A5024621602- Cancer Genomics and Diagnostics
- Pancreatic and Hepatic Oncology Research
- Genetic factors in colorectal cancer
- CAR-T cell therapy research
- Monoclonal and Polyclonal Antibodies Research
- Immunotherapy and Immune Responses
- Epigenetics and DNA Methylation
- Connexins and lens biology
- Glycosylation and Glycoproteins Research
- Lymphoma Diagnosis and Treatment
- Chronic Lymphocytic Leukemia Research
- Immune Cell Function and Interaction
- Single-cell and spatial transcriptomics
- Nanowire Synthesis and Applications
- Biosimilars and Bioanalytical Methods
- DNA Repair Mechanisms
- T-cell and B-cell Immunology
- Enzyme Structure and Function
- Heat shock proteins research
- Cutaneous lymphoproliferative disorders research
- Virus-based gene therapy research
- Cancer Research and Treatments
- Extracellular vesicles in disease
- Long-Term Effects of COVID-19
- Glioma Diagnosis and Treatment
Johns Hopkins University
2019-2024
Howard Hughes Medical Institute
2019-2024
Sidney Kimmel Comprehensive Cancer Center
2019-2024
University of Baltimore
2023
Johns Hopkins Medicine
2020-2023
Cancer Genetics (United States)
2023
Cancer Research Center
2023
National Institutes of Health
2015
National Institute of Diabetes and Digestive and Kidney Diseases
2015
Amherst College
2013
(tumor protein p53) is the most commonly mutated cancer driver gene, but drugs that target mutant tumor suppressor genes, such as
Bispecific T cell–engaging antibodies capable of specifically killing cancer cells expressing mutant RAS neoantigens were generated.
Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared those of healthy controls, but the sources this extra cfDNA have never been determined. To address issue, we assessed methylation patterns in 178 cancers colon, pancreas, lung, or ovary and 64 without cancer. Eighty-three these individuals had much greater than generally observed subjects. The major contributor all samples was leukocytes, accounting for ∼76% cfDNA, neutrophils predominating. This true...
Significance The lack of viable tumor-specific targets continues to thwart efforts implement selective anticancer drugs in the clinic. Clonal loss heterozygosity (LOH) occurs great majority human tumors and represents an irreversible genetic alteration present cancer cells that unequivocally distinguishes them from normal cells. Here, we report development NASCAR (Neoplasm-targeting Allele-Sensing CAR), a platform comprising pairwise chimeric receptors for detecting targeting LOH events...
Immunotherapies such as chimeric antigen receptor (CAR) T cells and bispecific antibodies redirect healthy to kill cancer expressing the target antigen. The pan-B cell antigen-targeting immunotherapies have been remarkably successful in treating B malignancies. Such therapies also result near-complete loss of cells, but this depletion is well tolerated by patients. Although analogous targeting pan-T markers could, theory, help control cancers, concomitant would severe unacceptable...
Abstract Chimeric antigen receptor (CAR) T cells have emerged as a promising class of therapeutic agents, generating remarkable responses in the clinic for subset human cancers. One major challenge precluding wider implementation CAR therapy is paucity tumor-specific antigens. Here, we describe development targeting isocitrate dehydrogenase 2 (IDH2) with R140Q mutation presented on cell surface complex common leukocyte allele, HLA-B*07:02. Engineering hinge domain CAR, well crystal...
Abstract Specificity remains a major challenge to current therapeutic strategies for cancer. Mutation associated neoantigens (MANAs) are products of genetic alterations, making them highly specific targets. MANAs HLA-presented (pHLA) peptides derived from intracellular mutant proteins that otherwise inaccessible antibody-based therapeutics. Here, we describe the cryo-EM structure an antibody-MANA pHLA complex. Specifically, determine TCR mimic (TCRm) antibody bound its MANA target, KRAS G12V...
Two types of engineered T cells have been successfully used to treat patients with cancer, one an antigen recognition domain derived from antibodies [chimeric receptors (CARs)] and the other cell (TCRs). CARs use high-affinity antigen-binding domains costimulatory induce activation but can only react against target relatively high amounts antigen. TCRs a much lower affinity for their antigens displaying few molecules. Here, we describe new type receptor, called Co-STAR (for synthetic TCR...
<p>Supplemental Figure 7. The amount of total cfDNA before and after surgery in patients with pancreatic cancer.</p>
<p>Supplemental Figure 1. Overview of the patient samples included in present study.</p>
<p>Supplemental Figure 7. The amount of total cfDNA before and after surgery in patients with pancreatic cancer.</p>
<p>Supplemental Figure 10. In silico mixing experiments (N = 10) of buffy coat bisulfite sequencing data with liver (A), lung (B), colon epithelial cell (C), and left atrium (D) deconvoluted using the Moss et al. (43) reference matrix quadratic programming shows excellent agreement between predicted actual fractional contribution.</p>
<p>Supplemental Figure 2. The concentration of plasma cfDNA in previous described patients with cancer according to stage. (A) all types (9). Stage III cancers was significantly higher than that I (p < 0.01). (B) individual types. classified AJCC 7th edition. breast 0.05). For both panels, data were derived from the previously published CancerSEEK study (9).</p>
<p>Supplemental Figure 9. Plasma AST and ALT levels before ~24 hours after surgery for pancreatic cancer. substantially increased in all five patients.</p>
<p>Supplemental Figure 2. The concentration of plasma cfDNA in previous described patients with cancer according to stage. (A) all types (9). Stage III cancers was significantly higher than that I (p < 0.01). (B) individual types. classified AJCC 7th edition. breast 0.05). For both panels, data were derived from the previously published CancerSEEK study (9).</p>
<p>Supplemental Figure 10. In silico mixing experiments (N = 10) of buffy coat bisulfite sequencing data with liver (A), lung (B), colon epithelial cell (C), and left atrium (D) deconvoluted using the Moss et al. (43) reference matrix quadratic programming shows excellent agreement between predicted actual fractional contribution.</p>
<p>Supplementary Notes 1-5. Supplementary Note 1: Origins of cell-free DNA. 2: Leukocyte Lysis. 3: Reference datasets and deconvolution algorithms used to interpret whole genome bisulfite sequencing data. 4: Turnover rates. 5: Relationships between ctDNA tissue specific cfDNA in cancer patients.</p>
<p>Supplemental Figure 3. Fraction of plasma cfDNA that could be attributed to high molecular weight genomic DNA in samples analyzed by RealSeqS.</p>
<p>Supplemental Figure 4. Methylation profiles using quadratic programming vs. non-negative least- squares regression the reference matrix described in Sun et al. (3). Pearson’s correlation coefficient and p values are presented at bottom of this figure, showing derived contributions from each 12 tissue types that could be assessed.</p>
<p>Supplemental Figure 3. Fraction of plasma cfDNA that could be attributed to high molecular weight genomic DNA in samples analyzed by RealSeqS.</p>