Creating an Innovative Artificial Intelligence-Based Technology (TCRact) for Designing and Optimizing T Cell Receptors for Use in Cancer Immunotherapies: Protocol for an Observational Trial.

BACKGROUND: Cancer continues to be the leading cause of mortality in high-income countries, necessitating the development of more precise and effective treatment modalities. Immunotherapy, specifically adoptive cell transfer of T cell receptor (TCR)-engineered T cells (TCR-T therapy), has shown promise in engaging the immune system for cancer treatment. One of the biggest challenges in the development of TCR-T therapies is the proper prediction of the pairing between TCRs and peptide-human leukocyte antigen (pHLAs). Modern computational immunology, using artificial intelligence (AI)-based platforms, provides the means to optimize the speed and accuracy of TCR screening and discovery. OBJECTIVE: This study proposes an observational clinical trial protocol to collect patient samples and generate a database of pHLA:TCR sequences to aid the development of an AI-based platform for efficient selection of specific TCRs. METHODS: The multicenter observational study, involving 8 participating hospitals, aims to enroll patients diagnosed with stage II, III, or IV colorectal cancer adenocarcinoma. RESULTS: Patient recruitment has recently been completed, with 100 participants enrolled. Primary tumor tissue and peripheral blood samples have been obtained, and peripheral blood mononuclear cells have been isolated and cryopreserved. Nucleic acid extraction (DNA and RNA) has been performed in 86 cases. Additionally, 57 samples underwent whole exome sequencing to determine the presence of somatic mutations and RNA sequencing for gene expression profiling. CONCLUSIONS: The results of this study may have a significant impact on the treatment of patients with colorectal cancer. The comprehensive database of pHLA:TCR sequences generated through this observational clinical trial will facilitate the development of the AI-based platform for TCR selection. The results obtained thus far demonstrate successful patient recruitment and sample collection, laying the foundation for further analysis and the development of an innovative tool to expedite and enhance TCR selection for precision cancer treatments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04994093; https://clinicaltrials.gov/ct2/show/NCT04994093. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45872.

Widely applicable, extended flow cytometric stem cell enumeration panel for quality control of advanced cellular products.

The most widely used quality control assay for CD34 + hematopoietic stem cell product characterization is the protocol established by the International Society of Hematotherapy and Graft Engineering (ISHAGE). While this protocol is still the gold standard for stem cell enumeration and viability assessment, it does not include T cell enumeration, which is nowadays mandatory for assaying standard allogeneic grafts and various advanced therapy medicinal products (ATMPs). In accordance, we have developed and extensively validated a new approach for a more comprehensive characterization of hematopoietic cellular products using a pre-formulated dried antibody format panel. In addition to the counting beads, the typical markers CD45 fluorescein isothiocyanate (FITC) and CD34 phycoerythrin (PE), as well as the viability dye 7-amino actinomycin D (7-AAD), our novel pre-formulated panel also contains CD3 Pacific Blue (PB) and CD19 allophycocyanin (APC) in the same tube, thereby allowing a combined calculation of leucocytes, stem cells, T and B cells. Showing high linearity, sensitivity and accuracy, our approach is easy to implement and enables a more in-depth characterization of the cellular product under release testing conditions. In addition, the dried pre-formulated antibody approach increases assay reliability compared to the standard antibody panel.

Standardized assay for assessment of minimal residual disease in blood, bone marrow and apheresis from patients with plasma cell myeloma.

The recent advances in myeloma treatment result in significantly better outcomes, defined as increased progression free survival (PFS) and overall survival (OS). Since there is a proven correlation between the extend of response and prolonged survival, there is an urgent need for highly sensitive assays for the detection of minimal residual disease (MRD). Next generation flow cytometry has become a valuable approach for sensitive evaluation of the depth of complete response (CR). Here, we report the diagnostic performance and validation results of a single-tube 9-color panel assay. The validation design included intra-assay analysis measuring accuracy, inter-assay analysis estimating method's linearity and precision and inter-assay analysis evaluating repeatability. Furthermore, in inter-operator analysis assessed the comparability of the result analysis of different operators. Staining stability was evaluated in age-of-stain experiments. Our validation results show that a reliable detection of residual myeloma cells is feasible to a detection level of 10-5 with a single-tube assay for a variety of materials (peripheral blood, bone marrow and stem cell apheresis). This study establishes highly sensitive, fully standardized approach for MRD detection in myeloma that is ready for implementation in routine diagnostic laboratories.

Smoldering multiple myeloma: prevalence and current evidence guiding treatment decisions.

Smoldering multiple myeloma (SMM) is an asymptomatic plasma cell proliferative disorder associated with risk of progression to symptomatic multiple myeloma (MM) or amyloidosis. In comparison to monoclonal gammopathy of undetermined significance (MGUS), SMM has a much higher risk of progression to MM. Thanks to advances in our understanding of the risk factors, the subset of patients with ultra-high risk of progression to MM (80%-90% at 2 years) has been identified. The revision of the diagnostic criteria resulted in changes in the management of this cohort of patients. In contrast to the management guidelines for MGUS patients, SMM patients need to be studied more intensively in order to identify biomarkers necessary for accurate risk stratification. In this review, we focus on the risk of progression from SMM to MM, as well as the influence of early treatment on overall survival, time to progression and quality of life.