Potential Biomarker For Lung Cancer Research Articles

CKAP4 is a potential exosomal biomarker and therapeutic target for lung cancer.

Globally, lung cancer causes the most cancer death. While molecular therapy progress, including epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), has provided remarkable therapeutic effects, some patients remain resistant to these therapies and therefore new target development is required. Cytoskeleton-associated membrane protein 4 (CKAP4) is a receptor of the secretory protein Dickkopf-1 (DKK1) and the binding of DKK1 to CKAP4 promotes tumor growth via Ak strain transforming (AKT) activation. We investigated if CKAP4 functions as a diagnostic biomarker and molecular therapeutic target for lung cancer. CKAP4 secretion with exosomes from lung cancer cells and the effect of CKAP4 palmitoylation on its trafficking to the exosomes were examined. Serum CKAP4 levels were measured in mouse xenograft models, and 92 lung cancer patients and age- and sex-matched healthy controls (HCs). The lung cancer tissues were immunohistochemically stained for DKK1 and CKAP4, and their correlation with prognosis and serum CKAP4 levels were investigated. Roles of CKAP4 in the lung cancer cell proliferation were examined, and the effects of the combination of an anti-CKAP4 antibody and osimertinib, a third generation TKI, on anti-tumor activity were tested using in vitro and in vivo experiments. CKAP4 was released from lung cancer cells with exosomes, and its trafficking to exosomes was regulated by palmitoylation. CKAP4 was detected in sera from mice inoculated with lung cancer cells overexpressing CKAP4. In 92 lung cancer patients, positive DKK1 and CKAP4 expression patients showed worse prognoses. Serum CKAP4 positivity was higher in lung cancer patients than in HCs. After surgical operation, serum CKAP4 levels were decreased. CKAP4 overexpression in lung cancer cells promoted in vitro cell proliferation and in vivo subcutaneous tumor growth, which were inhibited by an anti-CKAP4 antibody. Moreover, treatment with this antibody or osimertinib, a third generation TKI, inhibited AKT activity, sphere formation, and xenograft tumor growth in lung cancer cells harboring EGFR mutations and expressing both DKK1 and CKAP4, while their combination showed stronger inhibition. CKAP4 may represent a novel biomarker and molecular target for lung cancer, and combination therapy with an anti-CKAP4 antibody and osimertinib could provide a new lung cancer therapeutic strategy.

Overview of Adductomics in Toxicology.

Adductomics is epidemiology at the molecular level. Untargeted adductomics compares levels of chemical adducts on albumin, hemoglobin, and DNA between healthy and exposed individuals. The goal is to determine a cause-and-effect relationship between chemical exposure and illness. Chemical exposures are not necessarily due to synthetic chemicals but are often due to oxidation products of naturally occurring lipids, for example, 4-hydroxynonenal and acrolein produced by lipid peroxidation of arachidonic and linoleic acids. The preferred method used in adductomics is ultra-high pressure liquid chromatography coupled to with nanoelectrospray tandem mass spectrometry. The mass of the adduct indicates its structure and identifies the chemical. The advantages of molecular epidemiology include information about the many toxicants to which a person is exposed over a period of weeks or months and the relative exposure levels. The disadvantage is the absence of information about the mechanism of toxicity. Untargeted adductomics examines albumin and hemoglobin adducts, which serve as biomarkers of exposure but do not identify the proteins and genes responsible for the toxicity. Targeted adductomics is used when the origin of the toxicity is known. This can be either an adducted protein, such as the butyrylcholinesterase protein modified by nerve agents, or a toxicant, such as acetaminophen. Untargeted adductomics methods have identified potential protein adduct biomarkers of breast cancer, colorectal cancer, childhood leukemia, and lung cancer. Adductomics is a new research area that offers structural insights into chemical exposures and a platform for the discovery of disease biomarkers. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC.

Clinical features and lipid metabolism genes as potential biomarkers in advanced lung cancer

BackgroundLung cancer is one of the most lethal tumors with a poor survival rate even in those patients receiving new therapies. Metabolism is considered one of the hallmarks in carcinogenesis and lipid metabolism is emerging as a significant contributor to tumor metabolic reprogramming. We previously described a profile of some lipid metabolism related genes with potential prognostic value in advanced lung cancer.AimTo analyze clinical and pathological characteristics related to a specific metabolic lipid genomic signature from patients with advanced lung cancer and to define differential outcome.MethodsNinety samples from NSCLC (non-small cell lung cancer) and 61 from SCLC (small cell lung cancer) patients were obtained. We performed a survival analysis based on lipid metabolic genes expression and clinical characteristics. The primary end point of the study was the correlation between gene expression, clinical characteristics and survival.ResultsClinical variables associated with overall survival (OS) in NSCLC patients were clinical stage, adenocarcinoma histology, Eastern Cooperative Oncology Group (ECOG), number and site of metastasis, plasma albumin levels and first-line treatment with platinum. As for SCLC patients, clinical variables that impacted OS were ECOG, number of metastasis locations, second-line treatment administration and Diabetes Mellitus (DM). None of them was associated with gene expression, indicating that alterations in lipid metabolism are independent molecular variables providing complementary information of lung cancer patient outcome.ConclusionsSpecific clinical features as well as the expression of lipid metabolism-related genes might be potential biomarkers with differential outcomes.

Circ_0000520 interacts with miR-512-5p to upregulate KIAA0100 to promote malignant behaviors in lung cancer.

CircRNAs function as pivotal molecules to regulate the malignant development of lung cancer. This study was designed to research the functional role and how it acted in lung cancer progression. Circ_0000520, microRNA-512-5p (miR-512-5p) and Breast cancer-overexpressed gene 1 (KIAA0100) levels were measured through reverse transcription-quantitative polymerase chain reaction assay. Cell Counting Kit-8 assay and EdU assay were used to examine cell proliferation. Cell cycle and apoptosis were evaluated via flow cytometry. The protein levels were determined using western blot. Cell migration and invasion were assessed by wound healing assay and transwell assay. The circ_0000520 function in vivo was explored by tumor xenograft assay. The molecular interaction was analyzed via Dual-luciferase reporter assay. Circ_0000520 was obviously upregulated in lung cancer tissues and cells. Silence of circ_0000520 inhibited proliferation, cell cycle progression, migration, invasion and angiogenesis but promoted cell apoptosis. Circ_0000520 downregulation reduced tumor growth of lung cancer in vivo. Circ_0000520 served as a miR-512-5p sponge. The oncogenic function of circ_0000520 was partly achieved by sponging miR-512-5p in lung cancer. KIAA0100 was a target of miR-512-5p and miR-512-5p inhibited the malignant behaviors of lung cancer cells via downregulating KIAA0100. Circ_0000520 targeted miR-512-5p to regulate the level of KIAA0100. All these data demonstrated that circ_0000520 was able to drive the progression of lung cancer via the mediation of miR-512-5p/KIAA0100 axis. Circ_0000520 might be a potential biomarker for lung cancer.

Peripheral Blood-Derived CircVPS35L as a Potential Diagnostic Biomarker for Non-Small Cell Lung Cancer.

Circular RNAs (circRNAs) are dysregulated in cancers and are stably expressed in body fluids such as blood. We therefore identified and evaluated the clinical value of a newly found circRNA VPS35L (circVPS35L) as a biomarker for the diagnosis of non-small cell lung cancer (NSCLC). Reverse-transcription quantitative PCR (RT-qPCR) was used to determine the expression levels of circVPS35L in tissues, whole blood, and cell lines. The actinomycin D assay and RNase R treatment were utilized to determine the stability of circVPS35L. Receiver operating characteristic (ROC) curve analysis was conducted to predict the diagnostic value of blood-derived circVPS35L in NSCLC. CircVPS35L was found to be downregulated in NSCLC tissues and cell lines. Interestingly, circVPS35L expression was significantly correlated with tumor size (p = 0.0269), histology type (p < 0.0001), and TNM stage (p = 0.0437). Importantly, circVPS35L was poorly expressed in peripheral blood of NSCLC patients when compared with healthy controls and patients with benign lung disease. ROC analysis revealed a higher diagnostic value of circVPS35L than the three conventional tumor markers (CYFR21-1, NSE, and CEA) in patients with NSCLC. Moreover, circVPS35L was highly stable in peripheral blood when exposed to undesirable conditions. These findings demonstrate that circVPS35L has great potential as a novel biomarker for the diagnosis of NSCLC and can be used to distinguish NSCLC from benign lung disease.

Identification of Potential Key Genes and Prognostic Biomarkers of Lung Cancer Based on Bioinformatics.

To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment. Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein-protein interaction (PPI) network was constructed by STRING online software for further study, and the core genes were determined by Cytoscape software and KEGG pathway enrichment analysis. The clustering heat map was drawn by Excel software to verify its accuracy. In addition, we used the University of Alabama at Birmingham Cancer (UALCAN) website to analyze the expression of core genes in P53 mutation status, confirmed the expression of crucial core genes in lung cancer tissues with Gene Expression Profiling Interactive Analysis (GEPIA) and GEPIA2 online software, and evaluated their prognostic value in lung cancer patients with the Kaplan-Meier online plotter tool. CHEK1, CCNB1, CCNB2, and CDK1 were selected. The expression levels of these four genes in lung cancer tissues were significantly higher than those in normal tissues. Their increased expression was negatively correlated with lung cancer patients (including LUAD and LUSC) prognosis and survival rate. CHEK1, CCNB1, CCNB2, and CDK1 are the critical core genes of lung cancer and are highly expressed in lung cancer. They are negatively correlated with the prognosis of lung cancer patients (including LUAD and LUSC) and closely related to the formation and prediction of lung cancer. They are valuable predictors and may be predictive biomarkers of lung cancer.

Nucleolin; A tumor associated antigen as a potential lung cancer biomarker

Lung cancer is a primary cause of mortality in many communities. The poor prognosis and clinical outcome of this cancer are mostly attributable to its advanced stage upon diagnosis, and as a result, it places a significant cost on public health across the globe. The majority of patients experience severe adverse effects from conventional therapies that involve nonspecific invasion of both healthy and malignant cells. Furthermore, no particular tumor marker has been developed to evaluate the patients' status and prognosis. NCL as one of the vital nuclear proteins is involved in various cellular activities, including ribosome assembly and rRNA processing. Research have shown that following malignant transformation in lung cancer cells, both the cytosolic and plasma membrane levels of this protein rise dramatically. Furthermore, signaling generated by the surface nucleolin significantly enhances tumor proliferation, differentiation, and angiogenesis. On the other hand, findings showed that altering the size and other properties of tumor cells may influence the expression pattern of nucleolin. Therefore, in the current study, we intend to review the role of nucleolin in the development and progression of lung cancer cells and also evaluate its potential as a prognostic, therapeutic as well as diagnostic marker in lung cancer patients.

Costimulatory molecule-related lncRNA model as a potential prognostic biomarker in non-small cell lung cancer.

Costimulatory molecules have been demonstrated to exert essential roles in multiple cancers. However, their role in lung cancer remains elusive. Here, we sought to identify costimulatory molecule-related lncRNAs in non-small cell lung cancer (NSCLC) and establish a prognostic signature to predict the prognosis of patients with NSCLC. A total of 535 lung adenocarcinoma (LUAD) and 502 lung squamous cell carcinoma (LUSC) patients from the cancer genome atlas (TCGA) database were recruited. A novel costimulatory molecule-based lncRNA prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival. The Homo_sapiens.GRCh38 data set was set as a reference file for probe annotation. A total of 593 costimulatory molecule-related lncRNAs were extracted. After analysis, six costimulatory molecule-related lncRNAs (AC084859.1, AC079949.2, HSPC324, LINC01150, LINC01150, and AC090617.5) were screened. A prognostic model based on the six lncRNAs was established using systematic bioinformatics analyses. The prognostic model had a prognostic value in NSCLC patients. Furthermore, a prognostic nomogram was established based on clinical parameters and a risk-score model. Patients with different risk scores had considerably different tumor-infiltrating immune cells, somatic mutational loading, clinical outcomes, signaling pathways, and immunotherapy efficacy. In addition, LINC01137 was associated with unfavorable disease outcomes and fueled tumor progression in NSCLC. Taken together, our study demonstrated that a costimulatory molecule-related lncRNA model could be a potential prognostic biomarker in NSCLC. Moreover, LINC01137 could facilitate the proliferation and invasion of lung cancer.

Helicene-Hydrazide Encapsulated Ethyl Cellulose as a Potential Fluorescence Sensor for Highly Specific Detection of Nonanal in Aqueous Solutions and a Proof-of-Concept Clinical Study in Lung Fluid.

Over the past years, lung cancer has been one of the vital cancer-related mortalities worldwide and has inevitably exhibited the highest death rate with the subsequent need for facile and convenient diagnosis approaches to identify the severity of cancer. Previous research has reported long-chain aldehyde compounds such as hexanal, heptanal, octanal, and nonanal as potential biomarkers of lung cancer. Herein, the helicene dye-encapsulated ethyl cellulose (EC@dye-NH) nanosensors have been applied for the potentially sensitive and specific detection of long-chain aldehydes in aqueous media. The sensors contain the intrinsic hydrazide group of dye-NH, which is capable of reacting an aldehyde group via imine formation and the EC backbone. This offers the synergistic forces of hydrophobic interactions with alkyl long-chain aldehydes, which could induce self-assembly encapsulation of EC@dye-NH nanosensors and strong fluorescence responses. The addition of long-chain aldehyde would induce the complete micellar-like nanoparticle formation within 15 min in acetate buffer pH 5.0. The limit of detection (LOD) values of EC@dye-NH nanosensors toward heptanal, octanal, and nonanal were 40, 100, and 10 μM, respectively, without interference from the lung fluid matrices and short-chain aldehydes. For practical applicability, this sensing platform was developed for quantification of the long-chain aldehydes in lung fluid samples with 98-101% recoveries. This EC@dye-NH nanosensor was applied to quantify nonanal contents in lung fluid samples. The results of this method based on EC@dye-NH nanosensors were then validated using standard gas chromatography-mass spectrometry (GC-MS), which gave results consistent with the proposed method. With intracellular imaging application, the EC@dye-NH nanosensors demonstrated excellent intracellular uptake and strong green fluorescence emission upon introducing the nonanal into the lung cancer cells (A549). Thus, the developed nanosensing approach served as the potential fluorescent probes in medical and biological fields, especially for lung cancer disease diagnosis based on highly selective and sensitive detection of long-chain aldehydes.

Transcription factor AP2 enhances malignancy of non-small cell lung cancer through upregulation of USP22 gene expression

BackgroundUbiquitin-specific protease 22 (USP22), a putative cancer stem cell marker, is frequently upregulated in cancers, and USP22 overexpression is associated with aggressive growth, metastasis, and therapy resistance in various human cancers including lung cancer. However, USP22 gene amplification seldom occurs, and the mechanism underlying USP22 upregulation in human cancers remains largely unknown.MethodsA luciferase reporter driven by a promoter region of USP22 gene was selectively constructed to screen against a customized siRNA library targeting 89 selected transcription factors to identify potential transcription factors (TFs) that regulate USP22 expression in human non-small cell lung cancers (NSCLC). Association of identified TFs with USP22 and potential role of the TFs were validated and explored in NSCLC by biological assays and immunohistochemistry analysis.ResultsLuciferase reporter assays revealed that SP1 and activating transcription factor 3 (ATF3) inhibit USP22 transcription, while transcription factor AP-2 Alpha/Beta (TFAP2A/2B) and c-Myc promote USP22 transcription. Binding site-directed mutagenesis and chromosome immunoprecipitation (ChIP) assays validated AP2α and AP2β are novel TFs of USP22. Furthermore, overexpression of AP2A and AP2B significantly upregulates USP22 expression, and its target: Cyclin D1, concurrently enhances the proliferation, migration, and invasion of NSCLC A549 and H1299 cells in a partially USP22-dependent manner. Moreover, AP2 protein level correlated with USP22 protein in human NSCLC tissues.ConclusionOur findings indicate AP2α and AP2β are important transcription factors driving USP22 gene expression to promote the progression of NSCLC, and further support USP22 as a potential biomarker and therapeutic target for lung cancer.1HTL99SXtPtQRdWEzUs9UTVideo

Translation of a tissue epigenetic signature to circulating free DNA suggests BCAT1 as a potential noninvasive diagnostic biomarker for lung cancer

Lung cancer patients are diagnosed at late stages when curative treatments are no longer possible; thus, molecular biomarkers for noninvasive detection are urgently needed. In this sense, we previously identified and validated an epigenetic 4-gene signature that yielded a high diagnostic performance in tissue and invasive pulmonary fluids. We analyzed DNA methylation levels using the ultrasensitive digital droplet PCR in noninvasive samples in a cohort of 83 patients. We demonstrated that BCAT1 is the candidate that achieves high diagnostic efficacy in circulating DNA derived from plasma (area under the curve: 0.85). Impact of potentially confounding variables was also explored.

Determination of breath isoprene in 109 suspected lung cancer patients using cavity ringdown spectroscopy

Background: Lung cancer is one of the most common malignant tumors worldwide. Currently, effective screening methods for early lung cancer are still scarce. Breath analysis provides a promising method for the pre-screening or early screening of lung cancer. Isoprene is a potential and important breath biomarker of lung cancer. Material and Methods: To investigate the clinical value of isoprene for diagnosing lung cancer patients, a cavity ringdown spectroscopy (CRDS) based near-real time, sensitive analysis method of breath isoprene is developed in our lab. In this paper, 92 breath samples from lung cancer patients, 17 breath samples from patients with benign lesions, and 107 breath samples from healthy people were collected. Results: Research indicates that breath isoprene concentration is significantly higher in healthy individuals ([Formula: see text][Formula: see text]ppbv) than in patients with lung cancer ([Formula: see text][Formula: see text]ppbv) and benign lung lesions ([Formula: see text][Formula: see text]ppbv). The result of Receiver Operating Characteristic (ROC) curve suggests that the concentration of isoprene is meaningful for the diagnosis of lung cancer ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]). Conclusion: This study demonstrates that the CRDS breath isoprene analysis system can effectively analyze a large sample of human breath isoprene, and preliminarily confirms the use of breath isoprene as a biomarker for lung diseases.

New biochemical, immune and molecular markers in lung cancer: Diagnostic and prognostic opportunities.

Lung cancer is one of the most common neoplasms and the leading cause of cancer-related deaths worldwide. Despite recent progress in understanding the pathomechanisms of lung cancer, it is frequently associated with late diagnosis, high incidence of metastases and poor response to treatment. Thus, there is extensive research in the field of biomarkers that aims to optimize management of lung cancer. The aim of this study was to review the current perspectives of a wide spectrum of circulating molecules that seem promising as new potential biomarkers of lung cancer. Among these, biochemical (active proteins), immunological (immunocompetent cells, cytokines, chemokines, and antibodies) and genetic (circulating tumor DNA, cell-free DNA and microRNA) markers are presented and discussed. The use of these markers would support the early detection of lung cancer and might be used for predicting disease progression, response of the disease to targeted therapies, monitoring the course of treatment, and developing individualized diagnostic and therapeutic strategies. Special attention was given to potential markers of nervous system involvement in the course of lung cancer, due to its prevalence and devastating impact. Limitations of the potential biomarkers are also outlined and future directions of investigations in this field highlighted, with the aim of improving the accuracy and practical utility of these biomarkers.

Mitochondria-derived small RNAs as diagnostic biomarkers in lung cancer patients through a novel ratio-based expression analysis methodology

Small non-coding RNAs are potential diagnostic biomarkers for lung cancer. Mitochondria-derived small RNA (mtRNA) is a novel regulatory small non-coding RNA that only recently has been identified and cataloged. Currently, there are no reports of studies of mtRNA in human lung cancer. Currently, normalization methods are unstable, and they often fail to identify differentially expressed small non-coding RNAs (sncRNAs). In order to identify reliable biomarkers for lung cancer screening, we used a ratio-based method using mtRNAs newly discovered in human peripheral blood mononuclear cells. In the discovery cohort (AUC = 0.981) and independent validation cohort (AUC = 0.916) the prediction model of eight mtRNA ratios distinguished lung cancer patients from controls. The prediction model will provide reliable biomarkers that will allow blood-based screening to become more feasible and will help make lung cancer diagnosis more accurate in clinical practice.

Finding Lung-Cancer-Related lncRNAs Based on Laplacian Regularized Least Squares With Unbalanced Bi-Random Walk.

Lung cancer is one of the leading causes of cancer-related deaths. Thus, it is important to find its biomarkers. Furthermore, there is an increasing number of studies reporting that long noncoding RNAs (lncRNAs) demonstrate dense linkages with multiple human complex diseases. Inferring new lncRNA-disease associations help to identify potential biomarkers for lung cancer and further understand its pathogenesis, design new drugs, and formulate individualized therapeutic options for lung cancer patients. This study developed a computational method (LDA-RLSURW) by integrating Laplacian regularized least squares and unbalanced bi-random walk to discover possible lncRNA biomarkers for lung cancer. First, the lncRNA and disease similarities were computed. Second, unbalanced bi-random walk was, respectively, applied to the lncRNA and disease networks to score associations between diseases and lncRNAs. Third, Laplacian regularized least squares were further used to compute the association probability between each lncRNA-disease pair based on the computed random walk scores. LDA-RLSURW was compared using 10 classical LDA prediction methods, and the best AUC value of 0.9027 on the lncRNADisease database was obtained. We found the top 30 lncRNAs associated with lung cancers and inferred that lncRNAs TUG1, PTENP1, and UCA1 may be biomarkers of lung neoplasms, non-small–cell lung cancer, and LUAD, respectively.

Interleukin-11: A Potential Biomarker and Molecular Therapeutic Target in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.

Insulin-Like Growth Factor 2 mRNA-Binding Protein 3 and Its Related Molecules as Potential Biomarkers in Small-Cell Lung Cancer.

Background Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) plays a key role in tumorigenesis and tumor progression. Lung cancer is the leading cause of cancer-related death in men and women all over the world. However, the relationship between IGF2BP3 and small-cell lung cancer (SCLC) has not been reported yet. Methods SCLC and normal samples (GSE19945 and GSE149507) were obtained in the Gene Expression Omnibus (GEO) dataset. Differential genes were screened by R software, and functional analysis and signal pathway enrichment analysis were carried out. In addition, we used the survival analysis database to analyze the relationship between prognosis and gene expression. Besides, immunohistochemistry (IHC) and quantitative real-time PCR (qPCR) were used for further research. Results Five differentially expressed miRNAs and 9 differentially expressed mRNAs were selected by using R software. Survival analysis database results show that C7, CLIC5, PRDX1, IGF2BP3, and LDB2 were related the overall survival of patients with SCLC. Furthermore, multivariate analysis included that IGF2BP3 was independent risk factors for SCLC patients. Besides, gene function and signal pathway enrichment analysis showed that differentially expressed miRNAs were involved in the process of tumorigenesis and development. Furthermore, IHC and qPCR outcomes showed that the expression level of hsa-miR-182, hsa-miR-183, and IGF2BP3 was differentially expressed in normal lung tissues (NLTs) and SCLC tissues (SCLCTs). Conclusions Our results concluded that hsa-miR-182, hsa-miR-183, and IGF2BP3 may take part in the development of SCLC.

Bioinformatics Analysis Screened and Identified Key Genes as Potential Biomarkers for Progression of Lung Cancer.

To screen and identify key genes as potential biomarkers of lung cancer using bioinformatics analysis. Observational study. Department of Critical Care Medicine, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, China, from August 2018 to April 2021. Independent microarray datasets (GSE85841 and GSE118370) were downloaded from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were screened using GEO2R. Cytohubba was employed to identify the hub genes. Cellular component analysis, hierarchical clustering, and survival analyses of hub genes were performed via BiNGO, UCSC, and cBioPorta. A series of analyses of FGF2 and PIK3R1 were conducted using Oncomine. A total of 463 DEGs were identified and 11 hub genes were determined. BDNF, FGF2, JAK2, NCAM1, CAV1, TJP1, and PIK3R1 may affect the survival probability and life expectancy of lung cancer patients, but the p-values were not statistically significant. FGF2 and PIK3R1 had the highest node degrees, 40 and 32 respectively. The expression of FGF2 and PIK3R1 were significantly lower in the 4 lung cancer data sets compared with non-lung cancer tissues. And the low expression of FGF2 and PIK3R1 is related to tumor grades, family history of cancer, multiple tumors present, and prior therapy of lung cancer. Evaluation of FGF2 and PIK3R1 as potential biomarkers can contribute to the subsequent theoretical analysis of potential molecular mechanisms and development of lung cancer, so that the diagnosis of lung cancer may be more accurate, and it is possible to provide therapeutic and prognostic medicine targets. Lung neoplasms, Differentially expressed genes, Bioinformatical analysis, Microarray analysis, biomarkers.

Breath biopsy early detection of lung cancer using an EVOC probe targeting tumor-specific extracellular β-glucuronidase.

2569 Background: Lung cancer is a leading cause of mortality with 5-year survival less than 20%, largely a result of many cases being diagnosed late. Early detection can increase cancer survival up to 13-fold underscoring the need for effective screening. Targeted Low dose computed tomography (LDCT) has been shown to be effective but its impact to date has been limited due to slow adoption and variable uptake in high-risk populations. Breath analysis represents a non-invasive screening approach either alone or alongside LDCT. Numerous studies have investigated potential endogenous breath biomarkers of lung cancer. Many have produced promising results but to date, no validated biomarkers with clear connections to cancer metabolism have been revealed. We have explored an alternative, probe-based approach based around Exogenous Volatile Organic Compound Probes (EVOC Probes). The probes target tumour associated extracellular b-glucuronidase, a glycosidase enzyme that normally resides within lysosomes. Methods: We use a hydrophilic non cell permeable substrate probe D5-ethyl-βD-glucuronide (D5-EtGlu) that upon hydrolysis by the target enzyme releases D5-ethanol, a unique volatile reporter molecule detectable on breath. This provides a readout of tumour associated enzyme activity using breath analysis. Results: Administering D5-EtGlu to mice resulted in tumour specific release of D5-ethanol, enabling discrimination between healthy and tumour bearing animals. Increased expression of b-glucuronidase in lung cancer tissue and the tumour microenvironment was confirmed with immunohistochemistry (IHC) in clinical samples. A phase 1a clinical trial administered D5-EtGlu to healthy individuals in a single ascending dose study to establish safety and background D5-ethanol levels in healthy individuals. This resulted in no adverse events and low/no D5-ethanol signal verifying the inaccessibility of D5-EtGlu to intracellular b-glucuronidase. The next stage, currently ongoing, is a proof of mechanism in humans. D5-EtGlu is administered intravenously to confirmed lung cancer patients followed by breath analysis. D5-ethanol breath levels will be compared to cancer free individuals receiving the same dose of D5-EtGlu. Conclusions: Non-invasive breath testing has great potential to contribute to diagnosis for lung cancer including a potential role in screening. Our current work is evaluating the use of an administered probe to stimulate tumour-specific enzyme activity and produce a marker detectable on breath. Continued success could result in a sensitive and highly specific method for lung cancer early detection.