Huang Lab

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Mechanisms of Response and Resistance in Acute Myeloid Leukemias Characterized by Hyperactive Ras Signaling

Somatic NRAS and KRAS mutations or NF1 inactivation occur in 20-25% of acute myeloid leukemias (AMLs) and are particularly common in children, adolescents, and young adults. In addition, RAS mutations are frequently present at relapse after responses to IDH1/2 inhibitors and venetoclax. We harness accurate primary mouse models of AMLs characterized by hyperactive Ras signaling. We treat cohorts of recipient mice transplanted with AMLs in vivo with kinase inhibitors targeting downstream Ras effector pathways alone and in combination with chemotherapy or other targeted therapies. A subset of these AMLs responded dramatically to different treatments in vivo, but ultimately acquired drug resistance and relapsed. We are characterizing mechanisms of drug resistance, identifying pathways that modulate sensitivity to individual agents and drug combinations, and extending this work to human patient derived xenograft (PDX) models of AML.

Novel Germline and Somatic RAS Mutations in Developmental Disorders and Cancer

Codons 12, 13, and 61 of RAS are the most common targets of oncogenic mutations in cancer. Germline RAS mutations also occur in children with Noonan syndrome and other Rasopathy disorders and these alleles encode gain-of-function proteins that are less activated than oncogenic Ras. We have helped characterize developmental germline and unusual somatic RAS mutations identified in patients with hematologic diseases and generated mutant oncoproteins with second site amino acid substitutions to investigate the role of individual Ras effector pathways in development and tumorigenesis. For example, studies in isogenic model systems support a model whereby lateral, asymmetric assembly of Ras oligomers and interactions between K-Ras and the cystine-rich domain of Raf regulate signal output at the plasma membrane. We have also contributed to studies that support targeting the palmitoylation-depalmitoylation cycle in NRAS mutant cancers, a process that is required for transformation by oncogenic N-Ras. Because the normal K-RAS4b isoform does not require palmitate turnover, this approach has the potential to be selective for cancer cells that are dependent on oncogenic NRAS.

Next Generation Platforms for Detecting Residual Disease in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic cancer associated with poor outcomes and current therapies are toxic. Therefore, distinguishing who will be cured with chemotherapy alone from those who require more intensive therapies is critical to improving cure rates in AML. The presence of small numbers of persisting leukemia cells after chemotherapy has become an important predictor of leukemia relapse. However, current assays used to detect residual leukemia have limited sensitivity and many patients with no detectable leukemia still go on to relapse. This underscores the need to identify and develop more accurate and sensitive leukemia detection assays for AML. We are developing novel platforms that harnesses best in class technologies to enable ultrasensitive detection of leukemia cells. We are validating these assays in collaboration with the Children's Oncology Group (COG), which will then fill a critical unmet need in the field of AML.

Integrated Transcriptomics and Proteomics to Identify Targets in AML

Acute myeloid leukemia (AML) remains a therapeutic challenge with high mortality rates despite intensive and myeloablative therapies. Furthermore, relapse and survival outcomes for AML have not significantly improved for nearly 30 years due to a paucity of effective biologically based therapies. While immunotherapies targeting CD19 have yielded remarkable outcomes in B-cell acute lymphoblastic leukemia, identifying similar targets in AML remains a challenge due to overlapping immunophenotypes between leukemia cells and normal hematopoietic stem and progenitor cells (HSPCs) and transcriptional heterogeneity across AML subtypes. Therefore, in collaboration with Dr. Soheil Meshinchi (Fred Hutch), we integrated large transcriptome and proteome datasets from AML and normal tissues to identify potential targets expressed in leukemias, but not in normal bone marrow and other tissue types. Using this integrated approach, we identified several novel candidate immunotherapy targets. Importantly, a subset of these targets have clinically available antibody drug conjugates that are either FDA approved and/or undergoing early clinical development for other tumor types, serving as early candidates that we are currently pursuing with preclinical validation studies.