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Biology subjects

Aalinkeel, R.

Publications and source records attributed to Aalinkeel, R..

2 recordsLinked to original sources

A PSMA-Targeted Up-conversion Nanoplatform for Deep-Tissue dual activation Photodynamic and Sonodynamic Therapy of Castration Resistant Prostate Cancer.

Photodynamic therapy (PDT) for prostate cancer is limited by the shallow penetration of visible light into deep-seated tumors. In contrast, sonodynamic therapy (SDT) enables noninvasive deep-tissue activation using ultrasound, while near-infrared photodynamic therapy (NIR-PDT) enhances tissue penetration through up-conversion-mediated activation. Based on these advantages, we developed a prostate-specific membrane antigen (PSMA)-targeted nanotheranostic platform (UCNPs@mSiO2/HPPH@TCS) to compare NIR-PDT and SDT in vitro for penetration-enhanced and targeted prostate cancer therapy. The nanoformulation consists of NaYF4:Yb3+, Er3+ up-conversion nanoparticles coated with mesoporous silica for high loading of HPPH (Photochlor), which functions as both photosensitizer and sonosensitizer, and a PSMA-targeted chitosan shell for selective tumor targeting. Physicochemical characterization confirms a uniform core-shell structure ([~]63 nm). Tissue-mimicking depth studies demonstrate that SDT and NIR-PDT achieve greater penetration than conventional 665 nm PDT in thicker tissue layers. Intracellular reactive oxygen species (ROS) analysis shows that SDT generates higher total ROS levels, whereas NIR-PDT produces greater singlet oxygen generation. Three-dimensional spheroid models further validate efficacy, demonstrating rapid spheroid collapse via apoptosis, with SDT inducing earlier apoptosis and more uniform penetration than PDT. Collectively, the results suggest SDT provides superior overall therapeutic efficacy compared with NIR-PDT, highlighting the potential of this nanoplatform for precision prostate cancer therapy.

cancer biology↗

Effective drug combinations targeting driver KRAS mutations in non-small cell lung cancer

1.Pharmacogenomics is a rapidly growing field with the goal of providing personalized care to every patient. Previously, we developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to screen optimal compounds for any indication/disease by performing analytics on their interactions with large protein libraries. We implemented a comprehensive precision medicine drug discovery pipeline within the CANDO platform to determine which drugs are most likely to be effective against mutant phenotypes of non-small cell lung cancer (NSCLC) based on the supposition that drugs with similar interaction profiles (or signatures) will have similar behavior and therefore show synergistic effects. CANDO predicted that osimertinib, an EGFR inhibitor, is most likely to synergize with four KRAS inhibitors.Validation studies with cellular toxicity assays confirmed that osimertinib in combination with ARS-1620, a KRAS G12C inhibitor, and BAY-293, a pan-KRAS inhibitor, showed a synergistic effect on decreasing cellular proliferation by acting on mutant KRAS. Gene expression studies revealed that MAPK suppression is a key correlate of decreased cellular proliferation following treatment with KRAS inhibitor BAY-293, but not treatment with ARS-1620 or osimertinib. Our precision medicine pipeline may be used to identify compounds capable of synergizing with inhibitors of KRAS G12C, and to assess their likelihood of becoming drugs by understanding their behavior at the proteomic/interactomic scales.

bioinformatics↗