Environmental exposures strongly influence the development and progression of asthma. We have previously demonstrated that mice exposed to a diet enriched with methyl donors during vulnerable periods ...of fetal development can enhance the heritable risk of allergic airway disease through epigenetic changes. There is conflicting evidence on the role of folate (one of the primary methyl donors) in modifying allergic airway disease.
We hypothesized that blocking folate metabolism through the loss of methylene-tetrahydrofolate reductase (Mthfr) activity would reduce the allergic airway disease phenotype through epigenetic mechanisms.
Allergic airway disease was induced in C57BL/6 and C57BL/6Mthfr-/- mice through house dust mite (HDM) exposure. Airway inflammation and airway hyperresponsiveness (AHR) were measured between the two groups. Gene expression and methylation profiles were generated for whole lung tissue. Disease and molecular outcomes were evaluated in C57BL/6 and C57BL/6Mthfr-/- mice supplemented with betaine.
Loss of Mthfr alters single carbon metabolite levels in the lung and serum including elevated homocysteine and cystathionine and reduced methionine. HDM-treated C57BL/6Mthfr-/- mice demonstrated significantly less airway hyperreactivity (AHR) compared to HDM-treated C57BL/6 mice. Furthermore, HDM-treated C57BL/6Mthfr-/- mice compared to HDM-treated C57BL/6 mice have reduced whole lung lavage (WLL) cellularity, eosinophilia, and Il-4/Il-5 cytokine concentrations. Betaine supplementation reversed parts of the HDM-induced allergic airway disease that are modified by Mthfr loss. 737 genes are differentially expressed and 146 regions are differentially methylated in lung tissue from HDM-treated C57BL/6Mthfr-/- mice and HDM-treated C57BL/6 mice. Additionally, analysis of methylation/expression relationships identified 503 significant correlations.
Collectively, these findings indicate that the loss of folate as a methyl donor is a modifier of allergic airway disease, and that epigenetic and expression changes correlate with this modification. Further investigation into the mechanisms that drive this observation is warranted.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Prenatal and postnatal cigarette smoke exposure enhances the risk of developing asthma. Despite this as well as other smoking related risks, 11% of women still smoke during pregnancy. We hypothesized ...that cigarette smoke exposure during prenatal development generates long lasting differential methylation altering transcriptional activity that correlates with disease. In a house dust mite (HDM) model of allergic airway disease, we measured airway hyperresponsiveness (AHR) and airway inflammation between mice exposed prenatally to cigarette smoke (CS) or filtered air (FA). DNA methylation and gene expression were then measured in lung tissue. We demonstrate that HDM-treated CS mice develop a more severe allergic airway disease compared to HDM-treated FA mice including increased AHR and airway inflammation. While DNA methylation changes between the two HDM-treated groups failed to reach genome-wide significance, 99 DMRs had an uncorrected p-value < 0.001. 6 of these 99 DMRs were selected for validation, based on the immune function of adjacent genes, and only 2 of the 6 DMRs confirmed the bisulfite sequencing data. Additionally, genes near these 6 DMRs (Lif, Il27ra, Tle4, Ptk7, Nfatc2, and Runx3) are differentially expressed between HDM-treated CS mice and HDM-treated FA mice. Our findings confirm that prenatal exposure to cigarette smoke is sufficient to modify allergic airway disease; however, it is unlikely that specific methylation changes account for the exposure-response relationship. These findings highlight the important role in utero cigarette smoke exposure plays in the development of allergic airway disease.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing ...informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.
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Background: The measurement of tumor mutational burden (TMB) is critical to select patients who are expected to respond to immune checkpoint inhibitors or immune-oncology (IO). The majority of ...the clinical guidelines on the interpretation & utility of TMB values are based on studies performed on lung cancer, setting a cutoff of 10. Laboratories that are using comprehensive genomic profiling (CGP) for tumor testing are reporting TMB values &/or interpretations (high/low) beyond lung cancer. Multiple studies have shown that the TMB signature is not universal, but rather tumor &/or even patient-specific. However, the pan-cancer trial for IO (KEYNOTE-158) failed to consider setting different cutoffs per tumor type. Currently, no major guidelines or consensus statements address the issue of reporting TMB as a biomarker beyond lung cancer. In the current study, the membership of the SEQUOIA (Sequencing & Oncology Informatics Academic Team) Consortium investigates the landscape of TMB values across multiple cancer types. Methods: We investigated TMB values in 11,670 patient samples (M = 6225; F= 5445) across 13 different tumor types & histological subtypes, including cancers with lung, colorectal, gastrointestinal, brain, prostate, pancreatic, biliary, endometrioid, ovarian, skin, hematological (CLL myeloma) & lymphoid origin. All samples were processed by a CGP panel of 523 genes. Multiple specimen types were included in the study consisting of tissue, blood, marrow, & lymph node. Results: The range of TMB values varied significantly across different cancer types & histological subtypes. The colorectal, melanoma & endometrial cancers have a wider range of TMB values (2-400 mutations/MB) relative to prostate, breast, myeloma, & serous cancers (0-30 mutations/MB). Along with the range, the mean, & median TMB values are also significantly varied across these tumor types. We also identified that a subset of patients exhibits high TMB (>30 mutations/MB) values across almost all types of cancer. Conclusions: TMB values & their association with response to immune checkpoint inhibitors are not very well studied in all cancer types, although a TMB cut-off of 10 mutations/MB was defined as TMB-high for FDA-approved IO in patients with unresectable or metastatic solid tumors. The range, mean, median, cut-offs & clinical interpretations of TMB-high & low for IO based therapies for different tumor types has not been well established. Our data confirm the wide range, mean, & median across different tumor types, & thus laboratories & oncologists need to be cautious in the clinical interpretation of TMB values for patient management. Future studies should assess responsiveness to IO in specific tumor types based on TMB value to determine tumor-specific TMB cutoff values.
Abstract
Introduction:
Tumor mutational burden (TMB) is the number of somatic mutations per megabase in a tumor's genome and has shown promise as a predictive biomarker of response to immune ...checkpoint inhibitors across several cancers. TMB is typically measured by whole exome sequencing (WES TMB) or by targeted next-generation sequencing gene panels (panel TMB). As more assays are developed to estimate TMB, harmonization is emerging as an unmet need and is a key goal of the Friends of Cancer Research (Friends) TMB Harmonization Project. Phase I of the Harmonization Project demonstrated correlation between panel TMB and WES TMB using TCGA data and defined theoretical sources of variability across panels. In phase IIA, sustainable TMB reference standard materials generated from human derived cell lines were used to characterize variability in TMB measurements across panels and assessed for utility in TMB alignment. Phase IIB aims to characterize variability in TMB measurements in clinical samples and to establish best practices for estimating and aligning TMB in order to improve consistency across panels.
Methods:
Fifteen laboratories (16 targeted gene panels) at different stages of development participated in phase IIB. Thirty formalin-fixed paraffin-embedded (FFPE) samples with >30% tumor content were acquired; tumor DNA was isolated by a single reference lab. TMB values were calculated for DNA extracted from lung (N=10), bladder (N=10), and gastric tumors (N=10) using WES and a uniform bioinformatics pipeline agreed upon by all Consortium members. DNA samples were also sent to all laboratories, and each used their own sequencing and bioinformatics pipelines to estimate TMB from the genes represented in their respective panels. For each tumor sample, a median across panel TMB estimates was calculated; individual panel TMB estimates were translated to fold-changes relative to the sample median to quantify variability. Association between WES TMB (reference) and panel TMB will be assessed by regression analysis; dependence of association on cancer type was investigated.
Results:
A subset of tumor samples (9 bladder, 7 lung, and 5 gastric) was analyzed using 11 panels at the time of abstract submission. Median panel TMB values ranged 0.60 - 40.26 across samples, with median of median values of 5.35. Fold-change from sample-level medians ranged 0x - 6.67x. Assessment of these clinical samples by WES and all 16 gene panels, as well as regression analysis results, are forthcoming.
Conclusions:
The Friends TMB Harmonization Project has made substantial progress in characterization of TMB measurement variability and association between WES TMB and panel TMB. These are important steps toward alignment of TMB estimates generated by different gene panels which may improve the interpretation of findings within clinical development programs and ultimately enhance the usefulness of this predictive biomarker in clinical decision making.
Citation Format: Diana M. MERINO, Laura M. Yee, Lisa M. McShane, P. Mickey Williams, Tomas Vilimas, Rajesh Patidar, J. Carl Barrett, Shu-Jen Chen, Jen-Hao Cheng, Jeffrey M. Conroy, Dinesh Cyanam, Kenneth R. Eyring, David A. Fabrizio, Vincent Funari, Elizabeth P. Garcia, Sean T. Glenn, Christopher D. Gocke, Vikas Gupta, Lisa M. Haley, Matthew D. Hellmann, Laurel Keefer, Lauryn R. Keeler, Brett Kennedy, Alexander J. Lazar, Laura E. MacConaill, Kristen L. Meier, Arnaud Papin, Naiyer A. Rizvi, Ethan Sokol, Phillip Stafford, John F. Thompson, Warren Tom, Victor J. Weigman, Mingchao Xie, Chen Zhao, Mark D. Stewart, Jeff Allen. Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project abstract. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5671.
Prenatal and postnatal cigarette smoke exposure enhances the risk of developing asthma. Despite this as well as other smoking related risks, 11% of women still smoke during pregnancy. We hypothesized ...that cigarette smoke exposure during prenatal development generates long lasting differential methylation altering transcriptional activity that correlates with disease. In a house dust mite (HDM) model of allergic airway disease, we measured airway hyperresponsiveness (AHR) and airway inflammation between mice exposed prenatally to cigarette smoke (CS) or filtered air (FA). DNA methylation and gene expression were then measured in lung tissue. We demonstrate that HDM-treated CS mice develop a more severe allergic airway disease compared to HDM-treated FA mice including increased AHR and airway inflammation. While DNA methylation changes between the two HDM-treated groups failed to reach genome-wide significance, 99 DMRs had an uncorrected p-value < 0.001. 6 of these 99 DMRs were selected for validation, based on the immune function of adjacent genes, and only 2 of the 6 DMRs confirmed the bisulfite sequencing data. Additionally, genes near these 6 DMRs (Lif, Il27ra, Tle4, Ptk7, Nfatc2, and Runx3) are differentially expressed between HDM-treated CS mice and HDM-treated FA mice. Our findings confirm that prenatal exposure to cigarette smoke is sufficient to modify allergic airway disease; however, it is unlikely that specific methylation changes account for the exposure-response relationship. These findings highlight the important role in utero cigarette smoke exposure plays in the development of allergic airway disease.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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