Identification of a Potentially Functional microRNA-mRNA Regulatory Network in Lung Adenocarcinoma Using a Bioinformatics Analysis

Identification of an 11-miRNA-regulated and surface-protein genes signature predicts the prognosis of lung adenocarcinoma based on multi-omics study

Lung adenocarcinoma (LUAD) is one of the most prevalent and lethal cancers worldwide, signifying a critical need for improved prognostic tools. A growing number of studies have highlighted the role of microRNAs (miRNAs) and their regulatory functions in tumorigenesis and cancer progression. In this context, we performed an extensive analysis of bulk RNA- and miRNA-sequencing to identify LUAD-associated prognostic genes. A risk score system based on 11 miRNA-regulated and surface-protein genes was developed, which was later validated by internally and externally using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. Further single-cell RNA sequencing analysis revealed significant interactions between various cellular subpopulations within the tumor microenvironment, with the most pronounced differences observed between endothelial and epithelial cells. The mutational analysis highlighted TP53 as a key signaling pathway associated with the risk score. The study underscores that immune suppression, indicated by a positive association with regulatory T cells (Tregs) and an inverse correlation with M1-type macrophages, is prevalent in high-risk LUAD patients. These findings provide a promising prognostic tool for clinical outcomes of LUAD patients, facilitating future development of therapeutic strategies and enhancing our understanding of the regulatory function of miRNAs in LUAD.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

A panel of blood-derived miRNAs with a stable expression pattern as a potential pan-cancer detection signature

Introduction: MicroRNAs have a significant role in the regulation of the transcriptome. Several miRNAs have been proposed as potential biomarkers in different malignancies. However, contradictory results have been reported on the capability of miRNA biomarkers in cancer detection. The human biological clock involves molecular mechanisms that regulate several genes over time. Therefore, the sampling time becomes one of the significant factors in gene expression studies. Method: In the present study, we have tried to find miRNAs with minimum fluctuation in expression levels at different time points that could be more accurate candidates as diagnostic biomarkers. The small RNA-seq raw data of ten healthy individuals across nine-time points were analyzed to identify miRNAs with stable expression. Results: We have found five oscillation patterns. The stable miRNAs were investigated in 779 small-RNA-seq datasets of eleven cancer types. All miRNAs with the highest differential expression were selected for further analysis. The selected miRNAs were explored for functional pathways. The predominantly enriched pathways were miRNA in cancer and the P53-signaling pathway. Finally, we have found seven miRNAs, including miR-142-3p, miR-199a-5p, miR-223-5p, let-7d-5p, miR-148b-3p, miR-340-5p, and miR-421. These miRNAs showed minimum fluctuation in healthy blood and were dysregulated in the blood of eleven cancer types. Conclusion: We have found a signature of seven stable miRNAs which dysregulate in several cancer types and may serve as potential pan-cancer biomarkers.

Role and mechanism of benzo[a]pyrene in the transformation of chronic obstructive pulmonary disease into lung adenocarcinoma

OBJECTIVE

This experiment is explores the genes that play a key role, their expression changes and the biological processes in the transformation of chronic obstructive pulmonary disease (COPD) into lung adenocarcinoma (LAC). Meanwhile, identify the effects of Benzo[a]pyrene (BaP) in the conversion of COPD into LAC.

METHODS

1. Differential expression genes of COPD and LAC were screened and analyzed by high-throughput microarray data between the two diseases and their respective control groups. 2. The screened genes were used for routine bioinformatics analysis such as functional analysis, expression verification, protein interaction analysis and functional enrichment. 3. Cigarette smoke extract (CSE) combined with lipopolysaccharide (LPS) was used to establish an in vitro COPD model. 4. MTT assay was used to detect the influence of B(a)P in effect on A549 cell proliferation. CCK-8, Transwell invasion test and scratch test were used to detect the cell proliferation, invasion and migration ability, while qPCR and Western Blot tests were used to observe the cell proliferation, apoptosis and changes in related indicators such as EMT. 5. Experimental method of separately adding agonists (tBHQ) and inhibitors (DIC) of NQO1 was used to confirm the effect of NQO1 on A549 cell proliferation, apoptosis, migration and invasion. 6. To further clarify whether BaP exerted effect on cell proliferation, apoptosis, migration and invasion through NQO1, we knocked down NQO1 gene and then infecting cells with BaP.

RESULTS

1. We screened genes of COPD and LAC using datasets from GSE151052, GSE118370, and GSE140797. After screening, the genes upregulated in COPD and downregulated in LAC were RTKN2, SLC6A4, and HBB, the gene downregulated in COPD and upregulated in LAC was NQO1, the genes downregulated in both COPD and LAC were FPR1, LYVE1 and PKHD1L1. 2. The main signaling pathways in which the target genes were enriched are cell cycle, EMT, PI3K/AKT, and apoptosis. In the data included GEPIA, PKHD1L1, FPR1, LYVE1, RTKN2, HBB, and SLC6A4 were significantly downregulated and NQO1 was upregulated in LAC relative to controls. In addition, there were 46 interaction proteins in the target genes, and the functions they enriched included hydrogen peroxide catabolism, etc. 3. When A549 cell was stimulated with 100 ng/mL LPS+ 10% CSE, the COX-2 expression indicated that COPD model in vitro was successfully established. 4. The optimal dose and action time were screened which were 1 μM and 24 h. Compared to the control group, COPD and BaP group increased cell proliferation and invasion capabilities. On the basis of COPD, adding BaP could further increase the proliferation and migration capabilities. Interestingly, the levels of NQO1 decreased in COPD models, while increased by BaP. 5. tBHQ can increase the proliferation and migration capacity of A549 cells, which is inhibited by the addition of DIC. 6. The enhanced proliferation, migration and invasion of A549 cells by BaP were attenuated after knockdown of NQO1.

CONCLUSION

Our study reveals that PKHD1L1, FPR1, LYVE1, RTKN2, HBB, SLC6A4 and NQO1 may play an important role in the conversion of COPD to LAC. High NQO1 expression may increase the proliferation and migration ability of A549 cells, and BaP may promote the EMT state by increasing the expression of NQO1, thereby making the COPD model in vitro expose the tumor characteristics.

Identification of Candidate MicroRNA-mRNA Subnetwork for Predicting the Osteosarcoma Progression by Bioinformatics Analysis

Osteosarcoma (OS) is the pretty common primary cancer of the bone among the malignancies in adolescents. A single molecular component or a limited number of molecules is insufficient as a predictive biomarker of OS progression. Hence, it is necessary to find novel network biomarkers to improve the prediction and therapeutic effect for OS. Here, we identified 230 DE-miRNAs and 821 DE-mRNAs through two miRNA expression-profiling datasets and three mRNA expression-profiling datasets. We found that hsa-miR-494 is closely linked with the survival of OS patients. In addition, we analyzed GO and KEGG enrichment for targets of hsa-miR-494-5p and hsa-miR-494-3p through R programming. And five mRNAs were predicted as common targets of hsa-miR-494-5p and hsa-miR-494-3p. We further revealed that upregulated TRPS1 was strongly correlated with poor outcomes in OS patients through the survival analysis based on the TARGET database. The qRT-PCR study verified that the expression of hsa-miR-494-5p and hsa-miR-494-3p was declined considerably, while TRPS1 was notably raised in OS cells when compared to the osteoblasts. Thus, we generated a new regulatory subnetwork of key miRNAs and target mRNAs using Cytoscape software. These results indicate that the novel miRNA-mRNA subnetwork composed of hsa-miR-494-5p, hsa-miR-494-3p, and TRPS1 might be a characteristic molecule for assessing the prognostic value of OS patients.

Multi-Omics Integration-Based Prioritisation of Competing Endogenous RNA Regulation Networks in Small Cell Lung Cancer: Molecular Characteristics and Drug Candidates

Background

The competing endogenous RNA (ceRNA) network-mediated regulatory mechanisms in small cell lung cancer (SCLC) remain largely unknown. This study aimed to integrate multi-omics profiles, including the transcriptome, regulome, genome and pharmacogenome profiles, to elucidate prioritised ceRNA characteristics, pathways and drug candidates in SCLC.

Method

We determined the plasma messenger RNA (mRNA), microRNA (miRNA), long noncoding RNA (lncRNA) and circular RNA (circRNA) expression levels using whole-transcriptome sequencing technology in our SCLC plasma cohort. Significantly expressed plasma mRNAs were then overlapped with the Gene Expression Omnibus (GEO) tissue mRNA data (GSE 40275, SCLC tissue cohort). Next, we applied a multistep multi-omics (transcriptome, regulome, genome and pharmacogenome) integration analysis to first construct the network and then to identify the lncRNA/circRNA-miRNA-mRNA ceRNA characteristics, genomic alterations, pathways and drug candidates in SCLC.

Results

The multi-omics integration-based prioritisation of SCLC ceRNA regulatory networks consisted of downregulated mRNAs (CSF3R/GAA), lncRNAs (AC005005.4-201/DLX6-AS1-201/NEAT1-203) and circRNAs (hsa_HLA-B_1/hsa_VEGFC_8) as well as upregulated miRNAs (hsa-miR-4525/hsa-miR-6747-3p). lncRNAs (lncRNA-AC005005.4-201 and NEAT1-203) and circRNAs (circRNA-hsa_HLA-B_1 and hsa_VEGFC_8) may regulate the inhibited effects of hsa-miR-6747-3p for CSF3R expression in SCLC, while lncRNA-DLX6-AS1-201 or circRNA-hsa_HLA-B_1 may neutralise the negative regulation of hsa-miR-4525 for GAA in SCLC. CSF3R and GAA were present in the genomic alteration, and further identified as targets of FavId and Trastuzumab deruxtecan, respectively. In the SCLC-associated pathway analysis, CSF3R was involved in the autophagy pathways, while GAA was involved in the glucose metabolism pathways.

Conclusions

We identified potential lncRNA/cirRNA-miRNA-mRNA ceRNA regulatory mechanisms, pathways and promising drug candidates in SCLC, providing novel potential diagnostics and therapeutic targets in SCLC.

Identification of Down-Regulated ADH1C is Associated With Poor Prognosis in Colorectal Cancer Using Bioinformatics Analysis

Colorectal cancer (CRC) is the second most deadly cancer in the whole world, with the underlying mechanisms largely indistinct. Therefore, we aimed to identify significant pathways and genes involved in the initiation, formation and poor prognosis of CRC using bioinformatics methods. In this study, we compared gene expression profiles of CRC cases with those from normal colorectal tissues from three chip datasets (GSE33113, GSE23878 and GSE41328) to identify 105 differentially expressed genes (DEGs) that were common to the three datasets. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that the highest proportion of up-regulated DEGs was involved in extracellular region and cytokine-cytokine receptor interaction pathways. Integral components of membrane and bile secretion pathways were identified as containing down-regulated DEGs. 13 hub DEGs were chosen and their expression were further validated by GEPIA. Only four DEGs (ADH1C, CLCA4, CXCL8 and GUCA2A) were associated with a significantly lower overall survival after the prognosis analysis. Lower ADH1C protein level and higher CXCL8 protein level were verified by immunohistochemical staining and western blot in clinical CRC and normal colorectal tissues. In conclusion, our study indicated that the extracellular tumor microenvironment and bile metabolism pathways play critical roles in the formation and progression of CRC. Furthermore, we confirmed ADH1C being down-regulated in CRC and reported ADH1C as a prognostic predictor for the first time.

Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma

Background

The prevalence of lung adenocarcinoma (LUAD) has increased, thus novel biomarkers for its early diagnosis is becoming more important than ever. tRNA-derived small RNA (tsRNA) is a new class of non-coding RNA which has important regulatory roles in cancer biology. This study was designed to identify novel predictive and prognostic tsRNA biomarkers.

Methods

tsRNAs were identified and performed differential expression analysis from 10 plasma samples (6 LUAD and 4 normal, SRP266333) and 96 tissue samples (48 LUAD and 48 normal, SRP133217). Then a tsRNA-mRNA regulatory network was constructed to find hub tsRNAs. Functional enrichment analysis was performed to infer the potential pathways associated with tsRNAs. Afterwards, a Support Vector Machine (SVM) algorithm was used to explore the potential biomarkers for diagnosing LUAD. Lastly, the function of tRF-21-RK9P4P9L0 was explored in A549 and H1299 cell lines.

Results

A significant difference of read distribution was observed between normal people and LUAD patients whether in plasma or tissue. A tsRNA-mRNA regulatory network consisting of 155 DEtsRNAs (differential expression tsRNAs) and 406 DEmRNAs (differential expression mRNAs) was established. Three tsRNAs (tRF-16-L85J3KE, tRF-21-RK9P4P9L0 and tRF-16-PSQP4PE) were identified as hub genes with degree > 100. We found Co-DEmRNAs (intersection of DEtsRNAs target mRNAs and differentially expressed mRNAs in LUAD) were engaged in a number of cancer pathways. The AUC of the three hub tsRNAs’ expression for diagnosing LUAD reached 0.92. Furthermore, the qPCR validation of the three hub tsRNAs in 37 paired normal and LUAD tissues was consistent with the RNA-Seq results. In addition, tRF-21-RK9P4P9L0 was negatively associated with LUAD prognosis. Inhibition of tRF-21-RK9P4P9L0 expression reduced the proliferation, migration and invasion ability of A549 and H1299 cell lines.

Conclusion

These findings will help us further understand the molecular mechanisms of LUAD and contribute to novel diagnostic biomarkers and therapeutic target discovery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02481-6.

Macrophage-Related SPP1 as a Potential Biomarker for Early Lymph Node Metastasis in Lung Adenocarcinoma

Lymph node metastasis is a major factor that affects prognosis in patients with lung adenocarcinoma (LUAD). In some cases, lymph node metastasis has already occurred when the primary tumors are still small (i.e., early T stages), however, relevant studies on early lymph node metastasis are limited, and effective biomarkers remain lacking. This study aimed to explore new molecular biomarker for early lymph node metastasis in LUAD using transcriptome sequencing and experimental validation. Here, we performed transcriptome sequencing on tissues from 16 matched patients with Stage-T1 LUAD (eight cases of lymph node metastasis and eight cases of non-metastasis), and verified the transcriptome profiles in TCGA, GSE68465, and GSE43580 cohorts. With the bioinformatics analysis, we identified a higher abundance of M0 macrophages in the metastatic group using the CIBERSORT algorithm and immunohistochemistry (IHC) analysis and the enrichment of the epithelial–mesenchymal transition (EMT) pathway was identified in patients with higher M0 infiltration levels. Subsequently, the EMT hallmark gene SPP1, encoding secreted phosphoprotein 1 (SPP1), was identified to be significantly correlated with macrophage infiltration and M2 polarization, and was determined to be a key risk indicator for early lymph node metastasis. Notably, SPP1 in the blood, as detected by enzyme-linked immunosorbent assay (ELISA) showed a superior predictive capability for early lymph node metastasis [area under the curve (AUC) = 0.74]. Furthermore, a long non-coding RNA (lncRNA, AC037441), negatively correlated with SPP1 and macrophage infiltration, had also been identified and validated to be involved in the regulation of early lymph node metastasis. In conclusion, we revealed the potential role of macrophages in lymph node metastasis and identified the macrophage-related gene SPP1 as a potential biomarker for early lymph node metastasis in LUAD.