Cancer Biology & Medicine最新文献

Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models. Organoids preserve the complex tissue architecture and cellular diversity of human cancers, enabling more accurate predictions of tumor growth, metastasis, and drug responses. Integration with microfluidic platforms, such as organ-on-a-chip systems, further enhances the ability to model tumor-environment interactions in real-time. Organoids facilitate in-depth exploration of tumor heterogeneity, molecular mechanisms, and the development of personalized treatment strategies when coupled with multi-omics technologies. Organoids provide a platform for investigating tumor-immune cell interactions, which aid in the design and testing of immune-based therapies and vaccines. Taken together, these features position organoids as a transformative tool in advancing cancer research and precision medicine.

Breast cancer (BC) has the highest prevalence among cancers specific to women, and its incidence rates are increasing in many countries. Subtypes of BC, including HER2-positive or triple-negative BC, exhibit differing treatment responses; consequently, demand for personalized therapy is increasing, and relevant precision medicine strategies are under development. Aerobic glycolysis in cancer cells can lead to excessive lactate production, which in turn promotes lactylation and influences tumor cell behavior. Epigenetic alterations and metabolic reprogramming are prominent characteristics of tumors. Because lactate and lactylation are important in cancer, further investigation of the mechanisms underlying lactate metabolism and lactylation, and the development of therapeutic strategies targeting these processes, are topics of increasing interest. This review describes current research on lactate metabolism and lactylation in BC, thus offering new perspectives for advancing treatment and management toward more precise and personalized approaches that will ultimately increase BC survival rates and patient quality of life.

Objective: Gemcitabine combined with nab-paclitaxel therapy (GnP) represents first-line chemotherapy for advanced pancreatic ductal adenocarcinoma (PDAC). However, the efficacy of GnP is diminished due to chemotherapeutic resistance induced by the tumor microenvironment (TME), the underlying mechanisms of which remain poorly understood.

Methods: Clinical data from patients with PDAC who underwent GnP therapy were collected and neutrophil infiltration in tumor tissues was assessed. PDAC cell lines and a mouse model of PDAC were utilized to determine the mechanisms underlying GnP resistance and to focus on tumor-associated neutrophils and neutrophil extracellular traps (NETs).

Results: GnP therapy recruited neutrophils to the TME, which resulted in the formation of NETs that contributed to therapeutic resistance in the PDAC murine model. The NET inhibitor, PAD4, enhanced the efficacy of GnP by suppressing tumor growth. Furthermore, GnP significantly upregulated CXCL8 secretion in GnP-resistant MIA PaCa-2 cells, which was mediated by increased expression of GPRC5A in PDAC cells. Screening of classic NET-derived molecules identified cell-free DNA (cfDNA) as a pleiotropic factor that promoted tumor cell proliferation and migration and thereby contributed to chemotherapeutic resistance. In vivo experiments revealed that the combination of GnP with siGPRC5A or DNase was more effective in reducing tumor growth and prolonging survival in PDAC-bearing mice than either treatment alone.

Conclusions: The GPRC5A-CXCL8-NET-cfDNA axis has a critical role in the development of therapeutic resistance to GnP in PDAC. Targeting this axis may represent a promising strategy for overcoming GnP resistance and thereby enhancing the efficacy of chemotherapy in PDAC.

Objective: Hyper-progression recurrence (HPR) after hepatectomy is a specific recurrence pattern associated with extremely poor prognosis in patients with hepatocellular carcinoma (HCC). This study was aimed at investigating the probable risk factors and establishing comprehensive models for formulating clinical strategies.

Methods: Overall, 16,158 patients with HCC from 8 hospitals were screened, among whom 3,125 patients who underwent R0 resection were included, and divided into development (n = 2,113) and validation (n = 1,012) cohorts. A comprehensive study of HPR predictive models and biological features was conducted.

Results: Among the 3,125 enrolled patients, 506 (16.19%) developed HPR. The influence of HPR on extremely poor prognosis was reflected by recurrence features, adverse effects on systemic and liver function, and limited therapeutic options. Nine variables closely associated with HPR were identified, and incorporated into nomogram and conditional inference tree models, which successfully achieved pre- and post-operative HPR risk stratification and facilitated clinical decision-making. Multi-dimensional verification also confirmed the predictive accuracy of model combinations and their reliability in clinical applications. Furthermore, biological analyses revealed that HCCs with HPR exhibited hyperactive biological processes, inactive metabolism, and immune exhaustion features, together with high MYCN/HMGA2 co-expression, thereby enhancing understanding of the molecular events leading to HPR and providing valuable knowledge for HPR management.

Conclusions: HPR after hepatectomy is associated with extremely poor prognosis and requires substantial attention. We constructed comprehensive predictive models and propose a clinical strategy for guiding HPR prevention and management.

Prostate cancer (PCa) is a leading cause of cancer-related mortality among men. Radiotherapy is the cornerstone of PCa treatment. However, a major limitation of radiotherapy is the development of resistance, which compromises treatment efficacy. Reactive oxygen species (ROS), which are generated by radiation, have a dual role in PCa by inducing DNA damage and apoptosis, while also promoting tumor progression and radioresistance. Elevated ROS levels enhance metabolic reprogramming, activate oncogenic pathways, and influence the tumor microenvironment by modulating immune responses and promoting the epithelial-mesenchymal transition (EMT). Key molecular mechanisms, including the Nrf2/Keap1 signaling axis, Bcl-2 mutations, and Speckle-type POZ protein alterations, contribute to radioresistance by enhancing antioxidant defenses and DNA repair capacity. Additionally, the interplay between hypoxia, androgen receptor variants (AR-Vs), and ferroptosis regulators further influence radiotherapy outcomes. Understanding these resistance mechanisms is crucial for developing targeted strategies to enhance radiosensitivity and improve therapeutic outcomes in PCa patients.

Natural products (NPs) have long been recognized for their therapeutic potential, especially in cancer treatment, due to an ability to interact with multiple cellular pathways. The identification of molecular targets for NPs is a critical step in understanding anticancer mechanisms, with chemical proteomics emerging as a powerful approach. Both label-based and -free proteomic techniques have been utilized to identify these targets, each with their own advantages and limitations. While label-based methods provide high specificity through chemical tagging, the requirement for labeling can be a limitation, potentially altering NP natural properties. Conversely, label-free techniques allow for the detection of NP-protein interactions without structural modification but may struggle with transient interactions or low-abundance targets. Recent advances in artificial intelligence (AI) have further enhanced the field by improving target prediction and streamlining data analysis. AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. The integration of AI with chemical proteomics accelerates target identification and deepens our understanding of the molecular mechanisms underlying the anticancer effects of NPs. This review explores the application of chemical proteomics and AI in the identification of cancer-related targets for NPs, highlighting current challenges and future directions for clinical translation.

Objective: Partitioning defective protein 3 (Par3) has recently been found to have important roles in cancer progression. Interestingly, Par3's functions vary among cancers: both Par3 elevation (in the prostate or liver) and loss (in the breast or lung) have been implicated in cancer metastasis. Although Par3 overexpression has been correlated with diminished survival in renal cell carcinoma (RCC), data indicating the role of Par3 in RCC metastasis are lacking. Given reports of interactions between Par3 and oncoproteins such as Yes-associated protein (YAP)/WW domain-containing transcription regulator 1 (TAZ), we investigated whether Par3-mediated RCC metastasis might be due to activation of the Hippo pathway components YAP and TAZ.

Methods: Par3 levels were analyzed in RCC cell lines and human RCC patient tissues by western blotting and immunohistochemical (IHC) staining, as appropriate. Co-immunoprecipitation (co-IP) and immunofluorescence studies were conducted to examine the interaction between Par3 and YAP. Quantitative PCR and luciferase assays were used to investigate the effects of Par3 on YAP target gene expression and co-transcriptional regulation. PDZ domain deletion mutants of Par3 were generated to elucidate the structural basis of the interaction between Par3 and YAP.

Results: Higher Par3 levels were found in distant-organ-RCC-metastasis-derived ACHN sublines than wild type ACHN cell lines. Par3 levels were also higher in the patient tissue obtained from metastatic sites than in normal kidney and primary RCC tumor tissues. Co-IP and IHC experiments demonstrated that Par3 directly interacted and co-localized with YAP/TAZ proteins. Moreover, Par3 upregulated the transcription of YAP/TAZ downstream target genes and increased the luciferase activity of YAP/TAZ responsive elements. PDZ domain 3 in the PARD3 gene was demonstrated to be particularly important in the interactions between Par3 and YAP. Furthermore, Par3 was found to upregulate intracellular levels of YAP/TAZ molecules and promote nuclear translocation of YAP.

Conclusions: Together, these results indicate the role of Par3 in RCC metastasis, via driving metastatic RCC progression by promoting the YAP/TAZ pathway.

Hepatocellular carcinoma (HCC), a highly aggressive liver cancer, poses a large medical care burden worldwide. The prognosis of patients with HCC is poor, owing to recurrence and metastasis after common treatment methods. Therefore, identifying new targets to eliminate HCC cells is critical for treatment of HCC without recurrence. PANoptosis, a novel inflammatory cell death pathway, has become an intensively investigated area in recent years. The concept of PANoptosis has brought new hope for HCC therapy, given recent evidence implicating this form of programmed cell death in cancer progression, prognosis, and resistance to chemotherapy and immunotherapy. Despite increasing reviews describing the role of PANoptosis in various cancer types, to our knowledge, no systematic review has examined the implications of PANoptosis in HCC. Therefore, we sought to provide the first systematic review of the regulatory mechanisms and therapeutic potential of PANoptosis in HCC. We summarize recent progress in exploration of the role of PANoptosis in HCC, particularly regulation of the HCC tumor microenvironment by PANoptosis. Finally, we highlight the potential of PANoptosis-based diagnostic and therapeutic strategies for HCC.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosis that is driven primarily by oncogenic KRAS mutations present in > 90% of cases. KRAS mutations, particularly the G12D mutation which dominates in PDAC, fuel tumor initiation, progression, and immune evasion, thereby contributing to therapy resistance. Nevertheless, KRAS has long been considered "undruggable" due to its structure. Recent advances have spurred transformative progress in direct KRAS inhibition. While FDA-approved mutation-specific and pan-KRAS inhibitors show limited efficacy in PDAC, emerging agents (MRTX1133 and RMC-9805) have demonstrated preclinical promise. However, resistance remains a critical hurdle and is driven by pathway reactivation, secondary mutations, and metabolic adaptations. Alternative strategies targeting upstream regulators (SHP2 and SOS1) aim to block KRAS activation and associated resistance mechanisms. Preclinical studies have also highlighted synergistic benefits of combining KRAS inhibitors with MEK, PI3K, or CDK4/6 inhibitors, which are now undergoing clinical evaluation. Immunotherapies, including KRAS-targeted vaccines and adoptive T-cell therapies, have further expanded the therapeutic landscape of enhancing KRAS-targeted therapies in PDAC. The molecular basis of KRAS-driven PDAC, current inhibitors, resistance mechanisms, and innovative strategies are discussed herein to address treatment barriers. Opportunities to improve clinical outcomes are underscored in this challenging malignancy by integrating insights from preclinical and clinical research.

Objective: While immunotherapy holds great potential for triple-negative breast cancer (TNBC), the lack of non-invasive biomarkers to identify beneficiaries limits the application.

Methods: Paired baseline, on-treatment, and post-treatment plasma samples were collected from 195 TNBC patients receiving anti-PD-1 immunotherapy in this retrospective study conducted at the Fudan University Shanghai Cancer Center (FUSCC) for sequential high-precision proteomic profiling.

Results: ARG1, NOS3, and CD28 were identified as plasma proteins significantly associated with the response to immunotherapy in neoadjuvant settings or in advanced stages of TNBC. Matched single-cell RNA sequencing data were incorporated to correlate peripheral plasma with the tumor microenvironment. Furthermore, the Plasma Immuno Prediction Score was developed to demonstrate significant predictive power for evaluating the efficacy and prognosis of patients undergoing neoadjuvant immunotherapy.

Conclusions: The results underscore the importance of systemic immunity in the immunotherapy response and support the use of plasma protein profiles as a feasible tool for enhancing personalized management of immunotherapy in breast cancer.