ObjectiveThis study was conducted in order to establish a long non-coding RNA (lncRNA)-based model for predicting overall survival (OS) in patients with lung adenocarcinoma (LUAD).MethodsOriginal RNA-seq data of LUAD samples were extracted from The Cancer Genome Atlas (TCGA) database. Univariate Cox survival analysis was performed to select lncRNAs associated with OS. The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox analysis were performed for building an OS-associated lncRNA prognostic model. Moreover, receiver operating characteristic (ROC) curves were generated to assess predictive values of the hub lncRNAs. Consequently, qRT-PCR was conducted to validate its prognostic value. The potential roles of these lncRNAs in immunotherapy and anti-angiogenic therapy were also investigated.ResultsThe lncRNA-associated risk score of OS (LARSO) was established based on the LASSO coefficient of six individual lncRNAs, including CTD-2124B20.2, CTD-2168K21.1, DEPDC1-AS1, RP1-290I10.3, RP11-454K7.3, and RP11-95M5.1. Kaplan–Meier analysis revealed that LUAD patients with higher LARSO values had a shorter OS. Furthermore, a new risk score (NRS), including LARSO, stage, and N stage, could better predict the prognosis of LUAD patients compared with LARSO alone. Evaluation of the prognostic model in our cohort demonstrated that patients with higher scores had a worse prognosis. In addition, correlation analysis between these six lncRNAs and immune checkpoints or anti-angiogenic targets suggested that LUAD patients with high LARSO might not be sensitive to immunotherapy or anti-angiogenic therapy.ConclusionsThis robust six-lncRNA prognostic signature may be used as a novel and powerful prognostic biomarker for lung adenocarcinoma.
Cancer is one of the main causes of disease-related deaths in the world. Although cancer treatment strategies have been improved in recent years, the survival time of cancer patients is still far from satisfied. Cancer immunotherapy, such as Oncolytic virotherapy, Immune checkpoints inhibition, Chimeric antigen receptor T (CAR-T) cell therapy, Chimeric antigen receptor natural killer (CAR-NK) cell therapy and macrophages genomic modification, has emerged as an effective therapeutic strategy for different kinds of cancer. However, many patients do not respond to the cancer immunotherapy which warrants further investigation to optimize this strategy. The clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9), as a versatile genome engineering tool, has become popular in the biology research field and it was also applied to optimize tumor immunotherapy. Moreover, CRISPR-based high-throughput screening can be used in the study of immunomodulatory drug resistance mechanism. In this review, we summarized the development as well as the application of CRISPR/Cas9 technology in the cancer immunotherapy and discussed the potential problems that may be caused by this combination.
Background: Several studies reported improved outcomes with conventional treatments (CT, i.e., chemotherapy ± targeted therapy) administered after immune checkpoints inhibitors (ICI) in certain tumor types. No data are available concerning patients (pts) with metastatic colorectal cancer (mCRC) harboring mismatch repair deficiency/microsatellite instability (dMMR/MSI). We aimed to assess the outcomes of dMMR/MSI mCRC pts receiving CT after ICI failure. Methods: We conducted a retrospective multicenter study investigating the outcomes of all dMMR/MSI mCRC pts who received post-ICI CT between 2015 and 2020. Results: 31 pts (male 61%, median age 56 years) were included. ICI was an anti-PD(L)1 monotherapy in 71% of pts, and 61% received >2 lines before post-ICI CT. The overall response rate and disease control rate were 13% and 45%, with a median progression-free survival (PFS) and overall survival of 2.9 and 7.4 months, respectively. No association of the outcomes with either ICI efficacy or anti-angiogenic agents was observed. Prolonged PFS (range 16.1–21.3 months) was observed in 4 pts (13%). Conclusions: Although conducted on a limited number of patients, our results do not support an association of previous ICI treatment with an enhanced efficacy of CT in dMMR/MSI mCRC. However, prolonged disease control was observed in several cases, suggesting that some pts might derive an unexpected benefit from post-ICI treatments.
Objective: Advancing age is a major risk factor of atherosclerosis (AS). Nevertheless, the mechanism underlying this phenomenon remains indistinct. Herein, this study conducted a comprehensive analysis of the biological implications of aging-related genes in AS.Methods: Gene expression profiles of AS and non-AS samples were curated from the GEO project. Differential expression analysis was adopted for screening AS-specific aging-related genes. LASSO regression analysis was presented for constructing a diagnostic model, and the discriminatory capacity was evaluated with ROC curves. Through consensus clustering analysis, aging-based molecular subtypes were conducted. Immune levels were estimated based on the expression of HLAs, immune checkpoints, and immune cell infiltrations. Key genes were then identified via WGCNA. The effects of CEBPB knockdown on macrophage polarization were examined with western blotting and ELISA. Furthermore, macrophages were exposed to 100 mg/L ox-LDL for 48 h to induce macrophage foam cells. After silencing CEBPB, markers of cholesterol uptake, esterification and hydrolysis, and efflux were detected with western blotting.Results: This study identified 28 AS-specific aging-related genes. The aging-related gene signature was developed, which could accurately diagnose AS in both the GSE20129 (AUC = 0.898) and GSE43292 (AUC = 0.685) datasets. Based on the expression profiling of AS-specific aging-related genes, two molecular subtypes were clustered, and with diverse immune infiltration features. The molecular subtype–relevant genes were obtained with WGCNA, which were markedly associated with immune activation. Silencing CEBPB triggered anti-inflammatory M2-like polarization and suppressed foam cell formation.Conclusion: Our findings suggest the critical implications of aging-related genes in diagnosing AS and modulating immune infiltrations.
Background: Pyroptosis is a newly recognized form of cell death. Emerging evidence has suggested the crucial role of long non-coding RNAs (lncRNAs) in the tumorigenesis and progression of ovarian cancer (OC). However, there is still poor understanding of pyroptosis-related lncRNAs in OC.Methods: The TCGA database was accessed for gene expression and clinical data of 377 patients with OC. Two cohorts for training and validation were established by random allocation. Correlation analysis and Cox regression analysis were performed to identify pyroptosis-related lncRNAs and construct a risk model.Results: Six pyroptosis-related lncRNAs were included in the final signature with unfavorable survival data. Subsequent ROC curves showed promising predictive value of patient prognosis. Further multivariate regression analyses confirmed the signature as an independent risk factor in the training (HR: 2.242, 95% CI: 1.598–3.145) and validation (HR: 1.884, 95% CI: 1.204–2.95) cohorts. A signature-based nomogram was also established with a C-index of.684 (95% CI: 0.662–0.705). Involvement of the identified signature in multiple immune-related pathways was revealed by functional analysis. Moreover, the signature was also associated with higher expression of three immune checkpoints (PD-1, B7-H3, and VSIR), suggesting the potential of the signature as an indicator for OC immunotherapies.Conclusion: This study suggests that the identified pyroptosis-related lncRNA signature and signature-based nomogram may serve as methods for risk stratification of OC. The signature is also associated with the tumor immune microenvironment, potentially providing an indicator for patient selection of immunotherapy in OC.
BackgroundImmune checkpoint inhibitor (ICI) therapy dramatically prolongs melanoma survival. Currently, the identified ICI markers are sometimes ineffective. The objective of this study was to identify novel determinants of ICI efficacy.MethodsWe comprehensively curated pretreatment somatic mutational profiles and clinical information from 631 melanoma patients who received blockade therapy of immune checkpoints (i.e., CTLA-4, PD-1/PD-L1, or a combination). Significantly mutated genes (SMGs), mutational signatures, and potential molecular subtypes were determined. Their association with ICI responses was assessed simultaneously.ResultsWe identified 27 SMGs, including four novel SMGs (COL3A1, NRAS, NARS2, and DCC) that are associated with ICI efficacy and well-known driver genes. COL3A1 mutations were associated with improved ICI overall survival (hazard ratio (HR): 0.64, 95% CI: 0.45–0.91, p = 0.012), whereas immune resistance was observed in patients with NRAS mutations (HR: 1.42, 95% CI: 1.10–1.82, p = 0.006). The presence of the tobacco smoking-related signature was significantly correlated with inferior prognoses (HR: 1.42, 95% CI: 1.11–1.82, p = 0.005). In addition, the signature resembling that of alkylating agents and a newly discovered signature both exhibited extended prognoses (both HR < 1, p < 0.05). Based on the activities of the extracted 6 mutational signatures, we identified one immune subtype that was significantly associated with better ICI outcomes (HR: 0.44, 95% CI: 0.23–0.87, p = 0.017).ConclusionWe uncovered several novel SMGs and re-annotated mutational signatures that are linked to immunotherapy response or resistance. In addition, an immune subtype was found to exhibit favorable prognoses. Further studies are required to validate these findings.