Genome analyses identify the genetic modification of lung cancer subtypes

The Genetic Analysis and Clinical Therapy in Lung Cancer: Current Advances and Future Directions

Lung cancer, including both non-small cell lung cancer and small cell lung cancer, remains the leading cause of cancer-related mortality worldwide, representing 18% of the total cancer deaths in 2020. Many patients are identified already at an advanced stage with metastatic disease and have a worsening prognosis. Recent advances in the genetic understanding of lung cancer have opened new avenues for personalized treatments and targeted therapies. This review examines the latest discoveries in the genetics of lung cancer, discusses key biomarkers, and analyzes current clinical therapies based on this genetic information. It will conclude with a discussion of future prospects and potential research directions.

Isovaleryl Sucrose Esters from Atractylodes japonica and Their Cytotoxic Activity

Cancer represents one of the most significant health challenges currently facing humanity, and plant-derived antitumour drugs represent a prominent class of anticancer medications in clinical practice. Isovaleryl sucrose esters, which are natural constituents, have been identified as having potential antitumour effects. However, the mechanism of action remains unclear. In this study, 12 isovaleryl sucrose ester components, including five new (1-5) and seven known compounds (6-12), were isolated from the roots of Atractylodes japonica. The structures of the compounds were elucidated using 1D and 2D-NMR spectroscopy, complemented by HR-ESI-MS mass spectrometry. The cytotoxic activities of all the compounds against human colon cancer cells (HCT-116) and human lung adenocarcinoma cells (A549) were also evaluated using the CCK8 assay. The results demonstrated that compounds 2, 4, and 6 were moderately inhibitory to HCT-116 cells, with IC50 values of 7.49 ± 0.48, 9.03 ± 0.21, and 13.49 ± 1.45 μM, respectively. Compounds 1 and 6 were moderately inhibitory to A549, with IC50 values of 8.36 ± 0.77 and 7.10 ± 0.52 μM, respectively. Molecular docking revealed that compounds 1-9 exhibited a stronger affinity for FGFR3 and BRAF, with binding energies below -7 kcal/mol. Compound 2 exhibited the lowest binding energy of -10.63 kcal/mol to FGFR3. We screened the compounds with lower binding energies, and the protein-ligand complexes already obtained after molecular docking were subjected to exhaustive molecular dynamics simulation experiments, which simulated the dynamic behaviour of the molecules in close proximity to the actual biological environment, thus providing a deeper understanding of their functions and interaction mechanisms. The present study provides a reference for the development and use of iso-valeryl sucrose esters in the antitumour field.

Single nucleotide variants in lung cancer

Germline genetic variants, including single-nucleotide variants (SNVs) and copy number variants (CNVs), account for interpatient heterogeneity. In the past several decades, genome-wide association studies (GWAS) have identified multiple lung cancer-associated SNVs in Caucasian and Chinese populations. These variants either reside within coding regions and change the structure and function of cancer-related proteins or reside within non-coding regions and alter the expression level of cancer-related proteins. The variants can be used not only for cancer risk assessment and prevention but also for the development of new therapies. In this review, we discuss the lung cancer-associated SNVs identified to date, their contributions to lung tumorigenesis and prognosis, and their potential use in predicting prognosis and implementing therapeutic strategies.

RGD peptide in cancer targeting: Benefits, challenges, solutions, and possible integrin-RGD interactions

RGD peptide can be found in cell adhesion and signaling proteins, such as fibronectin, vitronectin, and fibrinogen. RGD peptides' principal function is to facilitate cell adhesion by interacting with integrin receptors on the cell surface. They have been intensively researched for use in biotechnology and medicine, including incorporation into biomaterials, conjugation to medicinal molecules or nanoparticles, and labeling with imaging agents. RGD peptides can be utilized to specifically target cancer cells and the tumor vasculature by engaging with these integrins, improving drug delivery efficiency and minimizing adverse effects on healthy tissues. RGD-functionalized drug carriers are a viable option for cancer therapy as this focused approach has demonstrated promise in the future. Writing a review on the RGD peptide can significantly influence how drugs are developed in the future by improving our understanding of the peptide, finding knowledge gaps, fostering innovation, and making drug design easier.

Identification of a novel anoikis-related gene signature to predict prognosis and tumor microenvironment in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent histotype of non-small cell lung cancer. Anoikis, an alternative form of programmed cell death, plays a pivotal role in cancer invasion and metastasis, preventing the detached cancer cells from readhering to other substrates for abnormal proliferation. The aim of this study was to conduct a comprehensive analyses of the prognostic implications of anoikis-related genes (ARGs) in LUAD.

METHODS

ARGs were selected from The Cancer Genome Atlas (TCGA) database and Genecards dataset using differential expression analysis. The signature incorporating ARGs was identified using univariate Cox regression analysis and LASSO regression analysis. Furthermore, a nomogram containing the signature and clinical information was developed through univariate and multivariate Cox regression analysis. Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were applied to evaluate the predictive validity of these risk models. Finally, functional analysis of the selected ARGs in signature and analysis of immune landscape were also conducted.

RESULTS

A 16-gene signature was integrated to stratify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and TNM stage were identified as independent prognostic factors and utilized to develop a nomogram. Both the signature and the nomogram showed satisfactory prediction performance in predicting overall survival (OS) of LUAD patients. The ARGs were enriched in several biological functions and signaling pathways. Finally, differences of immune landscape were investigated among the high- and low-risk groups stratified by the signature.

CONCLUSIONS

This study revealed potential relationships between ARGs and prognosis of LUAD. The prognostic predictors identified in present study could be utilized as potential biomarkers for clinical applications.

Evolution of small cell lung cancer tumor mutation: from molecular mechanisms to novel viewpoints

Small cell lung cancer (SCLC) is a clinically common malignant tumor originating from the lung neuroendocrine stem cells, which has a poor prognosis and accounts for approximately 15% of all lung cancer cases. However, research on its treatment has been slow, and the 5-year survival rate of patients with SCLC has been < 5% for many years. In recent years, the development and popularization of gene sequencing technology have facilitated the understanding of the gene mutation landscape and tumor evolution of SCLC, thereby leading to a more accurate prediction of the prognosis of SCLC and the development of individualized treatment. In this review, we aimed to discuss the mutation evolution of SCLC from the perspective of a tumor evolution theory and described the sequence of mutation evolution in the occurrence and development of SCLC. In addition, we summarized the existing whole-exome sequencing (WES) data of SCLC cases at our center along with relevant publications on sequencing. Thereafter, we discuss the role of different mutated pathways in the occurrence of SCLC to predict its prognosis more accurately and summarized individualized treatment strategies.

Prognostic value of lncRNAs related to fatty acid metabolism in lung adenocarcinoma and their correlation with tumor microenvironment based on bioinformatics analysis

Background

As a key regulator of metabolic pathways, long non-coding RNA (lncRNA) has received much attention for its relationship with reprogrammed fatty acid metabolism (FAM). This study aimed to investigate the role of the FAM-related lncRNAs in the prognostic management of patients with lung adenocarcinoma (LUAD) using bioinformatics analysis techniques.

Methods

We obtained LUAD-related transcriptomic data and clinical information from The Cancer Genome Atlas (TCGA) database. The lncRNA risk models associated with FMA were constructed by single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network (WGCNA), differential expression analysis, overlap analysis, and Cox regression analysis. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were utilized to assess the predictive validity of the risk model. Gene set variation analysis (GSVA) revealed molecular mechanisms associated with the risk model. ssGSEA and microenvironment cell populations-counter (MCP-counter) demonstrated the immune landscape of LUAD patients. The relationships between lncRNAs, miRNAs, and mRNAs were predicted by using LncBase v.2 and miRTarBase. The lncRNA-miRNA-mRNA regulatory network was visualized with Cytoscape v3.4.0. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using DAVID v6.8. Quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of the prognostic lncRNAs.

Results

We identified 249 differentially expressed FMA-related lncRNAs in TCGA-LUAD, six of which were used to construct a risk model with appreciable predictive power. GSVA results suggested that the risk model may be involved in regulating fatty acid synthesis/metabolism, gene repair, and immune/inflammatory responses in the LUAD process. Immune landscape analysis demonstrated a lower abundance of immune cells in the high-risk group of patients associated with poor prognosis. Moreover, we predicted 279 competing endogenous RNA (ceRNA) mechanisms for 6 prognostic lncRNAs with 39 miRNAs and 201 mRNAs. Functional enrichment analysis indicated that the ceRNA network may be involved in the process of LUAD by participating in genomic transcription, influencing the cell cycle, and regulating tissue and organogenesis. In vitro experiments showed that prognostic lncRNA CTA-384D8.35, lncRNA RP5-1059L7.1, and lncRNA Z83851.4 were significantly upregulated in LUAD primary tumor tissues, while lncRNA RP11-401P9.4, lncRNA CTA-384D8.35, and lncRNA RP11-259K15.2 were expressed at higher levels in paraneoplastic tissues.

Conclusion

In summary, the prognostic factors identified in this study can be used as potential biomarkers for clinical applications. ceRNA network construction provides a new vision for the study of LUAD pathogenesis.

Genomic Features of Organ-Specific Metastases in Lung Adenocarcinoma

Background

The genomic features of cancer cells may confer the metastatic ability of lung adenocarcinoma (LUAD) to metastasize to specific organs. We aimed to identify the differences in genomic alterations between patients with primary LUAD with and without metastases and to elucidate the metastatic biology that may help developing biomarker-directed therapies for advanced or metastatic disease.

Methods

A retrospective cohort of 497 patients with LUAD including 388 primary tumors (PR), 53 bone metastases (MT-bone), 30 liver metastases (MT-liver), and 26 brain metastases (MT-brain) was tested for genomic alterations by a next-generation sequencing assay.

Results

The EGFR, TP53, TERT, LRP1B, CDKN2A, ERBB2, ALK, and KMT2C genes had a high frequency of mutations, and the mutations were shared by PR and metastases groups. TP53 and EGFR were the most common mutated genes. In comparison with PR, KRAS, STK11, ATM, NPM1, and ROS1 were significantly mutated in MT-brain, and TP53, MYC, RSPO2, CDKN2a, and CDKN2B were significantly mutated in MT-liver. The frequencies of TP53, CDKN2A, MTAP, PRKCI, and APC mutations were higher in MT-bone than that in PR. The ERBB, phosphoinositide-3-kinase/protein kinase B (PI3K-AKT), cell cycle, Fibroblast growth factor (FGF), and homologous recombination deficiency signaling pathways were affected in both PR and metastases, and there is higher frequency of mutations in metastases. Moreover, the co-mutations in patients with PR and metastasis were respectively analyzed. In addition, the programmed death ligand 1 (PD-L1) level was obviously related to tumor stage and tumor metastases, and the tumor mutational burden was correlated to clinicopathological features including age, gender, pathological stages, and tumor metastases. FGFR1, KAT6A, MYC, RAD21, TP53, and DAXX were also dramatically correlated to the tumor mutational burden.

Conclusion

Metastases are the most devastating stage of tumors and the main cause of cancer-related deaths. Our results provided a clinically relevant view of the tumor-intrinsic mutational landscape of patients with metastatic LUAD.

The molecular mechanism of METTL3 promoting the malignant progression of lung cancer

Lung cancer remains one of the major causes of cancer-related death globally. Recent studies have shown that aberrant m⁶A levels caused by METTL3 are involved in the malignant progression of various tumors, including lung cancer. The m⁶A modification, the most abundant RNA chemical modification, regulates RNA stabilization, splicing, translation, decay, and nuclear export. The methyltransferase complex plays a key role in the occurrence and development of many tumors by installing m⁶A modification. In this complex, METTL3 is the first identified methyltransferase, which is also the major catalytic enzyme. Recent findings have revealed that METTL3 is remarkably associated with different aspects of lung cancer progression, influencing the prognosis of patients. In this review, we will focus on the underlying mechanism of METT3 in lung cancer and predict the future work and potential clinical application of targeting METTL3 for lung cancer therapy.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Centromere protein N promotes lung adenocarcinoma progression by activating PI3K/AKT signaling pathway

BACKGROUND

As an important member of centromere family, centromere associated protein N (CENPN) was abnormally expressed in varied malignant tumors.

OBJECTIVE

This paper aimed to analyze the expression and related mechanism of CENPN in lung adenocarcinoma (LUAD).

METHODS

The expression of CENPN in LUAD was analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) database. The mRNA expression, protein expression, cell viability, cell invasion, cell apoptosis, cell stem like characteristics were detected by RT-PCR, western blot, CCK8 assay, transwell assay, flow cytometry and spheroidization assay, respectively. Finally, the pathological changes of xenograft were estimated by H&E staining, and the expression of proteins was detected by immunohistochemistry.

RESULTS

GEPIA analysis showed that the CENPN expression in LUAD was significantly higher than that in normal lung tissue, which was negatively correlated with the prognosis. These results were consistent with our clinical data. Besides, CENPN was highly expressed in LUAD cell lines. In addition, the upregulation of CENPN amplified the cell viability, stemness and invasive ability in PC9 cells. However, the knockdown of CENPN inhibited the cell activity, stemness, invasive ability with increased cell apoptosis in A549. Furthermore, CENPN could positively regulate the phosphorylation of PI3K and AKT. The PI3K inhibitor, 740Y-P, could reverse the effect of CENPN silencing on the expression of Ki-67, cleaved caspase 3, OCT4, and snail 1. Finally, the downregulation of CENPN restrained the growth of xenograft and inactivated the PI3K/AKT pathway.

CONCLUSION

CENPN was abnormally overexpressed in LUAD, and promoted tumor progression of LUAD by affecting PI3K/AKT pathway.

Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the main causes of cancer deaths globally. Redox is emerging as a crucial contributor to the pathophysiology of LUAD, which can be regulated by long non-coding RNAs (lncRNAs). The aim of our research is to identify a novel redox-related lncRNA prognostic signature (redox-LPS) for better prediction of LUAD prognosis. 535 LUAD samples from The Cancer Genome Atlas (TCGA) database and 226 LUAD samples from the Gene Expression Omnibus (GEO) database were included in our study. 67 redox genes and 313 redox-related lncRNAs were identified. After performing LASSO-Cox regression analysis, a redox-LPS consisting of four lncRNAs (i.e., CRNDE, CASC15, LINC01137, and CYP1B1-AS1) was developed and validated. Our redox-LPS was superior to another three established models in predicting survival probability of LUAD patients. Univariate and multivariate Cox regression analysis revealed that risk score and stage were independent prognostic indicators. A nomogram plot including risk score and stage was constructed to predict survival probability of LUAD patients; this was further verified by calibration curves. Functional enrichment analysis and gene set enrichment analysis, were performed to determine the differences in cellular processes and signaling pathways between the high – and low-risk subgroups. A variety of algorithms (such as single-sample gene set enrichment analysis and CIBERSOFT) were conducted to uncover the landscape of tumor immune microenvironment in the high- and low-risk subgroups. In conclusion, a novel independent redox-LPS was constructed and validated for LUAD patients, which might provide new insights for clinical decision-making and precision medicine.

Combination of tumor mutation burden and immune infiltrates for the prognosis of lung adenocarcinoma

BACKGROUND

Tumor mutation burden (TMB) levels are associated with immune infiltrates in the tumor microenvironment and can modulate the responses to immune checkpoint inhibitors (ICIs) in lung adenocarcinoma (LUAD) patients. This study aimed at exploring the potential role of a signature of genes associated with TMB and immune infiltrates and the relevant nomogram in the prognosis of LUAD.

MATERIALS AND METHODS

The TMB levels in LUAD patients in the Cancer Genome Atlas (TCGA) were analyzed. The differentially expressed genes (DEGs) between the higher- and lower-TMB subgroups were functionally analyzed. The immune-related DEGs and their relationship with immune infiltrates in the tumor environment between two subgroups were analyzed. Nine immune-related DEGs were used to generate a TMB-related immune signature. The sensitivity to immunotherapy in TCGA-LUAD patients was analyzed by immunophenotypic scores (IPS). Subsequently, a nomogram was generated using tumor-related parameters and the signature score. The signature or nomogram values in predicting overall survival (OS) were evaluated and validated in LUAD patients in the GSE30219 and GSE72094.

RESULT

There were 468 DEGs between the higher and lower-TMB subgroups of LUAD patients. The TMB levels were associated positively with the number of immune infiltrates in LUAD patients. Nine DEGs were related to immune infiltrates in the tumor environment. The higher signature scores (high-risk) were associated with poor prognosis of LUAD in the TCGA, which was validated in LUAD patients of the GSE30219 and GSE72094 datasets. Interestingly, the patients in the high-risk group had higher PD-L1 expression in their tumors and the risk scores in LUAD patients. The IPS of LUAD patients in the high-risk group were predicted to benefit from immunotherapy. Finally, the nomogram had high AUC values in predicting the OS of LUAD patients.

CONCLUSION

The TMB-related immune signature or nomogram is valuable for the prognosis of LUAD patients and evaluating their responses to ICIs. These relevant genes may participate into the pathogenesis, ICIs, and drug resistance of LUAD.

Circular RNA expression profile of lung squamous cell carcinoma: identification of potential biomarkers and therapeutic targets

Emerging evidences indicated that exosomal circular RNAs (circRNAs) could serve as diagnostic biomarkers for cancers. However, the expression profiles and clinical significance of circRNAs in lung squamous cell carcinoma (LUSC) remain largely unknown. Herein, we analyzed circRNAs expression profile in six pairs of plasma exosome samples of LUSC patients using high-throughput sequencing. A total of 252 differentially expressed exosomal circRNAs were identified, including 133 up-regulated circRNAs and 119 down-regulated circRNAs. Subsequently, the circRNAs–miRNAs–mRNAs interaction network was built to investigate potential function of circRNAs. Three up-regulated circRNAs (hsa_circ_0014235, hsa_circ_0025580 and hsa_circ_0026403) were implied to participate in cancer-related pathways. QRT-PCR experiment confirmed the up-regulation of hsa_circ_0014235 and hsa_circ_0025580. Finally, clinical studies indicated that hsa_circ_0014235 and hsa_circ_0025580 could serve as novel diagnostic biomarkers for LUSC. Taken together, our study revealed exosomal circRNAs expression profile in LUSC for the first time and showed the important diagnostic potential for circRNAs in LUSC.

Genetic Heterogeneity Between Paired Primary and Brain Metastases in Lung Adenocarcinoma

Purpose:

About one-third of nonsmall cell lung cancer (NSCLC) patients develop brain metastases (BM). However, there is an unmet need for early diagnosis and treatment of BM. The precise mechanism for BM is still unknown. However, the genetic heterogeneity between primary tumor and paired BM indicates that sampling from the primary tumor may not be able to fully represent the mutational status in metastases. In this study, the genetic heterogeneity of primary lung adenocarcinoma and paired BM was analyzed.

Patients and methods:

A total of 11 paired samples of primary tumors and BM from lung cancer patients were included, in which 7 paired samples of patients were finally analyzed. Samples were sequenced by whole-exome sequencing (WES) to investigate the common and unique mutations in the primary tumors and BM, and the similarities and differences in copy number variation (CNV).

Results:

The consistency of gene mutation between primary lung adenocarcinoma and paired BM was 33% to 86%. FAM129C and ADAMTSs specifically mutated in BM, along with NKX2-1 high amplification and SAMD2/4 copy number deletion.

Conclusion:

The consistency of gene mutation between primary lung adenocarcinoma and corresponding BM is relatively high, while the individual differences were significant. FAM129C and ADAMTSs mutations and high amplification of NKX2-1 may be related to BM of lung cancer. The loss of copy number of SAMD2/4 may be a potential therapeutic target for BM from lung adenocarcinoma.

[Mechanism and Research Progress of Microbiome in the Development of Lung Cancer]

肺癌是我国最常见的、预后较差的恶性肿瘤之一，大多数患者确诊时即为晚期。有研究表明肺癌患者的微生态特征有别于健康人群，呼吸道的微生物可以通过多种机制影响肺癌的发生发展。近年来微生物组学与疾病相关性研究已成为继人类基因组计划又一研究热点，然而目前有关肺癌与呼吸道微生物组特征的研究相对较少，因此，需要更深入地探讨肺癌与微生物菌群间的潜在联系，通过研究呼吸道微生物在肺癌发生发展中的作用机制，以期在为肺癌的临床诊治、预后评估提供更明确的科学依据。本文对目前关于微生物菌群与肺癌相关研究进行综述，并为临床上诊断与治疗肺癌提供新的思路。

Identifying prognostic biomarkers of non-small cell lung cancer by transcriptome analysis

BACKGROUND

Prognostic biomarkers are promising targets for cancer prevention and treatment.

OBJECTIVE

We try to filtrate survival-related genes for non-small cell lung cancer (NSCLC) via transcriptome analysis.

METHODS

Transcriptome data and clinical information of Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), mainly subtypes of NSCLC, were obtained from The Cancer Genome Atlas (TCGA) program. Differentially expressed genes (DEGs) analyzed by DESeq2 package were regarded as candidate genes. For survival analysis, univariate and multivariate Cox regression were applied to select biomarkers for overall survival (OS) and progression-free survival (PFS), where univariate analysis was for preliminary filtration and multivariate analysis considering age, gender, TNM parameters and clinical stage was for ultimate determination. Gene ontology (GO) analysis and pathway enrichment were used for biological annotation.

RESULTS

We ultimately acquired a series of genes closely related to prognosis. For LUAD, we determined 314 OS-related genes and 275 PFS-related genes, while 54 OS-related genes and 78 PFS-related genes were chosen for LUSC. The final biological analysis indicated important function of proliferative signaling in LUAD but for LUSC, only cornification process had statistical meaning.

CONCLUSIONS

We strictly determined prognostic genes of NSCLC, which would contribute to its carcinogenesis investigation and therapeutic methods improvement.

Detecting Prognosis Risk Biomarkers for Colon Cancer Through Multi-Omics-Based Prognostic Analysis and Target Regulation Simulation Modeling

Background

Colon cancer is one of the most common health threats for humans since its high morbidity and mortality. Detecting potential prognosis risk biomarkers (PRBs) is essential for the improvement of therapeutic strategies and drug development. Currently, although an integrated prognostic analysis of multi-omics for colon cancer is insufficient, it has been reported to be valuable for improving PRBs’ detection in other cancer types.

Aim

This study aims to detect potential PRBs for colon adenocarcinoma (COAD) samples through the cancer genome atlas (TCGA) by integrating muti-omics.

Materials and Methods

The multi-omics-based prognostic analysis (MPA) model was first constructed to systemically analyze the prognosis of colon cancer based on four-omics data of gene expression, exon expression, DNA methylation and somatic mutations on COAD samples. Then, the essential features related to prognosis were functionally annotated through protein–protein interaction (PPI) network and cancer-related pathways. Moreover, the significance of those essential prognostic features were further confirmed by the target regulation simulation (TRS) model. Finally, an independent testing dataset, as well as the single cell-based expression dataset were utilized to validate the generality and repeatability of PRBs detected in this study.

Results

By integrating the result of MPA modeling, as well the PPI network, integrated pathway and TRS modeling, essential features with gene symbols such as EPB41, PSMA1, FGFR3, MRAS, LEP, C7orf46, LOC285000, LBP, ZNF35, SLC30A3, LECT2, RNF7, and DYNC1I1 were identified as PRBs which provide high potential as drug targets for COAD treatment. Validation on the independent testing dataset demonstrated that these PRBs could be applied to distinguish the prognosis of COAD patients. Moreover, the prognosis of patients with different clinical conditions could also be distinguished by the above PRBs.

Conclusions

The MPA and TRS models constructed in this paper, as well as the PPI network and integrated pathway analysis, could not only help detect PRBs as potential therapeutic targets for COAD patients but also make it a paradigm for the prognostic analysis of other cancers.

Comparative proteogenomics profiling of non-small and small lung carcinoma cell lines using mass spectrometry

Background

Evidences indicated that non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) might originate from the same cell type, which however ended up to be two different subtypes of lung carcinoma, requiring different therapeutic regimens. We aimed to identify the differences between these two subtypes of lung cancer by using integrated proteome and genome approaches.

Methods and Materials

Two representative cell lines for each lung cancer subtype were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics data were obtained from the Gene Expression Omnibus database. The integrated analyses of proteogenomic data were performed to determine key differentially expressed proteins that were positively correlated between proteomic and transcriptomic data.

Result

The proteomics analysis revealed 147 differentially expressed proteins between SCLC and NSCLC from a total of 3,970 identified proteins. Combined with available transcriptomics data, we further confirmed 14 differentially expressed proteins including six known and eight new lung cancer related proteins that were positively correlated with their transcriptomics data. These proteins are mainly involved in cell migration, proliferation, and invasion.

Conclusion

The proteogenomic data on both NSCLC and SCLC cell lines presented in this manuscript is complementary to existing genomic and proteomic data related to lung cancers and will be crucial for a systems biology-level understanding of the molecular mechanism of lung cancers. The raw mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015270.

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients' clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P < 0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.

The Metabolic Remodelling in Lung Cancer and Its Putative Consequence in Therapy Response

Lung cancer is the leading cause of cancer-related deaths worldwide in both men and women. Conventional chemotherapy has failed to provide long-term benefits for many patients and in the past decade, important advances were made to understand the underlying molecular/genetic mechanisms of lung cancer, allowing the unfolding of several other pathological entities. Considering these molecular subtypes, and the appearance of promising targeted therapies, an effective personalized control of the disease has emerged, nonetheless benefiting a small proportion of patients. Although immunotherapy has also appeared as a new hope, it is still not accessible to the majority of patients with lung cancer.The metabolism of energy and biomass is the basis of cellular survival. This is true for normal cells under physiological conditions and it is also true for pathophysiologically altered cells, such as cancer cells. Thus, knowledge of the metabolic remodelling that occurs in cancer cells in the sense of, on one hand, surviving in the microenvironment of the organ in which the tumour develops and, on the other hand, escaping from drugs conditioned microenvironment, is essential to understand the disease and to develop new therapeutic approaches.

Relationship between tumor size and metastatic site in patients with stage IV non-small cell lung cancer: A large SEER-based study

Objective

To analyze the relationship between tumor size and metastatic site in stage IV NSCLC patients.

Methods

A total of 40,196 stage IV NSCLC patients from 2010 to 2015 were screened by SEER database. Chi-square test was used to compare the characteristics of clinical variables. At the same time, multivariate Logistic regression analysis was used to evaluate the relationship between tumor size and organ metastasis.

Results

Regardless of tumor size, the proportion of bone metastasis and lung metastasis was higher and similar in patients with squamous cell carcinoma, while in patients with adenocarcinoma, bone metastasis accounted for the highest proportion. We found that whether the metastatic site was bone, brain, liver or lung, the proportion of patients with a tumor size of 3–7 cm was the highest. Multivariate regression analysis demonstrated that patients with a tumor size of 3–7 cm and a tumor size ≥7 cm were more likely to develop brain metastasis and lung metastasis compared with patients with a tumor size ≤3 cm (all P < 0.001), which meant the larger the tumor, the greater the risk of brain or lung metastasis. At the same time, the results indicated that patients with a tumor size of 3–7 cm had a tendency to develop liver metastasis (P = 0.004), while the statistical significance was not found for patients with a tumor size ≥7 cm (P = 0.524). The results also revealed that patients with a tumor size of 3–7cm had no significant difference to develop bone metastasis (P = 0.116), while the statistical significance was found for patients with a tumor size ≥7 cm (P < 0.001).

Conclusions

There was statistical significance between tumor size and metastatic site in patients with stage IV NSCLC. For brain or lung metastasis, the larger the tumor, the higher the risk of brain or lung metastasis. For liver metastasis, patients with a tumor size of 3–7 cm were more prone to develop liver metastasis. For bone metastasis, patients with a tumor size ≥7 cm were more likely to have bone metastasis.

CDK5 neutralizes the tumor suppressing effect of BIN1 via mediating phosphorylation of c-MYC at Ser-62 site in NSCLC

Background

Bridging integrator 1 (BIN1) has showed outstanding tumor-suppressive potential via inhibiting c-MYC-mediated tumorigenesis. However, a frequent phosphorylation of c-MYC at Ser-62 site could block the BIN1/c-MYC interaction and limits the tumor-suppressive effect of BIN1. Cyclin-dependent kinase 5 (CDK5), a generally dysregulated protein in various carcinomas, can mediate c-MYC phosphorylation at Ser-62 site. However, whether the existence of CDK5 could block the BIN1/c-MYC interaction remains unclear.

Materials and methods

The expression of CDK5 and BIN1 in non-small cell lung cancer (NSCLC) cell lines were measured. CDK5 was knocked down and overexpressed in H460 and PC9 cells, respectively. CCK-8, wound healing and transwell were used to detect the proliferation, migration and invasion ability of NSCLC cells. Tumor-bearing nude mouse model was built with H460 cells. Dinaciclib was added to realize the effect of CDK5 inhibition in vivo. NSCLC and matched para-carcinoma specimens were collected from 153 patients who underwent radical operation. IHC was performed to determine the expression of CDK5 in the specimens. Kaplan–Meier analysis was used to analyze the correlation between the postoperative survival and CDK5 expression.

Results

CDK5 was highly expressed in H460 cells, and knockdown of CDK5 could restore the BIN1/c-MYC interaction. Meanwhile, low expression of CDK5 was observed in PC9 cells, and overexpression of CDK5 blocked the BIN1/c-MYC interaction. Consequently, the growth, migration, invasion and epithelial mesenchymal transition (EMT) ability of H460 and PC9 cells could be facilitated by CDK5. The addition of CDK5 inhibitor Dinaciclib significantly suppressed the tumorigenesis ability of NSCLC cells in tumor-bearing mouse model. Furthermore, high expression of CDK5, along with low expression of BIN1, could predict poor postoperative prognosis of NSCLC patients. The patients with high expression of CDK5 and low expression of BIN1 showed similar prognosis, indicating that CDK5 could neutralize the tumor suppressing effect of BIN1 in clinical situation.

Conclusions

CDK5 blocked the interaction of BIN1 and c-MYC via promoting phosphorylation of c-MYC at ser-62 site, ultimately facilitated the progression of NSCLC.

miR-30a-5p together with miR-210-3p as a promising biomarker for non-small cell lung cancer: A preliminary study

BACKGROUND

Although an immense effort has been made to develop novel diagnostic methods and treatment strategies for non-small cell lung cancer (NSCLC), the survival rate of this disease has remained virtually unchanged. Small non-coding RNAs called microRNAs (miRNAs) have appeared to be very promising biomarkers of cancer including NSCLC.

OBJECTIVE

We investigated the expression level of six miRNAs, and subsequently we evaluated their diagnostic ability and their clinical significance.

METHODS

We performed an analysis in 50 paired cancer and non-cancerous lung tissue samples collected from NSCLC patients. The RT-qPCR technique was used to investigate the expression profile.

RESULTS

Obtained results indicate that miR-30a-5p, miR-126-3p and miR-486-5p are downregulated, while miR-205-5p and miR-210-3p are upregulated in NSCLC tissue. Moreover, performed stepwise discriminant analysis determined the model including miR-30a-5p and miR-210-3p which tested on the test set (n= 30) revealed an AUC of 0.969 and provided 100% sensitivity and 80% specificity in discriminating NSCLC tissue from non-cancerous lung tissue.

CONCLUSIONS

The present preliminary study demonstrated that five tested miRNAs were deregulated in cancer tissue. Moreover, miR-30a-5p together with miR-210-3p with excellent sensitivity and acceptable specificity may distinguish cancer tissue form non-cancerous tissue and thus may become a potential diagnostic biomarker for NSCLC.

Lung Cancer Radiogenomics: The Increasing Value of Imaging in Personalized Management of Lung Cancer Patients

Radiogenomics provide a large-scale data analytical framework that aims to understand the broad multiscale relationships between the complex information encoded in medical images (including computational, quantitative, and semantic image features) and their underlying clinical, therapeutic, and biological associations. As such it is a powerful and increasingly important tool for both clinicians and researchers involved in the imaging, evaluation, understanding, and management of lung cancers. Herein we provide an overview of the growing field of lung cancer radiogenomics and its applications.

Targeted DNA sequencing of non-small cell lung cancer identifies mutations associated with brain metastases

Introduction

This study explores the hypothesis that dominant molecular oncogenes in non-small cell lung cancer (NSCLC) are associated with metastatic spread to the brain.

Methods

NSCLC patient groups with no evidence of metastasis, with metastatic disease to a non-CNS site, who developed brain metastasis after diagnosis, and patients with simultaneous diagnosis of NSCLC and metastatic brain lesions were studied using targeted sequencing.

Results

In patients with brain metastasis versus those without, only 2 variants (one each in BCL6 and NOTHC2) were identified that occurred in ≥ 4 NSCLC of patients with brain metastases but ≤ 1 of the NSCLC samples without brain metastases. At the gene level, 20 genes were found to have unique variants in more than 33% of the patients with brain metastases. When analyzed at the patient level, these 20 genes formed the basis of a predictive test to discriminate those with brain metastasis. Further analysis showed that PI3K/AKT signaling is altered in both the primary and metastases of NSCLC patients with brain lesions.

Conclusion

While no single variant was associated with brain metastasis, this study describes a potential gene panel for the identification of patients at risk and implicates PI3K/AKT signaling as a therapeutic target.

Characteristics of genomic alterations of lung adenocarcinoma in young never-smokers

Non‐small‐cell lung cancer (NSCLC) has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. While never‐smoker patients with NSCLC have been well studied through next generation sequencing, we have yet to recognize the potentially unique molecular features of young never‐smoker patients with NSCLC. In this study, we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never‐smoker Chinese patients, who were diagnosed with lung adenocarcinoma (LUAD) at 45 years or younger. Besides the well‐known gene mutations (e.g., TP53 and EGFR), our study identified several potential lung cancer‐associated gene mutations that were rarely reported (e.g., HOXA4 and MST1). The lung cancer‐related copy number variations (e.g., EGFR and CDKN2A) were enriched in our cohort (41.7%, 15/36) and the lung cancer‐related structural variations (e.g., EML4‐ALK and KIF5B‐RET) were commonly observed (22.2%, 8/36). Notably, new fusion partners of ALK (SMG6‐ALK) and RET (JMJD1C‐RET) were found. Furthermore, we observed a high prevalence (63.9%, 23/36) of potentially targetable genomic alterations in our cohort. Finally, we identified germline mutations in BPIFB1 (rs6141383, p.V284M), CHD4 (rs74790047, p.D140E), PARP1 (rs3219145, p.K940R), NUDT1 (rs4866, p.V83M), RAD52 (rs4987207, p.S346*), and MFI2 (rs17129219, p.A559T) were significantly enriched in the young never‐smoker patients with LUAD when compared with the in‐house noncancer database (p < 0.05). Our study provides a detailed mutational portrait of LUAD occurring in young never‐smokers and gives insights into the molecular pathogenesis of this distinct subgroup of NSCLC.

What's new?

Young patients with non‐small‐cell lung cancer (NSCLC) represent a distinct disease entity: they are often female, never smoked and usually present with lung adenoma carcinomas. Here the authors performed whole‐genome sequencing in patients with early‐onset NSCLC who never smoked and find an overall lower mutation burden and fewer classic driver substitutions. However, oncogenic fusions were found more frequently, underscoring that a unique molecular make‐up defines this specific subgroup of cancer patients.

miR-96 promotes invasion and metastasis by targeting GPC3 in non-small cell lung cancer cells

Lung cancer is a major cause of death worldwide, and non-small cell lung cancer (NSCLC) is the most common type of lung cancer. The aim of this study was to investigate whether miR-96 mediated the invasion and metastasis of NSCLC by targeting glypican-3 (GPC3). Reverse transcription-quantitative PCR (RT-qPCR) was employed to detect the level of miR-96 and GPC3 mRNA. We applied western blot analysis to measure the protein expression level of GPC3 gene. The luciferase reporter assay was employed to confirm that GPC3 was a target gene of miR-96. The Transwell assay was used to detect migration and invasion. The results revealed that miR-96 was upregulated in NSCLC tissues and lung cancer cells (A549 and H460) compared with corresponding paracancerous tissues and normal epidermic MRC-5 cells. Overexpression of miR-96 promoted invasion and migration in A549 cells. GPC3 was a direct target of miR-96 and regulated by miR-96. GPC3 could reverse partial fuction of miR-96 on proliferation. In conclusion, miR-96 was able to promote the migration and invasion of lung cancer cells by targeting GPC3 gene. The newly identified miR-96/GPC3 axis may provide a therapeutic method for the treatment of NSCLC.

Relationship of SNP rs2645429 in Farnesyl-Diphosphate Farnesyltransferase 1 Gene Promoter with Susceptibility to Lung Cancer

Background and Purpose

The mevalonate pathway is one of the major metabolic pathways that use acetyl-CoA to produce sterols and isoprenoids. These compounds can be effective in the growth and development of tumors. One of the enzymes involved in the mevalonate pathway is FDFT1. Different variants of this gene are involved in the risk of suffering various diseases. The present study examined the relationship between FDFT1 rs2645429 polymorphism and the risk of nonsmall cell lung cancer (NSCLC) in a population from southern Iran.

Method

The genotypes of rs2645429 polymorphism of FDFT1 gene were examined in 95 samples: 34 patients with NSCLC and 61 healthy individuals by RFLP method.

Results

The results of this study indicated that C allele of this polymorphism was effectively associated with the risk of NSCLC in the Iranian population (p value = 0.023; OR = 2.71; 95% CI = 1.12–6.59) and CC genotype has significant relation with susceptibility to NSCLC (p value = 0.029; OR = 3.02; 95% CI = 1.09–8.39). This polymorphism is located in the promoter region FDFT1 gene, and CC genotype may increase the activity of this promoter. This study also found a significant relationship between C allele and metastatic status. C allele was more common in NSCLC patients. (p = 0.04).

Conclusion

C allele of FDFT1 rs2645429 polymorphism gene can be a risk factor for NSCLC, whereas T allele probably has a low protective role.

Clinicopathological significance of CHFR methylation in non-small cell lung cancer: a systematic review and meta-analysis

Checkpoint with Forkhead-associated and Ring finger domains (CHFR) is a G2/M checkpoint and tumor-suppressor gene. Recent publications showed the correlation of CHFR promoter methylation with clinicopathological significance of non-small cell lung cancer (NSCLC), however, the results remain inconsistent. The aim of this study is to investigate the Clinicopathological significance of CHFR promoter methylation in NSCLC with a meta-analysis. A total of nine studies were included in the meta-analysis that 816 patients were involved. Our data indicated that the frequency of CHFR promoter methylation was higher in NSCLC than in normal lung tissue, Odd Ratios (OR) was 9.92 with 95% corresponding confidence interval (CI) 2.17-45.23, p = 0.003. Further subgroup analysis revealed that CHFR promoter was more frequently methylated in squamous cell carcinoma (SCC) than in adenocarcinoma (ADC), OR was 4.46 with 95% CI 1.65-12.05, p = 0.003, suggesting the mechanism of SCC pathogenesis is different from ADC. Notably, CHFR promoter methylation was correlated with smoking behavior in NSCLC. In conclusion, CHFR could be a biomarker for diagnosis of NSCLC, and a promising drug target for development of gene therapy in SCC. CHFR promoter methylation is potentially associated with poor overall survival, additional studies need to be carried out for confirmation in future.

Promoter-level transcriptome in primary lesions of endometrial cancer identified biomarkers associated with lymph node metastasis

For endometrial cancer patients, lymphadenectomy is recommended to exclude rarely metastasized cancer cells. This procedure is performed even in patients with low risk of recurrence despite the risk of complications such as lymphedema. A method to accurately identify cases with no lymph node metastases (LN-) before lymphadenectomy is therefore highly required. We approached this clinical problem by examining primary lesions of endometrial cancers with CAGE (Cap Analysis Gene Expression), which quantifies promoter-level expression across the genome. Fourteen profiles delineated distinct transcriptional networks between LN + and LN- cases, within those classified as having the low or intermediate risk of recurrence. Subsequent quantitative reverse transcription polymerase chain reaction (qRT-PCR) analyses of 115 primary tumors showed SEMA3D mRNA and TACC2 isoforms expressed through a novel promoter as promising biomarkers with high accuracy (area under the receiver operating characteristic curve, 0.929) when used in combination. Our high-resolution transcriptome provided evidence of distinct molecular profiles underlying LN + /LN- status in endometrial cancers, raising the possibility of preoperative diagnosis to reduce unnecessary operations in patients with minimum recurrence risk.

Development of diagnostic model of lung cancer based on multiple tumor markers and data mining

Objective

To develop early intelligent discriminative model of lung cancer and evaluate the efficiency of diagnosis value.

Methods

Based on the genetic polymorphism profile of CYP1A1-rs1048943, GSTM1, mEH-rs1051740, XRCC1-rs1799782 and XRCC1-rs25489 and the methylations of p16 and RASSF1A gene, and the length of telomere in the peripheral blood from 200 lung cancer patients and 200 health persons, the discriminative model was established through decision tree and ANN technique.

Results

ACU of the discriminative model based on multiple tumour markers increased by about 10%; The accuracy rate of decision tree model and ANN model for testing set were 93.00% and 89.62% respectively. The ROC analysis showed the decision tree model’s AUC is 0.929 (0.894∼0.964), the ANN model’s AUC is 0.894 (0.853∼0.935). However, the classify accuracy rate and AUC of Fisher discriminatory analysis model are all about 0.7.

Conclusion

The early intelligent discriminative model of lung cancer based on multiple tumor markers and data mining techniques has a higher accuracy rate and might be useful for early diagnosis of lung cancer.

ANKRD22 promotes progression of non-small cell lung cancer through transcriptional up-regulation of E2F1

Lung cancer is the leading cause of death among all malignancies due to rapid tumor progression and relapse; however, the underlying molecular mechanisms of tumor progression are unclear. In the present study, we identified ANKRD22 as a novel tumor-associated gene in non-small cell lung cancer (NSCLC). According to the clinical correlation analysis, ANKRD22 was highly expressed in primary cancerous tissue compared with adjacent cancerous tissue, and high expression levels of ANKRD22 were significantly correlated with relapse and short overall survival time. Knockdown and overexpression analysis revealed that ANKRD22 promoted tumor progression by increasing cell proliferation. In xenograft assays, knockdown of ANKRD22 or in vivo treatment with ANKRD22 siRNA inhibited tumor growth. Furthermore, ANKRD22 was shown to participate in the transcriptional regulation of E2F1, and ANKRD22 promoted cell proliferation by up-regulating the expression of E2F1 which enhanced cell cycle progression. Therefore, our studies indicated that ANKRD22 up-regulated the transcription of E2F1 and promoted the progression of NSCLC by enhancing cell proliferation. These findings suggest that ANKRD22 could potentially act as a novel therapeutic target for NSCLC.

TRIM59 is a novel potential prognostic biomarker in patients with non-small cell lung cancer: A research based on bioinformatics analysis

Lung cancer is the leading cause of cancer-associated mortality worldwide and its prognosis is poor. Few effective biomarkers for non-small cell lung cancer (NSCLC) have been translated into the clinical practice aiming to assist in the treatment plan design and prognosis evaluation. The aim of the present study was to identify novel potential prognostic biomarkers for NSCLC. Tripartite motif 59 (TRIM59) was identified from a microarray dataset of matched-samples and was verified as an aberrantly upregulated gene in NSCLC tissue. The expression level of TRIM59 in NSCLC subtypes was observed to be significantly increased in large cell lung carcinoma and squamous cell carcinoma as compared with that in adenocarcinoma. Its expression correlated with several clinicopathological features, including gender, smoking habits, and unfavorable tumor node and pathological stages. Notably, TRIM59 demonstrated a negative correlation with survival time and its overexpression indicated a poor prognosis in NSCLC. Furthermore, univariate and multivariate Cox's regression analyses indicated that TRIM59 was an independent prognostic factor in tumor tissue as compared with age, gender, tumor stage, node stage, and metastasis. Gene set enrichment analysis and protein-protein interaction network construction revealed that TRIM59 was associated with oncogenic mammalian target of rapamycin (MTOR) and eukaryotic initiation factor 4E (EIF4E) signaling through ubiquitin C binding. In conclusion, it was revealed that TRIM59 is a novel prognostic biomarker modulating oncogenic MTOR and EIF4E signaling pathways in NSCLC. These findings provided a novel insight into the clinical application of TRIM59. Therefore, TRIM59 may serve as an independent predictor for prognosis and a potential therapeutic target for NSCLC.

Tomorrow's genome medicine in lung cancer

Tomorrow's genome medicine in lung cancer should focus more on the homogeneity and heterogeneity of lung cancer which play an important role in the development of drug resistance, genetic complexity, as well as confusion and difficulty of early diagnosis and therapy. Chromosome positioning and repositioning may contribute to the sensitivity of lung cancer cells to therapy, the heterogeneity associated with drug resistance, and the mechanism of lung carcinogenesis. The CCCTC-binding factor plays critical roles in genome topology and function, increased risk of carcinogenicity, and potential of lung cancer-specific mediations. Chromosome reposition in lung cancer can be regulated by CCCTC binding factor. Single-cell gene sequencing, as part of genome medicine, was paid special attention in lung cancer to understand mechanical phenotypes, single-cell biology, heterogeneity, and chromosome positioning and function of single lung cancer cells. We at first propose to develop an intelligent single-cell robot of human cells to integrate together systems information of molecules, genes, proteins, organelles, membranes, architectures, signals, and functions. It can be a powerful automatic system to assist clinicians in the decision-making, molecular understanding, risk analyzing, and prognosis predicting.