Deciphering key roles of B cells in prognostication and tailored therapeutic strategies for lung adenocarcinoma: a multi-omics and machine learning approach towards predictive, preventive, and personalized treatment strategies.

Background: Lung adenocarcinoma (LUAD) remains a significant global health challenge, with an urgent need for innovative predictive, preventive, and personalized medicine (PPPM) strategies to improve patient outcomes. This study leveraged multi-omics and machine learning approaches to uncover the prognostic roles of B cells in LUAD, thereby reinforcing the PPPM approach.

Methods: We integrated multi-omics data, including bulk RNA, ATAC-seq, single-cell RNA, and spatial transcriptomics sequencing, to characterize the B cell landscape in LUAD within the PPPM framework.

Oncofetal MCB1 Is a Functional Biomarker for HCC Personalized Therapy.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide and lacks biomarkers for personalized therapy. Herein, it is reported that MCB1 could be a novel oncofetal protein that is upregulated in the preneoplastic lesions and serum of early HCC patients. Functional studies reveal that MCB1 modulated p53 protein degradation to promote T-IC generation and drive HCC initiation.

DDR1 is a Novel Biomarker and Potential Therapeutic Target for the Combination Treatment of Liver Hepatocellular Carcinoma.

Aim: This study aimed to investigate the role of discoidin domain receptor tyrosine kinase 1 (DDR1) in liver hepatocellular carcinoma (LIHC) and to evaluate its prognostic value on patient response to combination therapy.

Methods: In the current retrospective study, we examined the protein expression of DDR1 in various cancers by standard immunohistochemical (IHC) methods and evaluated its clinical significance in LIHC personalized treatment. Multiple online databases, including The Cancer Genome Atlas (TCGA), TIMER, GEO, ROC Plotter, and Genomics of Drug Sensitivity in Cancer (GDSC), were used.

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and drug response. We utilized 13 PCD pathways, including apoptosis, pyroptosis, ferroptosis, autophagy, necroptosis, cuproptosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis to develop predictive models based on 73 machine learning combinations from 10 algorithms.

Epigallocatechin gallate modulates ferroptosis through downregulation of tsRNA-13502 in non-small cell lung cancer.

Ferroptosis, an iron-dependent regulated cell death mechanism, holds significant promise as a therapeutic strategy in oncology. In the current study, we explored the regulatory effects of epigallocatechin gallate (EGCG), a prominent polyphenol in green tea, on ferroptosis and its potential therapeutic implications for non-small cell lung cancer (NSCLC). Treatment of NSCLC cell lines with varying concentrations of EGCG resulted in a notable suppression of cell proliferation, as evidenced by a reduction in Ki67 immunofluorescence staining.

Predictive value of peripheral blood leukocytes-based methylation of Long non-coding RNA MALAT1 and H19 in the chemotherapy effect and prognosis of gastric cancer.

Background: The predictive value of the methylation of Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and H19 promoters in peripheral blood leukocytes as a non-invasive biomarker for the chemotherapy effect and prognosis gastric cancer (GC) is unclear.

Methods: The DNA methylation of H19 and MALAT1 between chemotherapy-sensitive and non-sensitive groups and between groups with better and worse survival of GC was compared using regression analyses. Several predictive nomograms were constructed.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy.

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer.

Objective: The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment.

Patients And Methods: Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC.

Global, regional, and national burden of digestive diseases: findings from the global burden of disease study 2019.

Background: The global burden of digestive diseases has been rising in the last 30 years. The rates and trends of incidence, deaths, and disability-adjusted life-years (DALYs) for digestive diseases need to be investigated.

Methods: We extracted the data on overall digestive diseases and by cause between 1990-2019 from the Global Burden of Diseases 2019 website, including the absolute number and the corresponding age-standardized rates of incidence (ASIR), deaths (ASDR), and DALYs (ASDALYs).

Identification and validation of a cellular senescence-related lncRNA signature for prognostic prediction in patients with multiple myeloma.

Multiple myeloma (MM) is the second most common hematologic malignancy, which primarily occurs in the elderly. Cellular senescence is considered to be closely associated with the occurrence and progression of malignant tumors including MM, and lncRNA can mediate the process of cellular senescence by regulating key signaling pathways such as p53/p21 and p16/RB. However, the role of cellular senescence related lncRNAs (CSRLs) in MM development has never been reported.

The global burden and trends of four major types of heart disease, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019.

Objectives: The global burden of heart disease is severe and increasing in the coming years. This study aims to analyze the global burden of heart disease.

Study Design: Rheumatic heart disease (RHD), ischemic heart disease (IHD), hypertensive heart disease (HHD), and non-rheumatic valvular heart disease (NRVHD) were selected and analyzed from the Global Burden of Disease Study 2019.

Global, regional, and national deaths, disability-adjusted life years, years lived with disability, and years of life lost for the global disease burden attributable to second-hand smoke, 1990-2019: A systematic analysis for the Global Burden of Disease Study.

Background: Smoke-free policies have led to a decline in smoking prevalence. Nevertheless, as the global population grows, more non-smokers are exposed to second-hand smoke (SHS) hazards. Mitigating SHS hazards requires a systematic analysis of the global disease burden attributable to SHS.

Multimolecular characteristics of cell-death related hub genes in human cancers: a comprehensive pan-cancer analysis.

Failure of the normal process of cell death pathways contributes to the defection of immune systems and the occurrence of cancers. The key genes, the multimolecular mechanisms, and the immune functions of these genes in pan-cancers remain unclear. Using online databases of The Cancer Genome Atlas, GEPIA2, TISIDB, HPA, Kaplan-Meier Plotter, PrognoScan, cBioPortal, GSCALite, TIMER, and Sangerbox, we identified the key genes from the six primary cell death-related pathways and performed a comprehensive analysis to investigate the multimolecular characteristics and immunological functions of the hub genes in 33 human cancers.

Polycystic ovary syndrome and the risk of endometrial, ovarian and breast cancer: An updated meta-analysis.

Background And Aims: This updated meta-analysis aimed to further quantify the risk of endometrial, ovarian, and breast cancer in patients with polycystic ovary syndrome (PCOS), thus providing updated and more reliable estimates.

Methods And Results: We identified relevant articles by searching electronic databases of PubMed, Embase, Web of Science, and Chinese Biological Medical Literature (CBM) published up to March 20, 2021. The pooled effect estimates and their 95% confidence intervals () were calculated using the random-effect model or the fixed-effect model.

Significantly correlation between tourism and COVID-19: evidence from 178 countries and territories.

Introduction: The high development of tourism is considered a factor that facilitates the global spread of infectious diseases. The association between tourism and the epidemic of coronavirus diseases 2019 (COVID-19) remains unclear.

Methodology: We retrieved the data of COVID-19 in 178 countries/territories from the Center for Systems Science and Engineering at Johns Hopkins University.

Peripheral Blood-Based DNA Methylation of Long Non-Coding RNA H19 and Metastasis-Associated Lung Adenocarcinoma Transcript 1 Promoters are Potential Non-Invasive Biomarkers for Gastric Cancer Detection.

Introduction: The early diagnosis and detection could greatly improve the clinical outcome of gastric cancer (GC) patients. However, the non-invasive biomarkers for GC detection remain to be identified.

Method: We used online databases (GEPIA, UALCAN, Kaplan-Meier plotter, TIMER, and MEXPRESS) to explore the association between H19 or metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) expression in tissues and the occurrence, development, prognosis, the levels of immune cell infiltration, and methylation of GC; the correlation between mRNA expression and DNA methylation levels of genes were also examined.

Prognostic Values of E2F1/2 Transcriptional Expressions in Chromophobe Renal Cell Carcinoma Patients: Evidence from Bioinformatics Analysis.

Background: Numerous studies on the E2F transcription factors have led to increasing insights that E2Fs could be an important driver of the formation and progression of many human cancers. Little is known about the function of distinct E2Fs in chromophobe renal cell carcinoma (chRCC).

Methods: We utilized the UALCAN, GEPIA, Cancer Genome Atlas (TCGA) database, cBioPortal, Metascape, STRING, Cytoscape, GeneMANIA, TIMER, TISIDB, GSCALite, and MEXPRESS databases to investigate the transcription level, genetic alteration, methylation, and biological function of E2Fs in chRCC patients, and its association with the occurrence, progress, prognosis, and immune cell infiltration in patients with chRCC.

Associations of BNIP3 and DAPK1 gene polymorphisms with disease susceptibility, clinicopathologic features, anxiety, and depression in gastric cancer patients.

The purpose of this study is to explore the associations of BNIP3 and DAPK1 polymorphisms with disease susceptibility, clinicopathologic characteristics, depression, and anxiety in gastric cancer (GC) patients. In this study, 150 GC patients and 100 healthy controls were recruited. 1000 Genomes database and Haploview 4.

Influence of age and gender on the epidemic of COVID-19 : Evidence from 177 countries and territories-an exploratory, ecological study.

Background: The pandemic of coronavirus disease 2019 (COVID-19) is spreading worldwide with an uncertain ultimate impact on every aspect of human society. Recognizing the groups with higher susceptibility and fatality are in urgent need.

Methods: We retrieved the total number of confirmed incident and death cases of COVID-19 in 177 countries/territories from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU).

Overexpression of Rictor protein and Rictor-H. pylori interaction has impact on tumor progression and prognosis in patients with gastric cancer.

Introduction: Growing evidence indicates that Rictor (Rapamycin-insensitive companion of mTOR) is overexpressed across several malignancies and associated with poor survival. However, only limited data indicate that Rictor plays a role in gastric cancer (GC). We sought to explore the prognostic value of Rictor in GC and present interaction analysis between Rictor expression and H.

More effective strategies are required to strengthen public awareness of COVID-19: Evidence from Google Trends.

Background: The outbreak of coronavirus disease 2019 (COVID-19) has posed stress on the health and well-being of both Chinese people and the public worldwide. Global public interest in this new issue largely reflects people's attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine global public awareness of COVID-19 using Google Trends.