An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Transcriptome characteristics of epithelial cells from advanced non-small cell lung cancer were revealed by single-cell RNA sequencing

BACKGROUND

Lung adenocarcinoma (LUAD) is the prevalent malignancy worldwide. The aim is to explore differentially expressed genes (DEGs) associated with immune infiltration and survival time of LUAD patients, and predict transcriptional factors for shedding new light on molecular mechanisms and individual therapy of LUAD.

METHOD

ScRNA-seq data of LUAD patients was downloaded from GSE148071 and analyzed by R packages. The clustering and protein-protein interaction network were constructed for screening DEGs. Gene Set Enrichment Analysis (GSEA) and GO enrichment analysis were performed in epithelial cell subgroups with high differentiation potential. Potential regulatory transcription factors were predicted.

RESULTS

Sixteen epithelial cell types were required and top 20 genes were identified on cell subgroup Epi4 with the highest differentiation potential associated with poor prognosis of LUAD in PPI network. GSEA and GO annotation results showed that cell subgroup Epi4 was enriched in the biological processes of cell proliferation and energy metabolism, and positively regulated the function of cell proliferation. TPI1 was significantly highly expressed in LUAD samples (p < .0001). TPI1 demonstrated a negative correlation with the infiltration levels of CD8+ T cells, CD4+ T cells, B cells, and activated mast cells, whilst manifesting a positive correlation with the infiltration levels of resident mast cells, Th2 cells, and MDSC. Epi4 was regulated by transcription factors MXD3 and GATA4.

CONCLUSION

Overexpression of TPI1 was identified as a novel biomarker for LUAD, and potential regulatory transcription factors MXD3 and GATA4 regulated the proliferation of LUAD with the poor prognosis, which may serve as potential targets to suppress the proliferation of LUAD.

Unrevealed roles of extracellular enolase‑1 (ENO1) in promoting glycolysis and pro‑cancer activities in multiple myeloma via hypoxia‑inducible factor 1α

The involvement of enolase‑1 (ENO1), intracellularly or extracellularly, has been implicated in cancer development. Moreover, anticancer activities of an ENO1‑targeting antibody has demonstrated the pathological roles of extracellular ENO1 (surface or secreted forms). However, although ENO1 was first identified as a glycolytic enzyme in the cytosol, to the best of our knowledge, extracellular ENO1 has not been implicated in glycolysis thus far. In the present study, the effects of extracellular ENO1 on glycolysis and other related pro‑cancer activities were investigated in multiple myeloma (MM) cells in vitro and in vivo. Knockdown of ENO1 expression reduced lactate production, cell viability, cell migration and surface ENO1 expression in MM cells. Notably, addition of extracellular ENO1 protein in cancer cell culture enhanced glycolytic activity, hypoxia‑inducible factor 1‑α (HIF‑1α) expression, glycolysis‑related gene (GRG) expression and pro‑cancer activities, such as cell migration, cell viability and tumor‑promoting cytokine secretion. Consistently, these extracellular ENO1‑induced cellular effects were inhibited by an ENO1‑specific monoclonal antibody (mAb). In addition, extracellular ENO1‑mediated glycolysis, GRG expression and pro‑cancer activities were also reduced by HIF‑1α silencing. Lastly, administration of an ENO1 mAb reduced tumor growth and serum lactate levels in an MM xenograft model. These results suggested that extracellular ENO1 (surface or secreted forms) enhanced a HIF‑1α‑mediated glycolytic pathway, in addition to its already identified roles. Therefore, the results of the present study highlighted the therapeutic potential of ENO1‑specific antibodies in treating MM, possibly via glycolysis inhibition, and warrant further studies in other types of cancer.

Biological characteristics of pancreatic ductal adenocarcinoma: Initiation to malignancy, intracellular to extracellular

Pancreatic ductal adenocarcinoma (PDAC) is a highly life-threatening tumour with a low early-detection rate, rapid progression and a tendency to develop resistance to chemotherapy. Therefore, understanding the regulatory mechanisms underlying the initiation, development and metastasis of pancreatic cancer is necessary for enhancing therapeutic effectiveness. In this review, we summarised single-gene mutations (including KRAS, CDKN2A, TP53, SMAD4 and some other less prevalent mutations), epigenetic changes (including DNA methylation, histone modifications and RNA interference) and large chromosome alterations (such as copy number variations, chromosome rearrangements and chromothripsis) associated with PDAC. In addition, we discussed variations in signalling pathways that act as intermediate oncogenic factors in PDAC, including PI3K/AKT, MAPK/ERK, Hippo and TGF-β signalling pathways. The focus of this review was to investigate alterations in the microenvironment of PDAC, particularly the role of immunosuppressive cells, cancer-associated fibroblasts, lymphocytes, other para-cancerous cells and tumour extracellular matrix in tumour progression. Peripheral axons innervating the pancreas have been reported to play a crucial role in the development of cancer. In addition, tumour cells can influence the behaviour of neighbouring non-tumour cells by secreting certain factors, both locally and at a distance. In this review, we elucidated the alterations in intracellular molecules and the extracellular environment that occur during the progression of PDAC. Altogether, this review may enhance the understanding of the biological characteristics of PDAC and guide the development of more precise treatment strategies.

Pancreatic Cancer-Secreted Proteins: Targeting Their Functions in Tumor Microenvironment

Pancreatic Ductal Adenocarcinoma (PDAC) is a ravaging disease with a poor prognosis, requiring a more detailed understanding of its biology to foster the development of effective therapies. The unsatisfactory results of treatments targeting cell proliferation and its related mechanisms suggest a shift in focus towards the inflammatory tumor microenvironment (TME). Here, we discuss the role of cancer-secreted proteins in the complex TME tumor-stroma crosstalk, shedding lights on druggable molecular targets for the development of innovative, safer and more efficient therapeutic strategies.

Secretome of Stromal Cancer-Associated Fibroblasts (CAFs): Relevance in Cancer

The cancer secretome reflects the assortment of proteins released by cancer cells. Investigating cell secretomes not only provides a deeper knowledge of the healthy and transformed state but also helps in the discovery of novel biomarkers. Secretomes of cancer cells have been studied in the past, however, the secretome contribution of stromal cells needs to be studied. Cancer-associated fibroblasts (CAFs) are one of the predominantly present cell populations in the tumor microenvironment (TME). CAFs play key role in functions associated with matrix deposition and remodeling, reciprocal exchange of nutrients, and molecular interactions and signaling with neighboring cells in the TME. Investigating CAFs secretomes or CAFs-secreted factors would help in identifying novel CAF-specific biomarkers, unique druggable targets, and an improved understanding for personalized cancer diagnosis and prognosis. In this review, we have tried to include all studies available in PubMed with the keywords "CAFs Secretome". We aim to provide a comprehensive summary of the studies investigating role of the CAF secretome on cancer development, progression, and therapeutic outcome. However, challenges associated with this process have also been addressed in the later sections. We have highlighted the functions and clinical relevance of secretome analysis in stromal CAF-rich cancer types. This review specifically discusses the secretome of stromal CAFs in cancers. A deeper understanding of the components of the CAF secretome and their interactions with cancer cells will help in the identification of personalized biomarkers and a more precise treatment plan.

Prostate Cancer Secretome and Membrane Proteome from Pten Conditional Knockout Mice Identify Potential Biomarkers for Disease Progression

Prostate cancer (PCa) is the second most common cause of mortality among men. Tumor secretome is a promising strategy for understanding the biology of tumor cells and providing markers for disease progression and patient outcomes. Here, transcriptomic-based secretome analysis was performed on the PCa tumor transcriptome of Genetically Engineered Mouse Model (GEMM) Pb-Cre4/Pten^f/f mice to identify potentially secreted and membrane proteins—PSPs and PMPs. We combined a selection of transcripts from the GSE 94574 dataset and a list of protein-coding genes of the secretome and membrane proteome datasets using the Human Protein Atlas Secretome. Notably, nine deregulated PMPs and PSPs were identified in PCa (DMPK, PLN, KCNQ5, KCNQ4, MYOC, WIF1, BMP7, F3, and MUC1). We verified the gene expression patterns of Differentially Expressed Genes (DEGs) in normal and tumoral human samples using the GEPIA tool. DMPK, KCNQ4, and WIF1 targets were downregulated in PCa samples and in the GSE dataset. A significant association between shorter survival and KCNQ4, PLN, WIF1, and F3 expression was detected in the MSKCC dataset. We further identified six validated miRNAs (mmu-miR-6962-3p, mmu-miR- 6989-3p, mmu-miR-6998-3p, mmu-miR-5627-5p, mmu-miR-15a-3p, and mmu-miR-6922-3p) interactions that target MYOC, KCNQ5, MUC1, and F3. We have characterized the PCa secretome and membrane proteome and have spotted new dysregulated target candidates in PCa.

Integrative, In Silico and Comparative Analysis of Breast Cancer Secretome Highlights Invasive-Ductal-Carcinoma-Grade Progression Biomarkers

Globally, BC is the most frequently diagnosed cancer in women. The aim of this study was to identify novel secreted biomarkers that may indicate progression to high-grade BC malignancies and therefore predict metastatic potential. A total of 33 studies of breast cancer and 78 of other malignancies were screened via a systematic review for eligibility, yielding 26 datasets, 8 breast cancer secretome datasets, and 18 of other cancers that were included in the comparative secretome analysis. Sequential bioinformatic analysis using online resources enabled the identification of enriched GO_terms, overlapping clusters, and pathway reconstruction. This study identified putative predictors of IDC grade progression and their association with breast cancer patient mortality outcomes, namely, HSPG2, ACTG1, and LAMA5 as biomarkers of in silico pathway prediction, offering a putative approach by which the abovementioned proteins may mediate their effects, enabling disease progression. This study also identified ITGB1, FBN1, and THBS1 as putative pan-cancer detection biomarkers. The present study highlights novel, putative secretome biomarkers that may provide insight into the tumor biology and could inform clinical decision making in the context of IDC management in a non-invasive manner.

Message in hand: the application of CRISPRi, RNAi, and LncRNA in adenocarcinoma

Gene editing interference technology has been flourishing for more than 30 years. It has always been a common means to interfere with the expression of particular genes. Today it has shown a broad application prospect in clinical treatment, especially in adenocarcinoma treatment. In just a few years, the CRISPRi technology has attracted much z attention with its precise targeting and convenient operability significantly promoted the transformation from bench to bedside, and won the Nobel Prize in Chemistry 2020. In recent years, the importance of non-coding RNA has led LncRNA research to the center. At the same time, it also recalls the surprises obtained in laboratory and clinic research by RNAi technologies such as microRNA, siRNA, and shRNA at the beginning of the century. Therefore, this article focuses on CRISPRi, RNAi, and LncRNA to review their gene interference mechanisms currently expected to be translational research. Their applications and differences in adenocarcinoma research will also be described powerfully. It will provide a helpful reference for scientists to understand better and apply several RNA interference technologies.

Fibronectin Modulates the Expression of miRNAs in Prostate Cancer Cell Lines

Prostate cancer (PCa) is a significant cause of cancer-related deaths among men and companion animals, such as dogs. However, despite its high mortality and incidence rates, the molecular mechanisms underlying this disease remain to be fully elucidated. Among the many factors involved in prostate carcinogenesis, the extracellular matrix (ECM) plays a crucial role. This ECM in the prostate is composed mainly of collagen fibers, reticular fibers, elastic fibers, proteoglycans and glycoproteins, such as fibronectin. Fibronectin is a glycoprotein whose dysregulation has been implicated in the development of multiple types of cancer, and it has been associated with cell migration, invasion, and metastasis. Furthermore, our research group has previously shown that fibronectin induces transcriptional changes by modulating the expression of protein coding genes in LNCaP cells. However, potential changes at the post-transcriptional level are still not well understood. This study investigated the impact of exposure to fibronectin on the expression of a key class of regulatory RNAs, the microRNAs (miRNAs), in prostate cancer cell lines LNCaP and PC-3. Five mammalian miRNAs (miR-21, miR-29b, miR-125b, miR-221, and miR-222) were differentially expressed after fibronectin exposure in prostate cell lines. The expression profile of hundreds of mRNAs predicted to be targeted by these miRNAs was analyzed using publicly available RNA-Sequencing data (GSE64025, GSE68645, GSE29155). Also, protein-protein interaction networks and enrichment analysis were performed to gain insights into miRNA biological functions. Altogether, these functional analyzes revealed that fibronectin exposure impacts the expression of miRNAs potentially involved in PCa causing changes in critical signaling pathways such as PI3K-AKT, and response to cell division, death, proliferation, and migration. The relationship here demonstrated between fibronectin exposure and altered miRNA expression improves the comprehension of PCa in both men and other animals, such as dogs, which naturally develop prostate cancer.

Oncogenic KRAS-Induced Protein Signature in the Tumor Secretome Identifies Laminin-C2 and Pentraxin-3 as Useful Biomarkers for the Early Diagnosis of Pancreatic Cancer

KRAS mutations characterize pancreatic cell transformation from the earliest stages of carcinogenesis, and are present in >95% of pancreatic ductal adenocarcinoma (PDAC) cases. In search of novel biomarkers for the early diagnosis of PDAC, we identified the proteins secreted by the normal human pancreatic cell line (HPDE) recently transformed by inducing the overexpression of the KRASG12V oncogene. We report a proteomic signature of KRAS-induced secreted proteins, which was confirmed in surgical tumor samples from resected PDAC patients. The putative diagnostic performance of three candidates, Laminin-C2 (LAMC2), Tenascin-C (TNC) and Pentraxin-3 (PTX3), was investigated by ELISA quantification in two cohorts of PDAC patients (n = 200) eligible for surgery. Circulating levels of LAMC2, TNC and PTX3 were significantly higher in PDAC patients compared to the healthy individuals (p < 0.0001). The Receiver Operating Characteristics (ROC) curve showed good sensitivity (1) and specificity (0.63 and 0.85) for LAMC2 and PTX3, respectively, but not for TNC, and patients with high levels of LAMC2 had significantly shorter overall survival (p = 0.0007). High levels of LAMC2 and PTX3 were detected at early stages (I−IIB) and in CA19-9-low PDAC patients. In conclusion, pancreatic tumors release LAMC2 and PTX3, which can be quantified in the systemic circulation, and may be useful in selecting patients for further diagnostic imaging.

Development of computational models using omics data for the identification of effective cancer metabolic biomarkers

Identification of novel biomarkers has been an active area of study for the effective diagnosis, prognosis and treatment of cancers. Among various types of cancer biomarkers, metabolic biomarkers, including enzymes, metabolites and metabolic genes, deserve attention as they can serve as a reliable source for diagnosis, prognosis and treatment of cancers. In particular, efforts to identify novel biomarkers have been greatly facilitated by a rapid increase in the volume of multiple omics data generated for a range of cancer cells. These omics data in turn serve as ingredients for developing computational models that can help derive deeper insights into the biology of cancer cells, and identify metabolic biomarkers. In this review, we provide an overview of omics data generated for cancer cells, and discuss recent studies on computational models that were developed using omics data in order to identify effective cancer metabolic biomarkers.

The PDAC Extracellular Matrix: A Review of the ECM Protein Composition, Tumor Cell Interaction, and Therapeutic Strategies

Pancreatic ductal adenocarcinoma (PDAC) is notorious for a dense fibrotic stroma that is interlaced with a collagen-based extracellular matrix (ECM) that plays an important role in tumor biology. Traditionally thought to only provide a physical barrier from host responses and systemic chemotherapy, new studies have demonstrated that the ECM maintains biomechanical and biochemical properties of the tumor microenvironment (TME) and restrains tumor growth. Recent studies have shown that the ECM augments tumor stiffness, interstitial fluid pressure, cell-to-cell junctions, and microvascularity using a mix of biomechanical and biochemical signals to influence tumor fate for better or worse. In addition, PDAC tumors have been shown to use ECM-derived peptide fragments as a nutrient source in nutrient-poor conditions. While collagens are the most abundant proteins found in the ECM, several studies have identified growth factors, integrins, glycoproteins, and proteoglycans in the ECM. This review focuses on the dichotomous nature of the PDAC ECM, the types of collagens and other proteins found in the ECM, and therapeutic strategies targeting the PDAC ECM.

Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms

Endocrine neoplasms remain a great threat to human health. It is extremely important to make a clear diagnosis and timely treatment of endocrine tumors. Machine learning includes radiomics, which has long been utilized in clinical cancer research. Radiomics refers to the extraction of valuable information by analyzing a large amount of standard data with high-throughput medical images mainly including computed tomography, positron emission tomography, magnetic resonance imaging, and ultrasound. With the quantitative imaging analysis and model building, radiomics can reflect specific underlying characteristics of a disease that otherwise could not be evaluated visually. More and more promising results of radiomics in oncological practice have been seen in recent years. Radiomics may have the potential to supplement traditional imaging analysis and assist in providing precision medicine for patients. Radiomics had developed rapidly in endocrine neoplasms practice in the past decade. In this review, we would introduce the general workflow of radiomics and summarize the applications and developments of radiomics in endocrine neoplasms in recent years. The limitations of current radiomic research studies and future development directions would also be discussed.

The tumor microenvironment in pancreatic ductal adenocarcinoma: current perspectives and future directions

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal malignancies and is characterized by a unique tumor microenvironment (TME) consisting of an abundant stromal component. Many features contained with the PDAC stroma contribute to resistance to cytotoxic and immunotherapeutic regimens, as well as the propensity for this tumor to metastasize. At the cellular level, PDAC cells crosstalk with a complex mixture of non-neoplastic cell types including fibroblasts, endothelial cells, and immune cells. These intricate interactions fuel the progression and therapeutic resistance of this aggressive cancer. Moreover, data suggest the polarization of these cell types, in particular immune and fibroblast populations, dictate how PDAC tumors grow, metastasize, and respond to therapy. As a result, current research is focused on how to best target these populations to render tumors responsive to treatment. Herein, we summarize the cell populations implicated in providing a supporting role for the development and progression of PDAC. We focus on stromal fibroblasts and immune subsets that have been widely researched. We discuss factors which govern the phenotype of these populations and provide insight on how they have been targeted therapeutically. This review provides an overview of the tumor microenvironment and postulates that cellular and soluble factors within the microenvironment can be specifically targeted to improve patient outcomes.

Molecular advances in pancreatic cancer: A genomic, proteomic and metabolomic approach

Pancreatic ductal adenocarcinoma (PDAC) represents a challenging pathology with very poor outcomes and is increasing in incidence within the general population. The majority of patients are diagnosed incidentally with insidious symptoms and hence present late in the disease process. This significantly affects patient outcomes: the only cure is surgical resection but only up to 20% of patients present with resectable disease at the time of clinical presentation. The use of “omic” technology is expanding rapidly in the field of personalised medicine - using genomic, proteomic and metabolomic approaches allows researchers and clinicians to delve deep into the core molecular processes of this difficult disease. This review gives an overview of the current findings in PDAC using these “omic” approaches and summarises useful markers in aiding clinicians treating PDAC. Future strategies incorporating these findings and potential application of these methods are presented in this review article.

DHA exhibits synergistic therapeutic efficacy with cisplatin to induce ferroptosis in pancreatic ductal adenocarcinoma via modulation of iron metabolism

Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal cancer with limited treatment options. Cisplatin (DDP) is used as a mainstay of chemotherapeutic agents in combination with other drugs or radiotherapy for PDAC therapy. However, DDP exhibits severe side-effects that can lead to discontinuation of therapy, and the acquired drug resistance of tumor cells presents serious clinical obstacles. Therefore, it is imperative to develop a more effective and less toxic therapeutic strategy. We and others have previously discovered that dihydroartemisinin (DHA) represents a safe and promising therapeutic agent to preferentially induce cancer cell ferroptosis. In the present study, we find that DHA could intensively strengthen the cytotoxicity of DDP and significantly reduce its effective concentrations both in vitro and in vivo. Combination of DHA and DDP synergistically inhibits the proliferation and induces DNA damage of PDAC cells. Mechanically, the combinative treatment impairs mitochondrial homeostasis, characterized by destroyed mitochondrial morphology, decreased respiratory capacity, reduced ATP production, and accumulated mitochondria-derived ROS. Further studies show that ferroptosis contributes to the cytotoxic effects in PDAC cells under the challenge of DHA and DDP, together with catastrophic accumulation of free iron and unrestricted lipid peroxidation. Moreover, pharmacologic depleting of the free iron reservoir or reconstituted expression of FTH contributes to the tolerance of DHA/DDP-induced ferroptosis, while iron addition accelerates the ferroptotic cell death. In summary, these results provide experimental evidence that DHA acts synergistically with DDP and renders PDAC cells vulnerable to ferroptosis, which may act as a promising therapeutic strategy.

The Glycolytic Pathway as a Target for Novel Onco-Immunology Therapies in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDA) is one of the most lethal forms of human cancer, characterized by unrestrained progression, invasiveness and treatment resistance. To date, there are limited curative options, with surgical resection as the only effective strategy, hence the urgent need to discover novel therapies. A platform of onco-immunology targets is represented by molecules that play a role in the reprogrammed cellular metabolism as one hallmark of cancer. Due to the hypoxic tumor microenvironment (TME), PDA cells display an altered glucose metabolism-resulting in its increased uptake-and a higher glycolytic rate, which leads to lactate accumulation and them acting as fuel for cancer cells. The consequent acidification of the TME results in immunosuppression, which impairs the antitumor immunity. This review analyzes the genetic background and the emerging glycolytic enzymes that are involved in tumor progression, development and metastasis, and how this represents feasible therapeutic targets to counteract PDA. In particular, as the overexpressed or mutated glycolytic enzymes stimulate both humoral and cellular immune responses, we will discuss their possible exploitation as immunological targets in anti-PDA therapeutic strategies.

Multi-Omic Biomarkers as Potential Tools for the Characterisation of Pancreatic Cystic Lesions and Cancer: Innovative Patient Data Integration

Pancreatic cancer (PC) is regarded as one of the most lethal malignant diseases in the world, with GLOBOCAN 2020 estimates indicating that PC was responsible for almost half a million deaths worldwide in 2020. Pancreatic cystic lesions (PCLs) are fluid-filled structures found within or on the surface of the pancreas, which can either be pre-malignant or have no malignant potential. While some PCLs are found in symptomatic patients, nowadays many PCLs are found incidentally in patients undergoing cross-sectional imaging for other reasons-so called 'incidentalomas'. Current methods of characterising PCLs are imperfect and vary hugely between institutions and countries. As such, there is a profound need for improved diagnostic algorithms. This could facilitate more accurate risk stratification of those PCLs that have malignant potential and reduce unnecessary surveillance. As PC continues to have such a poor prognosis, earlier recognition and risk stratification of PCLs may lead to better treatment protocols. This review will focus on the importance of biomarkers in the context of PCLs and PCand outline how current 'omics'-related work could contribute to the identification of a novel integrated biomarker profile for the risk stratification of patients with PCLs and PC.

Circulating miR-16-5p, miR-92a-3p, and miR-451a in Plasma from Lung Cancer Patients: Potential Application in Early Detection and a Regulatory Role in Tumorigenesis Pathways

BACKGROUND

Micro(mi)RNAs, potent gene expression regulators associated with tumorigenesis, are stable, abundant circulating molecules, and detectable in plasma. Thus, miRNAs could potentially be useful in early lung cancer detection. We aimed to identify circulating miRNA signatures in plasma from patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and to verify whether miRNAs regulate lung oncogenesis pathways.

METHODS

RNA isolated from 139 plasma samples (40 LUAD, 38 LUSC; 61 healthy/non-diseased individuals) were divided into discovery (38 patients; 21 controls for expression quantification using an 800-miRNA panel; Nanostring nCounter®) and validation (40 patients; 40 controls; TaqMan® RT-qPCR) cohorts. Elastic net, Maximizing-R-Square Analysis (MARSA), and C-Statistics were applied for miRNA signature identification.

RESULTS

When compared to healthy individuals, 580 of 606 deregulated miRNAs in LUAD and 221 of 226 deregulated miRNAs in LUSC had significantly increased levels. Among the 10 most significantly overexpressed miRNAs, 6 were common to patients with LUAD and LUSC. Further analysis identified three signatures composed of 12 miRNAs. Signatures included miRNAs commonly overexpressed in patient plasma. Enriched pathways included target genes modulated by three miRNAs in the C-Statistics signature: miR-16-5p, miR-92a-3p, and miR-451a.

CONCLUSIONS

The 3-miRNA signature (miR-16-5p, miR-92a-3p, miR-451a) had high specificity (100%) and sensitivity (84%) to predict cancer (LUAD and LUSC). These miRNAs are predicted to modulate genes and pathways with known roles in lung tumorigenesis, including EGFR, K-RAS, and PI3K/AKT signaling, suggesting that the 3-miRNA signature is biologically relevant in adenocarcinoma and squamous cell carcinoma of the lung.