Hub Genes in Non-Small Cell Lung Cancer Regulatory Networks

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson's correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes.

Maresin-1 and Its Receptors RORα/LGR6 as Potential Therapeutic Target for Respiratory Diseases

Maresin-1 is one of the representative specialized pro-resolving mediators that has shown beneficial effects in inflammatory disease models. Recently, two distinct types of receptor molecules were discovered as the targets of maresin-1, further revealing the pro-resolution mechanism of maresin-1. One is retinoic acid-related orphan receptor α (RORα) and the another one is leucine-rich repeat domain-containing G protein-coupled receptor 6 (LGR6). In this review, we summarized the detailed role of maresin-1 and its two different receptors in respiratory diseases. RORα and LGR6 are potential targets for the treatment of respiratory diseases. Future basic research and clinical trials on MaR1 and its receptors should provide useful information for the treatment of respiratory diseases.

Role of the BMP6 protein in breast cancer and other types of cancer

The BMP6 protein (Bone Morphogenetic Protein 6) is part of the superfamily of transforming growth factor-beta (TGF-β) ligands, participates in iron homeostasis, inhibits invasion by increasing adhesions and cell-cell type interactions and induces angiogenesis directly on vascular endothelial cells. BMP6 is coded by a tumor suppressor gene whose subexpression is related to the development and cancer progression; during neoplastic processes, methylation is the main mechanism by which gene silencing occurs. This work presents a review on the role of BMP6 protein in breast cancer (BC) and other types of cancer. The studies carried out to date suggest the participation of the BMP6 protein in the epithelial-mesenchymal transition (EMT) phenotype, cell growth and proliferation; however, these processes are affected in a variable way in the different types of cancer, the methylated CpG sites in BMP6 gene promoter, as well as the interaction with other proteins could be the cause of such variation.

Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

Methods

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.

Results

The six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.

Conclusions

Our study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

High expression of PTPRM predicts poor prognosis and promotes tumor growth and lymph node metastasis in cervical cancer

The prognosis for cervical cancer (CCa) patients with lymph node metastasis (LNM) is dismal. Elucidation of the molecular mechanisms underlying LNM may provide clinical therapeutic strategies for CCa patients with LNM. However, the precise mechanism of LNM in CCa remains unclear. Herein, we demonstrated that protein tyrosine phosphatase receptor type M (PTPRM), identified from TCGA dataset, was markedly upregulated in CCa with LNM and correlated with LNM. Moreover, PTPRM was an independent prognostic factor of CCa patients in multivariate Cox′s proportional hazards model analysis and associated with poor prognosis. Furthermore, through gain-of-function and loss-of-function approaches, we found that PTPRM promoted CCa cells proliferation, migration, invasion, lymphangiogenesis, and LNM. Mechanistically, PTPRM promoted epithelial–mesenchymal transition (EMT) via Src-AKT signaling pathway and induced lymphangiogenesis in a VEGF-C dependent manner, resulting in LNM of CCa. Importantly, knockdown of PTPRM dramatically reduced LNM in vivo, suggesting that PTPRM plays an important role in the LNM of CCa. Taken together, our findings uncover a novel molecular mechanism in the LNM of CCa and identify PTPRM as a novel prognostic factor and potential therapeutic target for LNM in CCa.

PFKP is highly expressed in lung cancer and regulates glucose metabolism

PURPOSE

Although it has been reported that up-regulation of phosphofructokinase (PFK) expression is a major feature of malignant tumors, the role of platelet type PFK (PFKP) in tumor initiation and progression is as yet poorly understood. The objective of this study was to evaluate PFKP expression in lung cancer and its effect on glycolysis, and to explore correlations between PFKP expression levels and clinical lung cancer patient features.

METHODS

PFKP mRNA expression levels in cancer tissues and adjacent normal tissues were compared using The Cancer Genome Atlas (TCGA) database. PFKP mRNA and protein expression levels in fresh lung cancer tissues and cell lines were assessed using quantitative real-time PCR and Western blotting. Immunohistochemistry (IHC) was used to assess PFKP expression in 150 archival lung adenocarcinoma samples, after which follow-up data and their correlations with clinical features and patient prognosis were evaluated. A retroviral shRNA-mediated method was used to construct stable cell lines expressing low levels of PFKP. Glucose, lactate and adenosine triphosphate concentrations in the cell culture supernatants were determined using enzymatic, spectrophotometric and enzyme-linked immunosorbent (ELISA) assays, respectively. The effect of PFKP expression on the proliferation of lung cancer cells was assessed using colony forming, MTT and flow cytometry assays, respectively. Finally, data from tissue samples of 533 patients with lung adenocarcinoma and 502 patients with lung squamous cell carcinoma were downloaded from the TCGA database, after which pathway and gene correlation information was retrieved using gene set enrichment analyses.

RESULTS

We found that PFKP was highly expressed in lung cancer tissues and cell lines. Using IHC we found that PFKP was highly expressed in primary lung adenocarcinoma tissues and that a high expression was associated with a poor prognosis. Clinical data analysis revealed that the PFKP expression levels correlated with tumor size and patient survival. Lung cancer cell lines with decreased PFKP expression levels showed significant decreases in glucose uptake rates, lactate levels and adenosine triphosphate concentrations. They also exhibited significantly decreased proliferation rates, colony forming abilities and increased G2/M cell cycle phase percentages. Gene set enrichment analysis revealed that multiple pathways, including glycolytic pathways, may be involved in the regulation PFKP.

CONCLUSIONS

Our data indicate that PFKP is highly expressed in lung cancer tissues and cell lines and is associated with tumor size and patient prognosis. As such, PFKP may serve as a prognostic biomarker. We also found that PFKP regulates the level of glycolysis in lung cancer cells and is associated with lung cancer cell proliferation. These data may be instrumental for the design of new lung cancer treatment options.

Downregulated SPINK4 is associated with poor survival in colorectal cancer

BACKGROUND

SPINK4 is known as a gastrointestinal peptide in the gastrointestinal tract and is abundantly expressed in human goblet cells. The clinical significance of SPINK4 in colorectal cancer (CRC) is largely unknown.

METHODS

We retrieved the expression data of 1168 CRC patients from 3 Gene Expression Omnibus (GEO) datasets (GSE24551, GSE39582, GSE32323) and The Cancer Genome Atlas (TCGA) to compare the expression level of SPINK4 between CRC tissues and normal colorectal tissues and to evaluate its value in predicting the survival of CRC patients. At the protein level, these results were further confirmed by data mining in the Human Protein Atlas and by immunohistochemical staining of samples from 81 CRC cases in our own center.

RESULTS

SPINK4 expression was downregulated in CRC compared with that in normal tissues, and decreased SPINK4 expression at both the mRNA and protein levels was associated with poor prognosis in CRC patients from all 3 GEO datasets, the TCGA database and our cohort. Additionally, lower SPINK4 expression was significantly related to higher TNM stage. Moreover, in multivariate regression, SPINK4 was confirmed as an independent indicator of poor survival in CRC patients in all databases and in our own cohort.

CONCLUSIONS

We concluded that reduced expression of SPINK4 relates to poor survival in CRC, functioning as a novel indicator.

Diagnostic Performance of Radial Probe Endobronchial Ultrasound without a Guide-Sheath and the Feasibility of Molecular Analysis

BACKGROUND

Radial probe endobronchial ultrasound (R-EBUS), is effective for tissue diagnosis of lung lesions. We evaluated the diagnostic performance of R-EBUS both a guide-sheath and fluoroscopy and identified factors associated with accurate diagnosis. The feasibility of molecular and genetic testing, using specimens obtained by R-EBUS, was also investigated.

METHODS

The study retrospectively reviewed 211 patients undergoing R-EBUS without a guide-sheath and fluoroscopy, June 2016-May 2017. After excluding 27 patients of which the target lesion was not reached, 184 were finally included. Multivariate logistic regression was used, to identify factors associated with accurate diagnosis.

RESULTS

Among 184 patients, R-EBUS-guided biopsy diagnosed malignancy in 109 patients (59%). The remaining 75 patients (41%) with non-malignant results underwent additional work-ups, and 34 were diagnosed with malignancy. Based on final diagnosis, diagnostic accuracy was 80% (136/170), and sensitivity and specificity for malignancy were 76% (109/143) and 100% (27/27), respectively. In multivariate analysis, peripheral location (adjusted odds ratio [aOR], 3.925; 95% confidence interval [CI], 1.203-12.811; p=0.023), and central position of the probe (aOR, 2.435; 95% CI, 1.424-7.013; p=0.035), were associated with accurate diagnosis of malignancy. Molecular and genetic analyses were successful, in all but one case, with inadequate specimens.

CONCLUSION

R-EBUS-guided biopsy without equipment, is effective for tissue diagnosis. Peripheral location and central position of the radial probe, were crucial for accurate diagnosis. Performance of molecular and genetic testing, using samples obtained by R-EBUS, was satisfactory.

Aberrant DOCK2, GRASP, HIF3A and PKFP Hypermethylation has Potential as a Prognostic Biomarker for Prostate Cancer

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75–94%) and specificity (84–100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP; 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24–3.10), adjusted p = 0.016; multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also.

PFKP Signaling at a Glance: An Emerging Mediator of Cancer Cell Metabolism

Phosphofructokinase-1 (PFK-1), a rate-determining enzyme of glycolysis, is an allosteric enzyme that regulates the oxidation of glucose in cellular respiration. Glycolysis phosphofructokinase platelet (PFKP) is the platelet isoform and works as an important mediator of cell metabolism. Considering that PFKP is a crucial player in many steps of cancer initiation and metastasis, we reviewed the specificities and complexities of PFKP and its biological roles in human diseases, especially malignant tumors. The possible use of PFKP as a diagnostic marker or a drug target in the prevention or treatment of cancer is also discussed.

Plasma metabolite profiling and chemometric analyses of tobacco snuff dippers and patients with oral cancer: Relationship between metabolic signatures

BACKGROUND

Cancer of oral cavity is a seriously growing problem in many parts of the world. In Indian subcontinent, most of these cases have been attributed to the use of tobacco-related products. This study is focused on the identification of distinguishing metabolites of oral cancer in comparison with tobacco snuff dippers and healthy controls.

METHODS

A total of 234 plasma samples including 62 healthy controls, 81 tobacco snuff dippers, and 91 oral cancer samples were analyzed using mass spectrometry.

RESULTS

Twenty-nine of 3326 metabolites were found to distinguish among oral cancer, tobacco snuff dippers, and healthy controls using P-value ≤.001 and fold change ≥3. Prediction model was generated with an overall accuracy of 89.3%. Two metabolites, that is, stearyl alcohol and sucrose, can be used as predictive biomarkers showing progression of tobacco snuff dippers toward oral cancer.

CONCLUSION

The unique metabolite profile gives evidence of a strong correlation between tobacco snuff dipping and oral cancer.

Aberrant CpG-methylation affects genes expression predicting survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common diagnosed disease with high-mortality rate, and its prognostic implications are under discovered. DNA methylation aberrations are not only an important event for dysregulation of gene expression during tumorigenesis but also a revolution in epigenetics by identifying key prognostic biomarkers for multiple cancers. In this study, we analyzed methylation status of 485 578 CpG sites and RNA-seq transcriptomes of 20 532 genes for 1095 LUAD samples in TCGA database. The association between DNA methylation and the prognostic value of the corresponding gene expression was identified as well. In total, ten aberrantly methylated and dysregulated genes (AURKA, BLK, CNTN2, HMGA1, PTTG1, TNS4, DAPK2, MFSD2A, THSD1, and WNT7A) were highlighted which were significantly correlated with overall survival of 492 LUAD patients, which were all reported as tumor-associated genes in other various cancers and worthy of further investigated and might be used as therapeutic targets for LUAD. Together, methylation aberrances regulate gene expression level during tumorigenesis and influence prognosis of LUAD patients. Integrating knowledge of epigenetics and expression of genes can be useful for an in-depth understanding of cancer mechanism and for the eventual purpose of precisely prognostic and therapeutic target verification.

Analysis of change in microRNA expression profiles of lung cancer A549 cells treated with Radix tetrastigma hemsleyani flavonoids

Background

The aim of this study was to determine the inhibition effects of Radix tetrastigma hemsleyani (RTH) flavonoids on human lung adenocarcinoma A549 cells and the underlying molecular mechanism. RTH is an important Chinese traditional herb that has been widely used in cancer therapy. As an important type of active substance, RTH flavones (RTHF) have been shown to have good antiproliferative effects on various cancer cells. MicroRNAs (miRNAs) are small, noncoding RNA molecules that play important roles in cancer progression and prevention. However, the miRNA profile of RTHF-treated A549 cells has not yet been studied.

Materials and methods

The miRNA expression profile changes of A549 cell treated with RTHF were determined using the miRNA-seq analysis. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed miRNAs' (DE-miRNAs) target genes were carried out.

Results

In this study, we identified 162 miRNAs that displayed expression changes >1.2-fold in RTHF-treated A549 cells. GO analysis results showed that target genes of DE-miRNAs were significantly enriched in protein binding, binding, cell, cell part, intracellular, cellular process, single-organism process, and single-organism cellular process. Pathway analysis illustrated that target genes of DE-miRNAs are mainly involved in endocytosis, axon guidance, lysosome, melanogenesis, and acute myeloid leukemia pathway.

Conclusion

These results may assist in the better understanding of the anticancer effects of RTHF in A549 cells.

Hybrid Method Based on Information Gain and Support Vector Machine for Gene Selection in Cancer Classification

It remains a great challenge to achieve sufficient cancer classification accuracy with the entire set of genes, due to the high dimensions, small sample size, and big noise of gene expression data. We thus proposed a hybrid gene selection method, Information Gain-Support Vector Machine (IG-SVM) in this study. IG was initially employed to filter irrelevant and redundant genes. Then, further removal of redundant genes was performed using SVM to eliminate the noise in the datasets more effectively. Finally, the informative genes selected by IG-SVM served as the input for the LIBSVM classifier. Compared to other related algorithms, IG-SVM showed the highest classification accuracy and superior performance as evaluated using five cancer gene expression datasets based on a few selected genes. As an example, IG-SVM achieved a classification accuracy of 90.32% for colon cancer, which is difficult to be accurately classified, only based on three genes including CSRP1, MYL9, and GUCA2B.

Parametric Linkage Analysis Identifies Five Novel Genome-Wide Significant Loci for Familial Lung Cancer

OBJECTIVE

One of four American cancer patients dies of lung cancer. Environmental factors such as tobacco smoking are known to affect lung cancer risk. However, there is a genetic factor to lung cancer risk as well. Here, we perform parametric linkage analysis on family-based genotype data in an effort to find genetic loci linked to the disease.

METHODS

197 individuals from families with a high-risk history of lung cancer were recruited and genotyped using an Illumina array. Parametric linkage analyses were performed using an affected-only phenotype model with an autosomal dominant inheritance using a disease allele frequency of 0.01. Three types of analyses were performed: single variant two-point, collapsed haplotype pattern variant two-point, and multipoint analysis.

RESULTS

Five novel genome-wide significant loci were identified at 18p11.23, 2p22.2, 14q13.1, 16p13, and 20q13.11. The families most informative for linkage were also determined.

CONCLUSIONS

The 5 novel signals are good candidate regions, containing genes that have been implicated as having somatic changes in lung cancer or other cancers (though not in germ line cells). Targeted sequencing on the significant loci is planned to determine the causal variants at these loci.