This is an extraordinary time in cell biology with evolving data pushing a reconsideration of the stability of cell systems and the regulatory mechanisms underlying cell phenotypes, especially the functional cell phenotypes. In this chapter, we will explore new insights into stem cell and extracellular vesicle biology with a focus on the role of extracellular vesicles in normal stem cell physiology as well as in various disease states. Extracellular vesicles (EVs) are being recognized as influential mediators of cellular function and potential experimental therapeutic strategies for a number of disorders outlined in this review. An evolving paradigm indicates a dynamic flux of EV populations within these disease states. We conclude our discussion of EV by extending our knowledge of robust EV biology toward disease detection and prognostication. Characterizing the biophysical and functional changes of vesicles amid disease progression or regression enables investigators to merge this information flux with existing deep learning computational and statistical techniques-allowing knowledge to be abstracted from large data sets profiling the biology of EVs within various disease states. Understanding how EV population shifts represent disease regression or progression creates paramount potential for EVs as salient and clinically relevant diagnostic and prognosticating tools.

2504 Background: TIM-3 expressed on tumor-infiltrating T cells is associated with T-cell suppression. AMBER (NCT02817633) is evaluating cobolimab (TSR-022/GSK4069889) monotherapy and with PD-1 inhibitors in advanced solid tumors. Methods: Multi-center, open-label study conducted with the following escalation arm (Parts 1A–C primary analysis reported here): (1A) cobolimab (IV Q2W) monotherapy at 7 doses (6 weight-based [0.03–10 mg/kg] and 1 flat [1200 mg] dose); (1B) cobolimab (1 mg/kg) + nivolumab (3 mg/kg IV Q2W); and (1C) cobolimab (100, 300, or 900 mg) + dostarlimab (500 mg IV Q3W). Primary endpoints were safety, tolerability, and recommended phase 2 dose (RP2D, monotherapy and combination). Results: 104 patients (pts) were included: 1A (n=46), 1B (n=7), or 1C (n=55); 4 pts from 1A crossed over to 1C (included in 1A and 1C safety and efficacy analyses). Most common cancers were non-small cell lung cancer (NSCLC) and melanoma (1A), NSCLC (1B), and NSCLC, skin, and peritoneal mesothelioma (1C). In 1A, 30.4% had ≥5 lines (L) of prior therapy; 42.9% had 3L in 1B; 33.3% had 2L in 1C. Treatment-related treatment-emergent adverse events (TR-TEAE) occurred in 67.4% (1A), 85.7% (1B), and 67.3% (1C); most commonly in 1A (n≥4) fatigue (13.0%) and nausea (8.7%); 1B (n≥3) diarrhea (57.1%) and nausea and vomiting (42.9% each); and 1C (n≥8) fatigue (20.0%) and rash (14.5%). Grade (Gr)≥3 TR-TEAEs occurred in 4.3% (1A), 28.6% (1B), and 14.5% (1C). There were no Gr5 TR-TEAEs or TR-TEAEs leading to dose delay. Serious TR-TEAEs occurred in 2.2% (1A), 0% (1B), and 12.7% (1C). TR-TEAEs led to discontinuation in 2.2% (1A), 28.6% (1B), and 9.0% (1C). Dose limiting toxicities (DLTs) occurred in 3.0% (1/33) in 1A (Gr3 lipase increased [10 mg/kg]); 40.0% (2/5) in 1B (Gr3 diarrhea and ALT and AST elevation); and 0% in 1C. Cobolimab serum exposure increased in a dose proportional manner at the therapeutic dose range. Preliminary mean terminal phase t1/2 ranged from 2.5–5.8 days for 0.03–0.3 mg/kg and 6.9–10.2 days for 1–10 mg/kg doses (1A), 6.9 days for 1B, and 9.5–12.3 days for 1C. Conclusions: Cobolimab + dostarlimab was well tolerated and showed preliminary anti-tumor activity, warranting further investigation of the RP2D + docetaxel in a randomized, phase 2 study. Funding: GSK (213348). Clinical trial information: NCT02817633. [Table: see text]

9513 Background: TIM-3 and PD-1 are markers of T-cell suppression that are upregulated in melanoma. AMBER (NCT02817633) is evaluating cobolimab (TSR-022/GSK4069889), an anti-TIM-3 therapy, monotherapy or with PD-1 inhibitors, including dostarlimab, in pts with solid tumors. Methods: This multicenter, open-label study was conducted in 2 parts: dose escalation (Parts 1 A–D and F–H) and cohort expansion (Parts 2 A–D). Part 1C and exploratory cohort 1E (reported here) included pts with advanced/metastatic melanoma; prior therapies, except for immunotherapies, were permitted. Pts received cobolimab (100 [1C only], 300, or 900 mg IV) with dostarlimab (500 mg IV) Q3W. Part 1C primary endpoints were safety, tolerability, and recommended Phase 2 dose. Objective response rate (ORR; complete [CR] or partial [PR] response per RECIST v1.1) was a secondary endpoint in 1C and the primary endpoint in 1E (ad hoc efficacy analysis reported). An integrated safety analysis for all pts (Parts 1 and 2) receiving cobolimab with dostarlimab, regardless of tumor type or cobolimab dose, is reported here. Results: 28 pts were enrolled in 1C (n=10) and 1E (n=18). Most pts (n=23; 82.1%) had cutaneous disease of the skin. One pt had anorectal mucosal disease and 3 pts in the 900-mg cohort had uveal melanoma. Most pts (67.9%) had an ECOG PS=0. At data cut-off (May 19, 2021), treatment was ongoing in 5 pts. In the integrated safety analysis of pts who received cobolimab 100 mg (n=41), 300 mg (n=167), or 900 mg (n=69) with dostarlimab, treatment-related treatment-emergent AEs (TR-TEAEs) occurred in 53.7%, 57.5%, and 59.4%, respectively. The most common TR-TEAEs (any grade, ≥10% in 100 mg, 300 mg, or 900 mg groups, respectively) were fatigue (22.0%, 13.2%, 24.6%), rash (9.8%, 5.4%, 11.6%), diarrhea (4.9%, 6.0%, 10.1%), and dyspnea (2.4%, 0%, 10.1%). Grade ≥3 TR-TEAEs occurred in 12.2% (100 mg), 10.8% (300 mg), and 20.3% (900 mg); serious TR-TEAEs occurred in 7.3%, 7.8%, and 11.6%, respectively. No pts died due to TR-TEAEs; 2.4% (100 mg), 4.2% (300 mg), and 7.2% (900 mg) discontinued due to TR-TEAEs. ORR and disease control rate (DCR: stable disease [SD] ≥16 weeks, PR, or CR) are shown in the Table. Twelve pts achieved a PR and an immune-related (ir)PR (1 in 100 mg; 8 in 300 mg; 3 in 900 mg groups). Three pts achieved SD (2 in 300 mg; 1 in 900 mg groups); 8 pts had irSD (1 in 100 mg; 4 in 300 mg; 3 in 900 mg groups). Conclusions: Cobolimab with dostarlimab showed preliminary clinical responses in pts with advanced/metastatic melanoma and an acceptable safety profile across advanced cancers. Funding: GSK (213348). Clinical trial information: NCT02817633. [Table: see text]

Background Extracellular Vesicles (EVs) compose a naturally occurring, heterogeneous group of membrane-bound, nano-sized particles shed by all cells. Depending on cellular type, physiological state, and mode of secretion some harbor potent regenerative properties while others have the propensity to induce disease. Human bone marrow mesenchymal stem cell (MSC)-derived EVs harbor regenerative potential. Our own studies have shown MSC-EVs are able to mitigate radiation damage to bone marrow, and to reverse the malignant phenotype in prostate and colorectal cancer. On the contrary, EVs isolated from neoplastic cells induce a neoplastic phenotype in non-cancerous cells. Leukemic EVs also potentiate the phenotypic change of healthy MSCs into cancer associated fibroblasts. The role of EVs within the leukemic microenvironment may provide insight for therapeutic advances. We hypothesize that EVs derived from normal MSCs inhibit the growth of nascent acute myelogenous leukemia (AML), and that the predominant EV population changes during leukemia progression. Neural network machine learning will allow us to capture these changes in order to build predictive models. Methods Kasumi AML cells lines were seeded with various concentrations of MSC-derived EVs. Vesicles were isolated using an established differential centrifugation technique, and co-cultured with Kasumi. To study cellular proliferation we employed a fluorescence-based method for quantifying viable cells (CyQuant). We also investigated the modes of death (apoptosis vs necrosis) EVs may induce on AML via a three die fluorescent system. Fluorescence intensities were normalized to control wells containing non-EV treated cells alone. Our neural network achieved 90.16% classification accuracy with cell culture data, and was tasked to classify the similarity of patient samples to the AML-derived EVs. Results Proliferation of AML cells after one day of co-culture with 2.6E8 &1.3E10 MSC-EVs respectively was inhibited in a dose dependent manner: with 2.6E8 EVs leading to ~ 15% reduction in growth, and 1.3E10 EVs leading to ~60% reduction when normalized to non-EV treated controls. 3 days of co-culture with similar doses resulted in ~40% and ~80% reduction in proliferation when normalized to control. At day 6 of co-culture growth was inhibited by ~80% at both EV concentrations. At multiple time points hMSC-EV treated AML cells showed a significantly higher proportion of apoptosis. Cellular necrosis was negligible. There was no statistically significant change in proliferation of MSC exposed to MSC-derived EVs when compared to non-EV treated controls. There was also no statistically significant change in proliferation of AML cells exposed to AML-derived EVs. Samples of AML, Chronic Myelomonocytic Leukemia, and Multiple Myeloma entered into our machine alogrithm were calculated to be 100%, 100%, and 66%, respectively, similar to the AML-derived EVs. Summary/Conclusion MSC-derived EVs inhibits the proliferation of the AML cell line in vitro via an apoptotic mechanism. This effect is seen as early as one day of co-culture and persists out to three, and six days, implicating an miRNA-mediated mechanism that has been discussed in previous works. We have also shown that when cells are exposed to their own EV there is no change or (in the case of leukemia) a statistically insignificant increase in proliferation. We feel this is perhaps a model of how a normal marrow works to suppress early cancer. As leukemia develops the cross-talk between AML and its microenvironment, via direct EV mediated effects, alters the MSCs to promote a survival signal favoring AML growth. This restructuring is EV mediated. Future work involves the capacity of AML-derived EVs to alter the phenotype of normal marrow towards a pro-leuekmic phenotype. This also includes the use of AML mouse models to further investigate the therapeutic potential MSC-derived EVs may have as single or adjunct therapy; as well as to study potential cellular mediators that may be involved in EV-direceted AML progression. Lastly we endeavor to employ machine learning networks to characterize and predict the dynamic restructuring the EV milieu undergoes as leukemia progresses. Capturing these alteration will allow the creation of reliable predictive models that will have direct inferences on clinical diagnosis and prognosis. Disclosures No relevant conflicts of interest to declare.