Foroughmand-Araabi, M.-H. | Search bioRxiv

bioRxiv2022

Delayed dynamics of migratory response to CTLA-4 blockade reveals a mechanistic view on potential T cells reinvigoration following immune checkpoint blockade

Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) receptors, two clinically relevant targets for immunotherapy of cancer, are negative regulators of in immune cell activation and migration. However, optimizing therapeutic outcomes still requires fundamental research to reach a comprehensive insight into the coherent function of immune regulators. Here, we investigated the statistical dynamics of T cells migration as a measure of the functional response to these pathways in an experimental setup of immune checkpoint blockade. For this purpose, we used a previously developed 3-dimensional organotypic culture of patient-derived tumor spheroids. Experiment-based dynamical modeling remarked distinct characteristics of the receptors regulation followed through with the modification of their proportions in the immune modulation. We demonstrated that time-delayed kinetics of PD-1 activation just overrides its relatively more efficient cell-level function which potentially makes an operative contribution to the functional dominance of CTLA-4 in the tumor microenvironment. Simulation results showed good agreement with data for tumor cells reduction and active immune cells count observed in each experiment. These analyses propose a new mechanistic view on relative immunogenicity of PD-1 and CTLA-4 inhibitors manifested in literature and point the possible inherent obstacles in checkpoint inhibition-based immunotherapy of cancer to address in the future. SignificanceEx vivo monitoring of temporal response to PD-1 and CTLA-4 in the closure of T cell movement dynamics and elucidating their feasible commitment to the kinetic constraints at cell-level resolution. Delayed dynamics of migratory response to CTLA-4 inhibition revealed a mechanistic view on potential T cell reinvigoration following immune checkpoint blockade.

cancer biology↗

bioRxiv2021

Scelestial: fast and accurate single-cell lineage tree inference based on a Steiner tree approximation algorithm

Single-cell genome sequencing provides a highly granular view of biological systems but is affected by high error rates, allelic amplification bias, and uneven genome coverage. This creates a need for data-specific computational methods, for purposes such as for cell lineage tree inference. The objective of cell lineage tree reconstruction is to infer the evolutionary process that generated a set of observed cell genomes. Lineage trees may enable a better understanding of tumor formation and growth, as well as of organ development for healthy body cells. We describe a method, Scelestial, for lineage tree reconstruction from single-cell data, which is based on an approximation algorithm for the Steiner tree problem and is a generalization of the neighbor-joining method. We adapt the algorithm to efficiently select a limited subset of potential sequences as internal nodes, in the presence of missing values, and to minimize cost by lineage tree-based missing value imputation. In a comparison against seven state-of-the-art single-cell lineage tree reconstruction algorithms - BitPhylogeny, OncoNEM, SCITE, SiFit, SASC, SCIPhI, and SiCloneFit - on simulated and real single-cell tumor samples, Scelestial performed best at reconstructing trees in terms of accuracy and run time. Scelestial has been implemented in C++. It is also available as an R package named RScelestial.

bioinformatics↗