Estrogen receptor-positive breast cancer survival prediction and analysis of resistance-related genes introduction

Prevention of liver metastasis via the pharmacological suppression of AMIGO2 expression in tumor cells

AMIGO2 adheres to liver endothelium and induces liver metastasis. We revealed that genetically altering AMIGO2 expression in tumor cells affects their liver metastatic potential, depending on the AMIGO2 expression level. The aim of this study was to prevent liver metastasis by pharmacologically suppressing AMIGO2 expression. For screening, we used the mouse LV12 cells because of their affinity to adhere to liver endothelium and metastasize the liver owing to elevated AMIGO2 expression. Of the 285 compounds tested, 17 reduced AMIGO2 mRNA expression. We subsequently screened for compounds that inhibited tumor cell adhesion to liver endothelium and identified five compounds that inhibit three signaling pathways (MEK, JAK, and JNK). Treatment with these compounds inhibited liver metastasis of LV12 cells. Next, we used clinically available signal inhibitors (MEK inhibitor trametinib, JAK inhibitor ruxolitinib, and JNK inhibitor SP600125), and found that ruxolitinib inhibits AMIGO2 expression more stably. Furthermore, ruxolitinib inhibited the adhesion of LV12 cells to liver endothelium and suppressed liver metastasis. Using the MKN45 gastric cancer cells, we confirmed that ruxolitinib could prevent liver metastasis of human cancer cells. These results demonstrate that pharmacological inhibition of AMIGO2 expression in tumor cells is a promising novel strategy to prevent and control liver metastasis.

Role of AMIGO2 in cancer progression: Novel insights (Review)

Adhesion molecule with IgG-like domain 2 (AMIGO2) is a novel scaffold protein initially identified in cerebellar granule neurons, and inhibits apoptosis of neurons. It is also widely expressed in various malignant tumors, including gastric cancer, colorectal carcinoma, ovarian cancer, prostate cancer and melanoma. During the past decades, it has been revealed that AMIGO2 can act as an oncogene, participating in tumor occurrence and development, for example by inhibiting apoptosis, accelerating cell proliferation, migration and adhesion, and promoting tumor metastasis and drug resistance. The present review discusses the recent advancements regarding AMIGO2 in the field of cancer, emphasizing its related molecular mechanisms to identify novel therapeutic strategies targeting AMIGO2 for cancer treatment in the future.

BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion

Breast cancer is a significant health concern affecting millions of women worldwide. Accurate survival risk stratification plays a crucial role in guiding personalised treatment decisions and improving patient outcomes. Here we present BioFusionNet, a deep learning framework that fuses image-derived features with genetic and clinical data to obtain a holistic profile and achieve survival risk stratification of ER+ breast cancer patients. We employ multiple self-supervised feature extractors (DINO and MoCoV3) pretrained on histopathological patches to capture detailed image features. These features are then fused by a variational autoencoder and fed to a self-attention network generating patient-level features. A co-dual-cross-attention mechanism combines the histopathological features with genetic data, enabling the model to capture the interplay between them. Additionally, clinical data is incorporated using a feed-forward network, further enhancing predictive performance and achieving comprehensive multimodal feature integration. Furthermore, we introduce a weighted Cox loss function, specifically designed to handle imbalanced survival data, which is a common challenge. Our model achieves a mean concordance index of 0.77 and a time-dependent area under the curve of 0.84, outperforming state-of-the-art methods. It predicts risk (high versus low) with prognostic significance for overall survival in univariate analysis (HR=2.99, 95% CI: 1.88-4.78, p 0.005), and maintains independent significance in multivariate analysis incorporating standard clinicopathological variables (HR=2.91, 95% CI: 1.80-4.68, p 0.005).

Precision unveiled: Synergistic genomic landscapes in breast cancer-Integrating single-cell analysis and decoding drug toxicity for elite prognostication and tailored therapeutics

BACKGROUND

Globally, breast cancer, with diverse subtypes and prognoses, necessitates tailored therapies for enhanced survival rates. A key focus is glutamine metabolism, governed by select genes. This study explored genes associated with T cells and linked them to glutamine metabolism to construct a prognostic staging index for breast cancer patients for more precise medical treatment.

METHODS

Two frameworks, T-cell related genes (TRG) and glutamine metabolism (GM), stratified breast cancer patients. TRG analysis identified key genes via hdWGCNA and machine learning. T-cell communication and spatial transcriptomics emphasized TRG's clinical value. GM was defined using Cox analyses and the Lasso algorithm. Scores categorized patients as TRG_high+GM_high (HH), TRG_high+GM_low (HL), TRG_low+GM_high (LH), or TRG_low+GM_low (LL). Similarities between HL and LH birthed a "Mixed" class and the TRG_GM classifier. This classifier illuminated gene variations, immune profiles, mutations, and drug responses.

RESULTS

Utilizing a composite of two distinct criteria, we devised a typification index termed TRG_GM classifier, which exhibited robust prognostic potential for breast cancer patients. Our analysis elucidated distinct immunological attributes across the classifiers. Moreover, by scrutinizing the genetic variations across groups, we illuminated their unique genetic profiles. Insights into drug sensitivity further underscored avenues for tailored therapeutic interventions.

CONCLUSION

Utilizing TRG and GM, a robust TRG_GM classifier was developed, integrating clinical indicators to create an accurate predictive diagnostic map. Analysis of enrichment disparities, immune responses, and mutation patterns across different subtypes yields crucial subtype-specific characteristics essential for prognostic assessment, clinical decision-making, and personalized therapies. Further exploration is warranted into multiple fusions between metrics to uncover prognostic presentations across various dimensions.

The biology of SCUBE

The SCUBE [Signal peptide-Complement C1r/C1s, Uegf, Bmp1 (CUB)-Epithelial growth factor domain-containing protein] family consists of three proteins in vertebrates, SCUBE1, 2 and 3, which are highly conserved in zebrafish, mice and humans. Each SCUBE gene encodes a polypeptide of approximately 1000 amino acids that is organized into five modular domains: (1) an N-terminal signal peptide sequence, (2) nine tandem epidermal growth factor (EGF)-like repeats, (3) a large spacer region, (4) three cysteine-rich (CR) motifs, and (5) a CUB domain at the C-terminus. Murine Scube genes are expressed individually or in combination during the development of various tissues, including those in the central nervous system and the axial skeleton. The cDNAs of human SCUBE orthologs were originally cloned from vascular endothelial cells, but SCUBE expression has also been found in platelets, mammary ductal epithelium and osteoblasts. Both soluble and membrane-associated SCUBEs have been shown to play important roles in physiology and pathology. For instance, upregulation of SCUBEs has been reported in acute myeloid leukemia, breast cancer and lung cancer. In addition, soluble SCUBE1 is released from activated platelets and can be used as a clinical biomarker for acute coronary syndrome and ischemic stroke. Soluble SCUBE2 enhances distal signaling by facilitating the secretion of dual-lipidated hedgehog from nearby ligand-producing cells in a paracrine manner. Interestingly, the spacer regions and CR motifs can increase or enable SCUBE binding to cell surfaces via electrostatic or glycan-lectin interactions. As such, membrane-associated SCUBEs can function as coreceptors that enhance the signaling activity of various serine/threonine kinase or tyrosine kinase receptors. For example, membrane-associated SCUBE3 functions as a coreceptor that promotes signaling in bone morphogenesis. In humans, SCUBE3 mutations are linked to abnormalities in growth and differentiation of both bones and teeth. In addition to studies on human SCUBE function, experimental results from genetically modified mouse models have yielded important insights in the field of systems biology. In this review, we highlight novel molecular discoveries and critical directions for future research on SCUBE proteins in the context of cancer, skeletal disease and cardiovascular disease.

The role of Evi/Wntless in exporting Wnt proteins

Intercellular communication by Wnt proteins governs many essential processes during development, tissue homeostasis and disease in all metazoans. Many context-dependent effects are initiated in the Wnt-producing cells and depend on the export of lipidated Wnt proteins. Although much focus has been on understanding intracellular Wnt signal transduction, the cellular machinery responsible for Wnt secretion became better understood only recently. After lipid modification by the acyl-transferase Porcupine, Wnt proteins bind their dedicated cargo protein Evi/Wntless for transport and secretion. Evi/Wntless and Porcupine are conserved transmembrane proteins, and their 3D structures were recently determined. In this Review, we summarise studies and structural data highlighting how Wnts are transported from the ER to the plasma membrane, and the role of SNX3-retromer during the recycling of its cargo receptor Evi/Wntless. We also describe the regulation of Wnt export through a post-translational mechanism and review the importance of Wnt secretion for organ development and cancer, and as a future biomarker.

SCUBE2 as a Marker of Resistance to Taxane-based Neoadjuvant Chemotherapy and a Potential Therapeutic Target in Breast Cancer

Objective

Taxane-based neoadjuvant chemotherapy is the most common neoadjuvant approach in breast cancer, especially in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative subtypes. However, chemoresistance is a problem in many patients, and success rates are low in estrogen receptor (ER)-positive breast cancer. The aim of this study was to identify predictive markers for resistance to taxane-based therapy, which may have a potential as therapeutic targets in breast cancer.

Materials and Methods

Three comprehensive breast cancer Gene Expression Omnibus datasets were analyzed to identify differentially expressed genes (DEGs) in breast cancer patients resistant to taxane-based neoadjuvant chemotherapy. Functional annotation clustering and enrichment analysis were performed on the DEGs list. A protein-protein interaction network was established with the upregulated genes. The predictive value and the differential expression of the central genes were validated in the extensive ROC Plotter database.

Results

Seventeen upregulated genes were found which were associated with resistance to taxane-based neoadjuvant therapy and high connectivity in the network analysis. ESR1, CCND1, and SCUBE2 emerged as the top three key genes associated with resistance. SCUBE2 displayed a high predictive power comparable to ESR1, and better than CCND1, the two commonly accepted markers. The predictive ability of SCUBE2 was higher in ER-positive and HER2-positive breast cancers.

Conclusion

These results suggest that SCUBE2 may be used as a predictive marker to guide decisions on neoadjuvant therapy. Emerging evidence about the role of SCUBE2 as a coreceptor involved in tumor progression and angiogenesis also suggests SCUBE2 as a potential therapeutic target. These points should be investigated in further studies.

The Multifaceted Role of Signal Peptide-CUB-EGF Domain-Containing Protein (SCUBE) in Cancer

Signal peptide, CUB, and EGF-like domain-containing proteins (SCUBE) are secretory cell surface glycoproteins that play key roles in the developmental process. SCUBE proteins participate in the progression of several diseases, including cancer, and are recognized for their oncogenic and tumor suppressor functions depending on the cellular context. SCUBE proteins promote cancer cell proliferation, angiogenesis, invasion, or metastasis, stemness or self-renewal, and drug resistance. The association of SCUBE with other proteins alters the expression of signaling pathways, including Hedgehog, Notch, TGF-β/Smad2/3, and β-catenin. Further, SCUBE proteins function as potential prognostic and diagnostic biomarkers for breast cancer, renal cell carcinoma, endometrial carcinoma, and nasopharyngeal carcinoma. This review presents key features of SCUBE family members, and their structure and functions, and highlights their contribution in the development and progression of cancer. A comprehensive understanding of the role of SCUBE family members offers novel strategies for cancer therapy.

Comprehensive Transcriptomic and Proteomic Analyses Identify a Candidate Gene Set in Cross-Resistance for Endocrine Therapy in Breast Cancer

Endocrine therapy (ET) of selective estrogen receptor modulators (SERMs), selective estrogen receptor downregulators (SERDs), and aromatase inhibitors (AIs) has been used as the gold standard treatment for hormone-receptor-positive (HR+) breast cancer. Despite its clinical benefits, approximately 30% of patients develop ET resistance, which remains a major clinical challenge in patients with HR+ breast cancer. The mechanisms of ET resistance mainly focus on mutations in the ER and related pathways; however, other targets still exist from ligand-independent ER reactivation. Moreover, mutations in the ER that confer resistance to SERMs or AIs seldom appear in SERDs. To date, little research has been conducted to identify a critical target that appears in both SERMs/SERDs and AIs. In this study, we conducted comprehensive transcriptomic and proteomic analyses from two cohorts of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) to identify the critical targets for both SERMs/SERDs and AIs of ET resistance. From a treatment response cohort with treatment response for the initial ET regimen and an endocrine therapy cohort with survival outcomes, we identified candidate gene sets that appeared in both SERMs/SERDs and AIs of ET resistance. The candidate gene sets successfully differentiated progress/resistant groups (PD) from complete response groups (CR) and were significantly correlated with survival outcomes in both cohorts. In summary, this study provides valuable clinical implications for the critical roles played by candidate gene sets in the diagnosis, mechanism, and therapeutic strategy for both SERMs/SERDs and AIs of ET resistance for the future.