Genetically engineered mouse models have advanced cancer research, but they fail to mimic some human diseases. Rats offer a powerful alternative for modeling human cancers that are inadequately represented in mice, yet their use has been constrained by technical barriers to genome editing. Here, we report somatic genome editing in rats and apply this approach to model estrogen receptor (ER)-positive breast cancer, which accounts for approximately 70% of human cases but remains poorly represented in mice. The resulting rat tumors reproduce hallmarks of human ER+ breast cancer, including ductal histology, hormone responsiveness, and immune microenvironment features. By contrast, identical genetic alterations in mice failed to yield ER+ tumors, underscoring critical species differences in tumorigenesis. Together, this work establishes a versatile platform for the rapid generation of clinically relevant rat tumor models, opening avenues to study tumor biology, therapeutic response, and immune interactions in cancer subtypes previously inaccessible to experimental modeling.

Single-cell RNA sequencing provides a powerful approach for characterizing cell types, states, and lineages within heterogeneous tissues. However, identifying cell subpopulations that drive phenotypes, particularly treatment responses, remains a challenge. In this study, we performed comprehensive analyses to identify treatment response–associated cell subpopulations in autoimmune diseases by mapping bulk response information onto single-cell data. We integrated single-cell and bulk biopsy data from 314 responders and 619 non-responders treated with six therapeutics targeting tumor necrosis factor (TNF), integrin, or interleukin pathways in inflammatory bowel diseases (IBD) and psoriasis (PsO). Our analyses captured 128,428 interactions among 3,617 differentially expressed genes (DEGs), 852 pathways, and nine cell types spanning immune, stromal, and epithelial compartments. The importance of epithelial barrier integrity and enterocyte-mediated permeability in responses and inflammatory signaling in macrophages in non-responses in all tested therapies were highlighted by the presence of shared DEGs and pathways in both Crohn’s disease (CD) and ulcerative colitis (UC). In PsO, keratinocytes drove non-response to integrin-targeting therapies via disrupted adhesion, migration, and sustained epidermal inflammation. Additionally we introduce SCTRAD (), an online web-based platform that allows exploration of mechanisms that influence the heterogeneity of cellular responses through DEGs and pathways at the single-cell level, as well as analysis of the cell-type-specific drug-related gene network. Our findings provide a comprehensive analysis of the role of cellular heterogeneity in treatment outcomes and for advancing precision medicine strategies in autoimmune diseases. ### Competing Interest Statement The authors have declared no competing interest. AbbVie (United States), https://ror.org/02g5p4n58

Cancer-associated fibroblasts (CAFs) constitute a heterogeneous population of stromal cells whose tumor-modulating activities are highly context-dependent. Unlike cancer cells, CAFs rarely harbor stable genetic mutations; instead, their phenotypic plasticity is largely driven by reversible epigenetic reprogramming. Within the tumor microenvironment (TME), CAFs function as key regulators by secreting extracellular matrix (ECM) components, paracrine growth factors, cytokines, and metabolic intermediates that collectively promote tumor growth, invasion, and therapeutic resistance. Recent advances in cancer biology have shifted attention from solely cataloging coding-sequence mutations toward understanding the epigenetic mechanisms that shape CAF identity and function. Major epigenetic regulatory mechanisms include DNA methylation, histone modifications, and RNA modifications, which dynamically regulate chromatin structure and gene expression without altering the underlying DNA sequence. Emerging evidence indicates that the activation and functional heterogeneity of CAFs are predominantly governed by these epigenetic alterations rather than by permanent genetic changes. Epigenetic reprogramming enables CAFs to acquire diverse tumor-promoting properties, including remodeling of the extracellular matrix, modulation of intercellular signaling pathways, and secretion of cytokines that influence gene expression in neighboring cancer and immune cells. These processes ultimately contribute to tumor initiation, progression, metastasis, and resistance to therapy. This review summarizes recent advances in understanding how epigenetic modifications regulate CAF activation and function within the tumor microenvironment. In addition, we discuss the potential of targeting CAF-associated epigenetic pathways as a promising therapeutic strategy for cancer treatment.

This protocol provides a methodological framework for conducting a meta-analysis to evaluate the effects of nutritional therapies on the nutritional status of gastric cancer patients. By following this protocol, researchers will be able to systematically identify, appraise, and synthesize evidence from randomized controlled trials and comparative studies. The steps include: formulating a comprehensive search strategy across multiple databases; dual-independent screening and selection of studies using predefined PICOS criteria (population, interference, comparison, outcome, and study design); standardized data extraction and harmonization of outcome measures; assessment of study quality using the Cochrane Risk of Bias 2.0 tool; and statistical synthesis using appropriate models, with exploration of heterogeneity and sensitivity analyses. Application of this protocol to the available evidence suggests potential benefits of specific nutritional interventions, e.g., oral supplementation for body weight, though high heterogeneity underscores the need for rigorous and standardized methodology in this field. A continuous model with fixed or random effects was used to get the mean difference (MD) with 95% confidence intervals (CIs). A total of 18 studies, involving 3,586 subjects, were selected for the meta-analysis. Oral nutritional supplementation had a significantly increased body weight (MD, 0.74; 95% CI, 0.20-1.27, p = 0.007) compared to the control in patients with gastric cancer. Early enteral nutrition had significantly improved prealbumin levels (MD, 22.53; 95% CI, 13.37-31.69, p < 0.001) compared to parenteral nutrition in patients. However, no significant differences were found between enteral immunonutrition and standard enteral nutrition for albumin (MD, 0.57, 95%CI,-0.31-1.44, p=0.20), prealbumin (MD, 0.23, 95%CI,-0.29-0.76, p=0.38), or transferrin levels (MD, 0.11, 95%CI,-0.09-0.32, p=0.28). The studied data showed that using oral nutritional supplementation had significantly increased body weight compared to control, and early enteral nutrition had significantly improved prealbumin levels compared to parenteral nutrition. However, more studies are required to validate this finding.

Genome-wide association studies implicate the PTPN2 gene locus (18p11.21) in risk for several autoimmune diseases, including inflammatory bowel disease. Through genetic fine mapping, we identified the single-nucleotide polymorphism rs80262450 in the PTPN2 gene as the putative causal variant. Analysis of GTEx tissue samples and genetically engineered myeloid cell lines carrying risk and nonrisk alleles of rs80262450 demonstrated increased expression of the PTPN2 splice isoform 4 (PTPN2.4), suggesting that the rs80262450 enhances disease susceptibility by favoring production of PTPN2.4. Furthermore, we found that PTPN2.4 contains a nuclear export sequence (NES) that leads to its retention in the cytoplasm. Differential localization of PTPN2.4 isoform results in a distinct protein binding profile revealed by mass-spectrometry analysis, and its overexpression increased TNF-α. PTPN2.4 knockdown reduced pro-inflammatory cytokines in human macrophages. Mutations within the NES motif abolished the unique localization and function of PTPN2.4. Lastly, increased expression of PTPN2.4 was found in Crohn's disease tissues, demonstrating its involvement in the disease. Together, we identified the pathogenic isoform PTPN2.4 as a novel driver of intestinal inflammation and a potential target to attenuate inflammation in IBD.

Stage III colorectal cancer (CRC) patients exhibit substantial variability in survival outcomes despite standardized Tumor-Node-Metastasis (TNM) staging and oxaliplatin-based adjuvant chemotherapy. Current prognostic models often rely on single-modality data, limiting their predictive accuracy and clinical utility. We developed a novel Multimodal Prognostic Index (MMPI) that integrates histopathological features from hematoxylin and eosin-stained whole-slide images and radiomic features from preoperative computed tomography scans. This retrospective, multicenter study included 253 stage III CRC patients from three institutions, all of whom received oxaliplatin-based adjuvant chemotherapy. Prognostic predictions were generated using a robust, risk-aware joint and individual representation learning algorithm (Robust risk-Aware Joint and Individual [RAJI]). MMPI was trained and tested on internal cohorts and validated externally. Feature contributions were interpreted using SHapley Additive exPlanations. MMPI consistently outperformed unimodal models based solely on pathomics or radiomics in predicting overall survival (concordance index: training set, 0.716 vs. 0.596-0.620; testing set, 0.672 vs. 0.594-0.642; external validation set, 0.632 vs. 0.580-0.605) and recurrence-free survival (C-index: training set, 0.713 vs. 0.609-0.656; testing set, 0.735 vs. 0.611-0.639). It remained an independent prognostic factor after multivariate adjustment and improved risk stratification within TNM-defined subgroups. Furthermore, MMPI effectively predicted chemotherapy efficacy, particularly distinguishing high-risk patients less responsive to 3- or 6-month XELOX and FOLFOX regimens. This study is the first to integrate radiological and pathological imaging for prognostic assessment in stage III CRC. It offers a non-invasive, interpretable tool to improve survival prediction and guide individualized chemotherapy decisions.

Patient-derived organoids (PDOs) are becoming increasingly important in prostate cancer (PCa) translational research. However, direct proof-of-concept studies demonstrating their ability to model disease evolution, identify relevant biomarkers, and accurately predict treatment response in PCa patients, remain scarce. Here, we report the establishment of serially transplantable xenografts series derived from two advanced PCa PDO lines, which can be further re-cultured as organoids. Newly-generated model series maintain key phenotypic, genomic, and functional characteristics of the original patient tumors, and emulate relevant molecular subtypes of advanced PCa. Single-cell RNA sequencing (scRNA-seq) analysis uncovers transcriptomic differences between xenograft and organoid models, as well as signaling pathways which are largely preserved and can be targeted ex vivo. Functional drug profiles correlate with molecular and clinical attributes, as exemplified by response to androgen receptor (AR) pathway inhibitors and glucocorticoid-mediated AR signaling activation. Longitudinal scRNA-seq analysis of perturbed PDOs identifies a rare PROX1+/ALDH1A1+ cell population, which pre-exist in the treatment-naïve setting and is significantly enriched upon androgen deprivation. Notably, this cell population is similarly enriched in post-treatment samples of the original patient and is associated with aggressive AR-negative PCa molecular subtypes, suggesting a potential link with PCa progression. Our study provides proof-of-concept evidence that organoids can mirror PCa patient-specific drug sensitivity profiles and molecular paths of disease progression, uncovering pertinent biomarkers. Ultimately, our organoid-xenograft model series provide a modular and scalable platform that can readily be used for mechanistic and translational studies. ### Competing Interest Statement The authors have declared no competing interest. Krebsliga Beider Basel, https://ror.org/05v5ag345, KLbB-5329-03-2021 Swiss National Science Foundation, https://ror.org/00yjd3n13, 320030_205086 University Hospital of Basel, Department of Surgery, PMC Platform

Abstract Sotorasib (AMG510) and adagrasib (MRTX849) have shown significant efficacy in KRASG12C mutant NSCLC, but acquired resistance occurs within 6–12 months. While some resistance arises from new mutations, over half of the resistant cases lack identifiable genomic alterations. We hypothesize that resistance is driven by signaling network rewiring, creating new therapeutic vulnerabilities. To investigate acquired resistance (AR) mechanisms, multiple AR models, including cell lines (H23AR & H358AR), PDXs (TC303AR & TC314AR), CDXs (H358AR CDX), and PDXOs (PDXO303AR & PDXO314AR) were developed. H23AR and H358AR cells displayed >600-fold and 200-fold and PDXO303AR and PDXO314AR, exhibited >300-fold and >100-fold resistance to sotorasib, respectively compared to their parental counterparts, however, no additional mutations in KRAS or other potential genetic alterations were identified. The AR cells and PDXOs also showed comparable resistance to adagrasib. Proteomic and phosphoproteomic analyses in TC303AR & TC314AR PDXs identified distinct protein signatures associated with KRAS reactivation, mTORC1 signaling upregulation, and PI3K/AKT/mTOR pathway activation. PI3K protein levels were significantly elevated in AR PDXs, H23AR, and H358AR cells. Pharmacological inhibition of PI3K with copanlisib or genetic knockout via CRISPR-Cas9 restored sotorasib sensitivity, suppressed colony formation, and inhibited downstream effectors, including p-AKT, p-mTOR, p-S6, p70S6K, p-GSK3β, and p-PRAS40 in AR cells. copanlisib also sensitized both acquired and primary resistant PDXOs and synergized with sotorasib in restoring drug sensitivity. We found that p4E-BP1 was significantly upregulated in H23AR and H358AR cells, and copanlisib suppressed its expression. The level of p4E-BP1 expression was correlated with Sotorasib sensitivity in PI3K knockout clones, where the most sensitive clone displayed reduced or no p4E-BP1 expression. CRISPR-Cas9-mediated knockout of 4E-BP1, either alone or in combination with PI3K knockout, dramatically restored sotorasib sensitivity to levels comparable to parental cells. Suppression of 4E-BP1 hyperphosphorylation required dual inhibition of mTORC1 and mTORC2, and treatment with AZD8055 or sapanisertib (mTORC1/2 dual inhibitors) significantly dephosphorylated 4E-BP1 and restored sotorasib sensitivity in resistant cells and PDXOs. In contrast, everolimus (a mTORC1-selective inhibitor) did not restore sotorasib sensitivity. In PDX, CDX, and xenograft models in vivo, the combination of sotorasib with either copanlisib or sapanisertib resulted in robust, synergistic, and durable tumor regression at well-tolerated doses. These findings showed the critical role of PI3K/mTOR signaling as a bypass mechanism of resistance to KRASG12C inhibitors. We conclude that mTORC1/2 mediated inhibition of p4E-BP1 and combination strategies targeting this pathway effectively overcomes acquired resistance to KRASG12C inhibitors in NSCLC.

Introduction: Di-(2-ethylhexyl) phthalate (DEHP) is a widely used environmental plasticizer. Although environmental pollutants are increasingly implicated in inflammatory bowel disease, how DEHP-related molecular programs connect to Crohn’s disease (CD)-associated intestinal remodeling remains unclear.Objective: This study aimed to investigate the associations among DEHP-related molecular programs, CD-associated inflammation, tissue remodeling, and their corresponding cellular-state contexts.Methods: DEHP candidate targets were predicted using ChEMBL, PharmMapper, and SwissTargetPrediction. Public CD transcriptomic cohorts underwent differential expression and weighted gene co-expression network analyses. Multi-algorithm machine learning and SHAP prioritized candidate genes. Single-cell RNA sequencing evaluated disease-aligned cell-state mapping. Additionally, molecular docking, dynamics simulations, a DSS-induced colitis model, and primary mouse intestinal fibroblast exposure experiments were conducted.Results: Multi-omics integration identified a transcriptional intersection among predicted DEHP targets, CD differentially expressed genes, and disease-associated co-expression modules. ANXA3, DUSP6, IGFBP2, and TNFSF13 emerged as a core disease-discriminative feature combination. Single-cell projection mapped this molecular program preferentially to inflammatory fibroblast-associated disease states, with latent vector analysis suggesting continuous disease-aligned state shifts. Simulations indicated potential structural compatibility between DEHP and candidate proteins. In vivo, DEHP aggravated DSS-induced intestinal inflammation and dysregulated these core genes. Primary fibroblast experiments confirmed candidate gene-axis alterations alongside increased extracellular matrix and inflammatory remodeling markers.Conclusions: This study establishes a cross-scale DEHP-CD candidate gene-cell state framework, directly linking environmental plasticizer exposure with CD-associated inflammatory fibroblast remodeling, thereby providing clues for future mechanistic validation.

Abstract Introduction. Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, yet identifying patients most likely to benefit remains challenging. Established biomarkers such as tumor mutational burden (TMB) and microsatellite instability (MSI) have performance limitations. We hypothesized that combining MSI and TMB with epigenomic features of tumor-intrinsic immune regulation and the tumor microenvironment from pretreatment plasma would improve prediction. We developed and validated a multimodal immunotherapy response score (MIRS-Score) that integrates MSI, TMB, and epigenomic signatures (Guardant360 Liquid) to identify patients likely to respond to ICI alone or in combination with chemotherapy. Methods. From the de-identified GuardantINFORM database we identified 695 advanced NSCLC (aNSCLC) patients treated with first- or second-line ICI monotherapy or ICI+chemotherapy and randomly split them into training (n=483) and test (n=212) sets. A literature-curated, data-driven epigenomic signature associated with real-world time to treatment discontinuation (rwTTD) was combined with MSI and TMB to train the multimodal model. Patients ≥80th MIRS percentile were labeled MIRS-High. Cox proportional hazards models adjusted for sex, age, therapy type (mono vs combo), line of therapy, and baseline tumor fraction provided adjusted hazard ratios (aHR); median rwTTD was estimated by Kaplan-Meier. Results. In the independent test set (n=212), MIRS-High patients had longer rwTTD (median 8.7 vs 5.1 months; aHR 0.61, 95% CI 0.41-0.93, p=0.02) and improved overall survival (OS) (aHR 0.33, 95% CI 0.16-0.68, p<0.005). In the ICI monotherapy subgroup (n=69), MIRS-High showed median rwTTD 11.0 vs 4.9 months (aHR 0.31, 95% CI 0.13-0.75, p=0.01) and longer OS (aHR 0.18, 95% CI 0.04-0.79, p=0.023). MIRS-High was not associated with rwTTD in patients treated with chemotherapy alone (aHR 1.16, 95% CI 0.94-1.44, p=0.18). Conclusions. A pretreatment plasma-based score combining MSI, TMB, and epigenomic signatures identifies aNSCLC patients with superior outcomes on ICI and outperforms MSI or TMB alone. The ICI treatment-specific stratification and strong association with both rwTTD and OS support the clinical utility of this multimodal approach, warranting further evaluation to assess the potential for guiding ICI treatment decisions. Citation Format: Sean Gordon, Jing Wang, Shile Zhang, Marisa Juntilla, Tingting Jiang, Matthew Ellis, Vishnu Ramani, Reagan Barnett, Bernard Herrman, Justin Odegaard, Darya Chudova. Blood-based integration of epigenomic profiles, TMB, and MSI to predict immune checkpoint inhibitor response in advanced non-small cell lung cancer (aNSCLC) [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 100.

Retinal hypoxia is a critical driver of blinding retinal vascular diseases like diabetic retinopathy (DR). This study aims to investigate the role and associated molecular mechanisms of hypoxia-inducing factor 1-α (HIF-1α) in mice with DR. Streptozotocin (STZ) was utilized to induce diabetic mouse models. Retinal structure and vasculature were assessed by Hematoxylin and Eosin (H&E) staining and Fundus Fluorescein Angiography (FFA). We analyzed key protein expression in retinal tissues via Western blot. Mice induced by STZ were treated with PX-478 (an inhibitor of HIF-1α), and Evans Blue staining was performed to assess the impact of HIF-1α depletion on blood-retinal barrier (BRB) function. Transmission electron microscopy (TEM) was used to observe autophagy in retinal tissue cells. H&E staining and FFA confirmed the successful establishment of the DR mouse model. In STZ-induced diabetic mice, we observed significant up-regulation of HIF-1α and the cellular senescence makers p16 and p21, alongside impaired autophagy. Furthermore, protein levels of the neuroprotective factors Glial cell line-derived neurotrophic factor (GDNF), and neurturin (NRTN), as well as sirtuin 1 (SIRT1), were decreased, while peroxisome proliferator-activated receptor-gamma (PPAR-γ) was increased. Following treatment with PX-478, the decreasing trend of GDNF, NRTN, microtubule-associated protein 1 light chain 3 B (LC3B), and SIRT1 protein levels was blocked, and the overexpression of HIF-1α, p16, p21, and PPAR-γ was inhibited. Additionally, PX-478 improved the barrier integrity of BRB in DR mice, and TEM showed an increase in autolysosomes in retinal tissues. This study demonstrates the significant role of HIF-1α in DR pathogenesis, providing a theoretical foundation for further exploration of HIF-1α-directed therapies for this sight-threatening complication of diabetes.

Cell deconvolution is a widely used method to characterize the composition of the mixed cell population in bulk transcriptomic datasets. While tissue- and blood-derived cell reference matrices (CRMs) are commonly used, their impact on deconvolution accuracy has yet to be systematically evaluated. In this study, we developed tissue- and blood-derived CRMs using single-cell RNA sequencing (scRNA-seq) data from inflammatory bowel disease (IBD). Three publicly available blood-derived CRMs (IRIS, LM22, and ImmunoStates) were incorporated for benchmarking. Deconvolution performance was evaluated using both public bulk transcriptomic datasets and simulated pseudobulk samples by goodness-of-fit and cell fractions correlation. Two infliximab-treated bulk datasets were used to identify treatment-related cell types. In addition, lung adenocarcinoma (LUAD) single-cell and bulk transcriptomic datasets were also used for deconvolution evaluation. We found tissue-derived CRMs consistently outperformed blood-derived CRMs in deconvolving bulk tissue transcriptomes, exhibiting higher goodness-of-fit and more accurate cellular proportion estimates, particularly for immune and stromal cells. They also revealed more treatment-related cell types. In contrast, all CRMs performed similarly when applied to blood bulk transcriptomics. These trends also were shown in the LUAD datasets. Our results emphasize the importance of selecting appropriate CRMs for cell deconvolution in bulk tissue transcriptomes, particularly in immunology and oncology. Such considerations can be extended to encompass other disease implications. The R package (DeconvRef) for building user-defined CRMs is available at https://github.com/alohasiqi/DeconvRef

Background Myocarditis is one of the most common health problems in young people. Despite imaging techniques and endomyocardial biopsies advancing, there is still inadequate for myocarditis characterization. Some studies have shown that myocarditis is closely associated with mitochondrial dysfunction. Therefore, this study was aimed to identify mitochondrial-related biomarkers and gene regulatory networks in myocarditis and potential therapeutic targets. Methods We downloaded GSE95368 dataset from GEO to get myocarditis gene expression profiles, then used EdgeR and AI algorithm for bioinformatics analysis of DEGs’ functions. Established CVB3-induced mouse myocarditis model via intraperitoneal injection, and assessed energy metabolism differences using targeted metabolomics. CVB3 stimulus induced myocarditis in H9C2 cells. We assessed mitochondrial dysfunction (ATP, MMP) with commercial kits, MAPK8 release via ELISA, and MAPK8, p-PI3K, p-AKT levels by western blot. Furthermore, a total of 8 patients primarily diagnosed with myocarditis were enrolled, and levels of MAPK8 and CK in serum were detected. SP600125, an inhibitor of MAPK8, was administrated to CVB3-infected mice to study its potential protective effect in viral myocarditis. Results We obtained 77 DEGs enriched in myocarditis. Analysis yielded 11 modules, MEpurple module genes linked to myocarditis progression were identified via WGCNA. MAPK8, NAMPT and ALB are associated with mitochondrial function. CVB3-infected mice showed cardiac inflammation and high MAPK8 expression in serum or heart tissues.The target metabolism results indicated altered central carbon metabolism distinguished CVB3 group from control, with higher D-Glucose-1-phosphate and D-Glucose-6-phosphate and lower L-Cystine, dCMP, IMP and Xylulose-5-phosphate levels. CVB3 treatment caused mitochondrial dysfunction in H9C2 cells (decreased ATP, MMP), and increased MAPK expression. Western blot showed MAPK8 consolidated the levels of p-PI3K and p-AKT. CK activity was notably higher in myocarditis patients than healthy individuals. MAPK8 levels in myocarditis patients serum also exceeded those in healthy individuals. Pearson analysis indicated that MAPK8 and CK may contribute to myocarditis progression via distinct mechanisms. In CVB3-infected mouse model with SP600125 treatment, cardiac inflammation and MAPK8, p-PI3k, p-AKT expression were reduced, confirming MAPK8’s crucial role in viral myocarditis. Conclusion Our study identified MAPK8 as a key biomarker of myocarditis, and it may be a potential therapeutic target for myocarditis. ### Competing Interest Statement The authors have declared no competing interest.

Background:Idiopathic pulmonary fibrosis (IPF) is a degenerative respiratory condition characterized by significant mortality rates and a scarcity of available treatment alternatives. Cuproptosis, a novel form of copper-induced cell death, has garnered attention for its potential implications. The study aimed to explore the diagnostic value of cuproptosis-related hub genes in patients with IPF. Additionally, multiple bioinformatics analyses were employed to identify immune-related biomarkers associated with the diagnosis of IPF, offering valuable insights for future treatment strategies. Methods:Four microarray datasets were selected from the Gene Expression Omnibus (GEO) collection for screening. Differentially expressed genes (DEGs) associated with IPF were analyzed. Additionally, weighted gene coexpression network analysis (WGCNA) was employed to identify the DEGs most associated with IPF. Ultimately, we analyzed five cuproptosis-related hub genes and assessed their diagnostic value for IPF in both the training and validation sets. Additionally, four immune-related hub genes were screened using a protein-protein interaction (PPI) network and evaluated through the receiver operating characteristic (ROC) curve. Lastly, single-cell RNA-seq was employed to further investigate differential gene distribution. Results:We identified a total of 92 DEGs. Bioinformatics analysis highlighted five cuproptosis-related genes as candidate biomarkers, including three upregulated genes (CFH, STEAP1, and HDC) and two downregulated genes (NUDT16 and FMO5). The diagnostic accuracy of these five genes in the cohort was confirmed to be reliable. Additionally, we identified four immune-related hub genes that demonstrated strong diagnostic performance for IPF, with CXCL12 showing an AUROC of 0.90. We also examined the relationship between these four genes and immune cells. CXCL12 was significantly negatively associated with neutrophils, while CXCR2 was associated exclusively with neutrophils, consistent with our single-cell sequencing results. CTSG showed a primarily positive association with follicular helper T, and SPP1 was most strongly associated with macrophages. Finally, our single-cell sequencing data revealed that in patients with IPF, CXCL12 was highly expressed in the endothelial cell subset (ECs), while SPP1 exhibited high expression in multiple cellular populations. The expression of the CTSG showed statistically significant differences in monocyte macrophages. Conclusion:The research methodically depicted the intricate interplay among five cuproptosis-related genes, four immune-related hub genes, and IPF, offering new ideas for diagnosing and treating patients with IPF.

Background and Aims Hidradenitis suppurativa (HS) is an understudied chronic inflammatory skin disease that is characterized by painful bumps and abscesses. Adalimumab and secukinumab are the only two approved biologics for the treatment of HS. Despite these advances in the treatment of disease, there remains significant unmet medical need, with many patients only achieving moderate improvements in disease, or continuing to experience flares. This suggests that there may be distinct patient subsets with unique molecule drivers of disease. The aim of this study is to identify and characterize the molecular subtypes of HS patients to further understand its heterogeneity. Methods Six public datasets with a total of 100 skin lesional samples were integrated to identify molecular subtypes and build a 36-gene classifier, which was validated by three independent lesional skin datasets. Two out of six training datasets generated from patients treated with adalimumab were used to identify the relationship between subtypes and response status. Results Two molecular subtypes were identified from the training datasets, in which subtype S1 had a higher response rate of adalimumab than subtype S2 in the two adalimumab treatment datasets. Subtype S1 was characterized by three gene modules associated with keratinization, development, and metabolism, and six cell types related to sebocytes, smooth muscle cells, endothelial cells, schwann cells, basal cells, and proliferating cells. Subtype S2 was associated with three modules related to immune response, wound healing, keratinization, and cell cycle, and three cell types related to T lymphocytes, dendritic cells, and fibroblasts. The two subtypes were replicated in three additional independent datasets. Conclusions This study discovered and validated two HS subtypes with different molecular mechanisms and drug response, which may aid interpretation of heterogeneous molecular and clinical information in HS patients. ### Competing Interest Statement All authors are employees of AbbVie. The design, study conduct and financial support for this research were provided by AbbVie. AbbVie participated in the interpretation of data, review, and approval of the publication.