Exploring and comparing of the gene expression and methylation differences between lung adenocarcinoma and squamous cell carcinoma

Engineered Immunologic Niche Monitors Checkpoint Blockade Response and Probes Mechanisms of Resistance

Antibodies to programmed cell death protein1 (anti-PD-1) have become a promising immunotherapy for triple negative breast cancer (TNBC), blocking PD-L1 signaling from pro-tumor cells through T cell PD-1 receptor binding. Nevertheless, only 10-20% of PD-L1+ metastatic TNBC patients who meet criteria benefit from ICB, and biomarkers to predict patient response have been elusive. We have previously developed an immunological niche, consisting of a microporous implant in the subcutaneous space, that supports tissue formation whose immune composition is consistent with that within vital organs. Herein, we investigated dynamic gene expression within this immunological niche to provide biomarkers of response to anti-PD-1. In a 4T1 model of metastatic TNBC, we observed sensitivity and resistance to anti-PD-1 based on primary tumor growth and survival. The niche was biopsied before, during, and after anti-PD-1 therapy, and analyzed for cell types and gene expression indicative of treatment refractivity. Myeloid cell-to-lymphocyte ratios were altered between ICB-sensitivity and resistance. Longitudinal analysis of gene expression implicated dynamic myeloid cell function that stratified sensitivity from resistance. A niche-derived gene signature predicted sensitivity or resistance prior to therapy. Analysis of the niche to monitor immunotherapy response presents a new opportunity to personalize care and investigate mechanisms underlying treatment resistance.

Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.

Data mining-based identification of epigenetic signatures with discrimination potential of lung adenocarcinoma and squamous cell carcinoma

BACKGROUND

Mounting evidence suggests that lung adenocarcinoma (LAC) and lung squamous cell carcinoma (LSC) have different biological behaviors and therapeutic regimens in clinical practice. However, limited improvements in molecular differential diagnosis of the two entities have been achieved in recent decades. We aimed to find novel markers that could define non-small cell lung cancer (NSCLC) subtypes.

METHODS

We first explored publically available databases to search for DNA methylation signatures that enable a precise discrimination of LAC and LSC. Next-generation sequencing (NGS) was then used to analyze the methylation status and sites of candidate genes in LAC/LSC tissue samples, and a quantitative methylation-sensitive PCR (qMS-PCR) assay was conducted to test the performance of the selected maker in tissue samples and bronchoalveolar lavage fluid (BALF) specimens.

RESULTS

We screened 19 top-ranked methylation loci that are differentially methylated between LAC and LSC. Among these hits, 6 methylation sites are enriched within the PREX1 gene promoter, thus becoming our focus. NGS analysis confirmed markedly higher PREX1 methylation levels in LAC than in LSC and revealed the right sites for detection of PREX1 methylation. Furthermore, PREX1 methylation analysis in lung cancer tissue samples defined 9 of 11 pathologically proven LACs, as well as 12 of 14 LSCs. In addition, ~ 80% LAC BALF samples showed methylated PREX1 compared to substantially lower test positivity (0-9%) of it in LSC and other lung conditions (P < 0.01).

CONCLUSION

Our pilot study identified a unique epigenetic signature that could effectively distinguish LAC from LSC in various lung samples. It may enhance our in-depth understanding of the biology of lung cancer and pave the way for better accurate diagnosis and treatment stratification in the future.

Fat Matters: Exploring Cancer Risk through the Lens of Computed Tomography and Visceral Adiposity

Obesity is an established risk factor for cancer. However, conventional measures like body mass index lack precision in assessing specific tissue quantities, particularly of the two primary abdominal fat compartments, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Computed tomography (CT) stands as the gold standard for precisely quantifying diverse tissue types. VAT, distinguished by heightened hormonal and metabolic activity, plays a pivotal role in obesity-related tumor development. Excessive VAT is linked to aberrant secretion of adipokines, proinflammatory cytokines, and growth factors, fostering the carcinogenesis of obesity-related tumors. Accurate quantification of abdominal fat compartments is crucial for understanding VAT as an oncological risk factor. The purpose of the present research is to elucidate the role of CT, performed for staging purposes, in assessing VAT (quantity and distribution) as a critical factor in the oncogenesis of obesity-related tumors. In the field of precision medicine, this work takes on considerable importance, as quantifying VAT in oncological patients becomes fundamental in understanding the influence of VAT on cancer development-the potential "phenotypic expression" of excessive VAT accumulation. Previous studies analyzed in this research showed that VAT is a risk factor for clear cell renal cell carcinoma, non-clear cell renal cell carcinoma, prostate cancer, and hepatocarcinoma recurrence. Further studies will need to quantify VAT in other oncological diseases with specific mutations or gene expressions, in order to investigate the relationship of VAT with tumor genomics.

Comprehensive serum N-glycan profiling identifies a biomarker panel for early diagnosis of non-small-cell lung cancer

Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were increased or decreased in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports potential application of N-glycan biomarker panel in clinical NSCLC detection.

Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans

Human longevity correlates with socio-economic status, and there is evidence that educational attainment increases human lifespan. However, to inform meaningful health policies, we need fine-grained causal evidence on which dimensions of socio-economic status affect longevity and the mediating roles of modifiable factors such as lifestyle and disease. Here we performed two-sample Mendelian randomization analyses applying genetic instruments of education, income and occupation (n = 248,847 to 1,131,881) to estimate their causal effects and consequences on parental lifespan and self-longevity (n = 28,967 to 1,012,240) from the largest available genome-wide association studies in populations of European ancestry. Each 4.20 years of additional educational attainment were causally associated with a 3.23-year-longer parental lifespan independently of income and occupation and were causally associated with 30-59% higher odds of self-longevity, suggesting that education was the primary determinant. By contrast, each one-standard-deviation-higher income and one-point-higher occupation was causally associated with 3.06-year-longer and 1.29-year-longer parental lifespans, respectively, but not independently of the other socio-economic indicators. We found no evidence for causal effects of income or occupation on self-longevity. Mediation analyses conducted in predominantly European-descent individuals through two-step Mendelian randomization suggested that among 59 candidates, cigarettes per day, body mass index, waist-to-hip ratio, hypertension, coronary heart disease, myocardial infarction, stroke, Alzheimer's disease, type 2 diabetes, heart failure and lung cancer individually played substantial mediating roles (proportion mediated, >10%) in the effect of education on specific longevity outcomes. These findings inform interventions for remediating longevity disparities attributable to socio-economic inequality.

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

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

Chronic Inhalation Exposure to Antimony Trioxide Exacerbates the MAPK Signaling in Alveolar Bronchiolar Carcinomas in B6C3F1/N Mice

Antimony trioxide (AT) is used as a flame retardant in fabrics and plastics. Occupational exposure in miners and smelters is mainly through inhalation and dermal contact. Chronic inhalation exposure to AT particulates in B6C3F1/N mice and Wistar Han rats resulted in increased incidences and tumor multiplicities of alveolar/bronchiolar carcinomas (ABCs). In this study, we demonstrated Kras (43%) and Egfr (46%) hotspot mutations in mouse lung tumors (n = 80) and only Egfr (50%) mutations in rat lung tumors (n = 26). Interestingly, there were no differences in the incidences of these mutations in ABCs from rats and mice at exposure concentrations that did and did not exceed the pulmonary overload threshold. There was increased expression of p44/42 mitogen-activated protein kinase (MAPK) (Erk1/2) protein in ABCs harboring mutations in Kras and/or Egfr, confirming the activation of MAPK signaling. Transcriptomic analysis indicated significant alterations in MAPK signaling such as ephrin receptor signaling and signaling by Rho-family GTPases in AT-exposed ABCs. In addition, there was significant overlap between transcriptomic data from mouse ABCs due to AT exposure and human pulmonary adenocarcinoma data. Collectively, these data suggest chronic AT exposure exacerbates MAPK signaling in ABCs and, thus, may be translationally relevant to human lung cancers.

Identification and Validation of Three-Gene Signature in Lung Squamous Cell Carcinoma by Integrated Transcriptome and Methylation Analysis

Since DNA methylation (DNAm) is associated with the carcinogenesis of various cancers, this study aimed to explore potential DNAm prognostic signatures of lung squamous cell carcinoma (LUSC). First, transcriptomic and methylation profiles of LUSC were obtained from The Cancer Genome Atlas database (TCGA). DNAm-related genes were screened by integrating DNAm and transcriptome profiles via MethylMix package. Subsequently, a prognostic signature was conducted with the least absolute shrinkage and selector operation (LASSO) Cox analysis. This signature combined with the clinicopathological parameters was then utilized to construct a prognostic nomogram via the rms package. A signature based on three DNAm-related genes claudin 1 (CLDN1), ATP-binding cassette subfamily C member 5 (ABCC5), and cystatin A (CSTA) that were hypomethylated and upregulated in LUSC was constructed. Univariate and multivariate Cox regression analysis suggested that this signature, combined with age and TNM.N stage, was significantly correlated with survival rate. Time-dependent receiver operating characteristics and calibration curves suggested the nomogram constructed with age and TNM.N stage variables could accurately evaluate the 3- and 5-year outcome of LUSC. Finally, the average mRNA and protein expression levels of CLDN1, ABCC5, and CSTA in LUSC were verified to be significantly higher than those in paracancerous tissues. Moreover, silencing CLDN1, ABCC5, and CSTA expressions could significantly reduce the carcinogenesis of the A549 cell line. The DNAm-driven prognostic signature consists of CLDN1, ABCC5, and CSTA incorporated with age and TNM. N stage could facilitate the prediction outcome of LUSC.

Assessment of causal effects of visceral adipose tissue on risk of cancers: a Mendelian randomization study

BACKGROUND

Despite the established association between obesity and cancer risk, it remains unclear whether visceral obesity is causally related to cancer risk and whether it is more pro-oncogenic than total body fat.

METHODS

We conducted two-sample Mendelian randomization (MR) analysis to assess the causal effects of visceral adipose tissue (VAT) on six common cancers. For exposure data, 221 genetic variants associated with the predicted volume of VAT in 325 153 Europeans from UK Biobank were used as instrumental variables. Genetic association data of six common cancers (breast, lung, colorectal, ovarian, pancreatic and prostate cancers) were obtained from large-scale consortia with an average of 19 576 cases and 43 272 controls. We performed univariable MR with five MR methods [inverse-variance weighted (IVW), MR-Egger regression, weighted median, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) and Radial MR] and multivariable MR to estimate the effect of VAT independent of body mass index (BMI). Finally, we performed a series of sensitivity analyses as validation of primary MR results.

RESULTS

Two associations survived the false discovery rate correction for multiple testing (q-value < 0.05): in IVW, the odds ratios (95% CIs) per unit increase in genetically determined VAT were 1.65 (1.03 to 2.62) for pancreatic cancer and 1.47 (1.20 to 1.82) for lung squamous-cell carcinoma, respectively, which showed the same directions and overlapped confidence intervals with MR-Egger regression and weighted median results. There were no outlier variants identified by MR-PRESSO and no evidence supporting the presence of heterogeneity and pleiotropy in sensitivity analyses, although with wider confidence intervals that included the null, multivariable MR results for these two cancers showed the same directions and similar effect sizes as in IVW, which were independent of the effect from BMI. There was no evidence for a causal effect of VAT on the risk of other types of cancer.

CONCLUSION

Our findings suggest that lifelong exposure to elevated volumes of VAT might increase the risk of pancreatic cancer and lung squamous-cell carcinoma, highlighting the importance of revealing the underlying mechanisms for intervention targets.

Targeted demethylation of the SLC5A7 promotor inhibits colorectal cancer progression

Background

SLC5A7 (solute carrier family 5 member 7), also known as choline transporter 1 (CHT1), is downregulated in colorectal cancer (CRC) and functions as a tumor suppressor. However, the mechanisms underlying the inactivation of SLC5A7 in CRC remain to be elucidated.

Results

In the present study, two broad-spectrum demethylation agents (azacitidine and decitabine) employed to treat CRC cells significantly upregulated SLC5A7 expression. Further results based on the CRC cohort and TCGA database indicated that SLC5A7 promoter methylation inversely correlated with SLC5A7 expression, and the status of SLC5A7 promotor methylation showed a promising prognostic value for patients with CRC. Next, the dCas9-multiGCN4/scFv-TET1CD-based precision demethylation system was constructed, which could significantly and specifically promote SLC5A7 expression in CRC cells through sgRNA targeting the SLC5A7 promoter. Both in vitro and in vivo experiments demonstrated that targeted demethylation of SLC5A7 by dCas9-multiGCN4/scFv-TET1CD-sgSLC5A7 inhibited tumor growth by stabilizing p53 and regulating downstream targets.

Conclusions

Collectively, DNA promoter methylation caused inactivation of SLC5A7 in CRC, and targeted demethylation of SLC5A7 might be a therapeutic target for CRC and other cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01308-5.

DNA Methylation in Lung Cancer: Mechanisms and Associations with Histological Subtypes, Molecular Alterations, and Major Epidemiological Factors

Lung cancer is the major leading cause of cancer-related mortality worldwide. Multiple epigenetic factors-in particular, DNA methylation-have been associated with the development of lung cancer. In this review, we summarize the current knowledge on DNA methylation alterations in lung tumorigenesis, as well as their associations with different histological subtypes, common cancer driver gene mutations (e.g., KRAS, EGFR, and TP53), and major epidemiological risk factors (e.g., sex, smoking status, race/ethnicity). Understanding the mechanisms of DNA methylation regulation and their associations with various risk factors can provide further insights into carcinogenesis, and create future avenues for prevention and personalized treatments. In addition, we also highlight outstanding questions regarding DNA methylation in lung cancer to be elucidated in future studies.

High Expression of lncRNA HEIH is Helpful in the Diagnosis of Non-Small Cell Lung Cancer and Predicts Poor Prognosis

Background

This study aims to investigate the expression and clinical value of long non-coding RNA (lncRNA) HEIH in peripheral blood of patients with non-small cell lung cancer (NSCLC).

Methods

Healthy subjects (N=70), patients with lung squamous cell carcinoma (LUSC, N=70) and patients with lung adenocarcinoma (LUAD, N=80) were included. LncRNA HEIH expression in peripheral blood of included subjects was detected using RT-qPCR. According to the median expression of lncRNA HEIH, LUSC and LUAD patients were allocated into lncRNA HEIH high/low expression groups. The correlation between lncRNA HEIH and clinical indicators of patients was analyzed; Logistic multifactor regression was used to analyze the independent risk factors influencing lncRNA HEIH level. Receiver-operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of lncRNA HEIH and carcinoembryonic antigen (CEA) in LUSC/LUAD patients. MedCalc-Comparison of ROC curves was used to compare the area under ROC curve. The cumulative survival rates of lncRNA HEIH high/low expression group were analyzed by Kaplan–Meier curve. COX multivariate analysis was used to assess the independent factors affecting prognosis of NSCLC.

Results

LncRNA HEIH in peripheral blood of LUSC/LUAD patients was higher than that in healthy controls, with no evident difference between LUSC and LUAD groups. In LUSC/LUAD patients, TNM stage, lymph node metastasis, distal metastasis, and CEA were independent risk factors affecting lncRNA HEIH; patients with high lncRNA HEIH expression had larger pack-years and tumor size, higher CEA level and tumor stage, and higher risk of lymph node metastasis and distal metastasis. LncRNA HEIH had higher diagnostic efficiency than CEA in NSCLC patients. High expression of lncRNA HEIH predicted poor prognosis in patients with NSCLC and was an independent risk factor for prognosis of NSCLC.

Conclusion

High expression of lncRNA HEIH is helpful in the diagnosis of NSCLC and predicts poor prognosis.

An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma

Background

Gastric adenocarcinoma (GAC), a common type of gastric cancer, poses a significant public health threat worldwide. This study aimed to determine the transcriptional regulatory mechanisms of GAC.

Methods

HTSeq-FPKM raw data were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma data collection. Subsequently, the limma package in R was used to identify differentially expressed genes (DEGs). Differentially methylated genes (DMGs), DEGs, and differentially expressed microRNAs (miRNAs) in normal, and tumor tissues of the same patients were screened and compared using R software tools. A functional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) for various DEGs, DMGs, promoter methylation, and miRNAs. DEG-specific methylation and transcription factors were analyzed using ENCODE ChIP-seq.

Results

DEGs were centrally modified by the histone trimethylation of lysine 27 on histone H3 (H3K27me3). Upstream transcription factors of DEGs were enriched in different ChIP-seq clusters, such as Forkhead Box M1, E2F Transcription Factor 4, and suppressor of zest 12. Integrated regulatory networks of DEGs, promoter methylation, and miRNAs were constructed. Two miRNAs (hsa-mir-1 and hsa-mir-133a) and four DEGs (A disintegrin and metalloproteinase domain 12, transcription factor AP-2 alpha, solute carrier family 5 member 7, and cadherin 19) separately played important roles in the integrated regulatory network. Therefore, these DEGs, DMGs, promoter methylation, and miRNAs may play an important role in GAC pathogenesis.

Conclusions

In summary, the present study results provide insights into the oncogenesis and progression of GAC, thus accelerating the development of novel targeted GAC therapies.

In silico assessment of EpCAM transcriptional expression and determination of the prognostic biomarker for human lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)

Epithelial cell adhesion molecule (EpCAM) is a transmembrane glycoprotein which is involved in cell signaling, proliferation, maturation, and movement, all of which are crucial for the proper development of cells and tissues. Cleavage of the EpCAM protein leads to the up-regulation of c-myc, e-fabp, and cyclins A and E which promote tumorigenesis. EpCAM can act as potential diagnostic and prognostic biomarker for different types of cancers as it is also found to be expressed in epithelia and epithelial-derived neoplasms. Hence, we aimed to analyze the EpCAM gene expression and any associated feedback in the patients of two major types of lung cancer (LC) i.e., lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), based on the publicly available online databases. In this study, server-based gene expression analysis represents the up-regulation of EpCAM in both LUAD and LUSC subtypes as compared to the corresponding normal tissues. Besides, the histological sections revealed the over-expression of EpCAM protein in cancerous tissues by depicting strong staining signals. Furthermore, mutation analysis suggested missense as the predominant type of mutation both in LUAD and LUSC in the EpCAM gene. A significant correlation (P-value < 0.05) between the higher EpCAM expression and lower patient survival was also found in this study. Finally, the co-expressed genes were identified with their ontological features and signaling pathways associated in LC development. The overall study suggests EpCAM to be a significant biomarker for human LC prognosis.

The increased expression and aberrant methylation of SHC1 in non-small cell lung cancer: Integrative analysis of clinical and bioinformatics databases

Despite the previous evidence showing that SHC adaptor protein 1 (SHC1) could encode three distinct isoforms (p46SHC, p52SHC and p66SHC) that function in different activities such as regulating life span and Ras activation, the precise underlying role of SHC1 in lung cancer also remains obscure. In this study, we firstly found that SHC1 expression was up‐regulated both in lung adenocarcinoma (LUAD) and in lung squamous cell carcinoma (LUSC) tissues. Furthermore, compared to patients with lower SHC1 expression, LUAD patients with higher expression of SHC1 had poorer overall survival (OS). Moreover, higher expression of SHC1 was also associated with worse OS in patients with stages 1 and 2 but not stage 3 lung cancer. Significantly, the analysis showed that SHC1 methylation level was associated with OS in lung cancer patients. It seemed that the methylation level at specific probes within SHC1 showed negative correlations with SHC1 expression both in LUAD and in LUSC tissues. The LUAD and LUSC patients with hypermethylated SHC1 at cg12473916 and cg19356022 probes had a longer OS. Therefore, it is reasonable to conclude that SHC1 has a potential clinical significance in LUAD and LUSC patients.

DNA methylome analysis identifies BMI-related epigenetic changes associated with non-small cell lung cancer susceptibility

Background

Body mass index (BMI) has been reported to be inversely associated with incident risk of non‐small cell lung cancer (NSCLC). However, the underlying mechanism is still unclear. This study aimed to investigate the role of DNA methylation in the relationship between BMI and NSCLC.

Methods

We carried out a genome‐wide DNA methylation study of BMI in peripheral blood among 2266 Chinese participants by using Illumina Methylation arrays. For the BMI‐related DNA methylation changes, their associations with NSCLC risk were further analyzed and their mediation effects on BMI‐NSCLC association were also evaluated.

Results

The methylation levels of four CpGs (cg12593793, cg17061862, cg11024682, and cg06500161, annotated to LMNA, ZNF143, SREBF1, and ABCG1, respectively) were found to be significantly associated with BMI. Methylation levels of cg12593793, cg11024682, and cg06500161 were observed to be inversely associated with NSCLC risk [OR (95%CI) =0.22 (0.16, 0.31), 0.39 (0.30, 0.50), and 0.66 (0.53, 0.82), respectively]. Additionally, cg11024682 in SREBF1 and cg06500161 in ABCG1 mediated 45.3% and 19.5% of the association between BMI and decreased NSCLC risk, respectively.

Conclusions

In this study, we identified four DNA methylation sites associated with BMI in the Chinese populations at the genome‐wide significant level. We also found that the BMI‐related methylations of SREBF1 and ABCG1 could mediate about a quintile‐to‐half of the effect of BMI on reduced NSCLC risk, which adds a potential mechanism underlying this association.

Females and Males Show Differences in Early-Stage Transcriptomic Biomarkers of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models.

Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma

BACKGROUND

DNA methylation plays a vital role in modulating genomic function and warrants evaluation as a biomarker for the diagnosis and treatment of lung squamous cell carcinoma (LUSC).

OBJECTIVE

In this study, we aimed to identify effective potential biomarkers for predicting prognosis and drug sensitivity in LUSC.

METHODS

A univariate Cox proportional hazards regression analysis, a random survival forests-variable hunting (RSFVH) algorithm, and a multivariate Cox regression analysis were adopted to analyze the methylation profile of patients with LUSC included in public databases: The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO).

RESULTS

A methylated region consisting of 3 sites (cg06675147, cg07064331, cg20429172) was selected. Patients were divided into a high-risk group and a low-risk group in the training dataset. High-risk patients had shorter overall survival (OS) (hazard ratio [HR]: 2.72, 95% confidence interval [CI]: 1.82-4.07, P< 0.001) compared with low-risk patients. The accuracy of the prognostic signature was validated in the test and validation cohorts (TCGA, n= 94; GSE56044, n= 23). Gene set variation analysis (GSVA) showed that activity in the cell cycle/mitotic, ERBB, and ERK/MAPK pathways was higher in the high-risk compared with the low-risk group, which may lead to differences in OS.Interestingly, we observed that patients in the high-risk group were more sensitive to gemcitabine and docetaxel than the low-risk group, which is consistent with results of the GSVA.

CONCLUSION

We report novel methylation sites that could be used as powerful tools for predicting risk factors for poorer survival in patients with LUSC.

A comparison of mRNA and circRNA expression between squamous cell carcinoma and adenocarcinoma of the lungs

Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the two major subtypes of non-small-cell lung cancer (NSCLC). This study aimed to compare mRNA and circRNA expression patterns between LUSC and LUAD. Cancer tissues from 8 LUSC patients and 12 LUAD patients were collected to obtain mRNA and circRNA expression profiles. The differentially expressed mRNAs (DEmRNAs) and circRNAs (DE-circRNAs) between LUSC and LUAD were screened. Afterwards, miRNA-DEcircRNA pairs and miRNA-DEmRNA pairs were predicted to construct a competing endogenous RNAs (ceRNAs) network, followed by functional enrichment analysis and survival analysis. In total, 635 DEmRNAs and 245 DEcircRNAs were obtained. The ceRNA analysis revealed that genes, such as EPHA2, EPHA7, NTRK2, CDK6, hsa_circ_027570, hsa_circ_006089, and hsa-circ_035997, had distinct expression patterns between LUSC and LUAD. Also, functional enrichment analysis indicated that DEmRNAs were mainly enriched in ERK1 and ERK2 cascade. Survival analyses suggested that STXBP1 and PMEPA1 were associated the prognosis of with both LUAD and LUSC, whereas EPHA2 and CDK6 might serve as prognostic factors for LUSC and LUAD, respectively. In conclusion, genes such as EPHA2, EPHA7, NTRK2, and CDK6 had different patterns in the two major histological subtypes of NSCLC. Notably, EPHA2 and CDK6 might be considered as potential therapeutic targets for LUSC and LUAD, respectively.

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

Background

Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relating to tumour cellular diversity on routine tissue images might correlate with outcome. This study investigated the prognostic ability of computer-extracted features of tumour cellular diversity (CellDiv) from haematoxylin and eosin (H&E)-stained histology images of non-small cell lung carcinomas (NSCLCs).

Methods

In this multicentre, retrospective study, we included 1057 patients with early-stage NSCLC with corresponding diagnostic histology slides and overall survival information from four different centres. CellDiv features quantifying local cellular morphological diversity from H&E-stained histology images were extracted from the tumour epithelium region. A Cox proportional hazards model based on CellDiv was used to construct risk scores for lung adenocarcinoma (LUAD; 270 patients) and lung squamous cell carcinoma (LUSC; 216 patients) separately using data from two of the cohorts, and was validated in the two remaining independent cohorts (comprising 236 patients with LUAD and 335 patients with LUSC). We used multivariable Cox regression analysis to examine the predictive ability of CellDiv features for 5-year overall survival, controlling for the effects of clinical and pathological parameters. We did a gene set enrichment and Gene Ontology analysis on 405 patients to identify associations with differentially expressed biological pathways implicated in lung cancer pathogenesis.

Findings

For prognosis of patients with early-stage LUSC, the CellDiv LUSC model included 11 discriminative CellDiv features, whereas for patients with early-stage LUAD, the model included 23 features. In the independent validation cohorts, patients predicted to be at a higher risk by the univariable CellDiv model had significantly worse 5-year overall survival (hazard ratio 1·48 [95% CI 1·06–2·08]; p=0·022 for The Cancer Genome Atlas [TCGA] LUSC group, 2·24 [1·04–4·80]; p=0·039 for the University of Bern LUSC group, and 1·62 [1·15–2·30]; p=0·0058 for the TCGA LUAD group). The identified CellDiv features were also found to be strongly associated with apoptotic signalling and cell differentiation pathways.

Interpretation

CellDiv features were strongly prognostic of 5-year overall survival in patients with early-stage NSCLC and also associated with apoptotic signalling and cell differentiation pathways. The CellDiv-based risk stratification model could potentially help to determine which patients with early-stage NSCLC might receive added benefit from adjuvant therapy.

Funding

National Institue of Health and US Department of Defense.

Prognostic significance of peripheral CD8+CD28+ and CD8+CD28- T cells in advanced non-small cell lung cancer patients treated with chemo(radio)therapy

BACKGROUND

Noninvasive prognostic biomarkers are needed for advanced non-small cell lung cancer (NSCLC) patients with different histological types to identify cases with poor survival. Here, we investigated the prognostic values of peripheral CD8+CD28+ T cells and CD8+CD28- T cells in advanced NSCLC patients treated with chemo(radio)therapy and the impact of histological type on them.

METHODS

Of 232 registered advanced NSCLC patients, 101 treatment-naïve individuals were eligible and included in our study. Flow cytometry was used to evaluate CD8+CD28+ T cells, CD8+CD28- T cells, CD4+ CD25^hi T cells, B cells, natural killer cells, γδT cells, and natural killer T cells in patients' peripheral blood.

RESULTS

The median follow-up time was 13.6 months. Fifty-nine (58.4%) patients died by the end of our study. Fifty-three of the 101 advanced NSCLC cases selected for our study were adenocarcinomas (ADs), and 48 were squamous cell carcinomas (SCCs). Multivariate analyses showed that increased levels of CD8+CD28+ T cells independently predicted favorable overall survival (OS) [hazard ratio (HR): 0.51, 95% confidence interval (CI) 0.30-0.89, P = 0.021] and progression-free survival (PFS) (HR: 0.66, 95% CI 0.37-0.93, P = 0.038) in ADs, but the prediction in SCCs was not statistically significant. In contrast, high levels of CD8+CD28- T cells independently predicted unfavorable OS (HR: 1.41, 95% CI 1.17-3.06, P = 0.035) and PFS (HR: 2.01, 95% CI 1.06-3.85, P = 0.029) in SCCs, but the prediction in ADs was not statistically significant. ADs had higher levels of CD4+CD25^hi T cells and CD8+CD28- T cells and lower NK cells (all P < 0.05) than SCCs.

CONCLUSIONS

Our findings uncovered the prognostic values of peripheral CD8+CD28+ T cells and CD8+CD28- T cells in advanced NSCLC patients treated with chemo(radio)therapy, which could help to identify patients with poor outcomes and refine treatment strategies.

Long non-coding RNA-HAGLR suppressed tumor growth of lung adenocarcinoma through epigenetically silencing E2F1

Emerging evidence indicates that long noncoding RNAs (LncRNAs) are new players in gene regulation but their mechanisms of action are mainly undocumented. In this study, we investigated LncRNA alterations that contribute to lung cancer by analyzing published microarray data in Gene Expression Obminus (GEO) and The Cancer Genome Atlas RNA (TCGA) sequencing data. Here, we reported that HAGLR (also called HOXD-AS1) was frequently down-regulated in lung adenocarcinoma (LUAD) tissues, and decreased HAGLR expression was clinically associated with shorter survival of LUAD patients. Preclinical studies using multiple LUAD cells and in vivo mouse model indicated that HAGLR could attenuate LUAD cell growth in vitro and in vivo. Mechanistically, HAGLR could physically interact with DNMT1, and recruit DNMT1 on E2F1 promoter to increase local DNA methylation. Overall, our study demonstrated that HAGLR promoted LUAD progression by recruiting DNMT1 to modulate the promoter methylation and expression of E2F1, which expanded potential therapeutic strategies for LUAD treatment.