PNN and KCNQ1OT1 Can Predict the Efficacy of Adjuvant Fluoropyrimidine-Based Chemotherapy in Colorectal Cancer Patients

Identification of a Novel miR-195-5p/PNN Axis in Colorectal Cancer

Pinin (PNN) is a desmosome-associated protein that reinforces the organization of keratin intermediate filaments and stabilizes the anchoring of the cytoskeleton network to the lateral surface of the plasma membrane. The aberrant expression of PNN affects the strength of cell adhesion as well as modifies the intracellular signal transduction pathways leading to the onset of CRC. In our previous studies, we characterized the role of miR-195-5p in the regulation of desmosome junctions and in CRC progression. Here, with the aim of investigating additional mechanisms related to the desmosome complex, we identified PNN as a miR-195-5p putative target. Using a public data repository, we found that PNN was a negative prognostic factor and was overexpressed in colon cancer tissues from stage 1 of the disease. Then, we assessed PNN expression in CRC tissue specimens, confirming the overexpression of PNN in tumor sections. The increase in intracellular levels of miR-195-5p revealed a significant decrease in PNN at the mRNA and protein levels. As a consequence of PNN regulation by miR-195-5p, the expression of KRT8 and KRT19, closely connected to PNN, was affected. Finally, we investigated the in vivo effect of miR-195-5p on PNN expression in the colon of AOM/DSS-treated mice. In conclusion, we have revealed a new mechanism driven by miR-195-5p in the regulation of desmosome components, suggesting a potential pharmacological target for CRC therapy.

Coronavirus herd immunity optimizer to solve classification problems

Classification is a technique in data mining that is used to predict the value of a categorical variable and to produce input data and datasets of varying values. The classification algorithm makes use of the training datasets to build a model which can be used for allocating unclassified records to a defined class. In this paper, the coronavirus herd immunity optimizer (CHIO) algorithm is used to boost the efficiency of the probabilistic neural network (PNN) when solving classification problems. First, the PNN produces a random initial solution and submits it to the CHIO, which then attempts to refine the PNN weights. This is accomplished by the management of random phases and the effective identification of a search space that can probably decide the optimal value. The proposed CHIO-PNN approach was applied to 11 benchmark datasets to assess its classification accuracy, and its results were compared with those of the PNN and three methods in the literature, the firefly algorithm, African buffalo algorithm, and β-hill climbing. The results showed that the CHIO-PNN achieved an overall classification rate of 90.3% on all datasets, at a faster convergence speed as compared outperforming all the methods in the literature.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00500-022-06917-z.

Role of Non-Coding RNAs in Colorectal Cancer: Focus on Long Non-Coding RNAs

Colorectal cancer is one of the most common causes of cancer-related deaths worldwide. Despite the advances in the knowledge of pathogenetic molecular mechanisms and the implementation of more effective drug treatments in recent years, the overall survival rate of patients remains unsatisfactory. The high death rate is mainly due to metastasis of cancer in about half of the cancer patients and the emergence of drug-resistant populations of cancer cells. Improved understanding of cancer molecular biology has highlighted the role of non-coding RNAs (ncRNAs) in colorectal cancer development and evolution. ncRNAs regulate gene expression through various mechanisms, including epigenetic modifications and interactions of long non-coding RNAs (lncRNAs) with both microRNAs (miRNAs) and proteins, and through the action of lncRNAs as miRNA precursors or pseudogenes. LncRNAs can also be detected in the blood and circulating ncRNAs have become a new source of non-invasive cancer biomarkers for the diagnosis and prognosis of colorectal cancer, as well as for predicting the response to drug therapy. In this review, we focus on the role of lncRNAs in colorectal cancer development, progression, and chemoresistance, and as possible therapeutic targets.

METTL3 enhances PNN mRNA stability through m6A modification to augment tumorigenesis of colon adenocarcinoma

NEW FINDINGS

What is the central question of this study? This study focuses on the role of Pinin (PNN) in the malignant phenotype of colon adenocarcinoma cells and the underlying mechanism. What is the main finding and its importance? PNN can be stabilized and upregulated by METTL3, which promotes glycolysis in COAD and augments cell proliferation, migration and invasiveness. METTL3 and PNN might serve as potential targets for the treatment of COAD.

ABSTRACT

Colon adenocarcinoma (COAD) is a fatal malignancy with high morbidity and mortality rates globally. Pinin (PNN), a desmosome associated protein, has been revealed as a tumor driver in several malignancies. This study aims to probe the expression and role of PNN in COAD and the underlying mechanism. PNN expressed at high levels in clinically collected COAD tumors and was linked to poor prognosis of patients. Downregulation of PNN reduced glucose uptake, lactate production and ATP levels in COAD cells and suppressed cell proliferation, migration, and invasiveness. Methyltransferase like 3 (METTL3) was positively associated with PNN levels in COAD tumor tissues. The RNA immunoprecipitation and m6A quantification assays indicated that METTL3 enhanced PNN mRNA stability and expression in COAD through m6A modification with the involvement of m6A "reader" protein YTHDF1. Downregulation of METTL3 reduced COAD cell glycolysis and proliferation in vitro and suppressed growth and metastasis of xenograft tumors in vivo, but further overexpression of PNN restored malignant behaviors of COAD cells and tumor growth. In summary, this study demonstrates that METTL3 promotes PNN mRNA stability and expression in COAD through m6A modification, which augments glycolysis and proliferation of COAD cells and leads to the resultant tumor progression. This article is protected by copyright. All rights reserved.

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

The World of Pseudogenes: New Diagnostic and Therapeutic Targets in Cancers or Still Mystery Molecules?

Pseudogenes were once considered as “junk DNA”, due to loss of their functions as a result of the accumulation of mutations, such as frameshift and presence of premature stop-codons and relocation of genes to inactive heterochromatin regions of the genome. Pseudogenes are divided into two large groups, processed and unprocessed, according to their primary structure and origin. Only 10% of all pseudogenes are transcribed into RNAs and participate in the regulation of parental gene expression at both transcriptional and translational levels through senseRNA (sRNA) and antisense RNA (asRNA). In this review, about 150 pseudogenes in the different types of cancers were analyzed. Part of these pseudogenes seem to be useful in molecular diagnostics and can be detected in various types of biological material including tissue as well as biological fluids (liquid biopsy) using different detection methods. The number of pseudogenes, as well as their function in the human genome, is still unknown. However, thanks to the development of various technologies and bioinformatic tools, it was revealed so far that pseudogenes are involved in the development and progression of certain diseases, especially in cancer.

LncRNA IGFL2-AS1 Promotes the Proliferation, Migration, and Invasion of Colon Cancer Cells and is Associated with Patient Prognosis

Background

LncRNAs play an important role in tumor initiation and development. However, the underlying involvement of lncRNA expression in colorectal carcinoma remains to be clarified.

Methods

All analyses were performed in R software v4.0, SPSS v13.0, and GraphPad Prism 8. The "limma" package was used to identify differentially expressed lncRNAs between two groups with the threshold of |logFC| >1 and P <0.05. The "Survival" package was used to conduct survival analysis. HCT8 and SE480 cell lines were used to conduct further phenotype experiments, including transwell, wound-healing, CCK8 and colony formation assay. Gene set enrichment analysis was used to explore the biological pathway difference in high and low IGFL2-AS1 patients.

Results

The lncRNA IGFL2-AS1 was highly expressed in colon adenocarcinoma (COAD) tissue and cell lines (HCT116, HCT8, HCT129, and SW480). The COAD patients with high IGFL2-AS1 were associated with a worse prognosis. Meanwhile, the knockdown of IGFL2-AS1 could significantly suppress the proliferation and invasion of COAD cells. Gene set enrichment analysis showed that the top five biological pathways involving IGFL2-AS1 were angiogenesis, epithelial-mesenchymal transition, KRAS signaling, myogenesis, and coagulation. Western blot results showed that the inhibition of IGFL2-AS1 could significantly reduce the N-cadherin, HIF1A and KRAS protein expression, yet increase the E-cadherin protein level. IGFL2-AS1 was also positively correlated with M0 macrophages, M2 macrophages, and neutrophils but negatively correlated with CD4+ memory T cells and CD8+ T cells.

Conclusion

IGFL1-AS1 could seriously worsen patient outcomes and facilitate COAD progression, thus serving as an independent tumor marker.

The role and regulation of Pnn in proliferative and non-dividing cells: Form embryogenesis to pathogenesis

Pnn, a multiple functional protein, plays roles in embryonic development, cellular differentiation, tumorigenesis, and metastasis. In the past two decades, the functions of Pnn in regulating RNA alternative splicing, gene regulation, and cell-cell connection have been revealed. Although Pnn is originally identified as a desmosome-associated protein for linking desmosome and intermediated filament, emerging evidence implies that Pnn not only is a desmosome protein but also plays critical roles in the nucleus. To date, through cell biology investigation and the generation of animal models with genetic manipulation, the physiological role of Pnn has been characterized in the research fields of developmental biology, tumor biology, and neuroscience. Through proteomic and molecular biology studies, transcription regulators, splicing regulators, and cytoskeletal proteins were found to interact with Pnn. In addition, histopathological and biochemical evidence has pointed to an association of Pnn expression level with tumorigenesis and metastasis. A previous clinical study also demonstrated a correlation between a reduced expression of Pnn and human dementia. Besides, experimental studies showed a protective role of Pnn against ischemic stress in astrocytes. All indicated a variety of roles of Pnn in different cell types. In this review article, we introduced the role of Pnn in embryogenesis and pathogenesis as well as discussed its potential clinical application.

Pinin acts as a poor prognostic indicator for renal cell carcinoma by reducing apoptosis and promoting cell migration and invasion

Pinin (PNN) was originally characterized as a desmosome-associated molecule. Its function and the mechanism of its regulation in renal cell carcinoma (RCC) are still undefined. Data on PNN expression, clinicopathological features, and prognosis of patients with RCC were obtained from The Cancer Genome Atlas (TCGA) database. Immunohistochemistry revealed high PNN expression in tumour cells. PNN expression showed negative correlation with survival in patients with RCC, acting as an independent prognostic factor in RCC. PNN up-regulation might be attributed to epigenetic alterations in RCC. Immunofluorescence revealed PNN expression mainly in the nucleus of RCC cells. The transfection of siRNA targeting the PNN gene resulted in enhanced apoptosis, which was detected by flow cytometry, and reduced cell migration and invasion, which were assessed using wound healing and transwell migration assay. Gene set enrichment analysis revealed associations between PNN expression and several signalling pathways involved in cancer progression, as a potential mechanism underlying the carcinogenicity of PNN. The analyses of the Tumor Immune Estimation Resource platform showed significant positive associations between high PNN expression and tumour immune infiltrating cells. PNN may function as an oncogenic factor by reducing apoptosis and promoting cell migration and invasion in RCC.