SHP2 inhibition displays efficacy as a monotherapy and in combination with JAK2 inhibition in preclinical models of myeloproliferative neoplasms

Myeloproliferative neoplasms (MPNs), including polycythemia vera, essential thrombocytosis, and primary myelofibrosis, are clonal hematopoietic neoplasms driven by mutationally activated signaling by the JAK2 tyrosine kinase. Although JAK2 inhibitors can improve MPN patients' quality of life, they do not induce complete remission as disease-driving cells persistently survive therapy. ERK activation has been highlighted as contributing to JAK2 inhibitor persistent cell survival. As ERK is a component of signaling by activated RAS proteins and by JAK2 activation, we sought to inhibit RAS activation to enhance responses to JAK2 inhibition in preclinical MPN models. We found the SHP2 inhibitor RMC-4550 significantly enhanced growth inhibition of MPN cell lines in combination with the JAK2 inhibitor ruxolitinib, effectively preventing ruxolitinib persistent growth, and the growth and viability of established ruxolitinib persistent cells remained sensitive to SHP2 inhibition. Both SHP2 and JAK2 inhibition diminished cellular RAS-GTP levels, and their concomitant inhibition enhanced ERK inactivation and increased apoptosis. Inhibition of SHP2 inhibited the neoplastic growth of MPN patient hematopoietic progenitor cells and exhibited synergy with ruxolitinib. RMC-4550 antagonized MPN phenotypes and increased survival of an MPN mouse model driven by MPL-W515L. The combination of RMC-4550 and ruxolitinib, which was safe and tolerated in healthy mice, further inhibited disease compared to ruxolitinib monotherapy, including extending survival. Given SHP2 inhibitors are undergoing clinical evaluation in patients with solid tumors, our preclinical findings suggest that SHP2 is a candidate therapeutic target with potential for rapid translation to clinical assessment to improve current targeted therapies for MPN patients.

Impact of obesity on chemotherapy dosing of carboplatin and survival of women with ovarian cancer

BACKGROUND

The study objective is to examine the impact of obesity on frontline carboplatin dosing in the neoadjuvant and adjuvant settings and to evaluate the association of dosing with survival among epithelial ovarian cancer (EOC) patients.

METHODS

We selected 1527 women diagnosed with EOC from January 1, 2011 to October 20, 2021 from a nationwide electronic health record-derived de-identified database. The dose reduction of frontline carboplatin was defined as a relative dose intensity (RDI) < 0.85. Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of RDI with survival overall and by histology.

RESULTS

Women with a BMI ≥ 30 kg/m2 versus <30 kg/m2 were more likely to be underdosed (RDI < 0.85) with frontline carboplatin. Underdosing of carboplatin in the neoadjuvant setting was associated with worse survival among women with serous tumours (HR = 1.98, 95% CI = 1.15, 3.42). Underdosing of carboplatin in the adjuvant setting was not associated with survival.

DISCUSSION

In the real-world setting, underdosing of carboplatin in the neoadjuvant setting was associated with inferior survival among women with serous tumours. With the increasing utilisation of neoadjuvant chemotherapy in EOC, actual weight-based dosing of carboplatin may be important to improve outcomes in this patient population.

spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data

Summary

Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley’s K, Besag’s L, Macron’s M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time.

Availability and implementation

spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME).

Supplementary information

Supplementary data are available at Bioinformatics online.