Mechanisms controlling cellular and systemic iron homeostasis.

ALK-positive NSCLC patients demonstrate initial responses to ALK tyrosine kinase inhibitor (TKI) treatments, but eventually develop resistance, causing rapid tumor relapse and poor survival rates. Growing evidence suggests that the combination of drug and immune therapies greatly improves patient survival; however, due to the low immunogenicity of the tumors, ALK-positive patients do not respond to currently available immunotherapies. Tumor-associated macrophages (TAMs) play a crucial role in facilitating lung cancer growth by suppressing tumoricidal immune activation and absorbing chemotherapeutics. However, they can also be programmed toward a pro-inflammatory tumor suppressive phenotype, which represents a highly active area of therapy development. Iron loading of TAMs can achieve such reprogramming correlating with an improved prognosis in lung cancer patients. We previously showed that superparamagnetic iron oxide nanoparticles containing core-cross-linked polymer micelles (SPION-CCPMs) target macrophages and stimulate pro-inflammatory activation. Here, we show that SPION-CCPMs stimulate TAMs to secrete reactive nitrogen species and cytokines that exert tumoricidal activity. We further show that SPION-CCPMs reshape the immunosuppressive Eml4-Alk lung tumor microenvironment (TME) toward a cytotoxic profile hallmarked by the recruitment of CD8+ T cells, suggesting a multifactorial benefit of SPION-CCPM application. When intratracheally instilled into lung cancer-bearing mice, SPION-CCPMs delay tumor growth and, after first line therapy with a TKI, halt the regrowth of relapsing tumors. These findings identify SPIONs-CCPMs as an adjuvant therapy, which remodels the TME, resulting in a delay in the appearance of resistant tumors.

Superparamagnetic Iron Oxide Nanoparticles Reprogram the Tumor Microenvironment and Reduce Lung Cancer Regrowth after Crizotinib Treatment.

BACKGROUND
Bladder cancer (BLCA) is a prevalent malignancy worldwide. Anoikis remains a new form of cell death. It is necessary to explore Anoikis-related genes in the prognosis of BLCA.


METHODS
We obtained RNA expression profiles from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases for dimensionality reduction analysis and isolated epithelial cells, T cells and fibroblasts for copy number variation analysis, pseudotime analysis and transcription factor analysis based on R package. We integrated machine-learning algorithms to develop the artificial intelligence-derived prognostic signature (AIDPS).


RESULTS
The performance of AIDPS with clinical indicators was stable and robust in predicting BLCA and showed better performance in every validation dataset compared to other models. Mendelian randomization analysis was conducted. Single nucleotide polymorphism (SNP) sites of rs3100578 (HK2) and rs66467677 (HSP90B1) exhibited significant correlation of bladder problem (not cancer) and bladder cancer, whereasSNP sites of rs3100578 (HK2) and rs947939 (BAD) had correlation between bladder stone and bladder cancer. The immune infiltration analysis of the TCGA-BLCA cohort was calculated via the ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) algorithm which contains stromal, immune and estimate scores. We also found significant differences in the IC50 values of Bortezomib_1191, Docetaxel_1007, Staurosporine_1034 and Rapamycin_1084 among the high- and low-risk groups.


CONCLUSIONS
In conclusion, these findings indicated Anoikis-related prognostic genes in BLCA and constructed an innovative machine-learning model of AIDPS with high prognostic value for BLCA.

Unveiling Anoikis-related genes: A breakthrough in the prognosis of bladder cancer.

Abstract The rise of pyrazinamide (PZA)‐resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA‐resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost‐effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide‐resistant Mycobacterium tuberculosis

Enhancing the sensitivity of radiotherapy in non-small cell lung cancer through nanotechnology-mediated reactive oxygen species generation

Despite a strong rationale for why cancer cells are susceptible to redox-targeting drugs, such drugs often face tumor resistance or dose-limiting toxicity in preclinical and clinical studies. An important reason is the lack of specific biomarkers to better select susceptible cancer entities and stratify patients. Using a large panel of lung cancer cell lines, we identified a set of "antioxidant-capacity" biomarkers (ACB), which were tightly repressed, partly by STAT3 and STAT5A/B in sensitive cells, rendering them susceptible to multiple redox-targeting and ferroptosis-inducing drugs. Contrary to expectation, constitutively low ACB expression was not associated with an increased steady state level of reactive oxygen species (ROS) but a high level of nitric oxide, which is required to sustain high replication rates. Using ACBs, we identified cancer entities with a high percentage of patients with favorable ACB expression pattern, making it likely that more responders to ROS-inducing drugs could be stratified for clinical trials. 

https://doi.org/10.1016/j.redox.2023.102639

Low level of antioxidant capacity biomarkers but not target overexpression predicts vulnerability to ROS-inducing drugs

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Low level of antioxidant capacity biomarkers but not target overexpression predicts vulnerability to ROS-inducing drugs