Ilya Shmulevich
A5061460061- Cancer Genomics and Diagnostics
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Cancer Mechanisms and Therapy
- CRISPR and Genetic Engineering
- RNA modifications and cancer
- Microbial Metabolic Engineering and Bioproduction
- Genomics and Chromatin Dynamics
- Image and Signal Denoising Methods
- Medical Imaging and Pathology Studies
- Occupational and environmental lung diseases
- Epigenetics and DNA Methylation
- Genetics, Bioinformatics, and Biomedical Research
- Cancer-related molecular mechanisms research
- Evolution and Genetic Dynamics
- RNA Research and Splicing
- Cell Image Analysis Techniques
- Ferroptosis and cancer prognosis
- Genetic factors in colorectal cancer
- MicroRNA in disease regulation
- Genomics and Phylogenetic Studies
- Acute Myeloid Leukemia Research
- Radiomics and Machine Learning in Medical Imaging
Institute for Systems Biology
2016-2025
North Seattle College
2012-2025
InSysBio (Russia)
2007-2024
Centrum Wiskunde & Informatica
2016-2020
Duke University
2020
Princeton University
2020
University of Oxford
2020
Sage Bionetworks
2019
Seattle University
2008-2016
Wellcome Sanger Institute
2016
Current clinical practice is organized according to tissue or organ of origin tumors. Now, The Cancer Genome Atlas (TCGA) Research Network has started identify genomic and other molecular commonalities among a dozen different types cancer. Emerging similarities contrasts will form the basis for targeted therapies future repurposing existing by rather than histological diseases. profiled analyzed large numbers human tumors discover aberrations at DNA, RNA, protein epigenetic levels. resulting...
Gastric cancer is a leading cause of deaths, but analysis its molecular and clinical characteristics has been complicated by histological aetiological heterogeneity. Here we describe comprehensive evaluation 295 primary gastric adenocarcinomas as part The Cancer Genome Atlas (TCGA) project. We propose classification dividing into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, amplification JAK2, CD274 (also...
We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled TCGA. Across types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized differences in macrophage or signatures, Th1:Th2 cell ratio, extent intratumoral heterogeneity, aneuploidy, neoantigen load, overall proliferation, expression immunomodulatory genes,...
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical contain key features representing the democratized nature collection process. To ensure proper use this large dataset associated genomic features, we developed standardized named Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major outcome endpoints. In...
Highlights•Alteration map of 10 signaling pathways across 9,125 samples from 33 cancer types•Reusable, curated pathway templates that include a catalogue driver genes•57% tumors have at least one potentially actionable alteration in these pathways•Co-occurrence alterations suggests combination therapy opportunitiesSummaryGenetic control cell-cycle progression, apoptosis, and cell growth are common hallmarks cancer, but the extent, mechanisms, co-occurrence differ between individual tumor...
Liver cancer has the second highest worldwide mortality rate and limited therapeutic options. We analyzed 363 hepatocellular carcinoma (HCC) cases by whole-exome sequencing DNA copy number analyses, we 196 HCC methylation, RNA, miRNA, proteomic expression also. mutation analysis identified significantly mutated genes, including LZTR1, EEF1A1, SF3B1, SMARCA4. Significant alterations or downregulation hypermethylation in genes likely to result metabolic reprogramming (ALB, APOB, CPS1) were...
We conducted comprehensive integrative molecular analyses of the complete set tumors in The Cancer Genome Atlas (TCGA), consisting approximately 10,000 specimens and representing 33 types cancer. performed clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, miRNA expression levels reverse-phase protein arrays, which all, except for revealed primarily organized by histology, tissue type, or anatomic origin. influence cell type was evident...
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify now exist, but systematic attempts combine and optimize them on large datasets are few. We report a PanCancer PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) using 26 computational tools catalog driver genes mutations. 299 with implications regarding their anatomical sites cancer/cell types. Sequence- structure-based...
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition progenitor stem-cell-like features. Here, we provide novel stemness indices for assessing degree oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic epigenetic feature sets derived from non-transformed pluripotent stem cells their progeny. Using OCLR, were able identify previously undiscovered biological mechanisms...
Abstract Motivation: Our goal is to construct a model for genetic regulatory networks such that the class: (i) incorporates rule-based dependencies between genes; (ii) allows systematic study of global network dynamics; (iii) able cope with uncertainty, both in data and selection; (iv) permits quantification relative influence sensitivity genes their interactions other genes. Results: We introduce Probabilistic Boolean Networks (PBN) share appealing properties networks, but are robust face...
Aneuploidy, whole chromosome or arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression proliferation genes. Aneuploidy anti-correlated immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss 3p squamous We applied genome...
<h2>Summary</h2> DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 types. Mutations with accompanying loss heterozygosity were observed in over 1/3 genes, including <i>TP53</i> <i>BRCA1/2</i>. Other prevalent included epigenetic silencing the direct genes <i>EXO5</i>, <i>MGMT</i>, <i>ALKBH3</i> ∼20% samples. Homologous recombination (HRD) was...
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings tumor-infiltrating lymphocytes (TILs) based on H&E from 13 tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches images. Affinity propagation revealed local spatial structure in patterns correlation with overall survival. map...
Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects events and tumor variants by reanalyzing RNA whole-exome sequencing data. Tumors have up to 30% more than normal samples. Association somatic with confirmed known trans associations in SF3B1 U2AF1 identified additional trans-acting (e.g., TADA1, PPP2R1A). Many tumors thousands not detectable samples; on average, we ≈930 exon-exon junctions ("neojunctions") typically...
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling Multiple Cancers project, our effort to generate a comprehensive encyclopedia somatic mutation calls for TCGA enable robust cross-tumor-type analyses. Our approach accounts variance and batch effects introduced by rapid advancement DNA extraction,...
Highlights•871 predisposition variants/CNVs discovered in 8% of 10,389 cases 33 cancers•Pan-cancer approach identified shared variants and genes across cancers•33 affecting activating domains oncogenes showed high expression•47 VUSs prioritized using cancer enrichment, LOH, expression other evidenceSummaryWe conducted the largest investigation to date, discovering 853 pathogenic or likely from types. Twenty-one single cross-cancer associations, including novel associations SDHA melanoma...
Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear RCC, 274 papillary 81 chromophobe RCC. Comprehensive genomic phenotypic analysis of subtypes reveals distinctive features each subtype that provide foundation for development subtype-specific management strategies patients...
Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an integrative holistic manner. It also paves way toward development systematic approaches for effective therapeutic intervention disease. The central theme this paper is Boolean formalism as a building block complex, large-scale, dynamical interactions. We discuss goals well data requirements. justified from several points view. then introduce...
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique features, clinically significant subtypes, potential therapeutic targets. found 61 somatic copy-number alterations (SCNAs) 46 significantly mutated genes (SMGs). Eleven SCNAs 11 SMGs had not been identified in previous TCGA studies the individual tumor types. functionally estrogen receptor-regulated long non-coding RNAs (lncRNAs)...
<h3>Context</h3>Attempts to determine the clinical significance of BRCA1/2 mutations in ovarian cancer have produced conflicting results.<h3>Objective</h3>To relationships between deficiency (ie, mutation and promoter hypermethylation) overall survival (OS), progression-free (PFS), chemotherapy response, whole-exome rate cancer.<h3>Design, Setting, Patients</h3>Observational study multidimensional genomics data on 316 high-grade serous cases that were made public 2009 2010 via The Cancer...
Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated 9,624 tumors across 33 cancer types using multiple fusion calling tools. identified a total 25,664 fusions, with 63% validation rate. Integration gene expression, copy number, and annotation data revealed that involving oncogenes tend to exhibit increased whereas tumor suppressors have the opposite effect. For kinases, we found 1,275 intact kinase domain, proportion which varied...
We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared distinguishing molecular characteristics gastrointestinal tract (GIACs). Hypermutated tumors were distinct regardless cancer type comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing MLH1 in context CpG island methylator phenotype, plus elevated single-nucleotide variants associated mutations POLE. Tumors chromosomal diverse,...