Identification of differentially expressed genes using microarray analysis and COL6A1 induction of bone metastasis in non-small cell lung cancer

COL6A1 Inhibits the Malignant Development of Bladder Cancer by Regulating FBN1

Bladder cancer (BLCA) is a prevalent malignancy worldwide with a high recurrence rate. Collagen Type VI Alpha 1 (COL6A1) plays a key role in several cancer types. In this study, we aimed to explore the role of COL6A1 in BLCA. COL6A1 expression in BLCA was determined using The Cancer Genome Atlas database and real-time quantitative polymerase chain reaction (RT-qPCR). Counting Kit-8, wound-healing, and transwell assays were used to assess the effect of COL6A1 on T24 and 5637 cells. Apoptosis in BLCA cell lines was explored using western blotting and flow cytometry. Co-immunoprecipitation was performed to determine interactions between proteins. The role of COL6A1 in tumor growth in nude mice was evaluated by hematoxylin-eosin, immunohistochemical, and terminal deoxynucleotidyl transferase dUTP Nick-End Labeling. In BLCA, COL6A1 expression was downregulated. Moreover, the COL6A1 overexpression suppressed the viability, migration, and invasion, while promoting apoptosis of BLCA cell lines, with increased Caspase-3, Bax, and p53, and decreased Bcl-2. Conversely, silencing of COL6A1 promoted proliferation, migration, and invasion, while inhibiting apoptosis in BLCA cell lines. In vivo, COL6A1 inhibits tumor growth and progression. Fibrillin-1 (FBN1) was positively correlated with COL6A1 expression. COL6A1 could bind to FBN1 in BLCA cell lines. The expression of FBN1 in BLCA cell lines decreased after COL6A1 silencing, whereas COL6A1 overexpression upregulated FBN1 expression. COL6A1 was downregulated and exerted an inhibitory effect on the development of BLCA, and its expression was positively correlated with the expression of FBN1.

Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset

BACKGROUND

Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between the miRNA expression profiles and BM occurrence in patients with LUAD remains unclear.

METHODS

We conducted an analysis to identify miRNAs in tissue samples that exhibited different expression levels between patients with and without BM. Using a machine learning approach, we confirmed whether the miRNA profile could be a predictive tool for BM. We performed pathway analysis of miRNA target genes using a matched mRNA dataset.

RESULTS

We selected 25 miRNAs that consistently exhibited differential expression between the two groups of 32 samples. The 25-miRNA profile demonstrated a strong predictive potential for BM in both Group 1 and Group 2 and the entire dataset (area under the curve [AUC] = 0.918, accuracy = 0.875 in Group 1; AUC = 0.867, accuracy = 0.781 in Group 2; and AUC = 0.908, accuracy = 0.875 in the entire group). Patients predicted to have BM, based on the 25-miRNA profile, had lower survival rates. Target gene analysis of miRNAs suggested that BM could be induced through the ErbB signaling pathway, proteoglycans in cancer, and the focal adhesion pathway. Furthermore, patients predicted to have BM based on the 25-miRNA profile exhibited higher expression of the epithelial-mesenchymal transition signature, TWIST, and vimentin than those not predicted to have BM. Specifically, there was a correlation between EGFR mRNA levels and BM.

CONCLUSIONS

This 25-miRNA profile may serve as a biomarker for predicting BM in patients with LUAD.

Changes in the expression of cell interaction-related pathways during brain metastasis in lung adenocarcinoma: Gene expression and immunohistochemical analysis

BACKGROUND

Brain metastasis (BM) is a prevalent prognostic event in the development of lung adenocarcinoma (LUAD) with a poor prognosis. Alterations in gene or protein expression during various phases of BM remain unclear.

METHODS

We performed gene expression and pathway analyses using a metastasis-related gene panel on 12 lung tissues from patients with confirmed BM, 12 lung tissues from patients without BM, and 12 matched brain tissues from patients with confirmed BM during follow-up after LUAD surgery. The results of the gene expression analysis were validated by immunohistochemistry.

RESULTS

Cell interaction-related pathways (such as focal adhesion, extracellular matrix-receptor interaction, and proteoglycans in cancer) showed the greatest differences among the three groups. Expression of the cell interaction-related pathway was highest in the lung sample of BM group and lowest in the matched brain tissue. Using a machine learning model, a signature of 20 genes from cell interaction-related pathways accurately predicted BM (area under the curve score of 0.792 and an accuracy rate of 0.875). Immunohistochemical analysis showed higher expression of proteins associated with cell interaction-related genes and a mesenchymal phenotype in the lung sample of BM group than in those without BM or matched brain tissue.

CONCLUSIONS

LUAD acquires the characteristics of the cell interaction-related pathway that leads to the development of BM, with a significant decrease in expression following brain colonization.

What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years

BACKGROUND

Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures.

AIM

To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research.

METHODS

We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide.

RESULTS

Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence.

CONCLUSION

Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

Exosomal hsa-miR-151a-3p and hsa-miR-877-5p are potential novel biomarkers for predicting bone metastasis in lung cancer

Exosomal miRNAs (exo-miRNAs) have arisen as novel diagnostic biomarkers for various cancers. However, few reports on exo-miRNAs related to bone metastasis (BM) in lung cancer exist. This study aims to screen out key exo-miRNAs and estimate their prognostic values for predicting BM in lung cancer. The differentially expressed exo-miRNAs between the highly-metastatic (95D) and lowly-metastatic (A549) human lung cancer cell lines were comprehensively analyzed using high-throughput sequencing followed by bioinformatic analyses. 29 candidate exo-miRNAs were identified, and 101 BM-related target genes were predicted. Enrichment analysis revealed that these target genes were mainly involved in regulating transcription and pathways in cancer. An exosomal miRNA-mRNA regulatory network consisting of 7 key miRNAs and 10 hub genes was constructed. Further function analysis indicated that these 10 hub genes were mainly enriched in regulating cancer's apoptosis and central carbon metabolism. The survival analysis indicated that 7 of 10 hub genes were closely related to prognosis. Mutation analysis showed that lung cancer patients presented certain genetic alterations in the 7 real hub genes. GSEA for a single hub gene suggested that 6 of 7 real hub genes had close associations with lung cancer development. Finally, ROC analysis revealed that hsa-miR-151a-3p and hsa-miR-877-5p provided high diagnostic accuracy in discriminating patients with bone metastasis (BM+) from patients without bone metastasis (BM-). These findings provided a comprehensive analysis of exo-miRNAs and target genes in the regulatory network of BM in lung cancer. In particular, hsa-miR-151a-3p and hsa-miR-877-5p may be novel biomarkers for predicting BM in lung cancer.

Immunological role and clinical prognostic significance of P2RY6 in lung adenocarcinoma: a multi-omics studies and single-cell sequencing analysis

BACKGROUND

There is increasing evidence that recombinant human P2Y purinoceptor 6 (P2RY6) may be involved in inflammatory responses. However, the role of P2RY6 in lung adenocarcinoma (LUAD) remains unknown.

METHODS

We used transcriptomic, genomic, single-cell transcriptomic, and methylation sequencing data from The Cancer Genome Atlas database to analyze the aberrant status and prognostic value of P2RY6 in a variety of tumors. The LUAD single-cell sequencing dataset was used to explore the effect of P2RY6 on the tumor microenvironment. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify immune cells in the tumor microenvironment. We also analyzed the correlation of P2RY6 with immune checkpoints and immune regulation-related genes. The correlation of between tumor mutation burden (TMB), microsatellite instability (MSI), and P2RY6 expression was also analyzed simultaneously. Tissue microarray and immunohistochemistry were employed to assess the expression of P2RY6 in internal tumor samples.

RESULTS

Our findings indicate that P2RY6 exhibits significantly higher expression levels in various cancer tissues, particularly in LUAD. High expression of P2RY6 was closely associated with a poor prognosis for patients, and it plays a role in regulating immune-related pathways, such as cytokine-cytokine receptor interaction. Notably, P2RY6 expression is closely linked to the abundance of CD8 + T cells. Furthermore, we have developed a P2RY6-related inflammation prediction model that demonstrates promising results in predicting the prognosis of LUAD patients, with an AUC (area under the curve) value of 0.83. This performance is significantly better than the traditional TNM staging system. Through single-cell transcriptome sequencing analysis, we observed that high P2RY6 expression is associated with increased intercellular communication. Additionally, pathway enrichment analysis revealed that P2RY6 influences antigen presentation and processing pathways within the LUAD microenvironment.

CONCLUSIONS

This study suggests that P2RY6 would be a new target for immunotherapy in LUAD.

PECAM1 plays a role in the pathogenesis and treatment of bone metastases

Bone is the third most common metastatic site for all primary tumors, the common primary focus of bone metastases include breast cancer, prostate cancer, and so on. And the median survival time of patients with bone metastases is only 2–3 years. Therefore, it is urgent to develop new targets to diagnose and treat bone metastases. Based on two data sets GSE146661 and GSE77930 associated with bone metastases, it was found that 209 genes differentially expressed in bone metastases group and control group. PECAM1 was selected as hub-gene for the follow-up research after constructing protein-protein interaction (PPI) network and enrichment analysis. Moreover, q-PCR analysis verified that the expression of PECAM1 decreased in bone metastatic tumor tissues. PECAM1 was believed to be possibly related to the function of osteoclasts, we knocked down the expression of PECAM1 with shRNA in lymphocytes extracted from bone marrow nailed blood. The results indicated that sh-PECAM1 treatment could promote osteoclast differentiation, and the sh-PECAM1-treated osteoclast culture medium could significantly promote the proliferation and migration of tumor cells. These results suggested that PECAM1 may be a potential biomarker for the diagnosis and treatment of bone metastases of tumor.

Adding recombinant AAVs to the cancer therapeutics mix

Gene therapy is a powerful biological tool that is reshaping therapeutic landscapes for several diseases. Researchers are using both non-viral and viral-based gene therapy methods with success in the lab and the clinic. In the cancer biology field, gene therapies are expanding treatment options and the possibility of favorable outcomes for patients. While cellular immunotherapies and oncolytic virotherapies have paved the way in cancer treatments based on genetic engineering, recombinant adeno-associated virus (rAAV), a viral-based module, is also emerging as a potential cancer therapeutic through its malleability, specificity, and broad application to common as well as rare tumor types, tumor microenvironments, and metastatic disease. A wide range of AAV serotypes, promoters, and transgenes have been successful at reducing tumor growth and burden in preclinical studies, suggesting more groundbreaking advances using rAAVs in cancer are on the horizon.

A pan-cancer analysis of collagen VI family on prognosis, tumor microenvironment, and its potential therapeutic effect

Background

Collagen VI family (COL6A) is a major member of extracellular matrix protein. There is accumulating evidence that COL6A is involved in tumorigenesis and tumor progression. In this study, we performed a systematic analysis of COL6A in pan-cancer based on their molecular features and clinical significance.

Methods

Based on updated public databases, we integrated several bioinformatics analysis methods to investigate the expression levels of COL6A as well as the relationship between their expression and patient survival, immune subtypes, tumor microenvironment, stemness scores, drug sensitivity, and DNA methylation.

Results

The expression levels of COL6A members varied in different cancers, suggesting their expression was cancer-dependent. Among COL6A members, COL6A1/2/3 were predicted poor prognosis in specific cancers. Furthermore, COL6A1/2/3 expression levels revealed a clear correlation with immune subtypes, and COL6A1/2/3 were associated with tumor purity, that is, gene expression levels were generally higher in tumors with higher stromal scores and immune scores. COL6A1/2/3 had a significantly negative correlation with RNA stemness scores, and meanwhile they were also related to DNA stemness scores in different degrees. In addition, the expression of COL6A1/2/3 was significantly related to drug sensitivity of cancer cells. Finally, our study revealed that COL6A1/2/3 expression was mainly negatively correlated with gene methylation, and the methylation levels showed remarkable differences in various cancers.

Conclusions

These findings highlight both the similarities and differences in the molecular characteristics of COL6A members in pan-cancer, and provide comprehensive insights for further investigation into the mechanism of COL6A.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04951-0.

Consensus gene modules related to levels of bone mineral density (BMD) among smokers and nonsmokers

Osteoporosis, as a common metabolic disorder characterized by the decrease of bone mass, can cause fractures, thereby threatening the life quality of females, especially postmenopausal women. Thus, it is necessary to reveal the genes involved in osteoporosis and explore biomarkers for osteoporosis. In this study, two groups, smokers and nonsmokers with different bone mineral density (BMD) levels, were collected from the Gene Expression Omnibus (GEO) database GSE13850. Consensus modules of the two groups were identified; the variety of gene modules between smokers and nonsmokers with different BMD levels was observed; and a consensus module, including 390 genes significantly correlated with different BMD levels, was identified. Function analysis revealed the significantly enriched osteoporosis-related pathways, such as the PI3K-Akt signaling pathway. Hub genes analysis revealed the critical role of CXCL12 and CHRM2 in modules related to BMD levels. Based on the support vector machine recursive feature elimination (SVM-RFE) analysis, the model containing 10 genes (TNS4, IRF2, BSG, GZMM, ARRB2, COX15, RALY, TP53, RPS6KA3, and SYNPO) with good performance in identifying people with different BMD levels was constructed. Among them, the roles of RALY and SYNPO in the osteogenic differentiation of hBMSCs were verified experimentally. Overall, this study provides a strategy to explore the biomarkers for osteoporosis through analysis of consensus modules.