Potentially functional genetic variants in the TNF/TNFR signaling pathway genes predict survival of patients with non-small cell lung cancer in the PLCO cancer screening trial

RNAseqCovarImpute: a multiple imputation procedure that outperforms complete case and single imputation differential expression analysis

Missing covariate data is a common problem that has not been addressed in observational studies of gene expression. Here, we present a multiple imputation method that accommodates high dimensional gene expression data by incorporating principal component analysis of the transcriptome into the multiple imputation prediction models to avoid bias. Simulation studies using three datasets show that this method outperforms complete case and single imputation analyses at uncovering true positive differentially expressed genes, limiting false discovery rates, and minimizing bias. This method is easily implemented via an R Bioconductor package, RNAseqCovarImpute that integrates with the limma-voom pipeline for differential expression analysis.

Development of a genome atlas for discriminating benign, preinvasive, and invasive lung nodules

To tackle misdiagnosis in lung cancer screening with low-dose computed tomography (LDCT), we aimed to compile a genome atlas for differentiating benign, preinvasive, and invasive lung nodules and characterize their molecular pathogenesis. We collected 432 lung nodule tissue samples from Chinese patients, spanning benign, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA). We performed comprehensive sequencing, examining somatic variants, gene expressions, and methylation levels. Our findings uncovered EGFR and TP53 mutations as key drivers in - early lung cancer development, with EGFR mutation frequency increasing with disease progression. Both EGFR mutations and EGF/EGFR hypo-methylation activated the EGFR pathway, fueling cancer growth. Transcriptome analysis identified four lung nodule subtypes (G1-4) with distinct molecular features and immune cell infiltrations: EGFR-driven G1, EGFR/TP53 co-mutation G2, inflamed G3, stem-like G4. Estrogen/androgen response was associated with the EGFR pathway, proposing a new therapy combining tyrosine kinase inhibitors with antiestrogens. Preinvasive nodules exhibited stem cell pathway enrichment, potentially hindering invasion. Epigenetic regulation of various genes was essential for lung cancer initiation and development. This study provides insights into the molecular mechanism of neoplastic progression and identifies potential diagnostic biomarkers and therapeutic targets for lung cancer.

Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients

Deep-learning tools that extract prognostic factors derived from multi-omics data have recently contributed to individualized predictions of survival outcomes. However, the limited size of integrated omics-imaging-clinical datasets poses challenges. Here, we propose two biologically interpretable and robust deep-learning architectures for survival prediction of non-small cell lung cancer (NSCLC) patients, learning simultaneously from computed tomography (CT) scan images, gene expression data, and clinical information. The proposed models integrate patient-specific clinical, transcriptomic, and imaging data and incorporate Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway information, adding biological knowledge within the learning process to extract prognostic gene biomarkers and molecular pathways. While both models accurately stratify patients in high- and low-risk groups when trained on a dataset of only 130 patients, introducing a cross-attention mechanism in a sparse autoencoder significantly improves the performance, highlighting tumor regions and NSCLC-related genes as potential biomarkers and thus offering a significant methodological advancement when learning from small imaging-omics-clinical samples.

Paeoniflorin, the Main Monomer Component of Paeonia lactiflora, Exhibits Anti-inflammatory Properties in Osteoarthritis Synovial Inflammation

OBJECTIVE

To explore the mechanism of paeoniflorin (PF) on osteoarthritis (OA) synovial inflammation from network pharmacology to experimental pharmacology.

METHODS

Targets of OA were constructed by detecting the database of network database platforms (Therapeutic Target database, DrugBank and GeneCards), and the targets of PF were constructed by PubChem and Herbal Ingredients' Targets database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of these co-targeted genes were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID) database, and protein-protein interaction (PPI) networks were conducted via the search tool for the retrieval of interacting genes (STRING) database. Cell counting kit-8 (CCK-8) assay was performed to assess the potential toxicity of PF on human OA fibroblast-like synoviocytes (FLS), quantitative real-time polymerase chain reaction (qPCR), enzyme-linked immunosorbent assay (ELISA) and Western blot were used to verify the potential mechanism of PF in synovial inflammation.

RESULTS

Twenty-six co-targeted genes were identified. GO enrichment results showed that these co-targeted genes were most likely localized in the cytoplasm, and the biological processes mainly involved 'cellular response to hypoxia' 'lipopolysaccharide (LPS)-mediated signaling pathway' and 'positive regulation of gene expression'. KEGG pathway analysis indicated that these co-targeted genes may function through pathways associated with 'hypoxia-inducible factor-1 (HIF-1) signaling pathway' and 'tumor-necrosis factor (TNF) signaling pathway'. The PPI network showed that the top 3 hub genes were TP53, TNF, and CASP3. Molecular docking results showed that PF was well docking with TNF. CCK-8 showed no potential toxicity of 10, 20 and 50 µmol/L PF on human OA FLS. And PF significantly decreased the expression levels of interleukin-1 β, interleukin-6, TNF-α matrix metalloproteinase 13 (MMP13), and a disintegrin and metalloproteinase with thrombospondin motifs 5 (ADAMTS5) and TNF-α in LPS-induced OA FLS.

CONCLUSION

PF exhibited potent anti-inflammatory effect in OA synovial inflammation.

Prediction of network pharmacology, molecular docking-based strategy, and vitro assays to determine potential pharmacological mechanism of Dioscoreae bulbiferae and Bruceae fructus against laryngocarcinoma

BACKGROUND

Based on network pharmacology, molecular docking, and vitro assays, investigate the probable pharmacological mechanism of Dioscoreae bulbiferae and Bruceae fructus in the treatment of laryngocarcinoma.

METHODS

The active components and targets of Dioscoreae bulbiferae and Bruceae fructus were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Targets linked with laryngocarcinoma were gathered from the GeneCards, DisGeNET, and DrugBank databases. The String database was utilized to build a protein-protein interaction network of common medication and illness targets, after which the core targets were filtered out. The Metascape database served for gene ontology enrichment and Kyoto encyclopedia of genes and genomes pathway analysis of common targets. AutoDock then performed molecular docking between the essential component and the vital target. To investigate the biological effects of diosbulbin B, we assessed the viability of laryngocarcinoma cells after diosbulbin B therapy using the Mahalanobis Taguchi system technique. Following that, we looked at how diosbulbin B affected colony formation after 14 days of culture of treated cells. Flow cytometry was utilized to detect apoptosis in order to examine the influence of diosbulbin B on laryngocarcinoma cell apoptosis.

RESULTS

According to a study of the literature, the fundamental components of Dioscoreae bulbiferae and Bruceae fructus in the treatment of laryngocarcinoma include brusatol and diosbulbin B, which may operate on core targets such as cyclin D1, Cyclin Dependent Kinase Inhibitor 1A, and E2F Transcription Factor 1. The significant pathways discovered using Kyoto encyclopedia of genes and genomes enrichment analysis were the phosphoinositide 3-kinase-protein kinase B signaling route, the tumor necrosis factor signaling pathway, and so on. These pathways primarily influence the development and prognosis of laryngeal cancer by controlling cell growth, cell proliferation, angiogenesis, tumorigenesis, and metastasis. The molecular docking studies revealed that the affinity between the heart and crucial targets was robust. The results of vitro assays indicate that diosbulbin B suppressed Hep-2 cell activity in a concentration-dependent manner. Besides, diosbulbin B has powerful antiproliferative properties in Hep-2 cells. Flow cytometry results showed that diosbulbin B promoted laryngocarcinoma cell apoptosis in a concentration-dependent manner.

CONCLUSION

The article delivered a preliminary discussion of the probable mechanism of Dioscoreae bulbiferae and Bruceae fructus in the treatment of laryngocarcinoma, which can serve as a theoretical basis and evidence for subsequent experimental investigation.

RNA-binding protein CELF6 modulates transcription and splicing levels of genes associated with tumorigenesis in lung cancer A549 cells

CELF6 (CUGBP Elav-Like Family Member 6), a canonical RNA binding protein (RBP), plays important roles in post-transcriptional regulation of pre-mRNAs. However, the underlying mechanism of lower expressed CELF6 in lung cancer tissues is still unclear. In this study, we increased CELF6 manually in lung cancer cell line (A549) and utilized transcriptome sequencing (RNA-seq) technology to screen out differentially expressed genes (DEGs) and alternative splicing events (ASEs) after CELF6 over-expression (CELF6-OE). We found that CELF6-OE induced 417 up-regulated and 1,351 down-regulated DEGs. Functional analysis of down-regulated DEGs showed that they were highly enriched in immune/inflammation response- related pathways and cell adhesion molecules (CAMs). We also found that CELF6 inhibited the expression of many immune-related genes, including TNFSF10, CCL5, JUNB, BIRC3, MLKL, PIK3R2, CCL20, STAT1, MYD88, and CFS1, which mainly promote tumorigenesis in lung cancer. The dysregulated DEGs were also validated by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) experiment. In addition, CELF6 regulates the splicing pattern of large number of genes that are enriched in p53 signaling pathway and apoptosis, including TP53 and CD44. In summary, we made an extensive analysis of the transcriptome profile of gene expression and alternative splicing by CELF6-OE, providing a global understanding of the target genes and underlying regulation mechanisms mediated by CELF6 in the pathogenesis and development of lung cancer.

Genome-wide expression of the residual lung reacting to experimental Pneumonectomy

Background

Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq).

Results

Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10^− 3) and “Response to insulin” (FDR q = 7.60 × 10^− 3) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10^− 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections.

Conclusion

This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08171-3.

Genetic Variants of CLEC4E and BIRC3 in Damage-Associated Molecular Patterns-Related Pathway Genes Predict Non-Small Cell Lung Cancer Survival

Accumulating evidence supports a role of various damage-associated molecular patterns (DAMPs) in progression of lung cancer, but roles of genetic variants of the DAMPs-related pathway genes in lung cancer survival remain unknown. We investigated associations of 18,588 single-nucleotide polymorphisms (SNPs) in 195 DAMPs-related pathway genes with non-small cell lung cancer (NSCLC) survival in a subset of genotyping data for 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the findings in another independent subset of genotyping data for 984 patients from Harvard Lung Cancer Susceptibility Study. We performed multivariate Cox proportional hazards regression analysis, followed by expression quantitative trait loci (eQTL) analysis, Kaplan-Meier survival analysis and bioinformatics functional prediction. We identified that two SNPs (i.e., CLEC4E rs10841847 G>A and BIRC3 rs11225211 G>A) were independently associated with NSCLC overall survival, with adjusted allelic hazards ratios of 0.89 (95% confidence interval=0.82-0.95 and P=0.001) and 0.82 (0.73-0.91 and P=0.0003), respectively; so were their combined predictive alleles from discovery and replication datasets (P_trend=0.0002 for overall survival). We also found that the CLEC4E rs10841847 A allele was associated with elevated mRNA expression levels in normal lymphoblastoid cells and whole blood cells, while the BIRC3 rs11225211 A allele was associated with increased mRNA expression levels in normal lung tissues. Collectively, these findings indicated that genetic variants of CLEC4E and BIRC3 in the DAMPs-related pathway genes were associated with NSCLC survival, likely by regulating the mRNA expression of the corresponding genes.

Exploration of prognostic biomarkers and therapeutic targets in the microenvironment of bladder cancer based on CXC chemokines

BACKGROUND

Bladder cancer (BLCA) has a high rate of morbidity and mortality, and is considered as one of the most malignant tumors of the urinary system. Tumor cells interact with surrounding interstitial cells, playing a key role in carcinogenesis and progression, which is partly mediated by chemokines. CXC chemokines exert anti-tumor biological roles in the tumor microenvironment and affect patient prognosis. Nevertheless, their expression and prognostic values patients with BLCA remain unclear.

METHODS

We used online tools, including Oncomine, UALCAN, GEPIA, GEO databases, cBioPortal, GeneMANIA, DAVID 6.8, Metascape, TRUST (version 2.0), LinkedOmics, TCGA, and TIMER2.0 to perform the relevant analysis.

RESULTS

The mRNA levels of C-X-C motif chemokine ligand (CXCL)1, CXCL5, CXCL6, CXCL7, CXCL9, CXCL10, CXCL11, CXCL13, CXCL16, and CXCL17 were increased significantly increased, and those of CXCL2, CXCL3, and CXCL12 were decreased significantly in BLCA tissues as assessed using the Oncomine, TCGA, and GEO databases. GEO showed that high levels of CXCL1, CXCL6, CXCL10, CXCL11, and CXCL13 mRNA expression are associated significantly with the poor overall survival (all p < 0.05), and similarly, those of CXCL2 and CXCL12 in the TCGA database (p < 0.05). The predominant signaling pathways involving the differentially expressed CXC chemokines are cell cycle, chemokine, and cytokine-cytokine receptor interaction. Moreover, transcription factors such as Sp1 transcription factor (SP1), nuclear factor kappa B subunit 1 (NFKB1), and RELA proto-oncogene, NF-KB subunit (RELA) were likely play critical roles in regulating CXC chemokine expression. LYN proto-oncogene, src family tyrosine kinase (LYN) and LCK proto-oncogene, src family tyrosine kinase (LCK) were identified as the key targets of these CXC chemokines. MicroRNAs miR200 and miR30 were identified as the main microRNAs that interact with several CXC chemokines through an miRNA-target network. The expression of these chemokines is closely associated with the infiltration of six categories of immune cells.

CONCLUSION

We explored the CXC chemokines superfamily-based biomarkers associated with BLCA prognosis using public databases, and provided possible chemokine targets for patients with BLCA.

Identification of the pyroptosis‑related prognostic gene signature and the associated regulation axis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. Pyroptosis could regulate tumour cell proliferation, invasion, and metastasis, thereby affecting the prognosis of cancer patients. However, the role of pyroptosis-related genes (PRGs) in LUAD remains unclear. In our study, comprehensive bioinformatics analysis was performed to construct a prognostic gene model and ceRNA network. The correlations between PRGs and tumour-immune infiltration, tumour mutation burden, and microsatellite instability were evaluated using Pearson’s correlation analysis. A total of 23 PRGs were upregulated or downregulated in LUAD. The genetic mutation variation landscape of PRG in LUAD was also summarised. Functional enrichment analysis revealed that these 33 PRGs were mainly involved in pyroptosis, the NOD-like receptor signalling pathway, and the Toll-like receptor signalling pathway. Prognosis analysis indicated a poor survival rate in LUAD patients with low expression of NLRP7, NLRP1, NLRP2, and NOD1 and high CASP6 expression. A prognostic PRG model constructed using the above five prognostic genes could predict the overall survival of LUAD patients with medium-to-high accuracy. Significant correlation was observed between prognostic PRGs and immune-cell infiltration, tumour mutation burden, and microsatellite instability. A ceRNA network was constructed to identify a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis in LUAD. In conclusion, we performed a comprehensive bioinformatics analysis and identified a prognostic PRG signature containing five genes (NLRP7, NLRP1, NLRP2, NOD1, and CASP6) for LUAD patients. Our results also identified a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis, which may also play an important role in the progression of LUAD. Further study needs to be conducted to verify this result.

Super-enhancer-associated long noncoding RNA RP11-569A11.1 inhibited cell progression and metastasis by regulating IFIT2 in colorectal cancer

BACKGROUND

Recent studies have revealed that super-enhancer-associated long noncoding RNAs (SE-LncRNAs) act pivotal roles in carcinogenesis. This study aimed to report the identification of a novel SE-LncRNA, RP11-569A11.1, and its functional role in colorectal cancer (CRC) progression.

METHODS

Arraystar human SE-LncRNA microarray was performed to detect differentially expressed SE-LncRNAs in CRC tissues. RT-qPCR was conducted to detect the expression level of RP11-569A11.1 in CRC tissues and cells. The ROC curve was used to analyze the sensitivity and specificity of RP11-569A11.1 in CRC diagnosis. CCK-8 assay, colony formation assay, flow cytometry assay, and transwell assay were used to study the function of RP11-569A11.1. RNA-seq array was performed to analyze the potential downstream target gene of RP11-569A11.1. Western blot assay was conducted to measure the protein level of interferon-induced protein with tetratricopeptide repeat 2 (IFIT2).

RESULTS

A total of 23 (15 up- and 8 downregulated) significantly expressed SE-LncRNAs were identified in CRC tissues. The top 8 upregulated SE-LncRNAs were RP11-893F2.9, PTCSC1, RP11-803D5.4, AC005592.2, LINC00152, LINC01232, AC017002.1, and RP4-673M15.1, and the top 8 downregulated SE-LncRNAs were RP11-569A11.1, RP11-245G13.2, RP11-556N21.1, U91328.19, AX748340, CTD-2337J16.1, CATG00000108830.1, and RP11-670E13.2. Of which, RP11-569A11.1 was found to be significantly downregulated in CRC tissues and cells. ROC curve analysis showed the area under the curve (AUC) of 0.77 [95% confidence interval (CI), 0.660-0.884, p < 0.001], and the diagnostic sensitivity and specificity were 74.29% and 71.43%, respectively. Functionally, overexpression of RP11-569A11.1 inhibited CRC cell proliferation, migration and invasion, and induced cell apoptosis, while knockdown of RP11-569A11.1 generated an opposite effect. Mechanistically, RP11-569A11.1 positively regulated IFIT2 expression in CRC cells.

CONCLUSION

RP11-569A11.1 inhibited CRC tumorigenesis by IFIT2-dependent and could serve as a promising diagnostic biomarker in CRC.

Anti-Colorectal Cancer Mechanisms of Formononetin Identified by Network Pharmacological Approach

Background

The network pharmacological approach was used to identity the anti-colorectal cancer (CRC) targets of formononetin (FN) and the molecular mechanisms of FN against CRC.

Material/Methods

A tool of the DisGeNET database was used for collection of CRC-based targets. Other tools of SuperPred, herbal ingredients target (HIT), and SwissTargetPrediction databases were applied in prediction of pharmacological targets of FN against cancer. A protein-protein interaction (PPI) network of FN against CRC was obtained by using a STRING database. All top biological functional processes and signaling pathways of FN against CRC were identified by using Database for Annotation, Visualization and Integrated Discovery (DAVID) software and Omicshare cloud platform.

Results

The most key anti-CRC targets of FN were identified as tumor protein p53 (TP53), cytochrome P450 3A4 (CYP3A4), ATP binding cassette subfamily G member 2 (ABCG2), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and cytochrome P450 1A1 (CYP1A1). In further assays, the treatment of CRC by FN was mainly involved in biological functional processes of reactive oxygen species metabolic process, positive regulation of transcription, DNA-templated, positive regulation of nucleic acid-templated transcription, and positive regulation of RNA metabolic process. anti-CRC by FN of signaling pathways were associated with amyotrophic lateral sclerosis (ALS), allograft rejection, cytokine-cytokine receptor interaction, asthma, mitogen-activated protein kinase (MAPK) signaling pathways, and others.

Conclusions

The anti-CRC molecular mechanisms of FN are implicated in suppression of cellular proliferation and regulation of cancer-related metabolic pathways. Interestingly, 8 optimal biological targets may be used as potential molecular markers for predicting and treating CRC.