Biomarker Research最新文献

Arginine methylation is a critical post-translational modification that modulates protein stability, enzymatic activity, and subcellular localization, thereby shaping cell fate decisions and maintaining cellular homeostasis. As the principal enzymes catalyzing this modification, protein arginine methyltransferases (PRMTs) participate in key biological processes, including transcriptional and post-transcriptional regulation as well as signal transduction. Dysregulated PRMT activity has been increasingly linked to tumor initiation, progression, and therapeutic resistance. This review summarizes PRMT classification, structural and functional characteristics, and upstream regulatory mechanisms, offering a framework for understanding their diverse roles in cancer biology and therapeutic relevance. We further discuss the mechanistic contributions of PRMTs to multiple cancer hallmarks and highlight recent advances in the development of PRMT inhibitors. Finally, we examine current strategies for clinical translation, with particular emphasis on combination approaches involving chemotherapy, targeted therapy, and immunotherapy, thereby offering a foundation for advancing PRMT-targeted precision oncology.

Current methods for post-treatment cancer surveillance and recurrence monitoring rely mainly on biophysical imaging methods like CT and MRI. Limitations associated with these approaches include risk of radiation, high cost and sophistication in operation. Minimally invasive blood test is a very attractive alternative but there is no biomarker that is of sufficient sensitivity for this purpose. In this study, we attempted to discover novel breast cancer-associated blood plasma proteins that can fill this gap. We tested the hypothesis that genes that are co-amplified HER2 can be used as a surrogate biomarker for detection of HER2+ breast cancer. Following identification of HER2-coamplified genes via copy number variation analysis, a series of bioinformatic tools were used that eventually led to the identification of WFIKKN2 as a novel cancer-associated blood plasma protein. ELISA analysis of more than 120 plasma samples from non-cancer and cancer patients with HER2+ breast cancer revealed WFIKKN2 to have sensitivity and specificity of up to 89% and 60%, respectively. While not ideal as a diagnostic biomarker due to its moderate specificity, the high sensitivity of WFIKKN2 is suitable for the purpose of post-treatment surveillance and recurrence monitoring. The data warrants WFIKKN2 to be further evaluated through clinical studies to validate its clinical utility.

With the advancement of novel technologies such as whole-genome sequencing, single-cell sequencing, and spatial transcriptomics, single-omics analyses have already promoted the research of tumorigenesis as well as development and have partly elucidated the evolutionary processes of lung cancer. However, it is still difficult to distinguish these confounding features via single dimensional approaches due to the complexity, heterogeneity and cell-cell interactions with the immune microenvironment in lung cancer. Multi-omics approaches provide a holistic framework for constructing detailed tumor ecosystem landscapes, thereby facilitating the development of a more robust classification system for precision diagnosis and treatment, and aiding in the discovery of novel cancer biomarkers. In this review, we summarize the potential and applications of multi-omics approaches in characterizing intratumor heterogeneity and the tumor microenvironment throughout the course of lung cancer development. By further discussing the discovery and application of diagnostic and therapeutic biomarkers across precancerous lesions, early-stage lung cancer, tumor progression, metastasis, and therapy resistance, we outline the current challenges and future prospects of using multi-omics to identify reliable biomarkers. Moreover, we emphasize that integrative multi-omics models hold great promise for elucidating the complex interactions within the lung cancer ecosystem, thereby contributing to improved diagnostic accuracy, optimized therapeutic strategies, and better patient outcomes.

The biological heterogeneity between left- and right-sided colorectal cancer (CRC) poses a significant clinical challenge and the underlying regulatory mechanisms remain elusive. As an emerging hallmark of cancer, the contribution of circadian rhythm disruption (CRD) to this side-specific heterogeneity is unclear. By integrating single-cell and spatial transcriptomic analyses, this study shows that tumor cells in right-sided CRC exhibit significantly higher CRD scores and identifies the emergence of a NONO-positive tumor-cell subpopulation (NONO⁺ TC) as a key molecular feature of this phenotype. Spatial analysis further confirms that this NONO⁺ TC forms a tightly co-localized microenvironment with fibroblasts in situ. Notably, cell-cell communication analyses indicate that NONO expression does not augment the signal-sending capacity of tumor cells but instead reprograms them into highly efficient signal receivers. These augmented incoming signals predominantly originate from the more pro-tumorigenic myofibroblastic cancer-associated fibroblast (myCAF) subtype, indicating that NONO⁺ TC are particularly sensitive to malignant stromal inputs. In conclusion, our study delineates the dual role of NONO as both a circadian regulator and a pro-tumorigenic signaling hub. By enhancing tumor-cell reception of CAF-derived signals, NONO links CRD to the formation of NONO⁺ TC niches and a malignant microenvironment in right-sided CRC, providing new mechanistic insight into the spatial heterogeneity of tumors.

Background: Gut microbiota may influence Alzheimer's disease (AD) pathogenesis by modulating host homeostasis. However, population-based causal evidence linking gut dysbiosis to Alzheimer's disease pathogenesis, especially via immune, vascular, and metabolic pathways, remains insufficient.

Methods: We performed Mendelian randomization (MR) and colocalization analysis on 629 gut microbiota features and 2,103 immune, blood-brain barrier (BBB), and metabolic biomarkers regarding the risk of AD and cerebrospinal fluid (CSF) pathological biomarkers.

Results: We identified that mucin-degraders, short-chain fatty acid (SCFA) producers, and Programmed Cell Death Protein 1/Programmed Death-Ligand 1 (PD-1/PD-L1)-related biomarkers were associated with lower AD risk, while cardiovascular microbes, Amyloid-beta (Aβ)-related proteins, and lipoproteins were linked to higher risk. Increased AD risk was associated with decreased SCFA producers, branched-chain amino acids (BCAAs), and lactate, but with increased liver-disease microbes, fatty acids, and glycoprotein acetyls. Notably, Desulfovibrionaceae and Methanobrevibacter emerged as critical contributors to AD. Erysipelotrichaceae abundance inversely modulates CSF phosphorylated tau (p-tau) pathology while being increased by Aβ42 pathology, suggesting a microbiota-mediated feedback circuit in AD. Mediation analysis highlighted the role of CD28^-CD8⁺ T cells, CD19 on IgD⁺ CD24⁺ B cells, glycoproteins, and low-density lipoprotein (LDL) in microbiota-gut-brain axis bidirectional communication. Colocalization analyses confirmed causal links between AD and LDL metabolism through shared variant rs7412 (posterior probability, PP = 1.0), while revealing colocalized architecture for amyloid-tau copathology at rs71352238 (PP = 1.0).

Conclusions: Our study reveals a bidirectional gut-brain feedback loop in AD, in which gut microbiota promote neuroinflammation and immune aging, while AD exacerbates gut dysbiosis via lipid metabolic dysregulation. This self-reinforcing mechanism involving immune signaling, BBB disruption, and SCFA imbalance offers potential targets for integrated microbiota-based interventions in AD prevention.

Breast cancer remains the most prevalent cancer among women, with hormone receptor-positive (HR +) tumors accounting for approximately 70% of breast cancer cases. While the immune checkpoint inhibitor (ICI) anti-programmed cell death 1 (PD-1) pembrolizumab has demonstrated efficacy in triple-negative breast cancers (TNBCs), its benefit in HR + subtypes is limited. ICI resistance in breast cancer is largely due to a "cold" tumor immune microenvironment characterized by low tumor-infiltrating lymphocytes (TILs). To identify novel genetic determinants of immune exclusion and pembrolizumab resistance, we analyzed multi-omics and clinical datasets from the I-SPY2 clinical trial and The Cancer Genome Atlas (TCGA), focusing on genes associated with low T cell infiltration and poor response to pembrolizumab. We identified thrombospondin type-1 domain containing 4 (THSD4) as a top candidate. THSD4 expression was significantly elevated in breast tumors with low T cells and in breast cancer patients exhibiting resistance to pembrolizumab, particularly within the HR + subtype. THSD4 expression is enriched in HR + breast cancers. Validation in local patient cohorts using RNA sequencing and multiplex immunofluorescence confirmed that both high THSD4 expression and anti-THSD4 antibody staining correlated with reduced T cell infiltration in the tumor epithelium and associations with poorer clinical outcomes. Functional studies in a syngeneic mouse HR + tumor model demonstrated that THSD4 promotes an immunosuppressive tumor microenvironment, with reduced T cells, resistance to anti-PD-1, and altered collagen fiber abundance. Collectively, these findings establish THSD4 as a prognostic biomarker of pembrolizumab resistance and a potential therapeutic target to enhance immunotherapy efficacy in breast cancer.

Background: Timely differentiation between ischemic stroke (IS) and intracerebral hemorrhage (ICH) is critical for guiding appropriate acute management strategies. While neuroimaging is the diagnostic gold standard, its accessibility is often limited in urgent clinical settings. Blood biomarkers offer a promising, scalable diagnostic alternative; however, no validated panel is yet available for distinguishing stroke subtypes during the hyperacute phase.

Methods: In a multicenter study, plasma samples were collected within 6 h of symptom onset. A total of 3,072 proteins were measured using Olink® proximity extension assays. We applied differential expression analysis, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and receiver operating characteristic (ROC) curve evaluation. To interpret the biological relevance of the findings, we conducted functional enrichment and protein-protein interaction (PPI) analyses.

Results: Among the 388 patients (344 IS, 44 ICH), 2,531 proteins were retained; 878 reached nominal significance (p < 0.05), and 67 remained significant after multiple-testing correction (FDR-adjusted p < 0.05). Of these, 844 were overexpressed in ICH and 34 in IS. GFAP, a glial marker, emerged as the most discriminative biomarker for ICH versus IS (AUC = 0.887; sensitivity: 80%, specificity: 90%), followed by BCAN (AUC = 0.820), SNAP25 (AUC = 0.797), and SPOCK1 (AUC = 0.786). For IS, S100A12 (AUC = 0.677) and MNDA (AUC = 0.657) showed the best performance. Multivariate analyses confirmed the presence of distinct proteomic patterns, with enrichment revealing a significant overrepresentation of neurodevelopmental and synaptic pathways. In PPI networks, GFAP and LYN emerged as central hubs.

Conclusion: This study reveals a robust plasma proteomic signature distinguishing IS from ICH within hours of onset. These results lay the groundwork for scalable, blood-based diagnostics to guide early stroke management when imaging is delayed or unavailable.

Investigating cancer metabolism is of paramount importance for understanding tumor biology and developing novel therapeutic strategies. Lactylation, a posttranslational modification facilitated by the glycolytic product lactate, plays a crucial role in regulating oncogenic signalling pathways. This review provides a comprehensive analysis of lactate metabolism, including its biosynthesis, compartmentalized transport, enzymatic network and structural features of lactate dehydrogenases, transporters, lactyltransferases and deacetylases. These enzymes contribute to malignant tumor progression through metabolic reprogramming and modulation of the immune microenvironment. Importantly, we emphasize that integrating cancer subtype-specific lactylation profiles with core signatures reveals promising therapeutic opportunities for targeting lactate shuttles, histone, and nonhistone lactylation mechanisms, and transcriptional networks regulated by lactylation. In the present review, we highlight the significant potential of targeting glycolysis and lactylation modifications in tumors to improve the efficacy of cancer treatments.