Circulating prostate-specific antigen (PSA) discriminates poorly in the diagnostic gray zone (3.0-9.99 ng/mL), where ~75% of biopsies yield no clinically significant prostate cancer (PCa). We evaluated whether urinary creatine riboside (CR), a tumor-derived metabolite excreted through the prostatic urethra, complements PSA for gray-zone detection and independently predicts prostate-cancer-specific mortality (PCSM). In the NCI-Maryland PCa Case-Control Study (951 cases, 962 controls; 47.6% African American men; median follow-up 11.5 years), urinary CR was quantified by UPLC-MS/MS. Within the PSA gray zone (n = 668), urinary CR was complementary to PSA, with markedly higher single-marker discrimination than PSA (AUC 0.93, 95% CI 0.88-0.98 vs 0.77, 0.66-0.89) and additive when combined (ΔAUC +0.17, p < 0.001; 91.4% sensitivity at 80% specificity). After adjustment for 11 clinical and sociodemographic covariates, urinary CR independently predicted PCSM complementary to PSA (Fine-Gray SHR 1.72, 1.35-2.19 for CR; 1.35, 1.08-1.68 for PSA; Harrell's C 0.85 for CR + PSA vs 0.77 for PSA alone), with strongest signal in African American men (SHR 2.43, 1.57-3.75 for CR). We conclude that urinary CR is a candidate non-invasive biomarker complementary to PSA - improving gray-zone triage and predicting PCSM; prospective validation in biopsy-referred cohorts is warranted. ### Competing Interest Statement The authors have declared no competing interest. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Institutional Review Board of the National Cancer Institute, National Institutes of Health gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. Individual-level data from the NCI-Maryland Prostate Cancer Case-Control Study are not publicly deposited due to participant privacy protections governing this NIH intramural research cohort. Intramural Research Program of the U.S. National Institutes of Health (NIH), National Cancer Institute, Center for Cancer Research, grant ZIA BC 011492 National Center for Advancing Translational Sciences, ZIC TR000547

Cancer development is shaped by host-microbe interactions, including viral infections. While several viruses are established oncogenic drivers, their potential protective roles in cancer remain unclear. Here we identify a dominant antibody response to CE1, a consensus epitope of enterovirus and rhinovirus, that is associated with reduced hepatocellular carcinoma (HCC) incidence and mortality. Anti-CE1 antibodies selectively recognize HCC cells and mediate anti-tumor activity through NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC). Mechanistically, anti-CE1 antibodies cross-react with aspartate β-hydroxylase (ASPH), with CE1-ASPH sequence homology underpinning tumor recognition and cytotoxicity. Clinically, ASPH is aberrantly upregulated in HCC and correlates with inferred NK cell-associated ADCC activity and improved survival in CE1-seropositive patients. Collectively, these findings reveal a mechanism by which antiviral humoral immunity confers cancer protection through molecular mimicry and highlight anti-CE1 immunity as a potential therapeutic strategy in HCC.

Zika virus (ZIKV) infection is known to cause microcephaly in newborns, and its outbreaks have previously emerged as a global public health crisis. The lack of a preventive vaccine or specific antiviral drugs underscores the urgency of investigating the detailed mechanisms of pathogenesis. We identified that interferon-induced protein 44 (IFI44) is significantly upregulated following ZIKV infection, but its role in ZIKV pathogenesis remains unclear. Using A549 and 2FTGH cells, we established ZIKV-infected cell models and employed quantitative real-time PCR and Western blotting to demonstrate that IFI44 overexpression suppressed ZIKV replication, whereas IFI44 knockdown via specific small interfering RNA promoted viral replication. Mechanistically, IFI44 inhibited early-stage ZIKV infection, including viral attachment and entry into host cells. Further analyses revealed that IFI44 promoted IFN-β expression, triggering activation of the Jak/STAT signaling pathway-as evidenced by increased phosphorylated STAT1 (p-STAT1), enhanced interferon-stimulated response element activity, and upregulated the downstream interferon-stimulated genes (MX1, OAS2, IFIT2, and RIG-I). Collectively, these findings demonstrate that ZIKV infection induced IFI44 expression, which acts as a positive feedback regulator of the Jak/STAT pathway to restrict viral replication. Our results establish IFI44 as a key component of the host antiviral response against ZIKV, highlighting its potential as a therapeutic target.

e17149 Background: Distinguishing clinically significant prostate cancer from indolent disease remains a major challenge in prostate cancer diagnosis and contributes to unnecessary biopsy and overtreatment. Prostate-specific antigen (PSA) testing, while widely used, has limited specificity for clinically significant disease and provides limited information for individualized risk assessment. Creatine riboside is a tumor-associated urinary metabolite previously linked to aggressive prostate cancer biology. We evaluated whether urinary creatine riboside could provide clinically interpretable risk stratification for clinically significant prostate cancer using a likelihood-ratio–based framework designed to complement existing diagnostic approaches and inform decision-making beyond PSA alone. Methods: Urinary creatine riboside concentrations were quantified using targeted liquid chromatography–mass spectrometry in men undergoing evaluation for prostate cancer. Clinically significant prostate cancer was defined according to standard pathological criteria. Risk strata were prespecified using percentile thresholds derived from the empirical distribution of urinary creatine riboside concentrations. Diagnostic performance across strata was evaluated using sensitivity, specificity, and positive likelihood ratios (LR+), interpreted according to established clinical benchmarks to define low-risk, intermediate-risk, and high-risk categories. Results: Urinary creatine riboside concentrations were higher among men with clinically significant prostate cancer than among those without. Diagnostic discrimination increased progressively across ascending percentile thresholds. Lower-risk strata were associated with minimal changes in post-test probability (LR+ approximately 1–2), consistent with low-risk classification. Intermediate-risk strata demonstrated moderate enrichment of risk (LR+ approximately 2–5). At higher percentile thresholds, urinary creatine riboside demonstrated strong rule-in performance, with LR+ values exceeding 10 and reaching greater than 30 at the highest thresholds. This likelihood-ratio–based framework enabled clear separation of patients into clinically actionable low-risk, intermediate-risk, and high-risk categories using a single noninvasive biomarker. Conclusions: Urinary creatine riboside enables robust, likelihood-ratio–based risk stratification for clinically significant prostate cancer, providing clinically interpretable decision support beyond PSA. This approach has the potential to reduce unnecessary biopsies while improving identification of aggressive disease and advancing precision prostate cancer diagnostics.

Background:Hepatocellular carcinoma (HCC) is characterised by significant racial disparities in incidence and outcomes, yet whether these reflect distinct tumour biology or differential distribution of molecular subtypes among immunotherapy patients remains unclear. Methods:We characterised molecular heterogeneity among 46 patients with HCC of differing background population from the NCI-CLARITY cohort receiving immune checkpoint inhibitor therapy, using transcriptomic and genomic profiling, with validation across multiple independent cohorts. Results:Differential expression analysis comparing African American versus non-African American patients identified 126 genes, of which 55 demonstrated tumour-specific expression across independent validation cohorts with paired tumour-normal samples. Consensus clustering revealed two molecular subtypes with no significant race association, indicating these clusters capture tumour-intrinsic biology rather than ancestry. The genomic landscape showed minimal differences between subtypes. A prognostic signature derived from these expression profiles demonstrated significant risk stratification in the NCI-CLARITY cohort and TCGA-LIHC, but not in Asian cohorts, suggesting population-specific applicability. Immune deconvolution revealed that the two subtypes represent distinct immune microenvironments: one subtype exhibited markedly elevated plasma cell infiltration with strong plasma cell-CD8+T cell correlation suggesting coordinated adaptive immunity, along with elevated tertiary lymphoid structure signatures. The other subtype showed regulatory T cell-macrophage correlation and enrichment for immune-excluded phenotypes. The immune-enriched subtype trended towards higher immunotherapy response rates. Conclusions:Molecular heterogeneity in HCC reveals distinct tumour-immune ecosystems that transcend racial classification. Tumour immune heterogeneity in HCC reflects distinct molecular patterns, with immune hot tumours characterised by elevated tertiary lymphoid structure signatures and enriched plasma cell and CD8+T cells. These patterns may serve as prognostic biomarkers for immunotherapy patient stratification and demonstrate the value of diverse cohort representation in identifying clinically relevant therapeutic targets.

Small Cell Lung Cancer (SCLC) is a highly aggressive malignancy, accounting for approximately 15% of all lung cancer cases. Characterized by low immunogenicity, SCLC may utilize epigenetic mechanisms to evade immune detection. Here, we demonstrate that entinostat, a class I histone deacetylase inhibitor (HDACi) upregulates immune-related genes in human SCLC cells. In vivo, we confirmed entinostat treatment increased expression of immunecheckpoint ligands and antigen presentation machinery in Myc-driven tumors in a Rb1/Trp53/MycT58A (RPM) SCLC mouse model, while shifting tumors from a neuroendocrine(NE)-high to a NE-low phenotype. Notably, combining entinostat with anti-PD-1 immunotherapy significantly enhances T-cell infiltration, suppresses tumor growth, and prolongs survival in RPM allograft models. These findings underscore the potential of entinostat to reprogram the immunological landscape and NE status of SCLC, enhance immune checkpoint blockade efficacy, and improve therapeutic outcomes.

Abstract Background Building on evidence linking urinary glyphosate to chronic liver disease (CLD) and hepatocellular carcinoma (HCC), we developed urinary pesticide profiling integrated with machine learning risk prediction (MLRP) to stratify risk in high-exposure populations.Methods We conducted a case-control study within the Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC; 2011-2016; n=593): 228 CLD, 116 HCC, and 249 controls. Eight urinary pesticides were quantified by LC-MS/MS (pendimethalin, oxadiazon, metsulfuron-methyl, butachlor, 2,4-dichlorophenoxyacetic acid [2,4-D], cypermethrin, flocoumafen, bromadiolone). A composite Pesticide Load Score (PLS), with and without glyphosate, estimated burden. Two predictive models were developed: a logistic-regression Pesticide-Informed Liver Cancer Risk Score (PILCRS) and an Extreme Gradient Boosting (XGBoost) classifier that incorporated age, sex, alcohol use, occupation, and PLS. Internal validity used 1,000 bootstrap resamples with optimism-corrected calibration.Findings Predicted CLD probability increased from 30% in the lowest PLS quartile to over 70% in the highest, and HCC from 10% to 40% (p<0ꞏ0001). Relative estimates were consistent; the highest versus lowest quartile yielded odds ratios of 2ꞏ84 (95% CI 1ꞏ66-4ꞏ91) for CLD and 4ꞏ76 (2ꞏ30- 10ꞏ29) for HCC. Cypermethrin remained independently associated. After optimism correction, both models demonstrated strong discrimination and calibration.Interpretation This framework establishes a scalable, exposure-informed tool for liver disease prediction. Findings underscore pesticide burden as a modifiable risk factor and align with Sustainable Development Goal 3ꞏ9 and WHO-FAO priorities in low- and middle-income countries (LMICs). External validation is essential. Citation Format: Daxeshkumar P. Patel, Christopher Loffredo, Majda Haznadar, Mohammed Khan, Amelia Parker, Benjarath Pupacdi, Siritida Rabibhadana, Panida Navasumrit, Nirush Lertprasertsuke, Anon Chotirosniramit, Chawalit Pairojkul, Vor Luvira, Ake Pugkhem, Wattana Sukeepaisarnjaroen, Teerapat Ungtrakul, Thaniya Sricharunrat, Kannika Phornphutkul, Frank J. Gonzalez, Anuradha Budhu, Chulabhorn Mahidol, Xin Wei Wang, Mathuros Ruchirawat, Curtis C. Harris, TIGER-LC Consortium.. Urinary pesticide biomarkers and liver disease risk in Thailand: A machine-learning-based risk-prediction model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2443.

Introduction Few machine learning (ML) studies have investigated the prediction of distant metastasis in patients with renal cell carcinoma (RCC). This retrospective study aimed to develop and validate predictive models based on ML algorithms for RCC patients with distant metastasis. Methods We extracted RCC data from the SEER database between 2004 and 2015 (n=192,912) and from the Chinese National Cancer Center (CNCC) database between 2010 and 2020 (n=3,034). Seven different algorithms were applied to predict distant metastasis in RCC. Fivefold cross-validation was employed for model construction. The data were analyzed by using Python based on incomplete data, complete data, upsampling data and downsampling data. Results After data cleaning and screening, 121,741 cases from the SEER dataset and 2803 cases from the CNCC external test set were retained. For incomplete data, the neural network model [area under the curve (AUC) 95% confidence interval (CI) of the external data: 0.7467±0.0573] achieved the highest accuracy. For the complete data, the support vector machine (SVM) model achieved the highest accuracy, with an AUC 95% CI of 0.8221±0.0485. The disparity between positive and negative samples significantly varied across the different datasets. Upsampling and downsampling analyses were also conducted. For the upsampling data, the extreme gradient boosting (XGBoost) model demonstrated the highest accuracy, with an AUC 95% CI for the external data of 0.8162±0.0558. For the downsampling data, the SVM model achieved the highest accuracy, with an AUC 95% CI of 0.8274±0.0546 for the external data. Conclusions Our study revealed that ML algorithms can effectively predict distant metastasis in patients with RCC. ML models exhibit favorable application prospects in clinical practice.

Lifelong microbial exposure progressively shapes antiviral antibody repertoires, yet whether their global organization follows distinct trajectories during physiological ageing and cancer remains unknown. Here, we used high-throughput VirScan serological profiling to compare antiviral antibody repertoires from healthy adult women, exceptionally healthy elderly women and patients with breast cancer, aiming to distinguish physiological immune remodeling from tumor-associated immune reorganization. Physiological ageing was characterized by a coordinated expansion of repertoire breadth and microbial richness, reflecting progressive diversification of antiviral immune memory accumulated throughout life. In contrast, breast cancer was not associated with comparable repertoire expansion but with increased antibody reactivity and selective redistribution of pre-existing antiviral responses. Although only a limited number of peptide-specific differences distinguished breast cancer from age-matched controls, these converged into coordinated microbial signatures involving multiple viral species, predominantly members of the Herpesviridae family. Global repertoire analyses further demonstrated that ageing and breast cancer are associated with distinct patterns of serological organization rather than discrete antiviral signatures, indicating alternative modes of adaptive immune remodeling. Together, these findings identify lifelong antiviral antibody repertoires as systems-level descriptors of immune organization and show that physiological ageing and breast cancer follow distinct trajectories of adaptive immune remodeling. Our study provides a framework for interpreting large-scale serological repertoires as integrated biomarkers of systemic immune state rather than collections of independent pathogen-specific antibody responses.

The connections between viruses and cancer have historically been studied in the context of viral oncogenesis. For decades, tumour virology has focused on oncogenic viruses such as hepatitis B virus, hepatitis C virus, human papillomavirus, Epstein-Barr virus, human T cell leukaemia virus type 1, Kaposi sarcoma-associated herpesvirus and Merkel cell polyomavirus, elucidating their oncogenic mechanisms, which include mutagenesis, chronic inflammation and immune evasion. However, the human virome is vast and complex, and this oncogenesis-centred view has overshadowed the possibility that certain viral exposures enhance antitumour immunity. Through millions of years of coevolution with animal hosts, the virome, consisting of diverse bacteriophages and eukaryotic viruses, including endogenous retroviruses, appear to have evolved strategies for coexistence that shape immune development and potentiate host surveillance pathways capable of recognizing and eliminating cancer cells. Non-oncogenic viruses can prime innate and adaptive immune responses, mimic tumour antigens and modulate the expression of immune checkpoints, as exemplified by the association of the enterovirus and rhinovirus CE1 epitope with protective liver cancer immunity. Moreover, endogenous retroviruses, naturally occurring oncolytic viruses and microbiome-associated phages may act as allies in cancer control. This Review explores the emerging evidence for viral anticancer immunity, its underlying mechanisms, and implications for a virome-guided framework for cancer prevention including new approaches to risk assessment, immune-based therapeutics and applications in low-resource settings.

Abstract Tumor spatial organization critically shapes disease progression and therapeutic response, yet remains poorly defined. Intrahepatic cholangiocarcinoma (iCCA), a rare and aggressive liver malignancy with extensive stromal and immune remodeling, provides a compelling model to study tumor architecture. We generated a single-cell spatial atlas of 1 million cells from 131 iCCA patients using 53-plex spatial proteomics. To systemically characterize tumor spatial organization, we developed a graph-based deep learning framework to define cell type-centric interaction networks, identifying 41 distinct multicellular spatial patterns. Integration of these networks revealed higher-order tumor- and immune-enriched microenvironments associated with patient outcomes. Notably, neutrophil-associated tumor-enriched and tumor-desert microenvironments delineated patient groups with opposing clinical outcomes and distinct neutrophil states. These findings were validated by single-cell spatial transcriptomic profiling of 6 million cells from 162 iCCA patients. Together, this study defines the spatial architecture of iCCA and provides a comprehensive resource for exploring tumor spatial organization.

Anti-cancer drug resistance driven by tumor-intrinsic and tumor microenvironment (TME) derived factors underpins cancer therapy efficacy. While the gold-standard tissue biopsies are limited by invasiveness, spatiotemporal heterogeneity, and poor repeatability, and thereby failing on continuous therapeutic monitoring, liquid biopsy functions as the counterpart to assist tumor-informed biomolecule detection in peripheral blood and other biofluids, enables real-time non-invasive tracking of molecular alterations in situ, converting drug resistance monitoring from a post-hoc clinical event into a predictable and actionable molecular signal. This has become a core technology for precision oncology. This review systematically summarizes the latest advances in detection technologies for key liquid biopsy-based biomarkers, elaborating their technical principles, clinical utility, and limitations, and compares the characteristics of diverse biofluid samples in drug resistance-relevant research. It also details the translational applications of these biomarkers in monitoring drug resistance across major malignancies, including resistance mutation detection, clonal evolution tracking, minimal residual disease (MDR) assessment, and adaptive therapy guidance. More importantly, this review addresses critical clinical translation challenges, including pre-analytical standardization, sensitivity-specificity trade-offs, multi-biomarker data interpretability, and outlines future development directions stressing the needs of multi-modalmodule based detection, technological standardization, translational research integration, personalized liquid biopsy panels, AI-assisted data mining, and novel technical direction such as Proximity Barcoding Assay for single-exosome profiling. This work provides a comprehensive mechanistic and technical framework for liquid biopsy-guided monitoring of anti-cancer drug resistance, highlighting its potential to enable early detection of drug resistance and timely treatment adjustments, thereby advancing precision cancer therapy.

Clinical and laboratory findings are presented from a 64-year-old female with myelodysplastic syndrome and increased blasts-2 (MDS-IB2) from Phase I/II trial evaluating the anti-IL8 antibody, BMS-986253, in combination with oral decitabine/cedazuridine (NCT05148234). Each 28-day cycle included BMS-986253 1200 mg IV on Day 1 and 15, and oral decitabine/cedazuridine (35 mg/100 mg) on Days 2-7. The patient received 2.5 cycles. Treatment was discontinued on Cycle 3 Day 8 after development of jaw osteonecrosis, deemed unlikely to be treatment related. Despite presenting with high-risk disease, the patient achieved stable disease. Serial bone marrow assessments revealed decreased granulocytes, increased lymphocytes, and reduced CD45 + CD33 + HLA-DR- and CD117 + HLA-DR- cells. Bone marrow plasma multiplex cytokine analysis demonstrated increased inflammatory and immune surveillance proteins. Optical genome mapping identified ETS-related gene, ERG, somatic duplication with post-treatment decreased variant allele frequency. Post-treatment molecular changes with clinical disease stability, suggest IL-8 pathway inhibition biological activity after even short duration.

Abstract A viral exposure signature (VES) has been previously described predicting the development of Hepatocellular carcinoma (HCC) in at-risk patients. This has been achieved by a serological profiling of the viral infection history using a synthetic human virome including >100k epitopes (VirScan). In the present study we applied the same VirScan strategy to identify a differential serum binding pattern (DSBP) for classifying patients of different cancer types from healthy individuals. In particular, the healthy group included both age-matched (ADULTS) as well as elderly (ELDERS) individuals, the latter counting also nonagenarians and centenarians. The class comparison performed with serological data show DSBPs supporting class predictions, as confirmed by the receiver operating characteristic (ROC) curve analysis. Antibody responses supporting the class predictions are specific to peptides from persistent herpesviruses, acute-infecting viruses and, consistently in all comparisons, human respiratory syncytial virus (HRSV). Strikingly, the DSB of the ELDERS vs. CANCER comparison is characterized by higher titers in the healthy subjects; on the contrary, the DSB of the ADULTS vs. CANCER comparison is characterized by lower titers in the healthy subjects. Overall, the results show a differential serological binding pattern predicting healthy individuals (ADULTS or ELDERS) from patients with different types of cancer. Such results provide the first evidence suggesting a close link between anti-microbial immunity and cancer development. They may be of the highest relevance in terms of predictive, diagnostic and/or prognostic impact in oncology.

BACKGROUND:Activated hepatic stellate cells (HSCs) induce alternative (M2) polarization of macrophages and contribute to the progression of fibrosis and hepatocellular carcinoma (HCC). However, the effects of small extracellular vesicles released by HSCs (HSC-sEVs) during activation remain largely unknown. METHODS:The aim of this study was to investigate the role of extracellular vesicles released by HSCs (HSC-sEVs) at different stages of activation in macrophage polarization. The effects of sEVs from short-term activated and long-term activated HSCs on liver macrophages was studied. Small RNA sequencing analyses were performed to obtain differential miRNAs transported by the short-term and long-term activated HSC- sEVs. The in vivo effects of short-term activated HSC-sEV-specific miRNA on liver macrophage and liver fibrosis were confirmed in a CCl4-induced liver injury mouse model. To study the tumor suppressive effects of the macrophages educated by short-term activated HSC-sEV-specific miRNA, human hepatoma cells were mixed and subcutaneously cotransplanted with miR-99a-5p mimic-pretreated macrophages. RESULTS:We found that consistent with activated HSCs, long-term activated HSC-sEVs (14dHSC-sEVs) induce bone marrow-derived monocytes (MOs) toward an M2 phenotype, but short-term activated HSC-sEVs (3dHSC-sEVs) induce the resident macrophages (Kupffer cells, KCs) toward a classically activated (M1) phenotype. We identified five 3dHSC-sEV-specific miRNAs, including miR-99a-5p. In vitro and in vivo experiments support that miR-99a-5p negatively regulates alternative polarization of macrophages, decreases collagen deposition in chronic liver injury model, and suppresses the progression of hepatoma in a xenograft model partially by targeting CD93. CONCLUSION:Collectively, our work reveals an unexpected proinflammatory role of 3dHSC-sEVs, preliminarily explores the underlying mechanism, and evaluates the therapeutic potential of 3dHSC-sEV-specific miR-99a-5p for liver fibrosis and tumorigenesis.

Non-alcoholic fatty liver disease (NAFLD) is a widespread chronic liver disorder, affecting nearly a quarter of the global population. It progresses from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The gut-liver axis is crucial in NAFLD progression, driven by intestinal barrier dysfunction, microbial translocation, and immune dysregulation. Neutrophil extracellular traps (NETs)-web-like structures of DNA, histones, and inflammatory proteins-promote chronic inflammation and liver injury. This review examines the role of NETs in gut-liver axis crosstalk and NAFLD progression. It explores how NETs amplify inflammation, contribute to fibrosis, and facilitate the progression from NAFLD to HCC by interacting with gut microbiota and immune signaling pathways. Therapeutic strategies targeting NETs, such as reducing their formation, enhancing degradation, and modulating the gut microbiota, offer promising approaches to mitigate disease progression. This review sheds light on the interplay between NETs and the gut-liver axis, offering new insights into NAFLD pathophysiology and potential therapeutic strategies to improve patient outcomes.

Anti-vascular endothelial growth factor (VEGF) treatment has shown clinical activity together with immune checkpoint blockade (ICB), but the exact mechanism is not known. We show that VEGF blockade in combination with anti-cytotoxic T-lymphocyte associated protein 4 (CTLA4) + anti-programmed death-ligand 1 (PD-L1) in cholangiocarcinoma (CCA) potentiated a multimodal mechanism dependent on B cell activating factor (BAFF), leading to a proinflammatory B cell response. It led to a BAFF- and interleukin (IL)-12-dependent expansion and rewiring of T regulatory cells (Tregs) toward an anti-tumor T helper-1 (Th-1)-like fragile state. We translated this approach to the clinic and observed immunological changes characterized by Treg cell expansion and rewiring toward fragile and unstable states. We explored the effect of VEGF receptor 2 (VEGFR2) signaling on Treg cell transcriptional programming and established a mouse model ablating VEGFR2 expression on Treg cells. This study reveals the immunological interplay resulting from targeting VEGF together with CTLA-4 and PD-L1 blockade.

Hepatocellular carcinoma (HCC) can be classified into several subtypes based on molecular traits, aiding in prognostic stratification. The subtype with a poor prognosis is often associated with stem/progenitor features. This study focused on identifying circulating biomarkers for aggressive HCC. We searched for secretory proteins whose expression was positively associated with the stem/progenitor markers KRT19, EPCAM, and PROM1 in 2 independent HCC cohorts. Serum folate receptor 1 (FOLR1) levels were measured in 238 chronic liver disease and 247 HCC patients, evaluating their diagnostic and prognostic capabilities. FOLR1 was identified as a secretory protein that was positively correlated with all 3 stem/progenitor markers and a poor prognosis in both the discovery and validation cohorts. Higher FOLR1 expression was detected in tumor than nontumor tissues and was associated with aggressive subtypes, and activation of p53, DNA repair, Myc, E2F, and PI3K/AKT/mTOR pathways. Serum FOLR1 levels correlated with tumoral FOLR1 expression in HCC patients and were significantly elevated compared with those in patients with chronic hepatitis or nonliver disease. Serum FOLR1 levels demonstrated diagnostic performance for HCC comparable to that of alpha-fetoprotein (AFP), and their combination increased the diagnostic accuracy. Elevated serum FOLR1 levels were associated with poor prognosis in HCC patients, regardless of treatment, especially in patients with early-stage disease. The multivariate analysis revealed that the serum FOLR1 level and the Gender, Age, AFP-L3, AFP, and Des-gamma-carboxy prothrombin (GALAD) score were independent predictors of a poor prognosis with their combination further stratifying prognosis. FOLR1 is a stemness-associated biomarker for HCC, with serum levels serving as a diagnostic marker for HCC and a prognostic indicator for early-stage disease.

BACKGROUND:Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. The combination of tremelimumab and durvalumab is now a standard treatment option for advanced HCC. OBJECTIVE:To study immune responses in HCC patients treated with tremelimumab and durvalumab. DESIGN:We treated 28 HCC patients with durvalumab, tremelimumab and locoregional therapies. We performed a high-dimensional multiomics analysis including whole exome sequencing, single-cell RNA seq, CO-Detection by indEXing, flow cytometry and multiplex cytokine/chemokine analysis of patients' blood and tumour samples and integrated this data to elucidate immune correlatives and response mechanisms. Mice with syngeneic HCC were treated with anti-PD-L1 plus anti-CTLA4 for hepatic lymphocytes, tumour-infiltrating lymphocytes and peripheral blood mononuclear cell analysis. RESULTS:The median overall survival was 19.2 months. Tumour tissue analysis revealed enhanced interferon responses, with stronger effects in responders. Gene set variation analysis indicated enhanced antigen presentation in responders. Spatial analysis revealed that non-responder tumours had higher numbers of Tregs located in neighbourhoods enriched with immune cells and expressed higher levels of ICOS and PD-1. Conversely, non-responder PD1+CD8+T in these Treg-enriched neighbourhoods expressed lower ICOS. Cell-communication analysis demonstrated that Treg-CD8+T interaction was enhanced in non-responder tissue. Peripheral blood analysis showed increased classical monocytes in responders and Tregs in non-responders. Treg-CD8+T interaction was confirmed in preclinical models. Finally, single-patient computational analysis from the all-across analysis was performed on 860 features, which led to the identification of multiomics feature sets including Treg features. CONCLUSION:Our study provides a blueprint for in-depth analysis of immune correlates in immunotherapy studies and demonstrates the importance of Treg distribution in HCC. TRIAL REGISTRATION NUMBERS:NCT02821754 and the EudraCT identifier: 2019-002767-98.