EPS8 supports pancreatic cancer growth by inhibiting BMI1 mediated proteasomal degradation of ALDH7A1

METTL3-mediated ALDH m6A methylation regulates the malignant behavior of BMI1+ HNSCC stem cells

OBJECTIVES

To reveal the effect and mechanism of methyltransferase-like 3 (METTL3) on cancer stem cells (CSCs) of head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

First, we analyzed 14-HNSCC-patients' scRNA-seq dataset and TCGA dataset of HNSCC. Then, Mettl3 knockout or overexpression mice models were studied via tracing and staining technologies. In addition, we took flow cytometry sorting and sphere formation assays to observe tumorigenicity and used cell transfection and western blotting to verify target protein expression levels. Furthermore, methylated RNA immunoprecipitation sequencing (MeRIP-seq) and MeRIP-quantitative real-time PCR (MeRIP-qPCR) were taken to identify the mechanism of Mettl3 regulating Bmi1+ CSCs in HNSCC.

RESULTS

Due to SOX4 transcriptional regulation, METTL3 regulated the malignant behavior of BMI1+ HNSCC stem cells through cell division pathway. The progression and malignancy of HNSCC were decreased after Mettl3 knocked-out, while increased after Mettl3 knocked-in in Bmi1+ CSCs in vivo. Knockdown of Mettl3 inhibited stemness properties of CSCs in vitro. Mechanically, Mettl3 mediated the m6A modification of ALDH1A3 and ALDH7A1 mRNA in Bmi1+ HNSCC CSCs.

CONCLUSION

Regulated by SOX4, METTL3-mediated ALDH m6A methylation regulates the malignant behavior of BMI1+ HNSCC CSCs through cell division pathway.

HPV16 infection promotes the malignant transformation of the esophagus and progression of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) may be correlated with HPV infection, and the mechanism underlying the ESCC formation induced by HPV16 infection remains elusive. Here, we overexpressed HPV16 E6 and E7 and coordinated the overexpression of these two genes in EPC2 and ESCC cells. We found that E7 and coordinated expression of E6 and E7 promoted the proliferation of EPC2 cells, and upregulation of shh was responsible for cell proliferation since the use of vismodegib led to the failure of organoid formation. Meanwhile, overexpression of E6 and E7 in ESCC cells promoted cell proliferation, migration, and invasion in vitro. Importantly, E6 and E7 coordinately increased the capability of tumor growth in nude mice, while vismodegib slowed the growth of tumors in NCG mice. Moreover, a series of genes and proteins changed in cell lines after overexpression of the E6 and E7 genes, the potential biological processes and pathways were systematically analyzed using a bioinformatics assay. Together, these findings suggest that the activation of the hedgehog pathway induced by HPV16 infection may initially transform basal cells in the esophagus and promote following malignant processes in ESCC cells. The application of hedgehog inhibitors may represent a therapeutic avenue for ESCC treatment.

Single-cell sequencing and establishment of an 8-gene prognostic model for pancreatic cancer patients

Background

Single-cell sequencing (SCS) technologies enable analysis of gene structure and expression data at single-cell resolution. However, SCS analysis in pancreatic cancer remains largely unexplored.

Methods

We downloaded pancreatic cancer SCS data from different databases and applied appropriate dimensionality reduction algorithms. We identified 10 cell types and subsequently screened differentially expressed marker genes of these 10 cell types using FindAllMarkers analysis. Also, we evaluated the tumor immune microenvironment based on ESTIMATE and MCP-counter. Statistical enrichment was evaluated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. We used all candidate gene sets in KEGG database to perform gene set enrichment analysis. We used LASSO regression to reduce the number of genes in the pancreatic risk model by R package glmnet, followed by rtPCR to validate the expression of the signature genes in different pancreatic cancer cell lines.

Results

We identified 15 cell subpopulations by dimension reduction and data clustering. We divided the 15 subpopulations into 10 distinct cell types based on marker gene expression. Then, we performed functional enrichment analysis for the 352 marker genes in pancreatic cancer cells. Based on RNA expression data and prognostic information from TCGA and GEO datasets, we identified 42 prognosis-related genes, including 5 protective genes and 37 high-risk genes, which we used to identified two molecular subtypes. C1 subtype was associated with a better prognosis, whereas C2 subtype was associated with a worse prognosis. Moreover, chemokine and chemokine receptor genes were differentially expressed between C1 and C2 subtypes. Functional and pathway enrichment uncovered functional differences between C1 and C2 subtype. We identified eight genes that could serve as potential biomarkers for prognosis prediction in pancreatic cancer patients. These genes were used to establish an 8-gene pancreatic cancer prognostic model.

Conclusions

We established an 8-gene pancreatic cancer prognostic model. This model can meaningfully predict prognosis and treatment response in pancreatic cancer patients.

Circulating cancer-associated extracellular vesicles as early detection and recurrence biomarkers for pancreatic cancer

Early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for improving patient survival rates, and non-invasive biomarkers are urgently required to identify patients who are eligible for curative surgery. Here, we examined extracellular vesicles (EVs) from the serum of PDAC patients to determine their ability to detect early-stage disease. EV-associated proteins purified by ultracentrifugation and affinity columns underwent proteomic analysis to identify novel PDAC markers G protein-coupled receptor class C group 5 member C (GPRC5C) and epidermal growth factor receptor pathway substrate 8 (EPS8). To verify the potency of GPRC5C- or EPS8-positive EVs as PDAC biomarkers, we analyzed EVs from PDAC patient blood samples using ultracentrifugation in two different cohorts (a total of 54 PDAC patients, 32 healthy donors, and 22 pancreatitis patients) by immunoblotting. The combination of EV-associated GPRC5C and EPS8 had high accuracy, with area under the curve (AUC) values of 0.922 and 0.946 for distinguishing early-stage PDAC patients from healthy controls in the two cohorts, respectively, and could detect PDAC patients who were negative for CA19-9. Moreover, we analyzed 30 samples taken at three time points from 10 PDAC patients who underwent surgery: before surgery, after surgery, and recurrence as an early-stage model. These proteins were detected in EVs derived from preoperative and recurrence samples. These results indicated that GPRC5C- or EPS8-positive EVs were biomarkers that have the potential to detect stage I early pancreatic cancer and small recurrent tumors detected by computed tomography.