Real-world treatment patterns, healthcare resource use and disease burden in patients with multiple myeloma in Europe.

Aim: To investigate treatment patterns, healthcare resource utilization and disease burden in patients with multiple myeloma (MM). Methods: Point-in-time survey of physicians and their patients presenting in a real-world clinical setting, collected across Europe between May and November 2021. Results: In total, 173 physicians provided data for 2179 patients with MM. Treatments received became more diverse as line of therapy increased, dictated by previous treatment choices. Overall, 25% of all patients were tri-exposed, and experienced a higher degree of healthcare resource utilization, disease burden and impairment than non-tri-exposed patients. Conclusion: The treatment landscape in MM is complex and evolving. There is an unmet need for more effective therapies to reduce disease burden, particularly in tri-exposed patients.

There are many new treatments available for patients with multiple myeloma. While outcomes such as survival, symptoms and health problems experienced have improved, patients still continue to relapse and fall ill again. This means their current treatment stops working and they have to change to a new treatment to prevent their disease from developing further. Patients who have received three different types of treatment are classed as being 'tri-exposed', and they experience greater problems with their health. To better understand this course of events, we used information from a survey of doctors and their patients with multiple myeloma across Europe in 2021. We looked at patient's symptoms, the treatments they received, how and when they accessed healthcare (including hospital visits and tests) and the overall difficulties experienced due to their illness. We found that patients were broadly treated according to the most recent European guidelines, although differences were seen between countries. When patients had to switch therapy, the type of treatment received next depended on what they had previously been prescribed, meaning that treatment choices became increasingly complicated. Overall, 25% of patients in our study were classed as tri-exposed, and had more hospitalisations, required more hospital tests, had greater health problems and experienced more difficulties at work than those who were not tri-exposed. Despite recent developments in the treatment of multiple myeloma, there is still a need for more effective therapies. This is especially true for patients who are tri-exposed, who have limited treatment options and experienced greater health problems.

Adjusted comparison of outcomes between patients from CARTITUDE-1 versus multiple myeloma patients with prior exposure to proteasome inhibitors, immunomodulatory drugs and anti-CD38 antibody from the prospective, multinational LocoMMotion study of real-world clinical practice.

Ciltacabtagene autoleucel (cilta-cel) is a chimeric antigen receptor T-cell therapy studied in patients with multiple myeloma exposed to three classes of treatment in the single-arm CARTITUDE-1 study. To assess the effectiveness of cilta-cel compared to real-world clinical practice (RWCP), we performed adjusted comparisons using individual patients' data from CARTITUDE-1 and LocoMMotion, a prospective, multinational study of patients with multiple myeloma triple-class exposed of treatment. Comparisons were performed using inverse probability weighting. In CARTITUDE-1, 113 patients were enrolled, and 97 patients were infused with cilta-cel. In LocoMMotion, 248 patients were enrolled, and 170 patients were included in the comparisons versus infused patients. Ninety-two unique regimens were used in LocoMMotion, most frequently carfilzomib-dexamethasone (13.7%), pomalidomide-cyclophosphamide-dexamethasone (13.3%) and pomalidomidedexamethasone (11.3%). Adjusted comparisons showed that patients treated with cilta-cel were 3.12-fold more likely to respond to treatment than those managed by RWCP (response rate, 3.12, 95% confidence interval [95% CI]: 2.24-4.00), had their risk of progression or death reduced to by 85% (progression-free survival hazard ratio=0.15, 95% CI: 0.08-0.29), and a risk of death lowered by 80% (overall survival hazard ratio HR=0.20, 95% CI: 0.09-0.41). The incremental improvement in healthrelated quality of life from baseline for cilta-cel versus RWCP at week 52, as measured by EORTC QLQ-C30 Global Health Status, was 13.4 (95% CI: 3.5-23.6) and increased to 30.8 (95% CI: 21.8-39.8) when including death as additional information regarding patients' health status. Patients treated with cilta-cel experienced more adverse events than those managed with RWCP (any grade: 100% vs. 83.5%). The results from this study demonstrate improved efficacy outcomes of cilta-cel versus RWCP and highlight its potential as a novel and effective treatment option for patients with multiple myeloma triple-class exposed of antimyeloma treatment. CARTITUDE-1 is registered with clinicaltrials gov. Identifier: NCT03548207. LocoMMotion is registered with clinicaltrials gov. Identifier: NCT04035226.

Adjusted Comparison of Outcomes between Patients from CARTITUDE-1 versus Multiple Myeloma Patients with Prior Exposure to PI, Imid and Anti-CD-38 from a German Registry.

Ciltacabtagene autoleucel (cilta-cel) is a Chimeric antigen receptor T-cell therapy with the potential for long-term disease control in heavily pre-treated patients with relapsed/refractory multiple myeloma (RRMM). As cilta-cel was assessed in the single-arm CARTITUDE-1 clinical trial, we used an external cohort of patients from the Therapie Monitor registry fulfilling the CARTITUDE-1 inclusion criteria to evaluate the effectiveness of cilta-cel for overall survival (OS) and time to next treatment (TTNT) vs. real-world clinical practice. Individual patient data allowed us to adjust the comparisons between both cohorts, using the inverse probability of treatment weighting (IPW; average treatment effect in the treated population (ATT) and overlap population (ATO) weights) and multivariable Cox proportional hazards regression. Outcomes were compared in intention-to-treat (HR, IPW-ATT: TTNT: 0.13 (95% CI: 0.07, 0.24); OS: 0.14 (95% CI: 0.07, 0.25); IPW-ATO: TTNT: 0.24 (95% CI: 0.12, 0.49); OS: 0.26 (95% CI: 0.13, 0.54)) and modified intention-to-treat (HR, IPW-ATT: TTNT: 0.24 (95% CI: 0.09, 0.67); OS: 0.26 (95% CI: 0.08, 0.84); IPW-ATO: TTNT: 0.26 (95% CI: 0.11, 0.59); OS: 0.31 (95% CI: 0.12, 0.79)) populations. All the comparisons were statistically significant in favor of cilta-cel. These results highlight cilta-cel's potential as a novel, effective treatment to address unmet needs in patients with RRMM.

Model-guided combinatorial optimization of complex synthetic gene networks.

Constructing gene circuits that satisfy quantitative performance criteria has been a long-standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three-gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high-throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model-guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators.

Precision multidimensional assay for high-throughput microRNA drug discovery.

Development of drug discovery assays that combine high content with throughput is challenging. Information-processing gene networks can address this challenge by integrating multiple potential targets of drug candidates' activities into a small number of informative readouts, reporting simultaneously on specific and non-specific effects. Here we show a family of networks implementing this concept in a cell-based drug discovery assay for miRNA drug targets. The networks comprise multiple modules reporting on specific effects towards an intended miRNA target, together with non-specific effects on gene expression, off-target miRNAs and RNA interference pathway. We validate the assays using known perturbations of on- and off-target miRNAs, and evaluate an ∼700 compound library in an automated screen with a follow-up on specific and non-specific hits. We further customize and validate assays for additional drug targets and non-specific inputs. Our study offers a novel framework for precision drug discovery assays applicable to diverse target families.

Highly modular bow-tie gene circuits with programmable dynamic behaviour.

Synthetic gene circuits often require extensive mutual optimization of their components for successful operation, while modular and programmable design platforms are rare. A possible solution lies in the 'bow-tie' architecture, which stipulates a focal component-a 'knot'-uncoupling circuits' inputs and outputs, simplifying component swapping, and introducing additional layer of control. Here we construct, in cultured human cells, synthetic bow-tie circuits that transduce microRNA inputs into protein outputs with independently programmable logical and dynamic behaviour. The latter is adjusted via two different knot configurations: a transcriptional activator causing the outputs to track input changes reversibly, and a recombinase-based cascade, converting transient inputs into permanent actuation. We characterize the circuits in HEK293 cells, confirming their modularity and scalability, and validate them using endogenous microRNA inputs in additional cell lines. This platform can be used for biotechnological and biomedical applications in vitro, in vivo and potentially in human therapy.