Kai Ni

Background: Prostate cancer is a leading malignancy among males, and conventional chemotherapy is often limited by insufficient tumor selectivity and systemic toxicity. Prostate-specific membrane antigen (PSMA), which is highly expressed on prostate cancer cells, represents a promising target for precision drug delivery. In this study, we developed a folate-modified, PSMA-targeting nanoliposome loaded with docetaxel (DFL) to enhance tumor specificity and therapeutic efficacy. Methods: DFL was prepared using a thin-film hydration–sonication method and characterized through physicochemical analyses. Cellular uptake and cytotoxicity were evaluated in PSMA-high LNCaP cells, with PSMA knockdown used to assess target-dependent internalization. Antitumor efficacy was examined with a microfluidic system and LNCaP xenograft nude mice, and safety was evaluated by measuring hepatic and renal biomarkers and performing histopathological analysis of major organs. Results: DFL demonstrated favorable physicochemical properties and significantly enhanced cellular uptake and cytotoxicity in LNCaP cells relative to control formulations. PSMA knockdown markedly attenuated cellular sensitivity to DFL, confirming PSMA-dependent internalization. A 3D microfluidic perfusion platform further corroborated robust and selective DFL uptake under dynamic flow conditions, thereby strengthening the translational relevance of the targeting effect beyond static cultures. In vivo, DFL substantially inhibited tumor progression in LNCaP xenograft models, reducing both tumor volume and weight by more than 50%. TUNEL assays showed increased apoptosis, and immunohistochemistry revealed reduced Ki-67 expression with concomitant upregulation of Caspase-3. No significant alterations in hepatic or renal biomarkers were observed, and histopathological evaluation demonstrated no treatment-associated lesions in major organs. Conclusions: A folate-modified, PSMA-targeting docetaxel nanoliposome was successfully developed, demonstrating enhanced tumor-specific drug delivery and improved antitumor activity with favorable biocompatibility in preclinical models. DFL represents a promising nanomedicine strategy for the precision chemotherapy of prostate cancer.

Conventional tumor models have historically failed to fully recapitulate the intricate pathophysiological complexity and dynamic microenvironment of human malignancies, significantly limiting their translational potential. The recent convergence of microfluidic technology and 3D bioprinting has ushered in a paradigm shift in oncology research, enabling more physiologically relevant models. This review provides a comprehensive analysis of the limitations inherent in traditional tumor modeling platforms and elaborates on the fundamental principles underlying microfluidics and additive manufacturing. We systematically explore the integrated applications of 3D-bioprinted microfluidic systems across three core domains: engineering pathomimetic tumor models, advancing therapeutic screening platforms, and developing high-sensitivity diagnostic tools. This interdisciplinary synergy allows for unprecedented spatiotemporal control over the tumor microenvironment, precise biochemical gradient formation, and seamless integration of functional biosensors. We further discuss persistent challenges—such as material biocompatibility, fabrication scalability, and the need for standardized validation—and propose future directions, including the development of multi-organ-on-chip systems, stimuli-responsive biomaterials, and AI-enhanced analytical frameworks. The continued integration of 3D bioprinting and microfluidics holds transformative potential for accelerating precision oncology and improving clinical outcomes.

Prostate cancer cells exhibit heightened transcriptional activity to sustain their aggressive phenotype, yet this creates DNA topological stress, leading to RNA: DNA hybrids (R-loops) and DNA damage that compromise genomic stability. LSH, an SNF2-family chromatin remodeler, is frequently dysregulated in cancers and linked to tumor progression, but its mechanistic role in genome maintenance remains unclear. Here, we demonstrate that LSH resolves R-loops in an ATP-dependent manner, mitigating transcription- replication (TR) conflicts in prostate cancer cells. LSH depletion caused R- loop accumulation due to reduced FANCD2 recruitment, exacerbating DNA damage and impairing Rad51 filament formation. Strikingly, LSH deficiency also increased R-loops at promoters of MYC and E2F target genes, stalling RNA polymerase II elongation and disrupting transcriptional programs critical for proliferation. Our findings reveal LSH is a key guardian of genome integrity, resolving R-loops to prevent TR conflicts and maintaining DNA repair fidelity. By linking LSH to R-loop resolution and transcriptional regulation, this study reveals its dual role in prostate cancer pathogenesis— supporting malignant proliferation while safeguarding genomic stability. These insights nominate LSH as a potential therapeutic target to disrupt oncogenic transcription and induce synthetic lethality in prostate cancer.

With the rising global incidence of cancer and the limitations of traditional treatment methods, the integration of three-dimensional (3D) printing technology with drug delivery systems offers a promising solution for precision medicine. 3D printing, with its high flexibility and precise production control, allows for the accurate modulation of drug delivery systems, particularly in terms of targeted delivery and controlled drug release rates, thus significantly enhancing therapeutic efficacy and reducing side effects. This review focuses on the applications of various drug delivery forms, such as microneedle patches, implants, and tablets, in the treatment of cancers including breast cancer, melanoma, osteosarcoma, cervical cancer, colorectal cancer, and prostate cancer. Furthermore, the review explores the synergistic effects of combination therapies, such as photothermal therapy, chemotherapy, and immunotherapy, within 3D-printed drug delivery systems, and assesses their potential in addressing tumor recurrence, drug resistance, and treatment-related side effects. Despite the substantial promise of 3D printing technology in cancer treatment, challenges remain in material selection, process optimization, and production standardization. As technology continues to evolve and multidisciplinary collaborations deepen, 3D printing is expected to play an increasingly significant role in the future of precision medicine and personalized cancer therapy.

Background: Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC). Methods: Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients’ clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers. Results: We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. Conclusions: Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

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Molecular subtyping is expected to enable bladder cancer (BC) precise treatment. However, its clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE) in tumor immune escape and immunotherapy, we aimed to develop a novel TIDE-based subtyping method to facilitate personalized management. Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. We identified 69 TIDE biomarker genes and classified BC samples into three subtypes. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples. This subtyping method was proved to be more efficient than known methods in identifying non-responders to immunotherapy. We also found that combining our TIDE subtypes with known biomarkers can improve the sensitivity and specificity in predicting ICB response. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, the TIDE subtypes are conserved across pan-tumors. In conclusion, our novel TIDE-based strategy is a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized immunotherapy.