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PubMed2006

Investigation of proteomic biomarkers in in vivo hepatotoxicity study of rat liver: toxicity differentiation in hepatotoxicants.

We investigated the overall protein expression profiles in the in vivo hepatotoxicity of rats induced by four well-recognized hepatotoxicants. Acetaminophen (APAP), amiodarone (AMD), tetracycline (TC) and carbon tetrachloride (CTC) were administered to male rats by gavages and the liver at 24 hr post-dosing was applied to the proteomic experiment. Blood biochemistry and histopathology were examined to identify specific changes related to the compounds given. Protein expression in the liver was investigated by 2-dimensional gel electrophoresis (2DE), and spots showing a significantly different expression in treated versus control group were excised from gels and identified by Q-Tof mass spectrometer. They were well characterized based on their functions related to the mechanisms of toxicity of the compounds. Among them, we focused on the 8 proteins that were affected by all 4 compounds examined. Proteins related to oxidative stress response such as carbonic anhydrase III (CA3) and 60kDa heat shock protein (HSP60), and energy metabolism such as adenylate kinase 4 (AK4) were found. Moreover, hierarchical clustering analysis using 2D-gel spots information revealed the possibility to differentiate the groups based on their toxicity levels such as severity of liver damage. These results suggested that assessing the effects of hepatotoxicants on protein expression is worth trying to screen candidate compounds at the developmental stage of drugs.

Acetaminophen↗

PubMed2006

Quality control metrics for LC-MS feature detection tools demonstrated on Saccharomyces cerevisiae proteomic profiles.

Quantitative proteomic profiling using liquid chromatography-mass spectrometry is emerging as an important tool for biomarker discovery, prompting development of algorithms for high-throughput peptide feature detection in complex samples. However, neither annotated standard data sets nor quality control metrics currently exist for assessing the validity of feature detection algorithms. We propose a quality control metric, Mass Deviance, for assessing the accuracy of feature detection tools. Because the Mass Deviance metric is derived from the natural distribution of peptide masses, it is machine- and proteome-independent and enables assessment of feature detection tools in the absence of completely annotated data sets. We validate the use of Mass Deviance with a second, independent metric that is based on isotopic distributions, demonstrating that we can use Mass Deviance to identify aberrant features with high accuracy. We then demonstrate the use of independent metrics in tandem as a robust way to evaluate the performance of peptide feature detection algorithms. This work is done on complex LC-MS profiles of Saccharomyces cerevisiae which present a significant challenge to peptide feature detection algorithms.

Algorithms↗

PubMed2026

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-β, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers↗

PubMed2026

Molecular and immune profiling of HER2-low, HER2 ultra-low, and HER2-null male breast cancer.

BACKGROUND: HER2 expression is described along a biological continuum from null to positive and serves as a critical biomarker for therapeutic guidance in breast cancer (BC). While HER2-low and ultra-low categories have emerged as actionable targets for antibody-drug conjugates (ADCs) in female BC, their molecular and immune characteristics remain largely unexplored in male breast cancer. METHODS: We profiled 214 male breast tumors using next-generation sequencing and whole-transcriptome sequencing to assess mutational, transcriptomic, and immune landscapes. Tumor mutational burden (TMB) was defined as high if > 10 mutations/Mb. Immune cell fractions were inferred using Quantiseq deconvolution. RESULTS: Among 214 samples, 66 (30.8%) were HER2-null, 53 (24.8%) HER2 ultra-low, 80 (37.4%) HER2-low, and 15 (7.0%) HER2-positive. HER2 ultra-low tumors exhibited a higher prevalence of PIK3CA mutations (39.2% vs 22.6%, p ≤ 0.05) compared to HER2-null. No significant differences were observed in TMB-high frequency or PD-L1 expression across subgroups. Immune composition differed primarily between HER2-null and HER2-expressing subgroups: HER2-ultra-low tumors showed higher B-cell infiltration, whereas HER2-null tumors were enriched in neutrophils. Transcriptomic analysis revealed upregulation of selected stemness-associated genes (NANOG, KLF4, POU5F1) and CEACAM1 in HER2-null tumors, while HER2-low and HER2-ultra-low tumors were largely similar across most molecular and immune readouts in this cohort. CONCLUSIONS: HER2-null male breast cancer appears to represent the most biologically divergent subgroup within the HER2-negative spectrum, whereas HER2-low and HER2-ultra-low tumors were largely similar in this cohort. These findings support further investigation of HER2-null disease as a distinct biological state and provide hypothesis-generating data for biomarker development in this rare population.

Male↗

PubMed2004

Evaluation of biological monitoring markers using genomic and proteomic analysis for automobile emission inspectors and waste incinerating workers exposed to polycyclic aromatic hydrocarbons or 2,3,7,8,-tetracholrodedibenzo-p-dioxins.

In this study, we investigated the effects of PAHs and dioxin on mRNA and plasma protein expression using genomic and proteomic analysis for automobile emission inspectors and waste incineration workers. About 54 workers from automobile emission inspection offices, 31 workers from waste incinerating company and 84 unexposed healthy subjects were enrolled in this study. Urine and air samples were collected and analyzed by HPLC and GC/MS. Comet assays were carried out to evaluate any DNA damage in mononuclear and polynuclear cells. A significant difference in Olive tail moments in mononuclear cells was observed between exposed and control subjects (P < 0.0001). To examine the differences of the gene expression profile in automobile emission inspectors and waste incineration workers, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 total genes. The gene expression profiles showed that 11 genes were up-regulated and 4 genes were down-regulated in waste incinerating workers as compared with controls. Plasma proteins were analyzed by 2-dimentional electrophoresis with pH 3-10 NL IPG Dry strip. The protein expression profiles showed that 8 proteins were up- regulated and 1 protein, haptoglobin, was down- regulated in automobile emission inspectors and waste incineration workers. Serum paraoxonase/ arylesterase was found only in the plasma of waste incineration workers. The expression of genes and proteins involved in oxidative stress were up-regulated in both automobile emission inspectors and waste incineration workers. Several proteins, such as transthyrethin, sarcolectin and haptoglobin, that were highly up- or down-regulated, could serve as biological monitoring markers for future study.

Adult↗

PubMed2025

Single-cell glycome and transcriptome profiling enabled by a library of anti-glycan antibodies.

Glycans play critical roles in cellular processes and clinical applications, but they remain difficult to study due to a shortage of well-characterized anti-glycan reagents and high-throughput technologies for glycome profiling, especially ones capable of single-cell resolution. To meet these needs, we generated a database of 650 anti-glycan antibody sequences, recombinantly expressed a library of 154 antibodies, and extensively characterized their binding properties using glycan microarrays. In addition to providing valuable information and resources for the field, the sequence database and microarray data also enabled development of "Glycomic-seq" (Glycome profiling via multiplexed immunoglobulins combined with sequencing), a DNA-barcoded anti-glycan antibody platform that enables high-throughput, single-cell profiling of both RNA and cell-surface glycan expression. Using Glycomic-seq, we profiled two isogenic colorectal cancer cell lines. The results revealed various glycans associated with cancer stem cells and metastasis, demonstrating the power of integrating glycomic information with multi-omic efforts to discover biomarkers and therapeutic targets.

Polysaccharides↗

PubMed2007

CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer.

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance.

Adult↗

PubMed2003

[Small but high throughput: how "tissue-microarrays" became a favorite tool for pathologists and scientists].

Progress in the knowledge of molecular genetics and availability of high-throughput technologies offer the opportunity to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. The recently developed "tIssue microarrays" (TMA) technology allows parallel molecular profiling of clinical samples. Using this technique and immunohistochemistry (IHC), fluorescence in situ hybridisation (FISH), or RNA in situ hybridisation (ISH), the pathologist is now able to perform unprecedented large-scale analyses. The advantages are significant: large number of cases assessed simultaneously for numerous markers, processed in identical conditions, from reduced amount of archival tIssues, with an excellent correlation with standard methods, and a reduction in cost and time. This Article provides a short review of this technology, and points out several aspects of the TMA construction and its applications for clinical research.

Biomarkers↗

PubMed2025

Blood from septic patients with necrotising soft tissue infection treated with hyperbaric oxygen reveal different gene expression patterns compared to standard treatment.

BACKGROUND: Sepsis and shock are common complications of necrotising soft tissue infections (NSTI). Sepsis encompasses different endotypes that are associated with specific immune responses. Hyperbaric oxygen (HBO2) treatment activates the cells oxygen sensing mechanisms that are interlinked with inflammatory pathways. We aimed to identify gene expression patterns associated with effects of HBO2 treatment in patients with sepsis caused by NSTI, and to explore sepsis-NSTI profiles that are more receptive to HBO2 treatment. METHODS: An observational cohort study examining 83 NSTI patients treated with HBO2 in the acute phase of NSTI, fourteen of whom had received two sessions of HBO2 (HBOx2 group), and another ten patients (non-HBO group) who had not been exposed to HBO2. Whole blood RNA sequencing and clinical data were collected at baseline and after the intervention, and at equivalent time points in the non-HBO group. Gene expression profiles were analysed using machine learning techniques to identify sepsis endotypes, treatment response endotypes and clinically relevant transcriptomic signatures of response to treatment. RESULTS: We identified differences in gene expression profiles at follow-up between HBO2-treated patients and patients not treated with HBO2. Moreover, we identified two patient endotypes before and after treatment that represented an immuno-suppressive and an immune-adaptive endotype respectively, and we characterized the genetic profile of the patients that transition from the immuno-suppressive to the immune-adaptive endotype after treatment. We discovered one gene MTCO2P12 that distinguished individuals who altered their endotype in response to treatment from non-responders. CONCLUSION: The global gene expression pattern in blood changed in response to HBO2 treatment in a direction associated with clinical biochemistry improvement, and the study provides potential novel biomarkers and pathways for monitoring HBO2 treatment effects and predicting an HBO2 responsive NSTI-sepsis profile. TRIAL REGISTRATION: Biological material was collected during the INFECT study, registered at ClinicalTrials.gov (NCT01790698) 04/02/2013.

Humans↗

PubMed2005

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.

OBJECTIVE: To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. METHODS: A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. RESULTS: The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. CONCLUSION: SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Adult↗

PubMed1999

Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis of effects on lipids and haemostatic factors.

OBJECTIVE: To summarise quantitatively the association between moderate alcohol intake and biological markers of risk of coronary heart disease and to predict how these changes would lower the risk. DESIGN: Meta-analysis of all experimental studies that assessed the effects of moderate alcohol intake on concentrations of high density lipoprotein cholesterol, apolipoprotein A I, fibrinogen, triglycerides, and other biological markers previously found to be associated with risk of coronary heart disease. PARTICIPANTS: Men and women free of previous chronic disease and who were not dependent on alcohol. Studies were included in which biomarkers were assessed before and after participants consumed up to 100 g of alcohol a day. INTERVENTIONS: Alcohol as ethanol, beer, wine, or spirits. MAIN OUTCOME MEASURES: Changes in concentrations of high density lipoprotein cholesterol, apolipoprotein A I, Lp(a) lipoprotein, triglycerides, tissue type plasminogen activator activity, tissue type plasminogen activator antigen, insulin, and glucose after consuming an experimental dose of alcohol for 1 to 9 weeks; a shorter period was accepted for studies of change in concentrations of fibrinogen, factor VII, von Willebrand factor, tissue type plasminogen activator activity, and tissue type plasminogen activator antigen. RESULTS: 61 data records were abstracted from 42 eligible studies with information on change in biological markers of risk of coronary heart disease. An experimental dose of 30 g of ethanol a day increased concentrations of high density lipoprotein cholesterol by 3.99 mg/dl (95% confidence interval 3.25 to 4.73), apolipoprotein A I by 8.82 mg/dl (7.79 to 9.86), and triglyceride by 5.69 mg/dl (2.49 to 8.89). Several haemostatic factors related to a thrombolytic profile were modestly affected by alcohol. On the basis of published associations between these biomarkers and risk of coronary heart disease 30 g of alcohol a day would cause an estimated reduction of 24.7% in risk of coronary heart disease. CONCLUSIONS: Alcohol intake is causally related to lower risk of coronary heart disease through changes in lipids and haemostatic factors.

Alcohol Drinking↗

PubMed2006

Nonenzymatic lipid peroxidation reprograms gene expression and activates defense markers in Arabidopsis tocopherol-deficient mutants.

Tocopherols (vitamin E) are lipophilic antioxidants that are synthesized by all plants and are particularly abundant in seeds. Two tocopherol-deficient mutant loci in Arabidopsis thaliana were used to examine the functions of tocopherols in seedlings: vitamin e1 (vte1), which accumulates the pathway intermediate 2,3-dimethyl-5-phytyl-1,4-benzoquinone (DMPBQ); and vte2, which lacks all tocopherols and pathway intermediates. Only vte2 displayed severe seedling growth defects, which corresponded with massively increased levels of the major classes of nonenzymatic lipid peroxidation products: hydroxy fatty acids, malondialdehyde, and phytoprostanes. In the absence of pathogens, the phytoalexin camalexin accumulated in vte2 seedlings to levels 100-fold higher than in wild-type or vte1 seedlings. Similarly, gene expression profiling in wild-type, vte1, and vte2 seedlings indicated that increased levels of nonenzymatic lipid peroxidation in vte2 corresponded to increased expression of many defense-related genes, which were not induced in vte1. Both biochemical and transcriptional analyses of vte2 seedlings indicate that nonenzymatic lipid peroxidation plays a significant role in modulating plant defense responses. Together, these results establish that tocopherols in wild-type plants or DMPBQ in vte1 plants limit nonenzymatic lipid peroxidation during germination and early seedling development, thereby preventing the inappropriate activation of transcriptional and biochemical defense responses.

Arabidopsis↗

PubMed2005

Preclinical drug safety analysis by chemogenomic profiling in the liver.

The economic hurdles of drug development and the emergence of genomic technologies such as chemogenomics are combining to shift the existing paradigms in preclinical drug development. Today, the information gleaned from high content molecular data has begun to augment traditional approaches to the assessment of drug safety. The optimal approach is a hybrid strategy employing chemogenomic data and gene expression-based biomarkers of drug efficacy and toxicity to supplement low content and insensitive methods for risk assessment and mechanistic evaluation of drug candidates. Large reference databases of chemogenomic data are essential to the derivation and validation of accurate and predictive gene expression biomarkers. An example of the development of a predictive biomarker for hepatic bile duct hyperplasia is described herein. As gene expression technologies improve, biomarkers will achieve higher throughput, and become more cost effective and increasingly accurate. This will elevate the value of chemogenomics in drug development, shift attrition to earlier in the process, and reduce the overall cost of drug development. Over the past 2 to 3 years, the transition of chemogenomics from a research tool to a decision-making tool has begun and regulatory agencies are anxiously awaiting implementation of this technology to make faster and more informed evaluations of potential drugs.

Animals↗

PubMed2002

Estrogen-related receptor alpha and estrogen-related receptor gamma associate with unfavorable and favorable biomarkers, respectively, in human breast cancer.

The importance of estrogen-related receptors (ERRs) in human breast cancer was assessed by comparing their mRNA profiles with established clinicopathological indicators and mRNA profiles of estrogen receptors (ERs) and ErbB family members. Using real-time quantitative PCR assays, mRNA levels of ERalpha, ERbeta, epidermal growth factor receptor, ErbB2, ErbB3, ErbB4, ERRalpha, ERRbeta, and ERRgamma were determined in unselected primary breast tumors (n = 38) and normal mammary epithelial cells enriched from reduction mammoplasties (n = 9). ERRalpha showed potential as a biomarker of unfavorable clinical outcome and, possibly, hormonal insensitivity. ERRalpha mRNA was expressed at levels greater than or similar to ERalpha mRNA in 24% of unselected breast tumors, and generally at higher levels than ERalpha in the progesterone receptor (PgR)-negative tumor subgroup (1-way ANOVA with repeated measures, P = 0.030). Increased ERRalpha levels associated with ER-negative (Fisher's exact, P = 0.003) and PgR-negative tumor status (Fisher's exact, P = 0.006; Kruskal-Wallis ANOVA, P = 0.021). ERRalpha levels also correlated with expression of ErbB2 (Spearman's rho, P = 0.005), an indicator of aggressive tumor behavior. Thus, ERRalpha was the most abundant nuclear receptor in a subset of tumors that tended to lack functional ERalpha and expressed ErbB2 at high levels. Consequently, ERRalpha may potentiate constitutive transcription of estrogen response element-containing genes independently of ERalpha and antiestrogens in ErbB2-positive tumors. ERRbeta's potential as a biomarker remains unclear; it showed a direct relationship with ERbeta (Spearman's rho, P = 0.0002) and an inverse correlation with S-phase fraction (Spearman's rho, P = 0.026). Unlike ERRalpha, ERRgamma showed potential as a biomarker of favorable clinical course and, possibly, hormonal sensitivity. ERRgamma was overexpressed in 75% of the tumors, resulting in the median ERRgamma level being elevated in breast tumors compared with normal mammary epithelial cells (Kruskal-Wallis ANOVA, P = 0.001). ERRgamma overexpression associated with hormonally responsive ER- and PgR-positive status (Fisher's exact, P = 0.054 and P = 0.045, respectively). Additionally, ERRgamma expression correlated with levels of ErbB4 (Spearman's rho, P = 0.052), a likely indicator of preferred clinical course, and associated with diploid-typed tumors (Fisher's exact, P = 0.042). Hence, ERRalpha and ERRgamma status may be predictive of sensitivity to hormonal blockade therapy, and ERRalpha status may also be predictive of ErbB2-based therapy such as Herceptin. Moreover, ERRalpha and ERRgamma are candidate targets for therapeutic development.

Biomarkers, Tumor↗

PubMed2003

Single-cell transcript analysis of pancreas development.

DNA microarray analysis was combined with a modified single-cell PCR procedure to study gene expression profiles of single cells at different stages of pancreatic development. This method identifies distinct cell types at embryonic day 10.5, a stage when the pancreatic epithelium is morphologically uniform. Some cells express unexpected combinations of genes, and these expression patterns provide new insights into pancreas development. Following on these findings, we use PCR products from different cell types to identify novel pancreatic genes, some of which mark subtypes of developing pancreatic cells. By integrating these data with previous genetic and biochemical studies, we propose a pathway for pancreatic cell development. This form of single-cell transcriptional analysis can be applied to any developmental process or tissue to characterize distinct cell types.

Animals↗

PubMed2003

pRB2/p130 target genes in non-small lung cancer cells identified by microarray analysis.

The retinoblastoma gene family consisting of RB/p105, p107, and RB2/p130 cooperate to regulate cell-cycle progression through the G1 phase of the cell cycle. Previous data demonstrated an independent role for the reduction or loss of pRb2/p130 expression in the formation and/or progression of lung carcinoma. Rb2/p130 is mutated in a human cell line of lung small cell carcinoma as well as in primary lung tumors. To identify potential pRb2/p130 target genes in an unbiased manner, we have utilized an adenovirus-mediated expression system of pRb2/p130 in a non-small lung cancer cell line to identify specific genes that are regulated by pRb2/p130. Using oligonucleotide arrays, a number of Rb2/p130 downregulated genes were identified and their regulation was confirmed by semiquantitative reverse transcription-polymerase chain reaction (RT-PCR) and Western blot analysis. As a result, 40 genes showed greater than 2.0-fold modification in their expression level after the RB2/p130 viral transduction. In conclusion, coupling adenoviral overexpression with microarray and semiquantitative RT-PCR analyses proved to be a versatile strategy for identifying pRb2/p130 target genes and for better understanding the expression profiles of these genes. Our results may also contribute to identifying novel therapeutic biomarkers in lung carcinoma.

Adenoviridae↗

PubMedDate not supplied

[Molecular biology and hepatocellular carcinoma: current status and future prospects].

Hepatocellular carcinoma (HCC) is among the fifth most common cancers worldwide. Its incidence is still rising in part because of the high level of hepatitis C virus infection. Tumor markers currently used such as serum alpha-foetoprotein are not sufficient for diagnosis of the tumor and satisfying follow-up of the patients. Mechanisms of hepatocarcinogenesis ar not completely understood although several altered genes have been described in HCC. The genetic changes involved can be divided in at least 4 different pathways, each pathway contributing to a limited number of tumors. These are: 1) the p53 pathway involved in response to DNA damage, 2) the retinoblastoma pathway involved in the control of the cell cycle, 3) the transforming growth factor-beta (TGF-beta) pathway involved in growth inhibition, and 4) the Wnt pathway involved in cell-cell adhesion and signal transduction. Alterations of the epigenetic regulation of gene expression have also been described. Evolution of molecular biology methods tends to the development of more global genomic approaches; microsatellite instability analysis, chromosomal instability analysis or gene expression profile analysis have been used to investigate HCC. Finally, attempts to develop molecular biomarkers based on peripheral blood analysis more easily accessible in clinical routine patients have also been developed.

Biomarkers, Tumor↗

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.

Humans↗