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Shah, S. B.

Publications and source records attributed to Shah, S. B..

2 recordsLinked to original sources

The CD58:CD2 axis is co-regulated with PD-L1 via CMTM6 and governs anti-tumor immunity

The cell autonomous balance of immune-inhibitory and -stimulatory signals is a critical yet poorly understood process in cancer immune evasion. Using patient-derived co-culture models and humanized mouse models, we show that an intact CD58:CD2 interaction is necessary for anti-tumor immunity. Defects in this axis lead to multi-faceted immune evasion through impaired CD2-dependent T cell polyfunctionality, T cell exclusion, impaired intra-tumoral proliferation, and concurrent protein stabilization of PD-L1. We performed genome-scale CRISPR-Cas9 and CD58 coimmunoprecipitation mass spectrometry screens identifying CMTM6 as a key stabilizer of CD58, and show that CMTM6 is required for concurrent upregulation of PD-L1 in CD58 loss. Single-cell RNA-seq analysis of patient melanoma samples demonstrates that most TILs lack expression of primary costimulatory signals required for response to PD-1 blockade (e.g. CD28), but maintain strong CD2 expression, thus providing an opportunity to mobilize a so far therapeutically untapped pool of TILs for anti-tumor immunity. We identify two potential therapeutic avenues, including rescued activation of human CD2-expressing TILs using recombinant CD58 protein, and targeted disruption of PD-L1/CMTM6 interactions. Our work identifies an underappreciated yet critical axis at the nexus of cancer immunity and evasion, uncovers a fundamental mechanism of co-inhibitory and -stimulatory signal balancing, and provides new approaches to improving cancer immunotherapies.

cancer biology↗

Generating complex patterns of gene expression without regulatory circuits

Synthetic biology has successfully advanced our ability to design and implement complex, time-varying genetic circuits to control the expression of recombinant proteins. However, these circuits typically require the production of regulatory genes whose only purpose is to coordinate expression of other genes. When designing very small genetic constructs, such as viral genomes, we may want to avoid introducing such auxiliary gene products while nevertheless encoding complex expression dynamics. To this end, here we demonstrate that varying only the placement and strengths of promoters, terminators, and RNase cleavage sites in a computational model of a bacteriophage genome is sufficient to achieve solutions to a variety of basic gene expression patterns. We discover these genetic solutions by computationally evolving genomes to reproduce desired gene expression time-course data. Our approach shows that non-trivial patterns can be evolved, including complex patterns where the relative ordering of genes by abundance changes over time. We find that some patterns are easier to evolve than others, and comparable expression patterns can be achieved via different genetic architectures. Our work opens up a novel avenue to genome engineering via fine-tuning the balance of gene expression and gene degradation rates. Author summaryViruses that infect bacteria, commonly called bacteriophages, typically have small genomes that encode as few as 10 genes. From the perspective of understanding genome design and regulation, these organisms are important model systems. Similar to cellular species, the genes encoded on a phage genome often must be expressed at different levels and at particular times during the phage lifecycle. Given their unique size constraints, it may be advantageous for phages to accomplish differential gene expression without having to produce a variety of dedicated regulatory molecules--which are frequently encoded on the larger and more complex genomes of free-living species. Here, we use a computational simulation of phage infection coupled with an evolutionary selection algorithm to illustrate that phage genomes can encode complex time-dependent gene expression patterns without the need for dedicated regulatory molecules. We anticipate that this simulation framework may additionally aid future phage genome design and engineering efforts.

synthetic biology↗