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Kheir Gouda, M.

Publications and source records attributed to Kheir Gouda, M..

2 recordsLinked to original sources

Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker

Background and AimsA subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that chemotherapy-resistant PDACs express a glycan biomarker called sTRA. Methods. We tested this marker to identify treatment-resistant PDAC in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from cohorts of human subjects. Results. Among a panel of 27 cell lines, high levels of cell-surface sTRA identified higher resistance to seven chemotherapeutics used against PDAC. Using primary tumors from two different cohorts, patients who were positive for a gene-expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, using direct measurements of sTRA in tissue microarrays by quantitative immunofluorescence, patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Further, a blood-plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy. This blood test performed with 96% specificity and 56% sensitivity in a blinded cohort using samples collected before the start of treatment. Conclusion. These findings establish that tissue or plasma sTRA can identify PDACs that are resistant to neoadjuvant or adjuvant chemotherapy. This capability could help apply systemic treatments more precisely and facilitate biomarker-guided trials targeting resistant PDAC.

cancer biology↗

Evolutionary regain of lost gene circuit function

Evolutionary reversibility - the ability to regain a lost function - is an important problem both in evolutionary and synthetic biology, where repairing natural or synthetic systems broken by evolutionary processes may be valuable. Here, we use a synthetic positive-feedback (PF) gene circuit integrated into haploid Saccharomyces cerevisiae cells to test if the population can restore lost PF function. In previous evolution experiments, mutations in a gene eliminated the fitness costs of PF activation. Since PF activation also provides drug resistance, exposing such compromised or broken mutants to both drug and inducer should create selection pressure to regain drug resistance and possibly PF function. Indeed, evolving seven PF mutant strains in the presence of drug revealed three adaptation scenarios through genomic mutations outside of the PF circuit that elevate PF basal expression, possibly by affecting transcription, translation, degradation and other fundamental cell functions. Nonfunctional mutants gained drug resistance without ever developing high expression, while quasi-functional and dysfunctional PF mutants developed high expression which then diminished, although more slowly for dysfunctional mutants where revertant clones arose. These results highlight how intracellular context, such as the growth rate, can affect regulatory network dynamics and evolutionary dynamics, which has important consequences for understanding the evolution of drug resistance and developing future synthetic biology applications.\n\nSignificance StatementNatural or synthetic genetic modules can lose their function over long-term evolution if the function is costly. How populations can evolve to restore broken functions is poorly understood. To test the reversibility of evolutionary breakdown, we use yeast cell populations with a chromosomally integrated synthetic gene circuit. In previous evolution experiments the gene circuit lost its costly function through various mutations. By exposing such mutant populations to conditions where regaining gene circuit function would be beneficial we find adaptation scenarios with or without repairing lost gene circuit function. These results are important for drug resistance or future synthetic biology applications where loss and regain of function play a significant role.

systems biology↗