Biology subjects

Nemati, N.

Publications and source records attributed to Nemati, N..

3 recordsLinked to original sources

bioRxiv2024

Dissecting heterogeneity of tumor microenvironment in colorectal cancer using high-resolution single-cell atlas

The immune composition of the tumor microenvironment (TME) has a major impact on the therapeutic response and clinical outcome in patients with colorectal cancer (CRC). Here, we comprehensively characterize the TME at the single-cell level by first building a large-scale atlas that integrates 4.27 million single cells from 1,670 patient samples. We then complemented the atlas with single-cell profiles from four CRC cohorts with 266 patients, including cells with low mRNA content, spatial transcriptional profiles from 3.7 million cells, and protein profiles from 0.7 million cells. The analysis of the atlas allows refined tumor classification into four immune phenotypes: immune desert, B cell enriched, T cell enriched, and myeloid cell enriched subtypes. Within the myeloid compartment we uncover distinct subpopulations of neutrophils that acquire new functional properties in blood and in the TME, including anti-tumorigenic capabilities. Further, spatial multimodal single-cell profiling reveals that neutrophils are organized in clusters within distinct functional niches. Finally, using an orthotopic mouse model we show that cancer-derived systemic signals modify neutrophil production in the bone marrow, providing evidence for tumor-induced granulopoiesis. Our study provides a big data resource for the CRC and suggests novel therapeutic strategies targeting neutrophils.

bioinformatics↗

bioRxiv2023

13C tracer analysis reveals the landscape of metabolic checkpoints in human CD8+ T cell differentiation

Naive T cells remain in an actively maintained state of quiescence until activation by antigenic signals, upon which they start proliferation and generation of effector cells to initiate a functional immune response. Metabolic reprogramming is essential to meet the biosynthetic demands of the differentiation process, and failure to do so can promote the development of hypofunctional exhausted T cells. Here we used 13C metabolomics and transcriptomics to study the metabolic dynamics of CD8+ T cells in their complete course of differentiation from naive over stem-like memory to effector cells. The quiescence of naive T cells was evident in a profound suppression of glucose oxidation and a decreased expression of ENO1, downstream of which no glycolytic flux was detectable. Moreover, TCA cycle activity was low in naive T cells and associated with a downregulation of SDH subunits. Upon stimulation and exit from quiescence, the initiation of cell growth and proliferation was accompanied by differential expression of T cell regulatory genes and metabolic reprogramming towards aerobic glycolysis with high rates of nutrient uptake, respiration and lactate production. High flux in anabolic pathways imposed a strain on NADH homeostasis, which coincided with engagement of the proline cycle for mitochondrial redox shuttling. With acquisition of effector functions, cells increasingly relied on glycolysis as opposed to oxidative phosphorylation, which paradoxically was not linked to changes in mitochondrial abundance. We further investigated the metabolic phenotype of exhausted T cells, finding that decreased effector function concurred with a reduction in mitochondrial metabolism, glycolysis and amino acid import, and an upregulation of suppressive and quiescence-associated genes, including TXNIP and KLF2. Thus, these results identify multiple features critical for the metabolic reprogramming that supports quiescence, proliferation and effector function of CD8+ T cells during differentiation. Further, an impairment of the same processes in exhaustion suggests that targeting these control points may be useful for both modulation of differentiation and prevention of exhaustion.

immunology↗

bioRxiv2022

Functional precision profiling reveals non-mutational rewiring of kinase signaling networks in colorectal cancer

BackgroundDespite major advances in the development of targeted therapies, precision (immuno)oncology approaches for patients with colorectal cancer continue to lag behind other solid cancers. Functional precision oncology - a strategy that is based on perturbing primary tumor cells from cancer patients with drugs - could provide an alternate road forward to personalize treatment. MethodsWe extend here the functional precision oncology paradigm to measuring phosphoproteome landscapes using patient-derived organoids (PDOs). We first employed steady-state multi-omics (exome sequencing, RNA sequencing, and proteomics) and single-cell characterization of the PDOs. The PDOs were then perturbed with kinase inhibitors (MEKi, PI3Ki, mTORi, TBKi, BRAFi, and TAKi), and large-scale phosphoproteomics profiling using data-independent acquisition was carried out. Further, we used imaging mass-cytometry-based single-cell proteomic profiling of the primary tumors to characterize cellular composition of the tumor-microenvironment (TME) and to quantify heterocellular signaling crosstalk. ResultsWe show that kinase inhibitors induce profound off-target effects resulting in a crosstalk with oncogenic and immune-related pathways. Reconstruction of the topologies of the kinase networks revealed that the patient-specific rewiring of the central EGFR-RAS-MAPK network is unaffected by mutations. Moreover, we show non-genetic heterogeneity of the PDOs and patient- and inhibitor-specific upregulation of stemness and differentiation genes by kinase inhibitors. We complemented our functional profiling by spatial proteomics profiling of the primary tumors using imaging mass cytometry. We quantify spatial heterocellular crosstalk and tumor-immune cell interactions, showing an avoidance of PD1+ immune cells and PD-L1+ tumor cells. ConclusionsCollectively, we provide a multi-modal framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno)-oncology in colorectal cancer.

cancer biology↗