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"Kanker payudara merupakan tipe kanker yang paling banyak terjadi didunia dan menjadi penyebab kematian terbanyak pada negara berkembang. Subtipe kanker payudara saat ini dapat diklasifikasikan berdasarkan profil ekspresi gennya dengan immunohistokimia (IHK) menjadi subtipe Luminal A, Luminal B, HER2+, dan TNBC. Namun, IHK memiliki beberapa keterbatasan yang dapat menyebabkan kesalahan klasifikasi. Penelitian ini bertujuan melakukan integrasi data multi-omik (genomik, epigenomik, dan transkriptomik) serta penggunaan machine learning dalam penentuan biomarker subtipe kanker payudara.Metode Isolat DNA dari pasien kanker payudara yang menjalani pengobatan di RSUPN Cipto Mangunkusumo dan RS Kanker Dharmais Jakarta sebanyak 48 subjek digunakan dalam penelitian ini. Untuk mengidentifikasi mutasi dan metilasi DNA, digunakan kit Illumina Infinium Asian Screening Array dan Illumina Infinium EPIC Human methylation array v2.0 yang kemudian dilakukan pembacaan dengan Illumina iScan. Biomarker mutasi dan metilasi DNA kemudian dianalisis dengan machine learning untuk mendapatkan biomarker subtipe kanker payudara. Pendekatan transkriptomik dengan analisis DEG (Differentially Expressed Genes) dilakukan dengan menggunakan dataset yang berada pada basis data GEO (Gene Expression Omnibus), yaitu dataset GSE33447 dan GSE20685. Studi translasional untuk identifikasi biomarker metilasi DNA, dilakukan dengan metode MSP (methylated specific PCR).Hasil Didapatkan biomarker mutasi dan metilasi DNA yang signifikan berasosiasi dengan masing-masing subtipe kanker payudara serta berkaitan dengan ekspresi gennya, yaitu Luminal A (rs2355062 dan cg14397888), Luminal B (rs36087647 dan cg14397888), HER2+ (rs4925108 dan cg25910261), TNBC (rs137966431, rs886040223 dan cg26371957). Adanya mutasi pada BRCA2 (rs886040223) pada pasien TNBC, diprediksi akan memberikan respon yang sensitif terhadap pemberian terapi inhibitor PARP. Kit diagnostik berbasis biomarker omik dengan metode methylation-specific PCR (MSP) dapat menentukan status metilasi DNA pada biomarker cg14397888 untuk subtipe Luminal A dan Luminal B dengan akurasi 75% dan 76%.Kesimpulan Pendekatan biomarker multiomik pada pasien kanker payudara dapat digunakan sebagai pilihan untuk melakukan klasifikasi subtipe kanker payudara dan memprediksi pilihan terapi yang tepat.......IntroductionBreast cancer is the predominant form of cancer globally and is the primary cause of mortality in emerging nations. Currently, breast cancer subtypes can be classified using immunohistochemistry (IHC) into four subtypes: Luminal A, Luminal B, HER2+, and TNBC. Nevertheless, the IHC possesses various constraints that may result in misclassification. The objective of this study is to combine multiple types of biological data (genomic, epigenomic, and transcriptomic) and apply machine learning techniques to identify biomarkers for different subtypes of breast cancer.MethodDNA isolates obtained from 48 breast cancer patients who were receiving therapy at RSUPN Cipto Mangunkusumo and Dharmais Cancer Hospital Jakarta. The Illumina Infinium Asian Screening Array and Illumina Infinium EPIC Human methylation array v2.0 kits were employed to detect mutations and DNA methylation which were then read using Illumina iScan. Machine learning was used to examine DNA mutation and methylation biomarkers in order to identify biomarkers specific to different subtypes of breast cancer. The transcriptomics approach was employed to analyze differentially expressed genes (DEGs) utilizing datasets from the Gene Expression Omnibus (GEO) database, namely the GSE33447 and GSE20685 datasets. The MSP approach was employed to conduct translational research to identify DNA methylation biomarkers.ResultsSignificant DNA mutations and methylation biomarkers were discovered to be linked to each subtype of breast cancer and were found to be associated with gene expression, namely, Luminal A (rs2355062 and cg14397888), Luminal B (rs36087647 and cg14397888), HER2+ (rs4925108 and cg25910261), and TNBC (rs137966431, rs886040223 and cg26371957). Predictions suggest that the presence of mutations in the BRCA2 gene (rs886040223) in TNBC patients will likely result in a highly responsive reaction to PARP inhibitor treatment. A diagnostic kit utilizing the methylation-specific PCR (MSP) approach can accurately assess the DNA methylation status of the cg14397888 biomarker for Luminal A and Luminal B subtypes with an accuracy of 75% and 76%, respectively.ConclusionThe utilization of the multiomics biomarker strategy in breast cancer patients offers a viable method for categorizing breast cancer subtypes and forecasting suitable therapy interventions.                                                                                                                                                                    "

"The focus of this volume is on critical epigenetic regulation and chromatin remodeling events that occur in the nervous system and on the presumed mechanisms that operate within neurons to translate them into long-lasting neuronal responses.Recent years have seen spectacular advances in the filed of epigenetics. These have attracted the interest of researchers in many fields and evidence connecting epigentic regulation to brain functions has been accumulationg. Neurons daily convert a variety of external stimuli into rapid or long-lasting changes in gene expression. A variety of studies have centered on the molcular mechanisms implicated in epigentic control and how these may operte in concert. It will be critical to unravel how specifity is achieved. The focus of this volume is on critical epigenetic regulation and chromatin remodeling events that occur in the nervous system and on the presumed mechanisms that operate within neurons to translate them into long-lasting neuronal responses."

"Epigenetics in psychiatry covers all major areas of psychiatry in which extensive epigenetic research has been performed, fully encompassing a diverse and maturing field, including drug addiction, bipolar disorder, epidemiology, cognitive disorders, and the uses of putative epigenetic-based psychotropic drugs. Uniquely, each chapter correlates epigenetics with relevant advances across genomics, transcriptomics, and proteomics. The book acts as a catalyst for further research in this potentially very important and useful area of psychiatry.The elucidation of basic principles of epigenetic biology points to the creation of more optimal and effective therapies for major classes of psychiatric disease. In this regard, epigenetic therapy, the use of drugs to correct epigenetic defects, may help in the pharmacotherapy of patients with these disorders. With time, such advances may eventually point to replacements for psychotropic drugs presently of symptomatic value and low efficacy. Moreover, there is evidence to suggest that other forms of treatment commonly used in the management of psychiatric disorders, like psychotherapy and electroconvulsive therapy, may also act by epigenetic mechanisms."

"This book discusses the various methods to reprogram cells, the control and determination of cell identity, the epigenetic models that have emerged and the application of iPS cell therapy for brain diseases, in particular Parkinson’s disease and Vanishing White Matter (VWM).​"