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PubMed2005

Identification of differentially expressed proteins in pancreatic cancer using a global proteomic approach.

Proteomics is the term used for the large-scale analysis of proteins in biological fluids or cells by biochemical methods. Two approaches are used for proteomics analysis: two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and a mass-spectrometry-based approach, such as surface-enhanced laser desorption ionization (SELDI). SELDI can be used for large protein profiling or peptide identification after enzymatic digestion. In pancreatic cancer, proteomics analysis can be performed with the aim to identify all differentially expressed proteins in cancer cells vs normal pancreatic cells. Protein profiling of pancreatic juice or serum may also identify biomarkers for pancreatic cancer that could be used as diagnostic markers or therapeutic targets. This chapter outlines the use of 2D-PAGE and SELDI for profiling the protein content of pancreatic juice samples and for identifying proteins differentially expressed in pancreatic cancer patient samples compared to control patient samples.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2005

Plasma protein profiling for diagnosis of pancreatic cancer reveals the presence of host response proteins.

Plasma protein profiling using separations coupled to matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has great potential in translational research; it can be used for biomarker discovery and contribute to disease diagnosis and therapy. Previously reported biomarker searches have been done solely by MS protein profiling followed by bioinformatics analysis of the data. To add to current methods, we tested an alternative strategy for plasma protein profiling using pancreatic cancer as the model. First, offline solid-phase extraction is done with 96-well plates to fractionate and partially purify the proteins. Then, multiple profiling and identification experiments can be conducted on the same protein fractions because only 5% of the fractions are used for MALDI MS profiling. After MALDI MS analysis, the mass spectra are normalized and subjected to a peak detection algorithm. Over three sets of mass spectra acquired using different instrument variables, approximately 400 unique ion signals were detected. Classification schemes employing as many as eight individual peaks were developed using a training set with 123 members (82 cancer patients) and a blinded validation set with 125 members (57 cancer patients). The sensitivity of the study was 88%, but the specificity was significantly lower, 75%. The reason for the low specificity becomes apparent upon protein identification of the ion signals used for the classification. The identifications reveal only common serum proteins and components of the acute phase response, including serum amyloid A, alpha-1-antitrypsin, alpha-1-antichymotrypsin, and inter-alpha-trypsin inhibitor.

Acute-Phase Proteins↗

PubMed2006

Apo-AII is an elevated biomarker of chronic non-human primate ethanol self-administration.

AIMS: Serum protein profiles were examined in naïve, ethanol self-administering and ethanol abstinent cynomolgus monkeys (Macaca fasicularis) to search for differences in protein expression which could possibly serve as biomarkers of heavy ethanol consumption. METHODS: Surface-enhanced laser desorption ionization time-of-flight (SELDI-ToF) mass spectrometry was used for proteomic profiling of serum. RESULTS: Two proteins were identified by SELDI-ToF to be increased in ethanol self-administering compared with abstinent animals. These proteins were identified to be apolipoprotein AI (Apo-AI) and apolipoprotein AII (Apo-AII) by peptide mass fingerprinting and comparison with spectra of purified human Apo-AI and AII proteins. Immunoblot analysis of Apo-AI and Apo-AII was performed on a separate group of animals (within-animal ethanol-naïve and self-administering) and confirmed a statistically significant increase in Apo-AII, while Apo-AI was unchanged. CONCLUSIONS: An open proteomic screen of serum and confirmation in a separate set of animals found Apo-AII to be increased in the serum of ethanol self-administering monkeys. These results are consistent with previous clinical studies of human ethanol consumption and serum apolipoprotein expression. Moreover, these results validate the use of non-human primates as a model organism for proteomic analysis of ethanol self-administration biomarkers.

Alcohol Drinking↗

PubMed2006

Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications.

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.

Biomarkers↗

PubMed2005

SELDI-MS-based expression profiling of ductal invasive and lobular invasive human breast carcinomas.

Expression profiling using proteomic techniques has a great potential to identify new biomarkers that might help to better diagnose and treat diseases such as breast cancer, which is one of the leading causes of cancer death in women. Surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS) combines chromatographic separation of peptides and proteins with mass spectrometry and is a fast, user-friendly tool to analyze protein and peptide profiles. SELDI-MS was employed for a comparative analysis of lobular invasive versus ductal invasive breast tumors to find differentially expressed proteins and peptides, and to validate this technique for biomarker identification using complex samples such as tissue. After optimization of sample preparation using HMEC and MCF-7 cell lines, 20 breast tumors were analyzed, and about 550 mass signals corresponding to an estimated 140 native peptides and proteins were detected in each tumor. Only 14% of the mass signals were present in more than six tumors of one subgroup or in more than 12 tumors of both groups showing a great overall heterogeneity of the peptide and protein profiles obtained. Peptide mass signals specific for each of the analyzed groups were identified. In addition, we detected peptides from laser-microdissected ductal invasive and intraductal tumor parts corresponding to peptides present in whole tumors. The low amount of identified peptides and proteins and the observed heterogeneity suggest that SELDI-MS is not well suited for biomarker identification of and profiling experiments on complex samples such as tumor tissue.

Breast Neoplasms↗

PubMed2026

Proteomic and machine learning analysis predicts treatment response signatures in Myasthenia Gravis.

BACKGROUND: Myasthenia gravis (MG) is a prototypical antibody-mediated autoimmune disease with variable treatment responses with a need for biomarkers to guide therapeutic decision making. Proteomic profiling, coupled with machine learning, offers a hypothesis-free approach to identify multi-protein signatures associated with treatment response. METHODS: We analyzed sera collected at entry (baseline) from participants in a phase 3 trial randomized trial comparing thymectomy plus prednisone versus prednisone alone, along with matched controls using liquid chromatography-mass spectrometry. We derived disease-specific proteomic signatures and evaluated associations between baseline proteins and 6-month clinical outcomes using multiple machine-learning approaches with internal validation. RESULTS: Baseline serum proteomes distinguished MG from controls, with pathway enrichment implicating complement activation, immunoglobulin production, and T-cell receptor signaling. Distinct protein panels predicted 6-month clinical improvement within each treatment arm. In the thymectomy-plus-prednisone group, models captured non-linear relationships of predictive proteins in contrast with the predominant additive patterns observed in the prednisone-alone group. Predictive proteins were enriched for T-cell signaling and leukocyte trafficking functions, providing insight into treatment-specific biology. CONCLUSIONS: Baseline serum proteomics captures core disease characteristics of MG and predicts short-term clinical response in a treatment-specific manner. While our results require validation in independent cohorts, these findings could enable biomarker-guided selection of thymectomy, refine risk stratification, and furnish mechanistic readouts for future MG trials and clinical care. We aim to conduct future studies using -omic approaches to validate these baseline predictive biomarkers and pathways of treatment response in patients with MG.

Adult↗

PubMed2005

Genome-wide expression profiling in malaria infection reveals transcriptional changes associated with lethal and nonlethal outcomes.

High-density oligonucleotide microarrays are widely used to study gene expression in cells exposed to a variety of pathogens. This study addressed the global genome-wide transcriptional activation of genes in hosts infected in vivo, which result in radically different clinical outcomes. We present an analysis of the gene expression profiles that identified a set of host biomarkers which distinguish between lethal and nonlethal blood stage Plasmodium yoelii malaria infections. Multiple biological replicates sampled during the course of infection were used to establish statistically valid sets of differentially expressed genes. These genes that correlated with the intensity of infection were used to identify pathways of cellular processes related to metabolic perturbations, erythropoiesis, and B-cell immune responses and other innate and cellular immune responses. The transcriptional apparatus that controls gene expression in erythropoiesis was also differentially expressed and regulated the expression of target genes involved in the host's response to malaria anemia. The biological systems approach provides unprecedented opportunities to explore the pathophysiology of host-pathogen interactions in experimental malaria infection and to decipher functionally complex networks of gene and protein interactions.

Animals↗

PubMed2026

Proteomics profiling of serum and liver in GSD Ia and Ib patients: insights into complication mechanisms and circulation biomarkers.

BACKGROUND: Glycogen Storage Disease (GSD) Types Ia and Ib are rare metabolic diseases caused by gene variants in G6PC1 and SLC37A4, respectively. Although life-threatening fasting hypoglycemia can be controlled by a strict diet, patients often suffer from multiple metabolic abnormalities and severe long-term complications. However, the underlying mechanisms remain incompletely understood, and there is a lack of effective monitoring biomarkers. Therefore, the aims of this study are to investigate the pathological mechanisms of the disease and disease complications in GSD I and identify potential protein biomarkers. METHODS: Comprehensive untargeted proteomics was performed on 18 GSD Ia and 8 GSD Ib sera samples from patients with 21 matched control sera, complemented by liver 3 GSD Ia samples and 1 GSD Ib sample from patient liver tissues, compared to 10 donor liver samples. RESULTS: We identified 415 proteins in total. Significantly changed (FDR < 0.05) were observed in 158 (38%) proteins for GSD Ia vs Control, 116 (28%) for GSD Ib vs. Control, and 151 (36%) for GSD Ia vs. Ib. Pathway analysis revealed distinct alterations in serum/plasma, with 58, 32, and 29 significantly changed biological processes (FDR < 0.05) in these three comparisons, respectively. The coagulation pathway was the most significantly changed one in the GSD Ia patients. Immune response-associated proteins, especially immunoglobulins, were increased in GSD Ib specifically. Proteins related to liver injury, cholesterol, and amyloidosis were altered in two subtypes, though more pronounced in GSD Ia. Potential biomarkers with significant alterations both in the circulation and in the liver tissue were identified specifically for monitoring GSD I subtypes and prognosing liver deterioration, namely APOC1 and CD5L to distinguish between GSD Ia and Ib and ALDOB for the presence of hepatocellular carcinoma (HCC) in GSD Ia patients. CONCLUSIONS: These findings provide new insights into the differences between the two GSD I subtypes and the pathogenesis of GSD I-related complications, as well as highlighting the potential of protein circulating biomarkers for monitoring complication progression in GSD I and assessing HCC risk in GSD Ia patients.

Humans↗

PubMed2024

Myoferlin: A Potential Marker of Response to Radiation Therapy and Survival in Locally Advanced Rectal Cancer.

PURPOSE: Patients with locally advanced rectal cancer often require neoadjuvant chemoradiation therapy to downstage the disease, but the response is variable with no predictive biomarkers. We have previously revealed through proteomic profiling that myoferlin is associated with response to radiation therapy. The aims of this study were to further validate this finding and explore the potential for myoferlin to act as a prognostic and/or therapeutic target. METHODS AND MATERIALS: Immunohistochemical analysis of a tissue microarray (TMA) for 111 patients was used to validate the initial proteomic findings. Manipulation of myoferlin was achieved using small interfering RNA, a small molecular inhibitor (wj460), and a CRISPR-Cas9 knockout cell line. Radiosensitization after treatment was assessed using 2-dimensional clonogenic assays, 3-dimensional spheroid models, and patient-derived organoids. Underlying mechanisms were investigated using electrophoresis, immunofluorescence, and immunoblotting. RESULTS: Analysis of both the diagnostic biopsy and tumor resection samples confirmed that low myoferlin expression correlated with a good response to neoadjuvant long-course chemoradiation therapy. High myoferlin expression was associated with spread to local lymph nodes and worse 5-year survival (P = .01; hazard ratio, 3.5; 95% CI, 1.27-10.04). This was externally validated using the Stratification in Colorectal Cancer database. Quantification of myoferlin using immunoblotting in immortalized colorectal cancer cell lines and organoids demonstrated that high myoferlin expression was associated with increased radioresistance. Biological and pharmacologic manipulation of myoferlin resulted in significantly increased radiosensitivity across all cell lines in 2-dimensional and 3-dimensional models. After irradiation, myoferlin knockdown cells had a significantly impaired ability to repair DNA double-strand breaks. This appeared to be mediated via nonhomologous end-joining. CONCLUSIONS: We have confirmed that high expression of myoferlin in rectal cancer is associated with poor response to neoadjuvant therapy and worse long-term survival. Furthermore, the manipulation of myoferlin led to increased radiosensitivity in vitro. This suggests that myoferlin could be targeted to enhance the sensitivity of patients with rectal cancer to radiation therapy, and further work is required.

Humans↗

PubMed2005

Protein expression analysis of rat testes induced testicular toxicity with several reproductive toxicants.

The utilization of safety biomarkers to predict the possibility of compound-related toxicity provides several advantages for drug discovery and development, especially at an early stage. The objectives of this study were to investigate the effects of male reproductive toxicants on protein expression profiles in the rat testes and to identify potential biomarker candidates. Four well-known reproductive toxicants, ethylene glycol monomethyl ether (EGME), cyclophosphamide (CP), sulfasalazine (SASP) and 2,5-hexanedione (2,5-HD), were administered to male rats in a single dose, and protein expression profiles were investigated after 24 hr by two-dimensional gel electrophoresis (2DE). Histopathological examination of the testes and serum concentration analysis were also performed. From the results of the comparison of 2D-gels among different doses of a compound and among compounds, 52, 20, 24 and 111 spots were nominated as differentially expressed spots with EGME, CP, SASP and 2,5-HD treatments, respectively. Several spermatogenesis-involved proteins were identified, including glutathione S-transferase (GST), testis-specific heat shock protein 70-2 (HSP70-2), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and phosphatidylethanolamine-binding protein (PEBP). Some of them were altered by more than one compound. In summary, remarkable histopathological findings were observed only in the EGME high-dose group, and most of the protein changes were detected before histopathological changes occurred. Therefore, the proteins identified in this study could potentially serve as biomarkers to evaluate male reproductive toxicity at an early stage of drug discovery and development.

Animals↗

PubMed2003

Proteomic applications for the early detection of cancer.

The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancers at their earliest stages. Proteomic analyses of early-stage cancers have provided new insights into the changes that occur in the early phases of tumorigenesis and represent a new resource of candidate biomarkers for early-stage disease. Studies that profile proteomic patterns in body fluids also present new opportunities for the development of novel, highly sensitive diagnostic tools for the early detection of cancer.

Biomarkers, Tumor↗

PubMed2004

Use of serial analysis of gene expression (SAGE) technology reveals new granulocytic markers.

Because of its short life span in blood, its low RNA content and its highly condensed nucleus, the granulocyte was initially considered as a terminally differentiated cell unable to express novel genes. However, mature granulocytes still contain a variety of mRNAs and may respond to external stimuli by rapid and complex changes in gene expression. The present work was undertaken to provide a wider view of the gene expression profile in unstimulated circulating PMNs. We used serial analysis of gene expression (SAGE) adapted to downsized extracts (SADE) to cope with their small mRNA content. As cell samples of the highest degree of purity were crucial for this project, we adapted a magnetic cell sorting method to reach the required high levels of purity (99.55 +/- 0.19%) together with low activation rates (1.37 +/- 0.28). We analyzed 20,787 tags identifying 8547 different transcripts, of which 47.8% were unknown, 34.6% were transcripts of known genes, and 13.8% matched with expressed sequence tags (EST). Highly expressed genes were those involved in cell mobility, diapedesis, cell signaling and destruction of micro-organisms. In addition, this method led to the identification of genes which had not previously been reported in granulocytes. These results could provide new molecular markers and a reliable reference for the investigation of pathologies involving alteration of the granulocyte gene expression profile.

Biomarkers↗

PubMed2026

Genomic profiling as an option for ovarian cancer diagnostics.

INTRODUCTION: Ovarian cancer (OC) is a highly heterogeneous and lethal gynecological malignancy. Precision oncology has shifted the management paradigm to comprehensive molecular profiling. Genomic-based diagnostics are now a clinical necessity for accurate prognostic stratification and the rational selection of targeted therapeutics, such as PARP and immune checkpoint inhibitors. AREAS COVERED: This review evaluates current literature regarding the distinct genomic landscapes defining OC histotypes to underlined the role of molecular profiling in the diagnostic field of OC. We discuss the practical implementation, technical aspect, and clinical validity of the main molecular diagnostic platforms, focusing on tissue-based Comprehensive Genomic Profiling (CGP) and Homologous Recombination Deficiency (HRD). Furthermore, we explore emerging translational data on liquid biopsy (LBx) applications. EXPERT OPINION: While current tissue-based methodologies provide critical baseline data, the OC diagnostic paradigm must pivot from static testing to proactive and longitudinal tracking. Integrating advanced LBx approaches enables a real-time monitoring of dynamic parameters as minimal residual disease (MRD) and acquired resistance. Integrating these dynamic blood-based assays with multi-omic profiling and artificial intelligence (AI)-driven tools allows a full understanding of the complex tumor behavior.

Humans↗

PubMed2021

RP-REP Ribosomal Profiling Reports: an open-source cloud-enabled framework for reproducible ribosomal profiling data processing, analysis, and result reporting.

Ribosomal profiling is an emerging experimental technology to measure protein synthesis by sequencing short mRNA fragments undergoing translation in ribosomes. Applied on the genome wide scale, this is a powerful tool to profile global protein synthesis within cell populations of interest. Such information can be utilized for biomarker discovery and detection of treatment-responsive genes. However, analysis of ribosomal profiling data requires careful preprocessing to reduce the impact of artifacts and dedicated statistical methods for visualizing and modeling the high-dimensional discrete read count data. Here we present Ribosomal Profiling Reports (RP-REP), a new open-source cloud-enabled software that allows users to execute start-to-end gene-level ribosomal profiling and RNA-Seq analysis on a pre-configured Amazon Virtual Machine Image (AMI) hosted on AWS or on the user's own Ubuntu Linux server. The software works with FASTQ files stored locally, on AWS S3, or at the Sequence Read Archive (SRA). RP-REP automatically executes a series of customizable steps including filtering of contaminant RNA, enrichment of true ribosomal footprints, reference alignment and gene translation quantification, gene body coverage, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially translated genes, and generation of heatmaps, co-translated gene clusters, enriched pathways, and other custom visualizations. RP-REP provides functionality to contrast RNA-SEQ and ribosomal profiling results, and calculates translational efficiency per gene. The software outputs a PDF report and publication-ready table and figure files. As a use case, we provide RP-REP results for a dengue virus study that tested cytosol and endoplasmic reticulum cellular fractions of human Huh7 cells pre-infection and at 6 h, 12 h, 24 h, and 40 h post-infection. Case study results, Ubuntu installation scripts, and the most recent RP-REP source code are accessible at GitHub. The cloud-ready AMI is available at AWS (AMI ID: RPREP RSEQREP (Ribosome Profiling and RNA-Seq Reports) v2.1 (ami-00b92f52d763145d3)).

AMI↗

PubMed2007

Use of molecular imaging to quantify response to IKK-2 inhibitor treatment in murine arthritis.

OBJECTIVE: The NF-kappaB signaling pathway promotes the immune response in rheumatoid arthritis (RA) and in rodent models of RA. NF-kappaB activity is regulated by the IKK-2 kinase during inflammatory responses. To elucidate how IKK-2 inhibition suppresses disease development, we used a combination of in vivo imaging, transcription profiling, and histopathology technologies to study mice with antibody-induced arthritis. METHODS: ML120B, a potent, small molecule inhibitor of IKK-2, was administered to arthritic animals, and disease activity was monitored. NF-kappaB activity in diseased joints was quantified by in vivo imaging. Quantitative reverse transcriptase-polymerase chain reaction was used to evaluate gene expression in joints. Protease-activated near-infrared fluorescence (NIRF) in vivo imaging was applied to assess the amounts of active proteases in the joints. RESULTS: Oral administration of ML120B suppressed both clinical and histopathologic manifestations of disease. In vivo imaging demonstrated that NF-kappaB activity in inflamed arthritic paws was inhibited by ML120B, resulting in significant suppression of multiple genes in the NF-kappaB pathway, i.e., KC, epithelial neutrophil-activating peptide 78, JE, intercellular adhesion molecule 1, CD3, CD68, tumor necrosis factor alpha, interleukin-1beta, interleukin-6, inducible nitric oxide synthase, cyclooxygenase 2, matrix metalloproteinase 3, cathepsin B, and cathepsin K. NIRF in vivo imaging demonstrated that ML120B treatment dramatically reduced the amount of active proteases in the joints. CONCLUSION: Our data demonstrate that IKK-2 inhibition in the murine model of antibody-induced arthritis suppresses both inflammation and joint destruction. In addition, this study highlights how gene expression profiling can facilitate the identification of surrogate biomarkers of disease activity and treatment response in an experimental model of arthritis.

Administration, Oral↗

PubMed2026

Genomic, transcriptomic, and molecular predictors of response to neoadjuvant therapy in locally advanced rectal cancer: a narrative review.

Total neoadjuvant therapy (TNT) has emerged as a key treatment paradigm for locally advanced rectal cancer, reducing distant metastasis rates and facilitating organ preservation in selected patients. However, treatment response remains heterogeneous, highlighting the need for biomarkers that can guide treatment selection and optimise outcomes. This narrative review synthesises the current evidence regarding tumour-intrinsic genomic biomarkers associated with response to neoadjuvant therapy, encompassing somatic mutations, germline polymorphisms, gene expression profiles, mismatch repair (MMR) status, protein expression, epigenetic markers, and circulating tumour-derived biomarkers across conventional chemoradiotherapy (CRT) and TNT paradigms. Across the reviewed literature, individual somatic mutations, including KRAS, TP53, and BRAF, demonstrated limited reproducibility as predictive biomarkers, although KRAS mutations were recurrently associated with lower pathological complete response (pCR) rates in CRT-era cohorts. Germline polymorphisms in DNA repair (XRCC1) and folate metabolism (MTHFR) genes showed inconsistent associations with treatment response. In contrast, transcriptomic biomarkers demonstrated greater biological coherence, with proliferative, epithelial-mesenchymal transition, and metabolic signatures frequently associated with treatment resistance, while multi-gene classifiers generally outperformed single-gene markers. Among currently available tumour-intrinsic biomarkers, MMR deficiency was the most consistently reported biomarker associated with reduced response to fluoropyrimidine-based regimens, including TNT, although TNT-specific evidence remains comparatively limited. Dynamic circulating tumour DNA (ctDNA) monitoring, particularly ctDNA clearance during or after therapy, was consistently associated with pathological response and long-term oncologic outcomes across reviewed studies, whereas baseline ctDNA levels showed limited predictive value. Overall, the reviewed literature suggests that biomarker research in rectal cancer has evolved from single-gene analyses towards pathway-level and dynamic biomarkers. The integration of transcriptomic signatures, MMR status, and dynamic ctDNA monitoring may represent a promising strategy for personalising neoadjuvant therapy, improving patient selection for organ-preserving approaches, and enhancing oncologic outcomes in locally advanced rectal cancer. Nevertheless, the evidence base remains heterogeneous, and further prospective validation, assay standardisation, and evaluation within contemporary TNT cohorts are required before these biomarkers can be routinely incorporated into clinical decision-making.

Humans↗

PubMed2025

Enhancing the sensitivity of non-invasive cervical cancer detection using CpG methylation haplotype profiling.

DNA methylation is a critical epigenetic modification that regulates gene expression and plays a significant role in cancer development. This methylation signature can be detected in cancer-derived DNA from non-invasive samples, such as plasma, urine or Pap smears. However, in early-stage cancers-when detection is most critical-the concentration of cancer DNA is often low, limiting the sensitivity of current detection methods. Traditional DNA methylation detection techniques, which rely on methylation ratio-based measurements, may obscure subtle variations in methylation patterns, further reducing detection sensitivity. In this study, we analyzed cervical scraping specimens and examined whether detecting cancer-specific methylation patterns in cervical cancer could be enhanced using a Highly Methylated Haplotype (HMH) approach. This novel approach captures highly methylated haplotypes at single-molecule resolution using next-generation sequencing, providing greater detail than conventional methods. HMHs in specific DNA regions are a hallmark of cancer and stand out in contrast to sporadic methylation commonly observed in non-cancerous tissues. We applied HMH profiling to a gene panel of four biomarkers (CA10, DPP10, FMN2, and HAS1) previously validated in cervical cancer studies. At pre-specified cutoffs (99th percentile of normals), haplotype-based scoring achieved 89.9% sensitivity for invasive cancer at high specificity (~ 94-98%), outperforming median (78.0%) and single-CpG (71.6%) methods. For clinically relevant endpoints, the combined panel detected 51-52% of CIN2 + and 66-67% of CIN3 + cases, again exceeding the performance of median- and single-CpG-based scoring methods.These findings demonstrate the potential of HMH to substantially enhance sensitivity in cervical cancer detection, offering a promising approach for non-invasive diagnostics.

Humans↗

PubMed2002

A prospective study of serum bile acid concentrations and colorectal cancer risk in post-menopausal women on the island of Guernsey.

Secondary bile acids produced by the action of the colonic microflora may increase risk of colorectal cancer. Serum bile acid concentrations reflect the faecal bile acid profile and may be of value as biomarkers of risk of colorectal cancer. In a pilot investigation we examined: (i) the reproducibility of measurements of serum bile acids in two blood samples collected several years apart; and (ii) the hypothesis that relatively high levels of secondary bile acids, particularly deoxycholic acid, would be positively associated with an increased risk of colorectal cancer in a prospective study of 3680 women in Guernsey. There was poor reproducibility between repeat measurements of absolute serum concentrations of bile acids, but there was moderately good reproducibility for the ratios of serum concentrations of deoxycholic/cholic acid, lithocholic/chenodeoxycholic and secondary/primary bile acid concentrations (duplicate blood samples were available for 30 women). There were no significant differences in ratios of serum secondary to primary bile acids or in absolute concentrations of bile acids between the 46 women who developed colorectal cancer and their matched controls, although there was a suggestion that an increased risk was associated with a high ratio of deoxycholic/cholic acid (relative risk in top third compared to lower third=3.92 (95% CI 0.91-17.0, P for trend=0.096). These findings suggest that the ratios of serum bile acid concentrations are sufficiently reproducible for epidemiological studies, but that a larger study than our own is needed to adequately test the hypothesis of their relation to cancer risk.

Adult↗