Biology subjects

Sherif, S.

Publications and source records attributed to Sherif, S..

21 records · Page 2Linked to original sources

bioRxiv2023

MRI-assessed locus coeruleus contrast and functional response are not associated in young and late middle-aged individuals

The brainstem locus coeruleus (LC) influences a broad range of brain processes, including cognition. The so-called LC contrast is an accepted marker of the integrity of the LC that consists of a local hyperintensity on specific Magnetic Resonance Imaging (MRI) structural images. The small size of the LC has, however, rendered its functional characterization difficult in humans, including in aging. A full characterization of the structural and functional characteristics of the LC in healthy young and late middle-aged individuals is needed to determine to potential roles of the LC in different medical conditions. Here, we wanted to determine whether the activation of the LC in a mismatch negativity task changes in aging and whether the LC functional response was associated to the LC contrast. We used Ultra-High Field (UHF) 7-Tesla functional MRI (fMRI) to record brain response during an auditory oddball task in 53 healthy volunteers, including 34 younger (age: 22.15y {+/-} 3.27; 29 women) and 19 late middle-aged (age: 61.05y {+/-} 5.3; 14 women) individuals. Whole-brain analyses confirmed brain responses in the typical cortical and subcortical regions previously associated with mismatch negativity. When focusing on the brainstem, we found a significant response in the rostral part of the LC probability mask generated based on individual LC images. Although bilateral, the activation was more extensive in the left LC. Individual LC activity was not significantly different between young and late middle-aged individuals. Critically, while the LC contrast was higher in older individuals, the functional response of the LC was not associated with its contrast. These findings show that the age-related alterations of the LC structural integrity may not necessarily be related to changes in its functional response. The results further indicate that LC responses could remain stable in healthy individuals aged 20 to 70.

neuroscience↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2021

The Immune landscape of solid pediatric tumors.

BackgroundImmunotherapy is quickly coming to the forefront of cancer treatment; however, the implementation of immunotherapy in solid pediatric cancers, which classically display a low mutational load, is hindered by insufficient understanding of the determinants of cancer immune responsiveness in children. In order to better understand tumor-host interplay, we sought to characterize solid pediatric cancers based on immunological parameters using analytes extracted from gene expression data. MethodsWe used RNAseq data from the publicly available TARGET studies for five pediatric solid tumor types (408 patients): Wilms tumor (WT), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of previously identified immune signatures like the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response associated with favorable prognosis and responsiveness to immunotherapy. We also performed gene set enrichment analysis (ssGSEA) and clustering, using more than 100 immune signatures to define immune subtypes in pediatric tumors and compared the overall survival across subtypes. The expression of immune checkpoints and enrichment of oncogenic pathways were also assessed across the immune subtypes. ResultsThe five tumor types showed distinct ICR score distributions. A higher ICR score was associated with better survival in OS and NBL-HR-MYCN_NA, but with poorer survival in WT. The clustering of immune signatures revealed the same five principal modules observed in adult solid tumors: Wound Healing, TGF-B signaling, IFN-G signaling, Macrophages, and Lymphocytes. These modules clustered pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival and was characterized by low enrichment of the wound healing signature, high Th1, low Th2. Conversely, cluster S4 showed the worst survival and highest enrichment of wound healing signature, low Th1, and high Th2. Furthermore, the upregulation of the WNT/Beta-catenin pathway is associated with unfavorable outcomes and lack of T-cell infiltration in OS. ConclusionsWe demonstrated that extracranial solid pediatric tumors could be classified according to their immune disposition, unveiling similarity with adults tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

cancer biology↗