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. The genetic alteration of MALAT1 and H19 and the association between gene expression and immune status in GC were also investigated using bioinformatics analysis. RESULTS: Higher genetic methylations in peripheral blood were noticed in GC groups with poorer survival. The constructed nomograms presented strong predictive values for the chemotherapy effect and 3-year survival of disease-free survival, progression-free survival, and overall survival, with the area under the curve as 0.838, 0.838, 0.912, and 0.925, respectively. Significant correlations between MALAT1 or H19 expression and marker genes of immune checkpoints and immune pathways were noticed. The high infiltration of macrophages in H19-high and low infiltration of CD8+ T cells in MALAT1-high groups were associated with worse survival of GC. CONCLUSIONS: MALAT1 and H19 have the potential to predict the chemotherapy response and clinical outcomes of GC.

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. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment 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. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis. RESULTS: The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC. CONCLUSION: The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

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. Herein, we identified 11 CSRLs (AC004918.5, AC103858.1, AC245100.4, ACBD3-AS1, AL441992.2, ATP2A1-AS1, CCDC18-AS1, LINC00996, TMEM161B-AS1, RP11-706O15.1, and SMURF2P1) to build the CSRLs risk model, which was confirmed to be highly associated with overall survival (OS) of MM patients. We further demonstrated the strong prognostic value of the risk model in MM patients receiving different regimens, especially for those with three-drug combination of bortezomib, lenalidomide, and dexamethasone (VRd) as first-line therapy. Not only that, our risk model also excels in predicting the OS of MM patients at 1, 2, and 3 years. In order to verify the function of these CSRLs in MM, we selected the lncRNA ATP2A1-AS1 which presented the largest expression difference between high-risk groups and low-risk groups for subsequent analysis and validation. Finally, we found that down-regulation of ATP2A1-AS1 can promote cellular senescence in MM cell lines. In conclusion, the CSRLs risk model established in present study provides a novel and more accurate method for predicting MM patients' prognosis and identifies a new target for MM therapeutic intervention.

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. METHODS: Data on SHS was extracted from the Global Burden of Disease Study 2019. First, we measured the disease burden of SHS by the number of cases and age-standardized rates of deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) from 1990 to 2019. Second, trends in the disease burden of SHS in different periods were estimated based on the annual percentage change (APC) by joinpoint regression analysis. Finally, using histogram plots, world maps, Pearson correlation analysis, and population attributable fraction (PAF), we conducted a stratified analysis of SHS exposure by sex, age, geographic location, sociodemographic index (SDI) level, and disease. RESULTS: The number of deaths caused by SHS remained stable between 1990 and 2019, and the number of YLDs more than doubled in three decades. In contrast, the number of DALYs and YLLs caused by SHS decreased. The declining trend in deaths (APC = -1.42 % [95 % UI -1.79 %, -1.05 %]), DALYs (APC = -1.91 % [95 % UI -2.15 %, -1.67 %]), and YLLs (APC = -1.28 % [95 % UI -1.93 %, -0.64 %]) had slowed down in recent years, while SHS-related YLDs were still increasing (APC = 1.84 % [95 % UI 0.74 %, 2.96 %]). From 2010 to 2019, we found that SHS exposure increased the risk of tracheal, bronchus, and lung cancer (PAF increased by 11.75 %), breast cancer (PAF increased by 5.36 %), diabetes mellitus (PAF increased by 8.24 %), and ischemic heart disease (PAF increased by 4.46 %). In addition, the disease burden caused by SHS was highest in middle SDI and low-middle SDI countries. CONCLUSION: The global disease burden attributable to SHS is still severe, and policymakers need to implement more effective measures to reduce the harm of 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. We identified five hub genes in the six primary cell death-related pathways (JUN, NFKB1, CASP3, PARP1, and TP53). We found that CASP3, PARP1, and TP53 were overexpressed in 28, 23, and 27 cancers. The expression of the five genes was associated with the development and prognosis of many cancers. Particularly, JUN, NFKB1, CASP3, and TP53 have prognostic values in Brain Lower Grade Glioma (LGG), while PARP1 and CASP3 could predict the survival outcomes in Adrenocortical carcinoma (ACC). In addition, an extensive association between five genes' expression, DNA methylation, and tumor-immune system interactions was noticed. The five cell death-related hub genes could function as potential biomarkers for various cancers, particularly LGG and ACC. The immunological function analysis of the five genes also proposes new targets for developing immunosuppressants and improving the immunotherapy efficacy of cancers. However, further extensive clinical and experimental research are required to validate their clinical values.

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 (CIs) were calculated using the random-effect model or the fixed-effect model. A total of 26 eligible studies were included. We found that PCOS was significantly associated with endometrial cancer (odds ratios [OR]: 3.66, 95%CI: 2.05-6.54, P < 0.001), but not with ovarian or breast cancer (OR: 1.23, 95%CI: 0.99-1.53, P = 0.059; OR: 0.94, 95%CI: 0.78-1.14, P = 0.551, respectively). However, in subgroups of high-quality studies, cohort studies, younger women (54 years or less or premenopausal), and studies with unadjusted body mass index (BMI), PCOS patients had a significantly higher risk of ovarian cancer. CONCLUSION: These results indicated that PCOS is a significant risk factor for endometrial cancer independent of BMI, but not for breast cancer. PCOS may increase the risk of ovarian cancer in younger women.

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. Methylation levels of H19 or MALAT1 in peripheral blood were compared between 150 GC patients and 100 healthy controls (HCs). Predictive nomograms were constructed among female and male groups for GC diagnosis. The calibration curves, Hosmer-Lemeshow test, and decision curve analysis were also used to examine the nomograms' predictive ability and clinical values. RESULTS: Using multiple online databases, we found that the mRNA expressions of H19 and MALAT1 in tissues were related to the occurrence of GC, and such expressions were associated with immune cell infiltration of GC and negatively correlated with DNA methylation levels of H19 and MALAT1. H19 gene, H19C island, and MALAT1B island, as well as 20 CpG sites were hypermethylated in peripheral blood of GC patients compared with HCs; similar results were also found in female and male groups (P < .05 for all). The combination of H19c3, H19c4, MALAT1b12, and age, as well as the combination of H19b7, H19c1, H19c5, and age in the nomograms could distinguish GC patients from HCs in the female group and male group, respectively. CONCLUSION: We found statistically significant hypermethylation of H19 and MALAT1 promoters in GC patients, and meaningful sensitivity and specificity of MALAT1 and H19 methylation in discriminating GC and HCs were observed in both female and male groups, which indicates that the peripheral blood-based DNA methylation of H19 and MALAT1 could act as potential non-invasive biomarkers for the diagnosis of GC.

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. RESULTS: We found that E2F1/2/4/7/8 were more expressed in chRCC tissues than in normal tissues, while the expression of E2F5/6 was lower in the former than in the latter, and the expression levels of E2F1/2/4/5/6//7/8 were also associated with the histological parameters of chRCC, including T-stage and N-stage. Higher expression of E2F1/2/7/8 was found to be significantly correlated with worse overall survival (OS) in chRCC patients. Cox regression and time-dependent ROC analysis further suggested that E2F1/2 could be the potential independent biomarkers for chRCC prognosis. Besides, a moderate mutation rate of E2Fs (34%) was noticed in chRCC, and the genetic mutations in E2Fs were associated with poor survival of chRCC patients. We noticed that the expression of E2Fs was statistically correlated with the immune cell infiltration in chRCC. Moreover, we also found that the expression of E2F1 was significantly correlated with tumor-infiltrating lymphocytes and immunomodulators, E2F7 expression was associated with MHC molecules, and the expression of E2F1/8 was correlated to their methylation levels. CONCLUSION: Our results provide novel insights for selecting the prognostic biomarkers for chRCC and suggest that E2F1/2 could act as potential prognostic biomarkers for the survival of chRCC patients. However, more in-depth experiments are required to identify the underlying mechanisms and verify the clinical value of E2F1/2 in the prognosis of 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 4.0 software were used to select tag SNPs. Improved multiplex ligase detection reaction was used for genotyping. Data were analyzed using Chi-square test (χ2 test) and univariate and multivariate logistic regression. The results demonstrated that the rs10781582 of BNIP3 in the dominant model was associated with a reduced risk of GC in the younger group (P BH = 0.015), and the minor allele G of rs1329600 at DAPK1 was associated with reduced risk of GC (P BH = 0.018). In the stratified analysis, the rs3793742 and rs10781582 of BNIP3 in the dominant model were associated with gender and age of GC patients, respectively (rs3793742: P BH = 0.033; rs10781582: P BH = 0.030). The rs10781582 of BNIP3 in the dominant model was correlated with depression in GC patients (P BH = 0.003). However, no association was found between BNIP3 and DAPK1 polymorphisms and differentiation degree, TNM stage, lymph node metastases, visceral metastasis, and anxiety. In summary, polymorphisms of BNIP3 and DAPK1 were associated with a protective effect against GC. So far, this is the first study to explore the association between BNIP3 and DAPK1 gene polymorphism and GC risk, which may provide new insight about biologic mechanisms of GC pathogenesis.

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. pylori status regarding their effects over the prognosis of GC patient. MATERIALS AND METHODS: 250 GC tissues and 124 lymph node metastases were collected for the detection of Rictor by immunohistochemistry. Cox regression model was used to assess the association between Rictor expression and patient prognosis. Functional experiments were examined in transfected cells using Rictor siRNA. Additive and multiplicative interactions of Rictor and H. pylori were evaluated. RESULTS: In this study, the positive rate of Rictor was 51.6% (129/150) in GC tissues. Multivariate analyses showed that Rictor was independent unfavorable predictor for OS (HR = 1.554, 95% CI = 1.076-2.244, P = 0.019) and DFS (HR = 1.556, 95% CI = 1.081-2.240, P = 0.017). Patients with upregulated Rictor in the primary tumor and lymph node metastases had the worst prognosis. We observed significant additive and multiplicative interactions between Rictor expression and H. pylori status for OS and DFS (P < 0.05). Our in vitro experiment showed that knockdown of Rictor could suppress cell proliferation, induce apoptosis and inhibit tumor migration and invasion. CONCLUSION: Our results demonstrate that Rictor, acting as an oncogene, might be a potential prognostic biomarker and therapeutic target in GC. We suggest that Rictor expression and H. pylori status may be a prognostic marker in gastric cancer.