Daniele Morelli

Background: Chronic inflammation from visceral obesity contributes to metabolic disorders and cancer through cytokine imbalance. Accurate cytokine measurement is crucial to understand these links. This study examined challenges in quantifying interleudin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), leptin, and adiponectin in historical biobank samples with limited volumes and varying plasma anticoagulants. Methods: Luminex-MAGPIX platform was used to evaluate three analytical aspects. Single-well precision was assessed via intra- and inter-assay coefficients of variability (CVs). Plasma matrix effects were examined by pairwise comparison of analyte concentrations across citrate, heparin, and EDTA plasma from 10 volunteers. Cytokine stability was tested after one freeze-thaw cycle (analysis of variance). Results: Single-well measurements showed good precision (CV <10% intra-assay, <15% inter-assay). Plasma matrix affected absolute concentrations. In particular, all analytes were lower in citrate than in EDTA and heparin, but relative relationships and subject-specific rankings remained preserved. Pearson correlation coefficients for IL-6, leptin, and adiponectin were high across matrices (r-range = 0.952–0.999), whereas correlations for TNF-α were lower (r-range = 0.897–0.972). Freeze–thaw stability was analyte- and matrix-dependent: leptin remained stable in heparin and EDTA but decreased 9.5% in citrate; adiponectin was stable in citrate but decreased in heparin (−9.0%) and EDTA (−11.8%). IL-6 and TNF-α were unaffected. Conclusion: IL-6, TNF-α, leptin, and adiponectin were accurately quantified using single-well Luminex assays and showed reasonable tolerance to a single freeze–thaw cycle, offering a practical strategy for preserving valuable specimens. Although plasma anticoagulant affected absolute concentrations, the preservation of relative analyte rankings permits their use in most study designs but limit absolute value comparisons.

Untargeted metabolomics faces significant challenges in standardization due to variability introduced by sample preparation and analytical workflows. We systematically evaluated the impact of biological matrices, extraction protocols, and chromatographic configurations to establish a mechanism-informed framework aimed at improving reproducibility in large-scale clinical and epidemiological studies. Three extraction protocols were compared using an in-house pooled heparin plasma: monophasic protein precipitation with isopropanol (IPA), methanol:acetonitrile (MeOH:ACN), and a modified Matyash biphasic method. The most reproducible protocol was then applied to four blood matrices. Samples were analysed using untargeted metabolomics on hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) HPLC columns, with mass spectrometry data processed using Compound Discoverer. Both IPA and MeOH:ACN extractions achieved over 80% of features with coefficient of variation (CV%) ≤ 30% for both RP and HILIC, whereas the Matyash method showed higher variability, with a larger proportion of metabolites exhibiting CV% > 30%. Across matrices, RP chromatography detected over 80% of metabolites with CV% < 30%, while HILIC showed higher variability, with at least 20% of metabolites above this threshold. Among matrices, serum and heparin plasma outperformed EDTA and citrate in reproducibility. We propose a standardized workflow in which monophasic extractions combined with RP chromatography maximize reproducibility and metabolite coverage, minimizing methodological artefacts and providing a reliable framework for robust biological discovery in large-scale untargeted metabolomics studies.

Supplemental Table 2. Prognostic Index of Inflammatory Biomarkers for primary Retroperitoneal Sarcoma (IBPI)

Supplemental Table 1. NLR changes after neoadjuvant treatments*

Supplemental Figure 2. Association of IBPI with postoperative serious complications Clavien-Dindo grade 3 or higher.

Supplemental Figure 1. Relationship between the risk of death, expressed as log-relative hazard from multivariable Cox model, and inflammation-related serum biomarkers.

Supplemental Table 1. NLR changes after neoadjuvant treatments*

Supplemental Table 2. Prognostic Index of Inflammatory Biomarkers for primary Retroperitoneal Sarcoma (IBPI)

Supplemental Figure 2. Association of IBPI with postoperative serious complications Clavien-Dindo grade 3 or higher.