Individual isogenic immune cells respond to identical stimuli with unique signaling kinetics. Shapes of kinetic trajectories describing time evolution of abundances of multiple signaling molecules in single cells contain key information regarding signaling mechanisms. However, it can be challenging to measure many signaling reporters simultaneously in single cell in experiments. Flow and mass cytometry experiments can assay a large number of proteins (4 to100) but individual cells are not tracked in these experiments, therefore, such measurements only provide a statistical description of the signaling kinetics, e.g., mean abundances, or, covariance between protein abundances. Is there a way to reconstruct signaling trajectories, even approximately, in individual cells using cytometry data? We address this question affirmatively by using a novel method based on identification of a dynamical invariant pertaining to chemical reaction networks. We validate our method in data obtained from in silico networks and published single cell experiments. We apply our trajectory reconstruction method to analyze mass cytometry data for NaturalKiller (NK) cells to decipher mechanisms underlying NK cell cytotoxic responses.