Preliminary Assessment of Viral Metagenome from Cancer Tissue and Blood from Patients with Lung Adenocarcinoma

2021 ◽  
Author(s):  
Hua‐Zhong Cai ◽  
Heteng Zhang ◽  
Jie Yang ◽  
Jian Zeng ◽  
Hao Wang
Keyword(s):  
Lung Adenocarcinoma ◽  
Cancer Tissue ◽  
Preliminary Assessment

Role of DACH1 on proliferation, invasion, and apoptosis in human lung adenocarcinoma cells

2021 ◽  
Vol 21 ◽  
Author(s):  
Junjie Yu ◽  
Ping Jiang ◽  
Ke Zhao ◽  
Zhiguo Chen ◽  
Tao Zuo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Tumor Cells ◽  
Human Lung ◽  
A549 Cells ◽  
Cancer Tissue ◽  
Lung Cancer Tissue ◽  
Adenocarcinoma Cells ◽  
Human Lung Adenocarcinoma Cells ◽  
Lung Adenocarcinoma Cells

Objective: To investigate DACH1 protein expression in lung cancer tissue and matched paracancerous tissue, and explore its effect on proliferation, invasion, and apoptosis in human lung adenocarcinoma cells (HLACs). Methods: Tumor tissue and matched paracancerous tissue was collected from 46 patients with pathologically diagnosed lung cancer. RT-PCR was perfomed to detect DACH1 mRNA expression and immunohistochemistry to measured DACH1 protein expression. To determine the effect of DACH1 on lung cancer behavior, small interfering RNA (siRNA) was used to silence DACH1 expression in A549 cells. The impact on the proliferation of tumor cells was then observed by MTT assay, changes in the invasion of tumor cells were identified using transwell chamber assay, and the effects on apoptosis in the cell line were detected using flow cytometry. Results: The expression of DACH1 mRNA and DACH1 protein were significantly decreased in lung cancer tissue versus matched paracancerous control tissue. Silencing of DACH1 expression in A549 cells significantly enhanced cell proliferation, significantly increased cell invasion and significantly reduced spontaneous apoptosis. Conclusion: DACH1 is downregulated in lung adenocarcinoma tissue. In vitro assessment shows that DACH1 functions as a tumor suppressor, suggesting its potential use as new target for lung cancer treatment.

scholarly journals Co-Expression of Coxsackievirus/Adenovirus Receptors and Desmoglein 2 in Lung Adenocarcinoma: A Comprehensive Analysis of Bioinformatics and Tissue Microarrays

2020 ◽  
Vol 9 (11) ◽  
pp. 3693
Author(s):  
Ching-Fu Weng ◽  
Chi-Jung Huang ◽  
Mei-Hsuan Wu ◽  
Henry Hsin-Chung Lee ◽  
Thai-Yen Ling
Keyword(s):  
Overall Survival ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Early Stage ◽  
The Cancer Genome Atlas ◽  
Cancer Tissue ◽  
Mesenchymal Transition ◽  
Kaplan Meier

Introduction: Coxsackievirus/adenovirus receptors (CARs) and desmoglein-2 (DSG2) are similar molecules to adenovirus-based vectors in the cell membrane. They have been found to be associated with lung epithelial cell tumorigenesis and can be useful markers in predicting survival outcome in lung adenocarcinoma (LUAD). Methods: A gene ontology enrichment analysis disclosed that DSG2 was highly correlated with CAR. Survival analysis was then performed on 262 samples from the Cancer Genome Atlas, forming “Stage 1A” or “Stage 1B”. We therefore analyzed a tissue microarray (TMA) comprised of 108 lung samples and an immunohistochemical assay. Computer counting software was used to calculate the H-score of the immune intensity. Cox regression and Kaplan–Meier analyses were used to determine the prognostic value. Results: CAR and DSG2 genes are highly co-expressed in early stage LUAD and associated with significantly poorer survival (p = 0.0046). TMA also showed that CAR/DSG2 expressions were altered in lung cancer tissue. CAR in the TMA was correlated with proliferation, apoptosis, and epithelial–mesenchymal transition (EMT), while DSG2 was associated with proliferation only. The Kaplan–Meier survival analysis revealed that CAR, DSG2, or a co-expression of CAR/DSG2 was associated with poorer overall survival. Conclusions: The co-expression of CAR/DSG2 predicted a worse overall survival in LUAD. CAR combined with DSG2 expression can predict prognosis.

MicroRNA-based assay for differential diagnosis of mesothelioma

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22079-e22079
Author(s):  
H. Benjamin ◽  
D. Lebanony ◽  
S. Tabak ◽  
N. Barabash ◽  
H. Gibori ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Lung Adenocarcinoma ◽  
Tissue Type ◽  
Cancer Tissue ◽  
Diagnostic Assay ◽  
Tissue Samples ◽  
Qrt Pcr ◽  
Primary Lung Adenocarcinoma ◽  
Small Set ◽  
Tumor Types

e22079 Background: Malignant mesothelioma is an aggressive pleural neoplasm, strongly linked to environmental exposures such as asbestos. Mesothelioma can be difficult to differentiate from other tumors in the lung or pleura such as primary lung adenocarcinoma presenting with pleural effusion or metastatic adenocarcinoma from extrathoracic sites. We addressed the increasing need for accurate differential diagnosis of these tumors by developing a diagnostic assay based on expression levels of microRNAs, a family of small, non-coding RNAs whose tissue-specificity has proven applicability for identification of cancer tissue type and histology. Methods: We developed protocols for extraction of high-quality RNA that retain the microRNA fraction from FFPE tissue samples. Microarrays were used for initial profiling. qRT-PCR was used to validate results and to develop a diagnostic assay. Results: We identified microRNAs that are differentially expressed between mesothelioma, lung adenocarcinoma, and other confounding tumor types. A diagnostic assay (miRview™ meso) was developed, that utilizes qRT-PCR measurement of a small set of microRNAs to differentiate between mesothelioma and non-mesothelioma samples. After establishing this profile in more than 30 mesotheliomas and 200 samples of confounding tumors, the microRNA biomarkers were measured using a standardized protocol on a blinded test set. The assay had accuracy greater than 90% in differentiating mesothelioma from other confounding tumor types. More than ¾ of samples were classified with high confidence, and these samples were all correctly identified. Conclusions: MicroRNAs are emerging as effective cancer biomarkers. A robust and simple assay based on the expression level of a few microRNA biomarkers can accurately differentiate mesothelioma from other possible tumors in the lung and pleura. This assay provides an important new tool for diagnosing mesothelioma. [Table: see text]

scholarly journals Prediction of best features in heterogeneous Lung adenocarcinoma samples using Least Absolute Shrinking and Selection Operator

2019 ◽  
Author(s):  
Ateeq Muhammed Khaliq ◽  
RG Sharathchandra ◽  
Meenakshi Rajamohan
Keyword(s):  
Lung Adenocarcinoma ◽  
Cancer Tissue ◽  
Consensus Clustering ◽  
Rna Seq ◽  
Multiple Cancer ◽  
Silhouette Width ◽  
Cancer Subtypes ◽  
Machine Learning Methods ◽  
Data Portal ◽  
Selection Operator

AbstractThis study aims to create a tumor heterogeneity-based model for predicting the best features of lung adenocarcinoma (LUAD) in multiple cancer subtypes using the Least Absolute Shrinking and Selection Operator (LASSO). The RNA-Seq raw count data of 533 LUAD samples and 59 normal samples were downloaded from the TCGA data portal. Based on consensus clustering method samples was divided into two subtypes, and clusters were validated using silhouette width. Furthermore, we estimated subtypes for the abundance of immune and non-immune stromal cell populations which infiltrated cancer tissue. We established the LASSO model for predicting each subtype’s best features. Enrichment pathway analysis was then carried out. Finally, the validity of the LASSO model for identifying features was established by the survival analysis. Our study suggests that the unsupervised clustering and Machine learning methods such as LASSO model-based feature selection can be effectively used to predict relevant genes which might play an essential role in cancer diagnosis.

scholarly journals Characteristics of Microbiome in Lung Adenocarcinoma Tissue from Patients in Southwestern China

2020 ◽  
Author(s):  
Sinuo Zhu ◽  
Yunping Zhao ◽  
Yanan Bao ◽  
Yue Cui ◽  
Xingming Zhu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Beta Diversity ◽  
Clinical Stage ◽  
Alpha Diversity ◽  
Southwestern China ◽  
Cancer Tissue ◽  
16S Rna ◽  
Significant Difference ◽  
Cancer Tissues

Abstract Background:Increasing evidences have unveiled the connection between microbiome and lung cancer. This study aims to identify the characteristics of microbial communities in the lung cancer tissues from patients in southwestern China, and to compare the distinct microbial genes at different clinical stages of lung cancer for uncovering potential immunotherapy targets.Methods:Forty samples of primary lung adenocarcinoma tissue were performed by 16S rRNA gene sequencing. The subjects were grouped according to TNM stages (T and N group), clinical stage and smoke status. To identify the taxa composition of each sample, Operational Taxonomic Units (OTUs) were classified on the Effective Tags with 97% identity. The linear discriminant analysis effect size (LEfSe) method was utilized to compare relative abundances of all bacterial taxa between non-metastasis group and metastasis group. The Shannon index of the 97% identity OTUs was calculated to evaluate alpha diversity. Beta diversity measurement was calculated using Principal Co-ordinates Analysis (PCoA).Results:A total of 951 OTUs were identified in the cancer tissues, including 224 overlapping genera. No significant difference has been found in the alpha diversity within all the groups. Beta diversity was significantly different in N group, T group and clinical stage group. By LEfSe analysis, nine differential species were identified in the N group, of which the relative abundance of genus Bifidobacterium was 10.78%±11.59% in the N0 group and 20.15%±13.44% in the N+ group (p<0.05). In the T1 and T2 group, the LEfSe result identified 4 phylum and 10 genera. The differential genera were Moraxella, Dolosigranulum, Corynebacteriaceae and Citrobacter in the T2 group and Bifidobacterium, Alistipes, Akkermansia, Blautia, Lactobacillus as well as Facelibacterium in the T1 group. Differential bacterial composition and abundance were also observed in the clinical stage group.Conclusions:In conclusion, by 16S RNA sequencing, we identified dominant species of lung cancer tissue in different groups of AD patients. Bifidobacterium plays important role both in lymph node metastasis and tumor progression, which could provide specific immunotherapy strategy for lung cancer.

scholarly journals Risk of lung adenocarcinoma from smoking and radiation arises in distinct molecular pathways

2019 ◽  
Vol 40 (10) ◽  
pp. 1240-1250 ◽  
Author(s):  
Noemi Castelletti ◽  
Jan Christian Kaiser ◽  
Cristoforo Simonetto ◽  
Kyoji Furukawa ◽  
Helmut Küchenhoff ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Radiation Exposure ◽  
Radiation Risk ◽  
Environmental Exposures ◽  
Driver Mutations ◽  
Cancer Tissue ◽  
Molecular Pathways ◽  
Data Set ◽  
Incidence Data ◽  
Atom Bomb

Abstract KRAS mutations of lung adenocarcinoma (LADC) are associated with smoking but little is known on other exposure-oncogene associations. Hypothesizing that different inciting agents may cause different driver mutations, we aimed to identify distinct molecular pathways to LADC, applying two entirely different approaches. First, we examined clinicopathologic features and genomic signatures of environmental exposures in the large LADC Campbell data set. Second, we designed a molecular mechanistic risk model of LADC (M3LADC) that links environmental exposure to incidence risk by mathematically emulating the disease process. This model was applied to incidence data of Japanese atom-bomb survivors which contains information on radiation and smoking exposure. Grouping the clinical data by driver mutations revealed two main distinct molecular pathways to LADC: one unique to transmembrane receptor-mutant patients that displayed robust signatures of radiation exposure and one shared between submembrane transducer-mutant patients and patients with no evident driver mutation that carried the signature of smoking. Consistently, best fit of the incidence data was achieved with a M3LADC with two pathways: in one LADC risk increased with radiation exposure and in the other with cigarette consumption. We conclude there are two main molecular pathways to LADC associated with different environmental exposures. Future molecular measurements in lung cancer tissue of atom-bomb survivors may allow to further test quantitatively the M3LADC-predicted link of radiation to transmembrane receptor mutations. Moreover, the developed molecular mechanistic model showed that for low doses, as relevant e.g. for medical imaging, smokers have the same radiation risk compared with never smokers.

scholarly journals The solid subtype, according to the IASLC/ATS/ERS classification of lung adenocarcinoma, as a predictive marker for PD-L1 expression

2021 ◽  
Author(s):  
Dachuan Zhang ◽  
Xie Gao ◽  
Yongqiang Shi ◽  
Zhantao Yan ◽  
Wenting He ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Predictive Marker ◽  
Tnm Stage ◽  
Smoking History ◽  
Cancer Tissue ◽  
Solid Structure ◽  
Acinar Structure ◽  
Papillary Structure ◽  
Significant Difference ◽  
Importance Factor

Abstract Background: PD-L1 expression in tumor cells can predict the efficacy of PD-1/PD-L1 inhibitors and prognosis in patients. However, the correlation between the PD-L1 expression and the novel lung adenocarcinoma classification are obscure. Methods: 126 lung adenocarcinoma cases were reviewed in the Third Affiliated Hospital of Soochow University from Jan. to Dec. 2019. PD-L1 (DAKO 22C3) was used to test the PD-L1 expression in lung cancer tissue. Result: TPS was used to interpret the PD-L1 expression. The negative, low positive and high positive of PD-L1 were 72 cases (57.14%), 39 cases (30.95%) and 15 cases (11.90%). PD-L1 TPS in solid structure was significantly higher than that in acinar structure, lepidic structure and papillary structure (P<0.001, respectively). The results of c2 test showed the PD-L1 expression had the significant difference with gender (P = 0.005), age (P = 0.030), smoking history (P = 0.024), lymph node metastasis (P <0.001), TNM stage (P = 0.001), acinar structure (P = 0.003) and solid structure (P < 0.001). Multi-factor linear regression results suggested that solid structure, TNM stage and smoking history were associated with PD-L1 expression (P < 0.05). The solid structure showed more capability to PD-L1 expression (β = 0.428). Conclusion: PD-L1 expression was heterogeneity in lung adenocarcinoma. The solid structure, TNM stage and smoking history were correlation to up-regulation of PD-L1 expression, and solid structure was the most importance factor.

Procedure for Maximizing Phonological Information from Single-Word Responses

1984 ◽  
Vol 15 (4) ◽  
pp. 267-274 ◽  
Author(s):  
Harriet B. Klein
Keyword(s):  
Phonological Information ◽  
Single Word ◽  
Preliminary Assessment ◽  
Target Attainment ◽  
Phonological Processes ◽  
Step Procedure ◽  
Yield Information ◽  
Assessment Measure ◽  
Busy Clinician ◽  
Planning Intervention

Formal articulation test responses are often used by the busy clinician as a basis for planning intervention goals. This article describes a 6-step procedure for using efficiently the single-word responses elicited with an articulation test. This procedure involves the assessment of all consonants within a word rather than only test-target consonants. Responses are organized within a Model and Replica chart to yield information about an individual's (a) articulation ability, (b) frequency of target attainment, substitutions, and deletions, (c) variability in production, and (d) phonological processes. This procedure is recommended as a preliminary assessment measure. It is advised that more detailed analysis of continuous speech be undertaken in conjunction with early treatment sessions.

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