Tumor metabolic reprogramming serves as a fundamental driver of malignancy, fueling cancer cell growth while reshaping the immune landscape through metabolite accumulation. Ferroptosis, an iron-dependent form of regulated cell death, is intricately linked to these metabolic shifts. In the tumor microenvironment, tumor-associated macrophages (TAMs) are pivotal in modulating immune evasion and therapeutic resistance through diverse and context-dependent functional states. Emerging evidence suggests that metabolic alterations can dictate TAM functional plasticity by intersecting with ferroptosis-related pathways. However, the precisely orchestrated mechanisms within the “tumor metabolism-ferroptosis-TAM” axis remain to be fully integrated. This narrative review critically examines current evidence on tumor metabolic reprogramming and its impact on ferroptosis and TAM functional-state remodeling. We specifically focus on the molecular crosstalk through which metabolic and ferroptosis-associated signals may shape macrophage inflammatory, immunoregulatory, tissue-remodeling, and oxidative-stress-associated programs, and discuss potential combinatorial strategies targeting this regulatory axis.
Recent advances in the management of early-stage non-small cell lung cancer (NSCLC), including perioperative immunotherapy and targeted treatments, have significantly improved outcomes. Nevertheless, a considerable proportion of patients relapse after curative-intent surgery, emphasizing the need for biomarkers that can more accurately define recurrence risk and guide individualized treatment. Circulating tumor DNA (ctDNA) has emerged as a promising, non-invasive biomarker for detecting minimal residual disease (MRD), assessing molecular response, and identifying relapse before clinical or radiologic evidence. Across retrospective and prospective studies, ctDNA detection at baseline or after treatment is consistently associated with inferior recurrence-free and overall survival, with postoperative positivity marking patients at the highest risk of relapse, often several months ahead of imaging findings. Evidence from recent pivotal trials further reinforces the prognostic significance of ctDNA dynamics in the perioperative setting. However, translation into clinical practice remains limited. ctDNA detection in early-stage disease is inherently challenging due to its low abundance and technical variability across assays. Moreover, no platform is yet validated or approved for MRD detection in this setting, and the predictive impact of ctDNA-guided treatment adaptation remains to be demonstrated. Ongoing efforts are focused on refining assay sensitivity, standardizing workflows, and conducting prospective interventional trials to establish ctDNA as a clinically actionable biomarker. This review provides an overview of current evidence, emerging technologies, and future directions toward clinical integration of ctDNA in resectable NSCLC.
Chronic inflammation is an established driver of tumorigenesis across multiple organs, including the liver. Yet, the precise mechanisms linking persistent inflammatory signaling to tumorigenesis remain unclear. While classic tumor immunology focuses on immune-mediated tumor eradication, in hepatocellular carcinoma (HCC), growing evidence highlights a paradoxical immune capacity to foster malignant growth. HCC is a major health burden, most often arising in the setting of chronic inflammatory liver disease and cirrhosis. Nonetheless, some HCC cases occur in patients lacking cirrhosis or its traditional triggers, underscoring gaps in our mechanistic understanding. The immune system orchestrates a highly regulated defense network; however, neoplastic cells can subvert this network by sculpting an immune-modulating milieu that mimics protective inflammation while promoting tumor survival and expansion. In HCC, immune influences are bidirectional and stage dependent. As liver disease evolves to cirrhosis, the interplay among the inflammatory response, immune response, cirrhosis-associated immune dysfunction syndrome, and the tumor microenvironment becomes increasingly intricate. This review delineates these overlapping but distinct processes, dissects their individual contributions to HCC pathogenesis, and highlights immune-cell compositional changes across disease stages. We contrast protective immune-inflammatory responses that contain early chronic liver injury with the pro-tumorigenic environment characteristic of cirrhosis. Finally, we propose that mapping stage-specific biomarker signatures could transform inflammatory staging into a precision modality, informing immune-based prevention strategies and guiding individualized systemic therapies for HCC.
Aim: This study aims to identify migrasome-associated long non-coding RNA (lncRNA) signatures for prognostic prediction and to analyze their correlation with tumor microenvironment (TME) features in bladder cancer. Methods: Data including transcriptome, mutation, and clinical profiles were obtained from TCGA. A total of 10 migrasome-related genes were used to screen co-expressed lncRNAs by Pearson correlation. Univariate Cox and LASSO-Cox regression analyses were performed for the selection of essential prognostic lncRNAs to construct a risk score model. Kaplan-Meier survival analysis, ROC curve, and nomogram were applied in model validation. The characteristics of TME were evaluated using ESTIMATE and CIBERSORT. Drug sensitivity was predicted using the oncoPredict algorithm. Results: A total of 808 lncRNAs associated with the migrasome were identified, and seven lncRNAs were selected to construct a prognostic model. The overall survival (OS) of individuals in the high-risk group was significantly shorter than that of those in the low-risk group in training, testing, and full datasets (all P < 0.001), with a 5-year AUC of 0.685. Multivariate analysis showed that the risk score was an independent prognostic factor (HR = 1.119, P < 0.001). Immune infiltration analysis revealed higher M0 macrophages but lower CD8+ T cell infiltration in the high-risk cohort (P < 0.05), while the stromal cell scores were significantly higher in high-risk patients (P < 0.001). High-risk patients had a lower tumor mutational burden (TMB) than low-risk patients (P = 0.00057). Drug sensitivity analysis indicated that nilotinib and KU-55933 may be potential drugs with significant differences in drug sensitivity between the two risk subgroups (P < 10-9). Conclusion: A 7-lncRNA signature serves as an effective predictor of bladder cancer prognosis, demonstrating a correlation with TME immune suppression and stromal activation. This discovery offers novel biomarkers for prognostic evaluation and the development of personalized therapy strategies.
Aim: To elucidate integrin beta 5 (ITGB5)-associated transcriptomic alterations in hepatocellular carcinoma cells and identify key coding and non-coding RNA regulators and their associated signaling pathways. Methods: Whole-transcriptome sequencing was conducted on HepG2 (human hepatocellular carcinoma cell line) cells overexpressing ITGB5. Differential expression analysis was performed, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Candidate transcripts were validated using real-time quantitative polymerase chain reaction (RT-qPCR). Results: ITGB5 overexpression induced extensive transcriptomic alterations. KEGG enrichment highlighted the phospholipase D, vascular endothelial growth factor (VEGF), and ErbB signaling pathways, with significant involvement of the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) cascades. Pathway-level analyses suggested a relative attenuation of PI3K/Akt signaling alongside the preferential engagement of MAPK/ERK-related programs. GO analysis indicated shifts in biological processes, notably the negative regulation of peptidase activity and cell-matrix adhesion. Furthermore, ITGB5 was associated with widespread lncRNA and circRNA regulation; predicted target genes of these non-coding RNAs were enriched in PI3K/Akt signaling, protein processing in the endoplasmic reticulum, and cell cycle regulation. RT-qPCR confirmed the upregulation of key transcripts, including dystroglycan 1 (DAG1; mRNA), small nucleolar RNA host gene 1 (SNHG1; lncRNA), and circFN1 (circRNA), in ITGB5-overexpressing cells. Conclusion: Our findings identify ITGB5 as a regulatory hub in hepatocellular carcinoma (HCC) associated with coding and non-coding RNA regulatory networks, offering insights into potential therapeutic targets.
Aim: Prostate cancer (PRAD) is the second most prevalent male malignancy globally, and advanced castration-resistant PRAD lacks effective targeted therapies. As a G protein-coupled receptor (GPCR), leucine-rich repeat-containing G-protein coupled receptor 6 (LGR6) is poorly understood in PRAD. This study aimed to clarify its biological role, regulatory mechanism, prognostic value, and therapeutic potential via in silico analysis. Methods: Multi-omics data including transcriptome, methylation, mutation, and clinical information from public databases were integrated. Differential expression, survival, and clinical correlation analyses were performed using edgeR, DESeq2, limma, and Kaplan-Meier methods. Epigenetic regulation, mutation landscape, and co-expression networks were examined. Functional enrichment, stemness index correlation, protein structure prediction, molecular docking, and drug repurposing were conducted to explore mechanisms and candidate agents. Results: LGR6 was the most significantly down-regulated GPCR in PRAD, and its low expression predicted poor disease-free survival and advanced clinicopathological features (Gleason score, T stage, N stage). Down-regulation was caused by promoter hypermethylation, not alternative splicing or somatic mutations. LGR6 was closely associated with WNT signaling and cancer stemness, and showed a predicted association with tumor suppressor tumor suppressor protein P53 (TP53). Conserved domains and structural similarity to leucine-rich repeat-containing G-protein coupled receptor 1-3 (LGR1-3) enabled the identification of multiple existing drugs as potential LGR6 agonists. Discussion: LGR6 functions as a putative tumor suppressor in PRAD, and its epigenetic silencing may contribute to disease progression through WNT signaling and the TP53 network. LGR6 is a robust prognostic biomarker and a potential therapeutic target. Drug repurposing of LGR1-3 agonists represents a speculative strategy that requires experimental validation for PRAD treatment. These findings support LGR6 as a novel molecular target for precision therapy of advanced prostate cancer.
Conventional cancer immunotherapy frequently encounters limitations such as suboptimal clinical responses, systemic adverse effects, and acquired immunologic tolerance. Rationally designed smart nanomaterials, engineered to recognize tumor-specific stimuli, target immune cells, and remodel the tumor microenvironment, offer significant potential in overcoming these formidable challenges in metastatic tumors. In this review, we summarize the latest advancements in efficacious therapeutic interventions for the purpose of improving pharmaceutical properties, remodeling tumor immune microenvironment, and achieving combined immunotherapy. Then, we provide a brief overview of the most recent combinational immunotherapy corresponding clinical management, highlighting the clinically validated combinations that elicit systemic antitumor immunity and long-term immunomodulatory memory. Furthermore, we outline key molecular mechanisms and signaling pathways for organ-specific metastasis, and discuss certain preclinical advancements in the realm of smart nanomaterials integrated with existing treatment modalities and immunomodulatory strategies. Additionally, the discussion includes present challenges and future opportunities in designing functional nanomaterials, emphasizing the critical factors related to material design, safety concerns, and regulatory mechanisms. Overall, this review synthesizes preclinical and clinical findings to demonstrate how smart nanomaterials can enhance the therapeutic index through multi-target immunomodulation, and it examines the major challenges and future possibilities of immunotherapy combinations.
Oncolytic virus (OV) therapy constitutes a novel advancement in cancer immunotherapy, with a distinctive dual mechanism of action against gynecological malignancies. These viruses, either genetically engineered or naturally occurring, are designed to selectively replicate within and lyse tumor cells, while eliciting a robust systemic antitumor immune response through the release of tumor-associated antigens and danger signals. This therapeutic strategy shows considerable promise for treating recurrent or treatment-resistant ovarian, cervical, and endometrial cancers, conditions for which conventional therapies are often inadequate. To standardize and enhance its clinical implementation, an expert consensus evaluated and endorsed three primary routes of administration. Intratumoral injection administers the virus directly into accessible tumors, thereby maximizing local viral concentration while minimizing systemic exposure. By contrast, intravenous infusion is useful for addressing disseminated or metastatic disease, as it enables the virus to circulate and target tumor sites throughout the body. Intraperitoneal delivery is particularly significant for gynecologic malignancies, such as ovarian cancer, which predominantly metastasizes within the abdominal cavity. This approach exposes peritoneal surfaces to a high concentration of the therapeutic virus, ensuring direct interaction with both primary and metastatic lesions. By delineating these strategic administration pathways, the consensus provides a practical framework to improve efficacy, inform clinical decision-making, and facilitate the broader integration of OV therapy into the oncological treatment repertoire for gynecological cancers.
Lung cancer remains one of the most prevalent and lethal malignancies worldwide, characterized by a poor prognosis and high mortality rates. Although therapeutic strategies targeting oncogenic signaling cascades, such as receptor tyrosine kinases, have shown promising outcomes by regulating cellular functions such as survival and proliferation, their long-term effectiveness is often limited by mechanisms, including tumor resistance, drug toxicity, and adverse events. These challenges underscore the urgent need to identify new molecular targets and develop alternative therapeutic approaches. One promising avenue lies in the exploration of microRNAs (miRs) and their significance in cancer biology. Among them, miR-218 has drawn significant attention for its tumor-suppressive properties. Multiple experimental studies have emphasized the role of miR-218 as a key regulator of cell signaling pathways critical to cancer progression, including proliferation, invasion, metastasis, and apoptosis. Notably, miR-218 has been investigated as both a diagnostic biomarker and a therapeutic target. Importantly, clinical evidence further supports its relevance, showing an inverse correlation between miR-218 expression levels and tumor aggressiveness, reinforcing its translational significance. This review logically consolidates the functional significance, mechanistic insights, and experimental and clinical findings that emphasize the pivotal role of miR-218 in regulating molecular pathways involved in lung cancer growth.
Aim: The FAM (family with sequence similarity) gene family, implicated in various malignancies, remains underexplored in microsatellite-stable (MSS) colorectal cancer (CRC). MSS CRC represents the majority of CRC cases and lacks reliable prognostic biomarkers as well as effective immunotherapeutic strategies. Methods: Transcriptome profiles and matched clinical data from The Cancer Genome Atlas-COADREAD cohort were used as a training set, while GSE29623 and GSE39582 served as independent validation cohorts. A prognostic signature (FAM gene Family-associated expression scoring (FAMscore)) was constructed based on FAM family genes using Multivariate-Cox regression. Associations between FAMscore, survival outcomes, tumor immune microenvironment features, and predicted drug sensitivity were explored through computational analyses. Results: The FAMscore stratified MSS CRC patients into high-and low-risk groups with significantly different (P <= 0.05) overall survival (OS) in the training cohort and consistent trends in validation datasets. A high FAMscore was associated with an immunosuppressive tumor immune microenvironment, characterized by increased regulatory T cells and M2 macrophages. Exploratory analyses suggested differential predicted sensitivity to selected targeted agents. Conclusions: FAMscore is associated with prognosis and immune landscape features in MSS CRC. These findings are exploratory and hypothesis-generating, and further experimental and prospective validation is required.
Glycans play a crucial role in modulating cellular interactions and disease progression. In the colon, they serve as key mediators between host cells, the microbiome, and the immune system. During tumorigenesis, however, glycans undergo significant alterations that not only influence oncogenic pathways but are also affected by changes in cell signaling, creating a self-perpetuating cycle. These feedback loops drive several cancer hallmarks, including sustained proliferative signaling and immune escape, thereby promoting disease progression. One prominent alteration in colorectal cancer is increased sialylation - the enrichment of sialic acid-containing glycans - which is strongly linked to tumor development, progression, and poor prognosis. Truncated O-glycan structures, such as the Sialyl-Tn (STn) antigen, are rarely presented in healthy colon tissue but are commonly associated with oncogenic transformation and immune evasion. Both commensal and pathogenic bacteria in the colon exploit host sialylated glycans as adhesion sites and nutrient sources. This interaction modulates local immune responses and inflammation, contributing to a complex and dynamic interplay that, when disrupted, accelerates cancer progression. This mini-review discusses the role of sialylated cancer-associated glycans in colorectal cancer, emphasising their involvement in tumor progression, metastasis, and interactions with the gut microbiome. Furthermore, it highlights emerging therapeutic strategies that target these glycans.
Breast cancer is the second largest cause of mortality globally. Early detection of breast cancer may aid in better therapeutic strategies and prolong the lives of the clinical subjects. However, conventional diagnostic methods rely mainly on subjective evaluations of tumor morphology, enhancement type, and anatomic connection to the adjacent tissues. Artificial intelligence (AI) has emerged as a transformative tool in breast cancer diagnosis, particularly within medical imaging. AI-driven methods such as deep learning and radiomics have demonstrated significant improvements in mammography, magnetic resonance imaging, and ultrasound by enhancing detection sensitivity, reducing false positives, and streamlining clinical workflows. Recent advances in convolutional neural networks and hybrid architectures have enabled more accurate tumor classification, lesion segmentation, and risk stratification. While multimodal strategies integrating imaging with clinical or genomic data show promise for personalized care, the primary impact of AI lies in its ability to improve imaging-based diagnostics. This review summarizes current advances in AI for breast cancer imaging, discusses challenges related to generalizability and clinical translation, and highlights future directions for developing clinically robust diagnostic tools. The goal is to advance the development of more accurate and efficient diagnostic tools by integrating multiple imaging modalities and other patient-specific information.
Aim: This study aims to investigate the expression of the Ankyrin Repeat Domain 6 (ANKRD6) gene in Colon Adenocarcinoma (COAD) and its regulatory role in key signaling pathways, evaluating its clinical value as a potential therapeutic target. Methods: To investigate the functional role of ANKRD6 in colon adenocarcinoma (COAD), we systematically analyzed its prognostic relevance, epigenetic regulation, and association with tumor stemness using publicly available TCGA (The Cancer Genome Atlas)-COAD data. Gene set variation analysis (GSVA) was applied to identify signaling pathways potentially modulated by ANKRD6. Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify key genes within the Wnt signaling pathway that are significantly associated with COAD patient survival. Immunohistochemical staining was performed to confirm ANKRD6 protein expression in COAD tissues. To investigate functional consequences, ANKRD6 was knocked down using small interfering RNAs, and subsequent quantitative real-time polymerase chain reaction and Western blot assays were applied to measure alterations in representative Wnt pathway-related genes and proteins. Results: ANKRD6 expression was significantly associated with DNA methylation patterns, RNA modification regulators, and tumor stemness features in COAD. These findings suggest that epigenetic and post-transcriptional mechanisms may underlie the regulatory role of ANKRD6 in COAD pathogenesis. GSVA analysis revealed that ANKRD6 significantly influences and negatively regulates Wnt signaling pathway activity. LASSO regression analysis highlighted 25 Wnt pathway genes relevant to COAD patient survival, with ANKRD6 expression significantly correlated with multiple targets. Furthermore, immunohistochemical staining confirmed that ANKRD6 protein was markedly upregulated in COAD tissues. Upon ANKRD6 knockdown, the messenger RNA levels of WNT7A (Wnt Family Member 7A), JNK (Mitogen-Activated Protein Kinase 8), and RHOA (Ras Homolog Family Member A), as well as WNT7A protein levels, showed a significant decrease in the Wnt signaling pathway. Conclusions: ANKRD6 plays a critical role in the development and progression of COAD by regulating the Wnt signaling pathway. It holds potential as a therapeutic target, warranting further investigation into its specific regulatory mechanisms and clinical applications.
Aim: Lung cancer remains a major global health challenge, and this study presents a censor-aware semi-supervised learning framework (SSL) that integrates clinical and imaging data to improve prognostic modeling and address biases in handling censored data. Methods: We analyzed clinical, positron emission tomography (PET), and computed tomography (CT) data from 199 lung cancer patients from public and local databases, focusing on overall survival time as the primary outcome. Handcrafted (HRF) and Deep Radiomics features were extracted after preprocessing using Visualized & Standardized Environment for Radiomics Analysis (ViSERA) software and were combined with clinical features. Features were reduced using Pearson's correlation coefficient regression (RR) and the F-test for regression (FR), followed by supervised learning (SL) and SSL. In SSL, censored data were pseudo-labeled using the Weibull accelerated failure time (AFT) model to enrich the training data. Seven regressors and three hazard ratio survival analyses (HRSAs) were optimized using five-fold cross-validation, grid search, and holdout test bootstrapping. Results: For PET-HRFs, the SSL approach reduced the mean absolute error by 14.81%, achieving 1.04 years with FR + AdaBoost Regression (ABR) compared to 1.20 years with SL. For clinical features, SSL with RR + ABR reached a mean absolute error of 1.04 years, outperforming SL (1.09 years) with a 4.9% improvement. In HRSA, CT_HRF combined with principal component analysis (PCA) + Component-Wise Gradient Boosting Survival Analysis yielded an external C-index of 0.65 +/- 0.02, effectively distinguishing high-and low-risk groups. Conclusions: The SSL strategy applied to HRFs from PET imaging significantly enhanced survival prediction compared to SL and uncovered complementary biological information that may remain hidden when only limited labeled data are used.
Background: Gastric cancer's heterogeneous nature and subtle symptoms necessitate the identification of reliable diagnostic and prognostic biomarkers. Methods: CHST14 expression in gastric cancer was analyzed using TCGA and GTEx data. Differentially expressed genes were identified and visualized through ROC, survival, volcano plots, and nomograms. Functional analyses included GO and KEGG enrichment, drug sensitivity predictions from the GDSC database, and immune cell infiltration estimation using TIMER algorithms. Results: CHST14 was overexpressed in gastric cancer tissues and correlated with poor overall survival and disease-specific survival, but showed no correlation with progression-free survival. Drug sensitivity analysis revealed CHST14's positive association with chemotherapeutic agents such as SN-38, paclitaxel, and 5-fluorouracil, and negative correlation with others including BEZ235 and doxorubicin. Immune analysis showed CHST14 expression positively associated with infiltration of B cells, CD4+ T cells and CD8+ T cells, macrophages, neutrophils, and dendritic cells. Single-cell RNA sequencing data highlighted CHST14's role in cell-cell interactions, particularly between malignant cells and fibroblasts, and its involvement in tumor-stroma crosstalk. Enrichment analyses linked CHST14 to oncogenic pathways such as epithelial-mesenchymal transition, TNF-alpha signaling, and MAPK regulation. Conclusion: CHST14 is a potential diagnostic and prognostic biomarker for gastric cancer, influencing drug
Osteosarcoma (OS) is a malignant bone tumor characterized by rapid progression and a high propensity to metastasis. Elucidating the mechanisms underlying cell proliferation and metastasis is crucial to improving prognosis. Recent advances in OS research span multiple dimensions, such as genetic mutations, epigenetic alterations, and aberrant signaling pathways. Additionally, the roles of the tumor microenvironment and cancer stem cells are increasingly recognized. Furthermore, traditional Chinese medicine (TCM) has gained significant attention due to its ability to regulate OS through multiple targets and pathways. Specifically, TCM formulations combat tumor progression via holistic mechanisms. These include reinforcing healthy Qi, eliminating pathogenic factors, promoting blood circulation, resolving stasis, and clearing heat toxicity. The monomeric components of TCM exert antitumor effects by suppressing tumor growth, inducing apoptosis, modulating the immune microenvironment, and reversing drug resistance. Acupuncture has shown efficacy in alleviating chemotherapy-induced side effects and improving drug sensitivity in tumor cells. This review summarizes the mechanisms of OS development and the progress in TCM-based interventions, emphasizing the need for further integration of modern scientific technologies to elucidate the specific mechanisms of TCM in targeting OS and advance its clinical application in OS therapy.
Aim: Glioma, the most common primary brain tumor, is known for its poor prognosis, limited treatment success, and high level of aggressiveness. Although cuproptosis-related genes have been linked to outcomes in other cancers, their role in glioma is still not well understood. Methods: By leveraging the Cancer Genome Atlas (TCGA) and additional databases, we conducted Cox regression and Kaplan-Meier analysis to determine the predictive importance of cuproptosis-related genes in individuals with glioma. By utilizing data from Gene Expression Omnibus (GEO) and other relevant databases, we examined how the expression of cuproptosis-associated genes correlates with immune cell infiltration, immunological checkpoint status, pathological stage, and histological grade. Additionally, we analyzed the connection between gene expression linked to cuproptosis and the prognosis in glioma patients. Results: Our newly developed cuproptosis-based glioma predictive model demonstrated promising prediction performance. Additionally, we identified glutaminase (GLS) in glioblastoma as a potential novel diagnostic indicator for glioma patients. Conclusion: GLS holds the potential to provide novel perspectives on cancer management and serve as a valuable diagnostic predictor for glioma patients.
Aim: This study focused on developing a prognostic index model associated with ferroptosis for predicting prostate cancer (PCa) relapse and progression. The aim was to enhance clinical decision making and improve immunotherapy strategies for PCa patients, ultimately leading to better patient outcomes. Methods: The study employed the least absolute shrinkage and selection operator to develop the Ferroptosisrelated gene (FRG) prognostic index model. This model's predictive power was validated across multiple PCa datasets, and its correlation with clinicopathological factors was investigated. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses were conducted to identify associated signaling pathways. Furthermore, the CIBERSORT algorithm was used to assess PCa patient outcomes based on the combination of the FRGs risk index and immune cell infiltration patterns. Results: The FRG index model emerged as an independent predictor of PCa recurrence. It correlated with advanced pathological stages, higher prostate-specific antigen levels, and higher tumor grades. Notably, the FRG index was significantly associated with immune cell infiltration, particularly activated mast cells, which are crucial in PCa recurrence and progression. Furthermore, the response of the FRG index in PCa cell lines implies that doxorubicin may hold clinical efficacy for recurrent PCa. Conclusion: The FRG index established here could serve as a valuable prognostic tool and clinical decision-making aid in PCa. It offers insights into the molecular mechanisms underlying PCa progression and suggests new avenues for immunotherapeutic strategies, potentially leading to improved patient outcomes and a better understanding of PCa biology.
