Transcriptome profiles of stem-like cells from primary breast cancers allow identification of ITGA7 as a predictive marker of chemotherapy response

Promoter hypermethylation-induced downregulation of ITGA7 promotes colorectal cancer proliferation and migration by activating the PI3K/AKT/NF-κB pathway

We previously reported that integrin alpha 7 (ITGA7) was downregulated in colorectal cancer (CRC) tissues and CRC cell lines and that the lower expression of ITGA7 in CRC tissues was correlated with distant metastasis, suggesting that ITGA7 may function as a suppressor in CRC. The present research was conducted to further investigate the role and mechanisms of ITGA7 in CRC progression. First, bisulfite modification and genomic sequencing (BSP) results showed that the methylation rate of ITGA7 promoter was higher in 10 CRC tissues than in the matched normal tissues. Additionally, 5-Aza-CdR treatment increased ITGA7 expression in CRC cells. Gain-of-function assays revealed the inhibitory role of ITGA7 in CRC cell proliferation and migration. Mechanistically, RNA sequencing, RT-qPCR, and cytoplasm and nuclear separation and rescue assays indicated that knockdown of ITGA7 activated the transcription of MMP9, SETD7, and ADAM15 by enhancing the nuclear translocation of NF-κB. Moreover, CoIP and Western blot suggested a mechanistic model in which ITGA7 binds to CKAP4 to block the interaction of CKAP4 and PI3K p85α and thereby suppress the PI3K/AKT/NF-κB pathway. Accordingly, the current study suggests that ITGA7 functions as a suppressor in CRC progression and that its expression is controlled by promoter methylation.

Transcriptomics Studies Reveal Functions of Transglutaminase 2 in Breast Cancer Cells Using Membrane Permeable and Impermeable Inhibitors

Transglutaminase 2 (TG2) performs many functions both under physiological and pathological conditions. In cancer, its expression is associated with aggressiveness, propensity to epithelial-mesenchymal transition, and metastasis. Since TG2 performs key functions both outside and inside the cell, using inhibitors with different membrane permeability we analyzed the changes in the transcriptome induced in two triple-negative cell lines (MDA-MB-436 and MDA-MB-231) with aggressive features. By characterizing pathways and gene networks, we were able to define the effects of TG2 inhibitors (AA9, membrane-permeable, and NCEG2, impermeable) in relation to the roles of the enzyme in the intra- and extracellular space within the context of breast cancer. The deregulated genes revealed p53 and integrin signaling to be the common pathways with some genes showing opposite changes in expression. In MDA-MB-436, AA9 induced apoptosis, modulated cadherin, Wnt, gastrin and cholecystokinin receptors (CCKR) mediated signaling, with RHOB and GNG2 playing significant roles, and affected the Warburg effect by decreasing glycolytic enzymes. In MDA-MB-231 cells, AA9 strongly impacted HIF-mediated hypoxia, including AKT and mTOR pathway. These effects suggest an anti-tumor activity by blocking intracellular TG2 functions. Conversely, the use of NCEG2 stimulated the expression of ATP synthase and proteins involved in DNA replication, indicating a potential promotion of cell proliferation through inhibition of extracellular TG2. To effectively utilize these molecules as an anti-tumor strategy, an appropriate delivery system should be evaluated to target specific functions and avoid adverse effects. Additionally, considering combinations with other pathway modulators is crucial.

ITGA7 loss drives the differentiation of adipose-derived mesenchymal stem cells to cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) represent a major cellular component of the tumor (pre-)metastatic niche and play an essential role in omental dissemination of ovarian cancer. The omentum is rich in adipose, and adipose-derived mesenchymal stem cells (ADSCs) have been identified as a source of CAFs. However, the molecular events driving the phenotype shift of ADSCs remain largely unexplored. In this research, we focus on integrins, transmembrane receptors that have been widely involved in cellular plasticity. We found that integrin α7 (ITGA7) was the only member of the integrin family that positively correlated with both overall survival and progression-free survival in ovarian cancer through GEPIA2. The immunohistochemistry signal of ITGA7 was apparent in the tumor stroma, and a lower omental ITGA7 level was associated with metastasis. Primary ADSCs were isolated from the omentum of patients with ovarian cancer and identified by cellular morphology, biomarkers, and multilineage differentiation. The conditional medium of ovarian cancer cells induced ITGA7 expression decrease and phenotypic changes in ADSCs. Downregulation of ITGA7 in primary omental ADSCs led to decrease in stemness properties and emerge of characteristic morphology and biomarkers of CAFs. Moreover, the conditioned medium of ADSCs with ITGA7 depletion exhibited enhanced abilities to improve the migration and invasion of ovarian cancer cells in vitro. Overall, these findings indicate that loss of ITGA7 may induce the differentiation of ADSCs to CAFs that contribute to a tumor-supportive niche.

Machine learning and bioinformatic analyses link the cell surface receptor transcript levels to the drug response of breast cancer cells and drug off-target effects

Breast cancer responds variably to anticancer therapies, often leading to significant off-target effects. This study proposes that the variability in tumour responses and drug-induced adverse events is linked to the transcriptional profiles of cell surface receptors (CSRs) in breast tumours and normal tissues. We analysed multiple datasets to compare CSR expression in breast tumours with that in non-cancerous human tissues. Our findings correlate the drug responses of breast cancer cell lines with the expression levels of their targeted CSRs. Notably, we identified distinct differences in CSR expression between primary breast tumour subtypes and corresponding cell lines, which may influence drug response predictions. Additionally, we used clinical trial data to uncover associations between CSR gene expression in healthy tissues and the incidence of adverse drug reactions. This integrative approach facilitates the selection of optimal CSR targets for therapy, leveraging cell line dose-responses, CSR expression in normal tissues, and patient adverse event profiles.

Bioinformatics analysis of immune cell infiltration patterns and potential diagnostic markers in atherosclerosis

This study aimed to investigate efficient diagnostic markers and molecular mechanisms of atherosclerosis and to analyze the role of immune infiltration through bioinformatics analysis. Expression profile datasets (GSE28829 and GSE43292) of patients with atherosclerosis and healthy controls were downloaded from the GEO database. Glutamine (GLN) metabolism-associated genes were obtained from the Molecular Signatures Database (MSigDB). The limma package in R was used to identify differentially expressed genes (DEGs). Significant modules were filtered using Weighted Gene Co-expression Network Analysis (WGCNA). MSigDB sets were subjected to Gene Set Enrichment Analysis and Gene Set Variation Analysis. The biological functions of DEGs were examined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. STRING and Cytoscape software were used to identify hub genes and functional modules through protein-protein interaction (PPI) network analysis. The xCell software was adopted to assess the composition patterns of immune and stromal cells. Correlation analyses were performed for key genes and immune cell subtypes. We identified 308 DEGs and GLN-associated genes. Functional enrichment analysis showed that these genes were strongly enriched in muscle contract, muscle tissue development, cutile fiber, mycobacterial, and actin binding. Enriched KEGG pathways comprised dilated cardiomyopathy, hypertrophic cardiomyopathy, and the cAMP signaling pathway. In the PPI network analysis, 27 genes were identified as hub genes. The area under the curve (AUC) values of 27 biomarkers were relatively high, indicating high diagnostic values. The atherosclerosis group exhibited a markedly higher degree of infiltration than the control group. This study identified 27 GLN-associated genes as potential biomarkers for the diagnosis of atherosclerosis. It provides a new perspective on immune responses that facilitates exploration of the molecular mechanisms of atherosclerosis.

Cancer invasion and metastasis: Insights from murine pubertal mammary gland morphogenesis

Cancer invasion and metastasis accounts for the majority of cancer related mortality. A better understanding of the players that drive the aberrant invasion and migration of tumors cells will provide critical targets to inhibit metastasis. Postnatal pubertal mammary gland morphogenesis is characterized by highly proliferative, invasive, and migratory normal epithelial cells. Identifying the molecular regulators of pubertal gland development is a promising strategy since tumorigenesis and metastasis is postulated to be a consequence of aberrant reactivation of developmental stages. In this review, we summarize the pubertal morphogenesis regulators that are involved in cancer metastasis and revisit pubertal mammary gland transcriptome profiling to uncover both known and unknown metastasis genes. Our updated list of pubertal morphogenesis regulators shows that most are implicated in invasion and metastasis. This review highlights molecular linkages between development and metastasis and provides a guide for exploring novel metastatic drivers.

The ALDH2, IGSF9, and PRDM16 Proteins as Predictive Biomarkers for Prognosis in Breast Cancer

INTRODUCTION

ALDH2, IGSF9, and PRDM16 play crucial roles in regulating diverse cellular pathophysiologic functions. The current study was to evaluate the effect of the 3 proteins on clinicopathologic features and prognosis of patients with breast cancer.

MATERIALS AND METHODS

The formalin-fixed and paraffin-embedded tissue specimens were collected from breast cancer patients by immunohistochemistry (IHC) were analyzed.

RESULTS

Of the 216 patients enrolled, ALDH2 high expression was significantly correlated with the age (p = .040), larger tumor size (p = .001), LVI (p < .001), LNM (p < .001), advanced TNM staging (p < .001), PR (p = .027), HER2 status (p = .002), and molecular subtype (p = .003). IGSF9 low expression was significantly correlated with the LV1 (p = .024), LNM (p = .024), advanced TNM staging (p = .001). The low expression of PRDM16 was significantly correlated with age (p = .023), and LNM (p = .014). The A⁺I^-P^- expression (13.4%) were markedly correlated with lymphatic vessel invasion (LVI) (p < .001), lymph node metastasis (LNM) (p < .001), advanced TNM staging (p < .001). Furthermore, patients with A⁺I^-P^- expression had significantly advanced-stage breast cancer [stage III (72.4%) vs. (23.0%)]. Univariate and multivariate analysis identified variables (ie, larger tumor size, lymph node involvement, and A⁺I^-P^- expression) as independent prognostic factors for survival.

CONCLUSION

Our results reveal ALDH2 high expression, IGSF9 and PRDM16 low expression, A⁺I^-P^- expression was associated with advanced clinicopathological characteristics, and shorter OS and DFS in breast cancer patients. The 3 proteins may be potential prognosis markers and therapeutic targets for breast cancer patients.

Clinical applications of deep learning in breast MRI

Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in artificial intelligence (AI). It can automatically learn from raw data without manual feature selection. DL models have led to remarkable advances in data extraction and analysis for medical imaging. Magnetic resonance imaging (MRI) has proven useful in delineating the characteristics and extent of breast lesions and tumors. This review summarizes the current state-of-the-art applications of DL models in breast MRI. Many recent DL models were examined in this field, along with several advanced learning approaches and methods for data normalization and breast and lesion segmentation. For clinical applications, DL-based breast MRI models were proven useful in five aspects: diagnosis of breast cancer, classification of molecular types, classification of histopathological types, prediction of neoadjuvant chemotherapy response, and prediction of lymph node metastasis. For subsequent studies, further improvement in data acquisition and preprocessing is necessary, additional DL techniques in breast MRI should be investigated, and wider clinical applications need to be explored.

pH-Driven Intracellular Nano-to-Molecular Disassembly of Heterometallic [Au2L2]{Re6Q8} Colloids (L = PNNP Ligand; Q = S2- or Se2-)

The present work introduces a simple, electrostatically driven approach to engineered nanomaterial built from the highly cytotoxic [Au₂L₂]²⁺ complex (Au₂, L = 1,5-bis(p-tolyl)-3,7-bis(pyridine-2-yl)-1,5-diaza-3,7-diphosphacyclooctane (PNNP) ligand) and the pH-sensitive red-emitting [{Re₆Q₈}(OH)₆]^4- (Re₆-Q, Q = S^2- or Se^2-) cluster units. The protonation/deprotonation of the Re₆-Q unit is a prerequisite for the pH-triggered assembly of Au₂ and Re₆-Q into Au₂Re₆-Q colloids, exhibiting disassembly in acidic (pH = 4.5) conditions modeling a lysosomal environment. The counter-ion effect of polyethylenimine causes the release of Re₆-Q units from the colloids, while the binding with lysozyme restricts their protonation in acidified conditions. The enhanced luminescence response of Re₆-S on the disassembly of Au₂Re₆-S colloids in the lysosomal environment allows us to determine their high lysosomal localization extent through the colocalization assay, while the low luminescence of Re₆-Se units in the same conditions allows us to reveal the rapture of the lysosomal membrane through the use of the Acridine Orange assay. The lysosomal pathway of the colloids, followed by their endo/lysosomal escape, correlates with their cytotoxicity being on the same level as that of Au₂ complexes, but the contribution of the apoptotic pathway differentiates the cytotoxic effect of the colloids from that of the Au₂ complex arisen from the necrotic processes.

Recent Advances in Nanoparticle-Based Co-Delivery Systems for Cancer Therapy

Cancer therapies have advanced tremendously throughout the last decade, yet multiple factors still hinder the success of the different cancer therapeutics. The traditional therapeutic approach has been proven insufficient and lacking in the suppression of tumor growth. The simultaneous delivery of multiple small-molecule chemotherapeutic drugs and genes improves the effectiveness of each treatment, thus optimizing efficacy and improving synergistic effects. Nanomedicines integrating inorganic, lipid, and polymeric-based nanoparticles have been designed to regulate the spatiotemporal release of the encapsulated drugs. Multidrug-loaded nanocarriers are a potential strategy to fight cancer and the incorporation of co-delivery systems as a feasible treatment method has projected synergistic benefits and limited undesirable effects. Moreover, the development of co-delivery systems for maximum therapeutic impact necessitates better knowledge of the appropriate therapeutic agent ratio as well as the inherent heterogeneity of the cancer cells. Co-delivery systems can simplify clinical processes and increase patient quality of life, even though such systems are more difficult to prepare than single drug delivery systems. This review highlights the progress attained in the development and design of nano carrier-based co-delivery systems and discusses the limitations, challenges, and future perspectives in the design and fabrication of co-delivery systems.