Meta-analysis of mRNA expression profiles to identify differentially expressed genes in lung adenocarcinoma tissue from smokers and non-smokers

Role of chromosomal cohesion and separation in aneuploidy and tumorigenesis

Cell division is a crucial process, and one of its essential steps involves copying the genetic material, which is organized into structures called chromosomes. Before a cell can divide into two, it needs to ensure that each newly copied chromosome is paired tightly with its identical twin. This pairing is maintained by a protein complex known as cohesin, which is conserved in various organisms, from single-celled ones to humans. Cohesin essentially encircles the DNA, creating a ring-like structure to handcuff, to keep the newly synthesized sister chromosomes together in pairs. Therefore, chromosomal cohesion and separation are fundamental processes governing the attachment and segregation of sister chromatids during cell division. Metaphase-to-anaphase transition requires dissolution of cohesins by the enzyme Separase. The tight regulation of these processes is vital for safeguarding genomic stability. Dysregulation in chromosomal cohesion and separation resulting in aneuploidy, a condition characterized by an abnormal chromosome count in a cell, is strongly associated with cancer. Aneuploidy is a recurring hallmark in many cancer types, and abnormalities in chromosomal cohesion and separation have been identified as significant contributors to various cancers, such as acute myeloid leukemia, myelodysplastic syndrome, colorectal, bladder, and other solid cancers. Mutations within the cohesin complex have been associated with these cancers, as they interfere with chromosomal segregation, genome organization, and gene expression, promoting aneuploidy and contributing to the initiation of malignancy. In summary, chromosomal cohesion and separation processes play a pivotal role in preserving genomic stability, and aberrations in these mechanisms can lead to aneuploidy and cancer. Gaining a deeper understanding of the molecular intricacies of chromosomal cohesion and separation offers promising prospects for the development of innovative therapeutic approaches in the battle against cancer.

Genes involved in immune, gene translation and chromatin organization pathways associated with Mycoplasma ovipneumoniae presence in nasal secretions of domestic sheep

Mycoplasma ovipneumoniae contributes to polymicrobial pneumonia in domestic sheep. Elucidation of host genetic influences of M. ovipneumoniae nasal detection has the potential to reduce the incidence of polymicrobial pneumonia in sheep through implementation of selective breeding strategies. Nasal mucosal secretions were collected from 647 sheep from a large US sheep flock. Ewes of three breeds (Polypay n = 222, Rambouillet n = 321, and Suffolk n = 104) ranging in age from one to seven years, were sampled at three different times in the production cycle (February, April, and September/October) over four years (2015 to 2018). The presence and DNA copy number of M. ovipneumoniae was determined using a newly developed species-specific qPCR. Breed (P<0.001), age (P<0.024), sampling time (P<0.001), and year (P<0.001) of collection affected log10 transformed M. ovipneumoniae DNA copy number, where Rambouillet had the lowest (P<0.0001) compared with both Polypay and Suffolk demonstrating a possible genetic component to detection. Samples from yearlings, April, and 2018 had the highest (P<0.046) detected DNA copy number mean. Sheep genomic DNA was genotyped with the Illumina OvineHD BeadChip. Principal component analysis identified most of the variation in the dataset was associated with breed. Therefore, genome wide association analysis was conducted with a mixed model (EMMAX), with principal components 1 to 6 as fixed and a kinship matrix as random effects. Genome-wide significant (P<9x10-8) SNPs were identified on chromosomes 6 and 7 in the all-breed analysis. Individual breed analysis had genome-wide significant (P<9x10-8) SNPs on chromosomes 3, 4, 7, 9, 10, 15, 17, and 22. Annotated genes near these SNPs are part of immune (ANAPC7, CUL5, TMEM229B, PTPN13), gene translation (PIWIL4), and chromatin organization (KDM2B) pathways. Immune genes are expected to have increased expression when leukocytes encounter M. ovipneumoniae which would lead to chromatin reorganization. Work is underway to narrow the range of these associated regions to identify the underlying causal mutations.

Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What's more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.

Analysis of four complete linkage sequence variants within a novel lncRNA located in a growth QTL on chromosome 1 related to growth traits in chickens

An increasing number of studies have shown that quantitative trait loci (QTLs) at the end of chromosome 1 identified in different chicken breeds and populations exert significant effects on growth traits in chickens. Nevertheless, the causal genes underlying the QTL effect remain poorly understood. Using an updated gene database, a novel lncRNA (named LncFAM) was found at the end of chromosome 1 and located in a growth and digestion QTL. This study showed that the expression level of LncFAM in pancreas tissues with a high weight was significantly higher than that in pancreas tissues with a low weight, which indicates that the expression level of LncFAM was positively correlated with various growth phenotype indexes, such as growth speed and body weight. A polymorphism screening identified four polymorphisms with strong linkage disequilibrium in LncFAM: a 5-bp indel in the second exon, an A/G base mutation, and 7-bp and 97-bp indels in the second intron. A study of a 97-bp insertion in the second intron using an F2 chicken resource population produced by Anka and Gushi chickens showed that the mutant individuals with genotype II had the highest values for body weight (BW) at 0 days and 2, 4, 6, 8, 10 and 12 weeks, shank girth (SG) at 4, 8 and 12 weeks, chest width (CW) at 4, 8 and 12 weeks, body slant length (BSL) at 8 and 12 weeks, and pelvic width (PW) at 4, 8 and 12 weeks, followed by ID and DD genotypes. The amplification and typing of 2,716 chickens from ten different breeds, namely, the F2 chicken resource population, dual-type chickens, including Xichuan black-bone chickens, Lushi green-shell layers, Dongxiang green-shell layers, Changshun green-shell layers, and Gushi chickens, and commercial broilers, including Ross 308, AA, Cobb and Hubbard broilers, revealed that II was the dominant genotype. Interestingly, only genotype II existed among the tested populations of commercial broilers. Moreover, the expression level in the pancreas tissue of Ross 308 chickens was significantly higher than that in the pancreas tissue of Gushi chickens (P < 0.001), which might be related to the conversion rates among different chickens. The prediction and verification of the target gene of LncFAM showed that LncFAM might regulate the expression of its target gene FAM48A through cis-expression. Our results provide useful information on the mutation of LncFAM, which can be used as a potential molecular breeding marker.

Differential expression of lung adenocarcinoma transcriptome with signature of tobacco exposure

Smoking accounts for almost 80-90% of lung cancer cases, which is also the most frequent cause of cancer-related deaths in humans. With over 60 carcinogens in tobacco smoke, cells dividing at the time of carcinogen exposure are at particular risk of neoplasia. The present study aimed to investigate global gene expression differences in lung adenocarcinoma (LUAD) tumour samples of current smokers and non-smokers, in an attempt to elucidate biological mechanisms underlying divergent smoking effects. Current and non-smoker tumour samples were analysed using bioinformatics tools, examining differences in molecular drivers of cancer initiation and progression, as well as evaluating the effect of smoking and sex on epithelial mesenchymal transition (EMT). As a result, we identified 1150 differentially expressed genes showing visible differences in the expression profiles between the smoking subgroups. The genes were primarily involved in cell cycle, DNA replication, DNA repair, VEGF, GnRH, ErbB and T cell receptor signalling pathways. Our results show that smoking clearly affected E2F transcriptional activity and DNA repair pathways including mismatch repair, base excision repair and homologous recombination. We observed that sex could modify the effects of PLA2G2A and PRG4 in LUAD tumour samples, whereas sex and smoking status might possibly have a biological effect on the EMT-related genes: HEY2, OLFM1, SFRP1 and STRAP. We also identified potential epigenetic changes smoking solely might have on EMT-related genes, which may serve as potential diagnostic and prognostic biomarkers for LUAD patients.

Identification of feature risk pathways of smoking-induced lung cancer based on SVM

Objective

The present study aims to explore the role of smoking factors in the risk of lung cancer and screen the feature risk pathways of smoking-induced lung cancer.

Methods

The expression profiles of the patient data from GEO database were standardized, and differentially expressed genes (DEGs) were analyzed by limma algorithm. Samples and genes were analyzed by Unsupervised hierarchical clustering method, while GO and KEGG enrichment analyses were performed on DEGs. The data of the protein-protein interaction (PPI) network were downloaded from the BioGrid and HPRD databases, and the DEGs were mapped into the PPI network to identify the interaction relationship. The enriched significant pathways were used to calculate the anomaly score and RFE method was used to optimize the feature sets. The model was trained using the support vector machine (SVM) and the predicted results were plotted into ROC curves. The AUC value was calculated to evaluate the predictive performance of the SVM model.

Results

A total of 1923 DEGs were obtained, of which 826 were down-regulated and 1097 were up-regulated. Unsupervised hierarchical clustering analysis showed that the diagnosis accuracy of lung cancer smokers was 74%, and that of non-lung cancer smokers was 75%. Five optimal feature pathway sets were obtained by screening, the clinical diagnostic ability of which was detected by SVM model with the accuracy improved to 84%. The diagnostic accuracy was 90% after combining clinical information.

Conclusion

We verified that five signaling pathways combined with clinical information could be used as a feature risk pathway for identifying lung cancer smokers and non-lung cancer smokers and increased the diagnostic accuracy.

A pilot study of cdc6 as a biomarker for circulating tumor cells in patients with lung cancer

BACKGROUND

Cell division cycle 6 (cdc6) is a key factor of DNA replication initiation license system and a proto-oncogene. It has been detected in some tumor tissues to aid cancer diagnosis in many research projects. However, it remains unclear that if cdc6 could be detected in the peripheral blood, just like liquid biopsy, in solid tumor patients. The aim of this study is to investigate the possibility of cdc6 as a biomarker for circulating tumor cells in patients with lung cancer.

METHODS

We first detected the expression of cdc6 in peripheral blood mononuclear cells (PBMCs) and tumor cells by in situ hybridization with cdc6 RNA probe. Then, we examined the expression of cdc6 in PBMCs from health individual, mononuclear cells from cord blood, or A549 cell line by RT-qPCR. Furthermore, we used RT-qPCR to test the cdc6 expression in PBMCs from tumor patients (test group) and non-tumor individuals as a control group. Chi-square test with Fisher's exact test was used to analyze the statistical significance of the difference. P < .05 is considered as statistically significant difference.

RESULTS

When compared the cdc6 expression in cells from difference sources, we found that A549 tumor cell line had the strongest expression of cdc6, samples from cord blood showed the least expression level, indicating the detection strategy of RT-qPCR is reasonable. Using this method, we studied whether cdc6 in Peripheral blood could be detected as a biomarker by examining cdc6 expression from PBMCs of patients with lung cancer. We found 20% of patients with lung cancer were cdc6 positive in PBMCs, whereas only 4.26% was found positive in the control group (P = .039, P < .05).

CONCLUSION

Cell division cycle 6 has a potential to be used as a circulating tumor cell biomarker for lung cancer. Further study in clinical application is still broad needed.

Identification of potential key genes and pathways in hepatitis B virus-associated hepatocellular carcinoma by bioinformatics analyses

Chronic hepatitis B virus (HBV) is one of the leading causes of hepatocellular carcinoma (HCC). The precise molecular mechanisms by which HBV contributes to HCC development are not fully understood. The key genes and pathways involved in the transformation of nontumor hepatic tissues into HCC tissues in patients with HBV infection are essential to guide the treatment of HBV-associated HCC. Five datasets were collected from the Gene Expression Omnibus database to form a large cohort. Differentially expressed genes (DEGs) were identified between HCC tissues and nontumor hepatic tissues from HBV-infected patients using the ‘limma’ package. The top 50 upregulated and top 50 downregulated DEGs in HCC vs. nontumor tissues were demonstrated in subsets by heat maps. Based on the DEGs, Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analyses were performed. Several key pathways of the up- and downregulated DEGs were identified and presented by protein-protein interaction (PPI) networks. A total of 1,934 DEGs were identified. The upregulated DEGs were primarily associated with the ‘cell cycle’. Among the DEGs enriched in the ‘cell cycle’ pathway, 6 genes had a log₂-fold change >2: SFN, BUB1B, TTK, CCNB1, CDK1 and CDC20. The downregulated DEGs were primarily associated with the metabolic pathways, such as ‘carbon metabolism’, ‘glycine, serine and threonine metabolism’, ‘tryptophan metabolism’, ‘retinol metabolism’ and ‘alanine, aspartate and glutamate metabolism’. The DEGs in the ‘cell cycle’ and ‘metabolic pathways’ were presented by the PPI networks respectively. Overall, the present study provides new insights into the specific etiology of HCC and molecular mechanisms for the transformation of nontumor hepatic tissues into HCC tissues in patients with a history of HBV infection and several potential therapeutic targets for targeted therapy in these patients.

Identification of differentially expressed protein-coding genes in lung adenocarcinomas

Lung adenocarcinoma accounts for a high proportion of lung cancers. Though efforts have been made to develop new and effective treatments for this disease, the mortality rate remains high. Gene expression microarrays facilitate the study of lung cancer at the molecular level. The present study aimed to detect differentially expressed protein-coding genes to identify novel biomarkers and therapeutic targets for lung adenocarcinoma. Aberrations in gene expression in lung adenocarcinoma were determined by analysis of mRNA microarray datasets from the Gene Expression Omnibus database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) networks and statistical analysis were used to identify the biological functions of the differentially expressed genes (DEGs). The results of the bioinformatics analysis were subsequently validated using reverse transcription-quantitative PCR. A total of 303 DEGs were identified in lung adenocarcinomas, and they were enriched in a number of cancer-associated GO terms and KEGG pathways. DNA topoisomerase 2α (TOP2A), cell division cycle protein homolog 20 (CDC20), mitotic checkpoint serine/threonine protein kinase BUB1 (BUB1) and mitotic spindle assembly checkpoint protein MAD2A (MAD2L1) exhibited the highest degree of interaction in the PPI network. Survival analysis performed using Kaplan-Meier curves and Cox regression indicated that these four genes were all significantly associated with the survival of patients with lung adenocarcinomas. In conclusion, TOP2A, CDC20, BUB1 and MAD2L1 may be key protein-coding genes that may serve as biomarkers and therapeutic targets in lung adenocarcinomas.

Clinical Significance And Integrative Analysis Of Kinesin Family Member 18B In Lung Adenocarcinoma

Background

Kinesin family member 18B (KIF18B) is a member of the kinesin-8 superfamily, and functions as an oncogene in human cancers. However, its expression profile and role in lung adenocarcinoma (LUAD) remain unclear.

Materials and methods

We examined the expression profile of KIF18B using quantitative real-time reverse transcription polymerase chain reaction and immunohistochemistry in fresh clinical samples. Using data downloaded from the Cancer Genome Atlas database and Gene Expression Omnibus, we explored the clinical significance of KIF18B, potential mechanisms of its dysregulation and its underlying biological function in LUAD.

Results

KIF18B was significantly over-expressed in LUAD tissues relative to normal tissues. High KIF18B expression was associated with smoking history, positive nodal invasion, advanced clinical stage, death status and poorer prognosis. Cox regression analyses revealed that KIF18B overexpression was an independent prognostic biomarker for poor overall survival (OS) and recurrence-free survival in LUAD. In addition, KIF18B mutation was observed in 2.2% of LUAD cases. DNA copy number variation was correlated with upregulated expression of KIF18B in LUAD tissues and cell lines. The methylation level of some KIF18B DNA CpG sites was negatively associated with its mRNA expression. KIF18B was predictively targeted by miR-125a-5p, which was downregulated in LUAD tissues, inversely correlated with KIF18B mRNA expression and significantly associated with poor OS. Furthermore, gene set enrichment analysis revealed that genes positively co-expressed with KIF18B were mainly enriched in cell cycle signaling pathways.

Conclusion

Our results indicate that KIF18B is a promising prognostic biomarker for LUAD. DNA amplification, hypomethylation as well as miR-125a-5p downregulation may be involved in the mechanism of KIF18B dysregulation in LUAD. KIF18B might function as a novel oncogene through cell cycle regulation pathways in LUAD.

Identification of differentially expressed genes in small and non-small cell lung cancer based on meta-analysis of mRNA

Lung cancer has the lowest survival rate spread globally resulting in a large number of deaths. This is attributed to insufficient measures such as lack of early detection and chemoresistance in the patients. It can be subdivided into two histological groups: Non-Small-Cell Lung Cancer (NSCLC), which is most prevalent (85% of all lung cancers) but less destructive; and Small-Cell Lung Cancer (SCLC), which is intermittently metastatic and less prevalent (15% of all lung cancers). The present study deals with the analysis of gene expression of two subtypes to identify the Differentially Expressed Genes (DEGs). For this study, we selected two datasets from the Omnibus database, which included 50 non-small cell lung cancer samples, 31 small cell lung cancer samples, and 48 samples from normal lung tissue. After DEGs identification using the meta-analysis approach, they were then subjected to further analysis following p-value adjustment via the Benjamini-Hochberg method. We identified 440 overexpressed and 489 underexpressed genes in NSCLC, and 489 overexpressed and 525 underexpressed genes in SCLC, compared with normal lung tissues. Furthermore, we identified 3 overlapping genes between upregulated DEGs in NSCLC and downregulated DEGs in SCLC; and 8 overlapping genes between upregulated DEGs in SCLC and downregulated DEGs in NSCLC. Accordingly, a Protein-Protein Interaction (PPI) network of the overlapping genes was generated, which contained a total of 261 genes, of which the top five were TRIM29, ANK3, CSTA, FGG, and AGR2. These five candidate genes reported herein may prove to be potential therapeutic targets.

A 5-gene prognostic nomogram predicting survival probability of glioblastoma patients

BACKGROUND

Glioblastoma (GBM) remains the most biologically aggressive subtype of gliomas with an average survival of 10 to 12 months. Considering that the overall survival (OS) of each GBM patient is a key factor in the treatment of individuals, it is meaningful to predict the survival probability for GBM patients newly diagnosed in clinical practice.

MATERIAL AND METHODS

Using the TCGA dataset and two independent GEO datasets, we identified genes that are associated with the OS and differentially expressed between GBM tissues and the adjacent normal tissues. A robust likelihood-based survival modeling approach was applied to select the best genes for modeling. After the prognostic nomogram was generated, an independent dataset on different platform was used to evaluate its effectiveness.

RESULTS

We identified 168 differentially expressed genes associated with the OS. Five of these genes were selected to generate a gene prognostic nomogram. The external validation demonstrated that 5-gene prognostic nomogram has the capability of predicting the OS of GBM patients.

CONCLUSION

We developed a novel and convenient prognostic tool based on five genes that exhibited clinical value in predicting the survival probability for newly diagnosed GBM patients, and all of these five genes could represent potential target genes for the treatment of GBM. The development of this model will provide a good reference for cancer researchers.

Downregulation of miR‑224‑5p in prostate cancer and its relevant molecular mechanism via TCGA, GEO database and in silico analyses

The function of the expression of microRNA (miR)-224-5p in prostate adenocarcinoma (PCa) remains to be elucidated, therefore, the present study aimed to investigate the clinical significance and potential molecular mechanism of miR-224-5p in PCa. Data on the expression of miR-224-5p in PCa were extracted from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), ArrayExpress and previous literature, and meta-analyses with standardized mean difference (SMD) and summary receiver operating characteristic (sROC) methods were performed for statistical analyses. The prospective target genes of miR-224-5p were collected by overlapping the differentially expressed mRNAs in TCGA and GEO, and target genes predicted by miRWalk2.0. Subsequently, in silico analysis was performed to examine the associated pathways of miR-224-5p in PCa. The expression of miR-224-5p was markedly lower in PCa; the overall SMD was −0.562, and overall sROC area under the curve was 0.80. In addition, Kyoto Encyclopedia of Genes and Genomes analysis revealed that the prospective target genes of miR-224-5p were largely enriched in the amino sugar and nucleotide sugar metabolism signaling pathway, and three genes [UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1), hexokinase 2 (HK2) and chitinase 1 (CHIT1)] enriched in this pathway showed higher expression (P<0.05). In addition, key genes in the protein-protein interaction network analysis [DNA topoisomerase 2-α (TOP2A), ATP citrate lyase (ACLY) and ribonucleotide reductase regulatory subunit M2 (RRM2)] exhibited significantly increased expression (P<0.05). The results suggested that the downregulated expression of miR-224-5p may be associated with the clinical progression and prognosis of PCa. Furthermore, miR-224-5p likely exerts its effects by targeting genes, including UAP1, HK2, CHIT1, TOP2A, ACLY and RRM2. However, in vivo and in vitro experiments are required to confirm these findings.