Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Biomarker Profiling”

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

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

At least 163 records · Page 9Linked to original sources

Follicular lymphoma: today's treatments and tomorrow's targets.

Over the past two decades, the incidence of follicular lymphoma has increased. Contemporary treatments include combinations of chemotherapy and monoclonal antibodies, radioimmunotherapy, new targeted agents and stem-cell transplantation. Prognostic tools are becoming more important in helping clinicians and patients decide on the most appropriate therapeutic regimens. Gene expression profiling and biomarkers are promising additions to this armamentarium. When patients do require therapy, the addition of rituximab to chemotherapy seems to improve remission duration and may improve overall survival. Radioimmunotherapy capitalises on the capacity to target radiation directly to malignant cells, and is currently approved for the treatment of relapsed/refractory follicular lymphoma. Further investigation is needed to clarify the role of stem-cell transplantation in follicular lymphoma. Only well-designed clinical trials can provide answers to the many questions that remain regarding the optimal treatment and sequence of treatments for patients with follicular lymphoma.

Alkylating Agents↗

Advanced and underlying therapeutic strategies in transformed small cell lung cancer.

Transformed small-cell lung cancer (T-SCLC) is a clinically important form of histologic transformation and a mechanism of acquired resistance in non-small-cell lung cancer (NSCLC). It is associated with poor prognosis, with a median overall survival of only about 9-13 months. This review summarizes recent advances in the mechanisms, diagnosis, monitoring, and treatment of T-SCLC. Repeat biopsy remains the gold standard for confirming histologic transformation, whereas molecular profiling and liquid biopsy may facilitate early detection and longitudinal disease monitoring. Platinum-etoposide remains the most commonly used clinical standard after transformation, but its benefit is typically transient and durable disease control remains uncommon. Continuation of EGFR tyrosine kinase inhibitors combined with chemotherapy may prolong progression-free survival in selected patients but has not consistently improved overall survival. Anti-angiogenic therapy, particularly anlotinib, and chemo-immunotherapy have shown encouraging activity in selected patients, while emerging strategies targeting DLL3, MYC, SOX2, and epigenetic regulators may broaden the therapeutic landscape. Prospective studies integrating repeat tissue sampling, comprehensive genomic profiling, biomarker-guided patient stratification, pharmacogenomics, functional drug-sensitivity testing where feasible, and integrated multi-omics approaches are needed to advance molecularly guided and individualized treatment for T-SCLC.

advanced therapy↗

Human IL-34 Deficiency Primes Microglia Toward Alzheimer's Disease-Associated States.

BACKGROUND: Genome-wide association studies (GWAS), with independent replication in large European consortia, have identified a common nonsense variant in IL-34 (Y213X) as a genetic risk factor for late-onset Alzheimer's disease (AD). However, the biological consequences of this IL-34 mutation in humans, its prevalence in the population, and the mechanisms by which IL-34-Y213X alters microglial homeostasis, cerebrospinal fluid (CSF) proteomic networks, and amyloid pathology remain poorly understood. METHODS: We combined human genetics, cerebrospinal fluid (CSF) and serum proteomics, transcriptomics, large-scale phenome-wide association analyses, and preclinical experimental models to define the impact of human IL-34 deficiency. IL-34 concentrations were first quantified in CSF and serum from deeply phenotyped AD cohorts stratified by the common IL-34-Y213X nonsense variant. IL-34 levels and IL-34-Y213X status were then integrated with unbiased CSF proteomic networks and AD biomarkers. Transcriptomic profiling of purified microglia from IL-34 knockout mice was performed to assess disease-associated microglial programs. Using APP/PS1 mice lacking IL-34, we examined the effects of IL-34 deficiency on microglial survival, tiling, and plaque encapsulation. Finally, we performed postmortem analyses of temporal cortex from AD patients carrying IL-34-Y213X to assess microglial density, spatial organization, and plaque-associated responses. FINDINGS: IL-34-Y213X was a strong, dose-dependent loss-of-function (LOF) allele that reduced IL-34 levels by up to 2.5 standard deviations in CSF and serum and was common in multiple populations. IL-34 deficiency reshaped CSF proteomic networks, downregulating axon guidance and microglial support modules while upregulating inflammatory and extracellular matrix signatures, and showed pleiotropic associations with neurological, inflammatory, and metabolic traits. Transcriptomic analysis of sorted microglia from healthy 9-month-old IL-34KO compare to wild-type mice revealed a profound pro-inflammatory and disease-associated microglial transcriptional program enriched for disease-associated microglia (DAM) signatures, inflammatory pathways, and AD risk genes including APOE, CLU, and CASS4. In APP/PS1 mice, genetic IL-34 deletion selectively depleted homeostatic gray-matter microglia, disrupted microglial tiling, and impaired plaque encapsulation, resulting in altered amyloid structure and enhancing neuritic injury. Concordantly, AD patients homozygous for IL-34-Y213X displayed markedly reduced cortical microglial density and increased microglial spatial dispersion, indicating a breakdown of the microglial network organization in the human brain. INTERPRETATION: A common human IL-34 LOF variant creates a naturally occurring model of IL-34 deficiency that links microglial survival, CSF network signatures, and amyloid pathology in both mice and humans. Importantly, IL-34 deficiency alone is sufficient to induce inflammatory, AD-associated microglial states beyond simply reducing microglial number. These findings identify IL-34/CSF1R signaling as a critical determinant of microglial resilience and a potential upstream pathway linking human genetic variation to AD susceptibility, highlighting IL-34-dependent pathways as promising targets for disease modification. FUNDING: This work was supported by grants from the Spanish Ministerio de Ciencia, Innovación y Universidades/FEDER/UE (PID2024-157400OB-I00) and FORTALECE program (FORT23/00008; Instituto de Salud Carlos III, Spain) to RRL and JLV, ISCIII of Spain co-financed by FEDER funds (European Union) through grants PI24/00308 (JV) and CIBERNED collaborative grant 2022/01 to JV, PID2023-147125OB-I00 and CEX2023-001386-S (Severo Ochoa Programme) to SMTBC. A.R. is supported by STAR Award. University of Texas System. Tx, United States, The South Texas ADRC. National Institute of Aging. National Institutes of Health. USA. (P30AG066546), the Keith M. Orme and Pat Vigeon Orme Endowed Chair in Alzheimer's and Neurodegenerative Diseases (2024-2025) and Patricia Ruth Frederick Distinguished Chair for Precision Therapeutics in Alzheimer's and Neurodegenerative Diseases (2025-2028). AR is also supported by the Agency for Innovation and Entrepreneurship (VLAIO) grant N° PR067/21 for the HARPONE project and the ADAPTED project the EU/EFPIA Innovative Medicines Initiative Joint Undertaking Grant N° 115975 and CIBERNED (ISCIII).

Journal Article↗

Identification of ultrasound-associated gene candidates in myeloid cells and construction of a prognostic risk model for acute myeloid leukemia.

BACKGROUND: Incorporating ultrasound (US) treatment sensitivity analysis may improve the treatment of acute myeloid leukemia (AML). METHODS: This study integrated single-cell and bulk datasets for analysis. Differential expression analysis between US-treated and control samples was performed using limma package. The AUCell package was used to calculate US-associated scores in the single-cell dataset. Differentially expressed genes (DEGs) between the specific groups were identified, followed by intersection analysis with previously identified DEGs. Univariate regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis (using the glmnet package), and stepwise multivariate regression (using the MASS package) were used to refine the candidate genes and to construct a risk model. The model genes were validated using in vitro experiments. Enrichment analysis was conducted using gene set enrichment analysis (GSEA), and immune infiltration was evaluate by single-sample GSEA (ssGSEA) and ESTIMATE algorithms. The correlations between RiskScores and drug sensitivity were analyzed by oncoPredict package. Finally, tumor mutational burden (TMB) and genomic mutations were compared between the risk groups. RESULTS: Nine prognostic signatures (SPINK2, HNRNPAB, SH3BGRL3, CLEC11A, ITGA4, RPL39L, MX1, HEXIM1, and MAP4K4) were identified. Particularly, low expression of SPINK2 attenuated the activity and invasion of AML cells. High-risk group had higher immune cell infiltration. Eight drugs were predicted to be correlated with the RiskScore model. DNMT3A and RUNX1 showed higher mutation frequencies in the high-risk group, whereas KIT and MUC16 showed higher mutation frequencies in the low-risk group. CONCLUSION: The RiskScore model established in this study provides a theoretical basis for clinically screening responsive populations and optimizing treatment strategies.

Humans↗

High-throughput screening, metabolomics and drug discovery.

The science of metabolomics has the potential to deliver wide-reaching benefits to the currently embattled pharmaceutical industry. Current applications for this field center around toxicological profiling and biomarker studies; however, the ability of metabolomics to quantitatively assess pharmacologically induced changes in biological systems at the phenotype level suggests that there would be value in its adoption at much earlier phases of the drug-discovery process. As is argued herein, this approach could be coupled with a re-organization of early drug-discovery paradigms to reduce both the rates of attrition and the costs of bringing a drug to market.

Animals↗

Identification of blood biomarkers of rheumatoid arthritis by transcript profiling of peripheral blood mononuclear cells from the rat collagen-induced arthritis model.

Rheumatoid arthritis (RA) is a chronic debilitating autoimmune disease that results in joint destruction and subsequent loss of function. To better understand its pathogenesis and to facilitate the search for novel RA therapeutics, we profiled the rat model of collagen-induced arthritis (CIA) to discover and characterize blood biomarkers for RA. Peripheral blood mononuclear cells (PBMCs) were purified using a Ficoll gradient at various time points after type II collagen immunization for RNA preparation. Total RNA was processed for a microarray analysis using Affymetrix GeneChip technology. Statistical comparison analyses identified differentially expressed genes that distinguished CIA from control rats. Clustering analyses indicated that gene expression patterns correlated with laboratory indices of disease progression. A set of 28 probe sets showed significant differences in expression between blood from arthritic rats and that from controls at the earliest time after induction, and the difference persisted for the entire time course. Gene Ontology comparison of the present study with previous published murine microarray studies showed conserved Biological Processes during disease induction between the local joint and PBMC responses. Genes known to be involved in autoimmune response and arthritis, such as those encoding Galectin-3, Versican, and Socs3, were identified and validated by quantitative TaqMan RT-PCR analysis using independent blood samples. Finally, immunoblot analysis confirmed that Galectin-3 was secreted over time in plasma as well as in supernatant of cultured tissue synoviocytes of the arthritic rats, which is consistent with disease progression. Our data indicate that gene expression in PBMCs from the CIA model can be utilized to identify candidate blood biomarkers for RA.

Animals↗

Derivatized cellulose combined with MALDI-TOF MS: a new tool for serum protein profiling.

Providing a rapid and sensitive protein profiling method for biomarker discovery from a variety of biological samples is crucial for the introduction of new markers that improve cancer patient diagnosis at early tumor stages, thus increasing the chances of curative treatment. We report here the development and application of derivatized cellulose particles for selective serum protein profiling. For immobilized metal ion affinity chromatography (IMAC), cellulose was derivatized with glycidyl methacrylate (GMA) and subsequently with iminodiacetic acid (IDA). To investigate the application of this material for generating protein profiles of human serum samples, the serum samples were agitated with the derivatized cellulose particles to a suspension and incubated for 2 h at 30 degrees C. After washing, 1 microL of the IDA-Cu(2+)-cellulose suspension was applied directly onto a MALDI-target, mixed with sinapinic acid (SA) and analyzed with MALDI-TOF MS. Consistent serum specific data were obtained from aliquoted samples analyzed several times, indicating the reliability of the method. However, the serum fingerprints obtained proved to be specific for any given serum. The technique presented allows a high enrichment of sample on the developed target leading to a high sensitivity and reproducibility without depletion of albumin and immunoglobulin, and sample elution prior to MS-analysis. The study demonstrates for the first time that derivatized cellulose particles combined with MALDI-TOF MS represent a simple, economical, and rapid approach to generate serum protein profiles for biomarker identification.

Biomarkers↗

Biomarkers for atherosclerosis: pathophysiological role and pharmacological modulation.

PURPOSE OF REVIEW: The aim of this article is to discuss the potential value of biomarkers for atherosclerosis in the assessment of risk for cardiovascular disease, in the pathogenesis of atherosclerosis, and in the monitoring of pharmacological treatment. RECENT FINDINGS: In an attempt to improve global cardiovascular risk prediction, considerable effort has been made in the discovery and characterization of soluble biomarkers which can go beyond the measure of total and LDL cholesterol levels. In particular, circulating molecules related to chronic inflammation have emerged as potential biomarkers for atherosclerosis. Evidence, obtained from in-vitro and in-vivo experimental models, has also documented that the majority of biomarkers play a pathological role in atherogenesis. Multiple screening of different biomarkers may therefore improve the assessment of risk, diagnosis, and prognosis for cardiovascular disease. In addition, soluble biomarkers have been shown to be modulated by hypolipidemic drugs and to be potentially useful in determining the clinical benefits of pharmacological therapies that do not alter serum lipid levels. SUMMARY: Altered levels of soluble biomarkers are associated with cardiovascular disease, and profiling of multiple biomarkers for atherosclerosis will be a useful indicator for better risk assessment, diagnosis, and prognosis, as well as monitoring pharmacological treatments for atherosclerosis.

Atherosclerosis↗

Haptoglobin-alpha subunit as potential serum biomarker in ovarian cancer: identification and characterization using proteomic profiling and mass spectrometry.

PURPOSE: The objective of this study was to identify and characterize new serum biomarkers in ovarian cancer patients using mass spectrometric protein profiling and specific immunological assays. EXPERIMENTAL DESIGN: Serum samples from 80 cancer patients and 91 healthy women were analyzed by surface enhanced laser desorption and ionization-mass spectrometry (MS) profiling. A candidate biomarker was purified by affinity chromatography, and its sequence was determined by liquid chromatography-tandem MS. An antibody was generated from the synthesized peptide for quantitative validation in the cases and controls. CA125 was determined and compared with the same set of specimens. RESULTS: Using surface enhanced laser desorption and ionization, we found a serum biomarker at approximately 11700 Da, which had peak intensity significantly higher in cases (1.366) compared with controls (0.208, P = 0.002), and subsequently identified this as the alpha chain of haptoglobin. ELISA indicated that Hp-alpha was </=2-fold higher in cancer serum compared with normal, benign tumor, and other gynecological cancers (P < 0.05) and had 64% sensitivity at 90% specificity alone and 91% sensitivity and 95% specificity if combined with CA125. CONCLUSIONS: Haptoglobin-derived alpha subunit is a potential marker for ovarian cancer that is complementary to CA125. MS-based protein profiling is a valuable tool for screening protein markers and useful to detect post-translational modification of tumor-associated proteins or abnormal metabolic products. However, confirmation of protein identity with specific antibodies is crucial for clinical application and functional studies.

Amino Acid Sequence↗

Identification of serum amyloid a protein as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling.

PURPOSE: Nasopharyngeal cancer (NPC) is a common cancer in Hong Kong, and relapse can occur frequently. Using protein chip profiling analysis, we aimed to identify serum biomarkers that were useful in the diagnosis of relapse in NPC. EXPERIMENTAL DESIGN: Profiling analysis was performed on 704 sera collected from 42 NPC patients, 39 lung cancer patients, 30 patients with the benign metabolic disorder thyrotoxicosis (TX), and 35 normal individuals (NM). Protein profile in each NPC patient during clinical follow up was correlated with the relapse status. RESULTS: Profiling analysis identified two biomarkers with molecular masses of 11.6 and 11.8 kDa, which were significantly elevated in 22 of 31 (71%) and 21 of 31 (68%) NPC patients, respectively, at the time of relapse (RP) as compared with 11 patients in complete remission (CR; RP versus CR, P = 0.009), 30 TX (RP versus TX, P < 0.001), or 35 NM (RP versus NM, P < 0.001). The markers were also elevated in 16 of 39 (41%) lung cancer patients at initial diagnosis. By tryptic digestion, followed by tandem mass spectrometry fragmentation, the markers were identified as two isoforms of serum amyloid A (SAA) protein. Monitoring the patients longitudinally for SAA level both by protein chip and immunoassay showed a dramatic SAA increase, which correlated with relapse and a drastic fall correlated with response to salvage chemotherapy. Serum SAA findings were compared with those of serum Epstein-Barr virus DNA in three relapsed patients showing a similar correlation with relapse and chemo-response. CONCLUSIONS: SAA could be a useful biomarker to monitor relapse of NPC.

Adult↗

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n&#x2009;=&#x2009;11), persistent FGR (n&#x2009;=&#x2009;9), and healthy controls (n&#x2009;=&#x2009;13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n&#x2009;=&#x2009;69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p&#x2009;<&#x2009;0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular&#xa0;signatures reflecting&#xa0;the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗

Daily profile of plasma %CoQ10 level, a biomarker of oxidative stress, in patients with diabetes manifesting postprandial hyperglycaemia.

The purpose of this study was to investigate the effect of regular meals on the daily profile of blood oxidative stress markers in type 2 diabetic patients with postprandial hyperglycaemia. %CoQ10, calculated as the ratio of ubiquinone-10 (oxidised form of coenzyme Q10) to ubiquinol-10 (reduced form), was used as a sensitive marker of oxidative stress. Blood samples were collected from patients before and 2 h after breakfast, lunch and supper, and at 10 p.m. Patients were selected for the study if their blood glucose levels were <7 mmol/l before breakfast and > or =11.1 mmol/l on at least one occasion after breakfast. %CoQ10 levels after breakfast and throughout the day were significantly higher than those before breakfast (p=0.006-0.04). In contrast to the wave-like changes in plasma glucose levels, %CoQ10 levels increased after breakfast and remained at high levels throughout the day. These results indicated that diabetic patients with postprandial hyperglycaemia were exposed to meal-induced periods of oxidative stress during the day. Postprandial hyperglycaemia therefore has the potential to increase the risk of atherosclerotic cardiovascular disease through induction of oxidative stress.

Ascorbic Acid↗

ProteinChip array profiling for identification of disease- and chemotherapy-associated biomarkers of nasopharyngeal carcinoma.

BACKGROUND: We previously used ProteinChip array profiling analysis to discover a serum biomarker associated with nasopharyngeal carcinoma (NPC). In this study, we used the same method to examine other biomarkers associated with NPC and response to chemotherapy (CT) in NPC patients. METHODS: We performed ProteinChip array analysis in 209 serum samples from 66 relapsed patients before and after salvage CT with gemcitabine and cisplatin or etoposide and cisplatin combinations, 11 patients in remission, and 35 healthy individuals. Intensities of the biomarker peaks were correlated with CT response of the patients and other clinical parameters. RESULTS: We discovered 13 candidate biomarkers associated with different clinical parameters. Two biomarkers (2803 and 3953 Da) were significantly increased in patients compared with controls at all stages of disease. Analysis of pre- and post-CT paired serum samples revealed 7 biomarkers correlated with impact of CT. Of these 7 biomarkers, 2 (2509 and 2756 Da) were significantly increased and 5 (7588, 7659, 7765, 7843, and 8372 Da) were significantly decreased post-CT in either 1 or both CT cohorts. Four biomarkers from pre-CT sera were correlated with CT response, with 3 (2950, 13 510, and 14 855 Da) being significantly decreased and 1 (6701 Da) significantly increased in patients who did not respond to CT. Tandem mass spectrometric sequencing and/or immunoaffinity capture assay identified the 3953 Da biomarker as a fragment of interalpha-trypsin inhibitor precursor and 7765 Da biomarker as platelet factor-4. CONCLUSIONS: Treatment-associated serum biomarkers found might serve to triage NPC patients for appropriate CT treatment.

Adult↗

Whole blood transcriptome profile identifies motor neurone disease RNA biomarker signatures.

Blood-based biomarkers for motor neuron disease are needed for better diagnosis, progression prediction, and clinical trial monitoring. We used whole blood-derived total RNA and performed whole transcriptome analysis to compare the gene expression profiles in (motor neurone disease) MND patients to the control subjects. We compared 42 MND patients to 42 aged and sex-matched healthy controls and described the whole transcriptome profile characteristic for MND. In addition to the formal differential analysis, we performed functional annotation of the genomics data and identified the molecular pathways that are differentially regulated in MND patients. We identified 12,972 genes differentially expressed in the blood of MND patients compared to age and sex-matched controls. Functional genomic annotation identified activation of the pathways related to neurodegeneration, RNA transcription, RNA splicing and extracellular matrix reorganisation. Blood-based whole transcriptomic analysis can reliably differentiate MND patients from controls and can provide useful information for the clinical management of the disease and clinical trials.

Humans↗

Large-scale proteomics profiling of peripheral blood of DM1 patients identifies biomarkers for disease severity and functional capacity.

BackgroundMyotonic Dystrophy Type 1 (DM1), the most common genetic neuromuscular disorder in adults, poses significant challenges for drug development due to its multisystem nature and high clinical variability in symptoms and disease progression. With a growing number of therapies entering clinical trials, this study addresses the urgent need for biomarkers that can serve as surrogate endpoints.MethodsWe profiled 437 serum samples from adult DM1 patients collected at two timepoints of the OPTIMISTIC trial using bottom-up mass spectrometry with data-independent acquisition. Associations between protein expression, the disease-causing CTG-repeat and 25 clinical outcome measures were studied using linear mixed-effect models. All key study findings were validated in an independent cohort of 69 DM1 patients and 10 healthy controls.ResultsOf the 259 identified proteins, 161 showed significant associations with the CTG-repeat length (FDR&#x2009;<&#x2009;5%). Hypogammaglobulinemia was confirmed and shown to be worse in severely affected patients. A strong proteomic signature was associated with clinical measures of functional capacity, with the 6-Minute Walk Test showing the strongest signal (70 associations, FDR&#x2009;<&#x2009;5%). These novel associations reveal a compelling link between chronic inflammation and reduced functional capacity. A machine learning algorithm identified a minimal set of 13 proteins robustly reflecting both the underlying genetic defect and functional capacity.ConclusionsDM1 induces a broad disease fingerprint in the serum proteome, predominantly affecting proteins of the immune system. A carefully selected panel of proteins showed the greatest potential to meet the statistical criteria required for surrogate endpoints in clinical trials.

Humans↗

[Preliminary biomarker related to nasopharyngeal carcinoma filtered from the whole genome expression profiling involved in microdissection nasopharyngeal tissues].

OBJECTIVE: To filter biomarkers of nasopharyngeal carcinoma (NPC) by constructing the homogenesis tissue gene expression profiling with the whole human genome GeneChip. METHODS: The epithelium cells of the homogenesis NPC and the pure nasopharyngeal normal tissues microdissected from nasopharyngeal biopsy which was preserved in the RNAlater were used to isolate RNA and then to harvest the aRNA through in vitro transcription, and aRNA prober was labled to hybridize to HG-U133. plus 2.0, so the expression profiling of each homogenesis tissue could be constructed. RESULTS: Some candidate biomarker genes related to the tumorigenesis of NPC had been filtered by comparing the expression profiling of NPC samples with the expression profiling of normal nasopharyngeal epithelia samples. Any genes regarding the metastasis of NPC might have been selected by comparing the expression profiling of no-metastasis samples with those of the metastasis samples. CONCLUSION: Using the whole genome GeneChip to construct the expression profiling for the microdissected homogenesis tissue is effective to filter the candidate biomarker genes.

Adult↗

Metabolic and hormonal profiles: HDL cholesterol as a plausible biomarker of breast cancer risk. The Norwegian EBBA Study.

Low serum high-density lipoprotein cholesterol (HDL-C) is an important component of the metabolic syndrome and has recently been related to increased breast cancer risk in overweight and obese women. We therefore questioned whether serum HDL-C might be a biologically sound marker of breast cancer risk. We obtained cross-sectional data among 206 healthy women ages 25 to 35 years who participated in the Norwegian EBBA study. We included salivary ovarian steroid concentrations assessed by daily samples throughout one entire menstrual cycle, metabolic profile with measures of adiposity [body mass index (BMI) and truncal fat percentage], serum concentrations of lipids and hormones (insulin, leptin, testosterone, dehydroepiandrostendione sulfate, insulin-like growth factor-I, and its principal binding protein), and mammographic parenchymal pattern. We examined how components of the metabolic syndrome, including low serum HDL-C, were related to levels of hormones, and free estradiol concentration in particular, and studied predictors of mammographic parenchymal patterns in regression models. In women with BMI > or = 23.6 kg/m(2) (median), overall average salivary estradiol concentration dropped by 2.4 pmol/L (0.7 pg/mL; 13.2% change in mean for the total population) by each 0.33 mmol/L (12.8 mg/dl; 1SD) increase in serum HDL-C (P = 0.03; P(interaction) = 0.03). A subgroup of women characterized by both relatively high BMI (> or =23.6 kg/m(2)) and high serum LDL-C/HDL-C ratio (> or = 2.08; 75 percentile) had substantially higher levels of salivary estradiol by cycle day than other women (P = 0.001). BMI was the strongest predictor of overall average estradiol with a direct relationship (P< 0.001). Serum HDL-C was inversely related to serum leptin, insulin, and dehydroepiandrostendione sulfate (P < 0.001, P < 0.01, and P < 0.05, respectively). There was a direct relationship between breast density and healthy metabolic profiles (low BMI, high serum HDL-C; P < 0.001) and salivary progesterone concentrations (P < 0.05). Our findings support the hypothesis that low serum HDL-C might reflect an unfavorable hormonal profile with, in particular, increased levels of estrogens and gives further clues to biomarkers of breast cancer risk especially in overweight and obese women.

Adult↗

Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.

BACKGROUND: Sessile serrated lesions (SSLs) account for 15% of colorectal cancers (CRCs) but detection remains difficult due to flat morphology, mucinous features, and subtle histology. AIMS: This study aimed to identify novel and functionally relevant biomarkers of SSLs using transcriptomic screening and multi-omics validation. METHODS: Paired SSL and normal mucosa specimens (n&#x2009;=&#x2009;6) underwent RNA sequencing. Differentially expressed genes (DEGs) were filtered for membrane or secretory proteins and validated across TCGA and adenoma transcriptomes. Functional significance was assessed using CRISPR dependency profiling, proteotranscriptomic concordance, pharmacogenomic sensitivity, and connectivity map analysis. RESULTS: We identified 216 upregulated genes in SSLs, including 68 encoding secretory/membrane proteins that better discriminated SSLs from controls and were enriched for adhesion and neuronal signaling while suppressing TNF&#x3b1;-NF&#x3ba;B inflammatory pathways. Cross-cohort comparison revealed five overlapping candidates between SSLs and TCGA CMS1 tumors. Among them, S100P emerged as the primary biomarker candidate, showing consistent upregulation in SSLs and CMS1 tumors while remaining low in normal mucosa and conventional adenomas. TFF1 also showed RNA-level upregulation but appeared more context-dependent. S100P demonstrated strong RNA-protein concordance in CRC cell-line profiling, supporting its detectability as a biomarker candidate. Pharmacogenomic profiling of LS411N cells revealed marked sensitivity to SN-38 and fluoropyrimidines, consistent with serrated CRC vulnerabilities. Connectivity map analysis identified perturbations, including MAPK1 and histone acetyltransferase suppression, that may reverse parts of the SSL transcriptional program. CONCLUSION: These findings prioritize S100P as a promising biomarker candidate for SSLs that warrants further validation in larger cohorts and clinically applicable platforms.

Humans↗