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Methyl DNA phosphate adduct formation in lung tumor tissue and adjacent normal tissue of lung cancer patients.

ABSTRACT: The formation of methyl DNA adducts is a critical step in carcinogenesis initiated by the exposure to methylating carcinogens. Methyl DNA phosphate adducts, formed by methylation of the oxygen atoms of the DNA phosphate backbone, have been detected in animals treated with methylating carcinogens. However, detection of these adducts in human tissues has not been reported. We developed an ultrasensitive liquid chromatography-nanoelectrospray ionization-high resolution tandem mass spectrometry method for detecting methyl DNA phosphate adducts. Using 50 ?g of human lung DNA, a limit of quantitation of two adducts/1010 nucleobases was achieved. Twenty-two structurally unique methyl DNA phosphate adducts were detected in human lung DNA. The adduct levels were measured in both tumor and adjacent normal tissues from 30 patients with lung cancer, including 13 current smokers and 17 current non-smokers, as confirmed by measurements of urinary cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol. Levels of total methyl DNA phosphate adducts in normal lung tissues were higher in smokers than non-smokers, with an average of 13 and 8 adducts/109 nucleobases, respectively. Methyl DNA phosphate adducts were also detected in lung tissues from untreated rats with steady-state levels of 5-7 adducts/109 nucleobases over a period of 70 weeks. This is the first study to report the detection of methyl DNA phosphate adducts in human lung tissues. The results provide new insights toward using these DNA adducts as potential biomarkers to study human exposure to environmental methylating carcinogens.

SUBMITTER: Ma B

PROVIDER: S-EPMC6875899 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Methyl DNA phosphate adduct formation in lung tumor tissue and adjacent normal tissue of lung cancer patients.

Ma Bin B Villalta Peter W PW Hochalter J Bradley JB Stepanov Irina I Hecht Stephen S SS

Carcinogenesis 20191101 11

The formation of methyl DNA adducts is a critical step in carcinogenesis initiated by the exposure to methylating carcinogens. Methyl DNA phosphate adducts, formed by methylation of the oxygen atoms of the DNA phosphate backbone, have been detected in animals treated with methylating carcinogens. However, detection of these adducts in human tissues has not been reported. We developed an ultrasensitive liquid chromatography-nanoelectrospray ionization-high resolution tandem mass spectrometry meth ...[more]

PMID: 30873516

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Project description:BackgroundAdenocarcinoma (ADC) and squamous cell carcinoma (SCC) are the most prevalent histological types among lung cancers. Distinguishing between these subtypes is critically important because they have different implications for prognosis and treatment. Normally, histopathological analyses are used to distinguish between the two, where the tissue samples are collected based on small endoscopic samples or needle aspirations. However, the lack of cell architecture in these small tissue samples hampers the process of distinguishing between the two subtypes. Molecular profiling can also be used to discriminate between the two lung cancer subtypes, on condition that the biopsy is composed of at least 50 % of tumor cells. However, for some cases, the tissue composition of a biopsy might be a mix of tumor and tumor-adjacent histologically normal tissue (TAHN). When this happens, a new biopsy is required, with associated cost, risks and discomfort to the patient. To avoid this problem, we hypothesize that a computational method can distinguish between lung cancer subtypes given tumor and TAHN tissue.MethodsUsing publicly available datasets for gene expression and DNA methylation, we applied four classification tasks, depending on the possible combinations of tumor and TAHN tissue. First, we used a feature selector (ReliefF/Limma) to select relevant variables, which were then used to build a simple naïve Bayes classification model. Then, we evaluated the classification performance of our models by measuring the area under the receiver operating characteristic curve (AUC). Finally, we analyzed the relevance of the selected genes using hierarchical clustering and IPA® software for gene functional analysis.ResultsAll Bayesian models achieved high classification performance (AUC > 0.94), which were confirmed by hierarchical cluster analysis. From the genes selected, 25 (93 %) were found to be related to cancer (19 were associated with ADC or SCC), confirming the biological relevance of our method.ConclusionsThe results from this study confirm that computational methods using tumor and TAHN tissue can serve as a prognostic tool for lung cancer subtype classification. Our study complements results from other studies where TAHN tissue has been used as prognostic tool for prostate cancer. The clinical implications of this finding could greatly benefit lung cancer patients.

Project description:BackgroundThe HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize "non-self" antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.MethodsRNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.ResultsThe genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.ConclusionsThe integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient's tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

Project description:Gene expression profiling of 60 lung adenocarcinoma tumors and their matched histologically normal adjacent lung tissue samples were analyzed using Illumina HumanWG-6 v3.0 expression beadchip. We integrated these data with DNA methylation profiles of the same samples to identify potential DNA methylation regulated genes. Lung cancer is the leading cause of cancer death worldwide and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung samples, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent downregulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and downregulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor-suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by providing new candidate DNA methylation biomarkers for early detection, identifying novel molecular alterations potentially involved in lung adenocarcinoma development/progression, and describing an epigenetic subgroup of lung adenocarcinoma associated with KRAS mutation. 58 lung adenocarcinoma and 58 adjacent non-tumor lung fresh frozen tissues were macrodissected, and total RNA was isolated to be analyzed using the Illumina HumanWG-6 v3.0 expression beadchip.

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Methyl DNA phosphate adduct formation in lung tumor tissue and adjacent normal tissue of lung cancer patients.

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Methyl DNA phosphate adduct formation in lung tumor tissue and adjacent normal tissue of lung cancer patients.

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