This session will provide an overview of the clinically significant molecular-genomic profiles in leukemias and discuss the incorporation of novel targeted therapies into current therapy regimens based on these profiles.     

Level of Instruction: Advanced

Learning Objectives:

• Outline important molecular-genomic profiles relevant to patient therapy in AML and other leukemias 
• Discuss incorporation of novel targeted therapies into current therapy regimens based on these molecular-genomic profiles 
• Present the MD Anderson Cancer Center pilot updates incorporating such research strategies 

This session will provide a comprehensive overview of telomere biology disorders, including their clinical presentation, diagnostic approaches, and clinical management.    

Level of Instruction: Advanced

Learning Objectives:

• Recognize the clinical manifestations of telomere biology disorders 
• Understand the role of genetics and telomere length in diagnosing telomere biology disorders 
• Identify clinical management options for patients with telomere biology disorders 

This session will explore how genomic testing impacts pediatric oncology care and clinical trials, and identify the molecular alterations and potential therapeutic strategies revealed by this testing of treatment-refractory pediatric cancers.   

Level of Instruction: Intermediate

Learning Objectives:

• Describe examples of the diverse ways in which molecular testing impacts pediatric oncology care and clinical trials 
• Understand the scientific rationale and considerations of trial design for Pediatric MATCH and other basket genomic medicine trials 
• Identify the molecular alterations and potential therapeutic strategies revealed by genomic testing of treatment-refractory pediatric cancers 

This session will comprehensively explore the latest advancements in structural variant (SV) analysis for clinical diagnostic workflow, specifically focusing on the emerging data pertaining to long-read sequencing. The speakers will review the currently available technologies for SV detection, highlighting the advantages and challenges, delve into the clinical applications of long-read sequencing and discuss bioinformatics infrastructure essential for supporting these workflows. Attendees will gain understanding of current and emerging approaches to SV analysis and prepare them to integrate these technologies effectively in clinical practice. 

Learning Objectives

1. Provide an overview of the currently available technologies for SV detection, and compare their clinical utility, advantages, and limitations to guide the laboratories in selecting the most suitable technology for implementation.  
2. Explore the utility of long-read sequencing technologies for clinical SV detection highlighting the advantages and challenges. 
3. Identify essential bioinformatics infrastructure and tools required for long-read sequencing implementation, computational workflow, and robust data integration. 

The rapid growth of genomic data has revolutionized cancer research and clinical diagnostics. Central to this progress is the role of variant interpretation databases, such as Clinical Interpretation of Variants in Cancer (CIViC), Variant Interpretation for Cancer Consortium (VICC), and ClinVar, in facilitating data sharing. This session will provide an overview of these databases, and highlight the work of VICC and their efforts to standardize the curation, representation, and interpretation of clinically relevant evidence associated with genomic variation in cancers.

Learning Objectives

1. Review the cancer variant interpretation databases
2. Demonstrate how to use the VICC Meta-Knowledgebase
3. Summarize the proceedings of the VICC/CGC/CIViC/ClinGen Cancer Variant Curation and Coding Unconference Agenda

This session will provide a comprehensive overview of bioinformatics workflows for processing, analyzing, and visualizing cancer genome data to support clinical decision-making. Attendees will gain insights into best practices for interpreting and classifying somatic and germline variants, with an emphasis on integrating data with established databases and clinical guidelines. The discussion will highlight how bioinformatics tools enable the identification of diagnostic, prognostic, and therapeutic biomarkers, empowering clinicians and researchers to drive precision oncology forward.

Learning Objectives

1. Learn about end-to-end workflows for processing, analyzing, and visualizing cancer genome data to support clinical decision-making.
2. Explore best practices for interpreting and classifying somatic and germline variants in cancer genomes, including integration with databases and guidelines.
3. Learn how bioinformatics facilitates the identification of diagnostic, prognostic, and therapeutic biomarkers in cancer.

This session will provide an overview of the federal regulations governing molecular diagnostic testing and the complex issue of gene patenting. Participants will learn about the regulatory landscape that ensures the safety, effectiveness, and ethical application of molecular diagnostic tests in clinical settings. The session will also delve into the legal complexities surrounding gene patenting, including how intellectual property laws affect the development and accessibility of genetic testing technologies. Key topics will include the federal regulation of molecular diagnostic testing and the implications of the U.S. Supreme Court’s decision in the "Association for Molecular Pathology v. Myriad Genetics" case on gene patenting.

Learning Objectives

1. Identify key federal requirements for the approval and regulation of molecular diagnostic tests.
2. Assess the balance between regulatory oversight and the promotion of innovation in the molecular diagnostics and biotechnology sectors, considering both safety and commercial interests.
3. Examine the history and current legal status of gene patenting in the U.S., including the impact of the Myriad Genetics decision and the role of patent laws in the development of genetic testing.
4. Explore the ethical issues surrounding gene patents, including concerns related to accessibility, innovation, and healthcare equity, and how federal regulations address these concerns.

Integrating molecular genetics and cytogenetics laboratories offers significant advantages, including a more comprehensive understanding of genetic abnormalities, improved accuracy in molecular diagnosis, and reduced redundant testing. This integration enables a cost-efficient diagnostic workflow while enhancing molecular classification, risk stratification, and treatment planning. However, challenges such as standardizing methodologies, cross-training personnel, and ensuring cost-effective consolidation, as well as the implementation or de-implementation of tests and testing platforms, must be addressed. Despite these concerns, the integration of cytogenetics and molecular genetics laboratories is pivotal for advancing precision medicine and improving patient care. In this session, experts will share their insights on integrating molecular genetics and cytogenetics laboratories, as well as their experiences and considerations when transitioning from traditionally separated molecular and cytogenetic laboratory efforts to the integrated molecular genetics and cytogenetics testing strategy. 

Learning Objectives

1. Understand the capabilities and limitations of cytogenetics and widely used molecular genetics testing approaches from a technical perspective, and their roles in diagnostic applications.
2. Explore the benefits of integrating these laboratories, including enhanced accuracy, efficiency, and improved patient outcomes.
3. Identify key challenges in the integration process, including technical, financial, and personnel training aspects.
4. Develop strategic approaches to harmonize workflows, ensure a seamless transition, and implement best practices for laboratory integration.

This session explores structural variations, chromothripsis, and copy number changes in solid tumors, highlighting their clinical and therapeutic significance. 

Level of Instruction: Advanced

Learning Objectives:

1. Recognize the role of rare oncogenic structural variations in FGFR genes in pediatric brain tumors and their potential as therapeutic targets.  
2. Understand the association between chromothripsis in meningiomas and more aggressive tumor behavior.  
3. Evaluate the clinicopathologic features and prognostic implications of KRAS codon 146 mutations in colorectal carcinomas. 
4. Appreciate the impact of complex copy number variations in atypical melanocytic neoplasms and early melanoma to refine diagnostic and therapeutic strategies. 

This session highlights expert-driven approaches to variant curation in cancer, from re-evaluating hereditary cancer genes to applying oncogenicity guidelines and defining diagnostic variants in pediatric and hematologic malignancies. 

Level of Instruction: Advanced

Learning Objectives:

• Systematically re-curate and refine gene-disease relationships in hereditary cancer syndromes.  
• Characterize the germline and somatic variant landscape in tumor suppressor genes across cancers.  
• Evaluate the application of expert-derived oncogenicity guidelines in hematologic malignancies.  
• Enhance pediatric oncology diagnostics through the expert curation of defining and supportive variants. 

This session explores cutting-edge applications of optical genome mapping (OGM) in B-ALL and pediatric leukemias alongside advanced T-cell receptor profiling and cell-free DNA technologies. Presentations will highlight implementation strategies, clinical utility, and quality considerations. 

Level of Instruction: Advanced

Learning Objectives:

• Evaluate the clinical utility of optical genome mapping for detecting structural variants in B-ALL.  
• Analyze outcomes of optical genome mapping in pediatric leukemia diagnostics within a hospital setting. 
• Assess how long-term plasma storage affects quality and reliability of cell-free DNA biomarker studies. 
• Apply validation frameworks for T-cell receptor profiling assays, emphasizing performance metrics and cross-platform comparisons. 

This session explores the use of multiple genetic and genomic technologies including FISH, RNA-Seq, optical genome mapping (OGM), and genomic proximity mapping (GPM) in clinical diagnostic and prognostic characterization of hematologic malignancies. 

Level of Instruction: Advanced

Learning Objectives:

• Appreciate the impact of FISH to characterize abnormalities that are diagnostic and prognostic in Ph-like B-ALL
• Understand the ability of RNA-Seq to determine CRLF2-rearrangement status in pediatric B-ALL
• Evaluate the robustness of genomic proximity mapping (GPM) to detect clinically significant abnormalities in AML
• Recognize the complementary abilities of RNA-Seq and optical genome mapping (OGM) to characterize gene rearrangements in hematologic malignancies

This session explores the use of Artificial Intelligence, Machine Learning, and bioinformatics tools to predict specific mutation and gene expression status. It will also focus on enhancing gene fusion detection from DNA sequences and improving copy number estimation from methylation array data. 

Level of Instruction: Advanced

Learning Objectives:

• Present examples of AI and Machine Learning models for predicting mutation and gene expression statuses in specific tumor types.
• Utilize bioinformatics tools to enhance fusion detection in the TruSight 500 panel, incorporating DNA sequence data to complement RNA sequencing fusion calls.
• Enhance CNV calling from methylation array data in central nervous system tumors.

This session examines advances in detecting low-level mosaicism, explores genomic disparities across populations, and addresses challenges in delivering molecular cancer testing in underserved settings. 

Level of Instruction: Advanced

Learning Objectives:

• Understand the clinical significance of low-level constitutional mosaic karyotypes and the utility of expanded cell analysis in their detection.
• Examine consensus recommendations and best practices for the testing and interpretation of low-level mosaic variants in somatic overgrowth and vascular anomalies.
• Explore how genetic variation influences inflammatory proteomes and contributes to genomic disparities between African and European populations.
• Evaluate barriers to implementing molecular cancer testing in resource-limited settings and identify strategies to promote equitable access to genomic diagnostics. 

This session highlights complex, novel, or educationally important diagnostic challenges in cancer genomics, and how evolving tools and collaboration are advancing genomic diagnostics in cancer. 

Level of Instruction: Intermediate

Learning Objectives:

• Recognize key features or situations that can contribute to diagnostically challenging clinical cases in cancer genomics, including but not limited to ambiguous variants, complex rearrangements, or atypical presentations of classical pathologies
• Describe how multidisciplinary and multimodal approaches can contribute to resolving complex genomic results in cancer diagnostics
• Apply strategies for interpreting and communicating uncertain or evolving genomic findings in clinical cancer genomics

This session features speed abstract talks on emerging biomarkers, AI-driven diagnostics, and liquid biopsy innovations, with a focus on translating genomic insights into clinical applications across cancer types. 

Level of Instruction: Advanced

Learning Objectives:

1. Evaluate emerging genomic biomarkers and their diagnostic, prognostic, and therapeutic relevance across diverse cancer types. 
2. Assess the integration and validation of artificial intelligence and computational tools in genomic and cytogenetic diagnostics. 
3. Explore the utility and expansion of high-throughput functional genomics data, such as MAVE maps, for clinical interpretation of variants. 
4. Investigate methodological advances in liquid biopsy and plasma-based detection strategies, including clonal hematopoiesis, for cancer monitoring. 

This session features speed abstract talks on advances in genomic data interpretation, including standards for gene fusions and somatic variants, transcriptome integration, and tools for variant curation—highlighting global applications and clinical impact. 

Level of Instruction: Advanced

Learning Objectives:

1. Develop and refine standards for assessing the oncogenic potential of gene fusions and somatic variants in cancer. 
2. Explore tools and frameworks that support the integration of transcriptomic data into precision oncology. 
3. Promote curation infrastructure and structured data models for improving the accuracy and efficiency of clinical variant interpretation. 
4. Evaluate the impact of accessible, in-house molecular testing in low-resource healthcare settings. 

This workshop will explore different perspectives on balancing professional and personal fulfillment in various career paths in clinical genomic diagnostics. The speakers will discuss negotiation of protected research time while in clinical service, staying connected while working remotely, etc. The attendees will learn about optional career paths in clinical diagnostics and about ways to enhance work-life balance and achieve enhanced satisfaction in their careers.

Learning Objectives:

1. Identify the key differences between academic and non-academic clinical pathways by understanding the unique roles, expectations, and career trajectories.
2. Identify strategies to stay motivated and focused on long-term career and personal happiness in your career path.
3. Gain insight into making smooth transitions between different stages of an academic or non-academic career.
4. Explore strategies for managing time and stress to maintain personal well-being while pursuing professional success in academic medicine.

This workshop will introduce key web tools and databases for identifying recurrent biomarkers in cancer genomes. The maintainers of these resources will demonstrate essential features and discuss their applications in research and clinical settings. Attendees will gain hands-on experience exploring these tools and engaging directly with the experts who build and maintain them.

Learning Objectives:

1. Discover resources for retrieving recurrent cancer genetic/genomic biomarker data.
2. Explore interfaces to publicly available cancer genetic/genomic biomarker databases with the resource creators.
3. Understand strengths and limitations of recurrent cancer genetic/genomic biomarker datasets.
4. Consider strategies for applying recurrent cancer genetic/genomic biomarkers in variant interpretation.