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Yu Liu

Publications and source records attributed to Yu Liu.

At least 19 recordsLinked to original sources
PubMed2026

Assessing the accuracy and efficiency of an electronic platform for managing childhood illnesses in rural China: A cluster randomized controlled trial.

OBJECTIVES: The Integrated Management of Childhood Illness (IMCI) faces challenges in capacity building and quality control. This trial aims to assess an electronic IMCI (eIMCI) platform in improving the effectiveness and efficiency in disease classification and management by community health workers (CHWs). DESIGN: Cluster randomized controlled trial. SETTING: Rural western China. PARTICIPANTS: 24 CHWs and 72 ill children aged 2 months to 5 years (3 children per CHW). CHWs were randomly assigned to intervention or control groups. INTERVENTIONS: The intervention CHWs received online training and performed disease management using the eIMCI platform featuring integrated training modules and decision-support tools. The control group received traditional face-to-face training and used paper-based IMCI protocols. MAIN OUTCOME MEASURES: Proportion of children correctly diagnosed or classified by CHWs, as determined by a pediatric specialist. Relative risk (RR) between groups was estimated using Poisson Generalized Linear Mixed Models incorporating a random intercept for CHW to account for clustering of children within individual CHWs and adjusting for key covariates at both the CHW and child levels. RESULTS: The intervention group (13 CHWs, 39 children) had a higher rate of correct classification (64.1%) compared to the control group (11 CHWs, 33 children) (39.4%, P&#x2009;=&#x2009;.056). Multivariable regression analysis confirmed this (RR&#x2009;=&#x2009;2.1, 95% CI: 1.5-3.1; P&#x2009;<&#x2009;.001). No significant difference was found in correct treatment rates (38.5% vs. 27.3%, P&#x2009;=&#x2009;.316). Online training reduced time and costs by approximately 80%, though with a slight decrease in post-training evaluation scores. CONCLUSIONS: The eIMCI platform shows potential in enhancing IMCI implementation and significantly reducing the training burden in resource-limited settings. Trial registration: Chinese Clinical Trial Registry: ChiCTR2100042533, https://www.chictr.org.cn/showproj.html?proj=119995.

Humans↗
PubMed2026

Serum Olink Proteomics Reveals Novel Biomarkers for Early Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor in China, and early diagnosis critically affects the prognosis. Current imaging and pathological biopsy techniques have limitations, including high invasiveness and limited accessibility, while the insufficient sensitivity of serum biomarkers (such as AFP) restricts their use in early screening. In this study, using the Olink proteomics platform based on the proximity extension assay (PEA), we screened for hepatocellular carcinoma-related differentially expressed proteins (DEPs) and constructed a multiprotein diagnostic model. In the discovery cohort, we included 15 patients with newly diagnosed HCCs and 16 healthy controls. DEPs were identified using Olink, and their diagnostic performance was analyzed to identify the candidate biomarkers. In an independent validation cohort, including 116 HCC patients (50 early stage, 66 late stage) and 83 healthy controls, we further validated the expression levels and diagnostic performance of identified proteins&#x2500;C1QA and GFER. The C1QA and GFER expression levels were significantly higher in the serum of patients with early and late HCC stages compared to healthy controls. By constructing a multiprotein diagnostic model, we identified C1QA, GFER, and AFP as the optimal diagnostic combination, demonstrating a combined diagnostic AUC of 0.92 and 0.99 for early-stage and advanced-stage HCC, respectively.

Humans↗
PubMed2026

Thalamic NRXN1-mediated input to human cortical progenitors drives excitatory neurogenesis.

The human cerebral cortex develops through coordinated signals from within the cortex and from other brain regions, including the thalamus. However, how thalamic neuronal projections influence early human cortical development remains less well-understood. In this study, we fused cortical and thalamic organoids to investigate how thalamic input shapes the maturation of human cortical cells. Using single-nuclei RNA-sequencing and cellular imaging, we found that thalamic input increases the production of cortical excitatory neurons. We identify neurexin-1 (NRXN1) as a mediator of physical contact between thalamic axons and cortical outer radial glia. Genetic knockout of thalamic NRXN1 reduced these contacts and attenuated the production of upper-layer excitatory neurons. These findings reveal a mechanism by which thalamic input regulates human cortical progenitors and shapes excitatory neuron production during development.

Animals↗
PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline&#xff1a;A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗
PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗
PubMed2026

Glutathione reductase deficiency potentiates the immunogenicity of ferroptosis and cuproptosis via amplified reactive oxygen species accumulation and cGAS-STING pathway activation.

BACKGROUND: Cancer remains a major therapeutic challenge due to drug resistance and metastasis, processes driven by oxidative stress and redox imbalance. Targeting this vulnerability through ferroptosis (iron-dependent lipid peroxidation) and cuproptosis (copper-driven mitochondrial dysfunction), two ROS-mediated cell death pathways, offers a promising therapeutic strategy. However, clinical translation is hindered by incomplete understanding of their redox regulation and limited immunogenicity. METHODS: A genome-wide CRISPR knockout screen was performed to identify key regulators of ferroptosis. Genetic depletion or pharmacological inhibition of candidate genes was evaluated across multiple cancer cell lines for sensitivity to ferroptosis inducer RSL3 and the cuproptosis inducer elesclomol (Es). Antitumor efficacy was assessed in xenograft, orthotopic, metastatic, and syngeneic mouse models, alone or combined with immune checkpoint inhibitors. Mechanistic studies also examined ROS production, mitochondrial stress, mitochondrial DNA release, cGAS-STING activation, and immune responses within the tumor microenvironment. RESULTS: Glutathione reductase (GSR), a central enzyme maintaining reduced glutathione (GSH) homeostasis, was identified as the top suppressor of ferroptosis. GSR knockout or pharmacological inhibition markedly sensitized diverse cancer cell lines to RSL3-induced ferroptosis, while GSR overexpression conferred resistance. Strikingly, GSR depletion also enhanced sensitivity to cuproptosis triggered by the copper ionophore Es. In multiple in vivo tumor models, GSR inhibition synergizes with RSL3 or Es to suppress tumor growth, inhibit lung metastasis, and prolong survival. Mechanistically, GSR deficiency amplified ROS production, induced mitochondrial stress, and triggered the cytosolic mitochondrial DNA release under ferroptotic or cuproptotic stress, activating the cGAS-STING pathway in vitro and in vivo. This increased inflammatory cytokine production, promoted immunogenic cell death, and enhanced the release of damage-associated molecular patterns (DAMPs), including HMGB1. Together, GSR inhibition combined with a ferroptosis or cuproptosis inducer transformed the tumor microenvironment into a highly immune stimulatory state, thereby enhancing the efficacy of immune checkpoint blockade through increased dendritic cell activation and T-cell infiltration and activation. CONCLUSIONS: GSR represents a key molecular node connecting and modulating ferroptosis and cuproptosis through redox regulation. Targeting GSR amplifies ROS-mediated immunogenic cell death, triggers cGAS-STING activation in cancer cells, and enhances the efficacy of cancer immunotherapy, providing a promising redox-based therapeutic strategy.

Ferroptosis↗
PubMed2026

Multi-Omics Analysis Reveals Molecular Networks and Key Pathways Associated with Cysteine- and Methionine-Mediated Biosynthesis of Sulfur-Containing Flavor Metabolites in Lentinula edodes.

Lentinula edodes is renowned for its unique aroma, which is characterized by various volatile sulfur-containing flavor metabolites (SCFMs). Cysteine and methionine could enhance the SCFMs biosynthesis in L. edodes; however, the underlying metabolic pathways remain unclear. To bridge this gap, integrated proteomic and metabolomic analysis were performed to decipher pathways through which cysteine and methionine regulate SCFM biosynthesis. Results showed that exogenous cysteine and methionine supplementation significantly increased the content of lenthionine, the key aroma compound of shiitake mushrooms. Both treatments induced substantial changes in the proteomic and metabolomic profiles. Proteomic analysis revealed that differentially expressed proteins were predominantly enriched in cysteine and methionine metabolism and sulfur metabolism following cysteine treatment, whereas methionine treatment mainly affected proteins associated with tryptophan metabolism and sulfur metabolism. Metabolomic analysis showed that differentially accumulated metabolites were significantly enriched in D-amino acid metabolism and cysteine and methionine metabolism, with glutathione metabolism specifically enriched under cysteine treatment. Integrated omics analysis further uncovered distinct sulfur metabolite-protein regulatory networks under different sulfur nutrition and identified treatment-specific hub proteins. These findings establish a molecular regulatory framework linking SCFM biosynthesis with broader primary metabolic pathways involved in sulfur intermediate generation and regulation, providing new insights into the potential regulatory networks underlying SCFM formation in L. edodes.

Methionine↗
PubMed2026

Architectural logic of the 3D genome: mechanisms of dysregulation and emerging cancer therapeutics.

The three-dimensional (3D) genome provides an essential layer of organization that shapes genome function in space and time. Chromatin compartments and topologically associating domains (TADs) arise from the interplay between intrinsic properties of chromatin and architectural factors, including cohesin and CTCF. Despite substantial progress in defining these structural features, whether 3D genome architecture plays a causal role in regulating processes such as transcription, DNA replication, and DNA repair, or instead reflects underlying regulatory activity, remains unresolved. Here, we use the distinction between chromatin-intrinsic features and architectural factors as a framework to evaluate evidence for causality in genome structure-function relationships. We extend this framework to cancer, where both intrinsic alterations (including noncoding mutations, structural variants, and changes in chromatin state) and architectural factor perturbations (such as mutations in architectural proteins and dysregulation of transcriptional machinery) disrupt genome organization and contribute to disease progression. These findings suggest that alterations in genome structure can, in some contexts, actively reshape oncogenic programs. A major limitation in applying 3D genome insights to cancer biology is the cost and complexity of omics assays. Recent advances in artificial intelligence (AI) and machine learning (ML) enable inference and prediction of 3D genome organization from sequence and epigenomic features, providing insight into the extent to which genome folding is encoded intrinsically versus dynamically regulated in architectural factors. This perspective provides a unified view of how genome structure is established, how it relates to function, and how its disruption contributes to tumorigenesis.

3D genome↗
PubMed2026

Simultaneous removal of nitrogen, Cu2+, and bisphenol A in a hydrogel-biochar-AQDS immobilized bioreactor with added bicarbonate: Performance and metagenomic insights.

As the complexity of industrial wastewater pollution continues to increase, the simultaneous removal of nitrogen, metal contaminants, and persistent organic pollutants under low carbon conditions has become a key challenge for biological treatment systems. To address the operational instability and dependence on carbon sources observed in immobilized systems when exposed to copper (Cu2+) and bisphenol A (BPA), the Pseudoalteromonas japonicus strain LY0623 was integrated into a hydrogel-biochar-AQDS composite carrier to construct a multifunctional immobilized biofilm system. Notably, under conditions containing only NaHCO3, the R4 system achieved an NH4+-N removal rate of 89%. Under conditions where Cu2+ and BPA coexist, the R4 system achieved removal of NH4+-N (89%), NO3--N (100%), Cu2+ (85%), and BPA (88%). Sediment characterization confirmed that Cu2+ was immobilized through adsorption, complexation, and microbiologically induced carbonate precipitation (MICP). Metagenomic analysis further indicated that the Pseudomonadota phylum remained the dominant phylum, while functional pathways associated with inorganic carbon assimilation, HNAD nitrogen metabolism, endogenous carbon transformation, biomineralization, electron transfer, and aromatic compound degradation were preserved. By combining ammonia oxidation driven energy production, inorganic carbon utilization, redox mediated processes, and biomineralization, this study provides a highly promising low carbon strategy for treating industrial wastewater containing mixed pollutants.

Bisphenol A Compounds↗
PubMed2026

Efferocytosis related KCTD12 is a clinico-immune target in lung adenocarcinoma.

BACKGROUND: Efferocytosis, the clearance of apoptotic cells by phagocytes, contributes to immune homeostasis but may also promote tumor immune tolerance. However, its transcriptional landscape and clinical relevance in lung adenocarcinoma (LUAD) remain incompletely understood. METHODS: We systematically analyzed efferocytosis-associated genes across TCGA and multiple GEO datasets to classify LUAD subtypes and construct a prognostic risk model. The prognostic and immunological relevance of this model was validated in four independent cohorts and further assessed through immune infiltration, genomic, and immunotherapy datasets. Functional and pharmacogenomic analyses were performed to identify potential therapeutic vulnerabilities, and the efferocytosis-associated signature gene KCTD12 was subsequently validated in vitro. RESULTS: Unsupervised clustering identified two efferocytosis-based LUAD subtypes with distinct prognostic and immune-metabolic characteristics. The derived risk model robustly predicted overall survival across validation cohorts. Among the model genes, KCTD12 emerged as an efferocytosis-associated candidate linked to an immune-active tumor microenvironment. Across the analyzed single-cell, spatial transcriptomic, and immunotherapy-treated cohorts, higher KCTD12 expression was associated with enhanced cytotoxic T-cell activity and more favorable treatment outcomes. Functional experiments confirmed that KCTD12 suppresses tumor cell proliferation, reduces colony formation, and enhances OT-1 CD8+ T-cell activation and cytotoxicity. CONCLUSIONS: Our study identifies an efferocytosis-associated transcriptional program linked to immune heterogeneity and prognosis in LUAD. The efferocytosis-related risk signature provides a framework for prognostic and immune stratification, while KCTD12 represents a candidate biomarker associated with immune activation and clinical outcomes in immunotherapy-treated cohorts. Its treatment-specific predictive value requires prospective validation in appropriately controlled studies.

KCTD12↗
PubMed2026

The mechanism by which long-term exposure to TDCIPP promotes cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice: Insights from multi-omics studies.

Tri(1,3-dichloro-2-propyl) phosphate (TDCIPP) is a commonly used organophosphate ester that has the potential to adversely affect human health. Although previous studies have closely associated TDCIPP with cognitive impairment, the underlying mechanisms remain unclear. To elucidate the neurotoxic effects of TDCIPP and its mechanistic contribution to cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice, a multi-omics approach incorporating proteomics, untargeted metabolomics, and 16S ribosomal RNA (rRNA) gene sequencing was employed to evaluate the impact of TDCIPP exposure on neurobehavioral function. TDCIPP exposure promoted cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice. Proteomic analyses revealed that this promotion is associated with disturbances in the hippocampal mitochondrial autophagy pathway. Furthermore, TDCIPP may interfere with the PINK1/Parkin-mediated mitophagy pathway at the functional level, without altering PINK1 protein abundance. Untargeted metabolomic analysis of urine samples demonstrated that TDCIPP exposure altered the metabolic profile of 3&#x202f;&#xd7;Tg-AD mice, with 58 metabolites upregulated and 11 downregulated. Additionally, 16S rRNA sequencing revealed substantial modifications in gut microbiome composition following exposure to TDCIPP. Notably, significant correlations were identified between the perturbed bacterial genera and the differential metabolites. In conclusion, exposure to TDCIPP promotes cognitive impairment in 3&#x202f;&#xd7;Tg-AD mice, which is associated with the interference with the PINK1/Parkin-mediated mitophagy pathway, as well as alterations in the urinary metabolome and gut microbiota. These findings suggest the potential to mitigate such cognitive impairment by targeting the microbiota-gut-brain axis.

Animals↗
PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12&#xa0;min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22&#xa0;ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗
PubMed2026

Oxidative Stress Associated LncRNAs as Potential Biomarkers for Prognosis and Immune Responses in Lung Squamous Cell Carcinoma Patients.

Long-chain non-coding RNA (lncRNA) significantly influences lung squamous cell carcinoma's (LUSC) prognostic value and immune infiltration. This study aimed to demonstrate how oxidative stress-related lncRNAs impact lung squamous cell carcinoma (SCC). The Cancer Genome Atlas (TCGA) dataset gathered transcriptome information and related clinical data for LUSC. To build a prognostic model, 10 prognostic-related genes were identified using a series of bioinformatics analyses that compared the OS gene's aberrant expression in tumor and healthy tissues, as well as its association with malignancy. Subjects were stratified into high- and low-risk groups based on the median risk score derived from the 10-gene signature. While the mathematical risk model demonstrated limited independent predictive performance in the validation cohort (AUC ~ 0.5), functional and immunological evaluations revealed significant differences in the tumor microenvironment (TME) across risk strata. Specifically, high-risk patients exhibited distinct immune infiltration profiles and altered immunological scores relative to their low-risk counterparts. Therefore, rather than serving as a direct clinical prediction tool, this oxidative stress-related lncRNA signature provides valuable biological insights into the immune landscape of LUSC and highlights potential therapeutic targets for further mechanistic investigation.

Humans↗
PubMed2026

Chromosome-level genome assembly of the small-sized Taihang donkey (Equus asinus).

China harbors a rich diversity of donkey breeds, with small-sized donkeys (<110&#x2009;cm) representing a largely underexplored group. Here, we present the first high-quality, chromosome-level genome assembly of a small-sized donkey, generated using PacBio HiFi sequencing (286.7&#x2009;Gb), Hi-C scaffolding (240.47&#x2009;Gb), and annotated with RNA-seq data. The final assembly has a total length of 2.7&#x2009;Gb and comprises 32 chromosomes (including both X and Y chromosomes), in which five chromosomes were fully assembled without gaps. It possesses a scaffold N50 of 106.70&#x2009;Mb and 84 contigs (contig N50&#x2009;=&#x2009;63.60&#x2009;Mb), and captures 99.2% of BUSCO genes. The assembly achieved a consensus quality value (QV) of 77.44, corresponding to an extremely low base-level error rate, indicating exceptional nucleotide accuracy. This high-quality genome provides a valuable resource for investigating genetic variation, adaptive evolution, and domestication processes in small-sized donkeys, and will facilitate the conservation and sustainable utilization of rich donkey genetic resources in China.

Animals↗
PubMed2026

The role of the external genitalia score (EGS) in evaluation of disorders of sex development.

OBJECTIVE: To investigate the utility of the External Genitalia Score (EGS) in the diagnosis of disorders of sex development (DSD) and decision-making regarding gender assignment in affected patients. METHODS: A retrospective cohort study was conducted, enrolling 114 DSD patients aged <2 years (88 reared as males, 26 reared as females) treated at our hospital between April 2005 and June 2023, alongside 40 hypospadias patients aged <2 years who underwent surgery at our institution from January to July 2023. Demographic data (age) and EGS assessments of external genitalia were collected for all participants. Statistical analyses included independent samples t-tests, Mann-Whitney U tests and Receiver Operating Characteristic (ROC) curve analysis. Specifically, EGS scores were compared between the hypospadias group and the male-reared subgroup of the DSD cohort; additionally, EGS scores were contrasted between male-reared and female-reared DSD subgroups. RESULTS: The mean age was 20.3 months in the hypospadias group, 17.9 months in the male-reared DSD group, and 18.8 months in the female-reared DSD group. EGS ranged from 5.5 to 11.5 (median 10.5) in the hypospadias group and from 1 to 12 (median 4.75) in the DSD group. ROC curve analysis was performed to compare EGS scores between the hypospadias group and the male-reared DSD subgroup. The optimal diagnostic threshold was determined by maximizing the Youden index (sensitivity + specificity - 1), which balances sensitivity and specificity. A cut-off value of &#x2264;8.50 was identified as indicative of DSD; clinically, patients with an EGS score <9 should be prioritized for DSD screening. Further comparison between male-reared and female-reared DSD subgroups yielded a threshold of 4.00. Clinically, an EGS score &#x2264;4 may suggest a preference for female gender assignment. DISCUSSION: The EGS scale is a reliable, valid, and clinically feasible tool for characterizing external genitalia in DSD patients. An EGS score of 9 can serve as an indicator for initiating detailed sex development evaluation in hypospadias patients. While gender assignment in DSD is a complex, multifactorial process, EGS scores showed a significant association with the sex of rearing in our cohort. In settings where major determinants are balanced, EGS may serve as an adjunctive descriptive parameter rather than a standalone decision-making tool.

Humans↗
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.

Humans↗