Reduced PLCG1 expression is associated with inferior survival for myelodysplastic syndromes

Deciphering signaling pathways in hematopoietic stem cells: the molecular complexity of Myelodysplastic Syndromes (MDS) and leukemic progression

Myelodysplastic Syndromes, a heterogeneous group of hematological disorders, are characterized by abnormalities in phosphoinositide-dependent signaling, epigenetic regulators, apoptosis, and cytokine interactions within the bone marrow microenvironment, contributing to disease pathogenesis and neoplastic growth. Comprehensive knowledge of these pathways is crucial for the development of innovative therapies that aim to restore normal apoptosis and improve patient outcomes.

Advances in MDS/AML and inositide signalling

Aberrant signaling pathways regulating proliferation and differentiation of hematopoietic stem cells (HSCs) can contribute to disease pathogenesis and neoplastic growth. Phosphoinositides (PIs) are inositol phospholipids that are implicated in the regulation of critical signaling pathways: aberrant regulation of Phospholipase C (PLC) beta1, PLCgamma1 and the PI3K/Akt/mTOR pathway play essential roles in the pathogenesis of Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML).

Construction of a metabolism-related gene prognostic model to predict survival of pancreatic cancer patients

Pancreatic cancer (PC) is one of the most fatal malignant tumors, and is commonly diagnosed at an advanced stage with no effective therapy. Metabolism-related genes (MRGs) and immune-related genes (IRGs) play considerable roles in the tumor microenvironment. Therefore, an effective prediction model based on MRGs and IRGs could aid in the prognosis of PC. In this study, differential expression analysis was performed to gain 25 intersectional genes from 857 differentially expressed MRGs (DEMRGs), and 1353 differentially expressed IRGs, from The Cancer Genome Atlas database of PC. Cox and Lasso regression were applied and a five-DEMRGs prognostic model constructed. Survival analysis, ROC values, risk curve and validation analysis showed that the model could independently predict PC prognosis. In addition, the correlation analysis suggested that the five-DEMRGs prognostic model could reflect the status of the immune microenvironment, including Tregs, M1 macrophages and Mast cell resting. Therefore, our study provides new underlying predictive biomarkers and associated immunotherapy targets.

Identification of the Pyroptosis-Related Prognosis Gene Signature and Immune Infiltration in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignancies worldwide with a dismal prognosis. Lack of efficient biomarkers, early detection, and prognosis is still a challenge for HCC. Pyroptosis is a new discovery inflammatory form of programmed cell death. There is growing evidence revealed that pyroptosis plays a role in physiological and pathological conditions of human cancers. However, the prognostic evaluation of these pyroptosis-related genes (PRGs) in HCC remains blank. Consensus clustering of PRGs was used to classify 374 patients with HCC from the TCGA-LIHC cohort. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, a 2-gene prognostic gene model (PLCG1 and GSDMC) was built and indicated the survival rate in HCC with medium-to-high accuracy. Then, the median risk score from the TCGA cohort was utilized; the prognostic gene model was also accurate in Gene Expression Omnibus (GEO) cohort. The functional enrichment analysis indicated that the oncogenic properties are associated with prominent hallmarks of cancer. The ssGSEA analyses and TIMER database indicated that immune infiltration tumor microenvironment in the HCC. In conclusion, our findings provide a foundation for further research targeting PRGs and their immune microenvironment.

Long noncoding RNAs, ENST00000598996 and ENST00000524265, are correlated with favorable prognosis and act as potential tumor suppressors in bladder cancer

Bladder cancer (BC) is a serious malignancy worldwide due to its distant metastasis and high recurrence rates. Increasing evidence has indicated that dysregulated long non-coding RNAs (lncRNAs) are involved in tumorigenesis and progression in multiple malignancies. However, their clinical significances, biological functions and molecular mechanisms in BC remain poorly understood. Hence, the present study investigated the expression profile of lncRNAs and mRNAs in five BC tissues and the corresponding adjacent normal specimens using high-throughput RNA sequencing (RNA-seq). A total of 103 differentially expressed (DE) lncRNAs were identified, including 35 upregulated and 68 downregulated ones in BC tissues. Similarly, a total of 2,756 DE-mRNAs were detected, including 1,467 upregulated and 1,289 downregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, and lncRNA-miRNA-mRNA network analyses suggested that these dysregulated lncRNAs are potentially implicated in the onset and progression of BC. Subsequently, four lncRNAs (upregulated ENST00000433108; downregulated ENST00000598996, ENST00000524265 and ENST00000398461) and two mRNAs (upregulated CCNB1 and CDK1) in 64 pairs of BC and adjacent normal tissues and four BC cell lines were detected using reverse transcription-quantitative PCR and these results were consistent with the sequencing data. Additionally, Fisher's exact test, Kaplan-Meier plots, and Cox regression analyses were used for elucidating the clinical values of ENST00000598996 and ENST00000524265. Furthermore, a receiver operating characteristic curve was constructed to assess their diagnostic values. The low expression level of ENST00000598996 and ENST00000524265 was correlated with unfavorable clinicopathological parameters, and shorter progression-free and overall survival time, whereas, ENST00000433108 was not associated with either. The in vitro functional experiments also revealed that the overexpression of ENST00000598996 and ENST00000524265 decreased the proliferation, migration, and invasion abilities of BC cells. Collectively, the results of the present study provide a novel landscape of lncRNA and mRNA expression profiles in BC. In addition, the results also indicated that ENST00000598996 and ENST00000524265 may serve as tumor suppressors, potential diagnostic biomarkers and prognostic predictors for patients with BC.

Reduced PLCG1 expression is associated with inferior survival for myelodysplastic syndromes

The PLCG1 gene, which encodes the phospholipase C γ1 isoform, is located within the commonly deleted region of the long arm of chromosome 20 (del(20q)) observed in myelodysplastic syndromes (MDS). Phospholipase C is involved in diverse physiological and pathological cellular processes through inositide signaling. We hypothesized that reduced PLCG1 expression because of haploinsufficiency by del(20q) plays a role in the molecular pathogenesis of MDS. Therefore, we analyzed PLCG1 expression in bone marrow mononuclear cells at diagnosis in 116 MDS patients with or without del(20q) by quantitative RT‐PCR to evaluate its clinical significance. The expression level of PLCG1 was significantly lower not only in MDS patients with del(20q) but also in those without del(20q) compared to that of the controls, which suggests that reduced PLCG1 expression is a common molecular event in MDS. Patients in the lowest quartile (Q4) group for PLCG1 expression had lower overall survival (OS) compared to that of other patients (Q1‐Q3) (log‐rank test, P = .0004) with estimated median OS times of 22 in the Q4 group and 106 months in the Q1‐3 group. Univariate and multivariate analysis indicated reduced PLCG1 expression (Q4) was associated with lower OS (hazard ratio 2.58, 95% CI 1.35‐4.84, P = .0049), which suggests that reduced PLCG1 expression is an independent prognostic factor for OS. In addition, patients were well‐stratified for OS by combining PLCG1 expression level (Q4 vs Q1‐3) and bone marrow blast percentage (5% or more vs less than 5%). Thus, the level of PLCG1 expression at time of diagnosis is a prognostic biomarker for MDS.