While multidrug-resistant Candida auris poses a global threat to public health, the impact and mechanism of drug resistance on fungal virulence remain unclear. By employing the same-parent-derived fluconazole-resistant C. auris strains, this study utilized in vitro screening and host–pathogen co-culture models. Labile zinc was visualized using the fluorescent probe Zinpyr and Zinquin. Mechanisms identified via dual RNA sequencing were further validated using genetic mutants and pharmacological inhibitors. For in vivo validation, a fly survival model was employed, followed by an infection model in C57BL/6J mice (total n = 84). Mice were challenged with C. auris via lateral tail vein injection and oral gavage. Efficacy was evaluated through daily survival monitoring, fungal burden via colony-forming unit (CFU) counting, histopathological examination of tissue sections, and cytokine level measurement. We revealed that fluconazole-resistant C. auris exhibits enhanced fitness and resistance to macrophage killing under zinc deficiency by mobilizing intracellular zinc. Mechanistically, the inhibition of gene encoding Zn(Ⅱ)2Cys6 transcription factor 4 (ZCF4) contributes to C. auris resistance to macrophage killing by suppressing the phosphoinositide 3-kinase (PI3K)-AKT-mammalian target of rapamycin (mTOR) pathway and downstream matrix metalloproteinase-9 (MMP-9) activity under low-zinc conditions. Furthermore, dietary zinc deficiency promotes the virulence of fluconazole-resistant C. auris. These findings highlight a fitness advantage of fluconazole-resistant C. auris under zinc-deficient conditions through host–fungal interactions, offering a potential nutrient intervention strategy against fungal infection.

Organoids, as a cutting-edge technology in nutritional evaluation, demonstrate research advantages with greater physiological relevance over traditional cell and animal models. These complex 3D models replicate the structures and functions of human organs, having unique applications in assessing nutrient absorption, metabolism, dietary interventions, and the effects of nutritional imbalances. This review highlights the application scenarios and methodologies of various organoid models-such as intestinal, liver, kidney, and brain organoids-in nutritional assessment. Despite challenges like high costs and insufficient standardization, the application scope of organoids is rapidly expanding with ongoing technological advancements. This review summarizes the current research progress and future directions of organoids in nutritional evaluation.

Human microbiomes, considered as a new emerging and enabling cancer hallmark, are increasingly recognized as critical effectors in cancer development and progression. Manipulation of microbiome revitalizing anticancer therapy from natural products shows promise toward improving cancer outcomes. Herein, we summarize our current understanding of the human microbiome-driven molecular mechanisms impacting cancer progression and anticancer therapy. We highlight the potential translational and clinical implications of natural products for cancer prevention and treatment by developing targeted therapeutic strategies as adjuvants for chemotherapy and immunotherapy against tumorigenesis. The challenges and opportunities for future investigations using modulation of the microbiome for cancer treatment are further discussed in this review.

Mass spectrometry (MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Data-independent acquisition (DIA) mode is considered to perform better than data-dependent acquisition (DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft (MiniPDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients. Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases. Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer (CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and MiniPDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.