Synaptotagmin-7 is overexpressed in hepatocellular carcinoma and regulates hepatocellular carcinoma cell proliferation via Chk1-p53 signaling

Potential roles of synaptotagmin family members in cancers: Recent advances and prospects

With the continuous development of bioinformatics and public database, more and more genes that play a role in cancers have been discovered. Synaptotagmins (SYTs) are abundant, evolutionarily conserved integral membrane proteins composed of a short N-terminus, a variable linker domain, a single transmembrane domain, and two C2 domains, and they constitute a family of 17 isoforms. The synaptotagmin family members are known to regulate calcium-dependent membrane fusion events. Some SYTs play roles in hormone secretion or neurotransmitter release or both, and much evidence supports SYTs as Ca²⁺ sensors of exocytosis. Since 5 years ago, an increasing number of studies have found that SYTs also played important roles in the occurrence and development of lung cancer, gastric cancer, colon cancer, and other cancers. Down-regulation of SYTs inhibited cell proliferation, migration, and invasion of cancer cells, but promoted cell apoptosis. Growth of peritoneal nodules is inhibited and survival is prolonged in mice administrated with siSYTs intraperitoneally. Therefore, most studies have found SYTs serve as an oncogene after overexpression and may become potential prognostic biomarkers for multiple cancers. This article provides an overview of recent studies that focus on SYT family members’ roles in cancers and highlights the advances that have been achieved.

GINS2 attenuates the development of lung cancer by inhibiting the STAT signaling pathway

GINS complex subunit 2 (GINS2) controls DNA replication. GINS2 expression is upregulated in several kinds of aggressive tumors. However, the effect of GINS2 in lung cancer remains unclear. We performed TCGA database analysis to confirm the clinical significance of GINS2 in lung cancer. After silencing GINS2 in A549 cells, we performed MTT assays, flow cytometry assays, colony formation assays, cell cycle analyses and RNA sequence analysis to elucidate the effect of GINS2 on lung cancer. Moreover, we assessed tumor growth and analyzed body fluorescence in mice as a measure of tumor burden. The TCGA database analysis demonstrated that GINS2 mRNA and protein was highly expressed in three kinds of lung cancer tissues. Subsequently, knockdown of GINS2 inhibited cell proliferation, colony formation, cell cycle arrest and apoptosis in A549 cells. On the other hand, we also investigated the effect of GINS2 on tumor formation in vivo. The analysis of nude mouse tumors showed that the tumor volume and weight of shGINS2 mice were significantly smaller than those of the control mice. To reveal the mechanism of GINS2 in lung cancer, we collected A549 cells with GINS2 knockdown to examine the downstream gene expression changes. The results showed that STAT1 and STAT2 mRNA and protein expression were significantly upregulated after GINS2 knockdown in A549 cells. Our results suggest that GINS2 inhibits the proliferation of lung cancer cells by inhibiting the STAT signaling pathway, which may be a potential biomarker for the diagnosis or prognosis of lung cancer.

Syt-7 overexpression predicts poor prognosis and promotes cell proliferation in hepatocellular carcinoma

Aim: To explore the prognostic significance of Syt-7 in hepatocellular carcinoma (HCC) and the potential mechanisms. Methods: Immunohistochemistry was used to examine the expression of Syt-7. Overall survival and disease-free survival were compared between Syt-7 positive and negative groups. The effects of Syt-7 knockdown on BEL-7404 cells were further evaluated. Results: Syt-7 expression was significantly higher in HCC tumorous tissues compared with paracancerous tissues. Syt-7 was closely associated with α-fetoprotein tumor size, vascular invasion, tumor node metastasis stage and tumor differentiation. Syt-7 was an independent risk factor for overall survival and disease-free survival. Additionally, Syt-7 knockdown inhibited proliferation and colony formation and induced cell cycle arrest in HCC cells. Conclusion: Syt-7 overexpression forecasts unfavorable prognosis and promotes cell proliferation in HCC.

Diagnostic and prognostic value of MCM3 and its interacting proteins in hepatocellular carcinoma

Aberrant DNA replication is one of the driving forces behind oncogenesis. Furthermore, minichromosome maintenance complex component 3 (MCM3) serves an essential role in DNA replication. Therefore, in the present study, the diagnostic and prognostic value of MCM3 and its interacting proteins in hepatocellular carcinoma (HCC) were investigated. By utilizing The Cancer Genome Atlas (TCGA) database, global MCM3 mRNA levels were assessed in HCC and normal liver tissues. Its effects were further analyzed by reverse transcription-quantitative PCR (RT-qPCR), western blotting and immunohistochemistry in 78 paired HCC and adjacent tissues. Functional and pathway enrichment analyses were performed using the Search Tool for the Retrieval of Interacting Genes database. The expression levels of proteins that interact with MCM3 were also analyzed using the TCGA database and RT-qPCR. Finally, algorithms combining receiver operating characteristic (ROC) curves were constructed using binary logistic regression using the TCGA results. Increased MCM3 mRNA expression with high α-fetoprotein levels and advanced Edmondson-Steiner grade were found to be characteristic of HCC. Survival analysis revealed that high MCM3 expression was associated with poor outcomes in patients with HCC. In addition, MCM3 protein expression was associated with increased tumor invasion in HCC tissues. MCM3 and its interacting proteins were found to be primarily involved in DNA replication, cell cycle and a number of binding processes. Algorithms combining ROCs of MCM3 and its interacting proteins were found to have improved HCC diagnosis ability compared with MCM3 and other individual diagnostic markers. In conclusion, MCM3 appears to be a promising diagnostic biomarker for HCC. Additionally, the present study provides a basis for the multi-gene diagnosis of HCC using MCM3.

Silencing of synaptotagmin 7 regulates osteosarcoma cell proliferation, apoptosis, and migration

BACKGROUND

Synaptotagmin 7 (SYT7) is a component of the synaptotagmin family, which is essential in many physiological and pathological processes. In this study, we aimed to investigate the role of SYT7 in osteosarcoma.

METHODS

We defined the expression levels of SYT7 in osteosarcoma tissues and para-sarcoma tissues by immunohistochemistry and analyzed the possible correlation between SYT7 expression and pathological characteristics via Mann-Whitney U analysis and Spearman correlation analysis. The effects of SYT7 silencing in vitro cell growth were assessed by MTT assay. Cell cycle and cell apoptosis were assessed by flow cytometry analysis. Wound healing assay and transwell assay were applied to assess the migration and invasion capacity.

RESULTS

The results showed that the expression levels of SYT7 were upregulated in osteosarcoma tissues compared with para-sarcoma tissues and positively correlated with the pathological characteristics of osteosarcoma. Functional experiments demonstrated that SYT7 silencing significantly inhibited cell proliferation and colony formation capacity (P<0.001), induced cell cycle arrest which increased the proportion of G2 phase and decreased the proportion of S phase, enhanced cell apoptosis (P<0.01), and limited the capacity of migration and invasion (P<0.01), compared with shCtrl group.

CONCLUSION

The results indicated that SYT7 plays a crucial role in the development of osteosarcoma. SYT7 can be applied as a new diagnostic and therapeutic target in osteosarcoma.

An 8‑gene signature predicts the prognosis of cervical cancer following radiotherapy

Gene expression and DNA methylation levels affect the outcomes of patients with cancer. The present study aimed to establish a multigene risk model for predicting the outcomes of patients with cervical cancer (CerC) treated with or without radiotherapy. RNA sequencing training data with matched DNA methylation profiles were downloaded from The Cancer Genome Atlas database. Patients were divided into radiotherapy and non‑radiotherapy groups according to the treatment strategy. Differently expressed and methylated genes between the two groups were identified, and 8 prognostic genes were identified using Cox regression analysis. The optimized risk model based on the 8‑gene signature was defined using the Cox's proportional hazards model. Kaplan‑Meier survival analysis indicated that patients with higher risk scores exhibited poorer survival compared with patients with lower risk scores (log‑rank test, P=3.22x10‑7). Validation using the GSE44001 gene set demonstrated that patients in the high‑risk group exhibited a shorter survival time comprared with the low‑risk group (log‑rank test, P=3.01x10‑3). The area under the receiver operating characteristic curve values for the training and validation sets were 0.951 and 0.929, respectively. Cox regression analyses indicated that recurrence and risk status were risk factors for poor outcomes in patients with CerC treated with or without radiotherapy. The present study defined that the 8‑gene signature was an independent risk factor for the prognosis of patients with CerC. The 8‑gene prognostic model had predictive power for CerC prognosis.

Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.