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Biology subjects

Michalowski, A. M.

Publications and source records attributed to Michalowski, A. M..

3 recordsLinked to original sources

Stability of c-Myc protein differentiates Ras oncogene addiction and MAPK pathway dependency in Ras-mutant multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy that frequently harbors activating mutations in NRAS and KRAS oncogenes. Previous clinical trials targeting the Ras/MAPK oncogenic pathway with MEK inhibitors (MEKi) were met with limited efficacy, and newer generation of Ras inhibitors (RASi) have not been specifically evaluated in MM patients. To investigate the vulnerabilities of Ras-mutant MM to targeted therapies, we examined the sensitivity of a panel of human MM cell lines to the RASi RMC-6236 (daraxonrasib) and the MEKi trametinib. Although Ras-mutant MM cells are responsive to oncogenic Ras signaling and are sensitive to RAS inhibition, their sensitivity to MEK inhibition is heterogeneous. Mechanistic studies revealed that c-Myc protein is destabilized by MEK inhibition only in MEKi-sensitive MM cells but not in MEKi-resistant cells, and pharmacological and genetic stabilization of c-Myc is sufficient to confer MEKi resistance. In contrast, Ras inhibition reduced c-Myc protein across all MM cell lines tested, regardless of their dependency on the MAPK pathway, and c-Myc expression was insufficient to promote RASi resistance. Together, these findings demonstrate that c-Myc protein stability differentiates the response of Ras-mutant MM cells to Ras and MEK inhibition, and suggest that direct targeting of the Ras oncoprotein, rather than its downstream MAPK pathway, may present a more effective strategy.

cancer biology↗

Melanoblast transcriptome analysis reveals novel pathways promoting melanoma metastasis

Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posited that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover novel metastatic melanoma biology. We used a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, identified melanoblast-specific genes whose expression contributed to metastatic competence, and derived a 43-gene signature that predicted patient survival. We identified a melanoblast gene, KDELR3, whose loss impaired experimental metastasis. In contrast, KDELR1 deficiency enhanced metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover novel targetable pathways for melanoma therapy.

cancer biology↗

Multi-model preclinical platform predicts clinical response of melanoma to immunotherapy

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrates durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models representing the main molecular and phenotypic subtypes of human melanomas and exhibiting their range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify new mechanisms and treatment strategies to improve patient care.

cancer biology↗