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PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗

PubMed2026

Translation of scRNA-seq to a clinical blood test for infection diagnostics.

INTRODUCTION: Early and accurate triage of patients with febrile illness is crucial for appropriate treatment. While standard inflammatory biomarkers are often nonspecific, transcriptome analysis of peripheral blood has diagnostic potential. However, bulk gene expression data is often confounded by changes in cell count proportions, a more robust quantification of gene expression in specific single-cell types, such as monocytes, is required to serve as a reliable clinical biomarker. AREAS COVERED: Various methods to obtain single-cell-type gene expression results, including the gold standard of gene expression analysis after cell sorting and single-cell RNA sequencing, which are difficult to implement in the routine settings are discussed. Other method to interrogate gene expression of a single cell-type is needed. Finally, monocyte cell-type specific ratio-based biomarker (RBB, called Direct Leukocyte Single cell-type Transcript Abundance, or DIRECT LS-TA) which can estimate single cell-type (monocyte) specific gene expression without cell sorting is introduced. EXPERT OPINION: Traditional diagnostic test for differentiating infection has several limitations requiring breakthrough including turn-around time and cost. DIRECT LS-TA provides a reliable way to quantify monocyte-specific gene expression that strongly correlates with gold-standard methods. It is more affordable than single-cell RNA sequencing and can be readily implemented in clinical laboratories using widely available quantitative PCR or digital PCR machines.

Humans↗

PubMed2026

RNA splicing and cardiovascular disease: a guide for cardiologists.

Alternative splicing (AS) is a fundamental RNA processing mechanism, which generates different RNA transcripts and consequently different protein isoforms from a single gene. This increases the diversity of proteins within an organism and can fine-tune biological processes. This review examines how cardiac-enriched RNA-binding proteins establish heart-specific splicing programs governing aspects of cardiac development, function, and disease. Developmentally, coordinated sarcomeric isoform switches underpin the foetal-to-adult transition and further isoform rewiring in ion channel and kinase genes determine electrophysiology and excitation-contraction coupling. AS contributes to the pathogenesis of several cardiomyopathies and emerging datasets suggest that pathological hypertrophy engages distinct splicing signatures compared with physiological hypertrophy. This review summarizes diagnostic and prognostic opportunities arising from bulk, long-read, and single-cell/nucleus transcriptomics, which resolve cell type-specific isoforms and disease-associated switches. Circulating RNA biomarkers (including splice ratios and circularRNAs) may signify myocardial remodelling and arrhythmic risk. Integrative approaches that link AS with proteomics and genomics improve variant interpretation, reveal previously unannotated protein isoforms, and enable tracking of disease progression and therapy response. Finally, an outline of therapeutic strategies to modulate AS in cardiovascular disease (CVD), including antisense oligonucleotides, small molecules, and genome-editing modalities (CRISPR, base, and prime editing), is provided. The major challenges that remain before splice-targeting therapeutics can be targeted to treat cardiovascular disease are highlighted. Lessons from neuromuscular indications establish clinical feasibility of splicing correction and motivate translation to cardiology. Together, mechanistic insight, biomarker development, and therapeutic innovation position RNA splicing as a tractable axis for precision cardiovascular medicine.

Humans↗

PubMed2025

CS Ratio is an immune-related prognostic biomarker for cervical cancer.

BACKGROUND: The tumor microenvironment (TME) plays a crucial role in cancer progression but its complex structure significant variability among patients present considerable challenges for research. Recent studies have demonstrated that macrophage polarization states defined by the expression levels of CXCL9 SPP1 (CS Ratio) are more prognostically relevant than traditional M1/M2 markers. The CS polarization state reflects a highly coordinated network of pro-tumor anti-tumor variables offering a simplified yet effective immune response indicator for the complex TME. The CS Ratio has been shown to correlate with the abundance of anti-tumor immune cells the gene expression programs of tumor-infiltrating cells responses to immunotherapy. Cervical cancer, one of the most common gynecological malignancies, still faces limited therapeutic options. CXCL9, a member of the CXC chemokine family, plays a critical role in immune regulation, inflammation, tumor growth, angiogenesis, and metastasis. Similarly, SPP1, a cytokine, influences immune-related pathways by regulating molecules such as interferon-γ and interleukin-12. However, no studies have systematically investigated the role of the CS Ratio in cervical cancer or its relationship with immunotherapy characteristics. Research in this area could provide critical insights into the role and clinical potential of the CS Ratio in cervical cancer and related tumors. METHODS: The expression ratio of CXCL9 to SPP1 was analyzed in cervical cancer patients using data from the Gene Expression Omnibus (GEO) database, which revealed significant differences. Data for cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. The optimal cutoff value for the CS Ratio was determined using the maxstat package in R, and Kaplan-Meier (KM) survival curves were constructed. Patients were categorized into High and Low groups based on the median CS Ratio. Immune scores were analyzed, and immune cell infiltration was assessed using CIBERSORT. Differences in the CS Ratio were evaluated across patients with varying pathological T stages and FIGO stages. Additionally, receiver operating characteristic (ROC) analysis was performed using the pROC package in R to calculate the area under the curve (AUC). Univariate and multivariate Cox regression analyses were performed to evaluate the potential of the CS Ratio as an independent prognostic factor in cervical cancer. A Cox regression-based nomogram integrating four key features was subsequently developed for the TCGA-CESC cohort. Nomogram performance was assessed using calibration curves and ROC analysis. RESULTS: The CS Ratio was significantly lower in cervical cancer patients compared to normal controls (P < 0.05). KM survival curves indicated that patients in the CS High group exhibited better prognoses. Immune score analysis revealed significantly higher immune scores (P < 0.05) and lower tumor purity (P < 0.05)in the CS High group compared to the Low group. CIBERSORT analysis revealed significantly higher proportions of CD8+ T cells (P < 0.05) and M1 macrophages (P < 0.05), and a significantly lower proportion of M2 macrophages (P < 0.05), in the CS High group compared to the Low group. The CS Ratio significantly decreased with advancing FIGO stage (P < 0.05). Both univariate (P < 0.05) and multivariate Cox regression analyses (P < 0.05) confirmed the CS Ratio as an independent prognostic factor. ROC analysis demonstrated that the CS Ratio had higher AUC values for predicting 1-year (AUC=0.69), 3-year (AUC=0.66), and 5-year OS (AUC=0.68) than CXCL9 or SPP1 alone. The Cox regression-based nomogram integrating four key features demonstrated predictive capability for 1-, 3-, and 5-year OS in CESC patients (Concordance Index = 0.751; 95% CI: 0.678-0.824; p = 1.50Í10-11). Significant survival differences were observed between the high-risk and low-risk groups based on the nomogram score. ROC analysis yielded high AUC values for survival prediction: 0.85 (95% CI: 0.94-0.75) at 1-year, 0.74 (95% CI:0.84-0.64) at 3-year, and 0.72 (95% CI:0.84-0.61) at 5-year. CONCLUSION: The CS Ratio may serve as a more effective prognostic biomarker for cervical cancer patients.

CXCL9↗

PubMed2026

Evolutionary and resistance dynamics in oligometastatic and oligoprogressive cancer treated with stereotactic radiotherapy and systemic therapies: A systematic review and focused meta-analysis.

BACKGROUND: Oligometastatic and oligoprogressive disease treated with stereotactic ablative radiotherapy (SABR) represents a clinically heterogeneous entity. Increasing evidence suggests that anatomical definitions alone may not adequately capture underlying biological diversity. This systematic review aimed to synthesize translational evidence exploring evolutionary dynamics, resistance mechanisms, and biomarker-driven stratification in patients treated with SABR. METHODS: A systematic literature review was performed including prospective and retrospective studies evaluating translational biomarkers in oligometastatic or oligoprogressive settings treated with SABR. Studies assessing genomic, transcriptomic, circulating or immune-related biomarkers were included. Data were summarized qualitatively according to predefined translational domains: (i) evolutionary dynamics under systemic therapy pressure, (ii) baseline biological stratification, (iii) longitudinal circulating biomarkers, and (iv) systemic immune remodeling. Exploratory quantitative visual syntheses were performed using reported hazard ratios when conceptually comparable endpoints were available. RESULTS: 19 studies comprising 1527 patients were included. Across tumor types and treatment contexts, translational analyses consistently indicated that anatomically defined oligometastatic states encompass biologically distinct subgroups with different risks of systemic progression. Studies evaluating oligoprogression under ongoing systemic therapy suggested a distinction between spatially constrained resistance and systemic molecular escape, supported by circulating tumor DNA and tissue- or plasma-based molecular profiling (including genomic and transcriptomic analyses). Baseline biological features, including adverse genomic signatures and circulating biomarkers, were associated with inferior progression outcomes despite metastasis-directed therapy. Longitudinal biomarkers provided early signals of treatment response and systemic control. Immune remodeling after SABR showed context-dependent effects, both systemic immune activation and treatment-related immunosuppression reported across studies.

Humans↗

PubMed2026

Development of a Computational Histology Artificial Intelligence-Powered Prognostic Biomarker in Colorectal Cancer in The Cancer Genome Atlas.

BACKGROUND: Risk stratification in colorectal cancer (CRC) plays an important role in treatment decision-making. As such, prognostic biomarkers that can augment risk stratification have clinical value. Quantitative histologic features from routine hematoxylin and eosin (H&E)-stained whole slide images (WSIs) provide a novel avenue for biomarker discovery. In this study, we explored the potential for a computational histology artificial intelligence (CHAI) platform to develop and validate a prognostic biomarker in CRC. METHODS: The Cancer Genome Atlas Colorectal Adenocarcinoma project was utilized for this study, with inclusion of all subjects (stage I-IV) with available digitized H&E specimens. The cohort was split into development and validation cohorts by a stratified random split. The previously developed CHAI platform was applied in the development cohort to construct a continuous risk score from histologic features associated with progression-free interval (PFI) that was dichotomized based on an optimized cutpoint for distinguishing PFI into a high risk CHAI (+) and lower risk CHAI (-). PFI was compared between CHAI (+) and CHAI (-) patients in the validation cohort in multivariable Cox proportional hazards models. Time-dependent area under the curve (tdAUC) and C-indices were also calculated for PFI. RESULTS: A total of 583 participants were included in the study, with 409 assigned to the validation cohort. The CHAI biomarker classified 229 participants (56%) as CHAI (+) and 180 (44%) as CHAI (-) in the validation set. CHAI (+) participants had worse PFI in a multivariable analysis adjusting for available clinicopathologic variables (hazard ratio (HR) = 2.65; 95% confidence interval (CI), 1.63-4.30). TdAUC for the CHAI biomarker was 0.60 (95% CI, 0.53-0.67) at 12 months, 0.62 (0.55-0.69) at 36 months, and 0.67 (0.55-0.79) at 60 months; the C-index was 0.62 (95% CI, 0.58-0.67). CONCLUSIONS: The CHAI platform was used to develop a prognostic digital pathology biomarker in CRC. This demonstrates the feasibility and potential to apply this artificial intelligence-based digital pathology biomarker platform for risk stratification in CRC and supports its further study.

Artificial intelligence↗

PubMed2026

Advances in Single-Molecule Immunoassay: From Counting Strategies to CRISPR-Enhanced Biosensing.

Single-molecule immunoassays (SMIs) overcome the sensitivity limitations of conventional bulk measurements by enabling a paradigm shift from analog to digital signal readouts, thereby facilitating highly sensitive quantification of ultra-low-abundance biomarkers for precision diagnostics. This review provides a systematic overview of recent advances in SMI technologies and the conceptual framework underlying their evolution. First, discretization strategies for single-molecule counting are classified into hard discretization, based on physical confinement, and soft discretization, based on spatiotemporal isolation, within heterogeneous and homogeneous assay systems, respectively. The fundamental mechanisms by which these strategies mitigate diffusion limitations and enhance signal-to-noise ratios are discussed. Second, the integration of SMIs with CRISPR-based diagnostic systems (CRISPR-dx) is examined, with particular emphasis on their complementary roles in target recognition and signal amplification. Finally, recent applications of SMIs in the diagnosis of oncological, neurological, infectious, and cardiovascular diseases are summarized, along with a critical discussion of current engineering challenges and future directions toward clinical translation.

Immunoassay↗

PubMed2026

Association of ctDNA RAS mutational status and clinical benefits in first-line metastatic colorectal cancer therapy with chemotherapy plus anti-EGFR (overall response rate and progression-free survival): a brief report of systematic review and meta-analysis.

Monitoring RAS mutations in circulating tumor DNA (ctDNA) is increasingly relevant in metastatic colorectal cancer (mCRC). In patients with tissue RAS wild-type (WT) tumors treated with first-line chemotherapy plus anti-epidermal growth factor receptor therapy (1LChT + anti-EGFR), some studies suggest that RAS WT ctDNA is associated with better outcomes, whereas others reported no differences according to ctDNA RAS mutational status. These inconsistencies may be related to small sample sizes, methodological heterogeneity, differences in assay sensitivity and tumor heterogeneity. We performed a systematic review in patients with tissue RAS WT treated with 1LChT + anti-EGFR. PubMed, Web of Science, and Scopus were searched up to April 2026. Risk of bias was assessed using the QUIPS tool, and random-effect models were applied. Fourteen studies met the inclusion criteria (ten non-interventional studies and four clinical trials). Compared with ctDNA RAS mutated tumors, ctDNA RAS WT tumors showed significantly higher overall response rates [ORR: pooled odds ratio (OR) 2.1, 95% confidence interval (CI): 1.3-3.4; P=0.002] and longer progression-free survival [PFS: pooled hazard ratio (HR) 1.6, 95% CI: 1.3-1.9; P<0.001] [non-interventional studies (NIS) + clinical trials (CT) data]. The pooled prevalence of ctDNA RAS mutations was 10.5% (95% CI: 6.2-14.8%). These findings support ctDNA RAS status as a potential biomarker of benefit from anti-EGFR-based therapy in mCRC, although methodological standardization and prospective validation remain necessary.

Circulating tumor DNA (ctDNA)↗

PubMed2026

Hyperprogression Upon Cemiplimab Alone or With Short Course Chemotherapy in PD-L1 ≥ 50% Non-small Cell Lung Cancer: A Biomarker Guided Multicenter International Phase 2 Trial-HYPERBOLIC Study.

BACKGROUND: Immune checkpoint inhibitor (ICI) monotherapy is the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) with PD-L1 ≥ 50%; however, up to 30% of patients experience early progression or death, including cases of hyperprogressive disease (HPD). High baseline levels (≥ 30.5%) of circulating CD10- low-density neutrophils (LDNs) have been associated with increased HPD occurrence. Emerging evidence suggests that combining ICI with platinum-based chemotherapy (PCT) may mitigate the risk of HPD. Currently, no prospective studies have addressed HPD prevention in this context. PATIENTS AND METHODS: HYPERBOLIC (NCT07274384) is a phase 2, randomized, open-label, multicenter, international trial evaluating whether adding 3 cycles of PCT to first-line cemiplimab reduces HPD rate in stage IV NSCLC with PD-L1 ≥ 50% and CD10- LDNs (identified by flow cytometry as CD15⁺CD11b⁺ within the PBMC fraction, with immature cells defined by loss of CD10) ≥ 30.5%. Seventy-four patients will be randomized (1:1 ratio) to receive cemiplimab alone or cemiplimab plus 3 PCT cycles, followed by cemiplimab maintenance. Randomization will be stratified by Lung Immune Prognostic Index. The first computed tomography scan at week 7 after treatment start will assess HPD occurrence, defined as RECIST v 1.1. disease progression with a delta tumor growth rate (ΔTGR) ≥ 50% and/or TGR ratio ≥ 2. The primary endpoint will be the combined rate of HPD and early death (death within 12 weeks with no radiological evaluation). Secondary endpoints will be HPD rate according to alternative definitions, overall survival, progression free survival, objective response rate, and safety. An extensive translational research platform will include spatial transcriptomics of tumor tissue, single-cell RNA sequencing of PBMCs, circulating-free DNA and plasma factors profiling, and saliva/stool microbiome genomics and metabolomics, to longitudinally explore tumor-host dynamic interactions during treatment. CONCLUSION: to our knowledge, HYPERBOLIC is the first prospective, biomarker-driven trial investigating early treatment escalation based on HPD risk in PD-L1-high NSCLC.

CD10↗

PubMed2025

Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity.

Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.

Alzheimer Disease↗

PubMed2026

An Exosomal Signature for Preoperative Detection of Occult Liver Metastasis in Pancreatic Cancer.

IMPORTANCE: Early liver metastasis (early-LiM) after pancreatectomy represents an aggressive biological phenotype of pancreatic ductal adenocarcinoma (PDAC) and is associated with markedly poor survival. Reliable preoperative biomarkers to identify occult hepatic micrometastasis remain lacking. OBJECTIVE: To develop and externally validate a circulating exosomal microRNA (exo-miRNA)-based machine learning model for preoperative detection of occult early-LiM in PDAC. DESIGN, SETTING, AND PARTICIPANTS: This multicenter retrospective case-control study included 3 phases: genome-wide discovery using exo-miRNA sequencing (discovery cohort), model development (training cohort), and independent external validation (2 validation cohorts). The study took place at 4 medical centers in China, Japan, and South Korea. A total of 372 patients were enrolled between 2011 and 2024. Data were analyzed from July 2024 to November 2025. EXPOSURES: Circulating plasma-derived exosomal miRNA expression profiles. MAIN OUTCOMES AND MEASURES: The primary outcome was early-LiM, defined as liver recurrence within 6 months after curative-intent resection. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and survival outcomes were assessed using Kaplan-Meier analysis. RESULTS: Among 372 patients with PDAC (median [IQR] age, 67 [59-73] years; 229 [61.6%] male and 143 [38.4%] female; median follow-up among survivors, 969 days),early-LiM was associated with significantly worse overall survival compared with other recurrence patterns (median OS, 9.1 months vs 26.6-31.8 months; log-rank P < .001). A 7-exo-miRNA extreme gradient boosting model demonstrated discrimination in the training cohort (AUC, 0.899; 95% CI, 0.822-0.976) and maintained performance in external testing cohorts (AUC, 0.876; 95% CI, 0.846-0.951 and AUC, 0.862; 95% CI, 0.744-0.981). The exo-miRNA panel score remained an independent identifier of early-LiM in multivariable analysis (odds ratio, 26.49; 95% CI, 18.45-55.28; P < .001) and stratified overall survival (log-rank P < .001). Decision curve analysis suggested improved net clinical benefit compared with conventional clinicopathologic variables. CONCLUSION AND RELEVANCE: In this multicenter study, a circulating exo-miRNA-based machine learning model enabled preoperative detection of occult early liver metastasis risk in PDAC. These findings support the potential of exosomal biomarkers to inform biology-guided treatment sequencing and warrant prospective validation.

Journal Article↗

PubMed2026

Sensitivity to Endocrine Therapy Index Predicts Benefit from Weekly Adjuvant Paclitaxel for Hormone Receptor-Positive Breast Cancer in the GEICAM/9906 Trial.

PURPOSE: To independently validate that low endocrine transcriptional activity measured by the sensitivity to endocrine therapy (SETER/PR) index in hormone receptor-positive (HR+) breast cancer predicts benefit from dose-dense paclitaxel chemotherapy within a second prospective-retrospective biomarker study. EXPERIMENTAL DESIGN: We conducted a blinded, prospective-retrospective biomarker analysis within the GEICAM/9906 trial (NCT00129922), which compared adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide (FEC) followed by weekly paclitaxel (P) versus six cycles of FEC in lymph node-positive breast cancer. The SETER/PR index was measured in all available HR+/HER2- tumor RNA samples using a prespecified cut point (<0.75). The primary endpoint was the distant recurrence-free interval (DRFI); secondary endpoints were overall survival (OS) and breast cancer-specific survival (BCSS). RESULTS: Of 647 HR+/HER2- tumors, 567 (87.6%) passed assay quality control (279 FEC + P; 288 FEC). A low SETER/PR index was identified in 92 tumors (16.2%). There was a significant interaction between SETER/PR status and treatment on DRFI (P = 0.046). Among patients with a low SETER/PR index, FEC + P significantly improved DRFI [hazard ratio (HR), 0.46; 95% confidence interval (CI), 0.22-0.95; P = 0.035], with similar results after adjustment (HR, 0.48; 95% CI, 0.24-1; P = 0.049). No treatment benefit was observed for SETER/PR ≥0.75 (HR, 1.02; 95% CI, 0.70-1.47; P = 0.931). Differences in OS and BCSS did not reach significance. CONCLUSIONS: Low endocrine transcriptional activity predicts benefit from adding weekly paclitaxel to anthracycline-based adjuvant chemotherapy in HR+/HER2- breast cancer. These findings independently validate the SETER/PR index as a predictive biomarker for paclitaxel-based chemotherapy and support its potential role in guiding regimen selection.

Humans↗

PubMed2026

Integrated single-cell transcriptomics, Mendelian randomization, and machine learning identify CEBPZ as an immune-related biomarker in oral lichen planus.

BACKGROUND: Oral lichen planus (OLP) is a chronic, immune-mediated oral mucosal disease with complex pathophysiology and potential for malignant transformation. Understanding its molecular basis is critical for the development of precise diagnostic and therapeutic strategies. OBJECTIVES: We aimed to identify key immune-related biomarkers and characterize cellular dynamics in OLP, with a particular focus on the role of CEBPZ in disease pathogenesis. MATERIAL AND METHODS: We analyzed single-cell RNA sequencing (scRNA-seq) data from OLP lamina propria samples (GSE211630) to identify disease-specific T-cell subpopulations using high-dimensional weighted gene co-expression network analysis (hdWGCNA) for oxidative stress-related gene modules.-data-based Mendelian randomization (SMR) integrated FinnGen genome-wide association study (GWAS; 342,499 Europeans) data with Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) data to identify causal genes. Machine learning (ML) models (least absolute shrinkage and selection operator (LASSO) and convolutional neural network (CNN)) were developed using bulk RNA-seq datasets (GSE52130 and GSE38616) for diagnostic purposes. RESULTS: We identified OLP-specific T-cell populations (clusters 0, 3, 5, 7, 13, and 15) with enhanced migration inhibition factor (MIF) pathway signaling toward B cells and monocytes. Two oxidative stress-associated modules contained hub genes, including CEBPZ. Summary-data-based Mendelian randomization analysis identified 231 OLP-associated genes, with CEBPZ uniquely intersecting LASSO-selected markers (odds ratio (OR) = 1.057, 95% confidence interval (95% CI) = 1.013-1.102, p = 0.010). Machine learning models achieved area under the curve (AUC) values ranging from 0.653 to 0.745, with the CNN model reaching a validation accuracy of 0.735. CEBPZ showed elevated expression in OLP T cells and correlated with enhanced MIF-(CD74+CXCR4) signaling. CONCLUSIONS: This integrative approach identifies CEBPZ as a pivotal biomarker linking genetic susceptibility, oxidative stress, and immune dysregulation in OLP. Our diagnostic models offer promising tools for OLP management.

CEBPZ↗

PubMed2026

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) with anti-angiogenic agents is the preferred first-line therapy option for patients with advanced hepatocellular carcinoma (HCC), yet only a subset of patients responds, urging the quest for prediction biomarkers. We aimed to integrate genomics with radiology to propose an immune-derived radiogenomics biomarker of response to such combination immunotherapy and evaluate its added value in clinical context. METHODS: We integrated bulk RNA sequencing (RNA-seq) and proteomics data of 994 HCC patients with single-cell RNA-seq data of 11 samples across multiple datasets to identify an immune-related signature (IRS) that may influence sensitivity or resistance to such combined immunotherapy strategy, followed by verification of selected marker genes using immunohistochemistry and cytological experiments. We then trained/validated a cross-modality radiogenomics biomarker using machine learning based on TCIA database that was further tested in multi-scale independent cohorts covering 754 HCC patients. RESULTS: Integrative multi-omics analysis identifed a parsimonious 2-gene prognostic signature including KPNA2 and SMG5 that was significantly associated with immune heterogeneity and response to combination immunotherapy. Machine-learning pipeline exported the optimal 4-feature radiogenomics biomarker using support vector machine that significantly discriminated prognosis (hazard ratio 1.415–1.890; p < 0.05 for all) and modestly predicted response to ICI plus anti-angiogenic therapy (area under the curve 0.720–0.829) in independent retrospective series across major imaging modalities (computed tomography/magnetic resonance imaging). In a prospective neoadjuvant cohort, this biomarker also showed favorable performance for predicting pathological response and tumor recurrence, accompanied by biological validation through single-cell RNA-seq analysis of pre-treatment biopsies. CONCLUSIONS: Our study provides a cross-device-cross-modal radiogenomics biomarker that can improve patient selection for emerging ICI plus anti-angiogenic therapy with novel potential therapeutic targets in HCC.

Humans↗

PubMed2026

C-Reactive Protein-Based Composite Indices for Predicting Tumor Overgrowth Restenosis After Partially Covered Duodenal Stenting in Gastric Cancer: A Cohort Study.

BACKGROUND/OBJECTIVES: Partially covered duodenal stents rapidly relieve malignant gastric outlet obstruction, but tumor overgrowth restenosis limits durability. We compared six preprocedural inflammatory, nutritional, and immune indices for predicting this outcome in patients with gastric cancer. METHODS: We retrospectively analyzed 68 consecutive patients from a prospectively maintained cohort. The primary endpoint was endoscopically or radiologically confirmed tumor overgrowth restenosis. Discrimination was assessed using receiver operating characteristic curves (pairwise DeLong tests with Bonferroni correction) and time-dependent areas under the curve (AUCs) accounting for death as a competing risk. Multivariable cause-specific Cox models were restricted to preprocedural covariates; post-stenting chemotherapy or radiotherapy was examined in time-dependent sensitivity analyses. RESULTS: Technical and clinical success rates were 100% and 94.1%. Seventeen patients (25.0%) developed restenosis at a median of 66 days. The C-reactive protein-albumin-lymphocyte (CALLY) index showed the highest AUC (0.859), followed by the C-reactive protein-to-albumin ratio (CAR; 0.822) and neutrophil-to-lymphocyte ratio (0.774); these three indices did not differ significantly. At an exploratory, internally derived cutoff of ≤0.110, CALLY had 76.5% sensitivity and 84.3% specificity and remained associated with restenosis after adjustment for stenosis site and stent length (adjusted hazard ratio, 12.30; 95% confidence interval, 3.89-38.83; C-index, 0.836), with consistent results in continuous, time-dependent, and tumor-covariate-adjusted analyses. The 180-day cumulative incidence was 52.4% with low CALLY versus 4.3% with high CALLY. CONCLUSIONS: C-reactive protein-based indices showed the highest numerical discrimination, although pairwise differences among CALLY, CAR, and NLR were not statistically significant. CALLY is a promising exploratory biomarker for restenosis risk stratification, but its cutoff should not guide clinical decisions until externally validated.

C-reactive protein↗

PubMed2026

One-carbon metabolism and chemotherapy-induced toxicities in patients with stage II-III colorectal cancer: a prospective cohort study.

BACKGROUND: One-carbon metabolism (OCM) is a target of the chemotherapeutic agent capecitabine. OBJECTIVES: We investigated OCM biomarker concentrations in relation to capecitabine-induced toxicities in patients with stage II-III colorectal cancer. METHODS: Within a prospective cohort, 297 patients receiving adjuvant capecitabine-based chemotherapy were included. Pretreatment plasma concentrations of the OCM biomarkers folate, vitamin B2, vitamin B6, vitamin B12, total homocysteine, methionine, serine, and glycine were determined. We also investigated whether associations differed according to methylenetetrahydrofolate reductase (MTHFR) C677T genotypes. Chemotherapy-induced toxicities were defined as toxicity-induced modifications of capecitabine treatment. To allow for inspection of shapes of the associations, restricted cubic splines and Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for age and sex. RESULTS: In total, 156 (53%) patients experienced toxicity-induced modifications of capecitabine treatment. Folate was not associated with toxicities in the overall population. Higher folate concentrations were associated with a lower risk of toxicities in patients with MTHFR C677T CT/TT genotype (HRperdoubling: 0.75; 95% CI: 0.57, 0.98) but not in patients with CC genotype (HRperdoubling: 1.17; 95% CI: 0.84, 1.63). Higher concentrations of vitamin B2 were associated with a lower risk of toxicities (HRperdoubling: 0.81; 95% CI: 0.67, 0.99), whereas higher glycine concentrations were associated with a higher risk of toxicities (HRperdoubling: 1.87; 95% CI: 1.18, 2.94). The association between vitamin B6 and vitamin B12 and toxicities appeared nonlinear. Homocysteine, methionine, and serine were not associated with toxicities. CONCLUSIONS: Future studies investigating whether nutrition-guided optimization of OCM biomarkers will result in improved treatment tolerance are warranted.

Humans↗

PubMed2025

Genome-wide methylation biomarkers and biological aging in patients with bipolar disorder characterized for lithium response.

BACKGROUND: Epigenetic mechanisms might play a role in modulating susceptibility to bipolar disorder (BD) and response to lithium, the mainstay treatment for BD. Additionally, individuals with BD experience accelerated biological aging. METHODS: We compared blood DNA methylation profiles measured with EPIC v.2.0 arrays between patients with BD (33 lithium responders and 31 nonresponders) and nonpsychiatric controls (n = 32), as well as based on long-term lithium response. In addition, we compared cellular aging between these groups using epigenetic age, pace of aging, and, for the first time, transcriptional age acceleration based on bulk RNA sequencing in 93 patients and 56 controls. RESULTS: We identified 191 differentially methylated positions (DMPs) and 8 differentially methylated regions between patients with BD and controls, located in genes enriched for "Postsynaptic Density" (odds ratio = 6.81, p = 0.001). No DMP was significantly associated with lithium response after multiple testing correction. Patients showed a significantly higher biological age acceleration than controls based on two epigenetic clocks (GrimAge, Mann-Whitney U = 551, p = 0.0009; GrimAge2: U = 477, p = 9.0E-05) and pace of aging (DunedinPACE, t = 3.01, p = 0.003), but not on transcriptional age. While we observed no significant difference in epigenetic aging based on lithium response, lithium responders showed lower epigenetic acceleration using all clocks, with a trend observed using the PhenoAge clock (t = 1.97, p = 0.053). CONCLUSIONS: Our findings point to methylation patterns characterizing BD and support the hypothesis of accelerated cellular aging in BD.

Humans↗

PubMed2026

Development and preliminary validation of plasma cell-free DNA methylation-based diagnostic prediction model for colorectal cancer detection.

BACKGROUND: Colorectal cancer (CRC) is a common malignancy associated with genetic and epigenetic alterations. Several methylation biomarkers have been investigated for non-invasive CRC detection; however, their reported performance varies across clinical settings, and the detection of early-stage or precancerous disease and discrimination from non-malignant colorectal conditions remain challenging. This exploratory study aimed to identify reproducible CRC-associated plasma cell-free DNA (cfDNA) methylation regions and to develop and preliminarily evaluate diagnostic prediction model for distinguishing CRC from healthy controls and benign samples. METHODS: Public CRC tissue methylation datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify reproducible CRC-associated methylation alterations. Plasma cfDNA methylation was profiled using methyl-CpG-binding-domain enrichment followed by paired-end sequencing in patients with CRC, patients with colorectal polyps, and healthy controls. After quality-control filtering, 30 CRC and healthy-control samples were randomly allocated at the participant level in a 7:3 ratio to a development set comprising 10 patients with CRC and 11 healthy controls and a held-out test set comprising 4 patients with CRC and 5 healthy controls. Hypermethylated regions were selected using least absolute shrinkage and selection operator (LASSO) logistic regression. The 12-region model was evaluated in the held-out test set and subsequently applied to 10 colorectal polyp samples without refitting or recalibration. RESULTS: Tissue methylation analysis identified reproducible CRC-associated alterations across independent datasets. In the plasma development set, 707 differentially methylated regions (DMRs) were identified between CRC and healthy-control samples, including 324 hypermethylated and 383 hypomethylated regions. LASSO regression selected a 12-region hypermethylation signature. In the held-out test set, the model achieved an area under the curve (AUC) of 0.85 [95% confidence interval (CI): 0.579-1.000]. At the development-set-derived threshold, sensitivity was 75.0% (3/4), specificity was 60.0% (3/5), and accuracy was 66.7% (6/9). When the original model was applied to colorectal polyp samples, model scores were significantly higher in both CRC and polyp samples than in healthy controls, while CRC samples showed a tendency toward higher scores than polyp samples. CONCLUSIONS: This exploratory study identified a 12-region plasma cfDNA hypermethylation signature associated with CRC and developed a LASSO-based diagnostic prediction model that showed preliminary discrimination between CRC and healthy controls in a small held-out test set. By integrating tissue methylation evidence with plasma cfDNA profiling, this study expands the repertoire of candidate region-level methylation markers for blood-based CRC detection.

Colorectal cancer (CRC)↗