Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer

NKX2‑1 copy number alterations are associated with oncogenic, immunological and prognostic remodeling in non‑small cell lung cancer

NK2 homeobox 1 (NKX2-1) copy number alterations (CNAs) are frequently observed in lung cancer. However, little is known about the complete landscape of focal alterations in NKX2-1 copy number (CN), their clinical significance and their therapeutic implications in non-small cell lung cancer (NSCLC). The correlations between NKX2-1 expression and EGFR driver mutations and programmed death ligand 1 (PD-L1) co-expression were studied using immunohistochemistry and PCR from the tumors of recruited Filipino patients (n=45). Clinical features of NSCLC with NKX2-1 CNAs were resolved at the tumor and clonal levels using the molecular profiles of patients with lung adenocarcinoma and lung squamous cell carcinoma from The Cancer Genome Atlas (n=1,130), and deconvoluted single-cell RNA-seq data from the Bivona project (n=1,654), respectively. Despite a significant and positive correlation between expression and CN (r=0.264; P<0.001), NKX2-1 CNAs exerted a stronger influence on the combined EGFR and PD-L1 status of NSCLC tumors than expression. NKX2-1 CN gain was prognostic of favorable survival (P=0.018) and a better response to targeted therapy. NKX2-1 CN loss predicted a worse survival (P=0.041). Mutational architecture in the Y-chromosome differentiated the two prognostic groups. There were 19,941 synonymous mutations and 1,408 genome-wide CN perturbations associated with NKX2-1 CNAs. Tumors with NKX2-1 CN gain expressed lymphocyte markers more heterogeneously than those with CN loss. Higher expression of tumor-infiltrating lymphocyte gene signatures in CN gain was prognostic of longer disease-free survival (P=0.005). Tumors with NKX2-1 CN gain had higher B-cell (P<0.001) and total T-cell estimates (P=0.003). NKX2-1 CN loss was associated with immunologically colder tumors due to higher M2 macrophage infiltrates (P=0.011) and higher expression of immune checkpoint proteins, CD274 (P=0.025), VTCN1 (P<0.001) and LGALS9 (P=0.002). In conclusion, NKX2-1 CNAs are associated with tumors that exhibit clinically diverse characteristics, and with unique oncogenic, immunological and prognostic signatures.

XL1R-Net: Explainable AI-driven improved L1-regularized deep neural architecture for NSCLC biomarker identification

BACKGROUND AND OBJECTIVE

Non-small cell lung cancer (NSCLC) exhibits intrinsic molecular heterogeneity, primarily driven by the mutation of specific biomarkers. Identification of these biomarkers would assist not only in distinguishing NSCLC into its major subtypes - Adenocarcinoma and Squamous Cell Carcinoma, but also in developing targeted therapy. Medical practitioners use one or more types of omic data to identify these biomarkers, copy number variation (CNV) being one such type. CNV provides a measure of genomic instability, which is considered a hallmark of carcinoma. However, the CNV data has not received much attention for biomarker identification. This paper aims to identify biomarkers for NSCLC using CNV data.

METHODS

An eXplainable AI (XAI)-driven L1-regularized deep learning architecture, XL1R-Net, is proposed that introduces a novel modification of the standard L1-regularized gradient descent algorithm to arrive at an improved deep neural classifier for NSCLC subtyping. Further, XAI-based feature identification has been used to leverage the trained classifier to uncover a set of twenty NCSLC-relevant biomarkers.

RESULTS

The identified biomarkers are evaluated based on their classification performance and clinical relevance. Using Multilayer Perceptron (MLP)-based model, a classification accuracy of 84.95% using 10-fold cross-validation is achieved. Moreover, the statistical significance test on the classification performance also revealed the superiority of the MLP model over the competitive machine learning models. Further, the publicly available Drug-Gene Interaction Database reveals twelve of the identified biomarkers as potentially druggable. The K-M Plotter tool was used to verify eighteen of the identified biomarkers with a high probability of predicting NSCLC patients' likelihood of survival. While nine of the identified biomarkers confirm the recent literature, five find mention in the OncoKB Gene List.

CONCLUSION

A set of seven novel biomarkers that have not been reported in the literature could be investigated for their potential contribution towards NSCLC therapy. Given NSCLC's genetic diversity, using only one omics data type may not adequately capture the tumor's complexity. Multiomics data and its integration with other sources will be examined in the future to better understand NSCLC heterogeneity.

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning

BACKGROUND AND OBJECTIVE

The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers responsible for the heterogeneity aid in distinguishing NSCLC into its prominent subtypes-adenocarcinoma and squamous cell carcinoma. Moreover, if identified, these biomarkers could pave the path to targeted therapy. Through this work, a novel explainable AI (XAI)-guided deep learning framework is proposed that assists in discovering a set of significant NSCLC-relevant biomarkers using methylation data.

METHODS

The proposed framework is divided into two blocks- the first block combines an autoencoder and a neural network to classify NSCLC instances. The second block utilizes various eXplainable AI (XAI) methods, namely IntegratedGradients, GradientSHAP, and DeepLIFT, to discover a set of seven significant biomarkers.

RESULTS

The classification performance of the biomarkers discovered using the proposed framework is evaluated by employing multiple machine learning algorithms, among which the Multilayer Perceptron (MLP) algorithm-based model outperforms others, yielding a 10-fold cross-validation accuracy of 91.53%. An improved accuracy of 96.37% is achieved by integrating RNA-Seq, CNV, and methylation data. On performing statistical analysis using the Friedman and Nemenyi tests, the MLP model is found to be significantly better than other machine learning-based models. Further, the clinical efficacy of the resultant biomarkers is established based on their potential druggability, the likelihood of predicting NSCLC patients' survival, gene-disease association, and biological pathways targeted by them. While the biomarkers C18orf18, CCNT2, THOP1, and TNPO2, are found potentially druggable, the biomarkers CCDC15, SNORA9, THOP1, and TNPO2 are found prognostically relevant. On further analysis, some of the discovered biomarkers are found to be associated with around 104 diseases. Moreover, five KEGG, ten Reactome, and three Wiki pathways are found to be triggered by the biomarkers discovered.

CONCLUSION

In summary, the proposed framework uncovers a set of clinically effective biomarkers that accurately classify NSCLC. As a future course of work, efforts would be made to combine a variety of omics data with histopathological data to unveil more precise biomarkers for devising personalized therapy.

Assessment of MYC and TERT copy number variations in lung cancer using digital PCR

OBJECTIVE

Lung cancer is the second most frequent cancer type and the most common cause of cancer-related deaths worldwide. Alteration of gene copy numbers are associated with lung cancer and the determination of copy number variations (CNV) is appropriate for the discrimination between tumor and non-tumor tissue in lung cancer. As telomerase reverse transcriptase (TERT) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) play a role in lung cancer the aims of this study were the verification of our recent results analyzing MYC CNV in tumor and non-tumor tissue of lung cancer patients using an independent study group and the assessment of TERT CNV as an additional marker.

RESULTS

TERT and MYC status was analyzed using digital PCR (dPCR) in tumor and adjacent non-tumor tissue samples of 114 lung cancer patients. The difference between tumor and non-tumor samples were statistically significant (p < 0.0001) for TERT and MYC. Using a predefined specificity of 99% a sensitivity of 41% and 51% was observed for TERT and MYC, respectively. For the combination of TERT and MYC the overall sensitivity increased to 60% at 99% specificity. We demonstrated that a combination of markers increases the performance in comparison to individual markers. Additionally, the determination of CNV using dPCR might be an appropriate tool in precision medicine.

Genomic analysis and clinical correlations of non-small cell lung cancer brain metastasis

Up to 50% of patients with non-small cell lung cancer (NSCLC) develop brain metastasis (BM), yet the study of BM genomics has been limited by tissue access, incomplete clinical data, and a lack of comparison with paired extracranial specimens. Here we report a cohort of 233 patients with resected and sequenced (MSK-IMPACT) NSCLC BM and comprehensive clinical data. With matched samples (47 primary tumor, 42 extracranial metastatic), we show CDKN2A/B deletions and cell cycle pathway alterations to be enriched in the BM samples. Meaningful clinico-genomic correlations are noted, namely EGFR alterations in leptomeningeal disease (LMD) and MYC amplifications in multifocal regional brain progression. Patients who developed early LMD frequently have had uncommon, multiple, and persistently detectable EGFR driver mutations. The distinct mutational patterns identified in BM specimens compared to other tissue sites suggest specific biologic underpinnings of intracranial progression.

Intratumoral Microbiota-Host Interactions Shape the Variability of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma in Recurrence and Metastasis

Differences in tissue microbiota-host interaction between lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) about recurrence and metastasis have not been well studied. In this study, we performed bioinformatics analyses to identify the genes and tissue microbes significantly associated with recurrence or metastasis. All lung cancer patients were divided into the recurrence or metastasis (RM) group and the nonrecurrence and nonmetastasis (non-RM) group according to whether or not they had recurred or metastasized within 3 years after the initial surgery. Results showed that there were significant differences between LUAD and LUSC in gene expression and microbial abundance associated with recurrence and metastasis. Compared with non-RM, the bacterial community of RM had a lower richness in LUSC. In LUSC, host genes significantly correlated with tissue microbe, whereas host-tissue microbe interaction in LUAD was rare. Then, we established a novel multimodal machine learning model based on genes and microbes to predict the recurrence and metastasis risk of a LUSC patient, which achieves an area under the curve (AUC) of 0.81. In addition, the predicted risk score was significantly associated with the patient's survival. IMPORTANCE Our study elucidates significant differences in RM-associated host-microbe interactions between LUAD and LUSC. Besides, the microbes in tumor tissue could be used to predict the RM risk of LUSC, and the predicted risk score is associated with patients' survival.

The Mechanism of Nemo-Like Kinase (NLK) in Non-Small Cell Lung Cancer (NSCLC) Cells by Regulating Vascular Endothelial Growth Factor (VEGF)

Nemo-like kinase (NLK) is abnormally expressed in several tumors, but its role in NSCLC have not been reported. Real time PCR and Western blot were used to assess NLK level in tumor tissues and adjacent tissues of NSCLC. NSCLC cell line A549 cells were divided into three groups; NC group and si-NLK group which was transfected with NLK negative control or NLK siRNA respectively followed by analysis of NLK expression by real time PCR and Western blot, cell proliferation by MTT assay, cell migration by cell wound healing assay, cell invasion by transwell chamber and MMP-9 and VEGF expression by Western blot. The expression of NLK in NSCLC tumor tissue was increased, and the difference was statistically significant compared with adjacent tissues (P <0.05), and it was related to tumor size, degree of differentiation, metastasis and survival time (P <0.05). A549 cells showed significantly increased NLK. Transfection of NLK siRNA could significantly inhibit tumor cell proliferation, migration and invasion, and decrease the expression of MMP-9 and VEGF proteins (P <0.05). Elevated NLK level in NSCLC tumor tissues is related to clinicopathological characteristics. Decreased the expression of NLK can inhibit VEGF and MMP-9 expression, and inhibit cell function.

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.

SIGNIFICANCE

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis

Differentiation between the various non-small-cell lung cancer subtypes is crucial for providing an effective treatment to the patient. For this purpose, machine learning techniques have been used in recent years over the available biological data from patients. However, in most cases this problem has been treated using a single-modality approach, not exploring the potential of the multi-scale and multi-omic nature of cancer data for the classification. In this work, we study the fusion of five multi-scale and multi-omic modalities (RNA-Seq, miRNA-Seq, whole-slide imaging, copy number variation, and DNA methylation) by using a late fusion strategy and machine learning techniques. We train an independent machine learning model for each modality and we explore the interactions and gains that can be obtained by fusing their outputs in an increasing manner, by using a novel optimization approach to compute the parameters of the late fusion. The final classification model, using all modalities, obtains an F1 score of 96.81±1.07, an AUC of 0.993±0.004, and an AUPRC of 0.980±0.016, improving those results that each independent model obtains and those presented in the literature for this problem. These obtained results show that leveraging the multi-scale and multi-omic nature of cancer data can enhance the performance of single-modality clinical decision support systems in personalized medicine, consequently improving the diagnosis of the patient.

High expression of HOXB3 predicts poor prognosis and correlates with tumor immunity in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most prevalent human cancers worldwide. The homeobox-B (HOXB) gene cluster has been reported to contribute to cancer development. Nevertheless, the expression status, clinical significance and biological role of HOXB genes in LUAD remain largely unclear.

METHODS AND RESULTS

This study comprehensively investigated the transcriptional levels and prognostic values of the HOXB genes in LUAD based on The Cancer Genome Atlas (TCGA) database. Flow cytometry, CCK-8, and Transwell assays were used for detecting apoptosis, proliferation, and migration, respectively. We discovered that eight members of the HOXB cluster genes (HOXB2, HOXB3, HOXB4, HOXB6, HOXB7, HOXB8, HOXB9, and HOXB13) were dysregulated in LUAD tumor tissues. Increased expression of HOXB3, HOXB6, HOXB7, HOXB8, or HOXB9 was independently associated with unsatisfactory overall survival (OS) in LUAD patients. In addition, a high level of HOXB3 also predicted poor patient relapse-free survival (RFS), suggesting that HOXB3 may play a vital role in the progression of LUAD compared to other members of the HOXB cluster. Additionally, further analysis by TIMER and TISIDB algorithms revealed that HOXB3 was positively correlated with a panel of immune checkpoint molecules (ICMs), tumor-infiltrating lymphocytes (TILs), and tumor immune regulators (TIRs). Gene enrichment analysis based on KEGG showed that HOXB3 was closely associated with multiple tumor-related biological processes and signaling pathways. Functionally, the in vitro experiments revealed that depletion of HOXB3 significantly alleviated the resistance of LUAD cells to apoptosis, and suppressed cell proliferation and migration.

CONCLUSION

Our study suggests that HOXB3 may play an oncogenic role in LUAD and correlate with tumor immunity.

Molecular charcterization of lung adenocarcinoma combining whole exome sequencing, copy number analysis and gene expression profiling

INTRODUCTION

Lung cancer is the leading cause of cancer mortality worldwide; lung adenocarcinoma (LUAD) corresponds to about 40% of lung cancers. LUAD is a genetically heterogeneous disease and the definition of this heterogeneity is of fundamental importance for prognosis and treatment.

AREAS COVERED

Based on primary literature, this review provides an updated analysis of multiomics studies based on the study of mutation profiling, copy number alterations and gene expression allowing for definition of molecular subgroups, prognostic factors based on molecular biomarkers, and identification of therapeutic targets. The authors sum up by providing the reader with their expert opinion on the potentialities of multiomics analysis of LUADs.

EXPERT OPINION

A detailed and comprehensive study of the co-occurring genetic abnormalities characterizing different LUAD subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of LUADs may provide a fundamental contribution to improve the survival of LUAD patients.

3D-PulCNN: Pulmonary cancer classification from hyperspectral images using convolution combination unit based CNN

Pulmonary cancer is one of the most common malignancies worldwide. Accurate classification of its subtypes is required in differential diagnosis. However, existing algorithms are mostly based on color images, and the improvement of accuracy is quite challenging. In this study, we propose a convolution combination unit (CCU)-based three-dimensional convolutional neural network (3D-PulCNN) for classifying pulmonary cancer presented in microscopic hyperspectral image with both spatial and spectral information. CCU is designed to fuse the features acquired by different convolution scales. Compared with VGGNet, only two fully connected layers are used in this model, reducing the network parameters and model complexity. Experimental results show that 3D-PulCNN achieves overall average (OA) of 0.962 and Precision, Recall, and Kappa of more than 0.920, superior to 2D-VGGNet. Then, 3D-UNet is leveraged to segment cancer cells, and their morphological characteristics are calculated to supply quantitative virtual analysis data for classification results explanation and prognosis assessment.

MicroRNA-140-3p represses the proliferation, migration, invasion and angiogenesis of lung adenocarcinoma cells via targeting TYMS (thymidylate synthetase)

MicroRNA (miR)-140-3p has been proved to repress lung adenocarcinoma (LUAD), and our study aims to further evaluate the mechanism. Bioinformatic analyses were performed. The viability, proliferation, migration, invasion and angiogenesis of transfected LUAD cells were all determined via Cell Counting Kit-8, colony formation, Scratch, Transwell, and tube formation assays. The targeting relationship between miR-140-3p and thymidylate synthetase (TYMS) was confirmed by dual-luciferase reporter assay. Relative expressions of miR-140-3p, TYMS, epithelial-to-mesenchymal transition- (E-cadherin, N-cadherin, vimentin), angiogenesis- (vascular endothelial growth factor (VEGF)), and apoptosis-related factors (cleaved caspase-3, B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax)) were quantified by quantitative real-time polymerase chain reaction or Western blot. TYMS was high-expressed yet miR-140-3p was low-expressed in LUAD cells. Upregulation of miR-140-3p inhibited TYMS expression, viability, colony formation, migration, invasion, and tube length within LUAD cells, while downregulation of miR-140-3p did oppositely. Silenced TYMS, the downstream target gene of miR-140-3p, reversed the effects of miR-140-3p downregulation on TYMS expression, cell viability, colony formation, migration, invasion, and tube length as well as the metastasis-, apoptosis- and angiogenesis-related proteins in LUAD cells. Upregulation of miR-140-3p inhibited the proliferation, migration, invasion and angiogenesis of LUAD cells via targeting TYMS.

Low-Coverage Whole Genome Sequencing of Cell-Free DNA From Immunosuppressed Cancer Patients Enables Tumor Fraction Determination and Reveals Relevant Copy Number Alterations

Cell-free DNA (cfDNA) analysis is a minimally invasive method that can be used to detect genomic abnormalities by directly testing a blood sample. This method is particularly useful for immunosuppressed patients, who are at high risk of complications from tissue biopsy. The cfDNA tumor fraction (TF) varies greatly across cancer type and between patients. Thus, the detection of molecular alterations is highly dependent on the circulating TF. In our study, we aimed to calculate the TF and characterize the copy number aberration (CNA) profile of cfDNA from patients with rare malignancies occurring in immunosuppressed environments or immune-privileged sites. To accomplish this, we recruited 36 patients: 19 patients with non-Hodgkin lymphoma (NHL) who were either human immunodeficiency virus (HIV)-positive or organ transplant recipients, 5 HIV-positive lung cancer patients, and 12 patients with glioma. cfDNA was extracted from the patients' plasma and sequenced using low-coverage whole genome sequencing (LC-WGS). The cfDNA TF was then calculated using the ichorCNA bioinformatic algorithm, based on the CNA profile. In parallel, we performed whole exome sequencing of patient tumor tissue and cfDNA samples with detectable TFs. We detected a cfDNA TF in 29% of immune-suppressed patients (one patient with lung cancer and six with systemic NHL), with a TF range from 8 to 70%. In these patients, the events detected in the CNA profile of cfDNA are well-known events associated with NHL and lung cancer. Moreover, cfDNA CNA profile correlated with the CNA profile of matched tumor tissue. No tumor-derived cfDNA was detected in the glioma patients. Our study shows that tumor genetic content is detectable in cfDNA from immunosuppressed patients with advanced NHL or lung cancer. LC-WGS is a time- and cost-effective method that can help select an appropriate strategy for performing extensive molecular analysis of cfDNA. This technique also enables characterization of CNAs in cfDNA when sufficient tumor content is available. Hence, this approach can be used to collect useful molecular information that is relevant to patient care.

The Effect of Smoking on the Immune Microenvironment and Immunogenicity and Its Relationship With the Prognosis of Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer

Background: The emergence of immune checkpoint inhibitors (ICIs) has opened a new chapter for the treatment of non-small cell lung cancer (NSCLC), and the best beneficiaries of ICI treatment are still being explored. Smoking status has been repeatedly confirmed to affect the efficacy of ICIs in NSCLC patients, but the specific mechanism is still unclear.

Methods: We performed analysis on the Memorial Sloan Kettering Cancer Center (MSKCC) clinical NSCLC cohort receiving ICI treatment, The Cancer Genome Atlas (TCGA) Pan-Lung Cancer cohort, and Gene Expression Omnibus (GEO) database GSE41271 lung cancer cohort that did not receive ICI treatment, including survival prognosis, gene mutation, copy number variation, immunogenicity, and immune microenvironment, and explored the impact of smoking status on the prognosis of NSCLC patients treated with ICIs and possible mechanism. In addition, 8 fresh NSCLC surgical tissue samples were collected for mass cytometry (CyTOF) experiments to further characterize the immune characteristics and verify the mechanism.

Result: Through the analysis of the clinical data of the NSCLC cohort treated with ICIs in MSKCC, it was found that the smokers in NSCLC receiving ICI treatment had a longer progression-free survival (HR: 0.69, 95% CI: 0.49–0.97, p = 0.031) than those who never smoked. Further analysis of the TCGA and GEO validation cohorts found that the differences in prognosis between different groups may be related to the smoking group’s higher immunogenicity, higher gene mutations, and stronger immune microenvironment. The results of the CyTOF experiment further found that the immune microenvironment of smoking group was characterized by higher expression of immune positive regulatory chemokine, and higher abundance of immune activated cells, including follicular helper CD4⁺ T cells, gamma delta CD4⁺ T cells, activated DC, and activated CD8⁺ T cells. In contrast, the immune microenvironment of non-smoking group was significantly enriched for immunosuppressive related cells, including regulatory T cells and M2 macrophages. Finally, we also found highly enriched CD45RA^highCD4⁺ T cells and CD45RA^highCD8⁺ T cells in the non-smoking group.

Conclusion: Our research results suggest that among NSCLC patients receiving ICI treatment, the stronger immunogenicity and activated immune microenvironment of the smoking group make their prognosis better.

ER expression associates with poor prognosis in male lung squamous carcinoma after radical resection

Background

Clinical options for lung squamous carcinoma (LUSC) are still quite limited. Carcinogenesis is an exceedingly complicated process involving multi-level dysregulations. Therefore, only looking into one layer of genomic dysregulation is far from sufficient.

Methods

We identified differentially expressed genes with consistent upstream genetic or epigenetic dysregulations in LUSC. Random walk was adopted to identify genes significantly affected by upstream abnormalities. Expression differentiation and survival analysis were conducted for these significant genes, respectively. Prognostic power of selected gene was also tested in 102 male LUSC samples through immunohistochemistry assay.

Results

Twelve genes were successfully retrieved from biological network, including ERα (ESRS1), EGFR, AR, ATXN1, MAPK3, PRKACA, PRKCA, SMAD4, TP53, TRAF2, UBQLN4 and YWHAG, which were closely related to sex hormone signaling pathway. Survival analysis in public datasets indicated ERα was significantly associated with a poor overall survival (OS) in male LUSC. The result of our immunohistochemistry assay also demonstrated this correlation using R0 resected tumors (n = 102, HR: 2.152, 95% CI: 1.089–4.255, p = 0.024). Although disease-free survival (DFS) difference was non-significant (n = 102, p = 0.12), the tendency of distinction was straight-forward. Cox analysis indicated ERα was the only independent prognostic factor for male patients’ OS after R0 resection (HR = 2.152, p = 0.037).

Conclusion

ERα was significantly related to a poor prognosis in LUSC, especially for male patients after radical surgery, confirmed by our immunohistochemistry data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08777-6.

Linc8087 predicts favorable prognosis and inhibits cell migration and invasion in NSCLC

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most common cancer and has poor prognosis. Long non-coding RNA(LncRNA) plays important roles in the regulation of cell migration in various types of cancer. In this study, we aimed to demonstrate the function of linc8087 in regulating cell migration and invasion in NSCLC cells.

METHODS

A lncRNA microarray was used to identify differentially expressed lncRNAs between NSCLC tissues and normal tissues. RT-qPCR was used to confirm the expression of linc8087 in tumor tissues. The association between linc8087 expression and clinicopathological characteristics was analyzed. RNA fluorescence in situ hybridization (FISH) was performed to observe the subcellular localization of linc8087. We investigated the effects of linc8087 expression on cell migration and invasion by wound healing assay, Transwell and invasion assays. The Human Tumor Metastasis RT² Profiler PCR Array was used to detect and analyze the mRNA levels of 84 genes involved in metastasis.

RESULTS

We found that linc8087 expression was obviously decreased in both NSCLC tissues and cell lines compared with paired normal tissues and a normal bronchial epithelium cell line. Low expression of linc8087 was significantly associated with poor survival. In addition, linc8087 was an independent risk factor for survival. Overexpressed linc8087 inhibited cell migration and invasion in A549 and PC9 cell lines. Knockdown of linc8087 promoted cell migration and invasion. The result of RT² Profiler PCR Array showed that overexpressed linc8087 upregulated the expression of the COL4A2, CST7 and FAT1 genes and led to the downregulation of SERPINE1.

CONCLUSIONS

These results indicate that linc8087 plays a key role in the progression of NSCLC, and it may serve as a meaningful prognostic biomarker as well as a latent therapeutic target in NSCLC patients.

Downregulation of m6A Reader YTHDC2 Promotes the Proliferation and Migration of Malignant Lung Cells via CYLD/NF-κB Pathway

Lung cancer is one of the most common types of carcinoma worldwide. Cigarette smoking is considered the leading cause of lung cancer. Aberrant expression of several YT521-B homology (YTH) family proteins has been reported to be closely associated with multiple cancer types. The present study aims to evaluate the function and regulatory mechanisms of the N6-methyladenosine (m6A) reader protein YTH domain containing 2 (YTHDC2) by in vitro, in vivo and bioinformatics analyses. The results revealed that YTHDC2 was reduced in lung cancer and cigarette smoke-exposed cells. Notably, bioinformatics and tissue arrays analysis demonstrated that decreased YTHDC2 was highly associated with smoking history, pathological stage, invasion depth, lymph node metastasis and poor outcomes. The in vivo and in vitro studies revealed that YTHDC2 overexpression inhibited the proliferation and migration of lung cancer cells as well as tumor growth in nude mice. Furthermore, YTHDC2 decreased expression was modulated by copy number deletion in lung cancer. Importantly, the cylindromatosis (CYLD)/NF-κB pathways were confirmed as the downstream signaling of YTHDC2, and this axis was mediated by m6A modification. The present results indicated that smoking-related downregulation of YTHDC2 was associated with enhanced proliferation and migration in lung cancer cells, and appeared to be regulated by DNA copy number variation. Importantly, YTHDC2 functions as a tumor suppressor through the CYLD/NF-κB signaling pathway, which is mediated by m6A modification.

Down-Regulation of TMPO-AS1 Induces Apoptosis in Lung Carcinoma Cells by Regulating miR-143-3p/CDK1 Axis

Evidence has shown that long non-coding RNAs (lncRNA) play pivotal roles in cancer promotion as well as suppression. But the molecular mechanism of lncRNA TMPO antisense transcript 1 (TMPO-AS1) in lung cancer (LC) remains unclear. This study mainly investigated the effect of TMPO-AS1 in LC treatment. TMPO-AS1 was tested by Kaplan-Meier method. Quantitative real time polymerase chain reaction (qRT-PCR) was employed to assess the expressions of TMPO-AS1, miR-143-3p, and CDK1 respectively in LC tissues and cell lines. TMPO-AS1, miR-143-3p and CDK1 expressions in LC cells were regulated through cell transfection, followed by MTT for cell viability detection. Besides, dual-luciferase reporter assays were performed to verify the interrelated microRNA of TMPO-AS1 and the target of miR-143-3p. Western blot experiments were used to examine the expressions of apoptosis-related proteins, and flow cytometry tested the cell apoptosis in treated cells. TMPO-AS1 and CDK1 were overexpressed in LC tissues and cells, while miR-143-3p level was suppressed. The decrease of TMPO-AS1 led to the increase of miR-143-3p, which further resulted in the reduction of CDK1. Down-regulating TMPO-AS1 reduced LC cell viability, motivated cell apoptosis, as well as promoted the expressions of Bcl and CCND1 and restrained Caspase-3 level, but all these consequences were abrogated by miR-143-3p inhibitor. Simultaneously, siCDK1 could reverse the anti-apoptosis and pro-activity functions of miR-143-3p inhibitor in LC cells. Down-regulation of TMPO-AS1 has the effects of pro-apoptosis in LC by manipulating miR-143-3p/CDK1, which is hopeful to be a novel therapy for LC patients.

Circular RNA hsa_circ_0008003 facilitates tumorigenesis and development of non-small cell lung carcinoma via modulating miR-488/ZNF281 axis

As one of the most aggressive malignancies, non‐small cell lung carcinoma (NSCLC) has high risks of death. It has been demonstrated that circRNAs accelerate NSCLC progression, but the underlying molecular mechanisms of circRNAs in NSCLC were still obscure. In the first place, the circRNA microarray of NSCLC was investigated in this study, and hsa_circ_0008003 (circ‐0008003) was chosen as the research object. Then, it was unveiled that the expression of circ‐0008003 examined via qRT‐PCR was elevated in tumour tissues relative to the non‐tumour tissues, which was associated with TNM stage and lymphatic metastasis in NSCLC. Additionally, the prognosis of NSCLC patients with high circ‐0008003 level was poor. Besides, circ‐0008003 silencing dampened the invasion and proliferation of NSCLC cells. Next, according to the mechanistic studies, circ‐0008003 functioned as a ceRNA of ZNF281 in NSCLC by acting as the endogenous sponge for miR‐488, which was proved to be a tumour suppressor in NSCLC. Additionally, ZNF281 overexpression and miR‐488 suppression recovered the influences of repressed circ‐0008003 on NSCLC cellular processes. It was validated in this research that circ‐0008003 triggered tumour formation in NSCLC, which was adjusted via miR‐488/ZNF281 axis, casting a novel light on the resultful target for treating NSCLC and predicting the prognosis.

Difference of copy number variation in blood of patients with lung cancer

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. Copy number variation (CNV) in several genetic regions correlate with cancer susceptibility. Hence, this study evaluated the association between CNV and non-small cell lung cancer (NSCLC) in the peripheral blood.

METHODS

Blood samples of 150 patients with NSCLC and 150 normal controls were obtained from a bioresource center (Seoul, Korea). Through an epigenome-wide analysis using the MethylationEPIC BeadChip method, we extracted CNVs by using an SVS8 software-supplied multivariate method. We compared CNV frequencies between the NSCLC and controls, and then performed stratification analyses according to smoking status.

RESULTS

We acquired 979 CNVs, with 582 and 967 copy-number gains and losses, respectively. We identified five nominally significant associations (ACOT1, NAA60, GSDMD, HLA-DPA1, and SLC35B3 genes). Among the current smokers, the NSCLC group had more CNV losses and gains at the GSDMD gene in chromosome 8 (P=0.02) and at the ACOT1 gene in chromosome 14 (P=0.03) than the control group. It also had more CNV losses at the NAA60 gene in chromosome 16 (P=0.03) among non-smokers. In the NSCLC group, current smokers had more CNV gains and losses at the ACOT1 gene in chromosome 14 (P=0.003) and at HLA-DPA1 gene in chromosome 6 (P=0.02), respectively, than non-smokers.

CONCLUSION

Five nominally significant associations were found between the NSCLC and CNVs. CNVs are associated with the mechanism of lung cancer development. However, the role of CNVs in lung cancer development needs further investigation.

Circular RNA 0001313 Knockdown Suppresses Non-Small Cell Lung Cancer Cell Proliferation and Invasion via the microRNA-452/HMGB3/ERK/MAPK Axis

Background

Non-small cell lung cancer (NSCLC) seriously endangers human health. Circular RNAs (circRNAs) regulate diverse types of cancers, including NSCLC. This study investigated the possible mechanism of circ0001313 in NSCLC.

Materials and Methods

Circ0001313 expression in NSCLC tissues was measured, and its correlation with clinicopathological features was analyzed. The binding relationships among circ0001313, microRNA (miR)-452 and HMGB3 were tested. The gain and loss of functions were performed to examine NSCLC cell malignant behaviors. After HMGB3 overexpression, ERK/MAPK pathway-related protein levels were detected. Subsequently, the rescue experiment was further performed using an ERK/MAPK pathway inhibitor PD98059.

Results

Abnormally elevated circ0001313 and decreased miR-452 in NSCLC cells were observed. Circ0001313 silencing or miR-452 overexpression significantly reduced NSCLC cell proliferation and invasion. Circ0001313 competitively bound to miR-452 to upregulate HMGB3, thus promoting NSCLC cell growth. HMGB3 overexpression activated the ERK/MAPK pathway to contribute to NSCLC development.

Conclusion

We highlighted that silencing of circ0001313 blunted the ERK/MAPK pathway via the miR-452/HMGB3 axis, thereby inhibiting NSCLC cell proliferation and invasion.

Deciphering the clonal relationship between glandular and squamous components in adenosquamous carcinoma of the lung using whole exome sequencing

Adenosquamous carcinoma of the lung (ASC) is a rare subtype of non-small cell lung cancer, consisting of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) components. ASC shows morphological characteristics of classic LUAD and LUSC but behaves more aggressively. Although ASC can serve as a model of lung cancer heterogeneity and transdifferentiation, its genomic background remains poorly understood. In this study, we sought to explore the genomic landscape of macrodissected LUAD and LUSC components of three ASC using whole exome sequencing (WES). Identified truncal mutations included the pan-cancer tumor-suppressor gene TP53 but also EGFR, BRAF, and MET, which are characteristic for LUAD but uncommon in LUSC. No truncal mutation of classical LUSC driver mutations were found. Both components showed unique driver mutations that did not overlap between the three ASC. Mutational signatures of truncal mutations differed from those of the branch mutations in their descendants LUAD and LUSC. Most common signatures were related to aging (1, 5) and smoking (4). Truncal chromosomal copy number aberrations shared by all three ASC included losses of 3p, 15q and 19p, and an amplified region in 5p. Furthermore, we detected loss of STK11 and SOX2 amplification in ASC, which has previously been shown to drive transdifferentiation from LUAD to LUSC in preclinical mouse models. Conclusively, this is the first study using WES to elucidate the clonal evolution of ASC. It provides strong evidence that the LUAD and LUSC components of ASC share a common origin and that the LUAD component appears to transform to LUSC.

Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis

Background

Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis.

Results

Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C (GYPC), NME/NM23 nucleoside diphosphate kinase 1 (NME1) and slit guidance ligand 2 (SLIT2), were found to be significantly correlated with LUAD patients’ smoking history. The expression levels of GYPC, NME1 and SLIT2 in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of NME1 was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of GYPC and SLIT2, as well as decreased expression of NME1 were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation.

Conclusion

In conclusion, our observations indicated that the differential expression of GYPC, NME1 and SLIT2 may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients.

An accurate and powerful method for copy number variation detection

MOTIVATION

Integration of multiple genetic sources for copy number variation detection (CNV) is a powerful approach to improve the identification of variants associated with complex traits. Although it has been shown that the widely used change point based methods can increase statistical power to identify variants, it remains challenging to effectively detect CNVs with weak signals due to the noisy nature of genotyping intensity data. We previously developed modSaRa, a normal mean-based model on a screening and ranking algorithm for copy number variation identification which presented desirable sensitivity with high computational efficiency. To boost statistical power for the identification of variants, here we present a novel improvement that integrates the relative allelic intensity with external information from empirical statistics with modeling, which we called modSaRa2.

RESULTS

Simulation studies illustrated that modSaRa2 markedly improved both sensitivity and specificity over existing methods for analyzing array-based data. The improvement in weak CNV signal detection is the most substantial, while it also simultaneously improves stability when CNV size varies. The application of the new method to a whole genome melanoma dataset identified novel candidate melanoma risk associated deletions on chromosome bands 1p22.2 and duplications on 6p22, 6q25 and 19p13 regions, which may facilitate the understanding of the possible roles of germline copy number variants in the etiology of melanoma.

AVAILABILITY AND IMPLEMENTATION

http://c2s2.yale.edu/software/modSaRa2 or https://github.com/FeifeiXiaoUSC/modSaRa2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

TMEM16A-inhibitor loaded pH-responsive nanoparticles: A novel dual-targeting antitumor therapy for lung adenocarcinoma

To overcome the adverse effects of conventional chemotherapy for cancers, various nanoparticles based drug delivery systems have been developed. However, nanoparticles delivering drugs directly to kill tumor cells still faced with challenges, because tumors possessed adopt complex mechanism to resist damages, which compromised the therapeutic efficacy. TMEM16A/CaCCs (Calcium activates chloride channels) has been identified to be overexpressed in lung adenocarcinoma which can serve as a novel tumor specific drug target in our previous work. Here, we developed a novel dual-targeted antitumor strategy via designing a novel nano-assembled, pH-sensitive drug-delivery system loading with specific inhibitors of TMEM16A against lung adenocarcinoma. For validation, we assayed the novel dual-targeting therapy on xenograft mouse model which exhibited significant antitumor activity and not affect mouse body weight. The dual targeting therapy accomplished in this study will shed light on the development of advanced antitumor strategy.

Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

Background

Accurate lung cancer classification is crucial to guide therapeutic decisions. However, histological subtyping by pathologists requires tumor tissue—a necessity that is often intrinsically associated with procedural difficulties. The analysis of circulating tumor DNA present in minimal-invasive blood samples, referred to as liquid biopsies, could therefore emerge as an attractive alternative.

Methods

Concerning adenocarcinoma, squamous cell carcinoma, and small cell carcinoma, our proof of concept study investigates the potential of liquid biopsy-derived copy number alterations, derived from single-end shallow whole-genome sequencing (coverage 0.1–0.5×), across 51 advanced stage lung cancer patients.

Results

Genomic abnormality testing reveals anomalies in 86.3% of the liquid biopsies (16/20 for adenocarcinoma, 13/16 for squamous cell, and 15/15 for small cell carcinoma). We demonstrate that copy number profiles from formalin-fixed paraffin-embedded tumor biopsies are well represented by their liquid equivalent. This is especially valid within the small cell carcinoma group, where paired profiles have an average Pearson correlation of 0.86 (95% CI 0.79–0.93). A predictive model trained with public data, derived from 843 tissue biopsies, shows that liquid biopsies exhibit multiple deviations that reflect histological classification. Most notably, distinguishing small from non-small cell lung cancer is characterized by an area under the curve of 0.98 during receiver operating characteristic analysis. Additionally, we investigated how deeper paired-end sequencing, which will eventually become feasible for routine diagnosis, empowers tumor read enrichment by insert size filtering: for all of the 29 resequenced liquid biopsies, the tumor fraction could be increased in silico, thereby “rescuing” three out of five cases with previously undetectable alterations.

Conclusions

Copy number profiling of cell-free DNA enables histological classification. Since shallow whole-genome sequencing is inexpensive and often fully operational at routine molecular laboratories, this finding has current diagnostic potential, especially for patients with lesions that are difficult to reach.

CASC5 is a potential tumour driving gene in lung adenocarcinoma

Previous studies have shown that cancer susceptibility candidate 5 (CASC5) plays important roles in several types of cancer. But its expression and clinical significance in human pan-cancer remain largely unclear. In the present study, we comprehensively analysed the expression profile and prognostic values of CASC5 in pan-cancer across 33 cancer types based on the online TCGA analysis databases. CASC5 was found to be abnormally expressed in 16 types of cancer. In addition, dysregulated expression of CASC5 was closely associated with patient overall survival (OS) in kidney renal papillary cell carcinoma (KIRP), lung adenocarcinoma (LUAD), pancreatic adenocarcinoma (PAAD) and thymoma (THYM). By comparative analysis, we found that CASC5 was significantly up-regulated in LUAD and predicted poor patient OS. High CASC5 expression was closely correlated with tumour advanced stages of patients with LUAD. Through GSEA based on the KEGG database, CASC5 was found to be closely related to DNA replication and microRNA regulation in LUAD. Functionally, knockdown of CASC5 could inhibit cell proliferation of LUAD cells in vitro, rather than affecting cell migration and invasion. Mechanistically, CASC5 promoted proliferation of LUAD cells by targeting miR-139-5p. Collectively, our findings reveal that CASC5 is a novel oncogenic gene in LUAD and may be a potential clinical target and (or) biomarker for this human malignancy. SIGNIFICANCE OF THE STUDY: In this study, we for the first time comprehensively analysed the transcriptional level and prognostic significance of CASC5 in human pan-cancer across 33 cancer types using online TCGA databases. Our study indicates that CASC5 is aberrantly expressed in many tumours and is closely related to the patient overall survival of several tumour types. Our findings reveal that CASC5 is a novel oncogene in LUAD based on bioinformatic analysis and functional experiments. Mechanistically, CASC5 promoted LUAD proliferation by targeting miR-139-5p. Results of this study suggest that CASC5 is a potential clinical target and (or) biomarker for LUAD.

The B7-H4 gene induces immune escape partly via upregulating the PD-1/Stat3 pathway in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is associated with high mortality rates worldwide. The costimulatory molecule, B7-H4, a member of the B7 family, plays an important role in immune regulation, mainly by inhibiting the proliferation of T cells to achieve a negative regulatory T cell immune response. The mechanism of action of B7-H4 in non-small cell lung cancer is unknown at present. Tumor tissues from 71 patients subjected to radical pneumonectomy were examined, along with NSCLC cells and BALB/c mice. Among the 71 NSCLC cases, overall and recurrence-free survival rates were significantly lower in those displaying high B7-H4 expression. Mechanistic analyses showed that B7-H4 promoted the growth and metastasis of non-small cell lung cancer tumor tissues in mice through effects on CD8⁺ T cell apoptosis. Data from western blot experiments further suggested that B7-H4 induced CD8⁺ T cell death, both in vitro and in vivo, and affecting the PD-1/Stat3 pathway and promoting immune escape of tumor cells. Our collective findings support the potential utility of B7-H4 gene expression as a marker of NSCLC prognosis and provide a novel strategy for targeted therapy.

Upregulated expression of pyruvate kinase M2 mRNA predicts poor prognosis in lung adenocarcinoma

Background

Pyruvate kinase M2 (PKM2) is critical regulator contributing to Warburg effect. However, the expression pattern and prognostic value of PKM2 remain unknown in lung adenocarcinoma (LUAD). The aim of this study is to clarify the prognostic value of PKM2 via intergrated bioinformatics analysis.

Methods

Firstly, mRNA expression levels of PKM2 in LUAD were systematically analyzed using the ONCOMINE and TCGA databases. Then, the association between PKM2 expression and clinical parameters was investigated by UALCAN. The Kaplan-Meier Plotter was used to assess the prognostic significance of PKM2. Finally, the relationship between PKM2 expression and its genetic and epigenetic changes was evaluated with MEXPRESS and MethHC database.

Results

Pooled analysis showed that PKM2 is frequently upregulated expression in LUAD. Subsequently, PKM2 expression was identified to be positively associated with tumor stage and lymph node metastasis and also strongly correlated with worse OS (P = 2.80e-14), PPS (P = 0.022), FP (P = 1.30e-6) and RFS (P = 3.41e-8). Importantly, our results demonstrated that over-expressed PKM2 is associated with PKM2 hypomethylation and copy number variations (CNVs).

Conclusion

This study confirms that over-expressed PKM2 in LUAD is associated with poor prognosis, suggesting that PKM2 might act as a promising prognostic biomarker and novel therapeutic target for LUAD.

Elevated Expression of LYPD3 Is Associated with Lung Adenocarcinoma Carcinogenesis and Poor Prognosis

Aberrant expression of LYPD3 plays an oncogenic role in several types of cancer. However, the functions of LYPD3 in lung adenocarcinoma (LUAD) remain unclear. Here, we investigated the regulatory function, clinical value, and prognostic significance of LYPD3 in LUAD patients. The gene expression and DNA methylation data of LUAD tumor and paracancerous tissues were obtained from The Cancer Genome Atlas (TCGA) database. The association between LYPD3 expression and clinicopathological variables was analyzed. The results showed that LYPD3 was highly expressed in LUAD tumor compared with paracancerous tissues, which was positively correlated with the race (p = 0.0448), tumor stage (p = 0.0191), and survival status (p < 0.001). Furthermore, the expression of LYPD3 was able to be regulated by the methylation in LYPD3 promoter region, which was positively associated with the overall survival. Furthermore, we explored the related pathways through which LYPD3 affects the pathogenesis and prognosis of LUAD by gene set enrichment analysis, and found that LYPD3 might affect the clinical manifestations of LUAD by regulating the P53 signaling pathway. In the future, we would focus on exploring the molecular mechanism of LYPD3 in the regulation of the occurrence and development of LUAD to provide a research basis for the screening of methylation markers related to the treatment and prognosis.

ESDA: An Improved Approach to Accurately Identify Human snoRNAs for Precision Cancer Therapy

Background:

SnoRNAs (Small nucleolar RNAs) are small RNA molecules with approximately 60-300 nucleotides in sequence length. They have been proved to play important roles in cancer occurrence and progression. It is of great clinical importance to identify new snoRNAs as fast and accurately as possible.

Objective:

A novel algorithm, ESDA (Elastically Sparse Partial Least Squares Discriminant Analysis), was proposed to improve the speed and the performance of recognizing snoRNAs from other RNAs in human genomes.

Methods:

In ESDA algorithm, to optimize the extracted information, kernel features were selected from the variables extracted from both primary sequences and secondary structures. Then they were used by SPLSDA (sparse partial least squares discriminant analysis) algorithm as input variables for the final classification model training to distinguish snoRNA sequences from other Human RNAs. Due to the fact that no prior biological knowledge is request to optimize the classification model, ESDA is a very practical method especially for completely new sequences.

Results:

89 H/ACA snoRNAs and 269 C/D snoRNAs of human were used as positive samples and 3403 non-snoRNAs as negative samples to test the identification performance of the proposed ESDA. For the H/ACA snoRNAs identification, the sensitivity and specificity were respectively as high as 99.6% and 98.8%. For C/D snoRNAs, they were respectively 96.1% and 98.3%. Furthermore, we compared ESDA with other widely used algorithms and classifiers: SnoReport, RF (Random Forest), DWD (Distance Weighted Discrimination) and SVM (Support Vector Machine). The highest improvement of accuracy obtained by ESDA was 25.1%.

Conclusion:

Strongly proved the superiority performance of ESDA and make it promising for identifying SnoRNAs for further development of the precision medicine for cancers.

Multiple genome pattern analysis and signature gene identification for the Caucasian lung adenocarcinoma patients with different tobacco exposure patterns

Background

When considering therapies for lung adenocarcinoma (LUAD) patients, the carcinogenic mechanisms of smokers are believed to differ from those who have never smoked. The rising trend in the proportion of nonsmokers in LUAD urgently requires the understanding of such differences at a molecular level for the development of precision medicine.

Methods

Three independent LUAD tumor sample sets—TCGA, SPORE and EDRN—were used. Genome patterns of expression (GE), copy number variation (CNV) and methylation (ME) were reviewed to discover the differences between them for both smokers and nonsmokers. Tobacco-related signature genes distinguishing these two groups of LUAD were identified using the GE, ME and CNV values of the whole genome. To do this, a novel iterative multi-step selection method based on the partial least squares (PLS) algorithm was proposed to overcome the high variable dimension and high noise inherent in the data. This method can thoroughly evaluate the importance of genes according to their statistical differences, biological functions and contributions to the tobacco exposure classification model. The kernel partial least squares (KPLS) method was used to further optimize the accuracies of the classification models.

Results

Forty-three, forty-eight and seventy-five genes were identified as GE, ME and CNV signatures, respectively, to distinguish smokers from nonsmokers. Using only the gene expression values of these 43 GE signature genes, ME values of the 48 ME signature genes or copy numbers of the 75 CNV signature genes, the accuracies of TCGA training and SPORE/EDRN independent validation datasets all exceed 76%. More importantly, the focal amplicon in Telomerase Reverse Transcriptase in nonsmokers, the broad deletion in ChrY in male nonsmokers and the greater amplification of MDM2 in female nonsmokers may explain why nonsmokers of both genders tend to suffer LUAD. These pattern analysis results may have clear biological interpretation in the molecular mechanism of tumorigenesis. Meanwhile, the identified signature genes may serve as potential drug targets for the precision medicine of LUAD.

Long Noncoding MAGI2-AS3 Suppresses Several Cellular Processes of Lung Squamous Cell Carcinoma Cells by Regulating miR-374a/b-5p/CADM2 Axis

Background

Lung squamous cell carcinoma (LUSC) accounts for approximately 30% of all lung cancers that possesses the highest occurrence and mortality in all cancer types. Long noncoding RNAs have been reported to modulate tumor development for several decades.

Aim of the Study

This research aims to investigate the role of MAGI2-AS3 in LUSC.

Methods

RT-qPCR tested genes (including MAGI2-AS3, miR-374a/b-5p and CADM2) expression. Cell proliferation was detected by colony formation and EdU assays. Cell migration and invasion were evaluated by transwell assay. Flow cytometry analysis of apoptotic cells and Western blot analysis on apoptosis-related genes were applied to measure cell apoptosis. Nuclear-cytoplasmic fractionation and FISH assay positioned MAGI2-AS3. The combination between miR-374a/b-5p and MAGI2-AS3 (or CADM2) was determined by luciferase reporter assay and RIP assay.

Results

MAGI2-AS3 inhibited the proliferative, migratory and invasive capability of LUSC cells with upregulated expression. Additionally, MAGI2-AS3 overexpression promoted cell apoptosis. We discovered that MAGI2-AS3 was located in the cytoplasm. Hereafter, we found out that MAGI2-AS3 targeted miR-374a/b-5p. CADM2 was targeted by miR-374a/b-5p. Finally, rescue assays indicated that the promoting effects of miR-374a/b-5p amplification on biological activities were restored by CADM2 addition.

Conclusion

In conclusion, lncRNA MAGI2-AS3 suppressed LUSC by regulating miR-374a/b-5p/CADM2 axis, which might potentially serve as a therapeutic marker for LUSC patients.

Low-depth whole genome sequencing reveals copy number variations associated with higher pathologic grading and more aggressive subtypes of lung non-mucinous adenocarcinoma

Objective

Histology grade, subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival. The aim of the study was to investigate the relationship between chromosomal instability, morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma (LNMA).

Methods

We developed a whole genome copy number variation (WGCNV) scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.

Results

Higher histological grades, aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score, particularly in CNV regions enriched for tumor suppressor genes and oncogenes. In addition, we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types (<100 cells) isolated by sample laser capture microdissection.

Conclusions

Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.

Clonality analysis of pulmonary tumors by genome-wide copy number profiling

Multiple tumors in patients are frequently diagnosed, either synchronous or metachronous. The distinction between a second primary and a metastasis is important for treatment. Chromosomal DNA copy number aberrations (CNA) patterns are highly unique to specific tumors. The aim of this study was to assess genome-wide CNA-patterns as method to identify clonally related tumors in a prospective cohort of patients with synchronous or metachronous tumors, with at least one intrapulmonary tumor. In total, 139 tumor pairs from 90 patients were examined: 35 synchronous and 104 metachronous pairs. Results of CNA were compared to histological type, clinicopathological methods (Martini-Melamed-classification (MM) and ACCP-2013-criteria), and, if available, EGFR- and KRAS-mutation analysis. CNA-results were clonal in 74 pairs (53%), non-clonal in 33 pairs (24%), and inconclusive in 32 pairs (23%). Histological similarity was found in 130 pairs (94%). Concordance between histology and conclusive CNA-results was 69% (74 of 107 pairs: 72 clonal and two non-clonal). In 31 of 103 pairs with similar histology, genetics revealed non-clonality. In two out of four pairs with non-matching histology, genetics revealed clonality. The subgroups of synchronous and metachronous pairs showed similar outcome for the comparison of histological versus CNA-results. MM-classification and ACCP-2013-criteria, applicable on 34 pairs, and CNA-results were concordant in 50% and 62% respectively. Concordance between mutation matching and conclusive CNA-results was 89% (8 of 9 pairs: six clonal and two non-clonal). Interestingly, in one patient both tumors had the same KRAS mutation, but the CNA result was non-clonal. In conclusion, although some concordance between histological comparison and CNA profiling is present, arguments exist to prefer extensive molecular testing to determine whether a second tumor is a metastasis or a second primary.

Comprehensive Profiling of Gene Copy Number Alterations Predicts Patient Prognosis in Resected Stages I-III Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) possesses a poor prognosis with a low 5-year survival rate even for stages I-III resected patients, it is thus critical to understand the determinants that affect the survival and discover new potentially prognostic biomarkers. Somatic copy number alterations (CNAs) are major source of genomic variations driving tumor evolution, CNAs screening may identify prognostic biomarkers. Methods: Oncoscan MIP array was used to analyze the patterns of CNAs on formalin fixed paraffin embedded(FFPE) tumor specimens from 163 consecutive stage I-III resected LUAD patients, 145 out of which received platinum-based adjuvant chemotherapy. Results: Of the 163 patients, 91(55.8%) were recurred within 3 years after surgery. The most common aberrations in our cohort were 1q, 5p, 5q, 7p, 8q, 14p, 16p, 17q, 20q for copy number gains and 8p, 9p, 13p, 16q, 18q for losses. The GISTIC2 analysis produced 45 amplification peaks and 40 deletion peaks, involving some reported genes TERT, EGFR, MYC, CCND1, CDK4, MDM2, ERBB2, NKX2-1, CCNE1, and CDKN2A, most of which were consistent with TCGA database. The amplifications of 12p12.1 (CMAS, GOLT1B, YS2, LDHB, RECQL, ETNK1, IAPP, PYROXD1, KRAS) and KDM5A were correlated with worse prognosis in our cohort, this result was further validated in 506 LUAD patients from TCGA. In addition, 163 patients could be well-classified into five groups, and the clinical outcomes were significantly different based on threshold copy number at reoccurring alteration peaks. Among the 145 patients who received adjuvant chemotherapy, focal amplification of ERBB2 and deletion of 4q34.3 were found to be specific in relapsed patients, this result was validated in an independent group of Imielinski et al., demonstrating these two CNAs may contribute to resected LUAD recurrence after adjuvant chemotherapy. Conclusion: This study suggests that CNAs profiling may be a potential prognostic classifier in resected LAUD patients. Amplifications of 12p12.1 and KDM5A might be prognostic biomarkers for LUAD, and amplification of ERBB2 and deletion of 4q34.3 predicted early relapse after adjuvant chemotherapy. These novel findings may provide implication for better implementation of precision therapy for lung cancer patients.

ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration

Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional gene research and cancer associated mechanism uncovering. While the existing web servers are valuable and widely used, many whole genome analysis functions urgently needed by experimental biologists are still not adequately addressed. A cloud-based platform, named CG (ClickGene), therefore, was developed for DIY analyzing of user's private in-house data or public genome data without any requirement of software installation or system configuration. CG platform provides key interactive and customized functions including Bee-swarm plot, linear regression analyses, Mountain plot, Directional Manhattan plot, Deflection plot and Volcano plot. Using these tools, global profiling or individual gene distributions for expression and copy number variation (CNV) analyses can be generated by only mouse button clicking. The easy accessibility of such comprehensive pan-cancer genome analysis greatly facilitates data mining in wide research areas, such as therapeutic discovery process. Therefore, it fills in the gaps between big cancer genomics data and the delivery of integrated knowledge to end-users, thus helping unleash the value of the current data resources. More importantly, unlike other R-based web platforms, Dubbo, a cloud distributed service governance framework for 'big data' stream global transferring, was used to develop CG platform. After being developed, CG is run on an independent cloud-server, which ensures its steady global accessibility. More than 2 years running history of CG proved that advanced plots for hundreds of whole-genome data can be created through it within seconds by end-users anytime and anywhere. CG is available at http://www.clickgenome.org/.