High SURF4 expression is associated with poor prognosis of breast cancer

Surfeit Locus Protein 4 as a Novel Target for Therapeutic Intervention in Cerebral Ischemia-Reperfusion Injury

Surfeit locus protein 4 (SURF4) functions as a cargo receptor that is capable of transporting newly formed proteins from the lumen of the endoplasmic reticulum into vesicles and Golgi bodies. However, the role of SURF4 in the central nervous system remains unclear. The aim of this study is to investigate the role of SURF4 and its underlying mechanisms in cerebral ischemia/reperfusion (I/R) injury in rats, and whether it can be used effectively for novel therapeutic intervention. We also examined whether transcranial direct-current stimulation (tDCS) can exert a neuroprotective effect via SURF4-dependent signalling. Following cerebral I/R injury in rats, a significant increase was observed in the expression of SURF4. In both I/R injury and oxygen-glucose deprivation (OGD) insult, suppressing the expression of SURF4 demonstrated a neuroprotective effect, while overexpression of SURF4 resulted in increased neuronal death. We further showed that the levels of nerve growth factor precursor (proNGF), p75 neurotrophin receptor (p75NTR), sortilin, and PTEN were increased following cerebral I/R injury, and that SURF4 acted through the PTEN/proNGF signal pathway to regulate neuronal viability. We demonstrated that tDCS treatment reduced SURF4 expression and decreased the infarct volume after cerebral I/R injury. Together, this study indicates that SURF4 plays a critical role in ischemic neuronal injury and may serve as a molecular target for the development of therapeutic strategies in acute ischemic stroke.

Disulfidptosis features and prognosis in head and neck squamous cell carcinoma patients: unveiling and validating the prognostic signature across cohorts

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a significant health concern with a variable global incidence and is linked to regional lifestyle factors and HPV infections. Despite treatment advances, patient prognosis remains variable, necessitating an understanding of its molecular mechanisms and the identification of reliable prognostic biomarkers.

METHODS

We analyzed 959 HNSCC samples and employed batch correction to obtain consistent transcriptomic data across cohorts. We examined 79 disulfidptosis-related genes to determine consensus clusters and utilized high-throughput sequencing to identify genetic heterogeneity within tumors. We established a disulfidptosis prognostic signature (DSPS) using least absolute shrinkage and selection operator (LASSO) regression and developed a prognostic nomogram integrating the DSPS with clinical factors. Personalized chemotherapy prediction was performed using the "pRRophetic" R package.

RESULTS

Batch corrections were used to harmonize gene expression data, revealing two distinct disulfidptosis subtypes, C1 and C2, with differential gene expression and survival outcomes. Subtype C1, characterized by increased expression of the MYH family genes ACTB, ACTN2, and FLNC, had a mortality rate of 48.4%, while subtype C2 had a mortality rate of 38.7% (HR = 0.77, 95% CI: 0.633-0.934, P = 0.008). LASSO regression identified 15 genes that composed the DSPS prognostic model, which independently predicted survival (HR = 2.055, 95% CI: 1.420-2.975, P < 0.001). The prognostic nomogram, which included the DSPS, age, and tumor stage, predicted survival with AUC values of 0.686, 0.704, and 0.789 at 3, 5, and 8 years, respectively, indicating strong predictive capability. In the external validation cohort (cohort B), the DSPS successfully identified patients at greater risk, with worse overall survival outcomes in the high-DSPS subgroup (HR = 1.54, 95% CI: 1.17-2.023, P = 0.002) and AUC values of 0.601, 0.644, 0.636, and 0.748 at 3, 5, 8, and 10 years, respectively, confirming the model's robustness.

CONCLUSION

The DSPS provides a robust prognostic tool for HNSCC, underscoring the complexity of this disease and the potential for tailored treatment strategies. This study highlights the importance of molecular signatures in oncology, offering a step toward personalized medicine and improved patient outcomes in HNSCC management.

ER exit in physiology and disease

The biosynthetic secretory pathway is comprised of multiple steps, modifications and interactions that form a highly precise pathway of protein trafficking and secretion, that is essential for eukaryotic life. The general outline of this pathway is understood, however the specific mechanisms are still unclear. In the last 15 years there have been vast advancements in technology that enable us to advance our understanding of this complex and subtle pathway. Therefore, based on the strong foundation of work performed over the last 40 years, we can now build another level of understanding, using the new technologies available. The biosynthetic secretory pathway is a high precision process, that involves a number of tightly regulated steps: Protein folding and quality control, cargo selection for Endoplasmic Reticulum (ER) exit, Golgi trafficking, sorting and secretion. When deregulated it causes severe diseases that here we categorise into three main groups of aberrant secretion: decreased, excess and altered secretion. Each of these categories disrupts organ homeostasis differently, effecting extracellular matrix composition, changing signalling events, or damaging the secretory cells due to aberrant intracellular accumulation of secretory proteins. Diseases of aberrant secretion are very common, but despite this, there are few effective therapies. Here we describe ER exit sites (ERES) as key hubs for regulation of the secretory pathway, protein quality control and an integratory hub for signalling within the cell. This review also describes the challenges that will be faced in developing effective therapies, due to the specificity required of potential drug candidates and the crucial need to respect the fine equilibrium of the pathway. The development of novel tools is moving forward, and we can also use these tools to build our understanding of the acute regulation of ERES and protein trafficking. Here we review ERES regulation in context as a therapeutic strategy.

Identifying prognostic markers in spatially heterogeneous breast cancer microenvironment

To gain deeper insights into the microenvironment of breast cancer, we utilized GeoMx Digital Spatial Profiling (DSP) technology to analyze transcripts from 107 regions of interest in 65 untreated breast cancer tissue samples. Our study revealed spatial heterogeneity in the expression of marker genes in tumor cell enriched, immune cell enriched, and normal epithelial areas. We evaluated a total of 55 prognostic markers in tumor cell enriched regions and 15 in immune cell enriched regions, identifying that tumor cell enriched regions had higher levels of follicular helper T cells, resting dendritic cells, and plasma cells than immune cell enriched regions, while the levels of resting CD4 memory in T cells and regulatory (Treg) T cells were lower. Additionally, we analyzed the heterogeneity of HLA gene families, immunological checkpoints, and metabolic genes in these areas. Through univariate Cox analysis, we identified 5 prognosis-related metabolic genes. Furthermore, we conducted immunostaining experiments, including EMILIN2, SURF4, and LYPLA1, to verify our findings. Our investigation into the spatial heterogeneity of the breast cancer tumor environment has led to the discovery of specific diagnostic and prognostic markers in breast cancer.