Metabolomics: from pattern recognition to biological interpretation.

Wolfram Weckwerth; Katja Morgenthal

doi:10.1016/s1359-6446(05)03609-3

Home/Archive/PubMed

PubMed · 16257378

Metabolomics: from pattern recognition to biological interpretation.

Wolfram Weckwerth·Katja Morgenthal

View original source ↗Export metadata ↓

Abstract

Metabolomics is a technology that aims to identify and quantify the metabolome -- the dynamic set of all small molecules present in an organism or a biological sample. In this sense, the technique is distinct from metabolic profiling, which looks for target compounds and their biochemical transformation. The combination of both approaches is an emerging technique for the characterization of biological samples and for drug treatment. Metabolomics has proven to be very rapid and superior to any other post-genomics technology for pattern-recognition analyses of biological samples. Changing steady state concentrations and fluctuations of metabolites that occur within milliseconds are a result of biochemical processes such as signalling cascades: metabolomic techniques are instrumental in measuring these changes rapidly and sensitively. Metabolite data can be complemented by protein, transcript and external (environmental) data, thereby leading to the identification of multiple physiological biomarkers embedded in correlative molecular networks that are not approachable with targeted studies.

Explore related subjects

Biomarkers Chemistry Techniques, Analytical Drug Design Genomics Metabolism Molecular Biology Statistics as Topic Journal Article Review

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Wolfram Weckwerth, Katja Morgenthal. 2005-11-15. Metabolomics: from pattern recognition to biological interpretation.. https://doi.org/10.1016/s1359-6446(05)03609-3

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Genomic and Transcriptomic Correlates of Deep PSA Response in Patients with Metastatic Androgen Pathway Modulation-Sensitive Prostate Cancer.

BACKGROUND: Despite advances in metastatic androgen pathway modulation-sensitive prostate cancer (mAPMS) treatment, outcomes remain heterogeneous. Achieving a post-treatment undetectable prostate specific antigen (PSA) is a strong prognostic marker. We aimed to identify genomic and transcriptomic determinants of PSA response in a real-world clinical-genomic cohort. PATIENTS AND METHODS: Patients with mAPMS who underwent DNA (Tempus xT) and, in a subset, RNA (Tempus xR) sequencing were identified from the Tempus Lens database. Inclusion required stage IV disease within 90 days of sample collection and samples obtained within 12 months before or 3 months after treatment initiation. Patients with PSA at 6 months (n = 525) were classified as PSA-low (<0.1 ng/mL, n = 240) or PSA-high (≥0.1 ng/mL, n = 285). Overall survival (OS) was assessed by 6-month landmark analysis with delayed-entry adjustment. Logistic and Cox models were adjusted for clinical variables. Sensitivity analyses used a relative definition of > 95% PSA decline from baseline. RESULTS: Baseline PSA was lower in PSA-low versus PSA-high patients (24 vs 36 ng/mL, p = 0.01). SPOP (17% vs 11%) and ZFHX3 (2.5% vs 6%) alterations differed between groups, but neither persisted after adjustment. Using the relative definition, ZMYM3 and JAK1 alterations were independently associated with failure to achieve a deep PSA response. Expression of PSMA, TROP2, B7-H3, and STEAP1 did not differ between groups. PSA-low status was independently associated with improved OS, as was deep relative response. CONCLUSION: Deep PSA response at 6 months correlates with improved OS in mAPMS. Integrating molecular markers with PSA response may inform treatment intensification or de-escalation strategies.

Biomarkers↗

PubMed2026

Systemic treatment of advanced pancreatic cancer: A Comprehensive Review.

IMPORTANCE: Pancreatic adenocarcinoma (PDAC) is an uncommon but potentially catastrophic diagnosis with historically poor prognosis. It is the tenth most prevalent cancer in the US & UK. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide, with a five-year survival rate of approximately 10%. Despite increasing understanding of its molecular biology, systemic treatment options for advanced disease remain limited, and survival outcomes have improved only modestly over the past decade. OBSERVATIONS: This narrative review traces the evolution of systemic therapy for advanced PDAC from gemcitabine monotherapy through the landmark FOLFIRINOX (PRODIGE trial) and gemcitabine/nab-paclitaxel (MPACT trial) combination regimens, which remain the standard of care. Second-line options including liposomal irinotecan plus 5-FU/LV (NAPOLI-1) and maintenance olaparib for germline BRCA1/2-mutated disease (POLO) are also reviewed. Emerging data on sequential treatment strategies (SEQUENCE trial), biomarker-driven treatment selection (PRIMUS-001, PASS-01), and precision medicine approaches targeting actionable molecular subgroups, including dMMR/MSI-H, NTRK fusions, and homologous recombination deficiency are discussed. Real-world evidence comparing FOLFIRINOX and gemcitabine/nab-paclitaxel is critically appraised, including the challenges of patient selection, tolerance, and applicability outside clinical trial settings. CONCLUSION AND RELEVANCE: Despite incremental progress, the treatment landscape of advanced PDAC remains challenging. Molecular stratification and biomarker-driven precision oncology represent the most promising path forward. This review serves as a clinical reference for physicians managing advanced pancreatic cancer, highlighting current evidence, evidence limitations, and future research priorities including prospective biomarker-driven trials and improved access to genomic testing.

Biomarkers↗

PubMed2026

Blood-based biomarkers of Alzheimer's disease and neurodegeneration in an indigenous African cohort using both Simoa and NULISA platforms.

In low- and middle-income countries, Alzheimer's disease (AD) constitutes a growing public health burden. However, AD biomarkers research remains underrepresented in African populations. This study assesses core biomarkers of AD and their relevance in the African context as potential aid in clinical diagnosis. Nigerian older adults from VALIANT cohort (n = 967) underwent biomarker quantification in plasma (p-tau217, GFAP, NfL, Aβ42 and Aβ40) employing both the Single Molecule Assay (Simoa, Quanterix) and Nucleic acid-Linked Immuno-Sandwich Assay (NULISA, Alamar). Biomarkers were associated with disease severity in clinical-diagnostic and clinical-biological groups, with stepwise increases of p-tau217, NfL and GFAP from cognitively unimpaired to dementia (p < 0.05). Results were consistent across platforms. Comparison between sexes showed higher biomarker levels in male participants across diagnostic groups. A significant effect of apoE-E4 proteotype on p-tau217 levels, after adjusting for age and sex was identified. These findings support the application of plasma AD biomarkers in the African context and the relevance of further AD biomarker research in diverse populations.

Biomarkers↗