Lung cancer is considered the most commonly diagnosed cancer [1, 2], and is the number one cause of cancer-related deaths worldwide [1], which primarily result from smoking tobacco [2, 3]. The risk of causation of lung cancer in smokers is reported to be nearly ten-fold higher compared to non-smokers [3, 4]. Tobacco smoke contains numerous toxic and carcinogenic compounds, such as nicotine, nitrogen oxides, and carbon monoxide or cadmium [5, 6]. Tobacco consumption is linked to an alteration in the expression of oncogenes and tumor suppressor genes [7]. Previous reports indicate that alterations in gene expression may affect the incidence and development of tumors intimately induced by epigenetic modulations [7, 8]. The epigenetic alterations could be in microRNA (miRNA), DNA methylation, histone modifications, and nucleosome remodeling [7]. These epigenetic alterations are standalone but may interact with each other to systematically control overall gene expression [9]. Thus, the interruptions of epigenetic pathways might encourage the procurement of a cancerous phenotype, the development of lung cancer cells, and the modulation of the response to lung cancer therapy among individuals [10].

MiRNAs are small, single-stranded, and highly conserved non-coding RNAs comprising about 19–24 nucleotides and are considered an important gene regulator of post-transcriptional modifications in lung cancer [11]. A single miRNA can regulate numerous different transcripts in the human genome alongside multiple RNA-coding transcripts [12]. Previous studies from our group and others have shown that miRNAs are involved in numerous biological processes by binding with their putative mRNA targets and regulating their expression [13, 14, 15]. The dysregulation of miRNAs is linked to the progression and suppression of cancer, thereby establishing miRNAs as important players in tumor suppressor genes or oncogenes [16].

The advent of high-throughput next-generation sequencing technology has reduced the costs and provided increased coverage to detect accurately the single nucleotide variants that occur in the coding and non-coding regions of human genomes during lung tumorigenesis. The precise analysis of these data detects novel variants and vital genes and biological processes related to the causation of tumors and provides an improved understanding of the mechanisms of occurrence, development, and prognosis associated with lung cancer [17, 18]. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) utilizes cutting-edge proteomic technologies, and workflows to clinical tumor samples with characterized genomic, and transcript profiles to fast-track and pinpoint the molecular basis of cancer under the auspices of the National Cancer Institute’s Office of Cancer Clinical Proteomics Research [19]. The CPTAC Data Portal is hosted under the auspices of the Cancer Genome Atlas database (TCGA, http://cancergenome.nih.gov/), and has revealed clinically significant pathogenic variants in mRNA through molecular studies in lung squamous cell carcinoma (LUSC) [17] and adenocarcinoma (LUAD) [18]. The TCGA database comprises data on clinically significant somatic mutations in human genes among lung cancer patients with a history of tobacco consumption. However, a systematic analysis is lacking that assesses the interactions between top enriched mRNA genes and miRNAs relating to the causation of lung cancer from tobacco consumption. Therefore, the present study was designed to perform this analysis. The goal of this study was to evaluate the impact of smoking tobacco on the incidence of simple somatic mutations in lung cancer. Subsequently, we also investigated the associations between miRNAs and mRNA candidate genes in the susceptibility and prognosis of lung cancer in tobacco smokers.

MicroRNAs serve as modulators of smoking-induced mRNA gene expression changes in the human airway epithelium [22] and have been implicated in the process of tumorigenesis through regulation of the cell cycle, metastasis, angiogenesis, metabolism, and apoptosis [23, 24]. Smoking is considered the single highest risk factor for lung cancer [25, 26] and has been suggested as being associated with accelerated somatic mutations in the respiratory mucosa that lead to the development of lung cancer [27]. The thermodynamics in the RNA–RNA interactions between miRNA and their mRNA target sites may be affected because of the presence of somatic mutations, resulting in the deregulation of target mRNA genes, and consequently, leading to phenotypic variations and lung cancer susceptibility. Considering these factors, this study examined the impact of smoking tobacco on the development of somatic mutations in mRNA genes and assessed their potential impact on the miRNA–mRNA interactions in lung cancers.

We found that the top five SSM-enriched mRNA proto-oncogenes in lung cancer were TP53, EGFR, KRAS, FAT4, and KMT2D. Interestingly, we observed the highest incidence of SSM in the TP53 gene at 63.64%. Similarly, the incidence of SSM was 23.94% in EGFR, 22.12% in KRAS, 18.48% in FAT4, and 14.24% in KMT2D (Table 1). Our results are consistent with previous reports, which have shown that the TP53 gene possesses the commonest somatic mutation in all human cancers, including lung cancers associated with smoking cigarettes [28, 29, 30]. Large-scale screening for somatic mutations in lung cancer studies has further strengthened our observations of the reported association between TP53, EGFR, and KRAS somatic mutations and lung cancer susceptibility [29, 31, 32]. The histone methyltransferase KMT2D is among the most highly inactivated epigenetic modifiers in lung cancer, and somatic mutations in this gene have been previously reported to be associated with vulnerability to lung cancer [33, 34]. FAT4 is an enormously large, atypical cadherin with critical roles in the regulation of planar cell polarity (PCP) and controlling the Hippo signaling pathway [35], while somatic mutations in this gene are also linked to lung cancer [36]. Similar to our observation in this study, the comprehensive genomic profiling in a previous lung cancer study revealed a significant association of high tumor burden with somatic mutations in the TP53, KMT2D, and FAT1 genes [36].

We observed a three-fold and almost two-fold higher incidence of SSMs in two proto-oncogenes, namely, EGFR (OR = 3.33, 95% CI = 2.36–4.69, p = 4.67 $\times$ 10${}^{-12}$) and KRAS (OR = 1.60, 95% CI = 1.15–2.20, p = 0.004), respectively, in lung cancer cases among tobacco smokers compared to non-smokers (Table 1). Similarly, the EGFR and KRAS somatic mutations were also found to be more frequent in smokers compared to non-smokers [37, 38]. Further, we found no significant difference in the SSM incidences for TP53, FAT4, and KMT2D proto-oncogenes in lung cancer cases related to tobacco smokers compared to non-smokers (Table 1). Our findings are consistent with a previous report that found no significant differences in the TP53 somatic mutation frequencies in lung cancer cases of smokers compared to non-smokers [39]. To the best of our knowledge, this is the first study that assessed and showed the frequency differences in somatic mutations in FAT4 and KMT2D proto-oncogenes between smokers and non-smokers in cases of lung cancer. Future studies are needed to confirm our findings regarding the differences in lung cancer cases between the frequency of somatic mutations in smokers and non-smokers.

In the next step, we used a bioinformatics approach to evaluate the effect of miRNA and mRNA interactions in lung cancer among the top SSM-enriched mRNA proto-oncogenes, namely, TP53, EGFR, KRAS, FAT4, and KMT2D. We found the top 20 most probable miRNAs that target these five enriched mRNA proto-oncogenes in lung cancer (Fig. 4), which were displayed in the miRNA–mRNA regulatory network (Fig. 5). Among these top 20 miRNAs, we observed 18 unique microRNAs that bind specifically to TP53, KRAS, and FAT4 genes and 17 and 19 microRNAs that bind exclusively to the EGFR and KMT2D genes, respectively. Two microRNAs, namely, has-miR-6812-5p and has-miR-6819-5p both bind to TP53 and EGFR. Similarly, has-miR-193a-3p and has-miR-193b-3p both bind to the KRAS and FAT4 genes, while hsa-miR-608 binds to both EGFR and KMT2D. Recent reports suggest that the role of miRNAs in targeting the TP53 [40], EGFR [41], KRAS [42], FAT4 [43], and KMT2D [44] genes, which play a pivotal role in tumorigenesis [40, 41, 42, 43, 44], are consistent with our findings, whereby miRNAs target these mRNA proto-oncogenes in lung cancer, namely, TP53, EGFR, KRAS, FAT4, and KMT2D. Further, the protein–protein interactions (PPIs) associated with the smoking-induced simple somatic mutations in the top five enriched mRNA proto-oncogenes found in lung cancer and the fifty closest neighboring genes were used to construct a network of 55 proteins with 1035 unique interactions (Supplementary Fig. 1), while the KEGG pathway enrichment analysis provided an important insight into the potential biological functions of these overlapping genes in lung cancer (Fig. 6).

The tumor suppressor TP53 gene is referred to as the guardian of the genome and plays a central role in tumor suppression [45, 46]. Thus, interruption of the usual TP53 function frequently leads to the onset and/or progression of cancer [45]. Previous studies have proven that miRNAs contribute to the regulation of TP53 levels and function [40]. Recently, more than 20 miRNAs have been demonstrated to serve as direct negative regulators of the TP53 level, with several of them frequently showing increased expression in tumors [40]. Similarly, we have also found more than 20 miRNAs that target the TP53 gene and may potentially downregulate TP53 expression. Some of the miRNAs (for example: hsa-let-7) that were identified as a potential target for TP53 have also been previously found in these studies [40, 47], thereby further strengthening our findings.

The epidermal growth factor receptor (EGFR) gene was among the first molecules to be chosen for targeted gene therapy in lung cancer [48]. A recent report suggests that EGFR mutations can be controlled by miRNAs in cancer therapies [49]. Further reports demonstrated that specific miRNA/EGFR axes may play crucial roles in lung tumorigenesis [41]. In the present study, we selected the top 20 miRNAs that could potentially target EGFR expression, along with KRAS, FAT4, and KMT2D. Further, experimental validation of these observed mRNA–miRNA interactions in our study may provide an important insight into the role of these interactions in lung cancer and their consequences in lung carcinogenesis. The improved knowledge of miRNA biology will assist in establishing the basis for the development of novel approaches to alter miRNA expressions and functions. The development of a novel class of synthetic oligonucleotide molecules to act as an inhibitor or enhancer can work to regulate the expression of a specific miRNA. Anti-miRs serve as inhibitors, which is an important characteristic of an ideal therapeutic agent.

To conclude, our study identified the top five SSM-enriched mRNA proto-oncogenes in lung cancers among tobacco smokers, namely, TP53, EGFR, KRAS, FAT4, and KMT2D. Further, the results of our study provide an important insight into the intricate network of mRNA–miRNA interactions involved in the development of lung cancer. In silico analysis showed quite significant observations, which suggest that expression-based studies should be carried out to assess the impact of predicted miRNA targets of altered mRNA proto-oncogenes in lung cancers among tobacco smokers.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

MKM, AKM, and NM designed the research study, and performed the research. AKM collected the data. NM, and MKM oversaw initial data collection. AKM, and MKM analyzed the data. AKM and MKM wrote the manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity.

Not applicable.

Not applicable.

This research received no external funding.

The authors declare no conflict of interest.