Modeling Metastatic Colonization in a Decellularized Organ Scaffold-Based Perfusion Bioreactor

Metastatic cancer spread is responsible for most cancer-related deaths. To colonize a new organ, invading cells adapt to, and remodel, the local extracellular matrix (ECM), a network of proteins and proteoglycans underpinning all tissues, and a critical regulator of homeostasis and disease. However, there is a major lack in tools to study cancer cell behavior within native 3D ECM. Here, an in-house designed bioreactor, where mouse organ ECM scaffolds are perfused and populated with cells that are challenged to colonize it, is presented. Using a specialized bioreactor chamber, it is possible to monitor cell behavior microscopically (e.g., proliferation, migration) within the organ scaffold. Cancer cells in this system recapitulate cell signaling observed in vivo and remodel complex native ECM. Moreover, the bioreactors are compatible with co-culturing cell types of different genetic origin comprising the normal and tumor microenvironment. This degree of experimental flexibility in an organ-specific and 3D context, opens new possibilities to study cell–cell and cell–ECM interplay and to model diseases in a controllable organ-specific system ex vivo

Larotrectinib in patients with TRK fusion-positive solid tumours: a pooled analysis of three phase 1/2 clinical trials

BackgroundThe selective TRK inhibitor larotrectinib was approved for paediatric and adult patients with advanced TRK fusion-positive solid tumours based on a primary analysis set of 55 patients. The aim of our analysis was to explore the efficacy and long-term safety of larotrectinib in a larger population of patients with TRK fusion-positive solid tumours.MethodsPatients were enrolled and treated in a phase 1 adult, a phase 1/2 paediatric, or a phase 2 adolescent and adult trial. Some eligibility criteria differed between these studies. For this pooled analysis, eligible patients were aged 1 month or older, with a locally advanced or metastatic non-CNS primary, TRK fusion-positive solid tumour, who had received standard therapy previously if available. This analysis set includes the 55 patients on which approval of larotrectinib was based. Larotrectinib was administered orally (capsule or liquid formulation), on a continuous 28-day schedule, to adults mostly at a dose of 100 mg twice daily, and to paediatric patients mostly at a dose of 100 mg/m2 (maximum of 100 mg) twice daily. The primary endpoint was objective response as assessed by local investigators in an intention-to-treat analysis. Contributing trials are registered with ClinicalTrials.gov, NCT02122913 (active not recruiting), NCT02637687 (recruiting), and NCT02576431 (recruiting).FindingsBetween May 1, 2014, and Feb 19, 2019, 159 patients with TRK fusion-positive cancer were enrolled and treated with larotrectinib. Ages ranged from less than 1 month to 84 years. The proportion of patients with an objective response according to investigator assessment was 121 (79%, 95% CI 72-85) of 153 evaluable patients, with 24 (16%) having complete responses. In a safety population of 260 patients treated regardless of TRK fusion status, the most common grade 3 or 4 larotrectinib-related adverse events were increased alanine aminotransferase (eight [3%] of 260 patients), anaemia (six, 2%), and decreased neutrophil count (five [2%]). The most common larotrectinib-related serious adverse events were increased alanine aminotransferase (two [<1%] of 260 patients), increased aspartate aminotransferase (two [<1%]), and nausea (two [<1%]). No treatment-related deaths occurred.InterpretationThese data confirm that TRK fusions define a unique molecular subgroup of advanced solid tumours for which larotrectinib is highly active. Safety data indicate that long-term administration of larotrectinib is feasible.FundingBayer and Loxo Oncology

IMPROVE:a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition

Background: Mutation-derived neoantigens are critical targets for tumor rejection in cancer immunotherapy, and better tools for neoepitope identification and prediction are needed to improve neoepitope targeting strategies. Computational tools have enabled the identification of patient-specific neoantigen candidates from sequencing data, but limited data availability has hindered their capacity to predict which of the many neoepitopes will most likely give rise to T cell recognition. Method: To address this, we make use of experimentally validated T cell recognition towards 17,500 neoepitope candidates, with 467 being T cell recognized, across 70 cancer patients undergoing immunotherapy. Results: We evaluated 27 neoepitope characteristics, and created a random forest model, IMPROVE, to predict neoepitope immunogenicity. The presence of hydrophobic and aromatic residues in the peptide binding core were the most important features for predicting neoepitope immunogenicity. Conclusion: Overall, IMPROVE was found to significantly advance the identification of neoepitopes compared to other current methods.</p