GTC presented abstracts at ASH 2022
GTC’s posters from 2022 Convention of American Society of Hematology are now available to be downloaded. Please reach out with any questions.
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Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation
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.
Combining cell-free RNA with cell-free DNA in liquid biopsy forhematologic and solid tumors
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
Genomics in the Diagnosis, Classification, and Management of Myeloid and Lymphoid Neoplasms
Washington, DCApril 26-27
San Antonio Breast Cancer Review 2023
John Theurer Cancer presents the 2023 San Antonio Breast Cancer Review: This program, based on data presented at the San Antonio Breast Cancer Symposium 2023, is designed to provide a review of state of the art information on experimental biology, etiology, prevention, diagnosis & therapy of breast cancer/premalignant breast disease to an audience of academic and private physicians and researchers involved in medical, surgical, GYN and radiation therapy, as well as other appropriate health care professionals
Predicting PD-L1 Status in Solid Tumors Using Transcriptomic Data and Artificial Intelligence Algorithms
This study delves into the potential of RNA profiling, specifically examining HER2, ESR1, and AR mRNA levels, providing nuanced insights for precise therapeutic interventions and outcome predictions in breast cancer.
The use of transcriptomic data in developing biomarkers in breast cancer
This study delves into the potential of RNA profiling, specifically examining HER2, ESR1, and AR mRNA levels, providing nuanced insights for precise therapeutic interventions and outcome predictions in breast cancer.