Identification of transcription factors that may reprogram lung adenocarcinoma

Molecular Subtypes and Machine Learning-Based Predictive Models for Intracranial Aneurysm Rupture

BACKGROUND

The determination of biological mechanisms and biomarkers related to intracranial aneurysm (IA) rupture is of utmost significance for the development of effective preventive and therapeutic strategies in the clinical field.

METHODS

GSE122897 and GSE13353 datasets were downloaded from Gene Expression Omnibus. Data extracted from GSE122897 were used for analyzing differential gene expression, and consensus clustering was performed to identify stable molecular subtypes. Clinical characteristics were compared between subgroups, and fast gene set enrichment analysis and weighted gene coexpression network analysis were performed. Hub genes were identified via least absolute shrinkage and selection operator analysis. Predictive models were constructed based on hub genes using the Light Gradient Boosting Machine, eXtreme Gradient Boosting, and logistic regression algorithm. Immune cell infiltration in IA samples was analyzed using Microenvironment Cell Population counter, CIBERSORT, and xCell algorithm. The correlation between hub genes and immune cells was analyzed. The predictive model and immune cell infiltration were validated using data from the GSE13353 dataset.

RESULTS

A total of 43 IA samples were classified into 2 subgroups based on gene expression profiles. Subgroup I had a higher risk of rupture, while 70% of subgroup II remained unruptured. In subgroup I, specific genes were associated with inflammation and immunity, and weighted gene coexpression network analysis revealed that the black module genes were linked to IA rupture. We identified 4 hub genes (spermine synthase, macrophage receptor with collagenous structure, zymogen granule protein 16B, and LIM and calponin-homology domains 1), which constructed predictive models with good diagnostic performance in differentiating between ruptured and unruptured IA samples. Monocytic lineage was found to be a significant factor in IA rupture, and the 4 hub genes were linked to monocytic lineage (P < 0.05).

CONCLUSIONS

We reveal a new molecular subtype that can reflect the actual pathological state of IA rupture, and our predictive models constructed by machine learning algorithms can efficiently predict IA rupture.

Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

Role of RBMS3 Novel Potential Regulator of the EMT Phenomenon in Physiological and Pathological Processes

RNA-binding protein 3 (RBMS3) plays a significant role in embryonic development and the pathogenesis of many diseases, especially cancer initiation and progression. The multiple roles of RBMS3 are conditioned by its numerous alternative expression products. It has been proven that the main form of RBMS3 influences the regulation of microRNA expression or stabilization. The absence of RBMS3 activates the Wnt/β-catenin pathway. The expression of c-Myc, another target of the Wnt/β-catenin pathway, is correlated with the RBMS3 expression. Numerous studies have focused solely on the interaction of RBMS3 with the epithelial-mesenchymal transition (EMT) protein machinery. EMT plays a vital role in cancer progression, in which RBMS3 is a new potential regulator. It is also significant that RBMS3 may act as a prognostic factor of overall survival (OS) in different types of cancer. This review presents the current state of knowledge about the role of RBMS3 in physiological and pathological processes, with particular emphasis on carcinogenesis. The molecular mechanisms underlying the role of RBMS3 are not fully understood; hence, a broader explanation and understanding is still needed.

LncRNA RP11‑805J14.5 functions as a ceRNA to regulate CCND2 by sponging miR‑34b‑3p and miR‑139‑5p in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common lung cancer with high incidence. The prognosis of LUAD is poor due to its aggressive behavior. Long non‑coding RNAs (lncRNAs) have been reported as a key modulator on LUAD progression. Therefore, the present study aimed to clarify the molecular mechanism of lncRNAs in LUAD development. The expression of lncRNA RP11‑805J14.5 (RP11‑805J14.5) in LUAD tissues and cells was quantified based on the data in The Cancer Genome Atlas (TCGA). Cell viability was determined using Cell Counting Kit‑8 method. Apoptotic cells were sorted and determined by flow cytometry. Cell migration and invasion abilities were detected by the Transwell assay. Luciferase reporter experiment and RNA pull‑down assay were utilized to determine the interactions between RP11‑805J14.5, microRNA (miR)‑34b‑3p, miR‑139‑5p, and cyclin D2 (CCND2). A xenograft tumor was established to determine tumor growth in vivo. RP11‑805J14.5 was highly expressed in LUAD and associated with poor survival of LUAD patients. Knockdown of RP11‑805J14.5 suppressed LUAD cell growth, invasion, migration and tumor growth, indicating that RP11‑805J14.5 is an important regulator of LUAD. Our study demonstrated that the regulation of RP11‑805J14.5 on LUAD was mediated by CCND2 whose expression was regulated by sponging miR‑34b‑3p and miR‑139‑5p. The expression of RP11‑805J14.5 was increased in LUAD, and the knockdown of RP11‑805J14.5 expression suppressed LUAD cell growth, invasion and migration by downregulating CCND2 by sponging miR‑34b‑3p and miR‑139‑5p, indicating that RP11‑805J14.5 could be a prospective target for LUAD therapy.

Functional characterization of FBXL7 as a novel player in human cancers

F-box and leucine-rich repeat protein 7 (FBXL7), an F-box protein responsible for substrate recognition by the SKP1-Cullin-1-F-box (SCF) ubiquitin ligases, plays an emerging role in the regulation of tumorigenesis and tumor progression. FBXL7 promotes polyubiquitylation and degradation of diverse substrates and is involved in many biological processes, including apoptosis, cell proliferation, cell migration and invasion, tumor metastasis, DNA damage, glucose metabolism, planar cell polarity, and drug resistance. In this review, we summarize the downstream substrates and upstream regulators of FBXL7. We then discuss its role in tumorigenesis and tumor progression as either an oncoprotein or a tumor suppressor, and further describe its aberrant expression and association with patient survival in human cancers. Finally, we provide future perspectives on validating FBXL7 as a cancer biomarker for diagnosis and prognosis and/or as a potential therapeutic target for anticancer treatment.

MYBL2-induced PITPNA-AS1 upregulates SIK2 to exert oncogenic function in triple-negative breast cancer through miR-520d-5p and DDX54

Background

In recent years, long non-coding RNAs (lncRNAs) have attracted much attention because of its regulatory role in occurrence and progression of tumors, including triple-negative breast cancer (TNBC). LncRNA PITPNA antisense RNA 1 (PITPNA-AS1) has been explored in some cancers, whereas its function and molecular mechanism in TNBC remain unclear.

Methods

PITPNA-AS1 expression in TNBC tissues and cells was determined by RT-qPCR. TNBC cell viability, proliferation, migration, invasion were assessed with CCK-8, colony formation, wound healing, transwell assays. Cell apoptosis was evaluated by flow cytometry. Expression of EMT-related markers was detected by western blot analyses. The molecular mechanism of PITPNA-AS1 was explored by RNA pull down, luciferase reporter, RIP and ChIP assays.

Results

PITPNA-AS1 showed high expression levels in TNBC tissues and cells. PITPNA-AS1 knockdown suppressed TNBC cell viability, proliferation, migration, invasion in vitro and inhibited xenograft tumor growth in mice. Mechanistically, PITPNA-AS1 upregulated SIK2 expression by sponging miR-520d-5p and recruiting DDX54 protein. Results of rescue assays suggested that the inhibitive effects of silenced PITPNA-AS1 on TNBC cellular processes were partially rescued by overexpressing SIK2 or combination of miR-520d-5p inhibition and DDX54 overexpression. More importantly, we found that the upregulation of PITPNA-AS1 in TNBC cells was attributed to transcription factor MYBL2.

Conclusion

PITPNA-AS1 activated by MYBL2 plays an oncogenic role in TNBC through upregulating SIK2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02956-6.

A 10-gene prognostic signature points to LIMCH1 and HLA-DQB1 as important players in aggressive cervical cancer disease

BACKGROUND

Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease.

METHODS

Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort.

RESULTS

Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ).

CONCLUSIONS

This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.

Loss of LIMCH1 predicts poor prognosis in patients with surgically resected Lung Adenocarcinoma: A study based on Immunohistochemical Analysis and Bioinformatics

Background: LIMCH1, a novel actin-binding protein, is reported to correlate with tumorigenesis in multiple cancer types, but its clinical prognostic value in lung adenocarcinoma (LUAD) patients remains unclear.

Methods: A total of 196 patients with LUAD who underwent R0 resection were included for analysis. We integrated immunohistochemistry (IHC) and data mining analyses to determine LIMCH1 expression in tumor specimens; the chi-square test was used to explore the correlation between clinicopathologic factors and LIMCH1 expression in LUAD; Kaplan-Meier curves and the Cox proportional hazards model were used to investigate the clinical prognostic role of LIMCH1 expression in patients with LUAD; and DAVID enrichment and gene set enrichment analysis (GSEA) were used to determine the underlying molecular mechanism.

Results: LIMCH1 protein and mRNA expressions were significantly decreased in LUAD tissues. LIMCH1 mRNA expression was a potential diagnostic indicator in the TCGA cohort, and was associated with poor prognosis. IHC results in our LUAD cohort demonstrated that the LIMCH1 expression level was significantly associated with pleural invasion, tumor length, tumor differentiation grade, and clinical tumor stage. Patients with higher LIMCH1 expression had longer overall survival times. Cox multivariate survival analysis showed that LIMCH1 expression independently predicted the outcome. GO and KEGG clustering analyses showed that LIMCH1-related genes may be involved in 'cell adhesion', 'signal transduction', and several cancer-related pathways. GSEA showed 8 enriched hallmarks in the low LIMCH1 expression group, including mTOR signaling, MYC signaling, DNA repair, and G2M checkpoint.

Conclusions: Our findings suggest that LIMCH1 may serve as a promising biomarker to predict LUAD prognosis.

Identification by Comprehensive Bioinformatics Analysis of KIF15 as a Candidate Risk Gene for Triple-Negative Breast Cancer

Background

Previous studies have shown that kinesin family proteins (KIFs) play an indispensable roles in several types of cancer. However, the expression and clinical significance of KIFs in triple-negative breast cancer remain unclear.

Methods

In this study, the role of KIF15, including gene expression analysis, methylation characteristic, CNV characteristic, and miRNA target regulation, was evaluated using multiple bioinformatic tools based on TCGA database. Quantitative real-time PCR and Western blot were used to determine the expression level of KIF15 in triple-negative breast cancer cell lines. Then, functional experiments were employed to explore the effects of KIF15 on tumor growth and metastasis in triple-negative breast cancer.

Results

Our data showed that KIF15 was significantly upregulated in triple-negative breast cancer (TNBC). Functionally, downregulation of KIF15 significantly facilitated apoptosis and G2/M phase arrest, and inhibited the migration and invasion of TNBC cells. The mechanism of action of KIF15 was closely related to DNA replication checkpoint and cell cycle regulation in TNBC based on GSEA. In addition, bioinformatics analysis demonstrated that high expression of KIF15 in TNBC was correlated with copy number aberration and DNA methylation levels.

Conclusion

Our findings suggest that KIF15 is a novel oncogene in TNBC and provide us a strong evidence that it might be served as a potential clinical target and biomarker in triple-negative breast cancer.

Investigation of miRNA and mRNA Co-expression Network in Ependymoma

Ependymoma (EPN) is a rare primary tumor of the central nervous system (CNS) that affects both children and adults. Despite the definition and classification of distinct molecular subgroups, there remains a group of EPNs with a balanced genome, which makes it difficult to predict a prognosis of patients with EPN. The role of miRNA-mRNA network on EPN is still poorly understood. We assessed the involvement of miRNA-mRNA pairs in EPN by applying a weighted co-expression network analysis (WGCNA) approach. Using whole genome expression profile analysis followed by functional enrichment, we detected hub genes involved in active proliferation and DNA replication of nerve cells. Key genes including CYP11B1, KRT33B, RUNX1T1, SIK1, MAP3K4, MLANA, and SFRP5 identified in co-expression networks were regulated by miR-15a and miR-24-1. These seven miRNA-mRNA pairs were considered to influence not only pathways in cancer and tumor suppression process, but also MAPK, NF-kappaB, and WNT signaling pathways which were associated with tumorigenesis and development. This study provides a novel insight into potential diagnostic biomarkers of EPN and may have value in choosing therapeutic targets with clinical utility.

Identification of the differential expression of genes and upstream microRNAs in small cell lung cancer compared with normal lung based on bioinformatics analysis

Small cell lung cancer (SCLC) is one of the most lethal cancer, mainly attributing to its high tendency to metastasis. Mounting evidence has demonstrated that genes and microRNAs (miRNAs) are related to human cancer onset and progression including invasion and metastasis.An eligible gene dataset and an eligible miRNA dataset were downloaded from the Gene Expression Omnibus (GEO) database based our screening criteria. Differentially expressed genes (DE-genes) or DE-miRNAs for each dataset obtained by the R software package. The potential target genes of the top 10 DE-miRNAs were predicted by multiple databases. For annotation, visualization and integrated discovery, Metascape 3.0 was introduced to perform enrichment analysis for the DE-genes and the predicted target genes of the selected top 10 DE-miRNAs, including Pathway and Process Enrichment Analysis or protein-protein interaction enrichment analysis. The intersection of predicted target genes and DE-genes was taken as the final DE-genes. Then apply the predicted miRNAs-targets relationship of top 10 DE-miRNAs to the final DE-genes to gain more convinced DE-miRNAs, DE-genes and their one to one relationship.GSE19945 (miRNA microarray) and GSE40275 (gene microarray) datasets were selected and downloaded. 56 DE-miRNAs and 861 DE-genes were discovered. 297 miRNAs-targets relationships (284 unique genes) were predicted as the target of top 10 upregulating DE-miRNAs. 245 miRNAs-targets relationships (238 unique genes) were identified as the target of top 10 downregulating DE-miRNAs. The key results of enrichment analysis include protein kinase B signaling, transmembrane receptor protein tyrosine kinase signaling pathway, negative regulation of cell differentiation, response to growth factor, cellular response to lipid, muscle structure development, response to growth factor, signaling by Receptor Tyrosine Kinases, epithelial cell migration, cellular response to organic cyclic compound, Cell Cycle (Mitotic), DNA conformation change, cell division, DNA replication, cell cycle phase transition, blood vessel development, inflammatory response, Staphylococcus aureus infection, leukocyte migration, and myeloid leukocyte activation. Differential expression of genes-upstream miRNAs (RBMS3-hsa-miR-7-5p, NEDD9-hsa-miR-18a-5p, CRIM1-hsa-miR-18a-5p, TGFBR2-hsa-miR-9-5p, MYO1C-hsa-miR-9-5p, KLF4-hsa-miR-7-5p, EMP2-hsa-miR-1290, TMEM2-hsa-miR-18a-5p, CTGF-hsa-miR-18a-5p, TNFAIP3-hsa-miR-18a-5p, THBS1-hsa-miR-182-5p, KPNA2-hsa-miR-144-3p, GPR137C-hsa-miR-1-3p, GRIK3-hsa-miR-144-3p, and MTHFD2-hsa-miR-30a-3p) were identified in SCLC.RBMS3, NEDD9, CRIM1, KPNA2, GPR137C, GRIK3, hsa-miR-7-5p, hsa-miR-18a-5p, hsa-miR-144-3p, hsa-miR-1-3p along with the pathways included protein kinase B signaling, muscle structure development, Cell Cycle (Mitotic) and blood vessel development may gain a high chance to play a key role in the prognosis of SCLC, but more studies should be conducted to reveal it more clearly.

Integrative Analysis of Methylation and Gene Expression in Lung Adenocarcinoma and Squamous Cell Lung Carcinoma

Lung cancer is a highly prevalent type of cancer with a poor 5-year survival rate of about 4-17%. Eighty percent lung cancer belongs to non-small-cell lung cancer (NSCLC). For a long time, the treatment of NSCLC has been mostly guided by tumor stage, and there has been no significant difference between the therapy strategy of lung adenocarcinoma (LUAD) and squamous cell lung carcinoma (SCLC), the two major subtypes of NSCLC. In recent years, important molecular differences between LUAD and SCLC are increasingly identified, indicating that targeted therapy will be more and more histologically specific in the future. To investigate the LUAD and SCLC difference on multi-omics scale, we analyzed the methylation and gene expression data together. With the Boruta method to remove irrelevant features and the MCFS (Monte Carlo Feature Selection) method to identify the significantly important features, we identified 113 key methylation features and 23 key gene expression features. HNF1B and TP63 were found to be dysfunctional on both methylation and gene expression levels. The experimentally determined interaction network suggested that TP63 may play an important role in connecting methylation genes and expression genes. Many of the discovered signature genes have been supported by literature. Our results may provide directions of precision diagnosis and therapy of LUAD and SCLC.

Emerging roles of F-box proteins in cancer drug resistance

Chemotherapy continues to be a major treatment strategy for various human malignancies. However, the frequent emergence of chemoresistance compromises chemotherapy efficacy leading to poor prognosis. Thus, overcoming drug resistance is pivotal to achieve enhanced therapy efficacy in various cancers. Although increased evidence has revealed that reduced drug uptake, increased drug efflux, drug target protein alterations, drug sequestration in organelles, enhanced drug metabolism, impaired DNA repair systems, and anti-apoptotic mechanisms, are critically involved in drug resistance, the detailed resistance mechanisms have not been fully elucidated in distinct cancers. Recently, F-box protein (FBPs), key subunits in Skp1-Cullin1-F-box protein (SCF) E3 ligase complexes, have been found to play critical roles in carcinogenesis, tumor progression, and drug resistance through degradation of their downstream substrates. Therefore, in this review, we describe the functions of FBPs that are involved in drug resistance and discuss how FBPs contribute to the development of cancer drug resistance. Furthermore, we propose that targeting FBPs might be a promising strategy to overcome drug resistance and achieve better treatment outcome in cancer patients. Lastly, we state the limitations and challenges of using FBPs to overcome chemotherapeutic drug resistance in various cancers.

LncRNA LOXL1-AS1 regulates the tumorigenesis and development of lung adenocarcinoma through sponging miR-423-5p and targeting MYBL2

Lung adenocarcinoma (LUAD) is the most common form of malignant tumor and closely correlated with high risk of death worldwide. Accumulating researches have manifested that long noncoding RNAs (lncRNAs) are deeply involved in the progression of multiple cancers. LncRNA LOXL1 antisense RNA 1 (LOXL1‐AS1) was identified as an oncogene in several cancers, nonetheless, its biological effect and regulatory mechanism have not been explained in LUAD. Our present study suggested that LOXL1‐AS1 expression was considerably increased in LUAD tissues and cells. Moreover, LOXL1‐AS1 deficiency notably hampered cell proliferation and migration as well as dramatically facilitated cell apoptosis. Through molecular mechanism assays, LOXL1‐AS1 was identified as a cytoplasmic RNA and acted as a sponge of miR‐423‐5p. Furthermore, MYBL2 was targeted and negatively modified by miR‐423‐5p. Rescue experiments revealed that MYBL2 knockdown could counteract miR‐423‐5p repression‐mediated enhancement on the progression of LOXL1‐AS1 downregulated LUAD cells. More importantly, MYBL2 was discovered to interact with LOXL1‐AS1 promoter, indicating a positive feedback loop of LOXL1‐AS1/miR‐423‐5p/MYBL2 in LUAD. These findings manifested the carcinogenic role of LOXL1‐AS1 and LOXL1‐AS1/miR‐423‐5p/MYBL2 feedback loop in LUAD, which could be helpful to explore effective therapeutic strategy for LUAD patients.

Smoking alters the evolutionary trajectory of non-small cell lung cancer

Smoking is the biggest risk factor for lung cancer. Smokers have a much higher chance of developing lung tumors with a worse survival rate; however, non-smokers also develop lung tumors. A number of questions remain including the underlying difference between smoker and non-smoker lung cancer patients and the involvement of genetic and epigenetic processes in tumor development. The present study analyzed the mutation data of 100 non-small cell lung cancer (NSCLC) patients, 12 non-smokers, 48 ex-smokers and 40 smokers, from Tracking Non-Small Cell Lung Cancer Evolution through Therapy Consortium. A total of 68 genes exhibited different mutation patterns across non-smokers, ex-smokers and smokers. A number of these 68 genes encode membrane proteins with biological regulation, metabolic process, and response to stimulus functions. For each group of patients, the top 10 most frequently mutated genes were selected and their oncogenetic tree inferred, which reflected how the genes evolve during tumor genesis. By comparing the oncogenetic trees of non-smokers and smokers, it was identified that in non-smokers, the mutation of epidermal growth factor receptor (EGFR) was an early genetic alteration event and EGFR was the key driver, but in smokers, the mutation of titin (TTN) was more important. Based on network analysis, TTN can interact with spectrin α erythrocytic 1 through calmodulin 2 and troponin C1. These genetic differences during tumorigenesis of non-smoker and smoker lung cancer patients provided novel insights into the effects of smoking on the evolutionary trajectory of non-small cell lung cancer and may prove helpful for targeted therapy of different lung cancer subtypes.

LIMCH1 suppress the growth of lung cancer by interacting with HUWE1 to sustain p53 stability

BACKGROUND

The aim of this study was to identify the expression of LIM and calponin-homology domains 1 (LIMCH1) in lung cancer and normal tissues, to determine the interaction between LIMCH1 and HUWE1 in regulating p53 stability.

METHODS

The expression of LIMCH1 was detected by the Oncomine and Cancer Genome Atlas databases. Expression of LIMCH1 mRNA was identified using qRT-PCR. In transfected human lung cancer cells, co-immunoprecipitation experiments were performed. The mechanism that HUWE1 sustained lung cancer malignancy was verified by western blotting. The proliferation of tranfected cells was assessed by CCK-8 assay and colony formation.

RESULTS

Bioinformatic data and e TCGA database suggested LIMCH1 mRNA levels in tumor tissues were down-regulated compared to tumor adjacent tissues. We found low expression of LIMCH1 mRNA in tumor sites and tumor cell line. Exogenous expression of LIMCH1 interacts with HUWE1 promotes expression of p53. Use of siRNA or shRNA against LIMCH1 resulted in decreased p53 protein levels. LIMCH1 deletion lead to enhance of p53 ubiquitination and protein expression of p53 and substrate p21, puma. Growth curve showed that LIMCH1 deletion significantly promoted the proliferation of A549 cells.

CONCLUSIONS

LIMCH1 was a negative regulator and indicated a new molecular mechanism for the pathogenesis of lung cancer via modulating HUWE1 and p53.

Gene set enrichment analysis and meta-analysis identified 12 key genes regulating and controlling the prognosis of lung adenocarcinoma

The aim of the present study was to analyze lung adenocarcinoma-associated microarray data and identify potentially crucial genes. The gene expression profiles were downloaded from the Gene Expression Omnibus database and 6 datasets, of which 2 were discarded and 4 were retained, were preprocessed using packages in the R computing language. Subsequently, Gene Set Enrichment Analysis (GSEA) and meta-analysis was used to screen the common pathways and differentially expressed genes at the transcriptional level. The genes detected from GSEA through The Cancer Genome Atlas databases were subsequently examined, and the crucial genes by survival data were identified. Pathways of the crucial genes were obtained using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the online website Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, and the pathways of crucial genes that were upregulated or downregulated were matched using the Venn method to identify the common crucial pathways. Furthermore, on the basis of the common crucial pathways, key genes that are closely associated with the development and progression of lung adenocarcinoma were identified with the KEGG pathway of DAVID. Additional information was obtained through Gene Ontology annotation. A total of two key pathways, including cell cycle and DNA replication, as well as 12 key genes [DNA polymerase δ subunit 2, DNA replication licensing factor MCM4, MCM6, mitotic checkpoint serine/threonine-protein kinase BUB1, BUB1β, mitotic spindle assembly checkpoint protein MAD2A, dual specificity protein kinase TTK, M-phase inducer phosphatase 1, cell division control protein 45 homolog, cyclin-dependent kinase inhibitor 1C, pituitary tumor-transforming gene 1 protein and polo-like kinase 1] were identified. These key pathways and genes may be studied in future studies involving gene transfection/knockdown, which may provide insights into the prognosis of lung adenocarcinoma. Additional studies are required to confirm their biological function.

Potentially functional genetic variants in the complement-related immunity gene-set are associated with non-small cell lung cancer survival

The complement system plays an important role in the innate and adaptive immunity, complement components mediate tumor cytolysis of antibody-based immunotherapy, and complement activation in the tumor microenvironment may promote tumor progression or inhibition, depending on the mechanism of action. In the present study, we conducted a two-phase analysis of two independently published genome-wide association studies (GWASs) for associations between genetic variants in a complement-related immunity gene-set and overall survival of non-small cell lung cancer (NSCLC). The GWAS dataset from Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was used as the discovery, and multivariate Cox proportional hazards regression with false-positive report probability for multiple test corrections were performed to evaluate associations between 14,699 single-nucleotide polymorphisms (SNPs) in 111 genes and survival of 1,185 NSCLC patients. The identified significant SNPs in a single-locus analysis were further validated with 984 NSCLC patients in the GWAS dataset from the Harvard Lung Cancer Susceptibility (HLCS) Study. The results showed that two independent, potentially functional SNPs in two genes (VWF rs73049469 and ITGB2 rs3788142) were significantly associated with NSCLC survival, with a combined hazards ratio (HR) of 1.22 [95% confidence interval (CI) = 1.07-1.40, P = 0.002] and 1.16 (1.07-1.27, 6.45 × 10^-4 ), respectively. Finally, we performed expression quantitative trait loci (eQTL) analysis and found that survival-associated genotypes of VWF rs73049469 were also significantly associated with mRNA expression levels of the gene. These results indicated that genetic variants of the complement-related immunity genes might be predictors of NSCLC survival, particularly for the short-term survival, possibly by modulating the expression of genes involved in the host immunity.

Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer

BACKGROUND

Lung cancer is a severe cancer with a high death rate. The 5-year survival rate for stage III lung cancer is much lower than stage I. Early detection and intervention of lung cancer patients can significantly increase their survival time. However, conventional lung cancer-screening methods, such as chest X-rays, sputum cytology, positron-emission tomography (PET), low-dose computed tomography (CT), magnetic resonance imaging, and gene-mutation, -methylation, and -expression biomarkers of lung tissue, are invasive, radiational, or expensive. Liquid biopsy is non-invasive and does little harm to the body. It can reflect early-stage dysfunctions of tumorigenesis and enable early detection and intervention.

METHODS

In this study, we analyzed RNA-sequencing data of tumor-educated platelets (TEPs) in 402 non-small-cell lung cancer (NSCLC) patients and 231 healthy controls. A total of 48 biomarker genes were selected with advanced minimal-redundancy, maximal-relevance, and incremental feature-selection (IFS) methods.

RESULTS

A support vector-machine (SVM) classifier based on the 48 biomarker genes accurately predicted NSCLC with leave-one-out cross-validation (LOOCV) sensitivity, specificity, accuracy, and Matthews correlation coefficients of 0.925, 0.827, 0.889, and 0.760, respectively. Network analysis of the 48 genes revealed that the WASF1 actin cytoskeleton module, PRKAB2 kinase module, RSRC1 ribosomal protein module, PDHB carbohydrate-metabolism module, and three intermodule hubs (TPM2, MYL9, and PPP1R12C) may play important roles in NSCLC tumorigenesis and progression.

CONCLUSION

The 48-gene TEP liquid-biopsy biomarkers will facilitate early screening of NSCLC and prolong the survival of cancer patients.