Biomarkers For Early Intervention Research Articles

P0557 Multiomics analysis identifies key pathways associated with severe disease course in children with IBD: a prospective study

Abstract Background Identifying biological pathways that are associated with poor disease course in IBD may improve early risk stratification and guide targeted therapeutic approaches. We therefore aimed to integrate multiomics data determined at disease onset to explore pathways associated with disease course in pediatric IBD, focusing on both microbial and host-derived signals. Methods Children with IBD were enrolled at disease onset and followed prospectively for18 months. Samples for whole exome sequencing (WES), serum metabolomics, stool metabolomics, and microbiome were analyzed using MaAsLin2 for differential expression and Random Forest for outcome prediction for single-omic. A late integration approach with Support Vector Machine was applied for multi-omics prediction. Severe outcome was defined as steroid-dependency, early or multiple biologics, or IBD-related hospitalizations/surgeries. Pathway enrichment analyses for each omic were assessed using Fisher’s exact test and odd ratio (OR) was calculated to asses the enrichment magnitude. Results Altogether, 182 children were enrolled (123 with CD (28% severe course) and 59 UC (39% severe course). Several pathways were differentially enriched in the severe group (Figure 1). Shared pathways across CD and UC included AGE-RAGE signaling, implicated in oxidative stress and inflammation (OR=36 [95%CI 3-459] in CD and OR=92 [7-1121] in UC), and choline metabolism in cancer, associated with lipid signaling, inflammation, and fibrosis (OR=37 [95%CI 4-382] and OR=66 [3-475]). CD-specific pathways included sphingolipid metabolism (OR=30 [95%CI 2-393]), linked to barrier dysfunction and chronic inflammation, glycerolipid metabolism (OR=11 [95%CI 1-160]), and fat digestion and absorption (OR=16 [95%CI 3-167]), highlighting disruptions in nutrient absorption and inflammation. UC-specific pathways included pathways in cancer (OR=23 [95%CI 3-263]), reflecting tissue remodeling and neoplasia risk, inflammatory regulation of TRP channels (OR=14 [95%CI 1-143]), contributing to colonic inflammation, sensory perception and purine metabolism (OR=5 [95%CI 0.4-58]). Random Forest machine learning models showed modest to no predictive performance of the different omics (area under ROC curve ranged between 0.41-0.67 in CD, and 0.38-0.72 in UC; Table 1). Conclusion Key biological pathways were identified in association with severity of disease course in pediatric IBD, utilizing large datasets of genetics, metabolomics and microbiome. The findings offer insights into mechanisms underlying pediatric IBD and highlight potential therapeutic targets as well as biomarkers for early intervention.

Immune changes in pregnancy: associations with pre-existing conditions and obstetrical complications at the 20th gestational week—a prospective cohort study

BackgroundPregnancy is a complex biological process and serious complications can arise when the delicate balance between the maternal and semi-allogeneic fetal immune systems is disrupted or challenged. Gestational diabetes mellitus (GDM), pre-eclampsia, preterm birth, and low birth weight pose serious threats to maternal and fetal health. Identification of early biomarkers through an in-depth understanding of molecular mechanisms is critical for early intervention.MethodsWe analyzed the associations between 47 proteins involved in inflammation, chemotaxis, angiogenesis, and immune system regulation, maternal and neonatal health outcomes, and the baseline characteristics and pre-existing conditions of the mother in a prospective cohort of 1049 pregnant women around the 20th gestational week. We used Bayesian linear regression models to examine the impact of risk factors on biomarker levels and Bayesian cause-specific parametric proportional hazards models to analyze the effect of biomarkers on maternal and neonatal outcomes. We evaluated the predictive value of baseline characteristics and 47 proteins using machine-learning models and identified the most predictive biomarkers using Shapley additive explanation scores.ResultsAssociations were identified between specific inflammatory markers and several conditions, including maternal age and pre-pregnancy body mass index, chronic diseases, complications from prior pregnancies, and COVID-19 exposure. Smoking during pregnancy affected GM-CSF and 9 other biomarkers. Distinct biomarker patterns were observed for different ethnicities. Within obstetric complications, IL-6 inversely correlated with pre-eclampsia risk, while birth weight to gestational age ratio was linked to markers including VEGF and PlGF. GDM was associated with IL-1RA, IL-17D, and eotaxin-3. Severe postpartum hemorrhage correlated with CRP, IL-13, and proteins of the IL-17 family. Predictive modeling yielded area under the receiver operating characteristic curve values of 0.708 and 0.672 for GDM and pre-eclampsia, respectively. Significant predictive biomarkers for GDM included IL-1RA and eotaxin-3, while pre-eclampsia prediction yielded the highest predictions when including MIP-1β, IL-1RA, and IL-12p70.ConclusionsOur study provides novel insights into the interplay between preexisting conditions and immune dysregulation in pregnancy. These findings contribute to our understanding of the pathophysiology of obstetric complications and the identification of novel biomarkers for early intervention(s) to improve maternal and fetal health.

Abstract LB212: Transcriptional dosage of oncogenic KRAS drives lung adenocarcinoma cell states, progression and metastasis

Abstract Metastasis is the endpoint of tumorigenesis and is generally diagnosed at an untreatable stage. The molecular mechanisms underlying metastasis and biomarkers for early intervention are largely unknown. Here, combining a mouse model of aggressive Kras-driven non-small-cell lung cancer with in vivo fate mapping and CRISPR activation screens, we show that transcriptional amplification of oncogenic Kras promotes orthotopic lung cancer lesions growth as well as oligoclonal and polyclonal metastasis to distal organs. Mild Kras transcriptional up-regulation by CRISPRa is sufficient to fuel competitive advantage in vitro and in vivo. Parallel CRISPR activation and transcriptome sequencing show that KrasG12D amplification cooperates with sterile inflammation to drive tumor progression and with the TGFß pathway to promote metastasis. Chromatin profiling of Kras-amplifying cells uncovers transcriptional regulators potentially collaborating with oncogenic Kras to drive lung cancer and metastasis in vivo. Transcriptional modulation of KRAS dosage in mouse cell and pharmacological inhibition in human PDXs affect cell stress and differentiation programs. These observations are corroborated by bulk and single-cell RNA-seq analysis in patients. Collectively, our data on a model oncogene advance our current understanding of how KRAS drives tumor evolution, with implications for prognosis and treatment of patients. Citation Format: Michela Serresi, Sonia Kertalli, Yuliia Dramaretska, Matthias Jürgen Schmitt, Heike Naumann, Maria Zschummel, Gaetano Gargiulo. Transcriptional dosage of oncogenic KRAS drives lung adenocarcinoma cell states, progression and metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB212.