Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of RCC. C8orf76 is upregulated in multiple cancers and linked to malignant progression, but its role in ccRCC remains unclear. Here, we explored the function and mechanism of C8orf76 in ccRCC using in vitro, in vivo, RNA-sequencing, and bioinformatic analyses. We found that C8orf76 and CALB2 were highly expressed in ccRCC and associated with poor prognosis. C8orf76 knockdown inhibited ccRCC proliferation and migration in vitro and in vivo by inducing G1 cell-cycle arrest and cellular senescence via downregulating CALB2, which could be partially reversed by CALB2 overexpression. Similarly, CALB2 knockdown induces cell-cycle arrest and cellular senescence in ccRCC, thereby inhibiting cell proliferation and migration. These effects are partially reversed by additional CDKN2A knockdown. Therefore, C8orf76 directly binds to the CALB2 promoter to activate its transcription. The C8orf76/CALB 2 axis promotes ccRCC progression by repressing cellular senescence.

The RNA epitranscriptome represents a critical layer of gene regulation, with N4-acetylcytidine (ac4C) emerging as a pivotal modification in cancer biology. Catalyzed exclusively by N-acetyltransferase 10 (NAT10), ac4C decorates a broad spectrum of RNAs, profoundly influencing their stability and translation efficiency. This review synthesizes recent advances illuminating how the NAT10-ac4C axis drives oncogenic processes, including sustained proliferation, metabolic reprogramming, invasion and metastasis, immunosuppression, and therapy resistance by selectively stabilizing mRNAs encoding key oncoproteins. We detail the molecular mechanisms underpinning these roles across diverse malignancies, highlighting context-dependent functions and intricate cross-talk with other signal pathways. Furthermore, we explore the translational promise of this pathway, discussing NAT10 inhibitors and rational combination therapies that resensitize tumors to conventional treatments in preclinical models. Unraveling the full regulatory circuitry of ac4C will not only deepen our understanding of cancer pathogenesis but also pave the way for novel diagnostic and therapeutic strategies in precision oncology.

Acquired resistance to cisplatin remains a major therapeutic challenge in muscle-invasive bladder cancer. Here, we demonstrate for the first time that lactate accumulation induces AARS2-dependent lactylation of the m6A reader YTHDF3, establishing lactylation as a previously unrecognized regulatory layer of this epitranscriptomic factor. YTHDF3 lactylation stabilizes the protein by antagonizing ubiquitin-mediated degradation. Importantly, a lactylation-deficient YTHDF3 mutant fails to confer cisplatin resistance, underscoring the functional importance of this modification. Mechanistically, lactylated YTHDF3 enhances its m6A-dependent recognition and decay of KDM6B RNA. The resulting downregulation of KDM6B suppresses CDKN1A transcription through impaired H3K27me3 demethylation, representing an epigenetic mechanism that weakens the DNA damage response and promotes chemoresistance. Functional assays further demonstrate that YTHDF3 knockdown enhances cisplatin sensitivity in bladder cancer cells and xenograft tumors, whereas enforced expression of KDM6B or CDKN1A phenocopies the cisplatin-sensitizing effect of YTHDF3 knockdown. Collectively, our findings define a lactate-AARS2-YTHDF3-KDM6B-CDKN1A axis that integrates metabolic reprogramming, m6A-dependent epitranscriptomic regulation, and epigenetic chromatin remodeling to drive cisplatin resistance in bladder cancer.

Malignant tumors pose a significant global health challenge. While established screening methods exist, they are largely site-specific, limiting comprehensive prevention. Multi-cancer screening, which detects multiple cancers simultaneously, offers substantial advantages including optimized sample utilization, reduced participant costs, enhanced efficiency, and improved resource allocation. Artificial intelligence (AI) has emerged as a transformative technology, revolutionizing healthcare by analyzing complex biomedical data and enhancing diagnostic accuracy. Integrating AI into multi-cancer screening holds immense potential for advancing early cancer detection. This review provides a comprehensive overview of AI-driven multi-cancer screening. We examine foundational technologies and current applications, including biomarker data and medical imaging data analysis, as well as core AI techniques like machine learning, deep learning, natural language processing, explainable AI and essential preprocessing steps. We assess key technical bottlenecks such as data sparsity, model generalizability, false positives and false negatives, and affordability, alongside solutions like transfer learning, federated learning, and Bayesian optimization. Additionally, we highlight clinical validation, regulatory approval, and ethical considerations for multi-cancer screening. Furthermore, we explore future prospects, envisioning enhanced accuracy and expanded coverage, deeper multi-modal data fusion, personalized and dynamic screening, and intelligent decision-support systems with improved accessibility. We also outline targeted recommendations for developing countries conducting AI-driven multi-cancer screening, building on global best practices while adapting to local realities including those in China. This review offers a forward-looking perspective on how AI will evolve multi-cancer screening into a more personalized, dynamic and accessible cornerstone of cancer prevention.

Urinalysis is one of the predominant tools for clinical testing owing to the abundant composition, sufficient volume, and non-invasive acquisition of urine. As a critical component of routine urinalysis, urine protein testing measures the levels and types of proteins, enabling the early diagnosis of diseases. Traditional methods require three separate steps including strip testing, protein/creatinine ratio measurement, and electrophoresis respectively to achieve qualitative, quantitative, and classification analyses of proteins in urine with long time and cumbersome operations. Herein, this work demonstrates a "three-in-one" protocol to analyze the urine composition by combining multifunctional nanoparticles with machine learning. This work constructs a sensor array to analyze proteinuria by employing nanoparticles with unique optical properties, outstanding catalytic activity, diverse composition, and tunable structure as probes. Different proteins interacted with nanoprobes differently and are classified by this sensor array based on their physicochemical heterogeneities. With the aid of machine learning, the urine composition is precisely detected for the diagnosis of bladder cancer. This protocol enables quantification and classification of 5 proteinuria in 10 min without any tedious pretreatment, showing proimise for the comprehensive analysis of body fluid for early disease diagnosis.

In this study, we report that KIF26B is upregulated in bladder cancer and acts as an independent prognostic factor. Knockdown of kif26b blocks the proliferation, metastasis, and cisplatin resistance of bladder cancer cells. Mechanistically, TCF4 potently stimulates kif26b transcription by directly binding to its promoter. KIF26B activates the Wnt/β-catenin signaling pathway through association with TRAF2 and thus promotes the formation of the TCF4/β-catenin complex. KIF26B promotes the protein stability of TRAF2 by facilitating the OTUB2-mediated de-ubiquitination of TRAF2. Importantly, KIF26B promotes the nuclear translocation of TRAF2 through enhancing its association with IPO11, a process that is dependent on the C-terminal domain of β-catenin. Additionally, phosphorylation of tyrosine 78 in TRAF2 is essential for its binding to KIF26B in response to Wnt3a signaling. Furthermore, a KIF26B/TRAF2/PD-L1 axis is identified in bladder cancer, and combined therapy of anti-B7-H3 antibody with kif26b knockdown yields superior anti-tumor effects.

Histone lactylation modification and RNA m6A modification play important roles in cisplatin resistance of bladder cancer (BCa). Hypoxia drives cisplatin resistance in BCa by analyzing the TCGA-BLCA cohort, where hypoxia signatures predicted poor overall survival. In vitro, hypoxia elevated lactate production via LDHA, inducing H3K18la catalyzed by KAT2B, which activated RBM15 transcription. RBM15 stabilized IGFBP3 mRNA via m6A modification depending on its SPOC domain, increasing IGFBP3 protein. Nuclear translocation of IGFBP3 complexed with p-EGFR/p-DNA-PKcs, enhancing DNA repair and reducing cisplatin-induced damage. Clinically, BCa tissues exhibited elevated LDHA/H3K18la/RBM15/IGFBP3, further amplifying post-cisplatin chemotherapy. Targeting this axis with LDHA inhibitor (stiripentol) and EGFR inhibitor (gefitinib) synergistically reversed cisplatin resistance in vitro and in vivo. This study unveils the “hypoxia–H3K18la–RBM15–IGFBP3” axis as a central driver of cisplatin resistance and proposes dual metabolic–epigenetic inhibition as a therapeutic strategy for refractory BCa.

IntroductionPersistent high-risk human papillomavirus (HR-HPV) infection is crucial in transforming cervical intraepithelial neoplasia (CIN) into cervical cancer (CC) by evading immune responses. Additionally, changes in the tumor immune microenvironment (TIME) are increasingly linked to CIN progression to CC.MethodsIn this study, we used public databases to collect transcriptome data for CIN, CC, and normal cervix, employing LASSO regression to find TIP genes with differential expression. We also used the CIBERSORT algorithm to analyze immune cells in the cervix. ROC curves were plotted to assess tumor-infiltrating immune cells (TICs) and the expression of tumor-infiltrating cell-related genes (TICRGs) for predicting CC efficacy and identifying immune-related genes and cells associated with cervical disease progression for future modeling. We developed a cervical "inflammation-cancer transition" prediction model using the random forest algorithm and assessed its accuracy with internal and external data. Clinical samples from two hospitals were analyzed using multiplexed immunohistochemistry (mIHC) to detect risk factors in various cervical diseases, serving as an independent validation cohort for the model's reliability.ResultsFour genes, ARG2, HSP90AA1, EZH2, ICAM1, and two immune cells, M1 macrophages and activated CD4 memory T cells, were selected as variables, and a predictive model was constructed. The model achieved an AUC of 1 for internal training sets and 0.912 for testing sets. For validation cohort, the AUC was 0.864 for GSE7803 and 0.918 for TCGA/GTEx. For external validation (GSE39001, GSE149763, and GSE138080), the AUC was 0.703, 0.889 and 0.696. At the same time, the mIHC experimental results also effectively validated the stability of the model.DiscussionIn conclusion, the developed model enhances the predictive accuracy for the progression of CIN to CC and offers novel insights for the early diagnosis and screening of CC.

The limited response rate and substantial interindividual variability in immunotherapy outcomes remain major barriers to improving prognosis in patients with bladder cancer (BCa). As central effectors of antitumor immunity, the extent of CD8 + T cell infiltration into tumors is a key determinant of immunotherapy response. Members of the histone deacetylase (HDAC) family play critical roles in modulating tumor immune evasion and sensitivity to immunotherapy, making HDAC inhibitors of clinical interest. A retrospective analysis was performed using data from the IMvigor210 clinical trial and follow-up data from patients with locally advanced BCa who received adjuvant immunotherapy at our center, assessing the association between HDAC1–11 expression and immunotherapy response. RNA sequencing, gene set enrichment analysis (GSEA), chromatin immunoprecipitation PCR (ChIP-PCR), co-immunoprecipitation (Co-IP), mass spectrometry, lysine site mutagenesis, RNA immunoprecipitation, and bioinformatics analysis were employed to outline the HDAC7–BTRC–SRSF7–CCL5 pathway. The immunoregulatory function of HDAC7 was evaluated using CD8 + T cell co-culture assays and tumor models in humanized NOG (HuNOG) mice. Virtual screening, MicroScale Thermophoresis (MST), and HDAC activity assays were conducted to identify potential HDAC7 specific inhibitor. The immunosensitizing effect of Pinocembrin on BCa immunotherapy was validated using a C57BL/6 mouse tumor-bearing model. Among the HDAC family members, only HDAC7 expression was significantly associated with immunotherapy response. HDAC7 was overexpressed in BCa and correlated with poorer prognosis. Functional assays demonstrated that HDAC7 suppresses CD8 + T cell infiltration, thereby reducing sensitivity to PD-1 antibody treatment. Mechanistically, HDAC7 reduced acetylation at lysine 24 of the splicing regulator SRSF7, enhancing BTRC-mediated ubiquitination and degradation of SRSF7, which promoted the processing and expression of CCL5 mRNA-a chemokine essential for CD8 + T cell recruitment. Furthermore, Pinocembrin was identified as a selective HDAC7 inhibitor that restores CD8 + T cell infiltration and improves immunotherapy efficacy in BCa. HDAC7 represents a promising diagnostic and therapeutic target in BCa immunotherapy. Pinocembrin, as a specific HDAC7 inhibitor, holds potential as a combination therapy agent to improve immunotherapy response in BCa.

The most common malignant type of kidney cancer is clear cell renal cell carcinoma (ccRCC). The expression levels of hyaluronan-mediated motility receptor (HMMR) in many tumor types are significantly elevated. HMMR is closely associated with tumor-related progression, treatment resistance, and poor prognosis, and has yet to be fully investigated in terms of its expression patterns and molecular mechanisms of action in ccRCC. Further research is imperative to elucidate these aspects. We used The Cancer Genome Atlas (TCGA) database to preliminarily investigate HMMR expression and function in ccRCC and the data for 19 samples from the NCBI GEO database (GSE207493) for single-cell analysis. We assessed the differential expression level of HMMR between ccRCC cancerous tissues and their matched non-tumor tissues. Subsequently, a series of in vivo and in vitro experiments were designed to elucidate the biological function of HMMR in ccRCC, including Transwell assays, CCK-8 assays, clone formation assays and subcutaneous xenograft experiments in nude mice. Through bioinformatics analysis, we identified potential microRNAs (miRNAs) that may regulate HMMR, as well as the possible signaling pathways involved. Finally, we conducted a series of cellular functional experiments to validate our hypotheses regarding the HMMR axis. HMMR expression was significantly up-regulated in tumor tissues of ccRCC patients, and elevated HMMR expression level showed a strong correlation with ccRCC progression and adverse prognoses of patients. Knocking down HMMR inhibited the proliferative and migratory abilities of ccRCC cells, while its overexpression amplified these oncogenic properties. In nude mice model, reduced HMMR expression inhibited ccRCC tumor proliferation in vivo. Furthermore, overexpression of an upstream transcriptional regulator, miR-9-5p, effectively downregulated HMMR expression and thus impeded ccRCC cells proliferation and migration. HMMR might influence ccRCC growth via the Epithelial-Mesenchymal Transition (EMT) pathway and the Janus Kinase 1/Signal Transducer and Activator of Transcription 1 (JAK1/STAT1) pathway. HMMR is overexpressed in ccRCC, and there is a significant link between high HMMR expression and tumor progression, as well as poor patient prognosis. Specifically, HMMR could be targeted and inhibited by miR-9-5p and might modulate the tumorigenesis and progression of ccRCC through both EMT and JAK1/STAT1 signaling pathway.

N-6-methyladenosine (m(6)A) is the predominant internal RNA modification that programs RNA splicing, stability, translation, and decay through writer, eraser, and reader proteins. Among readers, YTHDF3 has emerged as a pleiotropic and context-dependent effector. It enhances translation, promotes decay, or stabilizes transcripts-often in concert with YTHDF1/2-and its activities are further tuned by liquid-liquid phase separation and post-translational modifications. Physiologically, YTHDF3 regulates stem-cell fate, neuronal plasticity, and antiviral immunity. In cancer, it exerts dual actions by reinforcing oncogenic and metabolic pathways in many settings, yet restraining tumor growth or immune evasion in others. YTHDF3 also shapes responses to targeted therapy, chemotherapy, and immunotherapy. This review synthesizes the biochemical underpinnings, network positioning, and functional spectrum of YTHDF3, and outlines opportunities for context-specific therapeutic intervention within the epitranscriptomic landscape.

Advanced clear cell renal cell carcinoma (ccRCC) treatment primarily involves targeted therapy and immunotherapy; however, many patients exhibit resistance to these modalities. Understanding the mechanisms underlying this resistance is essential for improved outcomes. Herein, we created a pazopanib-resistant 786-O-PR cell line, revealing an active mitophagy pathway and increased Parkin expression in the resistant cells. Knocking down Parkin enhanced the sensitivity of resistant cells to pazopanib, while its overexpression in parental cells induced resistance, which was partially reversed by the mitophagy inhibitor 3-Methyladenine (3-MA). In xenograft models, Parkin knockdown and pazopanib administration inhibited tumorigenesis. We further identified GLI Family Zinc Finger 2 (GLI2) as a potential Parkin regulator, with high expression correlating with advanced tumor stages and poor prognosis. Knocking down GLI2 increased pazopanib sensitivity and diminished mitophagy level in resistant cells; however, its overexpression enhanced resistance and mitophagy, with partial rescue achieved using 3-MA. Furthermore, GLI2 knockdown reduced Parkin mRNA and protein levels. In pazopanib-resistant 786-O-PR cells, GLI2 knockdown and Parkin overexpression partially restored pazopanib resistance, while GLI2 overexpression and Parkin knockdown in parental cells partially restored sensitivity. GLI2's binding sites on the Parkin promoter were identified using JASPAR database analysis and confirmed using chromatin immunoprecipitation followed by quantitative polymerase chain reaction (CHIP-qPCR) and dual-luciferase assays, indicating GLI2's role in Parkin transcription. This study demonstrated that the GLI2-Parkin mitophagy pathway may be a therapeutic target for overcoming targeted therapy resistance in ccRCC.

Piwi-interacting RNAs (piRNAs), while crucial for genomic integrity in germline cells, remain poorly characterized in somatic cancers. This study identifies piR-43452 as a significantly downregulated piRNA in bladder cancer (BCa), with loss of expression correlating clinically with muscle invasion and lymph node metastasis. Through assays in vitro and in vivo, we demonstrate that piR-43452 acts as a potent tumor suppressor, inhibiting BCa cell proliferation, migration, and xenograft growth while promoting apoptosis. Mechanistically, we identified that piR-43452 directly binds the 3'UTR of LRP1 mRNA and recruits the GTSF1/PIWIL4 complex, which enhances target cleavage through GTSF1-dependent conformational activation. This post-transcriptional regulation led to significant LRP1 suppression, subsequently inhibiting proliferation and restoring chemosensitivity. Our findings establish a novel piRNA-guided mechanism for overcoming chemoresistance and suggest that targeting the piR-43452/GTSF1/PIWIL4/LRP1 axis may provide therapeutic benefit in gemcitabine-resistant BCa.

Prostate cancer (PCa) is a prevalent cancer and a major cause of cancer-related deaths in men worldwide. Growing evidence indicates that Staphylococcal nuclease and Tudor domain containing 1 (SND1) is a multifunctional protein extensively involved in transcriptional regulation, RNA maturation, post-transcriptional modifications, and other processes. However, previous studies have rarely investigated the function of SND1 as an RNA-binding protein in PCa tumorigenesis. The Cancer Genome Atlas and NCBI Gene Expression Omnibus (GEO) databases were used to evaluate SND1 expression levels in PCa. We conducted a series of in vitro and in vivo functional experiments to assess the biological functions of SND1, including cell counting kit-8, colony formation, Transwell and wound-healing assays, and animal experiments in nude mice. Chromatin immunoprecipitation, dual-luciferase reporter assay, and DNA pull-down assay were performed to validate the association between the upstream transcription factor and SND1. Based on mass spectrometry, RNA-seq, and RNA immunoprecipitation (RIP)-seq, we identified the downstream targets of SND1- Sestrin 2 (SESN2), which were validated through qRT-PCR, Western blotting, RIP-qPCR, dual-luciferase reporter assay, and RNA pull-down assay. Finally, a series of functional assays and Western blotting analyses confirmed SESN2 as a downstream target of SND1. Our research identified that SND1 was significantly elevated in PCa, and knocking down SND1 repressed PCa multiplication and migration. Mechanistically, sterol regulatory element binding transcription factor 1 (SREBF1) bound to the promoter of the SND1 gene and activated its transcription, which subsequently formed a complex with metadherin (MTDH). This complex is directly bound to and degraded SESN2 mRNA, and disruption of this interaction with C26-A6 inhibited MTDH-SND1-mediated SESN2 degradation. Notably, SESN2 expression was inhibited in PCa and may exert tumor-suppressive effects by affecting the AMPK/mTOR signaling pathway. Rescue experiments indicated that knocking down SND1 or MTDH significantly inhibited PCa proliferation and migration, and knocking down SESN2 partially reversed this effect. Our study reveals SND1 overexpression in PCa, which is transcriptionally activated by SREBF1. Mechanistically, SND1 interacts with MTDH and promotes SESN2 mRNA degradation, modulating PCa progression through the AMPK/mTOR pathway.

R-loops are prevalent three-stranded nucleic acid structures, comprising a DNA-RNA hybrid and a displaced single-stranded DNA, that frequently form during transcription and may be attributed to genomic stability and gene expression regulation. It was recently discovered that RNA modification contributes to maintain the stability of R-loops such as N6-methyladenosine (m6A). Yet, m6A-modified R-loops in regulating gene transcription remains poorly understood. Here, we demonstrated that insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) recognize R-loops in an m6A-dependent way. Consequently, IGF2BPs overexpression leads to increased overall R-loop levels, cell migration inhibition, and cell growth retardation in prostate cancer (PCa) via precluding the binding of DNA methyltransferase 1(DNMT1) to semaphorin 3 F (SEMA3F) promoters. Moreover, the K homology (KH) domains of IGF2BPs are required for their recognition of m6A-containing R-loops and are required for tumor suppressor functions. Overexpression of SEMA3F markedly enhanced docetaxel chemosensitivity in prostate cancer via regulating Hippo pathway. Our findings point to a distinct R-loop resolution pathway mediated by IGF2BPs, emphasizing the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology. The manuscript summarizes the new role of N6-methyladenosine in epigenetic regulation, we introduce the distinct R-loop resolution mediated by IGF2BP proteins in an m6A-dependent way, which probably lead to the growth retardation and docetaxel chemotherapy resistance in prostate cancer. Moreover, our findings first emphasized the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology. In addition, our research provides a novel RBM15/IGF2BPs/DNMT1 trans-omics regulation m6A axis, indicating the new crosstalk between RNA m6A methylation and DNA methylation in prostate cancer.

Several studies have indicated that circular RNAs (circRNAs) play vital roles in the progression of various diseases, including bladder cancer (BCa). However, the underlying mechanisms by which circRNAs drive BCa malignancy remain unclear. In this study, we identified a novel circRNA, circPSMA7 (circbaseID:has_circ_0003456), showing increased expression in BCa cell lines and tissues, by integrating the reported information with circRNA-seq and qRT-PCR. We revealed that circPSMA7 is associated with a higher tumor grade and stage in BCa. M6A modification was identified in circPSMA7, and IGF2BP3 recognized this modification and stabilized circPSMA7, subsequently increasing the circPSMA7 expression. In vitro and in vivo experiments showed that circPSMA7 promoted BCa proliferation and metastasis by regulating the cell cycle and EMT processes. CircPSMA7 acted as a sponge for miR-128-3p, which showed antitumor effects in BCa cell lines, increasing the expression of MAPK1. The tumor proliferation and metastasis suppression induced by silencing circPSMA7 could be partly reversed by miR-128-3p inhibition. Thus, the METTL3/IGF2BP3/circPSMA7/miR-128-3p/MAPK1 axis plays a critical role in BCa progression. Furthermore, circPSMA7 may be a potential diagnostic biomarker and novel therapeutic target for patients with BCa.

Hemodialysis is the primary treatment for end-stage renal disease patients, but its mortality rate is still unacceptably high. Based on multi-modality examination data of 63,499 patients from 333medical centers, we developed a Hemodialysis Early Warning and Intervention Copilot (HEWIC) system. This system assists healthcare professionals in identifying hemodialysis patients at high risk of mortality and provides risk factors to makeintervention decisions jointly with healthcare professionals. On the retrospective cohort, HEWICachieved ROC-AUC scores of 0.82and 0.79 on one-month and three-month mortality probability prediction, respectively. We then conducted a pragmatic clinical trial (RCT, ChiCTR2100052662) to evaluate whether HEWIC could assist healthcare professionals in intervention to reduce the mortality rate of hemodialysis patients in the real world. Involving 9,965 hemodialysis patients (5,216 intervention and 4,749 control) from 58 dialysis centers, the trial indicates that HEWIC’s high-risk patient identification and treatment recommendation can help reduce the three-month mortality rate of hemodialysis patients by 38.3%, with a more pronounced effect in primary hospitals. Patients managed by the intervention group (where professionals assisted by HEWIC) received more types of drug treatment and showed varying degrees of improvement in anemia, blood pressure, blood lipids, electrolytes, and inflammatory conditions, thanthe control group. Furthermore, HEWICdoes not require additional time investment from healthcare professionals, nor does it interfere with their clinical work. This study proves that the AI-copilot system not only can benefit hemodialysis treatment but also enhance the standardization of medical care across different regions. Additionally, it also suggests that the human-AIcollaborationframework has the potential to revolutionize clinical diagnosis and treatment practice for other diseases.