Early Diagnosis Of Lung Adenocarcinoma Research Articles

A novel microRNA miR-4433a-3p as a potential diagnostic biomarker for lung adenocarcinoma

BackgroundLung adenocarcinoma is one of the leading causes of cancer-related deaths because of the lack of early specific clinical indicators. MicroRNAs (miRNAs) have become the focus in lung cancer diagnosis. Further studies are required to explore miRNA expression in the serum of lung adenocarcinoma patients and their correlation with therapy and analyse specific messenger RNA targets to improve the specificity and sensitivity of early diagnosis. MethodsThe Toray 3D-Gene miRNA array was used to compare the expression levels of various miRNAs in the sera of patients with lung adenocarcinoma and healthy volunteers. Highly expressed miRNAs were selected for further analysis. To verify the screening results, serum and pleural fluid samples were analysed using qRT-PCR. Serum levels of the miRNAs and their correlation with the clinical information of patients with lung adenocarcinoma were analysed. The functions of miRNAs were further analysed using the Kyoto Encyclopedia of Gene and Genomes and Gene Ontology databases. ResultsMicroarray analysis identified 60 and 50 miRNAs with upregulated and downregulated expressions, respectively, in the serum of patients with lung adenocarcinoma compared to those in healthy individuals. Using qRT-qPCR to detection of miRNAs expression in the serum or pleural effusion of patients with early and advanced lung adenocarcinoma, we found that miR-4433a-3p could be used as a diagnostic marker and therapeutic evaluation indicator for lung adenocarcinoma. Serum of miR-4433a-3p levels significantly correlated with the clinical stage. miR-4433a-3p may be more suitable than other tumour markers for the early diagnosis and evaluation of therapeutic effects in lung adenocarcinoma. miR-4433a-3p may affect tumour growth and metastasis by acting on target genes (PIK3CD, UBE2J2, ICMT, PRDM16 and others) and regulating tumour-related signalling pathways (MAPK signal pathway, Ras signalling pathway and others). ConclusionmiR-4433a-3p may serve as a biomarker for the early diagnosis of lung adenocarcinoma and monitoring of therapeutic effects.

Value of the Air Bronchogram Sign and Other Computed Tomography Findings in the Early Diagnosis of Lung Adenocarcinoma.

The present study aims to explore the application value of the air bronchogram (AB) sign and other computed tomography (CT) signs in the early diagnosis of lung adenocarcinoma (LUAD). The pathological information and CT images of 130 patients diagnosed with N0 and M0 solitary pulmonary nodules (diameter ≤3 cm) and treated with surgical resection in our hospital between June 2021 and June 2022 were analyzed. The patients were divided into the benign pulmonary nodule (BPN) group (14 cases), the AIS group (30 cases), the MIA group (10 cases), and the IAC group (76 cases). Among the 116 patients with AIS and LUAD, 96 showed an AB sign. Among the 14 patients with BPN, only 4 patients showed an AB sign. The average CT value and maximum diameter were significantly higher in the IAC group than in the AIS and MIA groups. In the BPN group, 5 patients had an average CT value of >80 HU. Among all LUAD-based groups, there was only 1 patient with a CT value of >60 HU. The identification of the AB sign based on CT imaging facilitates the differentiation between benign and malignant nodules. The CT value and maximum diameter of pulmonary adenocarcinoma nodules increase with the increase of the malignancy degree. The nodule type, CT value, and maximum diameter are useful for predicting the pathological type and prognosis. If the average CT value of pulmonary nodules is >80 HU, LUAD may be excluded.

A Novel Methylation-based Model for Prognostic Prediction in Lung Adenocarcinoma.

Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients. DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models. Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival. This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.

P1.13-05 Targeting SGLT2 for Early Diagnosis of Lung Adenocarcinoma

P1.13-05 Targeting SGLT2 for Early Diagnosis of Lung Adenocarcinoma

Identification of TLRs as potential prognostic biomarkers for lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common tumors with the highest cancer-related death rate worldwide. Early diagnosis of LUAD can improve survival. Abnormal expression of the Toll-like receptors (TLRs) is related to tumorigenesis and development, inflammation and immune infiltration. However, the role of TLRs as an immunotherapy target and prognostic marker in lung adenocarcinoma is not well understood and needs to be analyzed. Relevant data obtained from databases such as ONCOMINE, UALCAN, GEPIA, and the Kaplan-Meier plotter, GSCALite, GeneMANIA, DAVID 6.8, Metascape, LinkedOmics and TIMER, to compare transcriptional TLRs and survival data of patients with LUAD. The expression levels of TLR1/2/3/4/5/7/8 in LUAD tissues were significantly reduced while the expression levels of TLR6/9/10 were significantly elevated. LUAD patients having low expression of TLR1/2/3/5/8 and high expression of TLR9 had a poor overall survival while patients with low expression of TLR2/3/7 presented with worse first progress. TLR4, TLR7 and TLR8 are the 3 most frequently mutated genes in the TLR family. Correlation suggested a low to moderate correlation among TLR family. TLR family was also involved in the activation or inhibition of the famous cancer related pathways. Analysis of immune infiltrates analysis suggested that TLR1/2/7/8 levels significantly correlated with immune infiltration level. Enrichment analysis revealed that TLRs were involved in TLR signaling pathway, immune response, inflammatory response, primary immunodeficiency, regulation of IL-8 production and PI3K-Akt signaling pathway. Our results provided information on TLRs expression and potential regulatory networks in LUAD. Moreover, our results suggested TLR2/7/8 as a potential prognostic biomarker for lung adenocarcinoma.

Identification of hsa-miR-619-5p and hsa-miR-4454 in plasma-derived exosomes as a potential biomarker for lung adenocarcinoma.

Introduction: Lung cancer has long been at the forefront of all cancers in terms of incidence and mortality. Lung adenocarcinoma is the most common type of lung cancer, accounting for 40% of all lung cancer types. Exosomes can act as biomarkers of tumors and thus play an important role. Methods: In this article, high-throughput sequencing of miRNAs in plasma exosomes from lung adenocarcinoma patients and healthy individuals was performed to obtain 87 upregulated miRNAs, which were then combined with data from the GSE137140 database uploaded by others for screening. The database included 1566 preoperative lung cancer patients, 180 postoperative patients, and 1774 non-cancerous controls. We overlapped the miRNAs upregulated in the serum of lung cancer patients in the database relative to those of non-cancer controls and post-operative patients with the upregulated miRNAs obtained from our next-generation sequencing to obtain nine miRNAs. Two miRNAs that were not reported as tumor markers in lung cancer, hsa-miR-4454 and hsa-miR-619-5p, were selected from them and then validated by qRT-PCR, and further analysis of miRNAs was performed using bioinformatics. Results: Real-time quantitative PCR showed that the expression levels of hsa-miR-4454 and hsa-miR-619-5p in plasma exosomes of patients with lung adenocarcinoma were significantly up-regulated. The AUC values of hsa-miR-619-5p and hsa-miR-4454 were 0.906 and 0.975, respectively, both greater than 0.5, showing good performance. The target genes of miRNAs were screened by bioinformatics methods, and the regulatory network between miRNAs and lncRNAs and mRNAs was studied. Discussion: Our work demonstrated that hsa-miR-4454 and hsa-miR-619-5p have the potential to be used as biomarkers for the early diagnosis of lung adenocarcinoma.

Abstract LB292: GCC2 on small extracellular vesicles for the early diagnosis of lung adenocarcinoma: A multicenter trial

Abstract Background: Early detection of lung cancer is extremely important for timely and effective therapeutic interventions to increase the survival rate of patients. Emerging evidence suggests that tumor-derived small extracellular vesicle (sEV) cargo may serve as cancer-specific biomarkers. We previously reported the identification of GRIP and coiled-coil domain-containing 2-enriched sEV (sEV-GCC2) as a promising biomarker for lung adenocarcinoma in a pilot study. In this multicenter study, we explored the diagnostic and therapeutic potential of sEV-GCC2 in early-stage lung adenocarcinoma. Methods: A total of 470 blood plasma samples (150 healthy controls and 320 patients with lung adenocarcinoma) were retrospectively obtained from five institutions. sEVs were isolated by size exclusion chromatography and sEV-GCC2 was quantified by enzyme-linked immunosorbent assay. Effect of sEV-GCC2 on lung cancer cell proliferation was investigated in vitro and in vivo. Results: sEV-GCC2 concentration was significantly higher in patients than that in controls with an area under the curve (AUC) of 0.856 (95% confidence interval [CI], 0.820-0.886). In patients at TisN0-T1miN0 stages vs controls, the AUC was 0.802 (95% CI, 0.734-0.859). The association between sEV-GCC2 and lung adenocarcinoma remained after adjustment for pathological TNM stage and tumor location in the left lower lobe. Immunohistochemical staining revealed that GCC2 expression was significantly higher in lung adenocarcinoma tissues than in the controls (p < 0.001). Furthermore, sEV-GCC2 enhanced cancer cell proliferation and accelerated tumor growth and lymph node metastasis. Conclusions: We identified sEV-GCC2 as a potential diagnostic marker for very early-stage lung cancer. sEV-GCC2 represents a promising therapeutic target for lung adenocarcinoma and may be quantified as key molecules in the progression of lung adenocarcinoma. Citation Format: Byeong Hyeon Choi, Hyonggin An, Sukki Cho, Sungsoo Lee, Hyeong Ryul Kim, Jong Ho Cho, Hyunku Shin, Ok Hwa Jeon, Yeonho Choi, Hyun Koo Kim. GCC2 on small extracellular vesicles for the early diagnosis of lung adenocarcinoma: A multicenter trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB292.

Molecular fingerprints of nuclear genome and mitochondrial genome for early diagnosis of lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer with high morbidity and mortality rates. Due to the heterogeneity of LUAD, its characteristics remain poorly understood. Exploring the clinical and molecular characteristics of LUAD is challenging but vital for early diagnosis.MethodsThis observational and validation study enrolled 80 patients and 13 healthy controls. Nuclear and mtDNA-captured sequencings were performed.ResultsThis study identified a spectrum of nuclear and mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with diagnosis. The correlation coefficient for somatic mutations in cfDNA and patient-matched tumor tissues was high in nuclear and mitochondrial genomes. The mutation number of highly mutated genes was evaluated, and the Least Absolute Shrinkage and Selection Operator (LASSO) established a diagnostic model. Receiver operating characteristic (ROC) curve analysis explored the diagnostic ability of the two panels. All models were verified in the testing cohort, and the mtDNA panel demonstrated excellent performance. This study identified somatic mutations in the nuclear and mitochondrial genomes, and detecting mutations in cfDNA displayed good diagnostic performance for early-stage LUAD. Moreover, detecting somatic mutations in the mitochondria may be a better tool for diagnosing early-stage LUAD.ConclusionsThis study identified specific and sensitive diagnostic biomarkers for early-stage LUAD by focusing on nuclear and mitochondrial genome mutations. This also further developed an early-stage LUAD-specific mutation gene panel for clinical utility. This study established a foundation for further investigation of LUAD molecular pathogenesis.

Secreted proteins MDK, WFDC2, and CXCL14 as candidate biomarkers for early diagnosis of lung adenocarcinoma

BackgroundEarly diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can’t meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation.MethodsDifferentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins.ResultsA total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells.ConclusionsMDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

Circular RNAs Hsa_circ_101555 and Hsa_circ_008068 as Diagnostic Biomarkers for Early-Stage Lung Adenocarcinoma.

BackgroundLung adenocarcinoma (LUAD) is a life-threatening disease worldwide with a high mortality rate. The early diagnosis of LUAD is crucial for improving subsequent treatment and prognosis. However, biomarkers for early detection remain a clinical challenge in LUAD. Here, we aimed to develop circular RNAs (circRNAs) in circulating plasma from LUAD patients as valuable diagnostic biomarkers in LUAD.MethodsCircRNA expression was determined by circRNA microarray in three pairs of LUAD tumour tissues and patient-matched normal lung tissues. Hsa_circ_101555 and hsa_circ_008068 were selected as potential biomarkers in LUAD tissues and plasma by RT–PCR, respectively. The diagnostic value was analysed by the area under the curve (AUC) and the receiver operating characteristic (ROC) test.ResultsOur results showed that 6261 circRNAs were upregulated and 7238 circRNAs were downregulated in LUAD tumour tissues compared with patient-matched normal lung tissues. Hsa_circ_101555 and hsa_circ_008068 were filtered as biomarkers for early-stage LUAD. Q-PCR results showed that hsa_circ_101555 and hsa_circ_008068 were significantly upregulated in both LUAD cancer tissues and circulating plasma. Hsa_circ_101555 and hsa_circ_008068 were positively associated with tumour differentiation, tumour size and CEA (P<0.05). The ROC analysis showed that hsa_circ_101555 and hsa_circ_008068 had a better diagnostic potential compared to the traditional biomarkers (CEA, SCC, CYFRA21-1) in the detection of early-stage LUAD.ConclusionThe circular RNAs hsa_circ_101555 and hsa_circ_008068 could serve as novel diagnostic biomarkers for early-stage LUAD.

Integration of bioinformatics analysis and experimental validation identifies plasma exosomal miR-103b/877-5p/29c-5p as diagnostic biomarkers for early lung adenocarcinoma.

The aim of this study was to identify miRNAs in plasma exosomes as noninvasive biomarkers for the early diagnosis of lung adenocarcinoma (LUAD). First, exosomal miRNA profiling of three patients with early LUAD and three patients with benign lung disease were screened by next-generation sequencing (NGS) method. Sequencing results showed that 154 exosomal miRNAs were differentially expressed in the plasma of LUAD patients, among which 68 miRNAs were up-regulated and 86 miRNAs were down-regulated. GSE137140 is a GEO database containing serum miRNAs sequencing data from 1566 lung cancer patients and 1774 non-cancer patients controls. When comparing the sequencing data, it was found that most miRNAs (37/68) up-regulated in our LUAD group were also significantly up-regulated in GSE137140, suggesting that circulating miRNAs in lung cancer patients may be enriched in plasma exosomes. In GSE137140, the AUC of the combination of hsa-miR-103b, hsa-miR-29c-5p and hsa-miR-877-5p was 0.873, showing great potential as new tumor markers. To our knowledge, these three exosomal miRNAs have not been reported in lung cancer research. Furthermore, bioinformatics tools were used to analyze the target genes of three candidate miRNAs, which were indeed closely related to the occurrence and development of lung cancer. Bioinformatics algorithms deduced a highly conserved sequence in the 3'-UTR of SFRP4, FOXM1 and TMEM98 that could be bound with miR-103b/877-5p/29c-5p. A luciferase assay indicated that miR-103b/877-5p/29c-5p directly targeted the 3'-UTR of SFRP4, FOXM1 and TMEM98, respectively. Finally, three candidate miRNAs were validated by qRT-PCR in 17 early LUAD samples and 17 control plasma samples. Integration of bioinformatics analysis and experimental validation identifies, this study provides novel insights into miRNA-related networks in LUAD. Hsa-miR-103b, hsa-miR-29c-5p, and hsa-miR-877-5p may be used as diagnostic biomarkers for early LUAD.

A Multi-Classification Model for Predicting the Invasiveness of Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodules.

ObjectivesTo establish a multi-classification model for precisely predicting the invasiveness (pre-invasive adenocarcinoma, PIA; minimally invasive adenocarcinoma, MIA; invasive adenocarcinoma, IAC) of lung adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).MethodsBy the inclusion and exclusion criteria, this retrospective study enrolled 346 patients (female, 297, and male, 49; age, 55.79 ± 10.53 (24-83)) presenting as pGGNs from 1292 consecutive patients with pathologically confirmed lung adenocarcinoma. A total of 27 clinical were collected and 1409 radiomics features were extracted by PyRadiomics package on python. After feature selection with L2,1-norm minimization, logistic regression (LR), extra w(ET) and gradient boosting decision tree (GBDT) were used to construct the three-classification model. Then, an ensemble model of the three algorithms based on model ensemble strategy was established to further improve the classification performance.ResultsAfter feature selection, a hybrid of 166 features consisting of 1 clinical (short-axis diameter, ranked 27th) and 165 radiomics (4 shape, 71 intensity and 90 texture) features were selected. The three most important features are wavelet-HLL_firstorder_Minimum, wavelet-HLL_ngtdm_Busyness and square_firstorder_Kurtosis. The hybrid-ensemble model based on hybrid clinical-radiomics features and the ensemble strategy showed more accurate predictive performance than other models (hybrid-LR, hybrid-ET, hybrid-GBDT, clinical-ensemble and radiomics-ensemble). On the training set and test set, the model can obtain the accuracy values of 0.918 ± 0.022 and 0.841, and its F1-scores respectively were 0.917 ± 0.024 and 0.824.ConclusionThe multi-classification of invasive pGGNs can be precisely predicted by our proposed hybrid-ensemble model to assist patients in the early diagnosis of lung adenocarcinoma and prognosis.

Plasma extracellular vesicle long RNA profiling identifies a diagnostic signature for stage I lung adenocarcinoma.

BackgroundThe early diagnosis of lung adenocarcinoma (LUAD) is particularly challenging. Recent studies have reported that extracellular vesicles (EVs) include both small and long RNA. However, the profile and diagnosis-related significance of EV long RNA (exLR) profiles for early LUAD remain unclear.MethodsA case-control analysis was carried out involving 110 participants, including 64 stage I LUAD cases, 24 benign pulmonary nodule (BPN) cases, and 22 healthy controls (HCs). The analysis was performed on the plasma samples’ exLR profile based on exLR sequencing. The d-signature was identified using the least absolute shrinkage and selection operator (LASSO) method and a training set (n=48), and validation was completed through use of an internal validation set (n=32) and an external validation set (n=30).ResultsA diagnostic signature (d-signature) encompassing 8 exLR markers (NFKBIA, NDUFB10, SLC7A7, ARPC5, SEPTIN9, HMGN1, H4C2, and lnc-PLA2G1B-2:3) was identified for the detection of LUAD. This d-signature exhibited a high level of accuracy, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.991 in the training group, 0.921 in the internal validation group, and 0.9 in the external validation group. Moreover, the d-signature could distinguish adenocarcinomas in situ (AIS) and minimally invasive adenocarcinomas (MIA) from the noncancerous controls (NCs), with AUCs of 0.934 and 0.909, respectively, in the combined cohorts.ConclusionsThis study initially characterized the plasma exLR profile of early LUAD and reported on an exLR-based diagnostic signature for the detection of LUAD. This d-signature could be a promising noninvasive biomarker for the early detection and routine screening of LUAD.

Identification and validation of novel DNA methylation markers for early diagnosis of lung adenocarcinoma.

Lung cancer has the highest mortality of all cancers worldwide. Epigenetic alterations have emerged as potential biomarkers for early diagnosis of various cancer tissue types. To identify methylation markers for early diagnosis of lung adenocarcinoma, we aimed to integrate genome-wide DNA methylation and gene expression data from The Cancer Genome Atlas. To this end, we first examined the global DNA methylation pattern of lung adenocarcinoma and investigated the relationship between DNA methylation subtypes and clinical features. We then extracted differentially methylated and expressed genes, and adopted feature selection techniques to determine the final methylation markers. The performance of the markers in predicting lung adenocarcinoma was evaluated on three independent datasets from Gene Expression Omnibus. Protein levels of marker genes were validated by immunohistochemistry, and their biological function was further verified invivo. We identified three novel methylation markers in lung adenocarcinoma including cg08032924, cg14823851, and cg19161124, mapping to CMTM2, TBX4, and DPP6, respectively. Validating these results on three independent datasets indicated that the three markers can achieve extremely high sensitivity and specificity in distinguishing lung adenocarcinoma from normal samples. Immunohistochemistry quantification results confirmed that markers are weakly expressed in human lung adenocarcinoma, and CMTM2 decreased tumor growth of mouse Lewis lung carcinoma invivo. Overall, our study identified three novel methylation markers in lung adenocarcinoma which may contribute toward an improved diagnosis potentially leading to a better outcome for patients with lung adenocarcinoma.

Serum von Willebrand factor for early diagnosis of lung adenocarcinoma in patients with type 2 diabetes mellitus.

BACKGROUNDThe elevation of plasma von Willebrand factor (vWF) has been proposed to be a predictor of lung cancer. Type 2 diabetes mellitus (T2DM) causes endothelial activation, resulting in the secretion of vWF. However, the role of vWF in patients with T2DM complicated with lung cancer remains unclear.AIMTo investigate the clinical value of serum vWF as a tumor marker in patients with T2DM combined with lung adenocarcinoma in situ (AIS).METHODSThis study enrolled 43 patients with T2DM combined with lung AIS (T2DM + AIS group), 43 patients with T2DM alone (T2DM group), 43 patients with lung AIS alone (AIS group), and 43 healthy volunteers (control group). The serum levels of vWF, insulin-like growth factor 1, and insulin-like growth factor binding protein 3 were determined. Multiple linear stepwise regression was performed to determine the correlations among variables.RESULTSSerum concentration of vWF in the T2DM + AIS group was significantly higher than those in the T2DM, AIS, and control groups (P < 0.05). Serum vWF levels in the T2DM and AIS groups were significantly higher than that in the control group (P < 0.05). There was no significant difference in serum vWF level between the T2DM and AIS groups. In the T2DM + AIS group, serum vWF was independently associated and positively correlated with serum levels of insulin-like growth factor 1 and insulin-like growth factor binding protein 3 (P < 0.05).CONCLUSIONSerum vWF level may represent a novel biomarker for the early diagnosis of lung AIS.

Serum TNFRII: A promising biomarker for predicting the risk of subcentimetre lung adenocarcinoma.

Early diagnosis of lung adenocarcinoma requires effective risk predictors. TNFRII was reported to be related to tumorigenesis, but remained unclear in lung cancer. This research set out to investigate the relationship between the sTNFRII (serum TNFRII) level and the risk of lung adenocarcinoma less than 1 cm in diameter. Seventy‐one pairs of subcentimetre lung adenocarcinoma patients and healthy controls were analysed through multiplex bead‐based Luminex assay and found a significantly lower expression of sTNFRII in patients with subcentimetre lung adenocarcinoma than that in the healthy controls (P < .001), which was further verified through ONCOMINE database analysis. Increased levels of sTNFRII reduced the risk of subcentimetre lung adenocarcinoma by 89% (P < .001). Patients with a higher level of BLC had a 2.70‐fold (P < .01) higher risk of subcentimetre adenocarcinoma. Furthermore, a higher BLC/TNFRII ratio was related to a 35‐fold higher risk of subcentimetre adenocarcinoma. TNFRII showed good specificity, sensitivity and accuracy (0.72, 0.75 and 0.73, respectively), with an AUC of 0.73 (P < .001). In conclusion, the present study assessed the value of sTNFRII as a potential biomarker to predict the risk of subcentimetre lung adenocarcinoma and provided evidence for the further use of TNFRII as an auxiliary marker in the diagnosis of subcentimetre lung adenocarcinoma.

P1.11-14 SGLT2 Is a Diagnostic and Therapeutic Target for Early-Stage Lung Adenocarcinoma

Early diagnosis of lung adenocarcinoma (LUAD) is crucial. The National Lung Screening Trial showed a 20% reduction in lung cancer mortality in high risk individuals using low-dose helical computed tomography (CT). CT is highly sensitive for detecting lung nodules, but is limited by low specificity, especially for LUAD. On CT, LUAD may appear as solid or subsolid nodules. Most subsolid nodules are not cancer, and many will remain stable or resolve; however, subsolid lesions can represent premalignancy or adenocarcinoma in situ. These lesions in the early spectrum of LUAD may persist for months to years before transforming into invasive disease. As a result, current standard of care is to follow these patients with CT imaging to monitor these indeterminate lesions for radiologic signs of malignant progression. The identification of novel biomarkers to predict the malignant potential of these nodules at their initial identification is of paramount importance. We have recently discovered that premalignant ad early invasive lesions of the LUAD spectrum rely on sodium-glucose transporter 2 (SGLT2) for glucose uptake, whereas advanced carcinomas up-regulate transporters of the GLUT family. This is consistent with the observation that positron emission tomography (PET) with 2-[18F] fluorodeoxyglucose (FDG), which detects GLUT but not SGLT activity, is a standard tool for staging advanced disease, but has low sensitivity for early-stage LUAD. We measured SGLT2 activity in vivo with the PET tracer methyl-4-[18F] fluorodeoxyglucose (Me4FDG). Me4FDG detects early-stage, FDG-negative LUAD in mouse models and in patients. Importantly, Me4FDG uptake correlates with tumor growth rate in patient-derived LUAD xenografts (fig. 1). Targeting SGLT2 with FDA-approved inhibitors significantly reduces tumor growth and prolongs survival in genetic and patient-derived murine models, confirming an important role of SGLT2 in early-stage LUAD. SGLT2 is a promising biomarker not only to diagnose early-stage tumors by PET imaging, but also to predict response to SGLT2 inhibitors.

Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma.

BackgroundCompeting endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer progression and poor prognosis. In this study, we aimed to identify ceRNAs that may serve as potential biomarkers for early diagnosis of lung adenocarcinoma (LUAD).MethodsWe performed differential gene expression analysis on TCGA-LUAD datasets to identify differentially expressed (DE) mRNAs, lncRNAs, and miRNAs at different tumor stages. Based on the ceRNA hypothesis and considering the synergistic or feedback regulation of ceRNAs, a lncRNA–miRNA–mRNA network was constructed. Functional analysis was performed using gene ontology term and KEGG pathway enrichment analysis and KOBAS 2.0 software. Transcription factor (TF) analysis was carried out to identify direct targets of the TFs associated with LUAD prognosis. Identified DE genes were validated using gene expression omnibus (GEO) datasets.ResultsBased on analysis of TCGA-LUAD datasets, we obtained 2,610 DE mRNAs, 915 lncRNAs, and 125 miRNAs that were common to different tumor stages (|log2(Fold change)| ≥ 1, false discovery rate < 0.01), respectively. Functional analysis showed that the aberrantly expressed mRNAs were closely related to tumor development. Survival analyses of the constructed ceRNA network modules demonstrated that five of them exhibit prognostic significance. The five ceRNA interaction modules contained one lncRNA (FENDRR), three mRNAs (EPAS1, FOXF1, and EDNRB), and four miRNAs (hsa-miR-148a, hsa-miR-195, hsa-miR-196b, and hsa-miR-301b). The aberrant expression of one lncRNA and three mRNAs was verified in the LUAD GEO dataset. Transcription factor analysis demonstrated that EPAS1 directly targeted 13 DE mRNAs.ConclusionOur observations indicate that lncRNA-related ceRNAs and TFs play an important role in LUAD. The present study provides novel insights into the molecular mechanisms underlying LUAD pathogenesis. Furthermore, our study facilitates the identification of potential biomarkers for the early diagnosis and prognosis of LUAD and therapeutic targets for its treatment.

Serum microRNAs improving the diagnostic accuracy in lung cancer presenting with pulmonary nodules.

MicroRNA (miRNA) is an approach for early diagnosing of cancer. We validated a panel of miRNAs (hsa-miR-199a-3p, hsa-miR-148a-3p, hsa-miR-210-3p, hsa-miR-378d and hsa-miR-138-5p) to aid early diagnosis of lung adenocarcinoma by blood test in lung cancer presenting with pulmonary nodules. A total of 369 individuals who were detected pulmonary nodules by computed tomography (CT) scan were enrolled into this study. These patients included 274 pulmonary malignant or borderline lung diseases and 122 lung benign pulmonary nodules. When the lung nodules were detected by combining with CT scan, we got patient blood samples in 2 days. Patients' serum was collected within 2 days prior to miRNAs analyses. We performed miRNAs panel by reverse transcription-polymerase chain reaction (RT-PCR). The sensitivity of miRNAs panel was 34.0% and the specificity of miRNAs panel was 90.2%. In invasive adenocarcinoma, the sensitivity of miRNAs panel was 44.7%. The overall false positive rate of CT imaging for nodules and glass ground nodules (GGNs) was 33.1%. When miRNAs panel test positive patients combined with the nodule size, the false positive rate was decreased to 3.2%. The greatest impact of using the miRNAs panel CT scan was decreasing the false positive. miRNAs panel can improve the diagnosis of lung cancer presenting with nodules combined with CT.