gene 1 (BRCA1), and breast cancer gene 2 (BRCA2). Finally, we discussed the search for covalent inhibitors against these receptors using computational techniques, advances, pitfalls, possible solutions, and future perspectives.

Establishing Single-Cell Clones from In Vitro-Cultured Circulating Tumor Cells

Cancer is a common health problem with more than 90% of deaths due to metastases. Circulating tumor cells (CTCs) contain precursors that can initiate metastases. However, CTCs are rare, heterogeneous, and difficult to expand in culture. We have previously created CTC-derived cell lines from stage IV breast cancer patients. These CTC lines were used to establish single-cell CTC clones using flow cytometry cell sorting.

Benzothiazole derivatives as p53-MDM2 inhibitors: in-silico design, ADMET predictions, molecular docking, MM-GBSA Assay, MD simulations studies

Breast cancer stands as the most prevalent malignancy among the female populace. One of the pivotal domains in the therapeutic landscape of breast cancer revolves around the precise targeting of the p53-MDM2 inhibitory pathway. The advent of p53-MDM2 inhibition in the context of developing treatments for breast cancer marks a significant stride. In the quest for enhancing the efficacy of p53-MDM2 inhibition against breast cancer, a new series of benzothiazole compounds (B1-B30) was designed through in-silico methodologies in the present work. Using Schrodinger Maestro, the compounds underwent molecular docking assessments against the p53-MDM2 target (PDB: 4OGT). Compared to reference compounds, B25 and B12 exhibited notably elevated glide scores. Extensive in-silico studies, including ADMET and toxicity evaluations, were performed to predict pharmacokinetics, drug likeness, and toxicity. All compounds adhered to Lipinski criteria, signifying favorable oral drug properties. The MM-GBSA analysis indicated consistent binding free energies. Molecular dynamics simulations for B25 over 200 ns assessed complex stability and interactions. In summary, these compounds exhibit potential for future cancer therapy medication development.Communicated by Ramaswamy H. Sarma.

Prediction of cell migration potential on human breast cancer cells treated with Albizia lebbeck ethanolic extract using extreme machine learning

Cancer is one of the major causes of death in the modern world, and the incidence varies considerably based on race, ethnicity, and region. Novel cancer treatments, such as surgery and immunotherapy, are ineffective and expensive. In this situation, ion channels responsible for cell migration have appeared to be the most promising targets for cancer treatment. This research presents findings on the organic compounds present in Albizia lebbeck ethanolic extracts (ALEE), as well as their impact on the anti-migratory, anti-proliferative and cytotoxic potentials on MDA-MB 231 and MCF-7 human breast cancer cell lines. In addition, artificial intelligence (AI) based models, multilayer perceptron (MLP), extreme gradient boosting (XGB), and extreme learning machine (ELM) were performed to predict in vitro cancer cell migration on both cell lines, based on our experimental data. The organic compounds composition of the ALEE was studied using gas chromatography-mass spectrometry (GC-MS) analysis. Cytotoxicity, anti-proliferations, and anti-migratory activity of the extract using Tryphan Blue, MTT, and Wound Heal assay, respectively. Among the various concentrations (2.5-200 μg/mL) of the ALEE that were used in our study, 2.5-10 μg/mL revealed anti-migratory potential with increased concentrations, and they did not show any effect on the proliferation of the cells (P < 0.05; n ≥ 3). Furthermore, the three data-driven models, Multi-layer perceptron (MLP), Extreme gradient boosting (XGB), and Extreme learning machine (ELM), predict the potential migration ability of the extract on the treated cells based on our experimental data. Overall, the concentrations of the plant extract that do not affect the proliferation of the type cells used demonstrated promising effects in reducing cell migration. XGB outperformed the MLP and ELM models and increased their performance efficiency by up to 3% and 1% for MCF and 1% and 2% for MDA-MB231, respectively, in the testing phase.

SREKA-targeted liposomes for highly metastatic breast cancer therapy

Chemotherapy is still a leading therapeutic approach in various tumor types that is often accompanied by a poor prognosis because of metastases. PEGylated liposomes with CREKA targeting moiety are well-known therapeutic agents, especially in highly metastatic experimental models. CREKA specifically targets tumor-associated ECM, which is present at the primary, as well as metastatic tumor sites. To better understand the function of the targeting moieties, we decided to design various liposome formulations with different amounts of targeting moiety attached to their DSPE-PEG molecules. Moreover, a new tumor-homing pentapeptide (SREKA) was designed, and a novel conjugation strategy between SREKA and DSPE-PEGs. First, the in vitro proliferation inhibition of drug-loaded liposomes and the cellular uptake of their cargo were investigated. Afterward, liposome stability in murine blood and drug accumulation in different tissues were measured. Furthermore, in vivo tumor growth, and metastasis inhibition potencies of the different liposome formulations were examined. According to our comparative studies, SREKA-liposomes have a uniform phenotype after formulation and have similar characteristics and tumor-homing capabilities to CREKA-liposomes. However, the exchange of the N-terminal cysteine to serine during conjugation results in a higher production yield and better stability upon conjugation to DSPE-PEGs. We also showed that SREKA-liposomes have significant inhibition on primary tumor growth and metastasis incidence; furthermore, increase the survival rate of tumor-bearing mice. Besides, we provide evidence that the amount of targeting moiety attached to DSPE-PEGs is largely responsible for the stability of liposomes, therefore it plays an important role in toxicity and targeting.

The activation of SIRT1 by resveratrol reduces breast cancer metastasis to lung through inhibiting neutrophil extracellular traps

Neutrophil extracellular traps (NETs) play a crucial role in breast cancer metastasis. However, the therapeutic target of NETs in breast cancer metastasis is still unknown. Using a natural metabolite library and single-cell sequencing data analysis, we identified resveratrol (RES), a polyphenolic natural phytoalexin, and agonist of silent information regulator-1 (SIRT1) that suppressed NETs formation after cathepsin C (CTSC) treatment. In vivo, RES significantly hindered breast cancer metastasis in a murine orthotopic 4T1 breast cancer model. Serum levels of myeloperoxidase-DNA and neutrophil elastase-DNA in mouse breast cancer model were significantly lower after RES treatment. Correspondingly, the tumour infiltrated CD8+T cells in the lungs increased after the treatment. Mechanistically, RES targets SIRT1 in neutrophils and significantly inhibits the citrullination of histones H3, which is essential for chromatin decondensation and NETs formation. Furthermore, we identified that the NETs were suppressed by RES in bone marrow neutrophils after CTSC treatment, while specific deficiency of SIRT1 in neutrophils promoted NETs formation and breast cancer to lung metastasis. Thus, our results revealed that RES could be potentially identified as a viable therapeutic drug to prevent neutrophil cell death and breast cancer metastasis.

Downregulation of complement factor H attenuates the stemness of MDA‑MB‑231 breast cancer cells via modulation of the ERK and p38 signaling pathways

The complement system is a powerful innate immune system deployed in the immediate response to pathogens and cancer cells. Complement factor H (CFH), one of the regulators involved in the complement cascade, can interrupt the death of target cells. Certain types of cancer, such as breast cancer, can adopt an aggressive phenotype, such as breast cancer stem cells (BCSCs), through enhancement of the defense system against complement attack by amplifying various complement regulators. However, little is known about the association between CFH and BCSCs. In the present study, the roles of CFH in the CSC characteristics and radioresistance of MDA-MB-231 human breast cancer cells were investigated. CFH knockdown in MDA-MB-231 cells decreased the viability of the cells upon complement cascade activation. Notably, CFH knockdown also decreased cell survival and suppressed mammosphere formation, cell migration and cell invasion by attenuating radioresistance. Additionally, CFH knockdown further enhanced irradiation-induced apoptosis through G2/M cell cycle arrest. It was also discovered that CFH knockdown attenuated the aggressive phenotypes of cancer cells by regulating CSC-associated gene expression. Finally, by microarray analysis, it was found that the expression of erythrocyte membrane protein band 4.1-like 3 (EPB41L3) was markedly increased following CFH knockdown. EPB41L3 inhibited ERK and activated the p38 MAPK signaling pathway. Taken together, these results indicated that CFH knockdown attenuated CSC properties and radioresistance in human breast cancer cells via controlling MAPK signaling and through upregulation of the tumor suppressor, EPB41L3.

3D bioprinted breast tumor-stroma models for pre-clinical drug testing

The use of three-dimensional (3D) bioprinting has been proposed for the reproducible production of 3D disease models that can be used for high-throughput drug testing and personalized medicine. However, most such models insufficiently reproduce the features and environment of real tumors. We report the development of bioprinted in vitro 3D tumor models for breast cancer, which physically and biochemically mimic important aspects of the native tumor microenvironment, designed to study therapeutic efficacy. By combining a mix of breast decellularized extracellular matrix and methacrylated hyaluronic acid with tumor-derived cells and non-cancerous stromal cells of biological relevance to breast cancer, we show that biological signaling pathways involved in tumor progression can be replicated in a carefully designed tumor-stroma environment. Finally, we demonstrate proof-of-concept application of these models as a reproducible platform for investigating therapeutic responses to commonly used chemotherapeutic agents.