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Krishanu Saha

Publications and source records attributed to Krishanu Saha.

2 recordsLinked to original sources

Directing fratricide within T cell products using an anti-uPAR chimeric antigen receptor to drive the production of potent therapeutic cells.

Cell therapy manufacturing of primary T cells often results in heterogeneous cell populations in the final product, with many cells lacking desired receptor expression or exhausted and other dysfunctional phenotypes. Here, we design a novel cell-intrinsic strategy to genetically reprogram primary human T cells to autonomously detect and eliminate dysfunctional cells. This integrated detection and elimination process, known as directed fratricide, is programmed via non-viral CRISPR genome editing to eliminate the T cell receptor (TCR) alpha chain (TRAC gene knockout) and integrate a chimeric antigen receptor (CAR) against the urokinase-type plasminogen activator receptor (uPAR), also known as CD87. In these cell products, strong T cell stimulation or activation during manufacturing causes a small subset of cells to express uPAR, which triggers CAR-mediated killing within the product. This fratricide induces proliferation in the desired cells and destroys undesired cells, a process that could be modeled computationally and controlled robustly via supplements to the culture media. The strategy enabled enrichment of anti-uPAR and anti-disialoganglioside (GD2) CAR-T cell products up to ≥99% CAR+/TCR-, favoring a memory-like phenotype. Understanding growth dynamics among T cell subsets and reprogramming them via CRISPR could accelerate the biomanufacturing of potent cell products without extensive selection methods.

Humans↗

Signal dynamics in Sonic hedgehog tissue patterning.

During development, secreted signaling factors, called morphogens, instruct cells to adopt specific mature phenotypes. However, the mechanisms that morphogen systems employ to establish a precise concentration gradient for patterning tissue architecture are highly complex and are typically analyzed only at long times after secretion (i.e. steady state). We have developed a theoretical model that analyzes dynamically how the intricate transport and signal transduction mechanisms of a model morphogen, Sonic hedgehog (Shh), cooperate in modular fashion to regulate tissue patterning in the neural tube. Consistent with numerous recent studies, the model elucidates how the dynamics of gradient formation can be a key determinant of cell response. In addition, this work yields several novel insights into how different transport mechanisms or ;modules' control pattern formation. The model predicts that slowing the transport of a morphogen, such as by lipid modification of the ligand Shh, by ligand binding to proteoglycans, or by the moderate upregulation of dedicated transport molecules like Dispatched, can actually increase the signaling range of the morphogen by concentrating it near the secretion source. Furthermore, several transcriptional targets of Shh, such as Patched and Hedgehog-interacting protein, significantly limit its signaling range by slowing transport and promoting ligand degradation. This modeling approach elucidates how individual modular elements that operate dynamically at various times during patterning can shape a tissue pattern.

Animals↗