Primary and secondary defects of the thymus.

The thymus is the primary site of T-cell development, enabling generation, and selection of a diverse repertoire of T cells that recognize non-self, whilst remaining tolerant to self- antigens. Severe congenital disorders of thymic development (athymia) can be fatal if left untreated due to infections, and thymic tissue implantation is the only cure. While newborn screening for severe combined immune deficiency has allowed improved detection at birth of congenital athymia, thymic disorders acquired later in life are still underrecognized and assessing the quality of thymic function in such conditions remains a challenge. The thymus is sensitive to injury elicited from a variety of endogenous and exogenous factors, and its self-renewal capacity decreases with age. Secondary and age-related forms of thymic dysfunction may lead to an increased risk of infections, malignancy, and autoimmunity. Promising results have been obtained in preclinical models and clinical trials upon administration of soluble factors promoting thymic regeneration, but to date no therapy is approved for clinical use. In this review we provide a background on thymus development, function, and age-related involution. We discuss disease mechanisms, diagnostic, and therapeutic approaches for primary and secondary thymic defects.

Differentiation of patients with and without prostate cancer using urine 1 H NMR metabolomics.

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate-specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)-based metabolomics has proven to be promising for advancing early-detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers. This retrospective study of urine-NMR samples, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate-key metabolites involved in cellular proliferation and microbiome effects, respectively-were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis.

Screening Newborns for Low T Cell Receptor Excision Circles (TRECs) Fails to Detect Immunodeficiency, Centromeric Instability, and Facial Anomalies Syndrome.

BACKGROUND: Assessment of T-cell receptor excision circles (TRECs) in dried blood spots of newborns allows the detection of severe combined immunodeficiency (SCID) (T cells <300/µL at birth) with a presumed sensitivity of 100%. TREC screening also identifies patients with selected combined immunodeficiency (CID) (T cells >300/µL, yet <1500/µL at birth). Nevertheless, relevant CIDs that would benefit from early recognition and curative treatment pass undetected. OBJECTIVE: We hypothesized that TREC screening at birth cannot identify CIDs that develop with age. METHODS: We analyzed the number of TRECs in dried blood spots in archived Guthrie cards of 22 children who had been born in the Berlin-Brandenburg area between January 2006 and November 2018 and who had undergone hematopoietic stem-cell transplantation (HSCT) for inborn errors of immunity. RESULTS: All patients with SCID would have been identified by TREC screening, but only 4 of 6 with CID. One of these patients had immunodeficiency, centromeric instability, and facial anomalies syndrome type 2 (ICF2). Two of 3 patients with ICF whom we have been following up at our institution had TREC numbers above the cutoff value suggestive of SCID at birth. Yet all patients with ICF had a severe clinical course that would have justified earlier HSCT. CONCLUSIONS: In ICF, naïve T cells may be present at birth, yet they decline with age. Therefore, TREC screening cannot identify these patients. Early recognition is nevertheless crucial, as patients with ICF benefit from HSCT early in life.

Treatment of Infants and Children With SARS-CoV-2 Monoclonal Antibodies: A European Case Series.

BACKGROUND: Although severe COVID-19 in children is rare, those with certain pre-existing health conditions are more prone to severe disease. Monoclonal antibodies (mAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are potent antiviral agents that reduce adverse clinical outcomes in adults, but are commonly not approved for use in pediatric patients. METHODS: We retrospectively evaluated mAb treatment in children <12 years of age or <40kg with SARS-CoV-2 infection between January 1, 2021, and March 7, 2022, in 12 tertiary care centers in 3 European countries. RESULTS: We received data from 53 patients from Austria, Denmark and Germany. Median age was 5.4 years [0-13.8, interquartile range (IQR) = 6.2], and median body weight was 20 kg (3-50.1, IQR = 13). The most frequent SARS-CoV-2 variant in this study, if known, was Omicron, followed by Delta and Alpha. Pre-existing conditions included immunodeficiency, malignancy, hematologic disease, cardiac disease, chronic lung disease, chronic liver disease, kidney disease and diabetes. Forty-two patients received sotrovimab (79%), 9 casirivimab/imdevimab (17%) and 2 bamlanivimab (4%). All but 1 patient survived. Median duration of hospital stay was 3 days (0-56, IQR = 6). Seven patients required treatment in an intensive care unit, and 5 required high-flow nasal cannula treatment. Potential side effects included neutropenia (6/53, 11%), lymphopenia (3/53, 6%), nausea or vomiting (2/53, 4%), rise of alanine transaminase (1/53, 2%) and hypotonia (1/53, 2%). CONCLUSIONS: MAb treatment was well tolerated by children in this cohort.

Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer.

Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.

Cancer metabolomic markers in urine: evidence, techniques and recommendations.

Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.

Metabolomic prostate cancer fields in HRMAS MRS-profiled histologically benign tissue vary with cancer status and distance from cancer.

In this article, we review the state of the field of high resolution magic angle spinning MRS (HRMAS MRS)-based cancer metabolomics since its beginning in 2004; discuss the concept of cancer metabolomic fields, where metabolomic profiles measured from histologically benign tissues reflect patient cancer status; and report our HRMAS MRS metabolomic results, which characterize metabolomic fields in prostatectomy-removed cancerous prostates. Three-dimensional mapping of cancer lesions throughout each prostate enabled multiple benign tissue samples per organ to be classified based on distance from and extent of the closest cancer lesion as well as the Gleason score (GS) of the entire prostate. Cross-validated partial least squares-discriminant analysis separations were achieved between cancer and benign tissue, and between cancer tissue from prostates with high (≥4 + 3) and low (≤3 + 4) GS. Metabolomic field effects enabled histologically benign tissue adjacent to cancer to distinguish the GS and extent of the cancer lesion itself. Benign samples close to either low GS cancer or extensive cancer lesions could be distinguished from those far from cancer. Furthermore, a successfully cross-validated multivariate model for three benign tissue groups with varying distances from cancer lesions within one prostate indicates the scale of prostate cancer metabolomic fields. While these findings could, at present, be potentially useful in the prostate cancer clinic for analysis of biopsy or surgical specimens to complement current diagnostics, the confirmation of metabolomic fields should encourage further examination of cancer fields and can also enhance understanding of the metabolomic characteristics of cancer in myriad organ systems. Our results together with the success of HRMAS MRS-based cancer metabolomics presented in our literature review demonstrate the potential of cancer metabolomics to provide supplementary information for cancer diagnosis, staging, and patient prognostication.