P16INK4a gene promoter methylation as a biomarker for the diagnosis of non-small cell lung cancer: An updated meta-analysis

Cuproptosis in lung cancer: mechanisms and therapeutic potential

Cuproptosis, a recently identified form of cell death that differs from other forms, is induced by the disruption of the binding of copper to mitochondrial respiratory acylation components. Inducing cell cuproptosis and targeting cell copper death pathways are considered potential directions for treating tumor diseases. We have provided a detailed introduction to the metabolic process of copper. In addition, this study attempts to clarify and summarize the relationships between cuproptosis and therapeutic targets and signaling pathways of lung cancer. This review aims to summarize the theoretical achievements for translating the results of lung cancer and cuproptosis experiments into clinical treatment.

Analyses of P16INK4a gene promoter methylation relative to molecular, demographic and clinical parameters characteristics in non-small cell lung cancer patients: A pilot study

BACKGROUND

The aim of this study was to examine the methylation status of p16^INK4a promoter region in non small cell lung cancer (NSCLC) patients and their associations with single nucleotide polymorphisms (SNPs) of the epidermal growth factor receptor (EGFR) gene, as well as with demographic or clinical characteristics.

METHODS

Formalin-fixed and paraffin-embedded (FFPE) DNA samples extracted from 22 NSCLC patients were analyzed with methylation-specific polymerase chain reaction (PCR) method to obtain promoter methylation profile. The same cohort was genotyped for - 216G > T, -191 C > A, and 181,946 C > T EGFR SNPs.

RESULTS

There was a significant association between methylated p16^INK4a in patients prior therapy (p = 0.017) since a significantly higher frequency of methylated p16^INK4a was detected in these patients (40.9%) in comparison to frequency in patients after therapy (31.8%). Also, a higher frequency of methylated p16^INK4a was detected among patients with leucopenia (p = 0.056). No associations were observed between the methylation status of the p16^INK4a promoter region and EGFR SNPs or other clinical and demographic data in this cohort.

CONCLUSION

High frequency of methylation of the p16^INK4a gene promoter was observed in NSCLC patients prior therapy and with leucopenia that can indicate their significance related to advanced clinical stage.

Bronchoalveolar Lavage Fluid-Isolated Biomarkers for the Diagnostic and Prognostic Assessment of Lung Cancer

Lung cancer is considered one of the most fatal malignant neoplasms because of its late detection. Detecting molecular markers in samples from routine bronchoscopy, including many liquid-based cytology procedures, such as bronchoalveolar lavage fluid (BALF), could serve as a favorable technique to enhance the efficiency of a lung cancer diagnosis. BALF analysis is a promising approach to evaluating the tumor progression microenvironment. BALF's cellular and non-cellular components dictate the inflammatory response in a cancer-proliferating microenvironment. Furthermore, it is an essential material for detecting clinically significant predictive and prognostic biomarkers that may aid in guiding treatment choices and evaluating therapy-induced toxicities in lung cancer. In the present article, we have reviewed recent literature about the utility of BALF analysis for detecting markers in different stages of tumor cell metabolism, employing either specific biomarker assays or broader omics approaches.

Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study

Lung adenocarcinoma (LUAD) is a common and very lethal cancer. Accurate staging is a prerequisite for its effective diagnosis and treatment. Therefore, improving the accuracy of the stage prediction of LUAD patients is of great clinical relevance. Previous works have mainly focused on single genomic data information or a small number of different omics data types concurrently for generating predictive models. A few of them have considered multi-omics data from genome to proteome. We used a publicly available dataset to illustrate the potential of multi-omics data for stage prediction in LUAD. In particular, we investigated the roles of the specific omics data types in the prediction process. We used a self-developed method, Omics-MKL, for stage prediction that combines an existing feature ranking technique Minimum Redundancy and Maximum Relevance (mRMR), which avoids redundancy among the selected features, and multiple kernel learning (MKL), applying different kernels for different omics data types. Each of the considered omics data types individually provided useful prediction results. Moreover, using multi-omics data delivered notably better results than using single-omics data. Gene expression and methylation information seem to play vital roles in the staging of LUAD. The Omics-MKL method retained 70 features after the selection process. Of these, 21 (30%) were methylation features and 34 (48.57%) were gene expression features. Moreover, 18 (25.71%) of the selected features are known to be related to LUAD, and 29 (41.43%) to lung cancer in general. Using multi-omics data from genome to proteome for predicting the stage of LUAD seems promising because each omics data type may improve the accuracy of the predictions. Here, methylation and gene expression data may play particularly important roles.

Comparison of Bisulfite Pyrosequencing and Methylation-Specific qPCR for Methylation Assessment

Different methodological approaches are available to assess DNA methylation biomarkers. In this study, we evaluated two sodium bisulfite conversion-dependent methods, namely pyrosequencing and methylation-specific qPCR (MS-qPCR), with the aim of measuring the closeness of agreement of methylation values between these two methods and its effect when setting a cut-off. Methylation of tumor suppressor gene p16/INK4A was evaluated in 80 lung cancer patients from which cytological lymph node samples were obtained. Cluster analyses were used to establish methylated and unmethylated groups for each method. Agreement and concordance between pyrosequencing and MS-qPCR was evaluated with Pearson’s correlation, Bland–Altman, Cohen’s kappa index and ROC curve analyses. Based on these analyses, cut-offs were derived for MS-qPCR. An acceptable correlation (Pearson’s R2 = 0.738) was found between pyrosequencing (PYRmean) and MS-qPCR (NMP; normalized methylation percentage), providing similar clinical results when categorizing data as binary using cluster analysis. Compared to pyrosequencing, MS-qPCR tended to underestimate methylation for values between 0 and 15%, while for methylation >30% overestimation was observed. The estimated cut-off for MS-qPCR data based on cluster analysis, kappa-index agreement and ROC curve analysis were much lower than that derived from pyrosequencing. In conclusion, our results indicate that independently of the approach used for estimating the cut-off, the methylation percentage obtained through MS-qPCR is lower than that calculated for pyrosequencing. These differences in data and therefore in the cut-off should be examined when using methylation biomarkers in the clinical practice.

Loss of CDKN2A at chromosome 9 has a poor clinical prognosis and promotes lung cancer progression

Objective

This study aimed to identify critical genes involved in the tumor biology of lung cancer via datamining of The Cancer Genome Atlas (TCGA) with special focus on gene copy number variation.

Methods

Genomic deletion and amplification were analyzed with cBioportal online tools. Relative expression of Cyclin Dependent Kinase Inhibitor 2A (CDKN2A) was analyzed by both real‐time polymerase chain reaction (PCR) and Western blot. The abundance of methylthioadenosine phosphorylase (MTAP) and epithelial‐mesenchymal transition markers were analyzed by real‐time PCR. Cell proliferation was determined by cell counting kit‐8 method and cell viability was measured with 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay. The cell migration and invasion were measured with transwell chamber assay, and migrative capacity was further evaluated by wound healing assay.

Results

We found the frequent loss of CDKN2A was associated with its downregulation in lung cancer, and siRNA‐mediated CDNKN2A knockdown significantly stimulated cell proliferation, invasion, and migration. Mechanistically, we unraveled that MTAP, which was positively correlated with CDKN2A, predominantly mediated the antitumoral function of CDKN2A in lung cancer.

Conclusion

Our study consolidated the involvement of CDKN2A‐MTAP signaling in the context of lung cancer.

DNA Methylation Markers in Lung Cancer

Lung cancer is the most common cancer and the leading cause of cancer-related morbidity and mortality worldwide. As early symptoms of lung cancer are minimal and non-specific, many patients are diagnosed at an advanced stage. Despite a concerted effort to diagnose lung cancer early, no biomarkers that can be used for lung cancer screening and prognosis prediction have been established so far. As global DNA demethylation and gene-specific promoter DNA methylation are present in lung cancer, DNA methylation biomarkers have become a major area of research as potential alternative diagnostic methods to detect lung cancer at an early stage. This review summarizes the emerging DNA methylation changes in lung cancer tumorigenesis, focusing on biomarkers for early detection and their potential clinical applications in lung cancer.

Clinical Significance of P16 Gene Methylation in Lung Cancer

Lung cancer is the leading cause of death from cancer in China. The lack of early screening technologies makes most patients to be diagnosed at advanced stages with a poor prognosis which often miss the best treatment opportunities. Thus, identifying biomarkers for minimally invasive detection and prognosis of early stage disease is urgently needed. Genetic and epigenetic alterations that promote tumorigenesis and metastasis exist in multiple cancers. These aberrant alterations usually represent early events in cancer progression suggesting their potential applications as a biomarker for cancer prediction. Studies have shown that DNA methylation is one of the key factors in progression of lung cancer. P16 promoter methylation is one of the most common epigenetic change plays a key role in lung cancer. In this review, we highlight the p16 gene methylation and its clinical significance in lung cancer.

Expression and role of p16 and GLUT1 in malignant diseases and lung cancer: A review

Non‐small cell lung cancer (NSCLC) is the leading cause of cancer death and in most cases it is often diagnosed at an advanced stage. Many genetic and microenvironmental factors are able to modify the cell cycle inducing carcinogenesis and tumor growth. Among the metabolic and genetic factors that come into play in carcinogenesis and tumor cell differentiation and growth there are two different proteins that should be considered which are glucose transporters (GLUTs) and p16^INK4 The first are glucose transporters which are strongly involved in tumor metabolism, notably accelerating cancer cell metabolism both in aerobic and anaerobic conditions. There are different subtypes of GLUT family factors of which GLUT 1 is the most important and widely expressed. By contrast, p16 is mainly a tumor‐suppressor protein that acts on cyclin‐dependent kinase favoring cell cycle arrest in the G1 phase. Our search focused on the action of the aforementioned factors.

Epigenetic Silencing of LMX1A Contributes to Cancer Progression in Lung Cancer Cells

Epigenetic modification is considered a major mechanism of the inactivation of tumor suppressor genes that finally contributes to carcinogenesis. LIM homeobox transcription factor 1α (LMX1A) is one of the LIM-homeobox-containing genes that is a critical regulator of growth and differentiation. Recently, LMX1A was shown to be hypermethylated and functioned as a tumor suppressor in cervical cancer, ovarian cancer, and gastric cancer. However, its role in lung cancer has not yet been clarified. In this study, we used public databases, methylation-specific PCR (MSP), reverse transcription PCR (RT-PCR), and bisulfite genomic sequencing to show that LMX1A was downregulated or silenced due to promoter hypermethylation in lung cancers. Treatment of lung cancer cells with the demethylating agent 5-aza-2'-deoxycytidine restored LMX1A expression. In the lung cancer cell lines H23 and H1299, overexpression of LMX1A did not affect cell proliferation but suppressed colony formation and invasion. These suppressive effects were reversed after inhibition of LMX1A expression in an inducible expression system in H23 cells. The quantitative RT-PCR (qRT-PCR) data showed that LMX1A could modulate epithelial mesenchymal transition (EMT) through E-cadherin (CDH1) and fibronectin (FN1). NanoString gene expression analysis revealed that all aberrantly expressed genes were associated with processes related to cancer progression, including angiogenesis, extracellular matrix (ECM) remodeling, EMT, cancer metastasis, and hypoxia-related gene expression. Taken together, these data demonstrated that LMX1A is inactivated through promoter hypermethylation and functions as a tumor suppressor. Furthermore, LMX1A inhibits non-small cell lung cancer (NSCLC) cell invasion partly through modulation of EMT, angiogenesis, and ECM remodeling.

Promoter Methylation of Selected Genes in Non-Small-Cell Lung Cancer Patients and Cell Lines

Specific gene promoter DNA methylation is becoming a powerful epigenetic biomarker in cancer diagnostics. Five genes (CDH1, CDKN2Ap16, RASSF1A, TERT, and WT1) were selected based on their frequently published potential as epigenetic markers. Diagnostic promoter methylation assays were generated based on bisulfite-converted DNA pyrosequencing. The methylation patterns of 144 non-small-cell lung cancer (NSCLC) and 7 healthy control formalin-fixed paraffin-embedded (FFPE) samples were analyzed to evaluate the applicability of the putative diagnostic markers. Statistically significant changes in methylation levels are shown for TERT and WT1. Furthermore, 12 NSCLC and two benign lung cell lines were characterized for promoter methylation. The in vitro tests involved a comparison of promoter methylation in 2D and 3D cultures, as well as therapeutic tests investigating the impact of CDH1/CDKN2Ap16/RASSF1A/TERT/WT1 promoter methylation on sensitivity to tyrosine kinase inhibitor (TKI) and DNA methyl-transferase inhibitor (DNMTI) treatments. We conclude that the selected markers have potential and putative impacts as diagnostic or even predictive marker genes, although a closer examination of the resulting protein expression and pathway regulation is needed.

Distal-type bronchiolar adenoma of the lung expressing p16INK4a - morphologic, immunohistochemical, ultrastructural and genomic analysis - report of a case and review of the literature

Bronchiolar adenoma (BA) of the lung is a rare benign neoplasm. Because of a chest abnormal shadow indicated by health checkup, a 77-year-old female nonsmoker underwent computed tomography, revealing an 8 mm ground glass nodule in the peripheral field of the right lower lobe. Wedge resection of the nodule was performed, with a frozen diagnosis of primary lung adenocarcinoma. The localized, 8 × 4 × 3 mm-sized, jelly-like mass microscopically revealed a lepidic-growing lesion composed of ciliated columnar cells, mucous cells and basal cells surrounded by mucin pool. Neither nuclear atypia nor mitotic activity was noted. Immunohistochemically, the ciliated, mucous and basal cells were positive for TTF-1 and p16^INK4a . Mucous cells were positive for napsin A and focally expressed MUC5AC. MUC6 was negative. Basal cells were positive for CK5/6, p40, p63 and podoplanin. Human papillomavirus genome was undetectable by in situ hybridization. Ultrastructurally, the bronchiolar epithelial tubules consisted of two layers, the inner nonciliated microvillous cells and the outer basal-like cells, and some of the inner cells were filled with mucin granules in cytoplasm. Molecular analysis of the tumor failed to show driver mutations. The final diagnosis was distal-type BA. The postoperative course was uneventful for 6 months.

A Diagnostic Panel of DNA Methylation Biomarkers for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common cancers and lethal diseases in the world. Recognition of the undetermined lung nodules at an early stage is useful for a favorable prognosis. However, there is no good method to identify the undetermined lung nodules and predict their clinical outcome. DNA methylation alteration is frequently observed in LUAD and may play important roles in carcinogenesis, diagnosis, and prediction. This study took advantage of publicly available methylation profiling resources and a machine learning method to investigate methylation differences between LUAD and adjacent non-malignant tissue. The prediction panel was first constructed using 338 tissue samples from LUAD patients including 149 non-malignant ones. This model was then validated with data from The Cancer Genome Atlas database and clinic samples. As a result, the methylation status of four CpG loci in homeobox A9 (HOXA9), keratin-associated protein 8-1 (KRTAP8-1), cyclin D1 (CCND1), and tubby-like protein 2 (TULP2) were highlighted as informative markers. A random forest classification model with an accuracy of 94.57% and kappa of 88.96% was obtained. To evaluate this panel for LUAD, the methylation levels of four CpG loci in HOXA9, KRTAP8-1, CCND1, and TULP2 of tumor samples and matched adjacent lung samples from 25 patients with LUAD were tested. In these LUAD patients, the methylation of HOXA9 was significantly upregulated, whereas the methylation of KRTAP8-1, CCND1, and TULP2 were downregulated obviously in tumor samples compared with adjacent tissues. Our study demonstrates that the methylation of HOXA9, KRTAP8-1, CCND1, and TULP2 has great potential for the early recognition of LUAD in the undetermined lung nodules. The findings also exhibit that the application of improved mathematic algorithms can yield accurate and particularly robust and widely applicable marker panels. This approach could greatly facilitate the discovery process of biomarkers in various fields.

Expression of p16 and p53 in non-small-cell lung cancer: clinicopathological correlation and potential prognostic impact

Aim: p16 and p53 are frequently altered intracellular pathways in cancers. We investigated the aberrant expression of p16 and its relationship with p53 and HPV status in primary non-small-cell lung carcinoma. Patients & methods: Lung tumor tissue microarray (n = 163), immunohistochemical study of p16 and p53, and HPV in-situ hybridization were analyzed. Results: p16 and p53 were detected in 50.7 and 57.3% of adenocarcinoma (ADCs; n = 75), and 35.2 and 63.6% of squamous cell carcinoma (n = 88). HPV was detected in 16 and 10.2% of ADC and squamous cell carcinoma. In ADCs, p16 positive tumors demonstrated a favorable median overall survival time of 60.9 months, compared with p16 negative tumors of 46.9 months (p < 0.05). Furthermore, we did not find significant relationships between p16 expression and HPV status, nor with p53 expression. Conclusion: p16 play an unique role in lung cancer survival. The mechanism of p16 needs to be further studied.

Comparison of value of biomarkers in diagnosing lung cancer: An overview of systematic reviews protocol

BACKGROUND

In both sexes combined, lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death. Furthermore, the incidence rate is increasing in many countries. Many lung cancer patients have a poor prognosis because they are usually diagnosed at an advanced stage. Therefore, there is an urgent need to develop effective methods for early diagnosis of lung cancer. Some systematic reviews have evaluated the value of biomarkers for diagnosing lung cancer. However, it remains unclear which biomarker has superior performance for early and accurate detection of lung cancer. This overview aims to assess the methodological and reporting quality of available systematic reviews and to find an optimal biomarker for diagnosing lung cancer.

METHODS

We searched PubMed, Embase.com, the Cochrane Library of Systematic Reviews, and Web of Science to identify relevant systematic reviews including randomized controlled trials, cross-sectional studies, case-control studies, or cohort studies that reported the value of biomarkers for diagnosing lung cancer. The methodological quality will be assessed using AMASAR-2 checklist, and the reporting quality will be assessed using PRISMA-DTA checklist. Bubble plot will be generated to map the biomarkers, methodological and reporting quality. The pairwise meta-analysis and indirect comparisons will be performed using STATA 13.0.

RESULTS

The results of this study will be published in a peer-reviewed journal CONCLUSION:: This overview will provide comprehensive evidence of different biomarkers for the diagnosis of lung cancer.

ETHICS AND DISSEMINATION

Ethics approval and patient consent are not required as this study is an overview based on published systematic reviews.