Therapeutic Monitoring of Palbociclib, Ribociclib, Abemaciclib, M2, M20, and Letrozole in Human Plasma: A Novel LC-MS/MS Method.

BACKGROUND: Therapeutic drug monitoring (TDM) using cyclin-dependent kinase inhibitors (CDK4/6is) is a novel approach for optimizing treatment outcomes. Currently, palbociclib, ribociclib, and abemaciclib are the available CDK4/6is and are primarily coadministered with letrozole. This study aimed to develop and validate an LC-MS/MS method for the simultaneous analysis of CDK4/6is, 2 active metabolites of abemaciclib (M2 and M20), and letrozole in human plasma for use in TDM studies. METHODS: Sample pretreatment comprised protein precipitation with methanol and dilution of the supernatant with an aqueous mobile phase. Chromatographic separation was achieved using a reversed-phase XBridge BEH C18 column (2.5 µm, 3.0 × 75 mm XP), with methanol serving as the organic mobile phase and pyrrolidine-pyrrolidinium formate (0.005:0.005 mol/L) buffer (pH 11.3) as the aqueous mobile phase. A triple quadrupole mass spectrometer was used for the detection, with the ESI source switched from negative to positive ionization mode and the acquisition performed in multiple reaction monitoring mode. RESULTS: The complete validation procedure was successfully performed in accordance with the latest regulatory guidelines. The following analytical ranges (ng/mL) were established for the tested compounds: 6-300, palbociclib and letrozole; 120-6000, ribociclib; 40-800, abemaciclib; and 20-400, M2 and M20. All results met the acceptance criteria for linearity, accuracy, precision, selectivity, sensitivity, matrix effects, and carryover. A total of 85 patient samples were analyzed, and all measured concentrations were within the validated ranges. The percent difference for the reanalyzed samples ranged from -11.2% to 7.0%. CONCLUSIONS: A simple and robust LC-MS/MS method was successfully validated for the simultaneous quantification of CDK4/6is, M2, M20, and letrozole in human plasma. The assay was found to be suitable for measuring steady-state trough concentrations of the analytes in patient samples.

Targeted therapy for multiple myeloma: an overview on CD138-based strategies.

Multiple myeloma (MM) is an incurable hematological disease characterized by the uncontrolled growth of plasma cells primarily in the bone marrow. Although its treatment consists of the administration of combined therapy regimens mainly based on immunomodulators and proteosome inhibitors, MM remains incurable, and most patients suffer from relapsed/refractory disease with poor prognosis and survival. The robust results achieved by immunotherapy targeting MM-associated antigens CD38 and CD319 (also known as SLAMF7) have drawn attention to the development of new immune-based strategies and different innovative compounds in the treatment of MM, including new monoclonal antibodies, antibody-drug conjugates, recombinant proteins, synthetic peptides, and adaptive cellular therapies. In this context, Syndecan1 (CD138 or SDC1), a transmembrane heparan sulfate proteoglycan that is upregulated in malignant plasma cells, has gained increasing attention in the panorama of MM target antigens, since its key role in MM tumorigenesis, progression and aggressiveness has been largely reported. Here, our aim is to provide an overview of the most important aspects of MM disease and to investigate the molecular functions of CD138 in physiologic and malignant cell states. In addition, we will shed light on the CD138-based therapeutic approaches currently being tested in preclinical and/or clinical phases in MM and discuss their properties, mechanisms of action and clinical applications.

Clinical Implementation of Rare and Novel DPYD Variants for Personalizing Fluoropyrimidine Treatment: Challenges and Opportunities.

Fluoropyrimidines (FLs) [5-Fluorouracil, Capecitabine] are used in the treatment of several solid tumors. Dihydropyrimidine dehydrogenase (DPD) is the rate-limiting enzyme for FL detoxification, and its deficiency could lead to severe, life-threatening or fatal toxicity after FL administration. Testing with a pharmacogenetic panel of four deleterious variants in the dihydropyrimidine dehydrogenase gene (DPYD) (DPYD*2A, DPYD*13, c.2846A > T, c.1129-5923C > G) prior to FL treatment, is recommended by scientific consortia (e.g., CPIC, DPWG) and drug regulatory agencies (e.g., EMA). However, this panel identifies < 20% of patients at risk of severe FL-related toxicity. Cumulative recent evidence highlights the potential clinical value of rare (minor allele frequency < 1%) and novel DPYD genetic variants for identifying an additional fraction of DPD-deficient patients at increased risk of severe FL-related toxicity. In this review, we aimed to comprehensively describe the available evidence regarding the potential clinical predictive role of novel and rare DPYD variants as toxicity markers in FL-treated patients, and to discuss the challenges and opportunities in tailoring FL treatment based upon clinical application of such markers. Although we must overcome existing barriers to the clinical implementation, the available data support that comprehensive assessment of the DPYD sequence, including rare and novel genetic variants, may significantly enhance the pre-emptive identification of at-risk patients, compared to the current targeted approach.

Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover hidden patterns from complex NGS data and to solve various PGx problems. In this review, we provide a comprehensive overview of the NGS approaches that can be employed and the different PGx studies implicating the use of NGS data. We also provide an excursus of the ML algorithms that can exert a role as fundamental strategies in the PGx field to improve personalized medicine in cancer.

Oral Administration of Cancer Vaccines: Challenges and Future Perspectives.

Cancer vaccines, a burgeoning strategy in cancer treatment, are exploring innovative administration routes to enhance patient and medical staff experiences, as well as immunological outcomes. Among these, oral administration has surfaced as a particularly noteworthy approach, which is attributed to its capacity to ignite both humoral and cellular immune responses at systemic and mucosal tiers, thereby potentially bolstering vaccine efficacy comprehensively and durably. Notwithstanding this, the deployment of vaccines through the oral route in a clinical context is impeded by multifaceted challenges, predominantly stemming from the intricacy of orchestrating effective oral immunogenicity and necessitating strategic navigation through gastrointestinal barriers. Based on the immunogenicity of the gastrointestinal tract, this review critically analyses the challenges and recent advances and provides insights into the future development of oral cancer vaccines.