SEARCH · Search PubMed

Results for “Biomarker stratification”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Salvage therapy for radiorecurrent prostate cancer: beyond equipoise - a call for biomarker-driven stratification.

The increasing incidence of localized radiorecurrent prostate cancer demands a shift from modality-centric comparisons toward biomarker-driven patient selection. Light et al. provide a matched comparison of salvage focal therapy (sFT) versus salvage radical prostatectomy (sRP), reporting comparable 10-year cancer-specific survival but fewer complications with sFT. However, the study lacks integration of modern PSMA PET/CT restaging and genomic risk stratification (e.g., Decipher classifier), both of which could profoundly influence therapeutic outcomes. Moreover, salvage reirradiation-a promising third option-is omitted. We argue that equipoise is no longer sufficient; the field needs prospective registries or trials that stratify by imaging and genomic biomarkers, with coprimary endpoints of metastasis-free survival and patient-reported functional outcomes. We also discuss the limitations of PSMA PET/CT for small-volume lesions and the importance of validating genomic thresholds specifically in the salvage setting. Only such an approach will enable truly personalized salvage therapy.

Biomarker stratification↗

PubMed2026

DIA proteomics of FFPE renal biopsies reveals two molecular subtypes of lupus nephritis and identifies APOL1 as candidate biomarker for stratification.

INTRODUCTION: Lupus nephritis (LN) exhibits substantial clinical and pathological heterogeneity. We aimed to define proteomics-based molecular subtypes of LN and identify candidate biomarkers for subtype discrimination. METHODS: We analysed formalin-fixed paraffin-embedded (FFPE) renal biopsy specimens from 292 patients with biopsy-proven LN from four tertiary hospitals using data-independent acquisition (DIA)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics. Molecular subtypes were identified by non-negative matrix factorisation. Differential proteins, functional enrichment, immune pathway activity, protein-protein interaction networks and subtype-associated clinical/pathological features were evaluated. Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were used to identify key subtype-related features and derive a protein panel distinguishing proliferative (class III/IV) from membranous (class V) LN. RESULTS: Two stable molecular subtypes were identified, with 1002 differential proteins between them. Subtype_2 was enriched for interferon-related innate immunity, complement activation, phagocytosis-endocytosis-lysosome pathways and ribosome biogenesis/RNA metabolism, whereas Subtype_1 was characterised by keratinisation and epithelial structural remodelling. Subtype_2 was associated with higher serum creatinine, lower estimated glomerular filtration rate and higher chronicity index. APOL1 showed discriminatory value between subtypes, and serum ELISA demonstrated a consistent pattern with FFPE proteomic findings. A five-protein LASSO panel achieved an area under the curve of approximately 0.76 for distinguishing class III/IV from class V LN. CONCLUSION: DIA-based proteomic profiling of FFPE renal biopsies identifies biologically and clinically relevant LN molecular subtypes and may support tissue-informed classification and risk stratification.

Humans↗

PubMed2026

Decoding context-dependent sirtuin pharmacology in cancer: Metabolic-epigenetic switches and precision therapeutic targeting.

Sirtuins (SIRT1-SIRT7) are a family of NAD+-dependent lysine deacetylases that possess mono-ADP-ribosyltransferase activity and integrate cellular metabolic status with chromatin regulation, genome maintenance, redox homeostasis, immune responses, and adaptation to cancer therapies. Their translational value has been obscured by a recurring paradox: the same isoform may constrain malignant transformation in one setting yet support metastatic competence, stemness, immune evasion, or drug resistance in another. This review reframes that paradox as a measurable problem of context. We define a SIRT context code in which NAD+ availability and compartmentalization, subcellular localization, PTM state, chromatin occupancy, oncogenic genotype, cell lineage, and tumor microenvironment jointly determine sirtuin output. Using recent mechanistic and translational evidence, we summarize how sirtuins regulate metabolic switching, histone acetylation and lactylation, genome stability, cancer-associated fibroblast programs, regulatory T-cell enrichment, cancer stem-cell plasticity, angiogenesis, and resistance to DNA-damaging, targeted, and immune therapies. We further argue that successful sirtuin pharmacology will require context matching rather than indiscriminate activation or inhibition. Priorities include spatial and single-cell biomarker discovery, compartment-specific NAD+ measurements, PTM-resolved activity assays, structure-guided isoform-selective agents, and degrader strategies targeting non-catalytic scaffolding functions. Sirtuins should therefore be viewed as metabolic-epigenetic decision nodes rather than fixed oncogenes or tumor suppressors. However, the evidence remains predominantly preclinical, and our search identified no clinical-stage oncology trials of direct sirtuin modulators using prospective biomarker stratification, underscoring that this framework remains translationally aspirational rather than clinically validated.

Humans↗

PubMed2026

Single-cell profiling reveals a novel CAF subpopulation linking stromal heterogeneity to immune suppression in breast cancer subtypes.

BACKGROUND: The tumor microenvironment critically influences breast cancer (BC) progression, immune surveillance, and therapeutic response. Cancer-associated fibroblasts (CAFs), a heterogeneous stromal population, are key regulators of these processes, yet their subtype-specific contributions in BC remain insufficiently defined. METHODS: We integrated three single-cell RNA sequencing datasets from 29 BC patients to characterize stromal populations. Bulk RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to assess correlations between CAF subsets and immune infiltration. Gene signatures were derived to identify subtype-specific CAF-immune interactions, prognostic markers, and potential predictors of chemotherapy response. RESULTS: Three conserved stromal populations (iCAFs, myCAFs, and pericytes) were identified, along with a previously unrecognized subset, the cluster 3 (CL3) CAF-like cells, referred as metabolic stressed CAF (msCAF). msCAF cells displayed transcriptional programs associated with antigen presentation, stress response, glycolysis, and extracellular matrix remodeling. Their abundance was inversely correlated with T-cell infiltration and function, in a subtype-specific manner: triple negative breast cancer (TNBC) was enriched for msCAFs in immune-infiltrated but functionally constrained microenvironments, whereas Luminal A tumors exhibited weaker immune infiltration with heterogeneous CAF-immune associations. msCAFs were characterized by a conserved gene signature (HLA-A, HLA-C, IL32, EMP3) and subtype-specific genes related to T-cell exhaustion. Several genes demonstrated prognostic relevance with distinct patterns in Luminal A (IER3, TIMP1, TBX3, SEC61G) and TNBC (ADM, C4orf3, LDHA) tumors, as well as shared biomarkers (FN1, LOXL2, P4HA1). Multiple msCAF genes also predicted chemotherapy response, suggesting utility as treatment stratification biomarkers. CONCLUSION: msCAFs represent a clinically relevant CAF subset that drives immune suppression, impacts subtype-specific prognosis, and influences therapy response in BC. These findings highlight msCAFs as promising targets for enhancing immunotherapy and personalizing treatment strategies.

Humans↗

PubMed2026

Nested co-expression network analysis identifies compact gene clusters in a black box.

MOTIVATION: Digital analysis of biological systems requires methods capable of identifying both broad and nested gene modules reflecting complex biological processes. Existing transcriptomic methods often miss compact gene sets corresponding to subprocesses in specialized cell types, limiting insights into functional heterogeneity. RESULTS: We present Nested-WGCNA, a two-stage unsupervised network analysis algorithm designed to identify coarse-grained and fine-grained gene modules. Applied to bulk RNA-Seq data, Nested-WGCNA reveals stable modules reproducible across datasets. When validated against scRNA-Seq data, these modules correspond to both major and minor immune cell subtypes. Application to immunotherapy response datasets uncovers predictive and prognostic biomarkers, highlighting its utility in treatment stratification and biomarker discovery. AVAILABILITY: The NestedWGCNA source code and analysis pipeline are available on GitHub (https://github.com/ilyada/NestedWGCNA) and archived on Zenodo (https://doi.org/10.5281/zenodo.18959244).

Algorithms↗

PubMed2026

Proteomics as a theranostic compass in BCR::ABL1-negative myeloproliferative neoplasms: Integrating biomarker discovery with therapeutic stratification.

Classic BCR::ABL1-negative myeloproliferative neoplasms (MPNs)-polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis-are clonal haematopoietic stem cell disorders with marked heterogeneity in clinical phenotype, disease trajectory, and therapeutic response. Genomic stratification by driver and cooperating mutations only partially accounts for this variability, leaving gaps in predicting thrombotic risk, fibrotic progression, leukaemic transformation, and treatment benefit. Proteomics bridges this gap by providing function-proximal readouts of protein abundance, post-translational modifications, pathway activity, and intercellular signalling that genomics and transcriptomics cannot capture, positioning it as a theranostic platform in which the same molecular readouts simultaneously inform diagnostic stratification and therapeutic decision-making. We propose a five-stage translational framework spanning from discovery-scale mass spectrometry and affinity-based plasma profiling to targeted validation, multicentre standardisation, and machine learning-integrated clinical panels. Proteomic evidence is synthesised across the following four disease axes: clonal fitness in haematopoietic stem and progenitor cells; bone marrow microenvironmental remodelling and fibrosis; chronic inflammation and thrombosis; and leukaemic transformation. We further describe how phosphoproteomics reveals resistance mechanisms to JAK inhibitors, including AXL-MAPK bypass and PP2A-autophagy-mediated tolerance, and how protein-level biomarkers (BCL2-BCL-XL, RAS-ERK, CAMK2G, and ROCK1/2) can guide individualised therapeutic selection. Affinity-based platforms (Olink PEA and SomaScan) and spatially resolved technologies (CODEX and single-cell proteomics) complement discovery proteomics. At present, however, this evidence base is constrained by small and heterogeneous cohorts, limited cross-platform reproducibility, and a scarcity of independent external validation for candidate protein panels. Realising this vision will require multicentre standardisation, analytically validated panel assays, and prospective clinical studies that translate molecular findings into decision-grade tools for patients with MPNs.

Humans↗

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

Circulating Biomarkers Related to Mitral Valve Prolapse: Current Evidence and Mechanistic Perspective.

PURPOSE OF REVIEW: Although imaging remains central to diagnosis and risk stratification, circulating biomarkers provide complementary information reflecting myocardial stress, fibrosis, extracellular matrix remodeling, inflammation, and metabolic dysregulation. The purpose of this review is to critically evaluate current and emerging circulating biomarkers in MVP and to assess whether these biomarkers may improve individualized management of this disease. RECENT FINDINGS: Natriuretic peptides are the most validated biomarkers in MVP, consistently predicting adverse outcomes and providing complementary prognostic information that may help inform the timing of surgical intervention, particularly in asymptomatic patients with significant mitral regurgitation. In contrast, evidence supporting fibrosis and inflammation mediators, proteomics, metabolomics, and circulating microRNAs remains emerging. In arrhythmic MVP, no circulating biomarker is currently recommended for routine risk stratification. Future research should prioritize phenotype-specific MVP registries, biomarker-CMR integration, multi-omics profiling, and biomarker-guided interventional trials.

Humans↗

PubMed2026

Plasma proteomics reveal SERPINA1 and CD59 as candidate biomarkers for COVID-19 severity stratification and prognosis prediction.

BACKGROUND: COVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes. OBJECTIVES: This study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications. METHODS: Plasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses. RESULTS: Proteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value. CONCLUSION: This exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.

Humans↗

PubMed2026

Biomarkers of metastatic disease in pheochromocytoma and paraganglioma.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors with variable metastatic potential. While metastatic disease occurs in approximately 10-20% of cases, its prediction remains a major clinical challenge, as no histological system has been universally validated to reliably identify aggressive tumors at diagnosis. This review aims to provide a comprehensive and updated overview of current and emerging biomarkers of metastatic risk in PPGL, encompassing histopathological scoring systems, genetic and molecular markers, biochemical phenotyping, liquid biopsy approaches, and imaging-based biomarkers. Among established markers, germline SDHB mutation status, loss of SDHB expression by immunohistochemistry, elevated plasma 3-methoxytyramine, and histopathological scoring systems, such as GAPP and COPPS, represent the most clinically validated tools for risk stratification. Emerging biomarkers - including somatic alterations in ATRX and TERT, genomic instability indices, tumor immune microenvironment characterization, circulating tumor DNA, and oncometabolite quantification - show promise in refining prognostic assessment but require prospective validation before routine clinical implementation. Accurate risk stratification in PPGL demands a multiparametric and dynamic approach, integrating clinical, genetic, biochemical, and molecular parameters. Future progress will depend on large prospective international cohorts, standardized biomarker platforms, and biomarker-driven clinical trial designs to translate emerging molecular knowledge into improved patient outcomes.

SDHB↗

PubMed2026

Redox Regulation in Glioblastoma: Mechanisms, Biomarkers, and Therapeutic Implications.

Glioblastoma is the most aggressive primary tumor of the central nervous system, characterized by high invasiveness, rapid progression, and a poor prognosis despite the current treatment modalities. Molecular stratification, using biomarkers such as IDH1, TERT, and MGMT, is a crucial step in the 2021 WHO classification for improving diagnosis and prognosis. Oxidative stress, a feature of GB, has been identified as an important factor in the initiation, progression, and resistance to treatment. It occurs due to an imbalance between reactive oxygen species generated by mitochondrial metabolism, NADPH oxidases, and exogenous sources such as ionizing radiation and xenobiotics and antioxidant defense. This imbalance leads to DNA damage, genomic instability, and deregulation of signaling pathways involved in cell proliferation, apoptosis, and tumor progression. This review provides an overview of key oxidative stress biomarkers and their dual roles in tumor suppression and progression. It highlights how oxidative stress contributes to treatment responses and resistance to current GB treatments, including redox-adaptive mechanisms such as the Nrf2-Keap1 pathway, which promotes radioresistance. Finally, it discusses the potential of understanding these mechanisms to develop therapeutic strategies that target redox balance and homeostasis, aiming to overcome resistance and improve survival outcomes for glioblastoma patients.

Humans↗

PubMed2026

Association of HPV16 infection with p53 and survivin expression in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common malignancy of the oral cavity and a major public health concern worldwide. This study aimed to investigate the relationship between p53 and survivin expression, clinicopathologic parameters and HPV16 infection in OSCC in order to elucidate the potential role of HPV16 in its pathogenesis.The study enrolled 45 patients who underwent surgical treatment for histologically confirmed OSCC. Tumor specimens were formalin-fixed and paraffin-embedded (FFPE) and histologically analyzed using hematoxylin/eosin staining. Immunohistochemistry for p53 and survivin was performed using the DAKO system. DNA extracted from FFPE tumor tissues was analyzed for HPV16 genome presence using polymerase chain reaction (PCR). All patients were followed for three years after primary treatment.No statistically significant associations were observed between p53 or survivin expression and clinicopathologic parameters including age, gender, tumor site, grade, stage, recurrence, metastasis or HPV16 status (P > 0.05). Among HPV16-positive patients (11/45, 24.4%), low survivin expression (<5%) was found in 8/11 (73%) patients, while high p53 expression (>10%) was observed in 7/11 (64%) patients. Disease-free interval did not differ significantly between patients with low vs. high p53 (P = 0.220) or survivin expression (P = 0.580). A significant correlation was detected between p53 and survivin expression (P = 0.04). HPV16 positivity was significantly associated with the absence of p53 immunoreactivity.These findings suggest that HPV16-independent oncogenic pathways are likely predominant in OSCC, while HPV16 infection may be associated with a distinct molecular subset characterized by absent p53 expression (p53-; survivin+/-; HPV16+). These results underscore the biological heterogeneity of OSCC and may have implications for future biomarker-based stratification of patients.

HPV16↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.

Sepsis is a life-threatening syndrome characterized by a heterogeneous host response to infection that remains a major cause of mortality worldwide. Current clinical scoring systems capture organ dysfunction but fail to reflect the underlying biological diversity, limiting their utility for patient stratification and targeted therapy. This review provides a comprehensive overview of molecular biomarker approaches used to predict sepsis course and prognosis in adult patients, covering genetic, transcriptomic, proteomic, and integrative strategies up to May 2026. Here, we summarize findings from genetic association studies, along with analyses based on polygenic risk scores to aggregate genetic effects, Mendelian randomization, and rare-variant sequencing approaches. We also review transcriptomic and proteomic strategies for endotyping, and diagnostic and prognostic discrimination. Lastly, we discuss how multi-omics integration is emerging as a promising framework to assist in distinguishing causal therapeutic targets from non-causal biomarkers. We also address the challenges that still constrain clinical translation towards precision medicine.

Biomarker↗

PubMed2026

KLK6 is Associated with a Neutrophil-Dominant Immunosuppressive Microenvironment and Epigenetic Deregulation in Lung Adenocarcinoma.

INTRODUCTION: Lung adenocarcinoma (LUAD) is the most prevalent histological subtype of lung cancer and is associated with poor survival despite advances in targeted therapies. Kallikrein-related peptidase 6 (KLK6) has been implicated in several malignancies, but its expression pattern, clinical relevance, and biological function in LUAD remain incompletely characterized. This study aimed to evaluate KLK6 expression and its associations with prognosis, epigenetic regulation, immune infiltration, and migratory phenotypes in LUAD. METHODS: RNA-seq expression and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. KLK6 expression was analyzed in relation to clinicopathological parameters, survival outcomes, promoter methylation status (via UALCAN), and tumor-infiltrating immune cell abundance (via TIMER2.0). In vitro, KLK6 was knocked down using shRNA in A549 and H1299 LUAD cell lines. Cell migration was assessed by transwell assays, and the expression of Epithelial-Mesenchymal Transition (EMT)- and Wnt signaling-related markers was examined by qRT-PCR and Western blotting. RESULTS: KLK6 expression was significantly upregulated in LUAD tissues compared with normal lung tissues. High KLK6 expression was associated with poorer overall survival (HR = 1.52, P = 0.009) and disease-specific survival (HR = 1.55, P = 0.03). ROC analysis showed that KLK6 discriminated stage I LUAD from normal tissues with an AUC of 0.73. Promoter hypomethylation was observed in LUAD tumors and correlated with increased KLK6 expression. Immune infiltration analysis revealed that KLK6-high tumors exhibited reduced B-cell infiltration and increased neutrophil infiltration. Functional experiments demonstrated that KLK6 knockdown significantly suppressed cell migration, accompanied by increased E-cadherin and decreased N-cadherin, Vimentin, Wnt5a, and β-catenin expression. DISCUSSION: These findings suggest that KLK6 overexpression in LUAD is driven in part by promoter hypomethylation and is closely linked to a neutrophil-dominant immunosuppressive microenvironment. Furthermore, KLK6 appears to promote LUAD cell migration through EMT- and Wnt-related signaling pathways. Collectively, these multi-layered data position KLK6 as a potential driver of aggressive tumor behavior and a candidate biomarker for risk stratification. CONCLUSION: KLK6 is aberrantly overexpressed in LUAD and is associated with poor prognosis and enhanced migratory capacity. It may serve as a promising prognostic biomarker and a potential therapeutic target for LUAD.

KLK6↗

PubMed2026

Diagnostic and prognostic value of fibroblast growth factor 23 in acute kidney injury: systematic review and meta-analysis.

Background: Acute kidney injury (AKI) is associated with high mortality and adverse outcomes. Fibroblast growth factor 23 (FGF23) has emerged as a potential biomarker for AKI; however, its diagnostic and prognostic utility remains inconsistent.Methods: We conducted a systematic review and meta-analysis of studies evaluating circulating intact FGF23 (iFGF23) or C-terminal FGF23 (cFGF23) (PROSPERO: CRD42022302659). PubMed, EMBASE, CNKI, and Wanfang databases were searched through June 9, 2026. QUADAS-2 was used for quality assessment. A random-effects bivariate model pooled sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (SROC AUC).Results: Twenty-three studies were included: 17 diagnostic, 6 prognostic (one addressing both). For AKI diagnosis, the pooled sensitivity was 0.79 (95% CI 0.73-0.86), specificity 0.82 (95% CI 0.75-0.89), PLR 4.40 (95% CI 2.59-6.21), NLR 0.25 (95% CI 0.16-0.34), DOR 17.49 (95% CI 8.67-35.16), and SROC AUC 0.87 (95% CI 0.81-0.92). Substantial heterogeneity was observed (I2 = 67%), with iFGF23 demonstrating higher accuracy than cFGF23 (AUC 0.91 vs 0.81). For AKI mortality, pooled sensitivity was 0.77 (95% CI 0.69-0.84), specificity 0.76 (95% CI 0.70-0.82), DOR 10.89 (95% CI 6.86-17.30), and SROC AUC 0.77 (95% CI 0.70-0.83). Significant heterogeneity was noted (I2 = 86.2% for sensitivity, 80.4% for specificity). No significant publication bias was detected.Conclusions: Circulating FGF23 exhibits moderate-to-high diagnostic and moderate prognostic performance in AKI, though interpretation is limited by substantial heterogeneity. It may serve as a complementary biomarker for risk stratification, pending further validation with standardized protocols.

Humans↗

PubMed2026

The extracellular matrix in cancer-associated fibrosis: molecular mechanisms and clinical relevance.

The ECM is a dynamic component of the tumor microenvironment with a critical role in cancer progression, invasion, metastasis, immune exclusion, and response to therapy. Recent advances in proteomic analyses investigating the insoluble ECM fractions (termed "matrisome analysis"), along with single-cell RNA sequencing and spatial transcriptomics, have revealed cancer-specific patterns of ECM remodeling. These studies have identified a panel of recurrently upregulated ECM proteins, including annexin A1, fibrillin-1, fibronectin, periostin, and tenascin-C, actively contributing to tumor growth, invasion, angiogenesis, and immune exclusion. The expression of the cancer-associated ECM is largely driven by cancer-associated fibroblasts (CAFs), whose molecular diversity has been dissected through single-cell profiling and consolidated in emerging CAF atlases across cancers. By investigating the matrisome composition and CAF heterogeneity, these studies have unraveled the pivotal role of the stroma in shaping tumor biology. Based on these discoveries, ECM proteins and CAFs are now being explored as biomarkers and therapeutic targets. Future integration of multi-omics datasets with clinical outcomes will help to translate these insights into novel biomarkers for patient stratification and stroma-directed therapeutic interventions.

Humans↗

PubMed2023

Immunogenomics of cholangiocarcinoma.

The development of cholangiocarcinoma spans years, if not decades, during which the immune system becomes corrupted and permissive to primary tumor development and metastasis. This involves subversion of local immunity at tumor sites, as well as systemic immunity and the wider host response. While immune dysfunction is a hallmark of all cholangiocarcinoma, the specific steps of the cancer-immunity cycle that are perturbed differ between patients. Heterogeneous immune functionality impacts the evolutionary development, pathobiological behavior, and therapeutic response of these tumors. Integrative genomic analyses of thousands of primary tumors have supported a biological rationale for immune-based stratification of patients, encompassing immune cell composition and functionality. However, discerning immune alterations responsible for promoting tumor initiation, maintenance, and progression from those present as bystander events remains challenging. Functionally uncoupling the tumor-promoting or tumor-suppressing roles of immune profiles will be critical for identifying new immunomodulatory treatment strategies and associated biomarkers for patient stratification. This review will discuss the immunogenomics of cholangiocarcinoma, including the impact of genomic alterations on immune functionality, subversion of the cancer-immunity cycle, as well as clinical implications for existing and novel treatment strategies.

Humans↗