Identification of a multidimensional transcriptome prognostic signature for lung adenocarcinoma

Glucose metabolism-based signature predicts prognosis and immunotherapy strategies for colon adenocarcinoma

BACKGROUND

The global prevalence and metastasis rates of colon adenocarcinoma (COAD) are high, and therapeutic success is limited. Although previous research has primarily explored changes in gene phenotypes, the incidence rate of COAD remains unchanged. Metabolic reprogramming is a crucial aspect of cancer research and therapy. The present study aims to develop cluster and polygenic risk prediction models for COAD based on glucose metabolism pathways to assess the survival status of patients and potentially identify novel immunotherapy strategies and related therapeutic targets.

METHODS

COAD-specific data (including clinicopathological information and gene expression profiles) were sourced from The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus (GEO) datasets (GSE33113 and GSE39582). Gene sets related to glucose metabolism were obtained from the MSigDB database. The Gene Set Variation Analysis (GSVA) method was utilized to calculate pathway scores for glucose metabolism. The hclust function in R, part of the Pheatmap package, was used to establish a clustering system. The mutation characteristics of identified clusters were assessed via MOVICS software, and differentially expressed genes (DEGs) were filtered using limma software. Signature analysis was performed using the least absolute shrinkage and selection operator (LASSO) method. Survival curves, survival receiver operating characteristic (ROC) curves and multivariate Cox regression were analyzed to assess the efficacy and accuracy of the signature for prognostic prediction. The pRRophetic program was employed to predict drug sensitivity, with data sourced from the Genomics of Drug Sensitivity in Cancer (GDSC) database.

RESULTS

Four COAD subgroups (i.e., C1, C2, C3 and C4) were identified based on glucose metabolism, with the C4 group having higher survival rates. These four clusters were bifurcated into a new Clust2 system (C1 + C2 + C3 and C4). In total, 2175 DEGs were obtained (C1 + C2 + C3 vs. C4), from which 139 prognosis-related genes were identified. ROC curves predicting 1-, 3- and 5-year survival based on a signature containing nine genes showed an area under the curve greater than 0.7. Meanwhile, the study also found this feature to be an important predictor of prognosis in COAD and accordingly assessed the risk score, with higher risk scores being associated with a worse prognosis. The high-risk and low-risk groups responded differently to immunotherapy and chemotherapeutic agents, and there were differences in functional enrichment pathways.

CONCLUSIONS

This unique signature based on glucose metabolism may potentially provide a basis for predicting patient prognosis, biological characteristics and more effective immunotherapy strategies for COAD.

Novel patients with NHLRC2 variants expand the phenotypic spectrum of FINCA disease

Purpose

FINCA disease (Fibrosis, Neurodegeneration and Cerebral Angiomatosis, OMIM 618278) is an infantile-onset neurodevelopmental and multiorgan disease. Since our initial report in 2018, additional patients have been described. FINCA is the first human disease caused by recessive variants in the highly conserved NHLRC2 gene. Our previous studies have shown that Nhlrc2-null mouse embryos die during gastrulation, indicating the essential role of the protein in embryonic development. Defect in NHLRC2 leads to cerebral neurodegeneration and severe pulmonary, hepatic and cardiac fibrosis. Despite having a structure suggestive of an enzymatic role and the clinical importance of NHLRC2 in multiple organs, the specific physiological role of the protein is unknown.

Methods

The clinical histories of five novel FINCA patients diagnosed with whole exome sequencing were reviewed. Segregation analysis of the biallelic, potentially pathogenic NHLRC2 variants was performed using Sanger sequencing. Studies on neuropathology and NHLRC2 expression in different brain regions were performed on autopsy samples of three previously described deceased FINCA patients.

Results

One patient was homozygous for the pathogenic variant c.442G > T, while the other four were compound heterozygous for this variant and two other pathogenic NHLRC2 gene variants. All five patients presented with multiorgan dysfunction with neurodevelopmental delay, recurrent infections and macrocytic anemia as key features. Interstitial lung disease was pronounced in infancy but often stabilized. Autopsy samples revealed widespread, albeit at a lower intensity than the control, NHLRC2 expression in the brain.

Conclusion

This report expands on the characteristic clinical features of FINCA disease. Presentation is typically in infancy, and although patients can live to late adulthood, the key clinical and histopathological features are fibrosis, infection susceptibility/immunodeficiency/intellectual disability, neurodevelopmental disorder/neurodegeneration and chronic anemia/cerebral angiomatosis (hence the acronym FINCA) that enable an early diagnosis confirmed by genetic investigations.

Integrative Analysis of the Predictive Value of Perilipin Family on Clinical Significance, Prognosis and Immunotherapy of Glioma

Gliomas are common tumors of the central nervous system. The PLINs family is widely involved in the regulation of lipid metabolism and has been associated with the development and invasive metastasis of various malignancies. However, the biological role of the PLINs family in gliomas is still unclear. TIMER and UALCAN were used to assess PLINs mRNA expression in gliomas. “Survminer” and “Survival” were used to evaluate the connection between PLINs expression and glioma patients’ survival. cBioPortal was applied to assess PLINs’ genetic alterations in glioblastoma multiforme (GBM) and low-grade glioma (LGG). The correlation of PLINs expression with tumor immune cells was analyzed by TIMER. The expressions of PLIN1, PLIN4, and PLIN5 were decreased in GBM compared to normal tissues. However, PLIN2 and PLIN3 were significantly increased in GBM. Prognostic analysis showed that LGG patients with high PLIN1 expression had better overall survival (OS), and high expression of PLIN2/3/4/5 was associated with unfavorable OS. We further determined that the expression of PLINs members in gliomas was strongly related to tumor immune cells and immune checkpoint-associated genes. PLINS may be potential biomarkers for regulating the tumor microenvironment and predicting the efficacy of immunotherapy. In addition, we determined that PLIN1 may affect glioma patients’ therapeutic sensitivity to temozolomide. Our results demonstrated the biological significance and clinical values of PLINs in gliomas and provide a basis for future in-depth exploration of the specific mechanisms of each member of PLINs in gliomas.

A telomerase regulation-related lncRNA signature predicts prognosis and immunotherapy response for gastric cancer

BACKGROUND

Telomeres are involved in the development and progression of gastric cancer (GC). However, the association of telomerase regulation-related lncRNAs with prognosis and immunotherapy responsiveness in gastric cancer is unclear.

METHODS

This study systematically evaluated the relationship between lncRNAs co-expressed with 67 telomerase regulatory genes and gastric cancer prognosis. The risk scores of the samples were calculated based on telomerase regulation-related lncRNAs with prognostic value, and the samples were classified into high-/low-risk groups. The prognostic value of risk groups was then evaluated, a GC prognostic prediction model based on risk groups and clinical characteristics was established, and the prediction accuracy of the model was clarified by receiving operating characteristic (ROC) curves and calibration curves. Finally, the value of risk grouping in GC immunotherapy sensitivity was predicted by comparing MSI status and tumor mutation load between the high- and low-risk groups.

RESULTS

We identified 13 lncRNAs with prognostic value co-expressed with telomerase regulatory genes and observed that the prognosis of the low-risk group was significantly better than that of the high-risk group. Meanwhile, a GC overall survival (OS) prediction model based on risk grouping and clinical characteristics was developed, and ROC curves and calibration curves confirmed the good predictive ability of the model. In addition, the low-risk group exhibited a higher tumor mutation load and MSI-H, suggesting a possible benefit of immunotherapy.

CONCLUSION

We found that telomerase regulation-related lncRNAs have prognostic value in GC patients and contribute to the exploration of more effective immunotherapeutic strategies.

NHLRC2 expression is increased in idiopathic pulmonary fibrosis

BACKGROUND

Variants of NHL repeat-containing protein 2 (NHLRC2) have been associated with severe fibrotic interstitial lung disease in early childhood and NHLRC2 has been listed as a differentially expressed gene between rapidly and slowly progressing idiopathic pulmonary fibrosis (IPF) patients. However, its cell type-specific localization in human lung tissue is unknown. The aim of this study was to evaluate NHLRC2 mRNA and protein expression in different cell types of lung tissue samples and to investigate the effect of transforming growth factor (TGF)-β1 exposure on NHLRC2 expression in vitro.

METHODS

The NHLRC2 expression in lung tissue samples was studied by immunohistochemistry (50 IPF, 10 controls) and mRNA in situ hybridization (8 IPF, 3 controls). The immunohistochemical NHLRC2 expression was quantified with image analysis software and associated with the clinical and smoking data of the patients. NHLRC2 expression levels in primary stromal and small airway epithelial cell lines after exposure to TGF-β1 was measured by quantitative reverse transcription polymerase chain reaction and Western blot analysis.

RESULTS

NHLRC2 expression was detected especially in bronchiolar epithelial cells, type II pneumocytes and macrophages in normal lung. In the lungs of IPF patients, NHLRC2 was mainly expressed in hyperplastic alveolar epithelial cells lining fibroblast foci and honeycombs. NHLRC2 expression assessed by image analysis was higher in IPF compared to controls (p < 0.001). Ever-smokers had more prominent NHLRC2 staining than non-smokers (p = 0.037) among IPF patients. TGF-β1 exposure did not influence NHLRC2 levels in lung cell lines.

CONCLUSIONS

NHLRC2 expression was higher in IPF compared to controls being widely expressed in type II pneumocytes, macrophages, bronchiolar epithelium, and hyperplastic alveolar epithelium. Additionally, its expression was not regulated by the exposure to TGF-β1 in vitro. Further studies are needed to clarify the role of NHLRC2 in IPF.

Current and Future Development in Lung Cancer Diagnosis

Lung cancer is the leading cause of cancer-related deaths in North America and other developed countries. One of the reasons lung cancer is at the top of the list is that it is often not diagnosed until the cancer is at an advanced stage. Thus, the earliest diagnosis of lung cancer is crucial, especially in screening high-risk populations, such as smokers, exposure to fumes, oil fields, toxic occupational places, etc. Based on the current knowledge, it looks that there is an urgent need to identify novel biomarkers. The current diagnosis of lung cancer includes different types of imaging complemented with pathological assessment of biopsies, but these techniques can still not detect early lung cancer developments. In this review, we described the advantages and disadvantages of current methods used in diagnosing lung cancer, and we provide an analysis of the potential use of body fluids as carriers of biomarkers as predictors of cancer development and progression.

Understanding the Role of Perilipin 5 in Non-Alcoholic Fatty Liver Disease and Its Role in Hepatocellular Carcinoma: A Review of Novel Insights

Consumption of high-calorie foods, such as diets rich in fats, is an important factor leading to the development of steatohepatitis. Several studies have suggested how lipid accumulation creates a lipotoxic microenvironment for cells, leading cells to deregulate their transcriptional and translational activity. This deregulation induces the development of liver diseases such as non-alcoholic fatty liver disease (NAFLD) and subsequently also the appearance of hepatocellular carcinoma (HCC) which is one of the deadliest types of cancers worldwide. Understanding its pathology and studying new biomarkers with better specificity in predicting disease prognosis can help in the personalized treatment of the disease. In this setting, understanding the link between NAFLD and HCC progression, the differentiation of each stage in between as well as the mechanisms underlying this process, are vital for development of new treatments and in exploring new therapeutic targets. Perilipins are a family of five closely related proteins expressed on the surface of lipid droplets (LD) in several tissues acting in several pathways involved in lipid metabolism. Recent studies have shown that Plin5 depletion acts protectively in the pathogenesis of liver injury underpinning the importance of pathways associated with PLIN5. PLIN5 expression is involved in pro-inflammatory cytokine regulation and mitochondrial damage, as well as endoplasmic reticulum (ER) stress, making it critical target of the NAFLD-HCC studies. The aim of this review is to dissect the recent findings and functions of PLIN5 in lipid metabolism, metabolic disorders, and NAFLD as well as the progression of NAFLD to HCC.

Expression status and prognostic value of the perilipin family of genes in breast cancer

BACKGROUND

The Perilipin (PLIN) family of genes were previously shown to be involved in the formation and degradation of Lipid Droplets (LDs). In addition, they may play important roles in the development and progression of breast cancer. However, the prognostic value of PLIN family members in breast cancer patients remains unclear.

METHODS

Mutations and copy number alterations of PLIN family genes in breast cancer were examined using the cBioportal for Cancer Genomics. In addition, the expression patterns of PLIN family genes were explored using the UCSC Xena online tool. Finally, the Kaplan-Meier Plotter was used to investigate the prognostic value of PLIN family genes in breast cancer.

RESULTS

The findings revealed a low frequency of genetic alterations and amplification was the most frequent change in the PLIN family genes. Additionally, there was an increase in the expression of Perilipin 3 (PLIN3) in breast cancer tissues compared to normal breast tissues. However, expression of the other genes in the PLIN family was significantly lower in breast cancer tissues compared to normal breast tissues. Moreover, there was an increase in the expression levels of Perilipin 1 (PLIN1), PLIN3, Perilipin 4 (PLIN4) and Perilipin 5 (PLIN5) in the luminal A and luminal B subgroups. On the other hand, the expression of Perilipin 2 (PLIN2) was elevated in the human epidermal growth factor receptor 2 (HER2) positive and basal-like subgroups. Furthermore, Kaplan-Meier Plotter analysis demonstrated that high expression of PLIN1 might predict a longer Overall Survival (OS) in patients with breast cancer while overexpression of PLIN2 indicated poor OS of breast cancer patients.

CONCLUSION

The findings from this study indicated that genes in the PLIN family were aberrantly expressed in breast cancer and may serve as novel therapeutic targets as well as prognostic biomarkers for the disease.

Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure

Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM_2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM_2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM_2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM_2.5 exposure.

Integrated analysis of a competing endogenous RNA network reveals an 11-lncRNA prognostic signature in ovarian cancer

Long noncoding RNA (lncRNA) can function as a competing endogenous RNA (ceRNA) involved in tumor initiation and progression. However, the prognostic roles of lncRNAs in the integrated analysis of the ceRNA network in ovarian cancer (OVC) are still lacking. This study aimed to identify lncRNAs associated with the prognosis of OVC. Differential expression analysis and WGCNA were used to screen OVC-specific RNAs. A lncRNA-miRNA-mRNA regulatory network consisting of 201 lncRNAs, 85 miRNA and 146 mRNAs was constructed, and functional enrichment and protein-protein network analyses were performed. Then, the OVC-specific RNAs were submitted to Cox regression analysis. Twelve differentially expressed lncRNAs and mRNAs were identified as significantly associated with OS of OVC patients. Meanwhile, 11 lncRNAs (including C4A-AS1, LINC02408, LINC00488) were established as prognostic risk formulas. The low-risk group had better OS and DFS than the high-risk group (P <0.01). Univariate and multivariate Cox regression analyses revealed the 11-lncRNA risk score as an independent prognostic factor. A prognostic nomogram was developed based on independent prognostic factors. Our data provide evidence that the 11-lncRNA signature could serve as an independent prognostic indicator. This study also suggests that these 11 lncRNAs potentially participate in the progression of OVC.

Identification of a multidimensional transcriptome prognostic signature for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the leading contributors to cancer-related deaths worldwide. The objective of the current study is to identify a multidimensional transcriptome prognostic signature by combining protein-coding gene (PCG) with long non-coding RNA (lncRNA) for patients with LUAD.

METHODS

We obtained LUAD PCG and lncRNA expression profile data from three datasets in the Gene Expression Omnibus database and conducted survival analyzes for these individuals.

RESULTS

We established a predictive model comprising the three PCGs (NHLRC2, PLIN5, GNAI3), and one lncRNA (AC087521.1). This model segregated patients with LUAD into low- and high-risk groups based on significant differences in survival in the training dataset (GSE31210, n = 226, log-rank test P < .001). Risk stratification of the model was subsequently validated in other two test datasets (GSE37745, n = 106, log-rank test P < .001; GSE30219, n = 85, log-rank test P = .006). Time-dependent receiver operating characteristic (timeROC) curve analysis demonstrated that the model correlated strongly with disease progression and outperformed pathological stage in terms of prognostic ability. Cox proportional hazards regression analysis revealed that the signature could serve as an independent predictor of clinical outcomes in patients with LUAD.

CONCLUSIONS

We describe a novel multidimensional transcriptome signature that can predict survival probabilities in patients with LUAD.