Immune Checkpoint Inhibitor Rechallenge After Immune-Related Adverse Events in Patients With Cancer.

Importance: Limited information is available on the safety of a rechallenge with an immune checkpoint inhibitor (ICI) after an immune-related adverse event (irAE). Objective: To identify the recurrence rate of the same irAE that prompted discontinuation of ICI therapy after an ICI rechallenge in patients with cancer and to identify the clinical features associated with such recurrences. Design, Setting, and Participants: This observational, cross-sectional, pharmacovigilance cohort study examined individual case safety reports from the World Health Organization database VigiBase, which contains case reports from more than 130 countries. Case reports were extracted from database inception (1967) to September 1, 2019. All consecutive ICI cases with at least 1 associated irAE were included. Main Outcomes and Measures: The primary outcome was the rate of recurrence of the initial irAE after an ICI rechallenge. Secondary outcomes included the factors associated with the recurrence after a rechallenge among informative rechallenges, the recurrence rate according to the ICI regimen (anti-programmed cell death 1 or anti-programmed cell death ligand 1 monotherapy, anti-cytotoxic T-lymphocyte antigen-4 monotherapy, or combination therapy), and the rate of occurrence of a different irAE after a rechallenge. Results: A total of 24 079 irAE cases associated with at least 1 ICI were identified. Among the irAEs, 452 of 6123 irAEs associated with ICI rechallenges (7.4%) were informative rechallenges. One hundred thirty recurrences (28.8%; 95% CI, 24.8-33.1) of the initial irAE were observed. In a rechallenge, colitis (reporting odds ratio [OR], 1.77; 95% CI, 1.14-2.75; P = .01), hepatitis (reporting OR, 3.38; 95% CI, 1.31-8.74; P = .01), and pneumonitis (reporting OR, 2.26; 95% CI, 1.18-4.32; P = .01) were associated with a higher recurrence rate, whereas adrenal events were associated with a lower recurrence rate (reporting OR, 0.33; 95% CI, 0.13-0.86; P = .03) compared with other irAEs. Conclusions and Relevance: This cohort study found a 28.8% recurrence rate of the same irAE associated with the discontinuation of ICI therapy after a rechallenge with the same ICI. Resuming ICI therapy could be considered for select patients, with appropriate monitoring and use of standard treatment algorithms to identify and treat toxic effects.

Protein dynamics in drug combinations: a linear superposition of individual-drug responses.

Drugs and drug combinations have complex biological effects on cells and organisms. Little is known about how drugs affect protein dynamics that determine these effects. Here, we use a dynamic proteomics approach to accurately follow 15 protein levels in human cells in response to 13 different drugs. We find that protein dynamics in response to combinations of drugs are described accurately by a linear superposition (weighted sum) of their response to individual drugs. The weights in this superposition describe the relative impact of each drug on each protein. Using these weights, we show that one can predict the dynamics in a three-drug or four-drug combination on the basis of the dynamics in drug pairs. Our approach might eliminate the need to increase the number of experiments exponentially with the number of drugs and suggests that it might be possible to rationally control protein dynamics with specific drug combinations.

Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells.

Recent advances allow tracking the levels and locations of a thousand proteins in individual living human cells over time using a library of annotated reporter cell clones (LARC). This library was created by Cohen et al. to study the proteome dynamics of a human lung carcinoma cell-line treated with an anti-cancer drug. Here, we report the Dynamic Proteomics database for the proteins studied by Cohen et al. Each cell-line clone in LARC has a protein tagged with yellow fluorescent protein, expressed from its endogenous chromosomal location, under its natural regulation. The Dynamic Proteomics interface facilitates searches for genes of interest, downloads of protein fluorescent movies and alignments of dynamics following drug addition. Each protein in the database is displayed with its annotation, cDNA sequence, fluorescent images and movies obtained by the time-lapse microscopy. The protein dynamics in the database represents a quantitative trace of the protein fluorescence levels in nucleus and cytoplasm produced by image analysis of movies over time. Furthermore, a sequence analysis provides a search and comparison of up to 50 input DNA sequences with all cDNAs in the library. The raw movies may be useful as a benchmark for developing image analysis tools for individual-cell dynamic-proteomics. The database is available at http://www.dynamicproteomics.net/.