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Journal of Biosciences 2024Cystic fibrosis (CF) is a life-threatening monogenic disease affecting thousands of people worldwide. Cystic fibrosis transmembrane conductance regulator (CFTR) is an... (Review)
Review
Cystic fibrosis (CF) is a life-threatening monogenic disease affecting thousands of people worldwide. Cystic fibrosis transmembrane conductance regulator (CFTR) is an ion channel that facilitates transportation of water and salts across epithelial cell membranes through the conductance of Cl and other anions. A dysfunctional CFTR due to abnormalities in the gene causes CF, which is believed to be a rare disease in India mainly due to mis/underdiagnosis. Although numerous diagnostic methods and treatment options are available for CF globally, most of these are unaffordable for developing countries like India. Currently, CF symptoms are managed with mucolytics, antibiotics, anti-inflammatory drugs, and various CFTR modulators based on the type of defect. While a definitive cure for CF remains elusive, advancements in stem cell and gene therapies hold promise for permanent cure in the near future. In this review, we discuss the prevalence of CF cases in India, affordable diagnostic methods, and treatment options amenable for developing countries. We further emphasize the scope for the universal newborn screening programme.
Topics: Cystic Fibrosis; Humans; India; Cystic Fibrosis Transmembrane Conductance Regulator; Developing Countries; Genetic Therapy; Neonatal Screening; Infant, Newborn; Mutation
PubMed: 38920104
DOI: No ID Found -
Frontiers in Immunology 2024The transitory emergence of myeloid-derived suppressor cells (MDSCs) in infants is important for the homeostasis of the immune system in early life. The composition and...
The transitory emergence of myeloid-derived suppressor cells (MDSCs) in infants is important for the homeostasis of the immune system in early life. The composition and functional heterogeneity of MDSCs in newborns remain elusive, hampering the understanding of the importance of MDSCs in neonates. In this study, we unraveled the maturation trajectory of polymorphonuclear (PMN)-MDSCs from the peripheral blood of human newborns by performing single-cell RNA sequencing. Results indicated that neonatal PMN-MDSCs differentiated from self-renewal progenitors, antimicrobial PMN-MDSCs, and immunosuppressive PMN-MDSCs to late PMN-MDSCs with reduced antimicrobial capacity. We also established a simple framework to distinguish these distinct stages by CD177 and CXCR2. Importantly, preterm newborns displayed a reduced abundance of classical PMN-MDSCs but increased late PMN-MDSCs, consistent with their higher susceptibility to infections and inflammation. Furthermore, newborn PMN-MDSCs were distinct from those from cancer patients, which displayed minimum expression of genes about antimicrobial capacity. This study indicates that the heterogeneity of PMN-MDSCs is associated with the maturity of human newborns.
Topics: Humans; Myeloid-Derived Suppressor Cells; Infant, Newborn; Single-Cell Analysis; Receptors, Interleukin-8B; Gene Expression Profiling; Transcriptome; Neutrophils; GPI-Linked Proteins; Cell Differentiation; Female; Male; Isoantigens; Receptors, Cell Surface
PubMed: 38919617
DOI: 10.3389/fimmu.2024.1367230 -
World Journal of Surgical Oncology Jun 2024Prior research exploring the correlation between the XRCC3 Thr241Met polymorphism and the susceptibility to pancreatic cancer has yielded conflicting outcomes. To date,... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Prior research exploring the correlation between the XRCC3 Thr241Met polymorphism and the susceptibility to pancreatic cancer has yielded conflicting outcomes. To date, there has been a notable absence of studies examining this polymorphism. The primary aim of the current investigation is to elucidate the potential role of the XRCC3 Thr241Met polymorphism as a risk factor in the development of pancreatic cancer.
METHODS
The comprehensive literature search was meticulously conducted across primary databases, including PubMed, Embase, and CNKI (China National Knowledge Infrastructure), spanning from the inception of each database through January 2024. To synthesize the data, a meta-analysis was performed using either a fixed or random-effects model, as appropriate, to calculate the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs).
RESULTS
The analysis revealed significant associations between the XRCC3 Thr241Met polymorphism and an increased risk of pancreatic cancer. This was evidenced through various genetic model comparisons: allele contrast (T vs. C: OR = 0.77, 95% CI = 0.70-0.86, P < 0.001), homozygote comparison (TT vs. CC: OR = 0.71, 95% CI = 0.58-0.88, P = 0.001), heterozygote comparison (TC vs. CC: OR = 0.67, 95% CI = 0.52-0.87, P = 0.003), and a dominant genetic model (TT/TC vs. CC: OR = 0.68, 95% CI = 0.57-0.81, P < 0.001). Additionally, subgroup analyses based on ethnicity disclosed that these associations were particularly pronounced in the Caucasian population, with all genetic models showing significance (P < 0.05).
CONCLUSIONS
The XRCC3 Thr241Met polymorphism has been identified as contributing to a reduced risk of pancreatic cancer in the Caucasian population. This finding underscores the need for further research to validate and expand upon our conclusions, emphasizing the urgency for continued investigations in this domain.
Topics: Humans; Pancreatic Neoplasms; Genetic Predisposition to Disease; DNA-Binding Proteins; Polymorphism, Single Nucleotide; Prognosis; Risk Factors; DNA Repair; Case-Control Studies
PubMed: 38918791
DOI: 10.1186/s12957-024-03450-1 -
Scientific Reports Jun 2024Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the...
Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple layers of biomedical information, such as different Omics, may allow more accurate understanding of complex diseases such as T2D. Our aim was to explore and use Machine Learning to integrate multiple sources of biological/molecular information (multiOmics), in our case RNA-sequening, DNA methylation, SNP and phenotypic data from islet donors with T2D and non-diabetic controls. We exploited Machine Learning to perform multiOmics integration of DNA methylation, expression, SNPs, and phenotypes from pancreatic islets of 110 individuals, with ~ 30% being T2D cases. DNA methylation was analyzed using Infinium MethylationEPIC array, expression was analyzed using RNA-sequencing, and SNPs were analyzed using HumanOmniExpress arrays. Supervised linear multiOmics integration via DIABLO based on Partial Least Squares (PLS) achieved an accuracy of 91 ± 15% of T2D prediction with an area under the curve of 0.96 ± 0.08 on the test dataset after cross-validation. Biomarkers identified by this multiOmics integration, including SACS and TXNIP DNA methylation, OPRD1 and RHOT1 expression and a SNP annotated to ANO1, provide novel insights into the interplay between different biological mechanisms contributing to T2D. This Machine Learning approach of multiOmics cross-sectional data from human pancreatic islets achieved a promising accuracy of T2D prediction, which may potentially find broad applications in clinical diagnostics. In addition, it delivered novel candidate biomarkers for T2D and links between them across the different Omics.
Topics: Humans; Diabetes Mellitus, Type 2; Machine Learning; DNA Methylation; Islets of Langerhans; Polymorphism, Single Nucleotide; Male; Female; Middle Aged; Biomarkers; Adult; Aged
PubMed: 38918439
DOI: 10.1038/s41598-024-64846-3 -
Nature Communications Jun 2024Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations...
Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles offer a comprehensive view of drug mechanisms, inherent noise often obscures the true signal, hindering their potential for meaningful insights. Here, we highlight the development of TranSiGen, a deep generative model employing self-supervised representation learning. TranSiGen analyzes basal cell gene expression and molecular structures to reconstruct chemical-induced transcriptional profiles with high accuracy. By capturing both cellular and compound information, TranSiGen-derived representations demonstrate efficacy in diverse downstream tasks like ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. Notably, in vitro validation of TranSiGen's application in pancreatic cancer drug discovery highlights its potential for identifying effective compounds. We envisage that integrating TranSiGen into the drug discovery and mechanism research holds significant promise for advancing biomedicine.
Topics: Drug Discovery; Humans; Deep Learning; Phenotype; Drug Repositioning; Pancreatic Neoplasms; Transcriptome; Gene Expression Profiling; Antineoplastic Agents; Artificial Intelligence
PubMed: 38918369
DOI: 10.1038/s41467-024-49620-3 -
Endoscopy Dec 2024
Topics: Humans; Stents; Pancreatitis, Acute Necrotizing; Male; Middle Aged; Drainage
PubMed: 38917979
DOI: 10.1055/a-2335-6707 -
Rhode Island Medical Journal (2013) Jul 2024The molecular pathogenesis of exocrine pancreatic cancer involves mutations K-RAS, TP53, CDKN2A, and SMAD4. The KRAS oncogene leads to constitutively active tumor cell... (Review)
Review
The molecular pathogenesis of exocrine pancreatic cancer involves mutations K-RAS, TP53, CDKN2A, and SMAD4. The KRAS oncogene leads to constitutively active tumor cell proliferation and is present in 90% of unresectable or metastatic pancreatic adenocarcinomas. Of these, the G12C variant of K-RAS genes accounts for 1-2% of mutations. A 65-year-old woman initially diagnosed with T3N0M0 pancreatic adenocarcinoma, underwent six cycles of neoadjuvant chemotherapy with mFOLFIRINOX followed by Whipple procedure. Her pathological stage was T4N2. She then received adjuvant mFOLFIRINOX but unfortunately her disease progressed through multiple lines of chemotherapy. Molecular analysis by Next Generation Sequence(NGS) panel revealed KRAS G12C mutation. Based on this mutational status, she was started on Sotorasib to which she had clinical response lasting for about 11 months prior to disease progression. Off-label use of Sotorasib as fourth-line treatment in our patient with KRAS G12C mutated pancreatic cancer was efficacious and relatively well tolerated.
Topics: Humans; Pancreatic Neoplasms; Female; Aged; Adenocarcinoma; Triazoles; Antineoplastic Combined Chemotherapy Protocols; Proto-Oncogene Proteins p21(ras); Pyrimidines; Mutation; Antineoplastic Agents; Irinotecan; Oxaliplatin; Fluorouracil; Leucovorin; Off-Label Use; Piperazines; Pyridines
PubMed: 38917307
DOI: No ID Found -
PloS One 2024Periodontitis is a highly prevalent complication of diabetes. However, the association between cystic fibrosis-related diabetes (CFRD) and periodontitis has not yet been...
OBJECTIVES
Periodontitis is a highly prevalent complication of diabetes. However, the association between cystic fibrosis-related diabetes (CFRD) and periodontitis has not yet been evaluated. The objective of this study was to assess if: 1) CFRD is associated with periodontitis among adults with CF, and 2) periodontitis prevalence differs by CF and diabetes status.
METHODS
This was a pilot cross-sectional study of the association between CFRD and periodontitis in adults with cystic fibrosis (CF) (N = 32). Historical non-CF controls (N = 57) from the U.S. National Health and Nutrition Examination Survey (NHANES) dataset were frequency matched to participants with CF on age, sex, diabetes status, and insulin use. We defined periodontitis using the U.S. Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) case definition, as the presence of two or more interproximal sites with CAL ≥3 mm and two or more interproximal sites with PD ≥4 mm (not on the same tooth) or one site with PD ≥5 mm. Because NHANES periodontal data were only available for adults ages ≥30 years, our analysis that included non-CF controls focused on this age group (CF N = 19, non-CF N = 57). Based on CF and diabetes status, we formed four groups: CFRD, CF and no diabetes, non-CF with diabetes, and non-CF and no diabetes (healthy). We used the Fisher's exact test for hypotheses testing.
RESULTS
There was no association between CFRD and periodontitis for participants with CF ages 22-63 years (CFRD 67% vs. CF no diabetes 53%, P = 0.49), this was also true for those ages ≥30 years (CFRD 78% vs. CF no diabetes 60%, P = 0.63). For the two CF groups, the prevalence of periodontitis was significantly higher than for healthy controls (CFRD 78% vs. healthy 7%, P<0.001; CF no diabetes 60% vs. healthy 7%, P = 0.001) and not significantly different than the prevalence for non-CF controls with diabetes (CFRD 78% vs. non-CF with diabetes 56%, P = 0.43; CF no diabetes 60% vs. non-CF with diabetes 56%, P = 0.99).
CONCLUSION
Among participants with CF, CFRD was not associated with periodontitis. However, regardless of diabetes status, participants with CF had increased prevalence of periodontitis compared to healthy controls.
Topics: Humans; Cross-Sectional Studies; Periodontitis; Male; Adult; Cystic Fibrosis; Female; Pilot Projects; Diabetes Mellitus; Prevalence; Middle Aged; Diabetes Complications; Young Adult
PubMed: 38917148
DOI: 10.1371/journal.pone.0305975 -
International Journal of... Apr 2024Microbiological diagnosis of mycobacteriosis is often difficult, as it is necessary to differentiate between transient colonization and active infection.
Construction of Composite Correlation Index Matrix and Analysis of Cultural Properties of Representatives of Mycobacterium abscessus Complex Isolated from Patients with Cystic Fibrosis.
BACKGROUND
Microbiological diagnosis of mycobacteriosis is often difficult, as it is necessary to differentiate between transient colonization and active infection.
METHODS
We studied the cultural properties of Mycobacterium abscessus complex (MABSc) strains obtained from cystic fibrosis patients, and also analyzed composite correlation index (CCI) values in patients with repeated MABSc inoculation and their correlation with the presence of clinical and radiological manifestations of mycobacteriosis.
RESULTS
As a result, MABSc more often grew in S-form colonies in patients without clinical manifestations of chronic infection, while R-form colonies were characteristic of patients with chronic infection and clinical symptoms. At the same time, in patients examined once, no growth of colonies in the R-form was recorded, and all strains produced growth in the form of either S-colonies or in the S- and R-forms simultaneously. Statistically significant results were obtained for the relationship of the CCI with the clinical and radiological picture. In addition, a heterogeneous MABSc population with low CCI score values correlated with the development of mycobacteriosis in patients. In patients with high CCI score values (homogeneity of isolated strains), on the contrary, there were no radiological or clinical signs of the disease.
CONCLUSION
These data make it possible to build a strategy for monitoring patients depending on changes in CCI score values. The use of CCI matrix to evaluate microorganisms' identification results is a potentially new method that expands the use of matrix-assisted laser desorption ionization time-of-flight mass spectrometry.
Topics: Humans; Cystic Fibrosis; Mycobacterium abscessus; Mycobacterium Infections, Nontuberculous; Female; Male
PubMed: 38916382
DOI: 10.4103/ijmy.ijmy_70_24 -
Journal of Cancer Research and Clinical... Jun 2024Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its...
Identified γ-glutamyl cyclotransferase (GGCT) as a novel regulator in the progression and immunotherapy of pancreatic ductal adenocarcinoma through multi-omics analysis and experiments.
BACKGROUND
Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown.
METHODS
The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT.
RESULTS
Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.
Topics: Humans; Carcinoma, Pancreatic Ductal; Pancreatic Neoplasms; gamma-Glutamylcyclotransferase; Immunotherapy; Disease Progression; Cell Proliferation; Prognosis; Cell Line, Tumor; Biomarkers, Tumor; Female; Gene Expression Regulation, Neoplastic; Male; Cell Movement; Multiomics
PubMed: 38914714
DOI: 10.1007/s00432-024-05789-0