A Phase I/II Trial of Carfilzomib, Pegylated Liposomal Doxorubicin, and Dexamethasone for the Treatment of Relapsed/Refractory Multiple Myeloma

Exploring the anti-myeloma potential of composite nanoparticles As4S4/Fe3O4: Insights from in vitro, ex vivo and in vivo studies

Given the profound multiple myeloma (MM) heterogeneity in clonal proliferation of malignant plasma cells (PCs) and anti-MM therapeutic potential of nanotherapies, it is inevitable to develop treatment plan for patients with MM. Two composite nanoparticles (NPs), As4S4/Fe3O4 (4:1) and As4S4/Fe3O4 (1:1) demonstrated effective anti-MM activity in in vitro, ex vivo, and in vivo in xenograft mouse model. Composite NPs triggered activation of p-ERK1/2/p-JNK, and downregulation of c-Myc, p-PI3K, p-4E-BP1; G2/M cell cycle arrest with increase in cyclin B1, histones H2AX/H3, activation of p-ATR, p-Chk1/p-Chk2, p-H2AX/p-H3; and caspase- and mitochondria-dependent apoptosis induction. NPs attenuated the stem cell-like side population in MM cells, both alone and in the presence of stroma. For a higher clinical response rate, As4S4/Fe3O4 (4:1) observed synergism with dexamethasone and melphalan, while As4S4/Fe3O4 (1:1) showed synergistic effects in combination with bortezomib, lenalidomide and pomalidomide anti-MM agents, providing the framework for further clinical evaluation of composite NPs in MM.

Therapeutic potential of anti-PIK3CG treatment for multiple myeloma via inhibiting c-Myc pathway

Multiple myeloma (MM) is a malignant plasma cell disease. The activity of PIK3CG (PI3K catalytic subunit γ) is regulated directly by G-protein-coupled receptor and has been confirmed to be highly expressed in MM cells. This study aimed to determine the effect of pharmacological inhibition of PIK3CG on MM. We found that different concentrations of the PIK3CG inhibitor AS-605240 could suppress the growth of MM cell lines and the expression of c-Myc. The combination of PIK3CG inhibitor and the chemotherapy Melphalan could effectively inhibit the proliferation and migration of MM cells, promote the cell apoptosis, and decrease the ratio of Bcl-2/Bax and the expression of vimentin. The expression of proto-oncogene c-Myc was decreased and the sensitivity of cells to chemotherapeutic drugs was enhanced. Collectively, PIK3CG regulates growth of MM via c-Myc pathway, thus emerging as a promising molecular targeted therapy.

Patient-Derived Organoids as a Promising Tool for Multimodal Management of Sarcomas

The management of sarcomas, a diverse group of cancers arising from connective tissues, presents significant challenges due to their heterogeneity and limited treatment options. Patient-derived sarcoma organoids (PDSOs) have emerged as a promising tool in the multimodal management of sarcomas, offering unprecedented opportunities for personalized medicine and improved treatment strategies. This review aims to explore the potential of PDSOs as a promising tool for multimodal management of sarcomas. We discuss the establishment and characterization of PDSOs, which realistically recapitulate the complexity and heterogeneity of the original tumor, providing a platform for genetic and molecular fidelity, histological resemblance, and functional characterization. Additionally, we discuss the applications of PDSOs in pathological and genetic evaluation, treatment screening and development, and personalized multimodal management. One significant advancement of PDSOs lies in their ability to guide personalized treatment decisions, enabling clinicians to assess the response and efficacy of different therapies in a patient-specific manner. Through continued research and development, PDSOs hold the potential to revolutionize sarcoma management and drive advancements in personalized medicine, biomarker discovery, preclinical modeling, and therapy optimization. The integration of PDSOs into clinical practice can ultimately improve patient outcomes and significantly impact the field of sarcoma treatment.

Modified isotonic regression based phase I/II clinical trial design identifying optimal biological dose

Conventional phase I/II clinical trial designs often use complicated parametric models to characterize the dose-response relationships and conduct the trials. However, the parametric models are hard to justify in practice, and the misspecification of parametric models can lead to substantially undesirable performances in phase I/II trials. Moreover, it is difficult for the physicians conducting phase I/II trials to clinically interpret the parameters of these complicated models, and such significant learning costs impede the translation of novel statistical designs into practical trial implementation. To solve these issues, we propose a transparent and efficient phase I/II clinical trial design, referred to as the modified isotonic regression-based design (mISO), to identify the optimal biological doses for molecularly targeted agents and immunotherapy. The mISO design makes no parametric model assumptions on the dose-response relationship and yields desirable performances under any clinically meaningful dose-response curves. The concise, clinically interpretable dose-response models and dose-finding algorithm make the proposed designs highly translational from the statistical community to the clinical community. We further extend the mISO design and develop the mISO-B design to handle the delayed outcomes. Our comprehensive simulation studies show that the mISO and mISO-B designs are highly efficient in optimal biological dose selection and patients allocation and outperform many existing phase I/II clinical trial designs. We also provide a trial example to illustrate the practical implementation of the proposed designs. The software for simulation and trial implementation are available for free download.

Repositioning linifanib as a potent anti-necroptosis agent for sepsis

Sepsis is a systemic inflammatory syndrome (SIRS) caused by acute microbial infection, and it has an extremely high mortality rate. Tumor necrosis factor-α (TNF-α)-induced necroptosis contributes to the pathophysiology of sepsis, so inhibiting necroptosis might be expected to improve clinical outcomes in septic patients. Here we predicted candidate drugs for treating sepsis in silico by combining genes differentially expressed in septic patients and controls combined with interrogation of the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 perturbation database. Sixteen candidate drugs were screened out through bioinformatics analysis, and the top candidate linifanib was validated in cellular and mouse models of TNF-α-induced necroptosis. Cell viability was measured using a luminescent ATP assay, while the effects of linifanib on necroptosis were investigated by western blotting, immunoprecipitation, and RIPK1 kinase assays. Linifanib effectively protected cells from necroptosis and rescued SIRS mice from TNF-α-induced shock and death. In vitro, linifanib directly suppressed RIPK1 kinase activity. In vivo, linifanib effectively reduced overexpressed IL-6, a marker of sepsis severity, in the lungs of SIRS mice. Our preclinical evidence using an integrated in silico and experimental drug repositioning approach supports the potential clinical utility of linifanib in septic patients. Further clinical validation is now warranted.

Addressing Modern Diagnostic Pathology for Patient-Derived Soft Tissue Sarcosphere Models in the Era of Functional Precision Oncology

Responses to therapy often cannot be exclusively predicted by molecular markers, thus evidencing a critical need to develop tools for better patient selection based on relations between tumor phenotype and genotype. Patient-derived cell models could help to better refine patient stratification procedures and lead to improved clinical management. So far, such ex vivo cell models have been used for addressing basic research questions and in preclinical studies. As they now enter the era of functional precision oncology, it is of utmost importance that they meet quality standards to fully represent the molecular and phenotypical architecture of patients' tumors. Well-characterized ex vivo models are imperative for rare cancer types with high patient heterogeneity and unknown driver mutations. Soft tissue sarcomas account for a very rare, heterogeneous group of malignancies that are challenging from a diagnostic standpoint and difficult to treat in a metastatic setting because of chemotherapy resistance and a lack of targeted treatment options. Functional drug screening in patient-derived cancer cell models is a more recent approach for discovering novel therapeutic candidate drugs. However, because of the rarity and heterogeneity of soft tissue sarcomas, the number of well-established and characterized sarcoma cell models is extremely limited. Within our hospital-based platform we establish high-fidelity patient-derived ex vivo cancer models from solid tumors for enabling functional precision oncology and addressing research questions to overcome this problem. We here present 5 novel, well-characterized, complex-karyotype ex vivo soft tissue sarcosphere models, which are effective tools to study molecular pathogenesis and identify the novel drug sensitivities of these genetically complex diseases. We addressed the quality standards that should be generally considered for the characterization of such ex vivo models. More broadly, we suggest a scalable platform to provide high-fidelity ex vivo models to the scientific community and enable functional precision oncology.

Establishment, characterization and functional testing of two novel ex vivo extraskeletal myxoid chondrosarcoma (EMC) cell models

Extraskeletal myxoid chondrosarcoma (EMC) is a malignant mesenchymal neoplasm of uncertain differentiation as classified by the WHO Classification of Tumours 2020. Although often associated with pronlonged survival, EMC has high rates of distant recurrences and disease-associated death. EMCs are translocation sarcomas and harbor in > 90% of the cases an NR4A3 rearrangement. The molecular consequences of the NR4A3 gene fusions are not yet fully elucidated as well-characterized ex vivo cell models for EMC are lacking. Patient-derived ex vivo models are important and essential tools for investigating disease mechanisms associated with diseases that are rare, that exhibit poor prognosis and for the identification of potential novel treatment options. We established two novel EMC ex vivo models (USZ20-EMC1 and USZ22-EMC2) for functional testing and research purposes. USZ20-EMC1 and USZ22-EMC2 were established and maintained as sarco-sphere cell models for several months in culture. The cells were molecularly characterized using DNA sequencing and methylation profiling. Both cell models represent their native tumor tissue as confirmed by histomorphology and their molecular profiles, suggesting that native tumor cell function can be recapitulated in the ex vivo models. Using a functional screening approach, novel anti-cancer drug sensitivities including potential synergistic combinations were identified. In conclusion, two novel EMC ex vivo cell models (USZ20-EMC1 and USZ22-EMC2) were successfully established and characterized from native tumor tissues. Both cell models will be useful tools for further investigating disease mechanisms and for answering basic and translational research questions.

Evaluation of Cardiac Function before and after PAD Regimen in Patients with Multiple Myeloma by Three-Dimensional Speckle Tracking Imaging

In this manuscript, we have evaluated numerous changes of cardiac function in patients with multiple myeloma before and after PAD chemotherapy with 3D speck tracking imaging (3D-STI). For this purpose, 39 patients with multiple myeloma, from July 2019 to December 2020, who received the PAD regimen (bortezomib + doxorubicin liposome + dexamethasone, a course of 12 days) were selected as subjects. A comparison of two-dimensional conventional echocardiographic parameters before and after chemotherapy and 3D-STI related parameters was carried out. After 6 cycles of chemotherapy, the levels of TAPSE, RVFAC, and LVEF were significantly lower than those before chemotherapy (P < 0.05). There was no significant difference in the results of left and right ventricle two-dimensional conventional echocardiography before chemotherapy and 2 or 4 cycles after chemotherapy (P > 0.05). There were significant differences in the levels of RVGCS, RVGLS, RVGRS, LVGLS, and LVGRS before and after chemotherapy (P < 0.05). Specifically, RVGCS: after 6 cycles of chemotherapy < after 4 cycles of chemotherapy < before chemotherapy; RVGLS: after 6 cycles of chemotherapy < after 4 cycles of chemotherapy < after 2 cycles of chemotherapy < before chemotherapy; RVGRS: after 6 cycles of chemotherapy < after 4 cycles of chemotherapy < before chemotherapy; LVGLS: after 6 cycles of chemotherapy < after 4 cycles of chemotherapy < before chemotherapy; and LVGRS: after 6 cycles of chemotherapy < before chemotherapy. The results of Pearson correlation analysis showed that the dose of doxorubicin was negatively correlated with RVGCS, RVGLS, RVGRS, and LVGLS, but not with TAPSE, RVFAC, LVEF, and LVGRS. 3D-STI is helpful for early detection of the changes of left and right ventricular myocardial function after PAD chemotherapy in patients with multiple myeloma. And the early screening value of the RVGLS parameter is higher.

Self-Delivery Janus-Prodrug for Precise Immuno-Chemotherapy of Colitis-Associated Colorectal Cancer

Aromatized thioketal (ATK) linked the immunoregulatory molecule (budesonide, Bud) and the cytotoxic molecule (gemcitabine, Gem) to construct a ROS-activated Janus-prodrug, termed as BAG. Benefiting from the hydrogen bonding, π-π stacking, and other intermolecular interactions, BAG could self-assemble into nanoaggregates (BAG NA) with a well-defined spherical shape and uniform size distribution. Compared to the carrier-based drug delivery system, BAG NA have ultrahigh drug loading content and ROS concentration-dependent drug release. Colitis-associated colorectal cancer (CAC) is a typical disease in which chronic inflammation transforms into tumors. BAG NA can be internalized by colon cancer C26 cells and then triggered by excessive intracellular ROS to release nearly 100% of the drugs. Based on this, BAG NA showed a stronger pro-apoptotic effect than free Bud combined with free Gem. What is gratifying is that orally administered BAG NA can precisely accumulate in the diseased colon tissues of CAC mice induced by AOM/DSS and simultaneously release Bud and Gem. Bud can regulate the tumor immune microenvironment to restore and enhance the cytotoxicity of Gem. Therefore, BAG NA maximizes the synergistic therapeutic effect through co-delivery of Bud and Gem. This work provided a cutting-edge method for constructing self-delivery Janus-prodrug based on ATK and confirmed its potential application in inflammation-related carcinogenesis.

Modeling Pharmacokinetics of Doxorubicin in Multiple Myeloma Cells

Doxorubicin (DOXO) is a well-established chemotherapy drug for treatment of different tumors, ranging from breast cancer, melanoma to multiple myeloma (MM). Here, we present a coupled experimental/modeling approach to study DOXO pharmacokinetics in MM cells, investigate its distribution among the extracellular and intracellular compartments during time. Three model candidates are considered and identified. Model selection is performed based on its ability to describe the data both qualitatively and in terms of quantitative indexes. The most parsimonious model consists of a nonlinear structure with a saturation-threshold control of intracellular DOXO efflux by the DOXO bound to the cellular DNA. This structure could explain the hypothesis that MM cells are drug-resistant, likely due to the involvement of P-glycoproteins.The proposed model is able to predict the intracellular (free and bound) DOXO and suggests the presence of a saturation-threshold drug-resistant mechanism.Clinical Relevance- The model can be used to properly understand and guide further experimental setup, e.g., to investigate multiple myeloma cell variability among different cell lines.

Pegylated Liposomal Doxorubicin in Vindesine-Based and Bortezomib-Based Regimens for Patients With Newly Diagnosed Multiple Myeloma: A Retrospective Study of Efficacy and Safety

Purpose

Although pegylated liposomal doxorubicin (PLD) has been approved in combination with bortezomib for relapsed/refractory multiple myeloma (MM), the antitumor efficacy and tolerability of PLD in different regimens for patients with newly diagnosed MM (NDMM) have not been fully defined.

Methods

A total of 249 NDMM patients diagnosed between January 2008 and October 2019 were included in this retrospective study. Among them, 112 patients received vindesine-based chemotherapy (35 vDD and 77 vAD) and 137 received bortezomib-based chemotherapy (58 VDD and 79 VD).

Results

In bortezomib-containing regimens, the complete response rate (48.3 vs. 30.4%, p = 0.033) and very good partial response or better rate (74.1 vs. 57.0%, p = 0.038) of VDD were significantly higher than those of VD subgroup. While no superior survival was found between VDD and VD subgroup. In vindesine-containing regimens, no statistical significance was identified between vDD and vAD in terms of response rate and survival. The occurrence rates of all cardiac AEs were similar between VDD and VD.

Conclusions

The vDD regimen was similar with vAD in the aspect of response rate, survival, and toxicity in NDMM patients. The addition of PLD to VD brought deeper response without increased toxicity, while no superior survival was found.

BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding in Immunotherapy and Targeted Therapies

PURPOSE

For immunotherapy, such as checkpoint inhibitors and chimeric antigen receptor T-cell therapy, where the efficacy does not necessarily increase with the dose, the maximum tolerated dose may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biologic dose (OBD) that optimizes patients' risk-benefit trade-off.

METHODS

We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off. The BOIN12 design makes the decision of dose escalation and de-escalation by simultaneously taking account of efficacy and toxicity and adaptively allocates patients to the dose that optimizes the toxicity-efficacy trade-off. We performed simulation studies to evaluate the performance of the BOIN12 design.

RESULTS

Compared with existing phase I/II dose-finding designs, the BOIN12 design is simpler to implement, has higher accuracy to identify the OBD, and allocates more patients to the OBD. One of the most appealing features of the BOIN12 design is that its adaptation rule can be pretabulated and included in the protocol. During the trial conduct, clinicians can simply look up the decision table to allocate patients to a dose without complicated computation.

CONCLUSION

The BOIN12 design is simple to implement and yields desirable operating characteristics. It overcomes the computational and implementation complexity that plagues existing Bayesian phase I/II dose-finding designs and provides a useful design to optimize the dose of immunotherapy and targeted therapy. User-friendly software is freely available to facilitate the application of the BOIN12 design.