Proteomics and Cancer Cell Signaling
Dr. Ashok Kumar Jayavelu
Our research group focuses on the fundamental principles of tumor evolution and therapy adaptation governed by signaling-to-translation networks.
Our Research
Our mission is to decipher the mechanisms that drive tumor initiation, progression, and therapy-tolerant states with emphasis on drug resistance, drug persistence, and phenotypic plasticity. We translate these insights into proteomics-informed therapeutic strategies using advanced mass spectrometry technologies such as spatial and single-cell proteomics.
Dysregulated Splicing Signaling in Cancer
Prior to translation, the introns must be precisely and efficiently removed and the exons ligated together in a process called pre-mRNA splicing, orchestrated by mRNA splicing factors and binding proteins, which is a fundamental process that occurs in all eukaryotic cells. We discovered that mRNA splicing factors plays a key role in mediating drug response in cancer cells. We showed non-mutated-splicing factor regulation by phosphorylation could alter the response to targeted therapy in cancer. How splicing factors as a class are post-translationally regulated by signaling pathways remains unknown, and this understanding may reveal novel mechanisms and therapeutic opportunities. Thus, the mechanism of mRNA splicing factors regulation in the context of various cancer relevant mutations and in different cancer entities, in particular hematological malignancies is one of the major foci of our work. Therefore, we intend to systematically investigate the regulators and pathways that mediate post-translational modifications to control the function of splicing factors.
Proteome-Informed Therapeutic Strategies
Drug resistance in cancer continues to be one of the principles limiting factors in achieving cure, and a major impediment to patient survival. Its multifaceted nature driven by both intrinsic and extrinsic factors influences creates a diverse spectrum of therapy responses. Despite advances in genomics, it often remains unclear which mutations and signaling dependencies determine outcome, leaving clinicians without clear strategies to overcome resistance. We leverage cutting-edge mass spectrometry, including high-sensitivity, high-throughput, spatial, and single-cell proteomics, to systematically map tumor proteomes and uncover dynamic signaling networks that govern therapy response. Our recent identification of a novel proteomic subtype in acute myeloid leukemia with clinical relevance demonstrates the power of this approach. By applying these technologies to cancers such as leukemia and osteosarcoma, we aim to define the molecular dependencies that underlie drug resistance, persistence, and plasticity and translate these insights into strategies that restore therapeutic vulnerability.
The Architectural Blueprint of Cancer Signaling and Evolution
Cancer evolution is not only genetic but also profoundly phenotypic. While mapping mutations in tumor clones has illuminated the genetic trajectory from normal to malignant states, it fails to capture the signaling rewiring and non-genetic processes that accompany this transition. Identifying the very first cell that acquires a cancer driver mutation in humans is currently impossible, and even inducible mouse models fall short in resolving temporal signaling dynamics at single-cell resolution. We aim to define how a healthy cell, upon acquiring an oncogenic kinase mutation, reorganizes its signaling pathways to become malignant. By engineering innovative in vitro cell-line models, we create tractable systems to interrogate the temporal dynamics of tumor initiation, bridging a critical gap left by current genomic and in vivo approaches. This work will reveal how signaling landscapes are reshaped at the very onset of cancer.