miRNA-363-3p Hinders Proliferation, Migration, Invasion and Autophagy of Thyroid Cancer Cells by Controlling SYT1 Transcription to affect NF-κB

Synaptotagmin-1 attenuates myocardial programmed necrosis and ischemia/reperfusion injury through the mitochondrial pathway

Programmed necrosis/necroptosis greatly contributes to the pathogenesis of cardiac disorders including myocardial infarction, ischemia/reperfusion (I/R) injury and heart failure. However, the fundamental mechanism underlying myocardial necroptosis, especially the mitochondria-dependent death pathway, is poorly understood. Synaptotagmin-1 (Syt1), a Ca2+ sensor, is originally identified in nervous system and mediates synchronous neurotransmitter release. The later findings of Syt1 expressions in many non-neuronal tissues including muscles suggest that Syt1 may exert important functions beyond regulation of neurotransmitter release. Syt1 is highly expressed in cardiomyocytes and has been used as an extracellular molecular probe for SPECT imaging of cardiac cell death in acute myocardial infarction. However, whether Syt1 functions in the pathogenesis of cardiac disorders and what is the molecular etiology have not yet been clarified. We showed here that Syt1 expression was significantly down-regulated in mice I/R injured heart tissues, H2O2-challenged cardiomyocytes and hypoxia/reoxygenation (H/R)-damaged cardiomyocytes. Enforced expression of Syt1 significantly inhibited myocardial necrotic cell death and interstitial fibrosis, and improved cardiac function in mice subjected to I/R operation. In exploring the underlying mechanisms, we found that Syt1 interacted with Parkin and promoted Parkin-catalyzed CypD ubiquitination, thus inhibited mitochondrial membrane permeability transition pore (mPTP) opening and ultimately suppressed cardiomyocyte necrosis. We further found that Syt1 expression was negatively regulated by miR-193b-3p. MiR-193b-3p regulated cardiomyocyte necrosis and mPTP opening by targeting Syt1. Our present work revealed a novel regulatory model of myocardial necrosis composed of miR-193b-3p, Syt1, Parkin, and CypD, which may provide potential therapeutic targets and strategies for heart protection.

Combination of inflammatory proteins in serum can be used to diagnose papillary thyroid carcinoma with lymph node metastasis

BACKGROUND

Accurately distinguishing lymph node metastases (LNM) from papillary thyroid carcinomas (PTC) is crucial in clinical practice. The role of the immune system in PTC-LNM has attracted increasing attention. The aim of the present study was to evaluate the differential expression of 92 immune-related proteins in the serum and identify their potential diagnostic effects in patients with PTC-LNM.

METHODS

The 92 immune-related proteins were analyzed using a proximity extension assay. In addition, logistic regression and least absolute shrinkage and selection operator regression methods were used to develop combined diagnostic markers for thyroid cancer. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic validity. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to analyze the potential regulatory pathways.

RESULTS

Five proteins, including IL-22RA1, IL-12B, CCL4, CCL3, and IL-1α, were significantly elevated in the serum of patients with LNM. The combined diagnosis of these five proteins demonstrated excellent diagnostic performance in distinguishing patients with PTC-LNM (area under the curve = 0.967, sensitivity = 0.941, and specificity = 0.889). Further analysis revealed that IL12B and IL1A mRNAs were significantly overexpressed in patients with PTC-LNM. This study also showed that the IL12B and IL1A was closely related to the PI3K-AKT, NF-κB, and MAPK signaling pathways.

CONCLUSION

The combination of IL-22RA1, IL-12B, CCL4, CCL3, and IL-1α represents a promising diagnostic panel for PTC-LNM. These findings provide a novel set of diagnostic markers for PTC-LNM based on serum inflammatory protein levels.

Beclin-1: a therapeutic target at the intersection of autophagy, immunotherapy, and cancer treatment

The significant identification of Beclin-1's function in regulating autophagy flow signified a significant progression in our understanding of cellular operations. Beclin-1 acts as a scaffold for forming the PI3KC3 complex, controlling autophagy and cellular trafficking processes in a complicated way. This intricate protein has garnered considerable attention due to its substantial impact on the development of tumors. Strong evidence indicates Beclin-1 plays a critical role in controlling autophagy in various human cancer types and its intricate connection with apoptosis and ferroptosis. The potential of Beclin-1 as a viable target for cancer therapy is highlighted by its associations with key autophagy regulators such as AMPK, mTOR, and ATGs. Beclin-1 controls the growth and dissemination of tumors by autophagy. It also affects how tumors react to therapies such as chemotherapy and radiation therapy. The role of Beclin-1 in autophagy can influence apoptosis, depending on whether it supports cell survival or leads to cell death. Beclin-1 plays a crucial role in ferroptosis by increasing ATG5 levels, which in turn promotes autophagy-triggered ferroptosis. Finally, we analyzed the possible function of Beclin-1 in tumor immunology and drug sensitivity in cancers. In general, Beclin-1 has a significant impact on regulating autophagy, offering various potentials for medical intervention and altering our understanding of cancer biology.

Bioinformatics Analysis and Experimental Validation for Exploring Key Molecular Markers for Glioblastoma

Glioblastoma (GBM) is the most common primary intracranial malignancy with a very low survival rate. Exploring key molecular markers for GBM can help with early diagnosis, prognostic prediction, and recurrence monitoring. This study aims to explore novel biomarkers for GBM via bioinformatics analysis and experimental verification. Dataset GSE103229 was obtained from the GEO database to search differentially expressed lncRNA (DELs), mRNAs (DEMs), and miRNAs (DEMis). Hub genes were selected to establish competing endogenous RNA (ceRNA) networks. The GEPIA database was employed for the survival analysis and expression detection of hub genes. Hub gene expression in GBM tissue samples and cell lines was validated using RT-qPCR. Western blotting was employed for protein expression evaluation. SYT1 overexpression vector was transfected in GBM cells. CCK-8 assay and flow cytometry were performed to detect the malignant phenotypes of GBM cells. There were 901 upregulated and 1086 downregulated DEMs identified, which were prominently enriched in various malignancy-related functions and pathways. Twenty-two hub genes were selected from PPI networks. Survival analysis and experimental validation revealed that four hub genes were tightly associated with GBM prognosis and progression, including SYT1, GRIN2A, KCNA1, and SYNPR. The four genes were significantly downregulated in GBM tissues and cell lines. Overexpressing SYT1 alleviated the proliferation and promoted the apoptosis of GBM cells in vitro. We identify four genes that may be potential molecular markers of GBM, which may provide new ideas for improving early diagnosis and prediction of the disease.

Biologic activity and treatment resistance to gastrointestinal cancer: the role of circular RNA in autophagy regulation

Circular RNAs (circRNAs) lack the 5'-end methylated guanine cap structure and 3' polyadenylate tail structure, classifying it as a non-coding RNA. With the extensive investigation of circRNA, its role in regulating cell death has garnered significant attention in recent years, establishing it as a recognized participant in cancer's biological processes. Autophagy, an essential pathway in programmed cell death (PCD), involves the formation of autophagosomes using lysosomes to degrade cellular contents under the regulation of various autophagy-related (ATG) genes. Numerous studies have demonstrated that circRNA can modulate the biological activity of cancer cells by influencing the autophagy pathway, exhibiting a dualistic role in suppressing or promoting carcinogenesis. In this review, we comprehensively analyze how autophagy-related circRNA impacts the progression of gastrointestinal cancer (GIC). Additionally, we discuss drug resistance phenomena associated with autophagy regulation in GIC. This review offers valuable insights into exploring potential biological targets for prognosis and treatment strategies related to GIC.

Integrated analysis of methylation and transcriptome identifies a novel risk model for diagnosis, prognosis, and immune characteristics in head and neck squamous cell carcinoma

BACKGROUND

DNA methylation is an important epigenetic modification that plays a crucial role in the development and progression of various tumors. However, the association between methylation‑driven genes and diagnosis, prognosis, and immune characteristics of head and neck squamous cell carcinoma (HNSCC) remains unclear.

METHODS

We obtained transcriptome, methylation, and clinical data from HNSCC patients in TCGA database, and used MethylMix algorithm to identify methylation-driven genes. A methylation driven gene-related risk model was constructed using Lasso regression analysis, and validated using data from GEO database. Immune infiltration and immune function analysis of the expression profiles were conducted using ssGSEA. Differences in immune checkpoint-related genes were analyzed, and the efficacy of immunotherapy was evaluated using TCIA database. Finally, a series of cell functional experiments were conducted to validate the results.

RESULTS

Five methylation-driven genes were identified and utilized to construct a prognostic risk model. Based on the median risk score, all patients were categorized into high-risk and low-risk groups. The K-M analysis revealed that patients in the high-risk group have a worse prognosis. Additionally, the risk model demonstrated better prognostic predictive value as indicated by ROC analysis. GSEA enrichment analysis indicated that gene sets in the high and low-risk groups were primarily enriched in pathways associated with tumor immunity and metabolism. Our subsequent investigations showed that high-risk patients exhibited more immunosuppressive phenotypes, while low-risk patients were more likely to respond positively to immunotherapy.

CONCLUSION

These findings of our research have the potential to improve patient stratification, guide treatment decisions, and advance the development of personalized therapies for HNSCC.

Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective

BACKGROUND

Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.

METHODS

We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.

RESULTS

We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.

CONCLUSIONS

These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.