Bioinformatics analysis for the role of CALR in human cancers

Acute promyelocytic leukemia with additional chromosome abnormalities in a patient positive for HIV: A case report and literature review

Acute promyelocytic leukemia (APL), especially cases of high-risk with complex chromosomes (CK), is rare in individuals infected with human immunodeficiency virus (HIV), making the establishment of therapeutic approaches challenging; often the treatment is individualized. This report describes a 49-year-old female patient with HIV who was diagnosed with high-risk APL with a new CK translocation and presents a literature review. At diagnosis, the patient presented with typical t(15;17)(q24;q21) with additional abnormalities, including add(5)(q15), add(5)(q31), add(7)(q11.2) and add(12) (p13). The results of acute myeloid leukemia mutation analysis suggested positivity for calreticulin and lysine methyltransferase 2C genes. The patient received all-trans retinoic acid combined with arsenic trioxide and chemotherapy, with morphologically complete remission after the first cycle of chemotherapy. The present report provided preliminary data for future clinical research.

DNA polymerase beta connects tumorigenicity with the circadian clock in liver cancer through the epigenetic demethylation of Per1

The circadian-controlled DNA repair exhibits a strong diurnal rhythm. Disruption in circadian clock and DNA repair is closely linked with hepatocellular carcinoma (HCC) progression, but the mechanism remains unknown. Here, we show that polymerase beta (POLB), a critical enzyme in the DNA base excision repair pathway, is rhythmically expressed at the translational level in mouse livers. Hepatic POLB dysfunction dampens clock homeostasis, whereas retards HCC progression, by mediating the methylation of the 4th CpG island on the 5'UTR of clock gene Per1. Clinically, POLB is overexpressed in human HCC samples and positively associated with poor prognosis. Furthermore, the hepatic rhythmicity of POLB protein expression is orchestrated by Calreticulin (CALR). Our findings provide important insights into the molecular mechanism underlying the synergy between clock and food signals on the POLB-driven BER system and reveal new clock-dependent carcinogenetic effects of POLB. Therefore, chronobiological modulation of POLB may help to promote precise interventions for HCC.

Integrative and Comprehensive Pan-Cancer Analysis of Lymphocyte-Specific Protein Tyrosine Kinase in Human Tumors

Lymphocyte-specific protein tyrosine kinase (LCK) is common in a variety of hematologic malignancies but comparatively less common in solid tumors. This study aimed to explore the potential diagnostic and prognostic value of LCK across tumors through integrative and comprehensive pan-cancer analysis, as well as experimental validation. Multiple databases were used to explore the expression, alteration, prognostic value, association with immune infiltration, and potential functional pathways of LCK in pan-cancers. The results were further validated by western blotting and qPCR of patient samples as well as tumor cell lines. High LCK expression typically represents a better prognosis. Notably, drug sensitivity prediction of LCK identified P-529 as a candidate for drug development. Gene Annotations (GO) and KEGG analyses showed significant enrichment of PD-L1 and the T-cell receptor pathway. The results from patient samples and tumor cell lines confirmed these conclusions in LIHC. In conclusion, LCK is differentially expressed in multiple tumors and normal tissues. Further analysis highlighted its association with prognostic implications, pan-cancer genetic alterations, and immune signatures. Our data provide evidence for a diagnostic marker of LCK and the possible use of LCK as a target for the treatment of tumors.

An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine learning

Background

Immunogenic Cell Death (ICD) is a novel way to regulate cell death and can sufficiently activate adaptive immune responses. Its role in immunity is still emerging. However, the involvement of ICD in Intracranial Aneurysms (IA) remains unclear. This study aimed to identify biomarkers associated with ICDs and determine the relationship between them and the immune microenvironment during the onset and progression of IA

Methods

The IA gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in IA were identified and the effects of the ICD on immune microenvironment signatures were studied. Techniques like Lasso, Bayes, DT, FDA, GBM, NNET, RG, SVM, LR, and multivariate analysis were used to identify the ICD gene signatures in IA. A consensus clustering algorithm was used for conducting the unsupervised cluster analysis of the ICD patterns in IA. Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.

Results

The above techniques were used for establishing the ICD gene signatures of HMGB1, HMGN1, IL33, BCL2, HSPA4, PANX1, TLR9, CLEC7A, and NLRP3 that could easily distinguish IA from normal samples. The unsupervised cluster analysis helped in identifying three ICD gene patterns in different datasets. Gene enrichment analysis revealed that the IA samples showed many differences in pathways such as the cytokine-cytokine receptor interaction, regulation of actin cytoskeleton, chemokine signaling pathway, NOD-like receptor signaling pathway, viral protein interaction with the cytokines and cytokine receptors, and a few other signaling pathways compared to normal samples. In addition, the three ICD modification modes showed obvious differences in their immune microenvironment and the biological function pathways. Eight ICD-regulators were identified and showed meaningful associations with IA, suggesting they could severe as potential prognostic biomarkers.

Conclusions

A new gene signature for IA based on ICD features was created. This signature shows that the ICD pattern and the immune microenvironment are closely related to IA and provide a basis for optimizing risk monitoring, clinical decision-making, and developing novel treatment strategies for patients with IA.

Artificial Intelligence Techniques to Predict the Airway Disorders Illness: A Systematic Review

Airway disease is a major healthcare issue that causes at least 3 million fatalities every year. It is also considered one of the foremost causes of death all around the globe by 2030. Numerous studies have been undertaken to demonstrate the latest advances in artificial intelligence algorithms to assist in identifying and classifying these diseases. This comprehensive review aims to summarise the state-of-the-art machine and deep learning-based systems for detecting airway disorders, envisage the trends of the recent work in this domain, and analyze the difficulties and potential future paths. This systematic literature review includes the study of one hundred fifty-five articles on airway diseases such as cystic fibrosis, emphysema, lung cancer, Mesothelioma, covid-19, pneumoconiosis, asthma, pulmonary edema, tuberculosis, pulmonary embolism as well as highlights the automated learning techniques to predict them. The study concludes with a discussion and challenges about expanding the efficiency and machine and deep learning-assisted airway disease detection applications.