SIRT1 regulates Mxd1 during malignant melanoma progression

In a murine melanoma model, malignant transformation promoted by a sustained stress condition was causally related to increased levels of reactive oxygen species resulting in DNA damage and massive epigenetic alterations. Since the chromatin modifier Sirtuin-1 (SIRT1) is a protein attracted to double-stranded DNA break (DSB) sites and can recruit other components of the epigenetic machinery, we aimed to define the role of SIRT1 in melanomagenesis through our melanoma model. The DNA damage marker, gamma H2AX was found increased in melanocytes after 24 hours of deadhesion, accompanied by increased SIRT1 expression and decreased levels of its target, H4K16ac. Moreover, SIRT1 started to be associated to DNMT3B during the stress condition, and this complex was maintained along malignant progression. Mxd1 was identified by ChIP-seq among the DNA sequences differentially associated with SIRT1 during deadhesion and was shown to be a common target of both, SIRT1 and DNMT3B. In addition, Mxd1 was found downregulated from pre-malignant melanocytes to metastatic melanoma cells. Treatment with DNMT inhibitor 5AzaCdR reversed the Mxd1 expression. Sirt1 stable silencing increased Mxd1 mRNA expression and led to down-regulation of MYC targets, such as Cdkn1a, Bcl2 and Psen2, whose upregulation is associated with human melanoma aggressiveness and poor prognosis. We demonstrated a novel role of the stress responsive protein SIRT1 in malignant transformation of melanocytes associated with deadhesion. Mxd1 was identified as a new SIRT1 target gene. SIRT1 promoted Mxd1 silencing, which led to increased activity of MYC oncogene contributing to melanoma progression.FAPESP [2011/0166-38, 2011/12306-1, 2014/13663-0, 2015/07925-5, 2016/06488-3]DAAD [PKZ A/12/79134]FAPESP/BAYLAT [2012/51300-7]Univ Fed Sao Paulo UNIFESP, Dept Pharmacol, Ontogeny & Epigenet Lab, Sao Paulo, SP, BrazilUniv Sao Paulo, Ribeirao Preto Med Sch, Dept Genet, Ribeirao Preto, SP, BrazilFriedrich Alexander Univ Erlangen Nurnberg FAU, Inst Pathol, Expt Tumorpathol, Erlangen, GermanyFriedrich Alexander Univ Erlangen Nurnberg FAU, Dept Pediat & Adolescent Med, Erlangen, GermanyUniv Fed Sao Paulo UNIFESP, Dept Pharmacol, Ontogeny & Epigenet Lab, Sao Paulo, SP, BrazilFAPESP [2011/0166-38, 2011/12306-1, 2014/13663-0, 2015/07925-5, 2016/06488-3]DAAD [PKZ A/12/79134]FAPESP/BAYLAT [2012/51300-7]Web of Scienc

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression

The epigenetic evolution of glioma is determined by the IDH1 mutation status and treatment regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histological progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neo-angiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution towards an IDHwt-like phenotype

Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas

Recurrence of meningiomas is unpredictable by current invasive methods based on surgically removed specimens. Identification of patients likely to recur using noninvasive approaches could inform treatment strategy, whether intervention or monitoring. In this study, we analyze the DNA methylation levels in blood (serum and plasma) and tissue samples from 155 meningioma patients, compared to other central nervous system tumor and non-tumor entities. We discover DNA methylation markers unique to meningiomas and use artificial intelligence to create accurate and universal models for identifying and predicting meningioma recurrence, using either blood or tissue samples. Here we show that liquid biopsy is a potential noninvasive and reliable tool for diagnosing and predicting outcomes in meningioma patients. This approach can improve personalized management strategies for these patients

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.</p

Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes

Depletion of 5-hydroxymethylcytosine in aggressive G-CIMP subtype

5-hydroxymethylcytosine (5hmC) is an oxidation product of 5-methylcytosine, a reaction potentially mediated by the Tet family of enzymes. Levels of 5hmC were reported to be lower in glioblastoma and because gliomas carrying an IDH1/2 mutation (high or low grade) manifest a CpG island methylator phenotype (G-CIMP), we decided to investigate 5hmC levels in G-CIMP subtypes, G-CIMP-high and G-CIMP-low, due to their distinct clinical outcome, independent of histological grade. We generated genome-wide maps of 5hmC for G-CIMP-low (n=4) and G-CIMP-high (n=6) samples by hMeDIP-seq (∼ 46M reads per sample). We also have additional whole-genome bisulfite sequencing (WGBS) data for G-CIMPlow (n=1), G-CIMP-high (n=2) and non-tumor brain (n=2) samples. When we compared hMeDIP-seq with WGBS, we found a positive correlation between DNA hypomethylation and depletion of 5hmC in G-CIMPlow. As reported in previous studies, the highest concentration of 5hmC is within gene bodies (75% vs. 25% in intergenic regions). However, we observed an unbalanced level of 5hmC in G-CIMP subtypes (68,397 5hmC peaks lost in G-CIMP-low vs. 2,554 gained, FDR \u3c 0.05). G-CIMP-high has an abundant number of 5hmC peaks, whereas G-CIMP-low seems to have poor 5hmC density in the same regions. We observed G-CIMP-low may arise from G-CIMP-high during tumor recurrence, and we suggest that loss of 5hmC within G-CIMP tumors lead to a more aggressive phenotype. Interestly, 85% of peaks associated with loss of 5hmC overlap regions with loss of intergenic enhancer activity in G-CIMP-low, as defined by H3K27ac peaks. Furthermore, 22% of genes with intronic loss of 5hmC in G-CIMP-low samples are downregulated (FDR \u3c 0.05). We did not find any distinct genomic alterations associated with G-CIMP-low nor did we observe differential expression of genes from the Tet family, we suggest that a yet to be determined alternative mechanism may be driving an aberrant loss of 5hmC in G-CIMP-low

Deep Learning Classification of Neuro-Oncology Medical Documents

Introduction Precision medicine and big data for cancer discovery requires well curated indexed critical health care data, however to date limited resources exist that successfully parse out unstructured clinical data in neuro-oncology. Current practice relies on time consuming manual extraction by researchers or clinicians resulting in data inconsistency and limitation in data set volume. Rule-based natural language processing algorithms could be used for simple consistent text, but medical documents are created longitudinally by multiple people across long periods of time resulting in inconsistencies and semantic heterogeneity that render rule-based techniques insufficient. Methods We applied a deep learning text classification method to multiple clinical document categories including clinical pathology reports and a text based clinical database spanning 17 years of clinical narratives with approximately 4000 unique cases. For this study we identified clinically relevant molecular criteria for glioma outlined in the WHO 2016 CNS classification of tumors including IDH mutation, MGMT methylation, and 1p19q co-deletion status. Using a convolutional neural network with two densely connected layers of 30 rectified linear nodes we were able to classify patients into their respected molecular cohort with an accuracy of 98%. Conclusion Parsing of unstructured text based clinical narratives and pathology reports using convolutional neural networks is a promising method to extract heterogeneous molecular data in neuro-oncology for large scale data analysis