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.

Early cytopenias and infections after standard of care idecabtagene vicleucel in relapsed or refractory multiple myeloma.

Idecabtagene vicleucel (ide-cel) was FDA-approved in March 2021 for the treatment of relapsed/refractory multiple myeloma after 4 lines of therapy. On the KarMMa trial, grade ≥ 3 cytopenias and infections were common. We sought to characterize cytopenias and infections within 100 days after ide-cel in the standard-of-care (SOC) setting. This multi-center retrospective study included 52 patients who received SOC ide-cel; 47 reached day-90 follow-up. Data were censored at day 100. Grade ≥ 3 cytopenia was present among 65% of patients at day 30 and 40% of patients at day 90. Granulocyte colony stimulating factor (G-CSF) was administered to 88%, packed red blood cell transfusions to 63%, platelet transfusions to 42%, thrombopoietin (TPO) agonists to 21%, intravenous immunoglobulin to 13%, and CD34+ stem cell boosts to 8%. At day 100, 19% and 13% of patients had ongoing use of TPO agonists and G-CSF, respectively. Infections occurred in 54% of patients and were grade ≥ 3 in 23%. Earlier infections in the first 30 days were typically bacterial (68%) and severe (50%). Later infections between days 31 and 100 were 50% bacterial and 42% viral; only 13% were grade ≥ 3. On univariate analysis, high pre-CAR-T marrow myeloma burden (≥ 50%), circulating plasma cells at pre-lymphodepletion (LD), and grade ≥ 3 anemia at pre-LD were associated with grade ≥ 3 cytopenia at both days 30 and 90. Longer time from last bridging treatment to LD was the only significant risk factor for infection.

Racial and ethnic differences in clonal hematopoiesis, tumor markers, and outcomes of patients with multiple myeloma.

Multiple myeloma (MM) incidence, mortality, and survival vary by race and ethnicity, but the causes of differences remain unclear. We investigated demographic, clinical, and molecular features of diverse MM patients to elucidate mechanisms driving clinical disparities. This study included 495 MM patients (self-reported Hispanic, n = 45; non-Hispanic Black, n = 52; non-Hispanic White, n = 398). Hispanic and non-Hispanic Black individuals had an earlier age of onset than non-Hispanic White individuals (53 and 57 vs 63 years, respectively, P < .001). There were no differences in treatment by race and ethnicity groups, but non-Hispanic Black patients had a longer time to hematopoietic cell transplant than non-Hispanic White patients (376 days vs 248 days; P = .01). Overall survival (OS) was improved for non-Hispanic Black compared with non-Hispanic White patients (HR, 0.50; 95% CI, 0.31-0.81; P = .005), although this association was attenuated after adjusting for clinical features (HR, 0.62; 95% CI, 0.37-1.03; P = .06). Tumor mutations in IRF4 were most common in Hispanic patients, and mutations in SP140, AUTS2, and SETD2 were most common in non-Hispanic Black patients. Differences in tumor expression of BCL7A, SPEF2, and ANKRD26 by race and ethnicity were observed. Clonal hematopoiesis was detected in 12% of patients and associated with inferior OS in non-Hispanic Black patients compared with patients without clonal hematopoiesis (HR, 4.36; 95% CI, 1.36-14.00). This study provides insight into differences in molecular features that may drive clinical disparities in MM patients receiving comparable treatment, with the novel inclusion of Hispanic individuals.

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.