Table S1. Information on the sequences of shRNAs, sgRNAs, and siRNAs;Table S2. Information of sequences for primers; Table S3. Information of primary antibodies;Figure S1. Expression levels of AFDN in the GEO database; Figure S2. AFDN deficiency promotes CRC cells migration and invasion; Figure S3. Snail knockdown did not reduce CRC cells migration and invasion induced by AFDN deficiency; Figure S4. CXCR4 expression was increased in AFDN-deficient cells.

Colorectal cancer (CRC) represents the third most prevalent malignancy and the second leading cause of cancer mortality worldwide. Metabolic dysregulation is critically involved in CRC pathogenesis. Functional metabolomics aims to translate metabolite biomarkers into mechanistic insights. In this study, comprehensive metabolomic profiling of 1257 participants across discovery and validation cohorts identified β-hydroxybutyrate, carnitine, and acetylcarnitine as potential early diagnostic biomarkers for CRC. This panel demonstrated robust diagnostic performance, achieving 88.79% sensitivity and 95% specificity in an independent validation set of 400 samples. Utilizing an AOM/DSS-induced mouse model under control or high-fat diet conditions, elevated carnitine and acetylcarnitine levels were shown to originate primarily from dietary intake. In vivo and in vitro analyses revealed that these metabolites drive oncogenic metabolic reprogramming via upregulated CPT1A expression, thereby accelerating CRC progression. Immunoprecipitation assays indicated carnitine and acetylcarnitine treatment increased PPARγ while decreasing FXR expression. Conversely, the FXR agonist GW4064 or β-hydroxybutyrate elevated FXR and suppressed PPARγ. Furthermore, β-hydroxybutyrate counteracted the proliferative effects of carnitine and acetylcarnitine by activating FXR and modulating the PPARγ/PGC1α/CPT1A axis. Genetic silencing of CPT1A or β-hydroxybutyrate administration inhibited the PI3K/AKT pathway, restored intestinal barrier function, attenuated inflammation, and significantly suppressed CRC advancement. These findings elucidate a novel mechanism whereby β-hydroxybutyrate attenuates high-fat diet-associated CRC through FXR signaling modulation, revealing promising metabolic strategies for CRC prevention.

Understanding biological processes requires spatiotemporal mapping of proliferative and transcriptional dynamics. Current spatial transcriptomics methods capture only protein-coding transcripts and static snapshots, obscuring non-coding RNAs (ncRNAs) and dynamic events. We developed SPTEdU-seq, integrating spatial total transcriptomics with 5-ethynyl-2'-deoxyuridine tracking to co-profile gene expression and proliferation dynamics. SPTEdU-seq demonstrates ultrahigh sensitivity for coding and non-coding transcripts and for splicing isoforms, with single-molecule probe design eliminating optical imaging. Applied to developing and adult mouse brains, it revealed spatial lncRNA patterns, reconstructed developmental trajectories, and enabled spatiotemporal lineage tracing. In murine ischemic stroke, it mapped regeneration dynamics and identified an Igfbp5+ astrocyte subtype within a pro-repair niche. In mouse and human renal tumors, it uncovered tumor-associated splicing and detected diagnostic 3p loss. By profiling newborn and resident cells in intact microenvironments, it unveiled previously inaccessible interaction networks. SPTEdU-seq thus establishes a powerful framework for investigating cell fate dynamics in regeneration, development, and cancer.

Clear cell renal cell carcinoma (ccRCC) is among the most prevalent malignancies of the urinary system. Patients with advanced ccRCC have poor clinical outcomes. This study aimed to investigate the role of nicotinamide N-methyltransferase (NNMT) in ccRCC. Multiomics analyses revealed aberrant expression of two enzymes in the nicotinamide metabolic pathway, both of which are associated with poor prognosis, with NNMT exhibiting the most pronounced alteration. NNMT modulation per se induces a malignant phenotype, irrespective of substrate or product supplementation. Mechanistically, using western blotting and chromatin immunoprecipitation assays, we demonstrated that NNMT decreases S-adenosylmethionine, thereby reducing histone H3 lysine 9 trimethylation (H3K9me3) at the fibronectin 1 (FN1) promoter and activating FN1 transcription. Exogenous FN1 rescued the migration and invasion in NNMT knockout cells. In clinical specimens, NNMT expression levels were markedly elevated in tumor tissues and correlated with tumor stage. NNMT inhibitor suppressed FN1 expression and tumor progression both in vitro and in vivo. Collectively, our findings establish NNMT as a pivotal epigenetic regulator that drives ccRCC progression through extracellular matrix remodeling, providing novel early-stage diagnostic and therapeutic strategies for ccRCC.

Activation of signal transducer and activator of transcription 3 (STAT3) is implicated in tumor progression and correlates with poor prognosis and reduced survival. In colorectal cancer (CRC), STAT3 activation serves as a key indicator of unfavorable outcomes. However, the scarcity of clinically available STAT3 inhibitors hinders the development of personalized treatment strategies targeting STAT3. Therefore, we aimed to develop a novel STAT3 inhibitor based on the molecular structure of STAT3 and our previously reported STAT3 inhibitor LY17 to inhibit the progression of CRC. The binding of the novel STAT3 inhibitor DB-2B to STAT3 was confirmed by computational docking, surface plasmon resonance, isothermal titration calorimetry, and cellular thermal shift assays. Western blotting and immunofluorescent staining demonstrated that DB-2B specifically inhibited STAT3 activation and nuclear translocation. In vitro studies revealed that DB-2B significantly suppressed proliferation, induced apoptosis, arrested cell cycle progression, and attenuated stemness by inhibiting STAT3 activation and its downstream signaling pathways. In vivo, DB-2B exhibited favorable oral bioavailability and safety, while significantly inhibiting the progression of CRC. Collectively, this study presents DB-2B as a promising small-molecule STAT3 inhibitor for the targeted treatment of CRC.

Despite the clinical success of PDCD1/PD-1 and CD274/PD-L1 immune checkpoint blockade in multiple cancers, its efficacy in colorectal cancer (CRC) remains limited. Here, we report that the combination of the tyrosine kinase inhibitor regorafenib with PDCD1 blockade enhances anti-tumor immunity in CRC, both in clinical observations and preclinical models. Mechanistically, regorafenib acts as a molecular glue, directly promoting the interaction between CD274 and the selective autophagy receptor SQSTM1/p62, leading to SQSTM1-mediated autophagic degradation of CD274 and restoration of T cell-mediated cytotoxicity. In summary, these findings identify a previously unrecognized role of regorafenib in modulating tumor immune evasion and provide a mechanistic rationale for its combination with PDCD1 inhibitors in CRC treatment.Abbreviations: 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; CD274/PD-L1: CD274 molecule; CHX: cycloheximide; co-IP: co-immunoprecipitation; CQ: chloroquine; CRC: colorectal cancer; CTLs: cytotoxic T cells; ECD: extracellular domain; GZMB: granzyme B; ICD: intracellular domain; IF: immunofluorescence; IFNG/IFN-γ: interferon gamma; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; mCRC: metastatic colorectal cancer; mIF: multiplex immunofluorescence; MSS: microsatellite stable; ORRs: objective response rates; PDCD1/PD-1: programmed cell death 1; PDCD1i: PDCD1 inhibitor; pMMR: mismatch repair-proficient; PROTACs: proteolysis-targeting chimeras; SPR: surface plasmon resonance; SQSTM1/p62: sequestosome 1; TKI: multikinase inhibitor; TME: tumor microenvironment; WB: western blot; WT: wild-type.

Colorectal cancer (CRC) typically originates from benign polyps within the colorectum. However, the mechanisms driving this transformation remain poorly understood. In this study, we employed a comprehensive multi-omics approach, incorporating multiplex immunostaining and adeno-associated virus (AAV)-mediated mouse models, to systematically dissect the key drivers of malignant transformation in CRC. Our investigations revealed a dynamic and stage-specific expression pattern of thrombospondin 2 (encoded by the gene THBS2), characterized by significantly downregulated expression during the polyp stage, followed by markedly upregulated expression in malignant CRC tissues compared to healthy colon tissue. Intriguingly, THBS2 expression was primarily localized within a distinct fibroblast subpopulation, with THBS2+ fibroblasts exhibiting a tumor-tropic infiltration pattern. Through a series of analyses, we hypothesized that THBS2+ fibroblasts may play a role in coordinating CRC progression via the THBS2-CD36 and THBS2-SDC1 pathways. Furthermore, depletion of THBS2+ fibroblasts enhanced polyp formation but suppressed tumor formation in a thymidine kinase 1/ganciclovir/azoxymethane/dextran sulfate sodium mouse model. The comprehensive multi-omics atlas and complementary data presented here will advance our understanding of the mechanisms underlying CRC malignant transformation and may provide a potential therapeutic target. © 2026 The Pathological Society of Great Britain and Ireland.

Over the past five decade, the pathological development of colorectal cancer has gone through four stages: histopathological typing, classification of molecular alterations, molecular detection-guided personalized therapy, and liquid biopsy-helped dynamic therapeutics. The standardized pathological examination and diagnosis of routine surgical resection specimens and endoscopic submucosal dissection (ESD)/endoscopic submucosal resection (ESR) specimens are the basis of clinical treatment. For surgical patients, TNM staging is the most valuable indicator for evaluating patient prognosis. In addition to routine evaluation for TNM staging, pathologists should determine vascular and nervous invasions, tumor budding, and poorly differentiated cell clusters. In the past decade, ESD/ESR has been widely carried out. To maximize patient benefit, the close cooperation between physicians and pathologists should be emphasized. Apart from skilled operations, physicians restore and flatten the resected samples to ensure better fixation of specimens. Pathologists then carefully examine specimens and find high-risk pathological parameters, including poor differentiation, submucous invasion depth >= 1000 um, vascular invasion, positive cut-edge and high-grade tumor budding(G2 or G3). Presently, the detection of MSl, Ras, BRAF, PlK3CA, CMET and other mutations, as well as HER2 amplification or mutations and the expressions of ALK, NTRK fusion genes can guide personalized treatment of patients and achieve the best clinical outcomes. Right colon cancer, left colon cancer, and rectal cancer have different mechanisms of carcinogenesis, prognosis, and drug treatment responses. Thus, based on detailed clinical observations and stratified treatment in these three categories, personalized treatment for colorectal cancer will be more defined. Liver metastasis poses a significant chanllenge in the treatment of advanced colorectal cancer, necessitating further exploration to the elucidation and intervention of the molecular mechanisms of metastasis from multiple disciplines. Molecular stratification of patients, circulating tumor DNA (ctDNA), single cell sequencing, spatial omics, organoids and artificial intelligence (AI)-assisted diagnosis applications are current research hotspots. The stratification study of patients with microsatellite instability-high-frequency and the transformation study of microsatellite stable patients based on multi-omics methods are currently urgent research topics that require in-depth research, so as to enable more patients to benefit from immunotherapy while avoiding the toxicity and super-progression associated with treatment. Liquid biopsy mainly using ctDNA detection nowadays can help identify minimal residual disease (MRD) and guide clinical implementation of dynamic treatment, transforming advanced colorectal cancer into a chronic disease. Single cell sequencing and spatial omics offer novel insights into tumor microenvironment and spacetime heterogeneity. Organoid might be served as a living biobank to test new therapeutic assays. The application of Al technology has shown us that more convenient methods can be used to stratify patients and implement personalized treatment. The basis for this stratification is the morphological phenotype changes presented by molecular changes. Therefore, Al-assisted pathological diagnosis and classification will take pathology to a new stage.

Renal cell carcinoma (RCC) is among the most frequently occurring types of cancer, and its metastasis is a major contributor to its elevated mortality. Before the primary tumor metastasizes to secondary or distant organs, it remodels the microenvironment of these sites, creating a pre-metastatic niche (PMN) conducive to the colonization and growth of metastatic tumors. RCC releases a variety of biomolecules that induce angiogenesis, alter vascular permeability, modulate immune cells to create an immunosuppressive microenvironment, affect extracellular matrix remodeling and metabolic reprogramming, and determine the organotropism of metastasis through different signaling pathways. This review summarizes the principal processes and mechanisms underlying the formation of the premetastatic niche in RCC. Additionally, we emphasize the significance and potential of targeting PMNs for the prevention and treatment of tumor metastasis in future therapeutic approaches. Finally, we summarized the currently potential targeted strategies for detecting and treating PMN in RCC and provide a roadmap for further in-depth studies on PMN in RCC.

Inflammatory bowel disease (IBD) is a chronic disorder linked to an increased risk of colorectal cancer (CRC) and is characterized by significant dysbiosis in the gut microbiota. The commensal bacterium Parabacteroides goldsteinii ( P. goldsteinii ) has shown potential in modulating host metabolism and inflammatory responses. In this study, we investigated the probiotic properties of P. goldsteinii and its mechanism of action in IBD models, with a particular focus on bile acid metabolism and diet‐microbiota interactions. Fecal samples from patients with ulcerative colitis ( n = 14), Crohn's disease ( n = 22), and healthy controls ( n = 13) were analyzed to assess P. goldsteinii relative abundance. In dextran sulfate sodium (DSS)‐induced colitis and azoxymethane (AOM)/DSS‐induced CRC mouse models, administration of P. goldsteinii significantly attenuated inflammation and tumorigenesis, particularly under fiber‐free diet conditions. Metabolomic profiling revealed an enrichment of secondary bile acids in P. goldsteinii ‐treated mice, suggesting a link between bile acid metabolism and its anti‐inflammatory effects. Further mechanistic studies using bile salt hydrolase inhibitors and Tgr5 knockout mice confirmed the role of bile acid regulation in mediating the therapeutic benefits of P. goldsteinii . Additionally, we found that dietary factors significantly influenced the colonization and metabolic activity of P. goldsteinii , thereby modulating its probiotic efficacy. This highlights the potential for microbiome‐based therapies tailored to specific dietary contexts in the treatment of IBD. Our findings demonstrate that P. goldsteinii can modulate gut bile acid metabolism to alleviate colitis, making it a promising candidate for probiotic applications in IBD management, with dietary modulation enhancing its therapeutic potential.

BACKGROUND:The development of adrenocortical adenoma (ACA) affects the endocrine homeostasis of the patient and causes various pathophysiological abnormalities. At this stage, the diagnosis of the disease and the distinguishing of adenoma subtypes in patients with ACA remains an unresolved clinical issue. Our study aimed to identify biomarkers for adenoma subtypes and their altered metabolic profiles. We also explored the metabolic differences between non-functional adenomas (NFA) of different sizes. METHODS:In this study, we employed untargeted metabolomic analysis on a discovery set of 246 subjects and a validation set of 275 subjects. Following the construction of a biomarker diagnostic model, we proceeded to validate the model through targeted metabolomic analysis in an independent cohort of 631 participants. RESULTS:In adenoma subtypes, the disturbed pathways in aldosterone-producing adenoma (APA), cortisol-producing adenoma (Cushing's syndrome, CS) and NFA were all mainly focused on the tricarboxylic acid cycle, purine metabolism, and lipid metabolism pathways. In NFA of different sizes, the metabolic profiles did not change significantly as the tumor increased in size. Furthermore, we successfully identified uric acid, isocitric acid, and proline as diagnostic biomarkers for ACA, 4-hydroxyestrone as a reliable marker for NFA, and LysoPC(P-16:0/0:0) for distinguishing APA from CS. CONCLUSIONS:The plasma of patients with ACA shows significant metabolic alterations, with a similar pattern of metabolic disturbances between the different adenoma subtypes. In addition, uric acid, isocitric acid and proline combinations, 4-hydroxyestrone and LysoPC (P-16:0/0:0) could serve as potential biomarkers to complement and improve the diagnosis of ACA.

Large-scale visual-language pre-trained models (VLPMs) have demonstrated exceptional performance in downstream object detection through text prompts for natural scenes. However, their application to zero-shot nuclei detection on histopathology images remains relatively unexplored, mainly due to the significant gap between the characteristics of medical images and the weboriginated text-image pairs used for pre-training. This paper aims to investigate the potential of the object-level VLPM, Grounded Language-Image Pre-training (GLIP), for zero-shot nuclei detection. Specifically, we propose an innovative auto-prompting pipeline, named AttriPrompter, comprising attribute generation, attribute augmentation, and relevance sorting, to avoid subjective manual prompt design. AttriPrompter utilizes VLPMs’ text-to-image alignment to create semantically rich text prompts, which are then fed into GLIP for initial zero-shot nuclei detection. Additionally, we propose a self-trained knowledge distillation framework, where GLIP serves as the teacher with its initial predictions used as pseudo labels, to address the challenges posed by high nuclei density, including missed detections, false positives, and overlapping instances. Our method exhibits remarkable performance in label-free nuclei detection, out-performing all existing unsupervised methods and demonstrating excellent generality. Notably, this work highlights the astonishing potential of VLPMs pre-trained on natural image-text pairs for downstream tasks in the medical field as well. Code will be released at github.com/AttriPrompter.

Inhibiting de novo lipogenesis (DNL) in hepatocytes is a promising strategy for treating metabolic fatty liver diseases. ACLY, a key enzyme in the DNL pathway, has become a therapeutic target for non-alcoholic fatty liver disease (NAFLD). However, its inhibition shows mixed outcomes, depending on interventions and diets. Evidence suggests ACLY inhibition activates the ACSS2-mediated acetate metabolism and the subsequent DNL, though potential mechanisms and possible consequences remain unclear. This study found that targeting hepatic ACLY with AAV8-shRNA failed to improve NAFLD in mice fed a high-fat, high-fructose diet. Instead, it worsened inflammation and liver injury. ACLY inhibition conditionally upregulated DNL enzymes, but consistently activated the ACSS2-acetyl-CoA pathway and suppressed fatty acid oxidation. Further, ACLY inhibition led to polyunsaturated fatty acid accumulation, triggering mitochondrial dysfunction. The resulting ROS redirected carbon flux into acetate, activating the ACSS2-acetyl-CoA pathway, which promoted lipid biosynthesis and exacerbated mitochondrial dysfunction-a vicious cycle that fueled inflammation and liver damage. Dual inhibition of ACLY and ACSS2 broke this cycle by reducing hepatic acetyl-CoA flux, suppressing DNL, enhancing fatty acid oxidation via PPAR-α activation, and improving mitochondrial function. This combined targeting strategy reduced lipid accumulation, alleviated inflammation, and normalized aminotransferase levels, effectively reversing NAFLD progression.

Cancer stem cells (CSCs) typically reside in perivascular niches, but whether endothelial cells of blood vessels influence the stemness of cancer cells remains poorly understood. This study revealed that endothelial cell-specific GLTSCR1 deletion promotes colorectal cancer (CRC) tumorigenesis and metastasis by increasing cancer cell stemness. Mechanistically, knocking down GLTSCR1 induces the transformation of endothelial cells into tip cells by regulating the expression of Neuropilin-1 (NRP1), thereby increasing the direct contact and interaction between endothelial cells and tumour cells. In addition, GLTSCR1 inhibits JAG1 transcription by competing with acetylated p65(Lys-310) to bind to the BRD4 interaction site. Therefore, GLTSCR1 deficiency increases JAG1 expression in endothelial cells. Subsequently, increased JAG1 levels on tip cell membranes bind to Notch on CRC cell membranes, activating the Notch signalling pathway in tumour cells and increasing CRC cell stemness. Taken together, our findings highlight the roles of endothelial cells in CRC development.

Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal cancer and is highly malignant. Despite advances in diagnostics and treatment, the prognosis for ccRCC remains poor. The dual nature (promotion or inhibition) of S100A2 in different cancer types shows the complex involvement of its tumorigenesis, but its effect in ccRCC remains unclear. In this study, we first elucidate the tumor-promoting function of S100A2 in ccRCC by reprogramming glycolysis. Mechanistically, we demonstrate that S100A2 accelerates cancer progression through its interaction with the transcription factor HNF1A, leading to activating GLUT2 transcription. The upregulation of GLUT2 significantly enhances glucose uptake by cancer cells, thereby fueling augmented glucose metabolism and fostering the malignant progression of ccRCC. Collectively, our findings highlight the pivotal role of the S100A2-HNF1A-GLUT2 axis in promoting migration and invasion of ccRCC by amplifying glycolysis and suggest that targeting the S100A2-HNF1A-GLUT2 axis is clinically relevant for the treatment of metastatic ccRCC.

Alternative splicing enables a single precursor mRNA to generate multiple mRNA isoforms, leading to protein variants with different structures and functions. Abnormal alternative splicing is frequently associated with cancer development and progression. Recent studies have revealed a complex and dynamic interplay between epigenetic modifications and alternative splicing. On the one hand, dysregulated epigenetic changes can alter splicing patterns; on the other hand, splicing events can influence epigenetic landscapes. The reversibility of epigenetic modifications makes epigenetic drugs, both approved and investigational, attractive therapeutic options. This review provides a comprehensive overview of the bidirectional relationship between epigenetic regulation and alternative splicing in cancer. It also highlights emerging therapeutic approaches aimed at correcting splicing abnormalities, with a special focus on drug-based strategies. These include epigenetic inhibitors, antisense oligonucleotides (ASOs), small-molecule compounds, CRISPR–Cas9 genome editing, and the SMaRT (splice-switching molecule) technology. By integrating recent advances in research and therapeutic strategies, this review provides novel insights into the molecular mechanisms of cancer and supports the development of more precise and effective therapies targeting aberrant splicing.

Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histopathology images. Despite its success, few works concentrate on the extraction of nucleus-level information, which is essential for pathologic analysis. In this work, we propose a novel nucleus-aware self-supervised pretraining framework for histopathology images. The framework aims to capture the nuclear morphology and distribution information through unpaired image-to-image translation between histopathology images and pseudo mask images. The generation process is modulated by both conditional and stochastic style representations, ensuring the reality and diversity of the generated histopathology images for pretraining. Further, an instance segmentation guided strategy is employed to capture instance-level information. The experiments on 7 datasets show that the proposed pretraining method outperforms supervised ones on Kather classification, multiple instance learning, and 5 dense-prediction tasks with the transfer learning protocol, and yields superior results than other self-supervised approaches on 8 semi-supervised tasks. Our project is publicly available at https://github.com/zhiyuns/UNITPathSSL.

Background: Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of malignant renal cell carcinoma and is well known as a common genitourinary cancer. Stratifying tumors based on heterogeneity is essential for better treatment options. Methods: In this study, consensus clusters were constructed based on gene expression, DNA methylation, and gene mutation data, which were combined with multiple clustering algorithms. After identifying two heterogeneous subtypes, we analyzed the molecular characteristics, immunotherapy response, and drug sensitivity differences of each subtype. And we further integrated bulk data and single-cell RNA sequencing (scRNA-Seq) data to infer the immune cell composition and malignant tumor cell proportion of subtype-related cell subpopulations. Results: Among the two identified consensus subtypes (CS1 and CS2), CS1 was enriched in more inflammation-related and oncogenic pathways than CS2. Simultaneously, CS1 showed a worse prognosis and we found more copy number variations and BAP1 mutations in CS1. Although CS1 had a high immune infiltration score, it exhibited high expression of suppressive immune features. Based on the prediction of immunotherapy and drug sensitivity, we inferred that CS1 may respond poorly to immunotherapy and be less sensitive to targeted drugs. The analysis of bulk data integrated with single-cell data further reflected the high expression of inhibitory immune features in CS1 and the high proportion of malignant tumor cells. And CS2 contained a large number of plasmacytoid B cells, presenting an activated immune microenvironment. Finally, the robustness of our subtypes was successfully validated in four external datasets. Conclusion: In summary, we conducted a comprehensive analysis of multi-omics data with 10 clustering algorithms to reveal the molecular characteristics of KIRC patients and validated the relevant conclusions by single-cell analysis and external data. Our findings discovered new KIRC subtypes and may further guide personalized and precision treatments.