Colorectal cancer (CRC) is a major public health issue worldwide, and novel tumor markers may contribute to its efficient management by helping in early detection, prognosis or surveillance of disease. The aim of our study was to identify new serum biomarkers for CRC, and we followed a phased biomarker discovery and validation process to obtain an accurate preliminary assessment of potential clinical utility. We compared colonic tumors and matched normal tissue from 15 CRC patients, using two‐dimensional difference gel electrophoresis (2D‐DIGE), and identified 17 proteins that had significant differential expression. These results were further confirmed by western blotting for heat shock protein (HSP) 60, glutathione‐S‐transferase Pi, α‐enolase, T‐complex protein 1 subunit β, and leukocyte elastase inhibitor, and by immunohistochemistry for HSP60. Using mAbs raised against HSP60, we developed a reliable (precision of 5–15%) and sensitive (0.3 ng·mL⁻¹) immunoassay for the detection of HSP60 in serum. Elevated levels of HSP60 were found in serum from CRC patients in two independent cohorts; the receiver‐operating characteristic curve obtained in 112 patients with CRC and 90 healthy controls had an area under the curve (AUC) of 0.70, which was identical to the AUC of carcinoembryonic antigen. Combination of serum markers improved clinical performance: the AUC of a three‐marker logistic regression model combining HSP60, carcinoembryonic antigen and carbohydrate antigen 19‐9 reached 0.77. Serum HSP60 appeared to be more specific for late‐stage CRC; therefore, future studies should evaluate its utility for determining prognosis or monitoring therapy rather than early detection.

Mass spectrometry (MS) in Selected Reaction Monitoring (SRM) mode is proposed for in-depth characterisation of microorganisms in a multiplexed analysis. Within 60–80 minutes, the SRM method performs microbial identification (I), antibiotic-resistance detection (R), virulence assessment (V) and it provides epidemiological typing information (T). This SRM application is illustrated by the analysis of the human pathogen Staphylococcus aureus, demonstrating its promise for rapid characterisation of bacteria from positive blood cultures of sepsis patients.

In a subset of children and adolescents, SARS-CoV-2 infection induces a severe acute hyperinflammatory shock¹ termed multisystem inflammatory syndrome in children (MIS-C) at four to eight weeks after infection. MIS-C is characterized by a specific T cell expansion² and systemic hyperinflammation³. The pathogenesis of MIS-C remains largely unknown. Here we show that acute MIS-C is characterized by impaired reactivation of virus-reactive memory T cells, which depends on increased serum levels of the cytokine TGFβ resembling those that occur during severe COVID-19 (refs. ^4,5). This functional impairment in T cell reactivity is accompanied by the presence of TGFβ-response signatures in T cells, B cells and monocytes along with reduced antigen-presentation capabilities of monocytes, and can be reversed by blocking TGFβ. Furthermore, T cell receptor repertoires of patients with MIS-C exhibit expansion of T cells expressing TCRVβ21.3, resembling Epstein–Barr virus (EBV)-reactive T cell clones capable of eliminating EBV-infected B cells. Additionally, serum TGFβ in patients with MIS-C can trigger EBV reactivation, which is reversible with TGFβ blockade. Clinically, the TGFβ-induced defect in T cell reactivity correlates with a higher EBV seroprevalence in patients with MIS-C compared with age-matched controls, along with the occurrence of EBV reactivation. Our findings establish a connection between SARS-CoV-2 infection and COVID-19 sequelae in children, in which impaired T cell cytotoxicity triggered by TGFβ overproduction leads to EBV reactivation and subsequent hyperinflammation.

Background: Fever is one of the leading causes of consultation in the pediatric emergency department for patients under the age of 3 years. Distinguishing between bacterial and viral infections etiologies in febrile patients remains challenging. We hypothesized that specific host biomarkers for viral infections, such as type I-interferon (IFN), could help clinicians’ decisions and limit antibiotic overuse. Methods: Paxgene tubes and serum were collected from febrile children (n = 101), age from 7 days to 36 months, with proven viral or bacterial infections, being treated at pediatric emergency departments in France. We assessed the performance of an IFN signature, which was based on quantification of expression of IFN-stimulated genes using the Nanostring® technology and plasma IFN-α quantified by digital ELISA technology. Results: Serum concentrations of IFN-α were below the quantification threshold (30 fg/mL) for 2% (1/46) of children with proven viral infections and for 71% (39/55) of children with bacterial infections (P < 0.001). IFN-α concentrations and IFN score were significantly higher in viral compared to bacterial infection (P < 0.001). There was a strong correlation between serum IFN-α concentrations and IFN score (p-pearson = 0.83). Both serum IFN-α concentration and IFN score robustly discriminated (Area Under the Curve >0.91 for both) between viral and bacterial infection in febrile children, compared to C-reactive protein (0.83). Conclusions: IFN-α is increased in blood of febrile infants with viral infections. The discriminative performance of IFN-α femtomolar concentrations as well as blood transcriptional signatures could show a diagnostic benefit and potentially limit antibiotic overuse. Clinical Trials Registration: clinicaltrials.gov (NCT03163628).

Protein biomarker discovery has inherent challenges linked to the validation of the analytical method used or to the impact of biological matrices. Matrix influences must be mastered to guarantee the reliability of the identified biomarkers to monitor human diseases. In this study, multiplexed mass spectrometry assays in selected reaction monitoring (SRM) mode have been developed to measure 107 inflammatory putative proteins in matched serum and plasma from 36 ICU trauma patients. The assays’ validation directly in clinical samples was shown to be valuable to manage intersample variability. Using the validation process developed here, assays were validated for 58 biomarkers in serum, 57 in plasma, and 55 in both matrices. Correlation analyses demonstrated that the quantitation using SRM of most of the validated biomarkers (45/55) was impacted by the biological matrix and that the matrix impact was biomarker-dependent. Among the 45 impacted biomarkers, 23 were nevertheless correlated between serum and plasma, whereas the quantitation was shown to be equivalent in both for the 10 last proteins. Matrix selection using SRM is therefore suggested to be suitable prior to clinical evaluation of biomarkers in a large cohort of patients.