NFIC regulates ribosomal biology and ER stress in pancreatic acinar cells and restrains PDAC initiation

A Common CTRB misfolding variant associated with pancreatic cancer risk causes ER stress and inflammation in mice

BACKGROUND

Genome-wide association studies have identified an exon 6 CTRB2 deletion variant proposed to increase pancreatic cancer risk.

OBJECTIVE

To acquire evidence on its causal role, we developed and analysed a new mouse strain carrying an equivalent variant in Ctrb1, the mouse CTRB2 orthologue.

DESIGN

We used CRISPR/Cas9 to introduce a 707 bp deletion encompassing Ctrb1 exon 6 (Ctrb1Δexon6 ). This mutation closely mimics the human variant. Mice carrying the mutant allele were profiled at 3 months to assess their phenotype.

RESULTS

Ctrb1Δexon6 mutant mice express a truncated CTRB1 that accumulates in the endoplasmic reticulum (ER). The pancreas of homozygous mutant mice displays reduced chymotrypsin activity, total protein synthesis and amylase secretion. The histological aspect of the pancreas is inconspicuous but ultrastructural analysis shows evidence of dramatic ER stress and cytoplasmic and nuclear inclusions. Transcriptomic studies of the mutant pancreas reveal downregulation of the acinar programme and increased activity of ER stress-related and inflammatory pathways. Agr2 is one of the most upregulated genes in mutant pancreata. Heterozygous mice have an intermediate phenotype. Ctrb1Δexon6 mutant mice exhibit impaired recovery from acute caerulein-induced pancreatitis. Administration of tauroursodeoxycholic acid or sulindac partially alleviates the phenotype. A transcriptomic signature derived from the mutant pancreata is significantly enriched in normal human pancreas of CTRB2 exon 6 deletion variant carriers from the GTEx cohort.

CONCLUSIONS

This mouse strain provides evidence that the exon 6 deletion causes ER stress and inflammation and is an excellent model to understand its contribution to pancreatic cancer and identify preventive strategies.

Identification of epithelial-related artificial neural network prognostic models for the prediction of bladder cancer prognosis through comprehensive analysis of single-cell and bulk RNA sequencing

Background

Bladder cancer (BLCA) presents as a heterogeneous epithelial malignancy. Progress in the early detection and effective treatment of BLCA relies heavily on the identification of novel biomarkers. Therefore, the primary goal of this study is to pinpoint potential biomarkers for BLCA through the fusion of single-cell RNA sequencing and RNA sequencing assessments. Furthermore, the aim is to establish practical clinical prognostic models that can facilitate accurate categorization and individualized therapy for patients.

Methods

In this research, training sets were acquired from the TCGA database, whereas validation sets (GSE32894) and single-cell datasets (GSE135337) were extracted from the GEO database. Single-cell analysis was utilized to obtain characteristic subpopulations along with their associated marker genes. Subsequently, a novel BLCA subtype was identified within TCGA-BLCA. Furthermore, an artificial neural network prognostic model was constructed within the TCGA-BLCA cohort and subsequently verified utilizing a validation set. Two machine learning algorithms were employed to screen hub genes. QRT-qPCR was performed to detect the gene expression levels utilized in the construction of prognostic models across various cell lines. Additionally, the cMAP database and molecular docking were utilized for searching small molecule drugs.

Results

The results of single-cell analysis revealed the presence of epithelial cells in multiple subpopulations, with 1579 marker genes selected for subsequent investigations. Subsequently, four epithelial cell subtypes were identified within the TCGA-BLCA cohort. Notably, cluster A exhibited a significant survival advantage. Concurrently, an artificial neural network prognostic model comprising 17 feature genes was constructed, accurately stratifying patient risk. Patients categorized in the low-risk group demonstrated a considerable survival advantage. The ROC analysis suggested that the model has strong prognostic ability. Furthermore, the findings of the validation group align consistently with those from the training group. Two types of machine learning algorithms screened NFIC as hub genes. Forskolin, a small molecule drug that binds to NFIC, was identified by employing a cMAP database and molecular docking.

Conclusion

The analysis results supplement the research on the role of epithelial cells in BLCA. An artificial neural network prognostic model containing 17 characteristic genes demonstrates the capability to accurately stratify patient risk, thereby potentially improving clinical decision-making and optimizing personalized therapeutic approaches.

Establishment of a chemokine-based prognostic model and identification of CXCL10+ M1 macrophages as predictors of neoadjuvant therapy efficacy in colorectal cancer

Background

Although neoadjuvant therapy has brought numerous benefits to patients, not all patients can benefit from it. Chemokines play a crucial role in the tumor microenvironment and are closely associated with the prognosis and treatment of colorectal cancer. Therefore, constructing a prognostic model based on chemokines will help risk stratification and providing a reference for the personalized treatment.

Methods

Employing LASSO-Cox predictive modeling, a chemokine-based prognostic model was formulated, harnessing the data from TCGA and GEO databases. Then, our exploration focused on the correlation between the chemokine signature and elements such as the immune landscape, somatic mutations, copy number variations, and drug sensitivity. CXCL10+M1 macrophages identified via scRNA-seq. Monocle2 showed cell pseudotime trajectories, CellChat characterized intercellular communication. CytoTRACE analyzed neoadjuvant therapy stemness, SCENIC detected cell type-specific regulation. Lastly, validation was performed through multiplex immunofluorescence experiments.

Results

A model based on 15 chemokines was constructed and validated. High-risk scores correlated with poorer prognosis and advanced TNM and clinical stages. Individuals presenting elevated risk scores demonstrated an increased propensity towards the development of chemotherapy resistance. Subsequent scRNA-seq data analysis indicated that patients with higher presence of CXCL10+ M1 macrophages in tumor tissues are more likely to benefit from neoadjuvant therapy.

Conclusion

We developed a chemokine-based prognostic model by integrating both single-cell and bulk RNA-seq data. Furthermore, we revealed epithelial cell heterogeneity in neoadjuvant outcomes and identified CXCL10+ M1 macrophages as potential therapy response predictors. These findings could significantly contribute to risk stratification and serve as a key guide for the advancement of personalized therapeutic approaches.

A common CTRB misfolding variant associated with pancreatic cancer risk causes ER stress and inflammation in mice

Objective

Genome wide association studies have identified an exon 6 CTRB2 deletion variant that associates with increased risk of pancreatic cancer. To acquire evidence on its causal role, we developed a new mouse strain carrying an equivalent variant in Ctrb1 , the mouse orthologue of CTRB2 .

Design

We used CRISPR/Cas9 to introduce a 707bp deletion in Ctrb1 encompassing exon 6 ( Ctrb1 Δexon6 ). This mutation closely mimics the human deletion variant. Mice carrying the mutant allele were extensively profiled at 3 months to assess their phenotype.

Results

Ctrb1 Δexon6 mutant mice express a truncated CTRB1 that accumulates in the ER. The pancreas of homozygous mutant mice displays reduced chymotrypsin activity and total protein synthesis. The histological aspect of the pancreas is inconspicuous but ultrastructural analysis shows evidence of dramatic ER stress and cytoplasmic and nuclear inclusions. Transcriptomic analyses of the pancreas of mutant mice reveals acinar program down-regulation and increased activity of ER stress-related and inflammatory pathways. Heterozygous mice have an intermediate phenotype. Agr2 is one of the most up-regulated genes in mutant pancreata. Ctrb1 Δexon6 mice exhibit impaired recovery from acute caerulein-induced pancreatitis. Administration of TUDCA or sulindac partially alleviates the phenotype. A transcriptomic signature derived from the mutant pancreata is significantly enriched in normal human pancreas of CTRB2 exon 6 deletion variant carriers from the GTEx cohort.

Conclusions

This mouse strain provides formal evidence that the Ctrb1 Δexon6 variant causes ER stress and inflammation in vivo , providing an excellent model to understand its contribution to pancreatic ductal adenocarcinoma development and to identify preventive strategies.

SUMMARY BOX

What is already known about this subject?: - CTRB2 is one of the most abundant proteins produced by human pancreatic acinar cells. - A common exon 6 deletion variant in CTRB2 has been associated with an increased risk of pancreatic ductal adenocarcinoma. - Misfolding of digestive enzymes is associated with pancreatic pathology.What are the new findings?: - We developed a novel genetic model that recapitulates the human CTRB2 deletion variant in the mouse orthologue, Ctrb1 . - Truncated CTRB1 misfolds and accumulates in the ER; yet, mutant mice display a histologically normal pancreas at 3 months age.- CTRB1 and associated chaperones colocalize in the ER, the cytoplasm, and the nucleus of acinar cells.- Transcriptomics analysis reveals reduced activity of the acinar program and increased activity of pathways involved in ER stress, unfolded protein response, and inflammation.- Mutant mice are sensitized to pancreatic damage and do not recover properly from a mild caerulein-induced pancreatitis.- TUDCA administration partially relieves the ER stress in mutant mice.How might it impact on clinical practice in the foreseeable future?: - The new mouse model provides a tool to identify the mechanisms leading to increased pancreatic cancer risk in CTRB2 exon 6 carriers. - The findings suggest that drugs that cause ER stress relief and/or reduce inflammation might provide preventive opportunities.

ZDHHC20-mediated S-palmitoylation of YTHDF3 stabilizes MYC mRNA to promote pancreatic cancer progression

Post-translational modifications of proteins in malignant transformation and tumor maintenance of pancreatic ductal adenocarcinoma (PDAC) in the context of KRAS signaling remain poorly understood. Here, we use the KPC mouse model to examine the effect of palmitoylation on pancreatic cancer progression. ZDHHC20, upregulated by KRAS, is abnormally overexpressed and associated with poor prognosis in patients with pancreatic cancer. Dysregulation of ZDHHC20 promotes pancreatic cancer progression in a palmitoylation-dependent manner. ZDHHC20 inhibits the chaperone-mediated autophagic degradation of YTHDF3 through S-palmitoylation of Cys474, which can result in abnormal accumulation of the oncogenic product MYC and thereby promote the malignant phenotypes of cancer cells. Further, we design a biologically active YTHDF3-derived peptide to competitively inhibit YTHDF3 palmitoylation mediated by ZDHHC20, which in turn downregulates MYC expression and inhibits the progression of KRAS mutant pancreatic cancer. Thus, these findings highlight the therapeutic potential of targeting the ZDHHC20-YTHDF3-MYC signaling axis in pancreatic cancer.

Molecular mechanisms underlying mitochondrial damage, endoplasmic reticulum stress, and oxidative stress induced by environmental pollutants

Mitochondria and endoplasmic reticulum (ER) are essential organelles playing pivotal roles in the regulation of cellular metabolism, energy production, and protein synthesis. In addition, these organelles are important targets susceptible to external stimuli, such as environmental pollutants. Exposure to environmental pollutants can cause the mitochondrial damage, endoplasmic reticulum stress (ERS), and oxidative stress, leading to cellular dysfunction and death. Therefore, understanding the toxic effects and molecular mechanisms of environmental pollution underlying these processes is crucial for developing effective strategies to mitigate the adverse effects of environmental pollutants on human health. In the present study, we summarized and reviewed the toxic effects and molecular mechanisms of mitochondrial damage, ERS, and oxidative stress caused by exposure to environmental pollutants as well as interactions inducing the cell apoptosis and the roles in exposure to environmental pollutants.