Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk

Jejunal transcriptomic profiling of carnosine synthesis precursor-related genes and pathways in slow-growing Korat chicken

Carnosine is a physiologically important molecule in normal human body functions. Chicken meat is an excellent source of carnosine; especially slow-growing Korat chicken (KR) females have a high carnosine content in their meat. The carnosine content of chicken meat can be increased by dietary supplementation of β-alanine (βA) and L-histidine (L-His). Our objective was to reveal the pathways and genes through jejunal transcriptomic profiling related to βA and L-His absorption and transportation. We collected whole jejunum samples from 5 control and 5 experimental KR chicken, fed with 1% βA and 0.5% L-His supplementation. A total of 407 differentially expressed genes (P < 0.05, log2 fold change ≥2) were identified, 272 of which were down-regulated and 135 up-regulated in the group with dietary supplementation compared to the control group. Based on the integrated analysis of the protein-protein interaction network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway maps, 87 gene ontology terms were identified and 6 KEGG pathways were significantly (P < 0.05) enriched in the jejunum. The analyses revealed 6 key genes, KCND3, OPRM1, CCK, GCG, TRH, and GABBR2, that are related to neuroactive ligand-receptor interaction and the calcium signaling pathway. These findings give insight regarding the molecular mechanism related to carnosine precursor absorption and transportation in the jejunum and help to identify useful molecular markers for improving the carnosine content in slow-growing KR chicken meat.

MIS18A upregulation promotes cell viability, migration and tumor immune evasion in lung adenocarcinoma

Lung adenocarcinoma (LUAD) presents a significant global health challenge owing to its poor prognosis and high mortality rates. Despite its involvement in the initiation and progression of a number of cancer types, the understanding of the precise impact of MIS18 kinetochore protein A (MIS18A) on LUAD remains incomplete. In the present study, the role of MIS18A in LUAD was investigated by analyzing the genomic and clinical data from multiple public datasets. The expression of MIS18A was validated using reverse transcription-quantitative polymerase chain reaction, and in vitro experiments involving small interfering RNA-induced downregulation of MIS18A in lung cancer cells were conducted to further explore its impact. These findings revealed that elevated MIS18A expression in LUAD was associated with advanced clinical features and poor prognosis. Functional analysis also revealed the role of MIS18A in regulating the cell cycle and immune-related pathways. Moreover, MIS18A altered the immune microenvironment in LUAD, influencing its response to immunotherapy and drug sensitivity. The results of the in vitro experiments indicated that suppression of MIS18A expression reduced the proliferative and migratory capacities of LUAD cells. In summary, MIS18A possesses potential as a biomarker and may serve as a possible therapeutic target for LUAD, with significant implications for tumor progression by influencing both cell cycle dynamics and immune infiltration.

Lung Cancer Screening-Trends and Current Studies

Lung cancer is the leading cause of death among all the oncological diseases worldwide. This applies to both women and men; however, the incidence and mortality among women is on the rise. In 2020, lung cancer was responsible for 1.8 million deaths (18%). More than 90% of lung cancer cases and 77.1% of lung cancer deaths occur in countries with high and very high HDI (human development index) values. The aim of our study is to the present trends and most recent studies aimed at lung cancer screening. In the face of the persistently high mortality rate, conducting research aimed at extending already-implemented diagnostic algorithms and behavioural interventions focused on smoking cessation is recommended.

Exploring the Common Genetic Underpinnings of Chronic Pulmonary Disease and Esophageal Carcinoma Susceptibility

Background: Pulmonary diseases and esophageal cancer are highly prevalent conditions with rising incidence worldwide. Prior evidence supports shared environmental and behavioral factors, but less is known regarding potential genetic links underlying this comorbidity. This study aimed to elucidate the complex genetic relationship between chronic lung diseases and esophageal cancer risk. Methods: Linkage disequilibrium score regression assessed the genetic correlation between esophageal cancer and asthma, COPD, and idiopathic pulmonary fibrosis leveraging extensive GWAS datasets. Pleiotropic analysis, gene-set enrichment, eQTL mapping, and mendelian randomization causality analyses were then conducted to identify specific shared genetic variants, enriched pathways, causal relationships and gene regulatory mechanisms connecting lung disease and cancer susceptibility. Results: Significant genetic correlations were observed between esophageal cancer and both COPD and asthma, but not idiopathic pulmonary fibrosis. Further analyses identified 13 pleiotropic loci and 6 shared genes including CHRNA4, ERBB3, and SMAD3, as well as pathways related to immune function. eQTL integration highlighted 53 genes like SOCS1, FGF2, and CHRNA5 with tissue-specific regulatory effects on disease risk. Bidirectional relationships were noted, whereby genetic predisposition to asthma and COPD increased esophageal cancer risk, while cancer liability reciprocally raised pulmonary fibrosis risk. Conclusions: These genomic analyses provide initial evidence that shared genetic factors may underpin the comorbidity between lung conditions and esophageal malignancy. The genes and pathways identified offer insights into biological mechanisms linking both diseases, aiding future screening, prevention and therapeutic efforts to mitigate this growing comorbidity burden.

NEDD1 overexpression increases cell proliferation, tumor immune escape, and drug resistance in LUAD

Background: Neural Precursor Cell Expressed Developmentally Down-Regulated Protein 1 (NEDD1) serves as a crucial factor in promoting cellular mitosis by directly facilitating wheel assembly and daughter centriole biogenesis at the lateral site of parent centrioles, ultimately driving centrosome replication. The amplification of centrosomes and the abnormal expression of centrosome-associated proteins contribute to the invasion and metastasis of non-small cell lung cancer cells. However, the specific mechanism by which NEDD1 contributes to the progression of lung adenocarcinoma (LUAD) remains unexplored. Therefore, the objective of this study is to uncover the role played by NEDD1 in LUAD. Methods: To verify the expression of NEDD1 in pan-carcinoma. The feasibility of NEDD1 as a prognostic marker for LUAD in TCGA and GEO databases was verified. Subsequently, Cox proportional hazard regression analysis was used to screen the prognostic factors of LUAD, so as to analyze the correlation between prognostic factors and NEDD1 expression. For another, NEDD1-related genes were screened for pathway enrichment analysis to verify their possible functions. In addition, the expression of NEDD1 in LUAD was verified by qPCR and IHC, then siRNA was used to construct NEDD1-knocked lung cancer cells for subsequent cytobehavioral experiments. Finally, the distribution of NEDD1 in single-cell samples was revealed, and then the correlation between its overexpression and LUAD immune escape and drug resistance was analyzed. Results: LUAD exhibits upregulation of NEDD1, which in turn promotes the proliferation, migration, invasion, and epithelial-mesenchymal transition of lung cancer cells, thereby contributing to a poor prognosis. Furthermore, the overexpression of NEDD1 is closely associated with immune escape and drug resistance in LUAD. Conclusion: NEDD1 serves as a reliable prognostic marker for LUAD, and its upregulation is associated with increased immune escape and drug resistance. Given these findings, NEDD1 holds potential as a novel therapeutic target for the treatment of LUAD.

Conventional and multi-omics assessments of subacute inhalation toxicity due to propylene glycol and vegetable glycerin aerosol produced by electronic cigarettes

Propylene glycol (PG) and vegetable glycerin (VG) are the most common solvents used in electronic cigarette liquids. No long-term inhalation toxicity assessments have been performed combining conventional and multi-omics approaches on the potential respiratory effects of the solvents in vivo. In this study, the systemic toxicity of aerosol generated from a ceramic heating coil-based e-cigarette was evaluated. First, the aerosol properties were characterized, including carbonyl emissions, the particle size distribution, and aerosol temperatures. To determine toxicological effects, rats were exposed, through their nose only, to filtered air or a propylene glycol (PG)/ glycerin (VG) (50:50, %W/W) aerosol mixture at the target concentration of 3 mg/L for six hours daily over a continuous 28-day period. Compared with the air group, female rats in the PG/VG group exhibited significantly lower body weights during both the exposure period and recovery period, and this was linked to a reduced food intake. Male rats in the PG/VG group also experienced a significant decline in body weight during the exposure period. Importantly, rats exposed to the PG/VG aerosol showed only minimal biological effects compared to those with only air exposure, with no signs of toxicity. Moreover, the transcriptomic, proteomic, and metabolomic analyses of the rat lung tissues following aerosol exposure revealed a series of candidate pathways linking aerosol inhalation to altered lung functions, especially the inflammatory response and disease. Dysregulated pathways of arachidonic acids, the neuroactive ligand-receptor interaction, and the hematopoietic cell lineage were revealed through integrated multi-omics analysis. Therefore, our integrated multi-omics approach offers novel systemic insights and early evidence of environmental-related health hazards associated with an e-cigarette aerosol using two carrier solvents in a rat model.

PLEK2 mediates metastasis and invasion via α5-nAChR activation in nicotine-induced lung adenocarcinoma

Evidence has shown a strong relationship between smoking and epithelial mesenchymal transition (EMT). α5-nicotinic acetylcholine receptor (α5-nAChR) contributes to nicotine-induced lung cancer cell EMT. The cytoskeleton-associated protein PLEK2 is mainly involved in cytoskeletal protein recombination and cell stretch migration regulation, which is closely related to EMT. However, little is known about the link between nicotine/α5-nAChR and PLEK2 in lung adenocarcinoma (LUAD). Here, we identified a link between α5-nAChR and PLEK2 in LUAD. α5-nAChR expression was correlated with PLEK2 expression, smoking status and lower survival in vivo. α5-nAChR mediated nicotine-induced PLEK2 expression via STAT3. α5-nAChR/PLEK2 signaling is involved in LUAD cell migration, invasion and stemness. Moreover, PLEK2 was found to interact with CFL1 in nicotine-induced EMT in LUAD cells. Furthermore, the functional link among α5-nAChR, PLEK2 and CFL1 was confirmed in mouse xenograft tissues and human LUAD tissues. These findings reveal a novel α5-nAChR/PLEK2/CFL1 pathway involved in nicotine-induced LUAD progression.

Screening of Immune-related lncRNAs in Lung Adenocarcinoma and Establishing a Survival Prognostic Risk Prediction Model

OBJECTIVE

This study aimed to improve lung adenocarcinoma (LUAD) prognosis prediction based on a signature of immune-related long non-coding RNAs (lncRNAs).

METHODS

LUAD samples from the TCGA database were divided into the immunity_H group and the immunity_L group. Differentially expressed RNAs (DERs) between the two groups were identified. Optimized immune-related lncRNAs combination was obtained using LASSO Cox regression. A prognostic risk prediction (RS) model was built and further validated in the training and validation datasets. A network among lncRNAs in the RS model, their co-expressed DERs, and the related KEGG pathways were established. Critical lncRNAs were validated in LUAD tissue samples.

RESULTS

In total, 255 DERs were obtained, and 11 immune-related lncRNAs were significantly related to prognosis. Six lncRNAs were demonstrated as an optimal combination for building the RS model, including LINC00944, LINC00930, LINC00607, LINC00582, LINC00543, and LINC00319. The KM curve and ROC curve revealed the RS model to be a reliable indicator for LUAD prognosis. LINC00944 and LINC00582 showed a co-expression relationship with the MS4A1. LINC00944, LINC00582, and MS4A1 were successfully validated in LUAD samples.

CONCLUSION

We have established a promising LUAD patient survival prediction model based on six immune-related lncRNAs. For LUAD patients, this prognostic model could guide personalized treatment.

A real-world study and network pharmacology analysis of EGFR-TKIs combined with ZLJT to delay drug resistance in advanced lung adenocarcinoma

OBJECTIVE

This study aimed to explore the efficacy and safety of combining epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) with ZiLongJin Tablet (ZLJT) in delaying acquired resistance in advanced EGFR-mutant lung adenocarcinoma (LUAD) patients. Furthermore, we employed network pharmacology and molecular docking techniques to investigate the underlying mechanisms.

METHODS

A retrospective comparative study was conducted on stage IIIc/IV LUAD patients treated with EGFR-TKIs alone or in combination with ZLJT at the Second Affiliated Hospital of the Air Force Medical University between January 1, 2017, and May 1, 2023. The study evaluated the onset of TKI resistance, adverse reaction rates, safety indicators (such as aspartate aminotransferase, alanine aminotransferase, and creatinine), and inflammatory markers (neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio) to investigate the impact of EGFR-TKI combined with ZLJT on acquired resistance and prognostic indicators. Additionally, we utilized the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine, PubChem, UniProt, and Swiss Target Prediction databases to identify the active ingredients and targets of ZLJT. We obtained differentially expressed genes related to EGFR-TKI sensitivity and resistance from the Gene Expression Omnibus database using the GSE34228 dataset, which included sensitive (n = 26) and resistant (n = 26) PC9 cell lines. The "limma" package in R software was employed to detect DEGs. Based on this, we constructed a protein‒protein interaction network, performed gene ontology and KEGG enrichment analyses, and conducted pathway network analysis to elucidate the correlation between the active ingredients in ZLJT and signaling pathways. Finally, molecular docking was performed using AutoDockVina, PYMOL 2.2.0, and Discovery Studio Client v19.1.0 software to simulate spatial and energy matching during the recognition process between predicted targets and their corresponding compounds.

RESULTS

(1) A total of 89 patients were included, with 40 patients in the EGFR-TKI combined with ZLJT group (combination group) and 49 patients in the EGFR-TKI alone group (monotherapy group). The baseline characteristics of the two groups were comparable. There was a significant difference in the onset of resistance between the combination group and the monotherapy group (P < 0.01). Compared to the monotherapy group, the combination group showed a prolongation of 3.27 months in delayed acquired resistance. There was also a statistically significant difference in the onset of resistance to first-generation TKIs between the two groups (P < 0.05). (2) In terms of safety analysis, the incidence of adverse reactions related to EGFR-TKIs was 12.5% in the combination group and 14.3% in the monotherapy group, but this difference was not statistically significant (P > 0.05). There were no statistically significant differences in serum AST, ALT, CREA, TBIL, ALB and BUN levels between the two groups after medication (P > 0.05). (3) Regarding inflammatory markers, there were no statistically significant differences in the changes in neutrophil-to-lymphocyte Ratio(NLR) and Platelet-to-lymphocyte Ratio(PLR) values before and after treatment between the two groups (P > 0.05). (4) Network pharmacology analysis identified 112 active ingredients and 290 target genes for ZLJT. From the GEO database, 2035 differentially expressed genes related to resistant LUAD were selected, and 39 target genes were obtained by taking the intersection. A "ZLJT-compound-target-disease" network was successfully constructed using Cytoscape 3.7.0. GO enrichment analysis revealed that ZLJT mainly affected biological processes such as adenylate cyclase-modulating G protein-coupled receptor. In terms of cellular components, ZLJT was associated with the cell projection membrane. The molecular function primarily focused on protein heterodimerization activity. KEGG enrichment analysis indicated that ZLJT exerted its antitumor and anti-drug resistance effects through pathways such as the PI3K-Akt pathway. Molecular docking showed that luteolin had good binding activity with FOS (-9.8 kJ/mol), as did tanshinone IIA with FOS (-9.8 kJ/mol) and quercetin with FOS (-8.7 kJ/mol).

CONCLUSION

ZLJT has potential antitumor progression effects. For patients with EGFR gene-mutated non-small cell LUAD, combining ZLJT with EGFR-TKI treatment can delay the occurrence of acquired resistance. The underlying mechanisms may involve altering signal transduction pathways, blocking the tumor cell cycle, inhibiting tumor activity, enhancing cellular vitality, and improving the bioavailability of combination therapy. The combination of EGFR-TKI and ZLJT represents an effective approach for the treatment of tumors using both Chinese and Western medicine.

Molecular Biomarker Identification Using a Network-Based Bioinformatics Approach That Links COVID-19 With Smoking

The COVID-19 coronavirus, which primarily affects the lungs, is the source of the disease known as SARS-CoV-2. According to "Smoking and COVID-19: a scoping review," about 32% of smokers had a severe case of COVID-19 pneumonia at their admission time and 15% of non-smokers had this case of COVID-19 pneumonia. We were able to determine which genes were expressed differently in each group by comparing the expression of gene transcriptomic datasets of COVID-19 patients, smokers, and healthy controls. In all, 37 dysregulated genes are common in COVID-19 patients and smokers, according to our analysis. We have applied all important methods namely protein-protein interaction, hub-protein interaction, drug-protein interaction, tf-gene interaction, and gene-MiRNA interaction of bioinformatics to analyze to understand deeply the connection between both smoking and COVID-19 severity. We have also analyzed Pathways and Gene Ontology where 5 significant signaling pathways were validated with previous literature. Also, we verified 7 hub-proteins, and finally, we validated a total of 7 drugs with the previous study.

TransOrGAN: An Artificial Intelligence Mapping of Rat Transcriptomic Profiles between Organs, Ages, and Sexes

Animal studies are required for the evaluation of candidate drugs to ensure patient and volunteer safety. Toxicogenomics is often applied in these studies to gain understanding of the underlying mechanisms of toxicity, which is usually focused on critical organs such as the liver or kidney in young male rats. There is a strong ethical reason to reduce, refine and replace animal use (the 3Rs), where the mapping of data between organs, sexes and ages could reduce the cost and time of drug development. Herein, we proposed a generative adversarial network (GAN)-based framework entitled TransOrGAN that allowed the molecular mapping of gene expression profiles in different rodent organ systems and across sex and age groups. We carried out a proof-of-concept study based on rat RNA-seq data from 288 samples in 9 different organs of both sexes and 4 developmental stages. First, we demonstrated that TransOrGAN could infer transcriptomic profiles between any 2 of the 9 organs studied, yielding an average cosine similarity of 0.984 between synthetic transcriptomic profiles and their corresponding real profiles. Second, we found that TransOrGAN could infer transcriptomic profiles observed in females from males, with an average cosine similarity of 0.984. Third, we found that TransOrGAN could infer transcriptomic profiles in juvenile, adult, and aged animals from adolescent animals with an average cosine similarity of 0.981, 0.983, and 0.989, respectively. Altogether, TransOrGAN is an innovative approach to infer transcriptomic profiles between ages, sexes, and organ systems, offering the opportunity to reduce animal usage and to provide an integrated assessment of toxicity in the whole organism irrespective of sex or age.

Robust correlation estimation and UMAP assisted topological analysis of omics data for disease subtyping

Deciphering information hidden in the gene expression assays for identifying disease subtypes has significant importance in precision medicine. However, computational limitations thwart this process due to the intricacy of the biological networks and the curse of dimensionality of gene expression data. Therefore, clustering in such scenarios often becomes the first choice of exploratory data analysis to identify natural structures and intrinsic patterns in the data. However, sparse and high dimensional nature of omics data prevents conventional clustering algorithms to discover subtypes that are clinically relevant and statistically significant. Hence, non-linear dimensionality reduction techniques coupled with clustering in such scenarios often becomes imperative to improve the clustering results. In this study, we present a robust pipeline to discover disease subtypes with clinical relevance. Specifically, we focus on discovering patient sub-groups that have a residual life patterns remarkably different from other sub-groups. This is significant because by refining prognosis, subtyping can reduce uncertainty in approximating patients expected outcome. The methodology present is based on robust correlation estimation, UMAP- a non-linear dimensionality reduction method and mapper- a tool from topology. Notably, we suggest a method for improving the robustness of the correlation matrix of gene expression data for improving the clustering results. The performance of the model is evaluated by applying to five cancer datasets obtained through TCGA and comparisons are performed with some state of the art methods of NEMO, RSC-OTRI and SNF with regard to log-rank test and Restricted Life Expectancy Difference. For example in GBM dataset, the minimum separation for any two discovered subtypes is 221 days which is significantly higher than the other methodologies. We also compared the results without using the robust correlation based estimate and observed that robust correlation improves separability between survival curves significantly. From the results we infer that our methodology performs better compared to other methodologies with regard to separating survival curves of patient sub-groups despite using single omics profiles of patients compared to multiple omics profiles of SNF and NEMO. Pathway over-representation analysis is performed on the final clustering results to investigate the biological underpinnings characterizing each subtype.

Global burden of cancers attributable to tobacco smoking, 1990-2019: an ecological study

Aim and background

Identifying risk factors for cancer initiation and progression is the cornerstone of the preventive approach to cancer management and control (EPMA J. 4(1):6, 2013). Tobacco smoking is a well-recognized risk factor for initiation and spread of several cancers. The predictive, preventive, and personalized medicine (PPPM) approach to cancer management and control focuses on smoking cessation as an essential cancer prevention strategy. Towards this end, this study examines the temporal patterns of cancer burden due to tobacco smoking in the last three decades at global, regional, and national levels.

Data and methods

The data pertaining to the burden of 16 cancers attributable to tobacco smoking at global, regional, and national levels were procured from the Global Burden of Disease 2019 Study. Two main indicators, deaths and disability-adjusted life years (DALYs), were used to describe the burden of cancers attributable to tobacco smoking. The socio-economic development of countries was measured using the socio-demographic index (SDI).

Results

Globally, deaths due to neoplasms caused by tobacco smoking increased from 1.5 million in 1990 to 2.5 million in 2019, whereas the age-standardized mortality rate (ASMR) decreased from 39.8/100,000 to 30.6/100,000 and the age-standardized DALY rate (ASDALR) decreased from 948.9/100,000 to 677.3/100,000 between 1990 and 2019. Males accounted for approximately 80% of global deaths and DALYs in 2019. Populous regions of Asia and a few regions of Europe account for the largest absolute burden, whereas countries in Europe and America have the highest age-standardized rates of cancers due to tobacco smoking. In 8 out of 21 regions, there were more than 100,000 deaths due to cancers attributable to tobacco smoking led by East Asia, followed by Western Europe in 2019. The regions of Sub-Saharan Africa (except southern region) had one of the lowest absolute counts of deaths, DALYs, and age-standardized rates. In 2019, tracheal, bronchus, and lung (TBL), esophageal, stomach, colorectal, and pancreatic cancer were the top 5 neoplasms attributable to tobacco smoking, with different burdens in regions as per their development status. The ASMR and ASDALR of neoplasms due to tobacco smoking were positively correlated with SDI, with pairwise correlation coefficient of 0.55 and 0.52, respectively.

Conclusion

As a preventive tool, tobacco smoking cessation has the biggest potential among all risk factors for preventing millions of cancer deaths every year. Cancer burden due to tobacco smoking is found to be higher in males and is positively associated with socio-economic development of countries. As tobacco smoking begins mostly at younger ages and the epidemic is unfolding in several parts of the world, more accelerated efforts are required towards tobacco cessation and preventing youth from entering this addiction. The PPPM approach to medicine suggests that not only personalized and precision medicine must be provided to cancer patients afflicted by tobacco smoking but personalized and targeted preventive solutions must be provided to prevent initiation and progression of smoking.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00308-y.

Screening and identification of hub-gene associated with brain metastasis in breast cancer

BACKGROUND

The presence of breast cancer in the brain, also known as brain metastasis (BMS), is the primary reason for a bad prognosis in cases of breast cancer. Breast cancer is the most prevalent malignant tumor seen in women in developing nations. At present, there is no effective method to inhibit brain metastasis of breast cancer. Therefore, it is necessary to conduct a systematic study on BMS of breast cancer, which will not provide ideas and sites for follow-up studies on the treatment and inhibition of BMS.

METHODS

In this study, data set GSE43837 was screened from gene expression omnibus database, and then R language tool was used for differential analysis of its expression spectrum, The gene ontology functional enrichment and Kyoto encyclopedia of genes and genomes signal pathway enrichment analyses, as well as the interactive gene retrieval tool for hub-gene analysis, were performed.

RESULTS

According to the findings, the primary genes linked to breast cancer brain metastases are those that involve interactions between cytokines and their respective receptors and between neuroactive ligands and their respective receptors. The majority of the gene ontology enrichment took place in the extracellular structural tissues, the extracellular matrix tissues, and the second message-mediated signaling. We were able to identify 8 genes that are linked to breast cancer spreading to the brain. The gene score for matrix metallopeptidase1 (MMP-1) was the highest among them, and the genes MMP10, tumor necrosis factor alpha-inducible protein 8, collagen type I alpha 2 chain, vascular cell adhesion molecule 1, and TNF superfamily member 11 were all connected to 1 another in an interaction way.

CONCLUSIONS

There is a possibility that the 8 key genes that were identified in this research are connected to the progression of BMS in breast cancer. Among them, MMP1 is 1 that has the potential to have a role in the diagnosis and treatment of BMS in breast cancer.

Non-Invasive Biomarkers for Early Lung Cancer Detection

Worldwide, lung cancer (LC) is the most common cause of cancer death, and any delay in the detection of new and relapsed disease serves as a major factor for a significant proportion of LC morbidity and mortality. Though invasive methods such as tissue biopsy are considered the gold standard for diagnosis and disease monitoring, they have several limitations. Therefore, there is an urgent need to identify and validate non-invasive biomarkers for the early diagnosis, prognosis, and treatment of lung cancer for improved patient management. Despite recent progress in the identification of non-invasive biomarkers, currently, there is a shortage of reliable and accessible biomarkers demonstrating high sensitivity and specificity for LC detection. In this review, we aim to cover the latest developments in the field, including the utility of biomarkers that are currently used in LC screening and diagnosis. We comment on their limitations and summarise the findings and developmental stages of potential molecular contenders such as microRNAs, circulating tumour DNA, and methylation markers. Furthermore, we summarise research challenges in the development of biomarkers used for screening purposes and the potential clinical applications of newly discovered biomarkers.

Development and validation of a prognostic 9-gene signature for colorectal cancer

Introduction

Colorectal cancer (CRC) is one of the most prevalent cancers globally with a high mortality rate. Predicting prognosis using disease progression and cancer pathologic stage is insufficient, and a prognostic factor that can accurately evaluate patient prognosis needs to be developed. In this study, we aimed to infer a prognostic gene signature to identify a functional signature associated with the prognosis of CRC patients.

Methods

First, we used univariate Cox regression, least absolute shrinkage and selection operator (lasso) regression, and multivariate Cox regression analyses to screen genes significantly associated with CRC patient prognosis, from colorectal cancer RNA sequencing data in The Cancer Genome Atlas (TCGA) database. We then calculated the risk score (RS) for each patient based on the expression of the nine candidate genes and developed a prognostic signature.

Results

Based on the optimal cut-off on the receiver operating characteristic (ROC) curve, patients were separated into high- and low-risk groups, and the difference in overall survival between the two groups was examined. Patients in the low-risk group had a better overall survival rate than those in the high-risk group. The results were validated using the GSE72970, GSE39582, and GSE17536 Gene Expression Omnibus (GEO) datasets, and the same conclusions were reached. ROC curve test of the RS signature also indicated that it had excellent accuracy. The RS signature was then compared with traditional clinical factors as a prognostic indicator, and we discovered that the RS signature had superior predictive ability.

Conclusion

The RS signature developed in this study has excellent predictive power for the prognosis of patients with CRC and broad applicability as a prognostic indicator for patients.

Functional studies of lung cancer GWAS beyond association

Fourteen years after the first genome-wide association study (GWAS) of lung cancer was published, approximately 45 genomic loci have now been significantly associated with lung cancer risk. While functional characterization was performed for several of these loci, a comprehensive summary of the current molecular understanding of lung cancer risk has been lacking. Further, many novel computational and experimental tools now became available to accelerate the functional assessment of disease-associated variants, moving beyond locus-by-locus approaches. In this review, we first highlight the heterogeneity of lung cancer GWAS findings across histological subtypes, ancestries and smoking status, which poses unique challenges to follow-up studies. We then summarize the published lung cancer post-GWAS studies for each risk-associated locus to assess the current understanding of biological mechanisms beyond the initial statistical association. We further summarize strategies for GWAS functional follow-up studies considering cutting-edge functional genomics tools and providing a catalog of available resources relevant to lung cancer. Overall, we aim to highlight the importance of integrating computational and experimental approaches to draw biological insights from the lung cancer GWAS results beyond association.

From COPD to Lung Cancer: Mechanisms Linking, Diagnosis, Treatment, and Prognosis

Many studies have proved that the pathogenesis of the chronic obstructive pulmonary disease (COPD) and lung cancer is related, and may cause and affect each other to a certain extent. In fact, the change of chronic airway obstruction will continue to have an impact on the screening, treatment, and prognosis of lung cancer.In this comprehensive review, we outlined the links and heterogeneity between COPD and lung cancer and finds that factors such as gene expression and genetic susceptibility, epigenetics, smoking, epithelial mesenchymal transformation (EMT), chronic inflammation, and oxidative stress injury may all play a role in the process. Although the relationship between these two diseases have been largely determined, the methods to prevent lung cancer in COPD patients are still limited. Early diagnosis is still the key to a better prognosis. Thus, it is necessary to establish more intuitive screening evaluation criteria and find suitable biomarkers for lung cancer screening in high-risk populations with COPD. Some studies have indicated that COPD may change the efficacy of anti-tumor therapy by affecting the response of lung cancer patients to immune checkpoint inhibitors (ICIs). And for lung cancer patients with COPD, the standardized management of COPD can improve the prognosis. The treatment of lung cancer patients with COPD is an individualized, comprehensive, and precise process. The development of new targets and new strategies of molecular targeted therapy may be the breakthrough for disease treatment in the future.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

INTRODUCTION

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

METHODS

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

RESULTS

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

CONCLUSIONS

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges

Advancements in the development of computer-aided decision (CAD) systems for clinical routines provide unquestionable benefits in connecting human medical expertise with machine intelligence, to achieve better quality healthcare. Considering the large number of incidences and mortality numbers associated with lung cancer, there is a need for the most accurate clinical procedures; thus, the possibility of using artificial intelligence (AI) tools for decision support is becoming a closer reality. At any stage of the lung cancer clinical pathway, specific obstacles are identified and "motivate" the application of innovative AI solutions. This work provides a comprehensive review of the most recent research dedicated toward the development of CAD tools using computed tomography images for lung cancer-related tasks. We discuss the major challenges and provide critical perspectives on future directions. Although we focus on lung cancer in this review, we also provide a more clear definition of the path used to integrate AI in healthcare, emphasizing fundamental research points that are crucial for overcoming current barriers.

Gene-gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

BACKGROUND

Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.

AIM

To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.

METHODS

Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.

RESULTS

No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR  = 1.20; 95% CI 1.13-1.27; p  = 5.6 × 10-10) and never smokers (e.g., maker rs1133683 Axin2; OR  = 1.27; 95% CI 1.19-1.35; p  = 1.0 × 10-12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.

CONCLUSIONS

The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.

Long Non-coding RNAs Gabarapl2 and Chrnb2 Positively Regulate Inflammatory Signaling in a Mouse Model of Dry Eye

Purpose: To elucidate the expression profile and the potential role of long non-coding ribonucleic acids (RNAs) (lncRNAs) in a dry eye disease (DED) model.

Methods: A DED model was established in C57BL/6J mice with 0.2% benzalkonium chloride (BAC) twice a day for 14 days. The differentially expressed lncRNAs were detected by RNA-seq technology (Gene Expression Omnibus, GEO GSE186450) and the aberrantly expressed lncRNAs were further verified by RT-qPCR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to predicate the related candidate genes and potential pathological pathways. Cells from a human corneal epithelial cell line (HCECs) were cultured under hyperosmolarity. The regulation of inflammatory factors by silencing potential targeted lncRNAs was verified in vitro in HCECs.

Results: In our study, a significant increase in corneal fluorescence staining and a reduction in tear production were observed in DED mice at all follow-ups compared with the controls, and the differences were increasing over time. In total, 2,649 upregulated and 704 downregulated lncRNAs were identified in DED mice. We selected six aberrantly expressed and most abundant lncRNAs and performed RT-qPCR using the samples for RNA-seq. Chrnb2, Gabarapl2, and Usp31 were thereby confirmed as the most significantly altered lncRNAs. Pathway analysis revealed that the neuroactive ligand–receptor interaction signaling pathway was the most enriched, followed by the calcium signaling pathway and cytokine–cytokine receptor interaction. Following treatment of Gabarapl2 siRNA and Chrnb2 siRNA, tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 were significantly downregulated in the HCECs.

Conclusion: Our study suggests that Chrnb2 and Gabarapl2 may be involved in the inflammation response by regulating TNF-α, IL-1β, and IL-6 in DED. These candidate lncRNAs may be both potential biomarkers and therapeutic targets for DED.

Gene regulatory networks analysis of muscle-invasive bladder cancer subtypes using differential graphical model

BACKGROUND

Recently, erdafitinib (Balversa), the first targeted therapy drug for genetic alteration, was approved to metastatic urothelial carcinoma. Cancer genomics research has been greatly encouraged. Currently, a large number of gene regulatory networks between different states have been constructed, which can reveal the difference states of genes. However, they have not been applied to the subtypes of Muscle-invasive bladder cancer (MIBC).

RESULTS

In this paper, we propose a method that construct gene regulatory networks under different molecular subtypes of MIBC, and analyse the regulatory differences between different molecular subtypes. Through differential expression analysis and the differential network analysis of the top 100 differential genes in the network, we find that SERPINI1, NOTUM, FGFR1 and other genes have significant differences in expression and regulatory relationship between MIBC subtypes.

CONCLUSIONS

Furthermore, pathway enrichment analysis and differential network analysis demonstrate that Neuroactive ligand-receptor interaction and Cytokine-cytokine receptor interaction are significantly enriched pathways, and the genes contained in them are significant diversity in the subtypes of bladder cancer.

The effect of CHRNA3 rs1051730 C>T and ABCB1 rs3842 A>G polymorphisms on non-small cell lung cancer and nicotine dependence in Iranian population

Aims

Lung cancer is still the leading cause of cancer mortality in all over the world. Nicotine and its derivatives are the most well-known carcinogens that participate in both etiology and progression of lung cancer. The objective of the current study was to investigate whether single nucleotide polymorphisms (SNPs) rs1051730C > T in CHRNA3 and rs3842A > G in ABCB1, two genes contributing in the mechanism of disposition and metabolism of nicotine and its derivatives, could modify the risk of developing lung cancer, as well as nicotine dependence in Iranian.

Main methods

The genotyping analysis for these two SNPs was conducted in a case-control study of 108 lung cancer cases and 120 healthy controls using ARMS-PCR and Tetra-primer ARMS-PCR techniques. The correlation between studied SNPs and lung cancer was assessed by the regression analysis.

Key findings

We observed a significant association between lung cancer and rs1051730C > T by using four genetic models: allele (OR:1.83; 95% CI:1.24-2.6; p = 0.002), dominant (OR: 2.19; 95% CI:1.27-3.78; p = 0.005), recessive (OR: 2.25; 95% CI: 1.02-4.95; p = 0.043) and additive (TT vs CC: OR:3.25; 95% CI:1.38-7.60; p = 0.007, CT vs CC: OR:1.96; 95% CI:1.10-3.48; p = 0.021). Furthermore, a significant association between this variant and nicotine dependence (OR: 2.27; 95% CI: 1.52-3.39; p = 0.00005) was reported. However, no association was found for rs3842A > G.

Significance

The results suggested that the CHRNA3 rs1051730C > T via a smoking-dependent manner could modify susceptibility to lung cancer among Iranian population.

Multiplex genome editing in Arabidopsis thaliana using Mb3Cas12a

The use of CRISPR-Cas proteins for the creation of multiplex genome engineering represents an important avenue for crop improvement, and further improvements for creation of knock-in plant lines via CRISPR-based technologies may enable the high-throughput creation of designer alleles. To circumvent limitations of the commonly used CRISPR-Cas9 system for multiplex genome engineering, we explored the use of Moraxella bovoculi 3 Cas12a (Mb3Cas12a) for multiplex genome editing in Arabidopsis thaliana. We identified optimized cis-regulatory sequences for driving expression of single-transcript multiplex crRNA arrays in A. thaliana, resulting in stable germline transmission of Mb3Cas12a-edited alleles at multiple target sites. By utilizing this system, we demonstrate single-transcript multiplexed genome engineering using of up to 13 crRNA targets. We further show high target specificity of Mb3Cas12a-based genome editing via whole-genome sequencing. Taken together, our method provides a simplified platform for efficient multiplex genome engineering in plant-based systems.

Genetic analysis of colorectal carcinoma using high throughput single nucleotide polymorphism genotyping technique within the population of Jammu and Kashmir

BACKGROUND

SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through MassARRAY™ is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis.

METHODS

In the present study, SNP genotyping was carried out using Agena MassARRAY™, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature.

RESULTS

This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, five SNPs rs2234593, rs1799966, rs2229080, rs8034191, rs1042522 were found to be significantly associated with the current study under the allelic model with an Odds Ratio OR = 2.981(1.731-5.136 at 95% CI); p value = 4.81E-05 for rs2234593,OR = 1.685(1.073-2.647 at 95% CI);; p value = 0.02292 for rs1799966, OR = 1.5 (1.1-2.3 at 95% CI), p value = 0.02 for rs2229080, OR = 1.699(1.035-2.791 at 95% CI); p value = 0.03521 for rs8034191, OR = 20.07 (11.26-35.75); p value = 1.84E-34 for rs1042522 respectively.

CONCLUSION

This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput MassARRAY™ technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

MiR-3130-5p is an intermediate modulator of 2q33 and influences the invasiveness of lung adenocarcinoma by targeting NDUFS1

Genome‐wide association studies (GWAS) have reported a handful of loci associated with lung cancer risk, of which the pathogenic pathways are largely unknown. We performed cis‐expression quantitative trait loci (eQTL) mapping for 376 lung cancer related GWAS loci in 227 TCGA lung adenocarcinoma (LUAD) and reported two risk loci as eQTL of miRNA. Among the miRNAs in association with lung cancer risk, we further predicted and validated miR‐3130‐5p as an intermediate modulator of risk loci 2q33 and the tumor suppressor NDUFS1. We assessed the phenotypic impacts of the interaction between miR‐3130‐5p and NDUFS1 in both lung cancer cell lines and mice xenograft models. As a result, miR‐3130‐5p directly regulates the expression of NDUFS1 and the corresponding tumor invasiveness, migration and epithelial‐mesenchymal transition (EMT). Our findings provide important clues for the pathogenic mechanism of 2q33 in lung carcinogenesis which informs clinical diagnosis and prognosis of LUAD.

We performed a cis‐eQTL analysis for 376 lung cancer risk loci based on the expression profiles of 251 miRNAs in a cohort of 227 TCGA lung adenocarcinoma. We report a novel pathogenic pathway of 2q33 via miR‐3130‐5p and NDUFS1.

Characteristic Volatile Composition of Seven Seaweeds from the Yellow Sea of China

Plant volatile organic compounds (VOCs) represent a relatively wide class of secondary metabolites. The VOC profiles of seven seaweeds (Grateloupia filicina, Polysiphonia senticulosa, Callithamnion corymbosum, Sargassum thunbergii, Dictyota dichotoma, Enteromorpha prolifera and Ulva lactuca) from the Yellow Sea of China were investigated using multifiber headspace solid phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS), among them, the VOCs of three red algae Grateloupia filicina, Polysiphonia senticulosa, and Callithamnion corymbosum were first reported. Principal component analysis (PCA) was used to disclose characteristic categories and molecules of VOCs and network pharmacology was performed to predict potential biomedical utilization of candidate seaweeds. Aldehyde was found to be the most abundant VOC category in the present study and (E)-β-ionone was the only compound found to exist in all seven seaweeds. The chemical diversity of aldehydes in E. prolifera suggest its potential application in chemotaxonomy and hinted that divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber is more suitable for aldehyde extraction. VOCs in D. dichotoma were characterized as sesquiterpenes and diterpenes and the most relevant pharmacological pathway was the neuroactive ligand–receptor interaction pathway, which suggests that D. dichotoma may have certain preventive and therapeutic values in cancer, especially in lung cancer, in addition to neuropsychiatric diseases.

Effect of Carbon Ion Radiation Induces Bystander Effect on Metastasis of A549 Cells and Metabonomic Correlation Analysis

Objective

To analyze the effect of carbon ion (¹²C⁶⁺) radiation may induce bystander effect on A549 cell metastasis and metabonomics.

Methods

A549 cell was irradiated with carbon ion to establish the clone survival model and the transwell matrix assay was applied to measure the effect of carbon ion on cell viability, migration, and invasion, respectively. Normal human embryonic lung fibroblasts (WI-38) were irradiated with carbon ions of 0 and 2 Gy and then transferred to A549 cell co-culture medium for 24 h. The migration and invasion of A549 cells were detected by the Transwell chamber. The analysis of metabonomic information in transfer medium by liquid phase mass spectrometry (LC-MS), The differential molecules were obtained by principal pomponent analysis (PCA) and the target proteins of significant differences (p = 1.7 × 10⁻³) obtained by combining with the STICH database. KEGG pathway was used to analyze the enrichment of the target protein pathway.

Results

Compared with 0 Gy, the colony formation, migration, and invasion of A549 cells were significantly inhibited by carbon ion 2 and 4 Gy irradiation, while the inhibitory effect was not significant after 1 Gy irradiation. Compared with 0 Gy, the culture medium 24 h after carbon ion 2 Gy irradiation significantly inhibited the metastasis of tumor cells (p = 0.03). LC-MS analysis showed that 23 differential metabolites were obtained in the cell culture medium 24 h after carbon ion 0 and 2 Gy irradiation (9 up-regulated and 14 down-regulated). Among them, two were up-regulated and two down-regulated (p = 2.9 × 10⁻³). 41 target proteins were corresponding to these four differential molecules. Through the analysis of the KEGG signal pathway, it was found that these target molecules were mainly enriched in purine metabolism, tyrosine metabolism, cysteine and methionine metabolism, peroxisome, and carbon metabolism. Neuroactive ligand-receptor interaction, calcium signaling pathway, arachidonic acid metabolism, and Fc epsilon RI signaling pathway.

Conclusion

The bystander effect induced by 2 Gy carbon ion radiation inhibits the metastasis of tumor cells, which indicates that carbon ions may change the metabolites of irradiated cells, so that it may indirectly affect the metabolism of tumor cell growth microenvironment, thus inhibiting the metastasis of malignant tumor cells.

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

Rare deleterious germline variants and risk of lung cancer

Recent studies suggest that rare variants exhibit stronger effect sizes and might play a crucial role in the etiology of lung cancers (LC). Whole exome plus targeted sequencing of germline DNA was performed on 1045 LC cases and 885 controls in the discovery set. To unveil the inherited causal variants, we focused on rare and predicted deleterious variants and small indels enriched in cases or controls. Promising candidates were further validated in a series of 26,803 LCs and 555,107 controls. During discovery, we identified 25 rare deleterious variants associated with LC susceptibility, including 13 reported in ClinVar. Of the five validated candidates, we discovered two pathogenic variants in known LC susceptibility loci, ATM p.V2716A (Odds Ratio [OR] 19.55, 95%CI 5.04-75.6) and MPZL2 p.I24M frameshift deletion (OR 3.88, 95%CI 1.71-8.8); and three in novel LC susceptibility genes, POMC c.*28delT at 3' UTR (OR 4.33, 95%CI 2.03-9.24), STAU2 p.N364M frameshift deletion (OR 4.48, 95%CI 1.73-11.55), and MLNR p.Q334V frameshift deletion (OR 2.69, 95%CI 1.33-5.43). The potential cancer-promoting role of selected candidate genes and variants was further supported by endogenous DNA damage assays. Our analyses led to the identification of new rare deleterious variants with LC susceptibility. However, in-depth mechanistic studies are still needed to evaluate the pathogenic effects of these specific alleles.

The relationship between CHRNA5/A3/B4 gene cluster polymorphisms and lung cancer risk: An updated meta-analysis and systematic review

BACKGROUND

Genetic polymorphisms in the 15q25 region have been associated with the risk of lung cancer (LC). However, studies have yielded conflicting results.

METHODS

Searches were conducted in databases, including PubMed, EMbase, Web of Science, CNKI, and Wanfang, for case-control studies up to August 1, 2019. After retrieving eligible studies and data extraction, we calculated pooled odds ratios with 95% confidence intervals. In the meta-analysis, we included 32 publications with a total of 52,795 patients with LC and 97,493 control cases to evaluate the polymorphisms in the CHRNA5/A3/B4 gene cluster in the 15q25 region.

RESULTS

Data of the meta-analysis showed a significantly increased risk of LC in the presence of genetic polymorphisms (rs1051730, rs16969968, rs8034191). In the smoking subgroup, the CHRNA3 rs1051730 polymorphism was found to contribute to LC risk using following 5 models: the allelic model, the homozygous model, the heterozygous model, the dominant model, and the recessive model. Thus, the rs1051730 polymorphism may modify LC susceptibility under the condition of smoking. Stratification studies for CHRNA5-rs8034191 showed that Caucasian groups with the wild-type genotype (C/C) may be susceptible to LC in all 5 models. No significant relationship between CHRNA3 rs6495309 or rs3743073 and LC susceptibility was found. However, Asians with the rs3743037 B-allele showed an obviously higher risk of LC susceptibility than the Caucasian population, observed via allelic, heterozygous, and dominant models.

CONCLUSIONS

The 3 polymorphisms of rs1051730, rs16969968 and rs8034191 in the CHRNA5/A3/B4 gene cluster in the 15q25 region were associated with LC risk, which might be influenced by ethnicity and smoking status.

Detecting rare haplotype association with two correlated phenotypes of binary and continuous types

Multiple correlated traits/phenotypes are often collected in genetic association studies and they may share a common genetic mechanism. Joint analysis of correlated phenotypes has well-known advantages over one-at-a-time analysis including gain in power and better understanding of genetic etiology. However, when the phenotypes are of discordant types such as binary and continuous, the joint modeling is more challenging. Another research area of current interest is discovery of rare genetic variants. Currently there is no method available for detecting association of rare (or common) haplotypes with multiple discordant phenotypes jointly. Our goal is to fill this gap specifically for two discordant phenotypes. We consider a rare haplotype association method for a binary phenotype, logistic Bayesian LASSO (univariate LBL) and its extension for two correlated binary phenotypes (bivariate LBL-2B). Under this framework, we propose a haplotype association test with binary and continuous phenotypes jointly (bivariate LBL-BC). Specifically, we use a latent variable to induce correlation between the two phenotypes. We carry out extensive simulations to investigate bivariate LBL-BC and compare it with univariate LBL and bivariate LBL-2B. In most settings, bivariate LBL-BC performs the best. In only two situations, bivariate LBL-BC has similar performance-when the two phenotypes are (1) weakly or not correlated and the target haplotype affects the binary phenotype only and (2) strongly positively correlated and the target haplotype affects both phenotypes in positive direction. Finally, we apply the method to a data set on lung cancer and nicotine dependence and detect several haplotypes including a rare one.

Investigation of Candidate Genes and Pathways in Basal/TNBC Patients by Integrated Analysis

PURPOSE

This study aims to identify the key pathway and related genes and to further explore the potential molecular mechanisms of triple negative breast cancer (TNBC).

METHODS

The transcriptome data and clinical information of breast cancer patients were downloaded from the TCGA database, including 94 cases of paracancerous tissue, 225 cases of Basal like type, 151 cases of Her2 type, 318 cases of Luminal type A, 281 cases of Luminal type B, and 89 cases of Normal Like type. The differentially expressed genes (DEGs) were identified based on the criteria of |logFC|≥1.5 and adjust P < 0.001.Their functions were annotated by gene ontology (GO) analysis and Kyoto Encyclopedia of differentially expressed genes & Genomes (KEGG) pathway analysis. Cox regression univariate analysis and Kaplan-Meier survival curves (Log-rank method) were used for survival analysis. FOXD1, DLL3 and LY6D were silenced in breast cancer cell lines, and cell viability was assessed by CCK-8 assay. Further, the expression of FOXD1, DLL3 and LY6D were explored by immunohistochemistry on triple negative breast tumor tissue and normal breast tissue.

RESULTS

A total of 533 DEGs were identified. Functional annotation showed that DEGs were significantly enriched in intermediate filament cytoskeleton, DNA-binding transcription activator activity, epidermis development, and Neuroactive ligand-receptor interaction. Survival analysis found that FOXD1, DLL3, and LY6D showed significant correlation with the prognosis of patients with the Basal-like type (P < 0.05). CCK-8 assay showed that compared with Doxorubicin alone group, the cytotoxicity of Doxorubicin combined with siRNA-knockdown of FOXD1, DLL3, or LY6D was much significant.

CONCLUSION

The DEGs and their enriched functions and pathways identified in this study contribute to the understanding of the molecular mechanisms of TNBC. In addition, FOXD1, DLL3, and LY6D may be defined as the prognostic markers and potential therapeutic targets for TNBC patients.

Integrating GWAS and eQTL to predict genes and pathways for non-syndromic cleft lip with or without palate

OBJECTIVE

To explore susceptibility genes and pathways for non-syndromic cleft lip with or without cleft palate (NSCL/P).

MATERIALS AND METHODS

Two genome-wide association studies (GWAS) datasets, including 858 NSCL/P cases and 1,248 controls, were integrated with expression quantitative trait loci (eQTL) dataset identified by Genotype-Tissue Expression (GTEx) project in whole-blood samples. The expression of the candidate genes in mouse orofacial development was inquired from FaceBase. Protein-protein interaction (PPI) network was visualized to identify protein functions. Go and KEGG pathway analyses were performed to explore the underlying risk pathways.

RESULTS

A total of 233 eQTL single-nucleotide polymorphisms (SNPs) in 432 candidate genes were identified to be associated with the risk of NSCL/P. One hundred and eighty-three susceptible genes were expressed in mouse orofacial development according to FaceBase. PPI network analysis highlighted that these genes involved in ubiquitin-mediated proteolysis (KCTD7, ASB1, UBOX5, ANAPC4) and DNA synthesis (XRCC3, RFC3, KAT5, RHNO1) were associated with the risk of NSCL/P. GO and KEGG pathway analyses revealed that the fatty acid metabolism pathway (ACADL, HSD17B12, ACSL5, PPT1, MCAT) played an important role in the development of NSCL/P.

CONCLUSIONS

Our results identified novel susceptibility genes and pathways associated with the development of NSCL/P.

Potential Genes Associated with the Survival of Lung Adenocarcinoma Were Identified by Methylation

Background

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. The purpose of this study is to search for genes related to the prognosis of LUAD through methylation based on a linear mixed model (LMM).

Methods

Gene expression, methylation, and survival data of LUAD patients were downloaded from the TCGA database. Based on the LMM model, the GEMMA algorithm was used to screen the predictive genes related to LUAD survival. The Cox model was used to further screen the predicted genes, and then, protein-protein interaction (PPI) network was constructed. Through the software plugin Cytoscape MCODE 3.8.0, the most closely related genes in the PPI network module were selected for in-depth biological function analysis to further explore the interaction and correlation between genes.

Results

We screened out 97 predictive genes from 18,834 genes and eliminated one gene associated with lung squamous cell carcinoma from previous studies, leaving 96 genes. The MCODE and the Kaplan-Meier curve analysis were used to finally identify two genes ASB16 and NEDD4 that are related to the prognosis of LUAD.

Conclusions

The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients.

Polymorphisms of xenobiotic-metabolizing and transporter genes, and the risk of gastric and colorectal cancer in an admixed population from the Brazilian Amazon

Colorectal (CRC) and gastric (GC) cancers are associated with increased morbidity and mortality. Single nucleotide polymorphisms (SNPs) of xenobiotic metabolism and transporter genes may play a role in the individual responses to exposure to substances implicated in susceptibility to cancer. The investigation of the genetic variation related to the activation and detoxification of xenobiotics may thus help to clarify the prevalence of neoplasms. We analyzed the role of 30 SNPs in xenobiotic-metabolizing and transporter genes in susceptibility to CRC and GC. The study included individuals diagnosed with CRC (n = 121) and GC (n = 95), and 141 controls (non-cancer patients) from the population of Belém, in the Brazilian Amazon. The results indicated an association between the polymorphisms rs2231142 (P = 0.013; OR = 3.01; 95% CI = 1.26-7.13), in the ABCG2 gene, and rs1801159 (P = 0.03; OR = 2.35; 95% CI = 1.14-5.05), in DPYD gene, with the risk of developing GC. The polymorphism rs17116806 of the DPYD gene was found to be associated with a lower risk of developing gastric (P≤0.0001; OR = 0.043; 95% CI = 0.015-0.12) or colorectal (P≤0.0001; OR = 0.076; 95% CI = 0.33-0.18) cancers, indicating that the same variant may play a similar role in different types of cancer tissue. Additionally, the carriers of the TT genotype of the polymorphism in the ABCB1 gene (rs1128503) presented a reduced probability of developing CRC (P = 0.0001; OR = 0.16; 95% CI = 0.06-0.41) as well as GC (P = 0.007; OR = 0.27; 95% CI = 0.1-0.7). Our findings indicate that polymorphisms in xenobiotic-metabolizing and transporter genes may modulate susceptibility to colorectal and gastric cancers.

Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint inhibitors has led to improved survival outcomes for patients with advanced-stage lung cancer; however, this disease remains the leading cause of cancer-related mortality worldwide. Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening in high-risk populations - the US National Lung Screening Trial (NLST) and NELSON - have provided evidence of a statistically significant mortality reduction in patients. LDCT-based screening programmes for individuals at a high risk of lung cancer have already been implemented in the USA. Furthermore, implementation programmes are currently underway in the UK following the success of the UK Lung Cancer Screening (UKLS) trial, which included the Liverpool Health Lung Project, Manchester Lung Health Check, the Lung Screen Uptake Trial, the West London Lung Cancer Screening pilot and the Yorkshire Lung Screening trial. In this Review, we focus on the current evidence on LDCT-based lung cancer screening and discuss the clinical developments in high-risk populations worldwide; additionally, we address aspects such as cost-effectiveness. We present a framework to define the scope of future implementation research on lung cancer screening programmes referred to as Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL).

Integrated Microarray and RNAseq Transcriptomic Analysis of Retinal Pigment Epithelium/Choroid in Age-Related Macular Degeneration

We report for the first time an integrated transcriptomic analysis of RPE/choroid dysfunction in AMD (mixed stages) based on combining data from publicly available microarray (GSE29801) and RNAseq (GSE135092) datasets aimed at increasing the ability and power of detection of differentially expressed genes and AMD-associated pathways. The analysis approach employed an integrating quantitative method designed to eliminate bias among different transcriptomic studies. The analysis highlighted 764 meta-genes (366 downregulated and 398 upregulated) in macular AMD RPE/choroid and 445 meta-genes (244 downregulated and 201 upregulated) in non-macular AMD RPE/choroid. Of these, 731 genes were newly detected as differentially expressed (DE) genes in macular AMD RPE/choroid and 434 genes in non-macular AMD RPE/choroid compared with controls. Over-representation analysis of KEGG pathways associated with these DE genes mapped revealed two most significantly associated biological processes in macular RPE/choroid in AMD, namely the neuroactive ligand-receptor interaction pathway (represented by 30 DE genes) and the extracellular matrix-receptor interaction signaling pathway (represented by 12 DE genes). Furthermore, protein-protein interaction (PPI) network identified two central hub genes involved in the control of cell proliferation/differentiation processes, HDAC1 and CDK1. Overall, the analysis provided novel insights for broadening the exploration of AMD pathogenesis by extending the number of molecular determinants and functional pathways that underpin AMD-associated RPE/choroid dysfunction.

Reduction of Liver Metastasis Stiffness Improves Response to Bevacizumab in Metastatic Colorectal Cancer

Tumors are influenced by the mechanical properties of their microenvironment. Using patient samples and atomic force microscopy, we found that tissue stiffness is higher in liver metastases than in primary colorectal tumors. Highly activated metastasis-associated fibroblasts increase tissue stiffness, which enhances angiogenesis and anti-angiogenic therapy resistance. Drugs targeting the renin-angiotensin system, normally prescribed to treat hypertension, inhibit fibroblast contraction and extracellular matrix deposition, thereby reducing liver metastases stiffening and increasing the anti-angiogenic effects of bevacizumab. Patients treated with bevacizumab showed prolonged survival when concomitantly treated with renin-angiotensin inhibitors, highlighting the importance of modulating the mechanical microenvironment for therapeutic regimens.

Protein-altering germline mutations implicate novel genes related to lung cancer development

Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio = 8.82, P = 1.18 × 10-15) and replication (adjusted OR = 2.93, P = 2.22 × 10-3) that is more pronounced in females (adjusted OR = 6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR = 2.61, P = 7.98 × 10-22) and replication datasets (adjusted OR = 1.55, P = 0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk.

Biological Roles and Mechanisms of Circular RNA in Human Cancers

Circular RNA (circRNA) is an intriguing class of RNA with covalently closed-loop structure and is highly stable and conservative. As new members of the ncRNAs, the function, mechanism, potential diagnostic biomarker, and therapeutic target have raised increased attention. Most circRNAs are presented with characteristics of abundance, stability, conservatism, and often exhibiting tissue/developmental-stage-specific manner. Over 30,000 circRNAs have been identified with their unique structures to maintain stability more easily than linear RNAs. An increased numbers of circRNAs are dysregulated and involved in several biological processes of malignance, such as tumorigenesis, growth, invasion, metastasis, apoptosis, and vascularization. Emerging evidence suggests that circRNAs play important roles by acting as miRNA sponge or protein scaffolding, autophagy regulators, and interacting with RNA-binding protein (RBP), which may potentially serve as a novel promising biomarker for prevention, diagnosis and therapeutic target for treatment of human cancer with great significance either in scientific research or clinic arena. This review introduces concept, major features of circRNAs, and mainly describes the major biological functions and clinical relevance of circRNAs, as well as expressions and regulatory mechanisms in various types of human cancer, including pathogenesis, mode of action, potential target, signaling regulatory pathways, drug resistance, and therapeutic biomarkers. All of which provide evidence for the potential utilities of circRNAs in the diagnosis and treatment of cancer.

Tobacco Smoking: Risk to Develop Addiction, Chronic Obstructive Pulmonary Disease, and Lung Cancer

BACKGROUND

The morbidity and mortality associated with tobacco smoking is well established. Nicotine is the addictive component of tobacco. Nicotine, through the non-neuronal α7nicotinic receptor, induces cell proliferation, neo-angiogenesis, epithelial to mesenchymal transition, and inhibits drug-induced apoptosis.

OBJECTIVE

To understand the genetic, molecular and cellular biology of addiction, chronic obstructive pulmonary disease and lung cancer.

METHODS

The search for papers to be included in the review was performed during the months of July- September 2018 in the following databases: PubMed (http://www.ncbi.nlm.nih.gov), Scopus (http://www.scopus.com), EMBASE (http://www.elsevier.com/online-tools/embase), and ISI Web of Knowledge (http://apps.webofknowledge.com/). The following searching terms: "nicotine", "nicotinic receptor", and "addiction" or "COPD" or "lung cancer" were used. Patents were retrieved in clinicaltrials.gov (https://clinicaltrials.gov/). All papers written in English were evaluated. The reference list of retrieved articles was also reviewed to identify other eligible studies that were not indexed by the above-mentioned databases. New experimental data on the ability of nicotine to promote transformation of human bronchial epithelial cells, exposed for one hour to Benzo[a]pyrene-7,8-diol-9-10-epoxide, are reported.

RESULTS

Nicotinic receptors variants and nicotinic receptors upregulation are involved in addiction, chronic obstructive pulmonary disease and/or lung cancer. Nicotine through α7nicotinic receptor upregulation induces complete bronchial epithelial cells transformation.

CONCLUSION

Genetic studies highlight the involvement of nicotinic receptors variants in addiction, chronic obstructive pulmonary disease and/or lung cancer. A future important step will be to translate these genetic findings to clinical practice. Interventions able to help smoking cessation in nicotine dependence subjects, under patent, are reported.

Identification of nicotinic acetylcholine receptor subunits in different lung cancer cell lines and the inhibitory effect of alpha-conotoxin TxID on lung cancer cell growth

Lung cancer is an aggressive tumor with high incidence and mortality rate. There was growing evidence supporting that nicotinic acetylcholine receptors (nAChRs) play vital role inlung cancer development. In this study, the expression of α3, α4, α5, α6, α7, α9, α10, β2, β3, β4 nAChR subunits on protein and mRNA level were studied in A549, NCI-H1299, NCI-H1688, DMS114 and normal human embryonic lung fibroblast (HEL) cell lines by real-time quantitative PCR (qPCR) and Western blot assay respectively. The results indicated that most of these nAChR subunits were expressed in these five cell lines. Compared with normal cells, the expression of α3 and β4 nAChR subunits were upregulated in A549 and NCI-H1299. Thus, we treated A549 and NCI-H1299 with an antagonist α-conotoxin TxID which potently and selectively blocks α3β4 nAChRs. TxID treatment could inhibit A549 and NCI-H1299 cell growth and enhance the inhibitory effect of adriamycin when treated simultaneously. To sum up, our study identified the expression of nAChR subunits in different lung cells and the anti-tumor effect of α-conotoxin TxID, which may provide novel strategies for lung cancer therapy.

Evaluation of USPSTF Lung Cancer Screening Guidelines Among African American Adult Smokers

Importance

The United States Preventive Services Task Force (USPSTF) recommends low-dose computed tomography screening for lung cancer. However, USPSTF screening guidelines were derived from a study population including only 4% African American smokers, and racial differences in smoking patterns were not considered.

Objective

To evaluate the diagnostic accuracy of USPSTF lung cancer screening eligibility criteria in a predominantly African American and low-income cohort.

Design, Setting, and Participants

The Southern Community Cohort Study prospectively enrolled adults visiting community health centers across 12 southern US states from March 25, 2002, through September 24, 2009, and followed up for cancer incidence through December 31, 2014. Participants included African American and white current and former smokers aged 40 through 79 years. Statistical analysis was performed from May 11, 2016, to December 6, 2018.

Exposures

Self-reported race, age, and smoking history. Cumulative exposure smoking histories encompassed most recent follow-up questionnaires.

Main Outcomes and Measures

Incident lung cancer cases assessed for eligibility for lung cancer screening using USPSTF criteria.

Results

Among 48 364 ever smokers, 32 463 (67%) were African American and 15 901 (33%) were white, with 1269 incident lung cancers identified. Among all 48 364 Southern Community Cohort Study participants, 5654 of 32 463 African American smokers (17%) were eligible for USPSTF screening compared with 4992 of 15 901 white smokers (31%) (P < .001). Among persons diagnosed with lung cancer, a significantly lower percentage of African American smokers (255 of 791; 32%) was eligible for screening compared with white smokers (270 of 478; 56%) (P < .001). The lower percentage of eligible lung cancer cases in African American smokers was primarily associated with fewer smoking pack-years among African American vs white smokers (median pack-years: 25.8 [interquartile range, 16.9-42.0] vs 48.0 [interquartile range, 30.2-70.5]; P < .001). Racial disparity was observed in the sensitivity and specificity of USPSTF guidelines between African American and white smokers for all ages. Lowering the smoking pack-year eligibility criteria to a minimum 20-pack-year history was associated with an increased percentage of screening eligibility of African American smokers and with equitable performance of sensitivity and specificity compared with white smokers across all ages (for a 55-year-old current African American smoker, sensitivity increased from 32.2% to 49.0% vs 56.5% for a 55-year-old white current smoker; specificity decreased from 83.0% to 71.6% vs 69.4%; P < .001).

Conclusions and Relevance

Current USPSTF lung cancer screening guidelines may be too conservative for African American smokers. The findings suggest that race-specific adjustment of pack-year criteria in lung cancer screening guidelines would result in more equitable screening for African American smokers at high risk for lung cancer.

A 7-lncRNA signature predict prognosis of Uterine corpus endometrial carcinoma

Current research indicate that long noncoding RNAs (lncRNAs) are associated with the progression of various cancers and can be used as prognostic biomarkers. This study aims to construct a prognostic lncRNA signature for the risk assessment of Uterine corpus endometrial carcinoma (UCEC). The RNA-Seq expression profile and corresponding clinical data of UCEC patients obtained from The Cancer Genome Atlas database. First, some prognosis-related lncRNAs were obtained by univariate Cox analysis. The minimum absolute contraction and selection operator (LASSO) regression and the Cox proportional hazard regression method were used to further identify the lncRNA prognostic model. Finally, seven lncRNAs (AC110491.1, AL451137.1, AC005381.1, AC103563.2, AC007422.2, AC108025.2, and MIR7-3HG) were identified as potential prognostic factors. According to the model constructed by the above analysis, the risk score of each UCEC patient was calculated, and the patients were classified into high and low-risk groups. The low-risk group had significant survival benefits. Moreover, we constructed a nomogram that incorporated independent prognostic factors (age, tumor stage, tumor grade, and risk score). The c-index value for evaluating the predictive nomogram model was 0.801. The area under the curve was 0.797 (3-year survival). The calibration curve also showed that there was a satisfactory agreement between the predicted and observed values in the probability of 1-, 3-, and 5-year overall survival. On the basis of the coexpression relationship, we established a coexpression network of lncRNA-messenger RNA (mRNA) of the 7-lncRNA. The Kyoto Encyclopedia of Genes and Genomes analysis of the coexpressing mRNAs showed that the main pathways related to the 7-lncRNA signature were neuroactive ligand-receptor interaction, serotonergic synapse, and gastric cancer pathway. Therefore, our study revealed that the 7-lncRNA could be used to predict the prognosis of UCEC and for postoperative treatment and follow-up.

[Study on the Difference of Gene Expression between Central and Peripheral Lung Squamous Cell Carcinoma Based on TCGA Database]

背景与目的

肺癌是一种具有高发病率与高死亡率的恶性肿瘤疾病，最常见的类型为非小细胞肺癌（non-small cell lung cancer, NSCLC），其中肺鳞癌作为NSCLC中的一个亚型，具有特殊的病理学类型及其特定的治疗方法，根据临床表型不同又可分为周围型和中央型。本研究基于中央型和周围型肺鳞癌的临床差异进一步探索其基因水平的差异和其潜在的价值。

方法

从癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库收集肺鳞癌数据集，下载临床信息资料及基因表达谱资料。整理资料，分析临床数据及相对应的基因信息。

结果

在临床特征分析中发现，中央型肺鳞癌较周围型肺鳞癌更容易发生淋巴结转移（46.2%, 67/145 vs 28.9%, 26/90; P=0.019），而在性别、年龄、肿瘤大小、有无远处转移、TNM分期、表皮生长因子受体（epidermal growth factor receptor, EGFR）突变等方面未见明显差异。在基因表达水平分析中发现，中央型与周围型肺鳞癌具有1, 031个差异表达基因，其中，周围型与中央型相比，629个基因表达水平上调，402个基因表达水平下调。进一步富集分析显示差异表达基因主要体现在6个信号通路中，其中，刺激神经组织的配体-受体相互作用（neuroactive ligand-receptor interaction）通路是差异表达基因主要富集通路，其他差异表达基因主要与脂类代谢和糖代谢有关。相互作用网络分析显示，在表达上调差异基因中，肝细胞核因子1同源体A（hepatocyte nuclear factor 1 homeobox A, HNF1A）和细胞色素P450家族里的A亚家族发现的第四种酶（cytochrome p450 family, Cytochrome P450 3A4, CYP3A4）影响较为广泛，在表达下调差异基因中，人血清白蛋白（Albumin, ALB）与载脂蛋白A1（Apolipoprotein, APOA1）位于该作用网络的关键位置。

结论

中央型和周围型肺鳞癌患者不仅在淋巴结转移发生率上存在临床特征的差异，而且在基因表达水平亦有明显的不同。其中，HNF1A、CYP3A4、ALB、APOA1位于差异基因相互作用网络的关键位置，有可能参与调控二者的差异表型（phenotypic difference）。