Modulation of the sensitivity to ruxolitinib-mediated JAK2 inhibition by mutationally activated SHP2 exhibits cell context dependency in pre-clinical models of myeloproliferative neoplasms
Classic Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) are hematopoietic stem cell cancers that result in aberrant trilineage myeloid cell proliferation, bone marrow fibrosis, and increased risk of acute myeloid leukemia. MPNs are driven by deregulated activity of the JAK2 kinase, induced by mutations in the JAK2, CALR, and MPL genes, but approved JAK2 inhibitors primarily offer palliative effects, not remission. Cell models that demonstrate MPN oncogene driven JAK2 activity requisite for cell proliferation are important research tools for the development of anti-JAK2 and anti-JAK2 signaling therapeutics for MPN. SET2 and UKE1 cells are two such cell lines, as they express JAK2-V617F, one of the major driving mutations of MPN, and require signaling by JAK2 for their growth and viability. These cell lines are AML cell lines that were derived from patients with a previous diagnosis of MPN before they developed AML. Our previous studies demonstrated that the SHP2 phosphatase may be a therapeutic target for MPNs, and here we report our identification and characterization of an activating point mutation of SHP2 (encoded by the PTPN11 gene), SHP2-F71L, in UKE1 cells. Given SHP2 functions downstream of JAK2 and mediates JAK2 activation of RAS, we set out to determine the effect of mutational activation of SHP2 on the sensitivity of MPN model cells to JAK2 inhibition. We used CRISPR-Cas9 to edit this mutation in UKE1 cells back to wildtype such that these cells only express wildtype SHP2. These cells exhibited enhanced sensitivity to SHP2 inhibition and, notably, enhanced sensitivity to the JAK2 inhibitor ruxolitinib. This altered sensitivity was reverted by exogenous expression of SHP2-F71L but not SHP2-WT, indicating expression of an activated SHP2 may alter sensitivity to JAK2 inhibition in MPN model cells. We further explored this by genetically editing SET2 cells to express SHP2-F71L but observed no change in SHP2 inhibitor or JAK2 inhibitor sensitivity in cells with a SHP2-F71L encoding allele of PTPN11. Using the cytokine dependent BaF3 cell line where deregulation of JAK2 signaling by expression of JAK2-V617F induces cytokine independent transformation that remains dependent on this JAK2 signaling, we observed no effect of the expression of an activated SHP2 mutant on the sensitivity of the growth and viability of these cells to ruxolitinib. Recent studies have demonstrated activation of RAS signaling can antagonize JAK2 inhibition in pre-clinical MPN models, and the presence of RAS pathway mutations associates with patients whose disease advances on ruxolitinib therapy. Such mutations include activating mutations in PTPN11, as SHP2 is an upstream activator of RAS signaling. Our results suggest that activating PTPN11 mutations have the potential to desensitize the effects of JAK2 inhibition therapy in patients undergoing therapy and may be dependent on unknown cell and molecular profile contexts.
It is concluded that bridging the gap between foundational CRISPR research and its real-world applications is imperative and future efforts should focus on democratizing tools via open-source platforms, advancing delivery systems, and fostering sustainable innovation through synthetic biology integration to fully realize the transformative potential of genome editing in organisms beyond model organisms.
S. Sarsaiya, Archana Jain, Jishuang Chen et al.· Biotechnology Advances· 2 citations
It is argued that formation of a tumour-intrinsic niche is a prerequisite for BRAF-mutant CRC seeding to distant organs and that interference with niche formation may help avoid metastatic relapse.
J. Bugter, L. El Bouazzaoui, E. Küçükköse et al.· bioRxiv· 2 citations
This review summarizes emerging therapeutic strategies for EOC, their mechanisms of action, and their potential to overcome treatment resistance, and covers molecularly targeted therapies, immunotherapies, metabolic and epigenetic approaches, cellular and gene therapies, targeted drug-delivery systems, and locoregional and physical modalities.
Zofia Pietrasik, Mikołaj Kapała, Joanna Pietrasik et al.· Cancers· 0 citations
Genetic engineering (GE) and gene editing may endow traits to trees such as increased biomass and the production of novel biomaterials. Long-lived organisms such as trees might be subject to biotechnology-related risks that could be different than those of annual row crops. Those risks could be relevant to production in engineered plantations and beyond plantations to natural forests. Therefore, appropriate risk regulation is important to assure biosafety of commercialized engineered trees. In addition to gene flow via sexual reproduction, vegetative reproduction might play an additional role in environmental "exposure" risk relative to transgene dispersal in GE tree plantations. While vegetative reproduction is beneficial for preserving desired genetic traits during tree propagation, it may lead to proximal clonal spread in the field. Although the environmental risks associated with vegetative reproduction of GE trees are recognized in commercial forestry, there are few field-based environmental risk assessment (ERA) studies on dispersal risks of self-propagated GE trees. GE or gene editing of target genes involved in the vegetative propagation processes may be useful to mitigate environmental risks of clonal spread through vegetative reproduction. This review provides updates for recent field test results of GE and gene edited trees. Gene candidates related to vegetative reproduction including adventitious shooting (AS) and adventitious rooting (AR) are discussed herein as a means to mitigate unintended clonal spread from GE tree plantations.
Findings establish Cas7-11 as a precise and efficient RNA knockdown tool for functional studies in embryonic development and stem cell biology, providing a versatile alternative to DNA-based gene-editing approaches.
Huan Yan, Imtiaz Ul Hassan, Kai Yan et al.· Cell & Bioscience· 0 citations
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
MIT News · Artificial Intelligence· news.mit.eduAug 17, 2026