Phosphatase and tensin homolog (PTEN) is one of the highly susceptible genes to breast cancer (BC); however, the role of PTEN-related RNAs in BC remains poorly understood. Understanding the effect of PTEN-related RNAs and their mechanisms may be helpful to clinicians. We screened the differentially expressed RNAs (deRNAs) related to PTEN and established the competitive endogenous RNA (ceRNA) network by integrating several databases. After that, the RNA model, prolactin receptor (PRLR)/calcium voltage-gated channel auxiliary subunit alpha2delta 1 (CACNA2D1), was obtained by KM survival analysis and logistic regression analysis. Finally, mutation, methylation, functional enrichment, and immune correlation were analyzed to explore the roles of these RNAs. Our results showed that PRLR might be harmful to BC, while CACNA2D1 might be beneficial to BC. Furthermore, the abnormal expression of PRLR in BC might result from mutation and hypomethylation, while the aberrant expression of CACNA2D1 might be ascribed to methylation. Mechanistically, PRLR might affect the prognosis of BC by inhibiting the expression of immune checkpoints, while CACNA2D1 might improve the prognosis of BC by increasing the immune cells infiltrating into BC and up-regulating the expression of immune checkpoints. The abnormal expression of PRLR and CACNA2D1 in BC is closely related to the prognosis of BC, and they may serve as targets for the treatment of BC.

Osteosarcoma (OS) is the most common primary bone malignancy with variable molecular biology and prognosis. However, our understanding of the association between cell types and OS progression remains poor. We generated a human OS cell atlas by integrating over 110,000 single cells from 17 samples. Multiple machine learning algorithms were applied to develop tumor purity prediction models based on transcriptomic profile of OS. The Scissor algorithm and gene enrichment analyses were conducted to delve into cell-intrinsic molecular characteristics linked to OS prognosis. Moreover, the study investigated the impact of ATF6α in OS aggressiveness through genetic and pharmacological loss of function analyses. Lastly, the CellChat algorithm was employed to investigate cell-cell communications. Utilizing the high-quality human OS cell atlas, we identified tumor purity as a prognostic indicator and developed a robust tumor purity prediction model. We respectively delineated cancer cell- and immune cell-intrinsic molecular characteristics associated with OS prognosis at single-cell resolution. Interestingly, tumor cells with activated unfolded protein response (UPR) pathway were significantly associated with disease aggressiveness. Notably, ATF6α emerged as the top-activated transcription factor for this tumor subcluster. Subsequently, we confirmed that ATF6α was markedly associated with OS progression, while both genetic and pharmacological inhibition of ATF6α impaired the survival of HOS cells. Lastly, we depicted the landscape of signal crosstalk between the UPR-related subcluster and other cell types within the tumor microenvironment. In summary, our work provides novel insights into the molecular biology of OS, and offers valuable resource for OS biomarker discovery and treatment strategy development.

Breast cancer has garnered global attention due to its high incidence worldwide, and even more noteworthy is that approximately 90% deaths due to breast cancer are attributed to cancer metastasis. Therefore, the early diagnosis of breast cancer metastasis holds significant importance for reducing mortality outcomes. Biosensors play a crucial role in the early detection of metastatic breast cancer due to their advantages, such as ease of use, portability, and real-time analysis capabilities. This review primarily described various types of sensors for detecting breast cancer metastasis based on biomarkers and cell characteristics, including electrochemical, optical, and microfluidic chips. We offered detailed descriptions of the performance of these various biosensors and made comparisons between them. Furthermore, we described the pathology of breast cancer and summarized commonly used biomarkers for metastatic breast cancer. Finally, we discussed the advantages of current-stage biosensors and the challenges that need to be addressed, as well as prospects for their future development.

Background: Recently, low-density lipoprotein receptor (LDLR)-related protein 6 (LRP6) has been the focus of molecular targeted therapy for breast cancer; however, its role in breast cancer is still controversial. The purpose of this study was to investigate the effect of LRP6 overexpression on the prognosis of breast cancer. Methods: We used immunohistochemistry to detect the expression of LRP6 via tissue microarrays in breast cancer samples, Chi-square test analyze the relationship between LRP6 expression and clinicopathological features of breast cancer, the Kaplan-Meier method to perform survival analysis, and the Cox proportional hazards regression model to explore the potential risk factors of breast cancer. The role of LRP6 in the proliferation, invasion, and metastasis of breast cancer was studied by colony formation, Transwell migration and invasion assay and scratch assay. The tumor-bearing model of LRP6 knockdown was established using MCF-7 cells, and corresponding negative control was set up to observe the growth rate of the two models. Results: High expression of LRP6 was observed in 89 out of 150 (59.3%) breast cancer cases, as detected by microarray of breast cancer tissue. Chi-square tests showed no significant correlation between LRP6 expression and tumor size, lymph node staging, or mitosis. Survival analysis showed that the overall survival rate of tumor patients with high LRP6 expression was significantly lower than that of patients with low LRP6 expression. Univariate and multivariate regression analyses revealed that LRP6 was an independent risk factor for breast cancer and was negatively correlated with the prognosis of breast cancer. Compared with the control group, small interference RNA (si-RNA) knockdown of LRP6 significantly reduced the clonogenic rate as well as the migration and invasion abilities of MCF-7 cells. In the scratch experiment, the wound healing ability of the LRP6 knockdown was significantly weaker than that of the control group. There were significant differences in tumor growth weight and volume between lentivirus transfected LRP6 knockdown MCF-7 cell line and control MCF-7 cell line in nude mice. Conclusions: LRP6 could be a useful biomarker of poor prognosis of breast cancer, as it plays an important role in tumor growth, migration, and invasion.

Intraglandular dissemination is an important pathological feature of thyroid cancer, yet the biological characteristics of this phenomenon remain relatively underexplored. This paper aims to provide a comprehensive overview of its biological behaviors, protein expressions, and identification methods. Several retrospective studies have found that thyroid cancers with intraglandular dissemination have higher rates of lymph node metastasis, capsule invasion, and vascular invasion, exhibiting more aggressive biological behavior. Immunohistochemistry results show abnormal expression of proteins such as FKBP5, CENPF, CX26, KIF11, PTK7, which are associated with poor prognosis in thyroid cancers with intraglandular dissemination, offering potential guidance for specific targeted therapy in the future. Moreover, adjunctive techniques including ultrasound, fine-needle aspiration, and genetic testing offer valuable support in accurately identifying these cases, facilitating moreproactive treatment and closer follow-up.

Plasma cell mastitis (PCM), a prevalent and refractory form of non-lactating mastitis, is characterized by the pathological triad of ductal ectasia (DE), plasma cell-dominated inflammatory infiltration, and progressive fibrosis. Despite its clinical burden, current surgical interventions yield suboptimal outcomes with recurrence rates up to 43%, underscoring an urgent need for mechanistic insights. This review synthesizes evidence establishing epithelial-mesenchymal transition (EMT) as a central driver of PCM pathogenesis, intricately regulated by the disease-specific immune microenvironment. We demonstrate that autoimmune-mediated DE initiates ductal damage, generating damage-associated molecular patterns (DAMPs) that activate pattern recognition receptors (PRRs). This triggers NF-κB signaling hubs, upregulating pro-inflammatory mediators (IL-1β, IL-6, TGF-β1, ICAM-1, CXCL12) and core EMT-transcription factors (Snail, TWIST). Crucially, IL-6/JAK/STAT3 signaling promotes plasma cell survival via Bcl-2 while concurrently driving EMT in ductal epithelium. Concurrently, IL-1βactivate PI3K/Akt to stabilize EMT effectors and enhance ECM synthesis. A unique, self-amplifying “EMT-fibrosis loop” is identified as a PCM hallmark: EMT-derived fibroblasts secrete CXCL12 and TGF-β1, which activate NF-κB pathways in adjacent epithelia to perpetuate EMT and ECM deposition. This loop, alongside sustained plasma cell activity via IL-6/STAT3/Bcl-2, underpins PCM’s chronicity and distinguishes it from other mastitides like granulomatous lobular mastitis (GLM). We further highlight exosomal involvement in CXCL12 transport and M1 macrophage polarization as amplifiers of inflammation and EMT. Targeting these convergent pathways (NF-κB, JAK/STAT3) or disrupting the EMT-fibrosis loop (e.g., via CXCL12/TGF-β1 inhibitors) represents a promising therapeutic strategy to mitigate fibrosis and recurrence. Future research must validate these mechanisms in human-relevant models and address critical gaps in bacterial-autoimmune interplay and temporal dynamics across PCM stages.