Distinguishing Lung Adenocarcinoma from Lung Squamous Cell Carcinoma by Two Hypomethylated and Three Hypermethylated Genes: A Meta-Analysis

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.

Deciphering the Epigenetic Symphony of Cancer: Insights and Epigenetic Therapies Implications

Epigenetic machinery is a cornerstone in normal cell development, orchestrating tissue-specific gene expression in mammalian cells. Aberrations in this intricate landscape drive substantial changes in gene function, emerging as a linchpin in cancer etiology and progression. While cancer was conventionally perceived as solely a genetic disorder, its contemporary definition encompasses genetic alterations intertwined with disruptive epigenetic abnormalities. This review explores the profound impact of DNA methylation, histone modifications, and noncoding RNAs on fundamental cellular processes. When these pivotal epigenetic mechanisms undergo disruption, they intricately guide the acquisition of the 6 hallmark characteristics of cancer within seemingly normal cells. Leveraging the latest advancements in decoding these epigenetic intricacies holds immense promise, heralding a new era in developing targeted and more efficacious treatment modalities against cancers driven by aberrant epigenetic modifications.

ANKRD49 promotes the metastasis of NSCLC via activating JNK-ATF2/c-Jun-MMP-2/9 axis

BACKGROUND

Ankyrin repeat domain 49 (ANKRD49) has been found to be highly expressed in multiple cancer including lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC). However, the function of ANKRD49 in the pathogenesis of NSCLC still remains elusive. Previously, ANKRD49 has been demonstrated to promote the invasion and metastasis of A549 cells, a LUAD cell line, via activating the p38-ATF-2-MMP2/MMP9 pathways. Considering the heterogeneity of tumor cells, the function and mechanism of ANKRD49 in NSCLC need more NSCLC-originated cells to clarify.

METHODS

Real-time qPCR was employed to test ANKRD49 expression levels in nine pairs of fresh NSCLC tissues and the corresponding adjacent normal tissues. The function of ANKRD49 was investigated using overexpression and RNA interference assays in lung adenocarcinoma cell line (NCI-H1299) and lung squamous carcinoma cell line (NCI-H1703) through gelatin zymography, cell counting kit-8, colony formation, wound healing, migration and invasion assays mmunoprecipitation was performed to in vitro. Immunoprecipitation was performed to test the interaction of c-Jun and ATF2. Chromatin immunoprecipitation was conducted to assess the transcriptional regulation of ATF2/c-Jun on MMP-2/9. Moreover, the tumorigenicity of ANKRD49 was evaluated in nude mice models and the involved signal molecular was also measured by immunohistochemical method.

RESULTS

We found that the levels of ANKRD49 in cancerous tissues were higher than those in adjacent normal tissues. in vitro assay showed that ANKRD49 promoted the migration and invasion of NCI-H1299 and NCI-H1703 cells via enhancing the levels of MMP-2 and MMP-9. Furthermore, ANKRD49 elevated phosphorylation of JNK and then activated c-Jun and ATF2 which interact in nucleus to promote the binding of ATF2:c-Jun with the promoter MMP-2 or MMP-9. In vivo assay showed that ANKRD49 promoted lung metastasis of injected-NSCLC cells and the high metastatic rate was positively correlated with the high expression of ANKRD49, MMP-2, MMP-9, p-JNK, p-c-Jun and p-ATF2.

CONCLUSION

The present study indicated that ANKRD49 accelerated the invasion and metastasis of NSCLC cells via JNK-mediated transcription activation of c-Jun and ATF2 which regulated the expression of MMP-2/MMP-9. The molecular mechanisms of ANKRD49's function is different from those found in A549 cells. The current study is a supplement and improvement to the previous research.

Two-Stage Deep-Learning Classifier for Diagnostics of Lung Cancer Using Metabolites

We developed a machine-learning system for the selective diagnostics of adenocarcinoma (AD), squamous cell carcinoma (SQ), and small-cell carcinoma lung (SC) cancers based on their metabolomic profiles. The system is organized as two-stage binary classifiers. The best accuracy for classification is 92%. We used the biomarkers sets that contain mostly metabolites related to cancer development. Compared to traditional methods, which exclude hierarchical classification, our method splits a challenging multiclass task into smaller tasks. This allows a two-stage classifier, which is more accurate in the scenario of lung cancer classification. Compared to traditional methods, such a "divide and conquer strategy" gives much more accurate and explainable results. Such methods, including our algorithm, allow for the systematic tracking of each computational step.

Shared network pattern of lung squamous carcinoma and adenocarcinoma illuminates therapeutic targets for non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is a malignant tumor with high mortality. Lung squamous carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the common subtypes of NSCLC. However, how LUSC and LUAD are compatible remains to be elucidated.

Methods

We used a network approach to find highly interconnected genes shared with LUSC and LUAD, and we then built modules to assess the degree of preservation between them. To quantify this result, Z-scores were used to summarize the interrelationships between LUSC and LUAD. Furthermore, we correlated network hub genes with patient survival time to identify risk factors.

Results

Our findings provided a look at the regulatory pattern for LUSC and LUAD. For LUSC, several genes, such as AKR1C1, AKR1C2, and AKR1C3, play key roles in regulating network modules of cell growth pathways. In addition, CCL19, CCR7, CCL21, and LY9 are enriched in LUAD network modules of T lymphocyte-related pathways. LUSC and LUAD have similar expressed gene expression patterns. Their networks share 46 hub genes with connectivity greater than 0.9. These genes are correlated with patient survival time. Among them, the expression level of COL5A2 in LUSC and LUAD is higher than that in normal tissues, which is closely related to the poor prognosis of LUSC and LUAD patients.

Conclusion

LUSC and LUAD share a network pattern. COL5A2 may be a risk factor in poor prognosis in LUSC and LUAD. The common landscape of LUSC and LUAD will help better define the regulation of NSCLC candidate genes and achieve the goals of precision medicine.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

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.

DNA methylation in lung cancer patients: Opening a "window of life" under precision medicine

DNA methylation is a work of adding a methyl group to the 5th carbon atom of cytosine in DNA sequence under the catalysis of DNA methyltransferase (DNMT) to produce 5-methyl cytosine. Some current studies have elucidated the mechanism of lung cancer occurrence and causes of lung cancer progression and metastasis from the perspective of DNA methylation. Moreover, many studies have shown that smoking can change the methylation status of some gene loci, leading to the occurrence of lung cancer, especially central lung cancer. This review mainly introduces the role of DNA methylation in the pathogenesis, early diagnosis and screening, progression and metastasis, treatment, and prognosis of lung cancer, as well as the latest progress. We point out that methylation markers, sample tests, and methylation detection limit the clinical application of DNA methylation. If the liquid biopsy is to become the main force in lung cancer diagnosis, it must make efficient use of limited samples and improve the sensitivity and specificity of the tests. In addition, we also put forward our views on the future development direction of DNA methylation.

Deep learning classification of lung cancer histology using CT images

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image analysis allude to the utility of radiologic data in further describing disease characteristics and for risk stratification. In this study, we propose a radiomics approach to predicting non-small cell lung cancer (NSCLC) tumor histology from non-invasive standard-of-care computed tomography (CT) data. We trained and validated convolutional neural networks (CNNs) on a dataset comprising 311 early-stage NSCLC patients receiving surgical treatment at Massachusetts General Hospital (MGH), with a focus on the two most common histological types: adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC). The CNNs were able to predict tumor histology with an AUC of 0.71(p = 0.018). We also found that using machine learning classifiers such as k-nearest neighbors (kNN) and support vector machine (SVM) on CNN-derived quantitative radiomics features yielded comparable discriminative performance, with AUC of up to 0.71 (p = 0.017). Our best performing CNN functioned as a robust probabilistic classifier in heterogeneous test sets, with qualitatively interpretable visual explanations to its predictions. Deep learning based radiomics can identify histological phenotypes in lung cancer. It has the potential to augment existing approaches and serve as a corrective aid for diagnosticians.

Machine Learning for Histologic Subtype Classification of Non-Small Cell Lung Cancer: A Retrospective Multicenter Radiomics Study

BACKGROUND

Histologic phenotype identification of Non-Small Cell Lung Cancer (NSCLC) is essential for treatment planning and prognostic prediction. The prediction model based on radiomics analysis has the potential to quantify tumor phenotypic characteristics non-invasively. However, most existing studies focus on relatively small datasets, which limits the performance and potential clinical applicability of their constructed models.

METHODS

To fully explore the impact of different datasets on radiomics studies related to the classification of histological subtypes of NSCLC, we retrospectively collected three datasets from multi-centers and then performed extensive analysis. Each of the three datasets was used as the training dataset separately to build a model and was validated on the remaining two datasets. A model was then developed by merging all the datasets into a large dataset, which was randomly split into a training dataset and a testing dataset. For each model, a total of 788 radiomic features were extracted from the segmented tumor volumes. Then three widely used features selection methods, including minimum Redundancy Maximum Relevance Feature Selection (mRMR), Sequential Forward Selection (SFS), and Least Absolute Shrinkage and Selection Operator (LASSO) were used to select the most important features. Finally, three classification methods, including Logistics Regression (LR), Support Vector Machines (SVM), and Random Forest (RF) were independently evaluated on the selected features to investigate the prediction ability of the radiomics models.

RESULTS

When using a single dataset for modeling, the results on the testing set were poor, with AUC values ranging from 0.54 to 0.64. When the merged dataset was used for modeling, the average AUC value in the testing set was 0.78, showing relatively good predictive performance.

CONCLUSIONS

Models based on radiomics analysis have the potential to classify NSCLC subtypes, but their generalization capabilities should be carefully considered.

FGD5‑AS1 promotes cisplatin resistance of human lung adenocarcinoma cell via the miR‑142‑5p/PD‑L1 axis

Previous studies have reported that long non-coding (lnc) RNA FGD5-antisense 1 (FGD5-AS1) promotes tumor proliferation, migration and invasion. Therefore, the present study aimed to elucidate the biological role and underlying molecular mechanisms of FGD5-AS1 in cisplatin (DDP) resistance of lung adenocarcinoma (LAD) cells. The results demonstrated that FGD5-AS1 was highly expressed in DDP-resistant LAD tissues and cells. Knockdown of FGD5-AS1 decreased the proliferative, migratory and invasive abilities of DDP-resistant LAD cells. Moreover, it was identified that FGD5-AS1 acted as a molecular sponge for microRNA (miR)-142, and FGD5-AS1 enhanced the resistance of A549/DDP cells to DDP by directly interacting with miR-142. Programmed cell death 1 ligand 1 (PD-L1) was also found to be a key effector of the FGD5-AS1/miR-142 axis to regulate the chemoresistance of DDP-resistant LAD cells. In conclusion, the present study demonstrated that FGD5-AS1 increased DDP resistance of LAD via the miR-142/PD-L1 axis, which may offer a novel treatment strategy for patients with DDP-resistant LAD.

Unique genomic features and prognostic value of COSMIC mutational signature 4 in lung adenocarcinoma and lung squamous cell carcinoma

Background

Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, and prognosis. Among the signatures cataloged at COSMIC, mutational signature 4 has been linked to smoking. However, the distribution of signature 4 in Chinese lung cancer patients has not been evaluated, and its clinical value has not been evaluated. Here we survey mutational signatures in Chinese lung cancer patients and explore the relationship between signature 4 and other genomic features in the patients.

Methods

We extracted mutational signatures from whole-exome sequencing data of Chinese non-small cell lung cancer patients. The data included 401 lung adenocarcinoma (LUAD) and 92 squamous cell carcinoma (LUSC). We then performed statistical analysis to search for genomic and clinical features that can be linked to mutation signatures.

Results

We found signature 4 is the most frequent mutational signature in LUSC and the second most frequent in LUAD. Fifty-six LUAD and thirty-five LUSC patients were named with high signature 4 similarities (cosine similarity >0.7). These patients have shorter survival and higher tumor mutational burden comparing to those with low signature 4 similarities. Dozens of genes with single nucleotide variation, index mutations, and copy number variations were differentially enriched in the patients with high signature 4 similarities. Among these genes, CSMD3, LRP1B, TP53, SYNE1, SLIT2, FGF4, and FGF19 are common in both LUADs and LUSCs with high signature 4 similarities, showing that these genes are tightly associated with signature 4.

Conclusions

The present study is the first to report a comparison in Chinese NSCLC patients with or without COSMIC mutational signature 4. These results will help find the Signature 4 related mutational process in NSCLC.

miR-708-5p targets oncogenic prostaglandin E2 production to suppress a pro-tumorigenic phenotype in lung cancer cells

Many cancers maintain an inflammatory microenvironment to promote their growth. Lung cancer is of particular importance, as it is the deadliest cancer worldwide. One inflammatory pathway commonly dysregulated in cancer is the metabolism of arachidonic acid (AA) by Cyclooxygenase-2 (COX-2) and microsomal Prostaglandin E Synthase 1 (mPGES-1) into Prostaglandin E2 (PGE2). While researchers have identified PGE2's pro-tumorigenic functions, the mechanisms governing overexpression of COX-2 and mPGES-1 are incompletely understood. MicroRNAs (miRNAs) are important post-transcriptional regulators commonly dysregulated in cancer. Interestingly, miR-708-5p (miR-708) is predicted to target both COX-2 and mPGES-1. In this study, we show that high miR-708 expression is associated with survival rates in lung squamous cell carcinoma patients. miR-708 also represses PGE2 production by suppressing both COX-2 and mPGES-1 expression in lung cancer cells. miR-708 regulation of COX-2 and mPGES-1 is mediated through targeting of their 3' untranslated regions (UTRs). Moreover, miR-708 decreases proliferation, survival, and migration of lung cancer cells, which can be partially attributed to miR-708's inhibition of PGE2 signaling. Lastly, we identify novel miR-708 predicted targets and possible regulators of miR-708 expression in lung cancer. Collectively, these data demonstrate that dysregulated miR-708 expression contributes to exacerbated PGE2 production, leading to an enhanced pro-tumorigenic phenotype in lung cancer cells.

Genetic Markers in Lung Cancer Diagnosis: A Review

Lung cancer is the most often diagnosed cancer in the world and the most frequent cause of cancer death. The prognosis for lung cancer is relatively poor and 75% of patients are diagnosed at its advanced stage. The currently used diagnostic tools are not sensitive enough and do not enable diagnosis at the early stage of the disease. Therefore, searching for new methods of early and accurate diagnosis of lung cancer is crucial for its effective treatment. Lung cancer is the result of multistage carcinogenesis with gradually increasing genetic and epigenetic changes. Screening for the characteristic genetic markers could enable the diagnosis of lung cancer at its early stage. The aim of this review was the summarization of both the preclinical and clinical approaches in the genetic diagnostics of lung cancer. The advancement of molecular strategies and analytic platforms makes it possible to analyze the genome changes leading to cancer development-i.e., the potential biomarkers of lung cancer. In the reviewed studies, the diagnostic values of microsatellite changes, DNA hypermethylation, and p53 and KRAS gene mutations, as well as microRNAs expression, have been analyzed as potential genetic markers. It seems that microRNAs and their expression profiles have the greatest diagnostic potential value in lung cancer diagnosis, but their quantification requires standardization.

Are There New Biomarkers in Tissue and Liquid Biopsies for the Early Detection of Non-Small Cell Lung Cancer?

Lung cancer is one of the most lethal malignancies worldwide, mainly due to its late diagnoses. The detection of molecular markers on samples provided from routine bronchoscopy including several liquid-based cytology tests (e.g., bronchoaspirate, bronchoalveolar lavage) and/or on easily obtained specimens such as sputum could represent a new approach to improve the sensitivity in lung cancer diagnoses. Recently growing interest has been reported for "noninvasive" liquid biopsy as a valuable source for molecular profiling. Unfortunately, a biomarker and/or composition of biomarkers capable of detecting early-stage lung cancer has yet to be discovered even if in the last few years there has been, through the use of revolutionary new technologies, an explosion of lung cancer biomarkers. Assay sensitivity and specificity need to be improved particularly when new approaches and/or tools are used. We have focused on the most important markers detected in tissue, and on several cytological specimens and liquid biopsies overall.

Applying circulating tumor DNA methylation in the diagnosis of lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Low dose computed tomography (LDCT) is commonly used for disease screening, with identified candidate cancerous regions further diagnosed using tissue biopsy. However, existing techniques are all invasive and unavoidably cause multiple complications. In contrast, liquid biopsy is a noninvasive, ideal surrogate for tissue biopsy that can identify circulating tumor DNA (ctDNA) containing tumorigenic signatures. It has been successfully implemented to assist treatment decisions and disease outcome prediction. ctDNA methylation, a type of lipid biopsy that profiles critical epigenetic alterations occurring during carcinogenesis, has gained increasing attention. Indeed, aberrant ctDNA methylation occurs at early stages in lung malignancy and therefore can be used as an alternative for the early diagnosis of lung cancer. In this review, we give a brief synopsis of the biological basis and detecting techniques of ctDNA methylation. We then summarize the latest progress in use of ctDNA methylation as a diagnosis biomarker. Lastly, we discuss the major issues that limit application of ctDNA methylation in the clinic, and propose possible solutions to enhance its usage.

Discriminating lung adenocarcinoma from lung squamous cell carcinoma using respiration-induced tumor shape changes

Based on 4D-CT, we aimed to characterize the pattern of morphological changes in lung tumors during respiration, and investigated its potential in non-invasively differentiating lung adenocarcinoma (AC) and squamous cell carcinoma (SCC). We applied a 3D surface analysis on 22 tumors (13 AC, 9 SCC) to investigate the tumor regional morphological fluctuations in response to respiration phases. Tumor surface vertices among ten respiratory phases were matched using surface-based registration, and the shape descriptors (ρ and detJ) were calculated and tracked across respiration stages in a regionally aligned scenario. Pair-wise group comparisons were performed between lung AC and SCC subtypes, in terms of ratios of maximal shape changes as well as correlation coefficients between tumor shape and respiratory stage indicators from the lung. AC type tumors had averaged larger surface measurements at exhale than at inhale, and these surface measurements were negatively correlated with lung volumes across respiratory stages. In contrast, SCC type tumors had averaged smaller surface measurements at exhale than at inhale, and the correlations with lung volumes were positive. The group differences in maximal shape changes as well as correlations were both statistically significant (p  <  0.05). We developed a non-invasive lung tumor sub-type detection pipeline based on respiration-induced tumor surface deformation. Significant differences in deformation patterns were detected between lung AC and SCC. The derived surface measurements may potentially serve as a new non-invasive imaging biomarker of lung cancer subtypes.

Genetic characterisation of molecular targets in carcinoma of unknown primary

BACKGROUND

Carcinoma of unknown primary (CUP) is a metastatic epithelial malignancy in the absence of an identifiable primary tumour. Prognosis for patients with CUP is poor because treatment options are generally limited to broad spectrum chemotherapy. A shift towards personalised cancer management based on mutation profiling offers the possibility of new treatment paradigms. This study has explored whether actionable, oncogenic driver mutations are present in CUP that have potential to better inform treatment decisions.

METHODS

Carcinoma of unknown primary cases (n = 21) were selected and DNA was isolated from formalin-fixed paraffin embedded sections prior to amplification and sequencing. Two distinct yet complementary targeted gene panels were used to assess variants in up to 76 known cancer-related genes for the identification of biologically relevant and actionable mutations.

RESULTS

Variants were detected in 17/21 cases (81%) of which 11 (52%) were potentially actionable with drugs currently approved for use in known primary cancer types or undergoing clinical trials. The most common variants detected were in TP53 (47%), KRAS (12%), MET (12%) and MYC (12%). Differences at the molecular level were seen between common CUP histological subtypes. CUP adenocarcinomas and poorly differentiated carcinomas harboured the highest frequency of variants in genes involved in signal transduction pathways (e.g. MET, EGFR, HRAS, KRAS, and BRAF). In contrast, squamous cell carcinoma exhibited a higher frequency of variants in cell cycle control and DNA repair genes (e.g. TP53, CDKN2A and MLH1).

CONCLUSION

Taken together, mutations in biologically relevant genes were detected in the vast majority of CUP tumours, of which half provided a potentially novel treatment option not generally considered in CUP.

Gene methylation as a powerful biomarker for detection and screening of non-small cell lung cancer in blood

DNA methylation has been reported to become a potential powerful tool for cancer detection and diagnosis. However, the possibilities for the application of blood-based gene methylation as a biomarker for non-small cell lung cancer (NSCLC) detection and screening remain unclear. Hence, we performed this meta-analysis to evaluate the value of gene methylation detected in blood samples as a noninvasive biomarker in NSCLC. A total of 28 genes were analyzed from 37 case-control studies. In the genes with more than three studies, we found that the methylation of P16, RASSF1A, APC, RARβ, DAPK, CDH13, and MGMT was significantly associated with risks of NSCLC. The methylation statuses of P16, RASSF1A, APC, RARβ, DAPK, CDH13, and MGMT were not linked to age, gender, smoking behavior, and tumor stage and histology in NSCLC. Therefore, the use of the methylation status of P16, RASSF1A, APC, RARβ, DAPK, CDH13, and MGMT could become a promising and powerful biomarker for the detection and screening of NSCLC in blood in clinical settings. Further large-scale studies with large sample sizes are necessary to confirm our findings in the future.

Correlation between serum IL-1β and miR-144-3p as well as their prognostic values in LUAD and LUSC patients

BACKGROUND

IL-1β is an essential factor of inflammation initiation, and it also promotes malignant transformation, indicating its tumorigenic property. We aimed to investigate the correlation between IL-1β and miR-144-3p as well as their prognostic values in LUAD and LUSC patients.

RESULTS

The IL-1β level in both LUAD and LUSC patients was significantly higher than that of healthy donors (P < 0.001). In both populations, patients with low IL-1β level had better prognosis than high IL-1β level (P < 0.001 and P = 0.010, respectively). In A549 cells, miR-144 showed the biggest expression change (-4.38 fold) after IL-1β exposure. In LUAD patients, a negative correlation was detected between IL-1β and miR-144-3p (r = -0.540, P < 0.001) and the high miR-144-3p group had better prognosis (P = 0.003), which was validated by TCGA data. Clinical stage, IL-1β and miR-144-3p were independent risk factors in LUAD patients. In vitro, IL-1β and miR-144-3p antagomir could enhance proliferation and miR-144-3p mimics would attenuate the promoting effect of IL-1β.

MATERIALS AND METHODS

ELISA and qRT-PCR were applied respectively to detected cytokines and miR-144-3p in 129 LUAD, 54 LUSC and 40 healthy donors. Moreover, miRNA array was carried out for miRNA profiling. TCGA database was employed for validation, and follow up data were collected for prognosis evaluation. MTT assay and western-blot were carried out for proliferation evaluation.

CONCLUSIONS

In LUAD patients, the serum IL-1β level was correlated with miR-144-3p may affect miR-144-3p at transcriptional level. Both of them were independent risk factors for LUAD prognosis. In addition, IL-1β and miR-144-3p might mediate inflammation-promoted tumorigenesis in LUAD patients.

Relationship between RAS Association Domain Family Protein 1A Promoter Methylation and the Clinicopathological Characteristics in Patients with Ovarian Cancer: A Systematic Meta-Analysis

BACKGROUND

To investigate the relationship between RAS association domain family protein 1A (RASSF1A) promoter methylation and the clinical features, and the survival of ovarian cancer patients.

METHODS

A comprehensive literature search was conducted in the PubMed, Embase, EBSCO, and Cochrane Library databases. The overall ORs with their 95% CIs were calculated in this meta-analysis.

RESULTS

Finally 17 relevant publications with 1,108 ovarian cancer samples were available for the current meta-analysis. RASSF1A promoter methylation had a significantly higher level in ovarian cancer than in low malignant potential (LMP) tumors. No significant relationship was observed between RASSF1A promoter methylation and the clinicopathological characteristics in ovarian cancer. Two studies reported that RASSF1A promoter methylation was not correlated with the survival of patients with ovarian cancer.

CONCLUSIONS

Our findings suggest that the use of RASSF1A promoter methylation could distinguish ovarian cancer and LMP tumors. -RASSF1A promoter methylation may not be correlated with the clinical features and the survival of ovarian cancer patients. More studies with large sample sizes are essential in the future.

Downregulation of DNMT3A by miR-708-5p Inhibits Lung Cancer Stem Cell-like Phenotypes through Repressing Wnt/β-catenin Signaling

Purpose: Lung cancer is the leading cause of cancer-related death in the world, and emerging evidences suggest that lung cancer stem cells (CSC) are associated with its poor prognosis, tumor recurrence, and therapy resistance. Here we reveal a novel role for miR-708-5p in inhibiting lung CSC-like features.Experimental Design: Phenotypic effects of miR-708-5p on the lung CSC-like properties were examined by in vitro sphere formation assay and in xenografted animal models. Immunoblotting, dual luciferase reporter, and immunocytochemistry were performed to determine the target of miR-708-5p. DNA methylation of CDH1 promoter region was tested using bisulfate sequencing. Genome-wide miRNA sequencing data of 990 patients from The Cancer Genome Atlas (TCGA) dataset and 148 patients from China cohort were analyzed to excavate the pathogenic implications of miR-708-5p.Results: Expression of miR-708-5p inhibits the CSC traits of NSCLC cells in vitro while antagonizing miR-708-5p promotes tumorigenesis in vivo miR-708-5p directly suppresses the translation of DNMT3A, which results in a substantial reduction of global DNA methylation and the upregulated expression of tumor suppressor CDH1. The upregulation of CDH1 decreased the activity of Wnt/β-catenin signaling and then impaired the stemness characteristics of NSCLC cells. Clinically, patients with high miR-708-5p expression show significantly better survival and lower recurrence. Furthermore, miR-708-5p has a promising potential to apply to differentiating histologic subtypes in NSCLC.Conclusions: Our findings support that miR-708-5p suppresses NSCLC initiation, development, and stemness through interfering DNMT3A-dependent DNA methylation. miR-708-5p may function as a novel diagnostic and prognostic biomarker in NSCLC. Clin Cancer Res; 24(7); 1748-60. ©2017 AACR.

Comprehensive epigenetic analysis of the signature genes in lung adenocarcinoma

Aim: This study aimed to explore the epigenetic modifications of signature genes in lung adenocarcinoma. Materials & methods: The data of miRNA expression, mRNA expression and DNA methylation were downloaded from The Cancer Genome Atlas. Differential analysis was performed, followed by correlation analysis of miRNA–mRNA and DNA methylation-mRNA. Results: A total of 14 significant inverse correlations between gene expression and DNA methylation were identified, the expressions of which were selected for further validation via GSE27262, displaying similar pattern with that of the integrated analysis. In addition, qRT-PCR results showed that the expression profiling results of six mRNAs and one miRNA were consistent with the findings of integrated analysis. Five genes showed higher diagnostic value, which was also associated with overall survival of patients. Conclusion: Taken together, the epigenetic alterations of signature genes may hold promise for becoming biomarkers for the early detection of lung adenocarcinoma.

Short stature homeobox 2 methylation as a potential noninvasive biomarker in bronchial aspirates for lung cancer diagnosis

Gene methylation has been frequently observed in lung cancer. However, the use of methylated genes in bronchial aspirates of patients with lung cancer remains to be evaluated. The purpose of this study was to analyze whether the detection of genes with aberrant promoter methylation can be useful noninvasive biomarkers in bronchial aspirates from lung cancer. We found that the methylation status of the cyclin-dependent kinase inhibitor 2A (P16), Ras association domain family 1 isoform (RASSF1A), adenomatous polyposis coli (APC) and short stature homeobox 2 (SHOX2) genes was significantly correlated with lung cancer in bronchial aspirates. The P16, RASSF1A and APC methylation had a bad diagnostic effect in bronchial aspirates of patients with lung cancer compared with non-tumor controls (P16: sensitivity = 0.26, specificity = 0.99, area under the curve (AUC) = 0.67; RASSF1A: sensitivity = 0.40, specificity = 0.99, AUC = 0.66; APC: sensitivity = 0.17, specificity = 0.98, AUC = 0.65). The pooled sensitivity, specificity, and AUC of the SHOX2 methylation were 0.75, 0.94, and 0.94, respectively. Moreover, when squamous cell carcinoma (SCC) was compared to adenocarcinoma (AC), the SHOX2 gene had a significantly higher methylation rate in SCC than in AC (P < 0.001). Methylated P16, RASSF1A, APC and retinoic acid receptor beta2 (RARβ2) genes had similar frequencies in these two histotypes (P > 0.1). Our findings suggest that methylated SHOX2 gene could be a specific and potential noninvasive biomarker using bronchial aspirates for lung cancer diagnosis, especially for SCC.

Clinical roles of the aberrantly expressed lncRNAs in lung squamous cell carcinoma: a study based on RNA-sequencing and microarray data mining

Lung squamous cell carcinoma (LUSC) accounts for a significant proportion of lung cancer and there have been few therapeutic alternatives for recurrent LUSC due to the lack of specific driver molecules. To investigate the prospective role of lncRNAs in the tumorigenesis and progression of LUSC, the aberrantly expressed lncRNAs were calculated based on The Cancer Genome Atlas RNA-seq data. Of 7589 lncRNAs with 504 LUSC cases, 884 lncRNAs were identified as being aberrantly expressed (|log2 fold change| >2 and adjusted P<0.05) by DESeq R. The top 10 lncRNAs with the highest diagnostic value were SFTA1P,LINC00968, LINC00961, LINC01572,RP1-78O14.1, FENDRR, LINC01314,LINC01272, GATA6-AS1, and MIR3945HG. In addition to the significant roles in the carcinogenesis of LUSC, several lncRNAs also played vital parts in the survival and progression of LUSC. SFTA1P, LINC01272, GATA6-AS1 and MIR3945HG were closely related to the survival time of LUSC. Furthermore, LINC01572 and LINC01314 could distinguish the LUSC at early stage from that at advanced stage. The prospective molecular assessment of key lncRNAs showed that a certain series of genes could be involved in the regulation network. Furthermore, the OncoPrint from cBioPortal indicated that 14% (69/501) LUSC cases with genetic alterations could be obtained, including amplification, deep deletion and mRNA upregulation. More interestingly, the cases with genetic alterations had a poorer survival as compared to those without alterations. Overall, the study propounds a potentiality for interpreting the pathogenesis and development of LUSC with lncRNAs, and provides a novel platform for searching for more capable diagnostic biomarkers for LUSC.

Differential expression and prognostic significance of GLUT1 according to histologic type of non-small-cell lung cancer and its association with volume-dependent parameters

BACKGROUND

We evaluated glucose transporter type 1 (GLUT1) and carbonic anhydrase IX (CAIX) expression, together with volume-based¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) parameters, in non-small cell lung cancer (NSCLC) patients, and examined the prognostic significance of those parameters according to its histologic subtype.

METHOD

A total of 269 patients, who underwent surgical resection for NSCLC, were reviewed retrospectively. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values were measured by preoperative ¹⁸F-fluorodeoxyglucose positron emission tomography computed tomography. GLUT1 and CAIX expression was evaluated using immunohistochemical method.

RESULTS

The mean MTV and TLG values were 30.0±57.1 and 165.4±361.3, respectively, and were significantly higher in patients with squamous cell carcinoma than with adenocarcinoma (p=0.047 for MTV; p=0.042 for TLG). GLUT1 expression was identified in 99% of squamous cell carcinoma and 50% of adenocarcinoma patients. MTV and TLG values were significantly higher in GLUT1-positive than GLUT-negative adenocarcinomas; however, CAIX expression did not show this pattern. GLUT1-positive adenocarcinoma patients had a lower OS than GLUT1-negative patients (p<0.001), whereas CAIX-positive and CAIX-negative patients showed similar OS rates (p=0.226). Patients with high MTV and TLG values showed lower OS rates than those with low MTV and TLG values. Multivariate analysis showed that GLUT1 positivity was an independent risk factor for a lower OS rate in lung adenocarcinoma patients (hazard ratio=2.574, p=0.016). GLUT1 expression was associated with micropapillary/solid histology, lymphovascular invasion, and advanced pTNM stage.

CONCLUSIONS

MTV and TLG values, and GLUT1 expression, significantly differed between patients with squamous cell carcinoma and adenocarcinoma. High GLUT1 expression levels were significantly associated with MTV and TLG values and adverse clinical outcomes in patients with adenocarcinoma.

Role of p14ARF and p15INK4B promoter methylation in patients with lung cancer: a systematic meta-analysis

Background

The cyclin-dependent kinase inhibitors p14^ARF and p15^INK4B are tumor suppressor genes that have been reported to be silenced through promoter methylation in many human cancers. However, the strength of association between p14^ARF or p15^INK4B promoter methylation and lung cancer remains unclear. Thus, we first determined whether p14^ARF and p15^INK4B promoter methylation played a key role in the carcinogenesis of lung cancer.

Methods

Eligible studies were selected from the online electronic databases. The pooled odds ratios or hazard ratios and 95% confidence intervals were calculated and summarized.

Results

Finally, 12 studies with 625 lung cancer samples and 488 nontumor samples were included under the fixed-effects model. The pooled odds ratio showed that p14^ARF promoter methylation was observed to be significantly higher in non-small-cell lung cancer (NSCLC) than in nontumor samples (P<0.001). No significant correlation was found between p15^INK4B promoter methylation and lung cancer (P=0.27). Subgroup analysis of ethnicity revealed that p14^ARF promoter methylation was significantly related to the risk of NSCLC in Asian and Caucasian populations. Subgroup analysis of sample type demonstrated that p14^ARF promoter methylation was correlated with the risk of NSCLC in tissue samples (P<0.001), but not in bronchoalveolar lavage fluid and blood samples. P14^ARF promoter methylation from one study was not significantly correlated with overall survival of patients with NSCLC. Promoter methylation of p14^ARF and p15^INK4B was not correlated with clinicopathological characteristics, such as gender status, smoking status, tumor differentiation, and tumor stage (P>0.05).

Conclusion

Our findings suggested that p14^ARF promoter methylation may play an important role in the carcinogenesis of lung cancer, but not p15^INK4B promoter methylation. Promoter methylation of p14^ARF and p15^INK4B was not associated with clinicopathological parameters. However, more extensive large-scale studies are essential to further validate our study.