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PubMed2026

Diagnostic Accuracy of Circulating Tumor DNA to Predict Retroperitoneal Histology in Patients Treated With Retroperitoneal Lymph Node Dissection for Testicular Germ Tumor.

Testicular germ cell tumor (GCT) has survival rates exceeding 90% and thus contemporary research has focused on reducing morbidity. While chemotherapy is efficacious, long-term effects are significant. Primary retroperitoneal lymphadenectomy (P-RPLND) has been offered, and postchemotherapy lymphadenectomy (PC-RPLND) is considered, based on residual node size, to reduce overtreatment. A significant number of patients have necrosis in the retroperitoneum and are thus overtreated. Circulating tumor DNA (ctDNA) may be used to determine which patients would benefit from RPLND. This retrospective analysis sought to determine the performance of ctDNA to detect retroperitoneal GCT only, teratoma only, and GCT/teratoma. All patients had a ctDNA obtained preoperatively and at 3, 6, and 12 months postoperatively. Ninety-two patients underwent P or PC-RPLND. The sensitivity, specificity, and positive predictive values (PPVs) and negative predictive values (NPVs) for detecting active GCT/teratoma in the entire cohort were 60%, 87%, 96%, and 30%, respectively. For GCT only these were 85%, 75%, 73%, and 86%. For teratoma only, these were 31%, 34%, 23%, and 43%. These findings indicate that patients with a positive ctDNA likely harbor active GCT and/or teratoma, as suggested by a PPV of 96%. Future studies may use whole-genome ctDNA assays to improve detection of teratoma and incorporate ctDNA into surveillance protocols.

Humans↗

PubMed2026

Translational Gap in Biomarker Discovery: Tumor Surface Markers Rarely Mirror Circulating Levels.

BACKGROUND: Tumor-associated cell surface proteins are frequently proposed as circulating biomarkers for colorectal cancer (CRC) based on their high tumor expression. However, many candidates identified through tissue-based analyses fail to translate into clinically useful biomarkers. We investigated the translational gap between tissue-level expression and circulating detectability in CRC, focusing on molecular subtypes defined by caudal-type homeobox 2 (CDX2) expression. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to identify cell surface markers differentially expressed between CDX2-Low and CDX2-High CRCs. A clinical cohort of right-sided CRC patients was evaluated using paired tumor tissue and preoperative plasma samples. CDX2 expression was assessed by immunohistochemistry, and circulating concentrations of selected cell surface proteins were quantified using a multiplex ELISA platform. RESULTS: Several tumor-associated cell surface markers exhibited marked CDX2-dependent differences in tissue expression. However, for most markers, circulating plasma levels did not mirror tissue-level patterns. CEACAM1 was the sole marker demonstrating concordant CDX2-dependent differences in both tumor tissue and plasma, with significantly lower levels in CDX2-Low CRCs. In contrast, CEACAM5 showed a dissociation between tissue expression and circulating levels, despite analytical validation against serum carcinoembryonic antigen (CEA). CONCLUSIONS: Our findings demonstrate that tumor overexpression of cell surface markers does not necessarily translate into detectable circulating biomarkers. This translational disconnect underscores limitations of biomarker selection strategies based solely on tissue expression and highlights the importance of integrating systemic biology into biomarker development. While some tumor-associated proteins may lack utility as circulating biomarkers, they may still represent viable therapeutic targets in CRC.

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PubMed2026

Variability in β-human chorionic gonadotropin concentrations following evacuation of a hydatidiform mole pregnancy: A retrospective cohort study from Vietnam.

BackgroundGestational trophoblastic disease refers to a group of tumors defined by abnormal trophoblastic proliferation. This disease produces a distinct tumor marker, beta-human chorionic gonadotropin, which can be useful for diagnosis and follow-up. The objective of this study was to investigate the variations in serum beta-human chorionic gonadotropin levels after uterine evacuation as well and the progression of gestational trophoblastic neoplasia.Materials and methodsThis retrospective cohort study was conducted at Tu Du Hospital, Vietnam, between January 2019 and December 2020. All patients diagnosed with molar pregnancy were analyzed retrospectively based on serial serum beta-human chorionic gonadotropin levels following uterine evacuation. Post-evacuation outcomes, including relapsed molar pregnancy and gestational trophoblastic neoplasia, were also monitored.ResultsWe enrolled 560 patients with molar pregnancy, including 298 with complete hydatidiform mole and 262 with partial hydatidiform mole. Severe symptoms were more common in those with complete hydatidiform mole. Over the follow-up period, 97 cases of gestational trophoblastic neoplasia were noted. The data show that the median time to gestational trophoblastic neoplasia diagnosis was 8.75 ± 4.41 (4-26) weeks. In terms of variations in the serum beta-human chorionic gonadotropin levels, the generalized estimating equation model showed a faster decline in the complete hydatidiform mole group than in the partial hydatidiform mole group. Similarly, regression in serum beta-human chorionic gonadotropin levels was significantly more rapid in patients who progressed to gestational trophoblastic neoplasia than in those with relapsed molar pregnancy (-11,593 vs. -20,651.22 and -12,946.26 vs. -46,329.23 mUI/mL, p < 0.001).ConclusionsSurveillance of serum beta-human chorionic gonadotropin levels remains essential for gestational trophoblastic neoplasia monitoring in patients with molar pregnancy following surgical evacuation. The post-evacuation serum beta-human chorionic gonadotropin level regression curve helps distinguish gestational trophoblastic neoplasia from hydatidiform moles. Further evidence is required to strengthen these findings.

Humans↗

PubMed2023

Bovine meat and milk factor protein expression in tumor-free mucosa of colorectal cancer patients coincides with macrophages and might interfere with patient survival.

Bovine milk and meat factors (BMMFs) are plasmid-like DNA molecules isolated from bovine milk and serum, as well as the peritumor of colorectal cancer (CRC) patients. BMMFs have been proposed as zoonotic infectious agents and drivers of indirect carcinogenesis of CRC, inducing chronic tissue inflammation, radical formation and increased levels of DNA damage. Data on expression of BMMFs in large clinical cohorts to test an association with co-markers and clinical parameters were not previously available and were therefore assessed in this study. Tissue sections with paired tumor-adjacent mucosa and tumor tissues of CRC patients [individual cohorts and tissue microarrays (TMAs) (n = 246)], low-/high-grade dysplasia (LGD/HGD) and mucosa of healthy donors were used for immunohistochemical quantification of the expression of BMMF replication protein (Rep) and CD68/CD163 (macrophages) by co-immunofluorescence microscopy and immunohistochemical scoring (TMA). Rep was expressed in the tumor-adjacent mucosa of 99% of CRC patients (TMA), was histologically associated with CD68+/CD163+ macrophages and was increased in CRC patients when compared to healthy controls. Tumor tissues showed only low stromal Rep expression. Rep was expressed in LGD and less in HGD but was strongly expressed in LGD/HGD-adjacent tissues. Albeit not reaching statistical significance, incidence curves for CRC-specific death were increased for higher Rep expression (TMA), with high tumor-adjacent Rep expression being linked to the highest incidence of death. BMMF Rep expression might represent a marker and early risk factor for CRC. The correlation between Rep and CD68 expression supports a previous hypothesis that BMMF-specific inflammatory regulations, including macrophages, are involved in the pathogenesis of CRC.

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PubMed2026

Circulating tumor-associated autoantibody signatures for diagnosis and prognosis in small-cell lung cancer and lung adenocarcinoma.

BACKGROUND: Tumour-associated autoantibodies (TAAbs) are promising biomarkers for cancer detection, but their induction and clinical relevance in lung cancer remain unclear. METHODS: Serum samples from 695 individuals were analysed for TAAb profiling by protein-array screening and two-stage ELISA validation. Diagnostic models were constructed with identified TAAbs and compared with conventional tumour markers. Potential mechanisms, clinical and prognostic features of TAAb seropositivity were analysed and its presence in prediagnostic sera was evaluated to assess the potential for early detection. RESULTS: Six TAAbs for small cell lung cancer (SCLC) and four for lung adenocarcinoma (LUAD) were identified, demonstrating excellent diagnostic performance (AUC > 0.8) and outperforming ProGRP and CEA. TAAb induction correlated with antigen overexpression, somatic mutations and HLA class II amino acid polymorphisms. TAAb panel seropositivity was associated with older age and advanced stage in both subtypes, and predicted poor survival in SCLC but a favourable outcome in advanced LUAD. In prediagnostic sera, the TAAb concentration increased progressively, with detectability up to 2 years before clinical diagnosis. CONCLUSIONS: Distinct TAAb panels were identified for SCLC and LUAD, serving as accurate diagnostic markers that enable early detection and as indicators of prognosis in different clinical contexts.

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PubMed2026

Multi-Omics Biomarker Signatures for Precision Diagnosis and Prognosis in Primary Liver Cancer: A Literature Review.

Primary liver cancer (PLC) is a biologically heterogeneous group of malignancies dominated by hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and a smaller subset of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and its clinical burden remains high because current diagnostic and prognostic tools do not adequately capture molecular diversity. Conventional imaging, serum markers, and histopathological assessment remain insufficient for precise early diagnosis, subtype-resolved classification, and outcome stratification, while tissue and liquid biopsy approaches have expanded the range of analytes available for clinical assessment. Recent studies have identified candidate biomarker signatures across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and circulating layers, suggesting that integrated multi-omics profiling may better represent tumor lineage, clonal evolution, immune context, and therapeutic vulnerability than isolated molecular readouts. However, these layers are not equally mature for clinical use: genomic testing is closest to routine therapeutic application in iCCA, plasma methylation assays are advancing for HCC surveillance augmentation, and many proteomic or metabolomic panels remain validation-stage tools. Their clinical value remains constrained by sampling bias, biospecimen-dependent signal loss, assay standardization, cost, and the need for prospective validation across clinically diverse populations. This narrative review critically synthesizes current evidence on multi-omics biomarker signatures for precision diagnosis and prognosis in primary liver cancer and argues that clinically useful signatures should be question-specific, stage-aware, and specimen-aware rather than universal multi-analyte panels.

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PubMed2026

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy. Yet, no rapid, non-invasive biomarkers are available for diagnosis or screening. Urine represents an ideal analyte matrix due to its accessibility, low invasiveness, longitudinal sampling, and the kidney's central role in filtration. Here, we integrated proteomic, lipidomic, and metabolomic analyses of urine from ccRCC patients and controls to identify diagnostic biomarkers. Multi-omics profiling revealed urogenital metabolic dysregulation in ccRCC, including increased lipid metabolism, altered mitochondrial respiration signatures, and elevated urinary lipid content. We identified three urinary protein biomarkers: serum amyloid A1 (SAA1), haptoglobin (HP), and lipocalin 15 (LCN15). Using a parallel reaction monitoring mass spectrometry workflow, we developed a rapid and sensitive assay and combined these markers into a diagnostic UrineScore. The UrineScore achieved 0.96 in an area under the receiver operating characteristic curve analysis in the discovery cohort, and 0.95 in an independent validation cohort. Together, these results support the feasibility of multi-omics-guided urinary biomarker discovery and represent a step toward accessible diagnostic platforms for ccRCC.

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PubMed2026

Tumor-associated macrophages display differential protein cargo sorting in extracellular vesicles associated with poor survival in ovarian cancer.

Ovarian cancer (OC) progression and metastasis are promoted by ascites, which constitutes a central part of the tumor microenvironment (TME). In this fluid, tumor-associated macrophages (TAMs) represent a prominent immune cell type. In addition to tumor and other host cells such as TAMs, ascites is highly enriched in soluble factors as well as extracellular vesicles (EVs). How TAMs contribute to the EV compartment of the OC TME remains, however, underexplored. In this work peripheral blood monocytes from healthy donors were differentiated into monocyte-derived macrophages (MDMs) and polarized into classically activated (M1-like), alternatively activated (M2-like) and TAM-like (by ascites incubation). For all subtypes, serum-free conditioned medium was collected for 24 h and EVs were isolated and characterized by nano-flow cytometry (nFC), label-free mass spectrometry-based proteomics and electron microscopy, among others. Our results demonstrated distinct traits for EV release and cargo across the different macrophage subtypes. Specifically, TAM-like macrophages exhibited impaired release of small EVs and reduced frequency of tetraspanin-positive particles. These EV subpopulations displayed sizing profiles closer to M1-like than to M2-like samples. Also, the low EV release in TAM-like MDMs was accompanied by altered expression of biogenesis-related markers like flotillin-1 (FLOT1) and a decreased N-glycosylation of CD63 protein, which was validated in patient-derived samples. Remarkably, the EV-associated proteome of TAMs displayed significant enrichment in both pro- and anti-inflammatory molecules with clinical value. Markers significantly enriched in the ascites TAM-EV signature were mostly associated with poor prognosis, whereas M1-like EV-related markers (pro-inflammatory) were mostly associated with longer survival. Our results confirmed previous data for proteins like CD163 and MRC1 to be associated to TAM-EVs, while also describing novel candidates with diagnostic (i.e., COLEC12) and/or prognostic (i.e., MSR1) value in plasma. Taken together, our data support a unique secretory profile of TAMs in OC and provide new EV-associated biomarkers with translational impact. Our results pave the way for a better understanding of the mechanisms behind TAM-EV cargo loading and function, and how these cells participate in the TME landscape.

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PubMed2026

Development and validation of a serum peptidomic signature for early detection of asymptomatic ovarian cancer: A multi-center prospective study.

Early detection of asymptomatic ovarian cancer (asym-OC) remains a critical challenge, the failure of which underlies its high mortality. Performing serum peptidomic profiling of 843 participants in the cohort SOCFCP, we distill 1,081 initial features into a 7-marker panel for asym-OC detection via a biology-informed machine-learning (ML)-based feature selection strategy. Three markers significantly revert toward non-OC levels after surgery. Integrating the panel with age, CA125, and HE4, we develop and externally validate (n = 159) a LightGBM model, ProMS+. For early-stage OC detection, ProMS+ shows a specificity of 92.6% at 95.0% sensitivity, outperforming CA125 (44.7%), HE4 (11.2%), and Risk of Ovarian Malignancy Algorithm (ROMA) (24.0%), with an area under the curve (AUC) of 0.993. In a simulated high-risk population (n = 100,000; OC prevalence = 1%), ProMS+ yields a high AUC (0.983) and a higher positive predictive value than CA125, HE4, and Age + CA125 + HE4 combined model (0.201 vs. 0.027, 0.090, and 0.064). ProMS+ offers a promising, non-invasive, and interpretable approach for the early detection of asym-OC.

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PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

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PubMed2024

Acute strength exercise training impacts differently the HERV-W expression and inflammatory biomarkers in resistance exercise training individuals.

BACKGROUND: Human Endogenous Retroviruses (HERVs) are fossil viruses that composes 8% of the human genome and plays several important roles in human physiology, including muscle repair/myogenesis. It is believed that inflammation may also regulate HERV expression, and therefore may contribute in the muscle repair, especially after training exercise. Hence, this study aimed to assess the level of HERVs expression and inflammation profile in practitioners' resistance exercises after an acute strength training session. METHODS: Healthy volunteers were separated in regular practitioners of resistance exercise training group (REG, n = 27) and non-trained individuals (Control Group, n = 20). All individuals performed a strength exercise section. Blood samples were collected before the exercise (T0) and 45 minutes after the training session (T1). HERV-K (HML1-10) and W were relatively quantified, cytokine concentration and circulating microparticles were assessed. RESULTS: REG presented higher level of HERV-W expression (~2.5 fold change) than CG at T1 (p<0.01). No difference was observed in the levels of HERV-K expression between the groups as well as the time points. Higher serum TNF-α and IL-10 levels were verified post-training session in REG and CG (p<0.01), and in REG was found a positive correlation between the levels of TNF-α at T1 and IL-10 at T0 (p = 0.01). Finally, a lower endothelial microparticle percentage was observed in REG at T1 than in T0 (p = 0.04). CONCLUSION: REG individuals exhibited a significant upregulation of HERV-W and modulation of inflammatory markers when compared to CG. This combined effect could potentially support the process of skeletal muscle repair in the exercised individuals.

Humans↗

PubMed2024

Development of a Fit-For-Purpose Multi-Marker Panel for Early Diagnosis of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) suffers from a lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for the discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating the analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, the throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from the early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In the discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including a short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

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PubMed2026

Noise-Induced Hepatic Stress Is Associated with Transglutaminase Activation and TG7 Upregulation in Rats.

OBJECTIVE: Environmental noise is increasingly recognized as a systemic stressor capable of inducing oxidative and inflammatory responses beyond the auditory system. This study aimed to investigate the effects of chronic noise exposure on transglutaminase (TG) activation, particularly TG7, and its association with hepatic stress responses in rat liver tissue. METHODS: Thirty adult male Wistar albino rats were randomly assigned to control, short-term noise exposure (LT1), and long-term noise exposure (LT2) groups. Gene expression of TG isoforms (TG1, TG2, TG3, TG6, and TG7), inflammatory markers (IL6 and TNF-α), and apoptotic markers (CASP3 and P53) was evaluated using quantitative real-time PCR. Total TG enzymatic activity was assessed colorimetrically. TG7 protein expression and localization were examined by immunohistochemistry and immunofluorescence. DNA integrity was evaluated by agarose gel electrophoresis. Biochemical parameters, including serum malondialdehyde (MDA), interleukin-1 beta (IL1β), cortisone, aspartate aminotransferase, alanine aminotransferase, glucose, insulin, and total cholesterol, were also measured. RESULTS: Noise exposure induced selective upregulation of TG isoforms, with TG7 showing the highest increase (∼10-12-fold). Total transglutaminase enzymatic activity was significantly increased in both noise-exposed groups, with a higher increase in LT1 (*** P < 0.001) and a significant increase in LT2 (** P < 0.01) compared with control, while no significant difference was observed between LT1 and LT2. IL6 and TNF-α increased progressively, particularly in LT2, whereas CASP3 expression was elevated in LT1 but reduced in LT2. DNA analysis revealed mild alterations in genomic integrity without clear internucleosomal fragmentation. TG7 protein showed strong localization within hepatocyte cytoplasm and perisinusoidal regions. Biochemical analysis demonstrated significant increases in MDA (up to 61.28%), IL1β, cortisone, liver enzymes, glucose, insulin, and total cholesterol. CONCLUSION: Chronic noise exposure induces early TG activation, particularly TG7, accompanied by sustained oxidative stress and inflammatory responses in liver tissue. These findings identify TG7 as a potential stress-responsive mediator in noise-induced hepatic injury.

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PubMed2026

Potential evaluation of SULT1A3 as an early diagnostic marker for nasopharyngeal carcinoma: a study based on serum proteomics screening and ELISA validation.

BACKGROUND: Nasopharyngeal carcinoma (NPC) represents a highly prevalent and aggressive malignancy endemic to Southeast Asia. Early and accurate diagnosis is critical to improving survival outcomes; however, the absence of robust, stage-specific biomarkers remains a key obstacle to clinical implementation of early screening strategies. METHODS: We performed untargeted serum proteomic profiling using mass spectrometry in 15 treatment-naïve early-stage NPC patients and 15 VCA-IgA-positive healthy controls. Bioinformatics analyses were conducted to identify differentially expressed proteins (DEPs). Machine learning (random forest combined with recursive feature elimination) was employed to prioritize candidate biomarkers, which were subsequently verified using enzyme-linked immunosorbent assay (ELISA) in independent sample cohorts. RESULTS: In total, 1,428 serum proteins were identified, among which 1,410 were reliably quantified. We observed 31 upregulated and 189 downregulated proteins in NPC patients relative to controls. Spearman correlation analysis revealed significant associations: LTA4H (leukotriene A4 hydrolase) levels correlated with serum cell infiltration (r = 0.383, p = 0.032) and CD8 + T-cell abundance (r = 0.408, p = 0.021); both SULT1A3 (sulfotransferase family 1 A member 3) and FGL1 (fibrinogen-like protein 1) levels were positively associated with M1 macrophage infiltration (r = 0.510, p = 0.003 and r = 0.430, p = 0.015, respectively). In a preliminary validation cohort (n = 80), ELISA yielded AUC values of 0.631 (95% CI: 0.515-0.736, p = 0.04) for LTA4H, 0.787 (95% CI: 0.681-0.871, p < 0.001) for SULT1A3, and 0.688 (95% CI: 0.575-0.787, p = 0.002) for FGL1. In large-scale independent validation, SULT1A3 achieved an AUC of 0.826 (95% CI: 0.766-0.876; sensitivity = 78.89%, specificity = 75.47%) in cohort 1 (n = 196) and 0.796 (95% CI: 0.723-0.857; sensitivity = 76.67%, specificity = 76.67%) in cohort 2 (n = 150). CONCLUSIONS: Through an integrated workflow combining proteomic screening, machine learning prioritization, and multi-stage ELISA validation, we identified SULT1A3 as a candidate serum-based biomarker for early detection of NPC. Preliminary findings suggest that SULT1A3 may have potential utility in clinical screening, though further validation in independent, multi‑center cohorts is required.

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