Percutaneous transluminal balloon angioplasty with a large balloon is a safe and effective treatment that could provide excellent rates of long-term patency and survival for the majority of Chinese patients with BCS and HVO.
Background: Recent evidence demonstrates that pyroptosis-derived long non-coding RNAs (lncRNAs) have profound impacts on the initiation, progression, and microenvironment of tumors. However, the roles of pyroptosis-derived lncRNAs (PDLs) in gastric cancer (GC) remain elusive.Methods: We comprehensively analyzed the multi-omics data of 839 GC patients from three independent cohorts. The previous gene set enrichment analysis embedding algorithm was utilized to identify PDLs. A gene pair pipeline was developed to facilitate clinical translation via qualitative relative expression orders. The LASSO algorithm was used to construct and validate a pyroptosis-derived lncRNA pair prognostics signature (PLPPS). The associations between PLPPS and multi-omics alteration, immune profile, and pharmacological landscape were further investigated.Results: A total of 350 PDLs and 61,075 PDL pairs in the training set were generated. Cox regression revealed 15 PDL pairs associated with overall survival, which were utilized to construct the PLPPS model via the LASSO algorithm. The high-risk group demonstrated adverse prognosis relative to the low-risk group. Remarkably, genomic analysis suggested that the lower tumor mutation burden and gene mutation frequency (e.g., TTN, MUC16, and LRP1B) were found in the high-risk group patients. The copy number variants were not significantly different between the two groups. Additionally, the high-risk group possessed lower immune cell infiltration abundance and might be resistant to a few chemotherapeutic drugs (including cisplatin, paclitaxel, and gemcitabine).Conclusion: PDLs were closely implicated in the biological process and prognosis of GC, and our PLPPS model could serve as a promising tool to advance prognostic management and personalized treatment of GC patients.
BackgroundFormation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA.MethodsWe analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index).ResultsA total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells.ConclusionEGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells.
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