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Innovation Spotlight Information Stage Number: Innovation Spotlight Stage #1 Innovation Spotlight Date: Thursday, November 21, 2024 Innovation Spotlight Time: 4:25 PM – 4:55 PMInnovation Spotlight Title: The Role of

Innovation Spotlight Information Stage Number: Innovation Spotlight Stage #1 Innovation Spotlight Date: Thursday, November 21, 2024 Innovation Spotlight Time: 4:25 PM – 4:55 PMInnovation Spotlight Title: The Role of

Join Genomic Testing Cooperative at the Advancing Precision Medicine Annual Conference and Expo 2024 in Philadelphia, PA on November 1-2. As pioneers in genomics, we’re

New publication in New England Journal of Medicine for Genomic Testing Cooperative (GTC). GTC work was in collaboration with Dana-Faber cancer Institute/Harvard Medical School, Georgetown

New Paper in Journal of Clinical Pathways GTC has participated in a new paper titled: Bringing Value to Health Care. Read the paper as it

GTC presented abstracts at ASCO 2024 GTC’s posters from 2024 Convention of American Society of Clinical Oncology are now available to be downloaded. Please reach

CorePath Laboratories is partnering with Genomic Testing Cooperative (GTC) to enhance its next-generation sequencing (NGS) capabilities for cancer diagnostics. This collaboration combines targeted DNA and RNA profiling with other pathology testing methods, providing comprehensive evaluations of patient samples. Additionally, liquid biopsy capabilities offer a non-invasive way to monitor therapy and detect relapse.

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT), occurring to some degree in over 50% of patients and being a direct cause of death in about 20% of patients. This complication occurs even despite a better understanding of donor selection and GvHD prophylaxis regimens. aGvHD is a complex event in which multiple contributing factors are involved. We performed RNA transcriptome analysis of 1408 genes in bone marrow samples obtained before and after transplantation using machine learning to predict the risk of aGvHD and post-transplant survival for a cohort of patients undergoing HSCT. Differential gene expression identified several signaling pathways in the bone marrow microenvironment that may be major regulators of the complex biology of GvHD, and identified targets of intervention to ameliorate the risk of aGvHD and improve patient survival.

Introducing a novel liquid biopsy approach combining cfRNA and cfDNA sequencing. Our findings demonstrate superior mutation detection with cfRNA, while cfDNA excels in identifying chromosomal aberrations. Elevated cfRNA biomarkers correlate with tumor types, aiding diagnosis. Machine learning predicts cancer types accurately. Host immune response analysis through cfRNA ratios reveals distinct patterns in cancer patients. This integrated approach holds promise for predicting genomic abnormalities and cancer diagnosis

Washington, DCApril 26-27