Changes in Nutritional Status during Induction Phase and Their Association with Fever and Minimal Residual Disease in Paediatric Acute Lymphoblastic Leukaemia.

Background and objectives: Acute lymphoblastic leukaemia (ALL) is associated with a cytokine imbalance and oxidative stress, which can be aggravated by malnutrition. Malnutrition, defined by the World Health Organisation (WHO) as obesity or undernutrition, can affect treatment complications and outcomes. Therefore, we aimed to analyse the change in the body mass index (BMI) z-score during induction, as well as evaluate the impact of childhood malnutrition on fevers at an ALL presentation and early response to therapy. Methods: An observational cohort study of 50 consecutive children with ALL, diagnosed in 2019-2022, was performed. Patients were divided into age groups of 0-5, 6-11, and 12-17 years. BMI-for-age z-scores were used to define undernutrition and overnutrition according to WHO growth standards. Results: The number of patients with an abnormal BMI increased from 3 (6%) at diagnosis to 10 (20%) at the end of induction (from 2 (4%) to 6 (12%) in overweight/obese, and from 1 (2%) to 4 (8%) in underweight patients). At the end of induction, all overweight/obese patients were 0-5 years old. On the other hand, a statistically significant decrease in the mean BMI z-score among patients aged 12-17 was observed (p = 0.005). The mean BMI z-score differed statistically significantly among children aged 0-5 presenting with and without fever (p = 0.001). The minimal residual disease (MRD) level at the end of induction was not related to BMI at diagnosis. Conclusions: Despite the use of steroids, adolescents are prone to losing weight during an ALL induction, in contrast to preschool children, who tend to gain weight under the same treatment. BMI at diagnosis was related to a fever of ≥38 °C (at ALL presentation) in the 0-5 age group. The results emphasise the importance of careful nutritional status monitoring, with younger and older children as important target groups for weight gain and weight loss interventions, respectively.

A gene signature for immune subtyping of desert, excluded, and inflamed ovarian tumors.

PROBLEM: The current tumor immunology paradigm emphasizes the role of the immune tumor microenvironment and distinguishes several histologically and transcriptionally different immune tumor subtypes. However, the experimental validation of such classification is so far limited to selected cancer types. Here, we aimed to explore the existence of inflamed, excluded, and desert immune subtypes in ovarian cancer, as well as investigate their association with the disease outcome. METHOD OF STUDY: We used the publicly available ovarian cancer dataset from The Cancer Genome Atlas for developing subtype assignment algorithm, which was next verified in a cohort of 32 real-world patients of a known tumor subtype. RESULTS: Using clinical and gene expression data of 489 ovarian cancer patients in the publicly available dataset, we identified three transcriptionally distinct clusters, representing inflamed, excluded, and desert subtypes. We developed a two-step subtyping algorithm with COL5A2 serving as a marker for separating excluded tumors, and CD2, TAP1, and ICOS for distinguishing between inflamed and desert tumors. The accuracy of gene expression-based subtyping algorithm in a real-world cohort was 75%. Additionally, we confirmed that patients bearing inflamed tumors are more likely to survive longer. CONCLUSION: Our results highlight the presence of transcriptionally and histologically distinct immune subtypes among ovarian tumors and emphasize the potential benefit of immune subtyping as a clinical tool for treatment tailoring.