Parallel multiOMIC analysis reveals glutamine deprivation enhances directed differentiation of renal organoids.

Metabolic pathways play a critical role in driving differentiation but remain poorly understood in the development of kidney organoids. In this study, parallel metabolite and transcriptome profiling of differentiating human pluripotent stem cells (hPSCs) to multicellular renal organoids revealed key metabolic drivers of the differentiation process. In the early stage, transitioning from hPSCs to nephron progenitor cells (NPCs), both the glutamine and the alanine-aspartate-glutamate pathways changed significantly, as detected by enrichment and pathway impact analyses.

Differential metabolic profiles by Hispanic ethnicity among male Tucson firefighters.

Introduction: Firefighters face regular exposure to known and probable human carcinogens, such as polycyclic aromatic hydrocarbons (PAHs), benzene, and formaldehyde, leading to an increased risk of various cancers compared to the general population. Hispanic and black firefighters are at increased risk of additional cancers not elevated in non-Hispanic white firefighters, yet biological pathways underlying these differences are unknown.

Objectives: The study objectives were to evaluate differences in the urinary metabolome between Hispanic and non-Hispanic firefighters, pre-and post-fireground exposure.

Tumor mutational burden and survival on immune checkpoint inhibition in >8000 patients across 24 cancer types.

Background: There is uncertainty around clinical applicability of tumor mutational burden (TMB) across cancer types, in part because of inconsistency between TMB measurements from different platforms. The KEYNOTE 158 trial supported United States Food and Drug Administration (FDA) approval of the Foundation Medicine test (FoundationOneCDx) at TMB≥10 mut/Mb as a companion diagnostic (CDx) for single-agent pembrolizumab in second+line. Using a large real-world dataset with validated survival endpoint data, we evaluated clinical validity of TMB measurement by the test in over 8000 patients across 24 cancer types who received single-agent immune checkpoint inhibitor (ICI).

Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors.

We introduce a quantum-classical generative model for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. We apply the method to design, select and synthesize 15 proposed molecules that could notably engage with KRAS for cancer therapy, with two holding promise for future development as inhibitors. This work showcases the potential of quantum computing to generate experimentally validated hits that compare favorably against classical models.