Biology subjects

Omran, D. K.

Publications and source records attributed to Omran, D. K..

3 recordsLinked to original sources

bioRxiv2024

Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma

High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer. STATEMENT OF SIGNIFICANCEThis study maps the immune response in fallopian tube precursors of high-grade serous ovarian cancer, highlighting localized interferon signaling, CIN, and competing immune surveillance and suppression along the progression axis. It provides an explorable public spatial profiling atlas for investigating precancer mechanisms, biomarkers, and early detection and interception strategies.

cancer biology↗

bioRxiv2022

Performance of computational algorithms to deconvolve heterogeneous bulk tumor tissue depends on experimental factors

BackgroundSingle-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay. ResultsWe generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method. ConclusionsPrevious benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.

bioinformatics↗

bioRxiv2021

Systematic analysis of CD39, CD103, CD137 and PD-1 as biomarkers for naturally occurring tumor antigen-specific TILs

The detection of tumor-specific T cells in solid tumors is integral to the interrogation of endogenous antitumor responses and to the advancement of downstream therapeutic applications, such as checkpoint immunotherapy and adoptive cell transfer. A number of biomarkers are reported to identify endogenous tumor-specific tumor infiltrating lymphocytes (TILs), namely CD137, PD-1, CD103, and CD39, however a direct comparison of these molecules has yet to be performed. Here, we evaluate these biomarkers in primary human high-grade serous ovarian tumor samples using single-cell mass cytometry to characterize and compare their relative phenotypic profiles, as well as their response to autologous tumor cells ex vivo. CD137+, PD-1+, CD103+, and CD39+ TILs are all detectable in tumor samples with CD137+ TILs being the least abundant. PD-1+, CD103+, and CD39+ TILs all express a subset of CD137+ cells, while CD137+ TILs highly co-express the aforementioned markers. CD137+ TILs exhibit the highest expression of cytotoxic effector molecules, such as IFN{gamma} and Granzyme B, compared to PD-1+, CD103+ or CD39+ TILs. Removal of CD137+ TILs from PD-1+, CD103+, or CD39+ TILs results in lower secretion of IFN{gamma} in response to autologous tumor stimulation, while CD137+ TILs highly secrete IFN{gamma} in an HLA-dependent manner. CD137+ TILs exhibited an exhausted phenotype with CD28 co-expression, suggestive of antigen recognition and receptiveness to reinvigoration via immune checkpoint blockade. Together, our findings demonstrate that the antitumor abilities of PD-1+, CD103+, and CD39+ TILs are mainly derived from a subset of TILs expressing CD137, implicating CD137 is a more selective biomarker for naturally occurring tumor-specific TILs.

immunology↗