Serum DSG2 as a potential biomarker for diagnosis of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma

Background: Exploration of serum biomarkers for early detection of upper gastrointestinal cancer is required. Here, we aimed to evaluate the diagnostic potential of serum desmoglein-2 (DSG2) in patients with esophageal squamous cell carcinoma (ESCC) and esophagogastric junction adenocarcinoma (EJA).Methods: Serum DSG2 levels were measured by enzyme-linked immunosorbent assay (ELISA) in 459 participants including 151 patients with ESCC, 96 with EJA, and 212 healthy controls. Receiver operating characteristic (ROC) curves were used to evaluate diagnostic accuracy.Results: Levels of serum DSG2 were significantly higher in patients with ESCC and EJA than those in healthy controls (P<0.001). Detection of serum DSG2 demonstrated an area under the ROC curve (AUC) value of 0.724, sensitivity of 38.1%, and specificity of 84.8% for the diagnosis of ESCC in the training cohort, and AUC 0.736, sensitivity 58.2%, and specificity 84.7% in the validation cohort. For diagnosis of EJA, measurement of DSG2 provided a sensitivity of 29.2%, a specificity of 90.2%, and AUC of 0.698. Similar results were observed for the diagnosis of early-stage ESCC (AUC 0.715 and 0.722, sensitivity 36.3 and 50%, and specificity 84.8 and 84.7%, for training and validation cohorts, respectively) and early-stage EJA (AUC 0.704, sensitivity 44.4%, and specificity 86.9%). Analysis of clinical data indicated that DSG2 levels were significantly associated with patient age and histological grade in ESCC (P<0.05).Conclusion: Serum DSG2 may be a diagnostic biomarker for ESCC and EJA.     

IGFBP-4: A promising biomarker for lung cancer

Background: Insulin-like growth factor binding protein-4 (IGFBP-4), a member of the insulin-like growth factor (IGF) family, transports, and regulates the activity of IGFs. The pregnancy-associated plasma protein-A (PAPP-A) has proteolytic activity towards IGFBP-4, and both proteins have been associated with a variety of cancers, including lung cancer. Thus, we aimed to evaluate the use of IGFBP-4 and PAPP-A as potential biomarkers for lung cancer. Methods: Eighty-three volunteers, including 60 patients with lung cancer and 23 healthy individuals, were included in this study. The patients with lung cancer were selected based on their treatment status, histological subgroup, and stage of the disease. Enzyme-linked immunosorbent assays were used to assess the serum levels of IGFBP-4 and PAPPA, whereas the IGF-1 levels were measured using a chemiluminescent immunometric assay. Results: The serum IGFBP-4 levels in all patient groups, regardless of the treatment status and histological differences, were significantly higher than those in the control group (p<0.005). However, the serum PAPP-A levels in the untreated patient group were found to be higher than those in the control group, but this difference was not statistically significant (p=0.086). Conclusions: The serum PAPP-A and IGFBP-4 levels are elevated in lung cancer. However, IGFBP-4 may have better potential than PAPP-A as a lung cancer biomarker.     

Identification SYT13 as a novel biomarker in lung adenocarcinoma

Synaptotagmins are a class of proteins that play an important role in the secretion of neurotransmitters by synaptic vesicles. However, recent studies have shown that members of this family also have a certain function in the development of tumors. In this study, we first identified through The Cancer Genome Atlas data analyzed that a novel synaptotagmin, SYT13, was closely related to the prognosis of lung adenocarcinoma, but was not significantly correlated with the prognosis of lung squamous cell carcinoma. Then we knocked down the expression of SYT13 gene in lung adenocarcinoma cell lines A549 and H1299, and successfully induced decreased proliferation and clonality of lung adenocarcinoma cell lines, and observed cell cycle arrest and apoptosis enhancement in both cell lines. In addition, we detected the migration ability of SYT13 knockdown lung adenocarcinoma cell lines by the cell scratch test and the transwell test. Interestingly, there was a decreased migration ability of SYT13 knockdown in H1299 cells even though there was no significant difference in the migration of A549 cells. These results demonstrate that SYT13 plays an important role in the development of lung adenocarcinoma, which deepens our understanding of the mechanism of lung adenocarcinoma development and provides new possibilities for targeted therapy of lung adenocarcinoma.     

Serum exosomal miR-7977 as a novel biomarker for lung adenocarcinoma

Exosomal microRNAs (miRNAs) have great potentials as a novel biomarker to predict lung cancer. We applied a miRNA microarray to identify aberrantly expressed serum exosomal miRNAs as candidate biomarkers for patients with lung adenocarcinoma (LUAD). Compared with the normal control, 31 exosomal miRNAs were found to be upregulated and 29 exosomal miRNAs were downregulated in the serum of LUAD respectively. Then, 10 dysregulated exosomal miRNAs expression levels in serum were further validated via qRT-polymerase chain reaction. Notably, exosomal miR-7977 was highest expressed and miR-98-3p was lowest expressed in the patients with LUAD, and exosomal miR-7977 showed significant correlation with the N stage and TNM stage with patients with LUAD (P < .05). Receiver operating characteristic curve showed that the abundant level of exosomal miR-7977 may predict LUAD with an area of under the curve (AUC) of 0.787. In comparison with exosomal miR-7977, exosomal miR-98-3p had a smaller area (0.719). The combination of exosomal miR-7977 and miR-98-3p improved the AUC to 0.816. Furthermore, in vitro experiments revealed that inhibition of miR-7977 enhanced the proliferation, invasion, and inhibited apoptosis in A549 cells, the opposite results were performed by miR-7977 mimics. In conclusion, exosomal miR-7977 was identified as a novel biomarker for patients with LUAD and may play as a tumor suppressor in lung cancer.     

Differences in protein-protein association networks for lung adenocarcinoma: A retrospective study

Various methods to determine the connectivity scores between groups of proteins associated with lung adenocarcinoma are examined. Proteins act together to perform a wide range of functions within biological processes. Hence, identification of key proteins and their interactions within protein networks can provide invaluable information on disease mechanisms. Differential network analysis provides a means of identifying differences in the interactions among proteins between two networks. We use connectivity scores based on the method of partial least squares to quantify the strength of the interactions between each pair of proteins. These scores are then used to perform permutation-based statistical tests. This examines if there are significant differences between the network connectivity scores for individual proteins or classes of proteins. The expression data from a study on lung adenocarcinoma is used in this study. Connectivity scores are computed for a group of 109 subjects who were in the complete remission and as well as for a group of 51 subjects whose cancer had progressed. The distributions of the connectivity scores are similar for the two networks yet subtle but statistically significant differences have been identified and their impact discussed.     

A case of resectable lung adenocarcinoma associated with sarcoidosis

A 71-year-old woman with uveitis was referred to our hospital for further examination of the possible underlying diseases. In roentgenological examination with plain X-ray and CT scan, hilar and mediastinal lymphadenopathy and a mass shadow in the right upper lung field was observed, whereas fibrotic changes were not obvious in both lung fields. Transbronchial lung biopsy with fiberoptic bronchoscope revealed granulomatous interstitial pneumonia. CD4-positive lymphocytes were increased in bronchoalveolar lavage. The patient was diagnosed as having sarcoidosis. Subsequently, right upper lobectomy was performed, and Stage I lung adenocarcinoma was diagnosed. The patient is under follow up without medication and the disease has been stable for two years. A relationship between epithelioid granulomatosis and malignant diseases is discussed and a review of the literature is given. Since it is still controversial as to the incidence of malignant diseases in sarcoidosis patients, it is important to accumulate data on these associations.     

MNX1-AS1 is a novel biomarker for predicting clinical progression and poor prognosis in lung adenocarcinoma

Motor neuron and pancreas homeobox 1-antisense RNA1 (MNX1-AS1) is a novel long noncoding RNA and has been suggested to be overexpressed in human ovarian cancer and glioma. The role of MNX1-AS1 in lung cancer was still unknown. In our study, we observed levels of MNX1-AS1 expression through analyzing The Cancer Genome Atlas and found MNX1-AS1 expression was highly expressed in lung adenocarcinoma tissues compared with normal lung tissues, but there was no statistical difference between lung squamous cell carcinoma tissues and normal lung tissues. Furthermore, we conducted quantitative real-time polymerase chain reaction, and confirmed that the expression of MNX1-AS1 was definitely higher in lung adenocarcinoma tissue samples, but not in lung squamous cell carcinoma tissue samples. In addition, high MNX1-AS1 expression was found to be associated with the low differentiated degree, advanced clinical stage, big tumor size, lymph node metastasis, and distant metastasis in lung adenocarcinoma patients. High expression of MNX1-AS1 was negatively correlated with overall survival time and served as an independent unfavorable prognostic factor in patients with lung adenocarcinoma. The in vitro functional studies suggested that suppression of MNX1-AS1 inhibited lung adenocarcinoma cell proliferation and migration, and promoted apoptosis. In conclusion, MNX1-AS1 is overexpressed in lung adenocarcinoma, and associated with clinical progression and poor prognosis.     

Identification of a panel of mitotic spindle-related genes as a signature predicting survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most malignant tumor types worldwide. Our objective was to identify a genetic signature that could predict the prognosis of patients with LUAD. We extracted gene data sets from The Cancer Genome Atlas and obtained differentially expressed genes that were highly expressed at every stage. These genes were analyzed using gene set enrichment analysis to obtain four biological processes associated with LUAD. Subsequently, Cox univariate and multivariate analyses were performed to generate four optimized models (G2M checkpoint, E2F targets, mitotic spindle, and glycolysis). We identified a mitotic spindle-related signature (KIF15, BUB1, CCNB2, CDK1, KIF4A, DLGAP5, ECT2, and ANLN), which could be an independent prognostic indicator, to predict the prognosis of patients with LUAD. This new discovery should offer opportunities to explore the pathogenesis of LUAD and prove clinically useful in predicting LUAD patient prognosis.     

Serum CYR61 as a potential biomarker for the diagnosis of esophagogastric junction tumor

Background: Esophagogastric junction tumor (EGJ) is a rare but fatal disease with a rapid rising incidence worldwide in the late 20 years, and it lacks a convenient and safe method for diagnosis. The present study aimed to evaluate the potential of serum CYR61 as a biomarker for the diagnosis of EGJ tumor.Methods: Enzyme-linked immunosorbent assay (ELISA) was used to estimate CYR61 levels in sera of 152 EGJ tumor patients and 137 normal controls. Receiver operating characteristics (ROC) was carried out to evaluate the diagnostic accuracy. The Mann–Whitney’s U test was used to compare the difference of serum levels of CYR61 between groups. And chi-square tests were employed to estimate the correlation of the positive rate of serum CYR61 between/among subgroups.Results: Serum CYR61 levels were statistically lower in EGJ tumor and early-stage EGJ tumor patients than those in normal controls (P<0.0001). The sensitivity, specificity and the area under the curve (AUC) of this biomarker in EGJ tumor were 88.2%, 43.8% and 0.691, respectively, and those for early stage of EGJ tumor were 80.0%, 66.4% and 0.722, respectively. Analyses showed that there was no correlation between the clinical data and the levels of CYR61 (P>0.05).Conclusion: The present study showed that CYR61 might be a potential biomarker to assist the diagnosis of EGJ tumor.     

细胞外微RNA:一种新型的肺癌分子生物标志物

尽管癌症的早期诊断和治疗在不断发展和进步,但寻找一种敏感、准确和微创的分子生物标志物,用于肿瘤的诊断仍是一项艰巨任务。微RNA(miRNA)是一类长约21～24个核甘酸的内源性非编码小分子RNA。细胞外miRNA作为一种新型的分子生物标志物,在癌症诊断方面具有微创、高灵敏度和高特异性等许多潜在特征。近年来,细胞外miRNA研究成果颇丰。文章就细胞外miRNA的来源、功能、检测以及作为分子标志物在肺癌诊断中的作用和目前存在的一些问题进行了综述。     

52例肺腺癌的临床表现及影像学分析

目的:探讨肺腺癌的临床表现及影像学特点。方法:回顾性分析52例肺腺癌的临床表现及影像学资料,从该病的临床表现、影像学特点进行归纳及总结性研究。结果:52例肺腺癌患者主要症状为咳嗽、咯血、胸闷和其他转移病灶表现,转移多见于脑、肝、骨骼、肾上腺等,发生淋巴结转移患者的5年生存率明显下降;47例患者行普通X线胸片检查,6例未见明显异常病灶,13例为中心型肺癌,25例为周围型肺癌,3例为细支气管-肺泡癌;52例患者均行CT扫描检查,各叶均可发生,病灶呈圆形、椭圆形、分叶状,病灶大多边缘有切迹、细小毛刺或棘状突起者。结论:结合临床表现,CT能够较准确的对肺癌做出诊断,组织病理学检查可确诊为肺腺癌     

Choline Transporters in Human Lung Adenocarcinoma： Expression and Functional Implications

Choline is an essential nutrient for cell survival and proliferation, however, the expression and function of choline transporters have not been well identified in cancer. In this study, we detected the mRNA and protein expression of organic cation transporter OCT3, carnitine/cation transporters OCTN 1 and OCTN2, and choline transporter-like protein CTL1 in human lung adenocarcinoma cell lines A549, H 1299 and SPC-A-1. Their expression pattern was further confirmed in 25 human primary adenocarcinoma tissues. The choline uptake in these cell lines was significantly blocked by CTL1 inhibitor, but only partially inhibited by OCT or OCTN inhibitors. The efficacy of these inhibitors on cell proliferation is closely correlated with their abilities to block choline transport. Under the native expression of these transporters, the total choline uptake was notably blocked by specific PI3K/AKT inhibitors. These results describe the expression of choline transporters and their relevant function in cell proliferation of human lung adenocarcinoma, thus providing a potential ＂choline-starvation＂ strategy of cancer interference through targeting choline transporters, especially CTL1.     

A novel autophagy-related lncRNA survival model for lung adenocarcinoma

Long non-coding RNA (lncRNA) is an important regulatory factor in the development of lung adenocarcinoma, which is related to the control of autophagy. LncRNA can also be used as a biomarker of prognosis in patients with lung adenocarcinoma. Therefore, it is important to determine the prognostic value of autophagy-related lncRNA in lung adenocarcinoma. In this study, autophagy-related mRNAs-lncRNAs were screened from lung adenocarcinoma and a co-expression network of autophagy-related mRNAs-lncRNAs was constructed by using The Cancer Genome Atlas (TCGA). The univariate and multivariate Cox proportional hazard analyses were used to evaluate the prognostic value of the autophagy-related lncRNAs and finally obtained a survival model composed of 11 autophagy-related lncRNAs. Through Kaplan-Meier analysis, univariate and multivariate Cox regression analysis and time-dependent receiver operating characteristic (ROC) curve analysis, it was further verified that the survival model was a new independent prognostic factor for patients with lung adenocarcinoma. In addition, based on the survival model, gene set enrichment analysis (GSEA) was used to illustrate the function of genes in low-risk and high-risk groups. These 11 lncRNAs were GAS6-AS1, AC106047.1, AC010980.2, AL034397.3, NKILA, AL606489.1, HLA-DQB1-AS1, LINC01116, LINC01806, FAM83A-AS1 and AC090559.1. The hazard ratio (HR) of the risk score was 1.256 (1.196-1.320) (P < .001) in univariate Cox regression analysis and 1.215 (1.149-1.286) (P < .001) in multivariate Cox regression analysis. And the AUC value of the risk score was 0.809. The 11 autophagy-related lncRNA survival models had important predictive value for the prognosis of lung adenocarcinoma and may become clinical autophagy-related therapeutic targets.     

Deep learning for predicting subtype classification and survival of lung adenocarcinoma on computed tomography

ObjectivesThe subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung adenocarcinoma diagnosed through computed tomography (CT) images.MethodsA dataset of 1222 patients with lung adenocarcinoma were retrospectively enrolled from three medical institutions. The anonymised preoperative CT images and pathological labels of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, invasive adenocarcinoma (IAC) with five predominant components were obtained. These pathological labels were divided into 2-category classification (IAC; non-IAC), 3-category and 8-category. We modeled the classification task of histological subtypes based on modified ResNet-34 deep learning network, radiomics strategies and deep radiomics combined algorithm. Then we established the prognostic models in lung adenocarcinoma patients with survival outcomes. The accuracy (ACC), area under ROC curves (AUCs) and C-index were primarily performed to evaluate the algorithms.ResultsThis study included a training set (n = 802) and two validation cohorts (internal, n = 196; external, n = 224). The ACC of deep radiomics algorithm in internal validation achieved 0.8776, 0.8061 in the 2-category, 3-category classification, respectively. Even in 8 classifications, the AUC ranged from 0.739 to 0.940 in internal set. Further, we constructed a prognosis model that C-index was 0.892(95% CI: 0.846–0.937) in internal validation set.ConclusionsThe automated deep radiomics based triage system has achieved the great performance in the subtype classification and survival predictability in patients with CT-detected lung adenocarcinoma nodules, providing the clinical guide for treatment strategies.     

Exploration of the prognostic prediction value of the PANoptosis-based risk score and its correlation with tumor immunity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common cancer with high mortality worldwide. PANoptosis is a novel inflammatory programmed cell death modality with the characteristics of pyroptosis, apoptosis and necroptosis. It is necessary to explore PANoptosis-related genes in LUAD patients and offer evidence for prognosis prediction and therapeutic strategies. Single-cell RNA sequencing data and RNA expression profiles of LUAD patients from The Cancer Genome Atlas and Gene Expression Omnibus databases are used to screen PANoptosis-related differential genes for the construction of a risk model. Fifteen PANoptosis-related markers with prognostic value were identified by Least Absolute Shrinkage and Selection Operator (LASSO)–Cox regression analysis. Kaplan–Meier analysis and receiver operating characteristic curve analysis further demonstrated the significant predictive capability. Immune infiltration, Single Nucleotide Variants (SNV) mutations, and clinical drug susceptibility were analyzed. In conclusion, a risk model of 15 PANoptosis-related genes has significant value in prognostic prediction for LUAD and has potential to direct clinical therapeutic strategies during the treatment.