Patient-derived tumor organoids (PDTOs) represent a significant advancement in cancer research and personalized medicine. These organoids, derived from various cancer types, have shown the ability to retain the genetic and molecular characteristics of the original tumors, allowing for the detailed study of tumor biology and drug responses on an individual basis. The success rates of establishing PDTOs vary widely and are influenced by factors such as cancer type, tissue quality, and media composition. Furthermore, the dynamic nature of organoid cultures may also lead to unique molecular characteristics that deviate from the original tumors, affecting their interpretation in clinical settings without the implementation of rigorous validation and establishment of standardized protocols. Recent studies have supported the correlation between PDTOs and the corresponding patient response. Although these studies involved a small number of patients, they promoted the integration of PDTOs in observational and interventional clinical trials to advance translational cancer therapies.

In this paper, the design, synthesis, and molecular modeling of a new azole-based HO-1 inhibitors was reported, using compound 1 as a lead compound, in which an imidazole moiety is linked to a hydrophobic group by means of an ethanolic spacer. The tested compounds showed a good inhibitor activity and possessed IC₅₀ values in the micromolar range. These results were obtained by targeting the hydrophobic western region. Molecular modeling studies confirmed a consolidated binding mode in which the nitrogen of the imidazolyl moiety coordinated the heme ferrous iron, meanwhile the hydrophobic groups were located in the western region of HO-1 binding pocket. Moreover, the new compounds were screened for in silico ADME-Tox properties to predict drug-like behavior with convincing results. Finally, the in vitro antitumor activity profile of compound 1 was investigated in different cancer cell lines and nanomicellar formulation was synthesized with the aim of improving compound’s 1 water solubility. Finally, compound 1 was tested in melanoma cells in combination with doxorubicin showing interesting synergic activity.

Human papillomavirus (HPV) is a sexually transmitted disease (STD) imposing a considerable clinical and economic burden on public health providers and havi

Breast cancer remains a leading cause of cancer mortality worldwide, underscoring the urgent need for advanced preclinical models that faithfully recapitulate tumor complexity and improve therapeutic prediction. Traditional two-dimensional cell cultures and animal models often fail to capture the heterogeneous and dynamic nature of the disease, limiting their translational relevance. This review addresses a critical gap in the literature by providing a comprehensive and integrated comparison of three contemporary, complementary platforms—patient-derived organoids, zebrafish xenografts, and organ-on-chip systems—within a unified translational framework for breast cancer research. We evaluate each model's capacity to elucidate key signaling pathways, model molecular and genetic alterations, and recapitulate the biology of major breast cancer subtypes. Furthermore, we critically assess their roles in drug screening, personalized treatment prediction, and the study of resistance mechanisms, explicitly distinguishing between early-stage proof-of-concept studies, validated preclinical applications, and emerging clinical predictability. A key contribution of this work is a practical, decision-oriented synthesis, supported by comparative matrices, that guides researchers in model selection based on biological relevance, throughput, cost, and clinical predictability. We also highlight current challenges in reproducibility, scalability, and clinical validation, and discuss how emerging technologies such as CRISPR/Cas9 gene editing, artificial intelligence, and bioprinting are poised to address these limitations. By synthesizing the distinct advantages and applications of each platform, this review aims to accelerate the rational use of these advanced models in mechanistic discovery, drug development, and the advancement of precision oncology for breast cancer.