The PTB-Associated Splicing Factor/Peroxisome Proliferator-Activated Receptor Gamma Axis Regulates Autophagosome Formation in Human Pancreatic Cancer Cells

Splicing alterations in pancreatic ductal adenocarcinoma: a new molecular landscape with translational potential

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers worldwide, mainly due to its late diagnosis and lack of effective therapies, translating into a low 5-year 12% survival rate, despite extensive clinical efforts to improve outcomes. International cooperative studies have provided informative multiomic landscapes of PDAC, but translation of these discoveries into clinical advances are lagging. Likewise, early diagnosis biomarkers and new therapeutic tools are sorely needed to tackle this cancer. The study of poorly explored molecular processes, such as splicing, can provide new tools in this regard. Alternative splicing of pre-RNA allows the generation of multiple RNA variants from a single gene and thereby contributes to fundamental biological processes by finely tuning gene expression. However, alterations in alternative splicing are linked to many diseases, and particularly to cancer, where it can contribute to tumor initiation, progression, metastasis and drug resistance. Splicing defects are increasingly being associated with PDAC, including both mutations or dysregulation of components of the splicing machinery and associated factors, and altered expression of specific relevant gene variants. Such disruptions can be a key element enhancing pancreatic tumor progression or metastasis, while they can also provide suitable tools to identify potential candidate biomarkers and discover new actionable targets. In this review, we aimed to summarize the current information about dysregulation of splicing-related elements and aberrant splicing isoforms in PDAC, and to describe their relationship with the development, progression and/or aggressiveness of this dismal cancer, as well as their potential as therapeutic tools and targets.

The Dysregulated MAD in Mad: A Neuro-theranostic Approach Through the Induction of Autophagic Biomarkers LC3B-II and ATG

The word mad has historically been associated with the psyche, emotions, and abnormal behavior. Dementia is a common symptom among psychiatric disorders or mad (schizophrenia, depression, bipolar disorder) patients. Autophagy/mitophagy is a protective mechanism used by cells to get rid of dysfunctional cellular organelles or mitochondria. Autophagosome/mitophagosome abundance in autophagy depends on microtubule-associated protein light chain 3B (LC3B-II) and autophagy-triggering gene (ATG) which functions as an autophagic biomarker for phagophore production and quick mRNA disintegration. Defects in either LC3B-II or the ATG lead to dysregulated mitophagy-and-autophagy-linked dementia (MAD). The impaired MAD is closely associated with schizophrenia, depression, and bipolar disorder. The pathomechanism of psychosis is not entirely known, which is the severe limitation of today's antipsychotic drugs. However, the reviewed circuit identifies new insights that may be especially helpful in targeting biomarkers of dementia. Neuro-theranostics can also be achieved by manufacturing either bioengineered bacterial and mammalian cells or nanocarriers (liposomes, polymers, and nanogels) loaded with both imaging and therapeutic materials. The nanocarriers must cross the BBB and should release both diagnostic agents and therapeutic agents in a controlled manner to prove their effectiveness against psychiatric disorders. In this review, we highlighted the potential of microRNAs (miRs) as neuro-theranostics in the treatment of dementia by targeting autophagic biomarkers LC3B-II and ATG. Focus was also placed on the potential for neuro-theranostic nanocells/nanocarriers to traverse the BBB and induce action against psychiatric disorders. The neuro-theranostic approach can provide targeted treatment for mental disorders by creating theranostic nanocarriers.

Prognostic Significance of Autophagy-Relevant Gene Markers in Colorectal Cancer

Background

Colorectal cancer (CRC) is a common malignant solid tumor with an extremely low survival rate after relapse. Previous investigations have shown that autophagy possesses a crucial function in tumors. However, there is no consensus on the value of autophagy-associated genes in predicting the prognosis of CRC patients. This work screens autophagy-related markers and signaling pathways that may participate in the development of CRC, and establishes a prognostic model of CRC based on autophagy-associated genes.

Methods

Gene transcripts from the TCGA database and autophagy-associated gene data from the GeneCards database were used to obtain expression levels of autophagy-associated genes, followed by Wilcox tests to screen for autophagy-related differentially expressed genes. Then, 11 key autophagy-associated genes were identified through univariate and multivariate Cox proportional hazard regression analysis and used to establish prognostic models. Additionally, immunohistochemical and CRC cell line data were used to evaluate the results of our three autophagy-associated genes EPHB2, NOL3, and SNAI1 in TCGA. Based on the multivariate Cox analysis, risk scores were calculated and used to classify samples into high-risk and low-risk groups. Kaplan-Meier survival analysis, risk profiling, and independent prognosis analysis were carried out. Receiver operating characteristic analysis was performed to estimate the specificity and sensitivity of the prognostic model. Finally, GSEA, GO, and KEGG analysis were performed to identify the relevant signaling pathways.

Results

A total of 301 autophagy-related genes were differentially expressed in CRC. The areas under the 1-year, 3-year, and 5-year receiver operating characteristic curves of the autophagy-based prognostic model for CRC were 0.764, 0.751, and 0.729, respectively. GSEA analysis of the model showed significant enrichment in several tumor-relevant pathways and cellular protective biological processes. The expression of EPHB2, IL-13, MAP2, RPN2, and TRAF5 was correlated with microsatellite instability (MSI), while the expression of IL-13, RPN2, and TRAF5 was related to tumor mutation burden (TMB). GO analysis showed that the 11 target autophagy genes were chiefly enriched in mRNA processing, RNA splicing, and regulation of the mRNA metabolic process. KEGG analysis showed enrichment mainly in spliceosomes. We constructed a prognostic risk assessment model based on 11 autophagy-related genes in CRC.

Conclusion

A prognostic risk assessment model based on 11 autophagy-associated genes was constructed in CRC. The new model suggests directions and ideas for evaluating prognosis and provides guidance to choose better treatment strategies for CRC.