Urine-derived podocytes from steroid resistant nephrotic syndrome patients as a model for renal-progenitor derived extracellular vesicles effect and drug screening.

Background: Personalized disease models are crucial for assessing the specific response of diseased cells to drugs, particularly novel biological therapeutics. Extracellular vesicles (EVs), nanosized vesicles released by cells for intercellular communication, have gained therapeutic interest due to their ability to reprogram target cells. We here utilized urinary podocytes obtained from children affected by steroid-resistant nephrotic syndrome with characterized genetic mutations as a model to test the therapeutic potential of EVs derived from kidney progenitor cells. Methods: EVs were isolated from kidney progenitor cells (nKPCs) derived from the urine of a preterm neonate. Three lines of urinary podocytes obtained from nephrotic patients' urine and a line of Alport patient podocytes were characterized and used to assess albumin permeability in response to various drugs or to nKPC-EVs. RNA sequencing was conducted to identify commonly modulated pathways. Results: Podocytes appeared unresponsive to pharmacological treatments, except for a podocyte line demonstrating responsiveness, in alignment with the patient's clinical response at 48 months. At variance, treatment with the nKPC-EVs was able to significantly reduce permeability in all the steroid-resistant patients-derived podocytes as well as in the line of Alport-derived podocytes. RNA sequencing of nKPC-EV-treated podocytes revealed the common upregulation of two genes (small ubiquitin-related modifier 1 (SUMO1) and Sentrin-specific protease 2 (SENP2)) involved in the SUMOylation pathway, a process recently demonstrated to play a role in slit diaphragm stabilization. Gene ontology analysis on podocyte expression profile highlighted cell-to-cell adhesion as the primary upregulated biological activity in treated podocytes. Conclusions: nKPCs emerge as a promising non-invasive source of EVs with potential therapeutic effects on podocyte dysfunction. Furthermore, our findings suggest the possibility of establishing a non-invasive in vitro model for screening regenerative compounds on patient-derived podocytes.

CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applications.

BACKGROUND: The analysis of large and complex biological datasets in bioinformatics poses a significant challenge to achieving reproducible research outcomes due to inconsistencies and the lack of standardization in the analysis process. These issues can lead to discrepancies in results, undermining the credibility and impact of bioinformatics research and creating mistrust in the scientific process. To address these challenges, open science practices such as sharing data, code, and methods have been encouraged. RESULTS: CREDO, a Customizable, REproducible, DOcker file generator for bioinformatics applications, has been developed as a tool to moderate reproducibility issues by building and distributing docker containers with embedded bioinformatics tools. CREDO simplifies the process of generating Docker images, facilitating reproducibility and efficient research in bioinformatics. The crucial step in generating a Docker image is creating the Dockerfile, which requires incorporating heterogeneous packages and environments such as Bioconductor and Conda. CREDO stores all required package information and dependencies in a Github-compatible format to enhance Docker image reproducibility, allowing easy image creation from scratch. The user-friendly GUI and CREDO's ability to generate modular Docker images make it an ideal tool for life scientists to efficiently create Docker images. Overall, CREDO is a valuable tool for addressing reproducibility issues in bioinformatics research and promoting open science practices.

A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity.

Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumour research, enabling the exploration of molecular complexities at the individual cell level. It offers new technical possibilities for advancing tumour research with the potential to yield significant breakthroughs. However, deciphering meaningful insights from scRNA-seq data poses challenges, particularly in cell annotation and tumour subpopulation identification. Efficient algorithms are therefore needed to unravel the intricate biological processes of cancer. To address these challenges, benchmarking datasets are essential to validate bioinformatics methodologies for analysing single-cell omics in oncology. Here, we present a 10XGenomics scRNA-seq experiment, providing a controlled heterogeneous environment using lung cancer cell lines characterised by the expression of seven different driver genes (EGFR, ALK, MET, ERBB2, KRAS, BRAF, ROS1), leading to partially overlapping functional pathways. Our dataset provides a comprehensive framework for the development and validation of methodologies for analysing cancer heterogeneity by means of scRNA-seq.

Surface protein and functional analyses identify CD4+CD39+ TCR αß+ and activated TCR Vδ1+ cells with distinct pro-inflammatory functions in Crohn's disease lesions.

Crohn's disease (CD) is a chronic immune-mediated disorder of the gastrointestinal tract. Extensive screening studies have revealed the accumulation of immune cell subsets with unique plasticity and immunoregulatory properties in patients with CD. We performed phenotypic and functional studies on inflamed and non-inflamed bioptic tissue to investigate the presence of distinct T cells in the intestinal mucosa of CD patients. We analysed hundreds of surface molecules expressed on cells isolated from the intestinal tissue of CD patients using anti-CD45 mAbs-based barcoding. A gene ontology enrichment analysis showed that proteins that regulate the activation of T cells were the most enriched group. We, therefore, designed T-cell focused multicolour flow-cytometry panels and performed clustering analysis which revealed an accumulation of activated TEM CD4+CD39+ T cells producing IL-17 and IL-21 and increased frequency of terminally differentiated TCR Vδ1+ cells producing TNF-α and IFN-γ in inflamed tissue of CD patients. The different functional capacities of CD4+ and TCR Vδ1+ cells in CD lesions indicate their non-overlapping contribution to inflammation. The abnormally high number of terminally differentiated TCR Vδ1+ cells suggests that they are continuously activated in inflamed tissue, making them a potential target for novel therapies.

RNAseq Analysis of Livers from Pigs Treated with Testosterone and Nandrolone Esters: Selection and Field Validation of Transcriptional Biomarkers.

The use of anabolic-androgenic steroids (AASs) as growth promoters in farm animals is banned in the European Union, representing both an illicit practice and a risk for consumer health. However, these compounds are still illegally administered, often in the form of synthetic esters. This work aimed to characterize significant coding RNA perturbations related to the illicit administration of testosterone and nandrolone esters in fattening pigs. A total of 27 clinically healthy 90-day-old pigs were randomly assigned to test and control groups. Nine animals were treated with testosterone esters (Sustanon®) and other nine with nandrolone esters (Myodine®). At the end of the trial, liver samples were collected and analyzed using RNAseq, allowing the identification of 491 differentially expressed genes (DEGs). The transcriptional signature was further characterized by a smaller sub-cluster of 143 DEGs, from which a selection of 16 genes was made. The qPCR analysis confirmed that the identified cluster could still give good discrimination between untreated gilt and barrows compared to the relative testosterone-treated counterparts. A conclusive field survey on 67 liver samples collected from pigs of different breeds and weight categories confirmed, in agreement with testosterone residue profiles, the specificity of selected transcriptional biomarkers, showing their potential applications for screening purposes when AAS treatment is suspected, allowing to focus further investigations of competent authorities and confirmatory analysis where needed.

Circulating hsa-miR-5096 predicts 18F-FDG PET/CT positivity and modulates somatostatin receptor 2 expression: a novel miR-based assay for pancreatic neuroendocrine tumors.

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are rare diseases encompassing pancreatic (PanNETs) and ileal NETs (SINETs), characterized by heterogeneous somatostatin receptors (SSTRs) expression. Treatments for inoperable GEP-NETs are limited, and SSTR-targeted Peptide Receptor Radionuclide Therapy (PRRT) achieves variable responses. Prognostic biomarkers for the management of GEP-NET patients are required. 18F-FDG uptake is a prognostic indicator of aggressiveness in GEP-NETs. This study aims to identify circulating and measurable prognostic miRNAs associated with 18F-FDG-PET/CT status, higher risk and lower response to PRRT. Methods: Whole miRNOme NGS profiling was conducted on plasma samples obtained from well-differentiated advanced, metastatic, inoperable G1, G2 and G3 GEP-NET patients enrolled in the non-randomized LUX (NCT02736500) and LUNET (NCT02489604) clinical trials prior to PRRT (screening set, n= 24). Differential expression analysis was performed between 18F-FDG positive (n=12) and negative (n=12) patients. Validation was conducted by Real Time quantitative PCR in two distinct well-differentiated GEP-NET validation cohorts, considering the primary site of origin (PanNETs n=38 and SINETs n=30). The Cox regression was applied to assess independent clinical parameters and imaging for progression-free survival (PFS) in PanNETs. In situ RNA hybridization combined with immunohistochemistry was performed to simultaneously detect miR and protein expression in the same tissue specimens. This novel semi-automated miR-protein protocol was applied in PanNET FFPE specimens (n=9). In vitro functional experiments were performed in PanNET models. Results: While no miRNAs emerged to be deregulated in SINETs, hsa-miR-5096, hsa-let-7i-3p and hsa-miR-4311 were found to correlate with 18F-FDG-PET/CT in PanNETs (p-value:<0.005). Statistical analysis has shown that, hsa-miR-5096 can predict 6-month PFS (p-value:<0.001) and 12-month Overall Survival upon PRRT treatment (p-value:<0.05), as well as identify 18F-FDG-PET/CT positive PanNETs with worse prognosis after PRRT (p-value:<0.005). In addition, hsa-miR-5096 inversely correlated with both SSTR2 expression in PanNET tissue and with the 68Gallium-DOTATOC captation values (p-value:<0.05), and accordingly it was able to decrease SSTR2 when ectopically expressed in PanNET cells (p-value:<0.01). Conclusions: hsa-miR-5096 well performs as a biomarker for 18F-FDG-PET/CT and as independent predictor of PFS. Moreover, exosome-mediated delivery of hsa-miR-5096 may promote SSTR2 heterogeneity and thus resistance to PRRT.

Promiscuous recognition of MR1 drives self-reactive mucosal-associated invariant T cell responses.

Mucosal-associated invariant T (MAIT) cells use canonical semi-invariant T cell receptors (TCR) to recognize microbial riboflavin precursors displayed by the antigen-presenting molecule MR1. The extent of MAIT TCR crossreactivity toward physiological, microbially unrelated antigens remains underexplored. We describe MAIT TCRs endowed with MR1-dependent reactivity to tumor and healthy cells in the absence of microbial metabolites. MAIT cells bearing TCRs crossreactive toward self are rare but commonly found within healthy donors and display T-helper-like functions in vitro. Experiments with MR1-tetramers loaded with distinct ligands revealed significant crossreactivity among MAIT TCRs both ex vivo and upon in vitro expansion. A canonical MAIT TCR was selected on the basis of extremely promiscuous MR1 recognition. Structural and molecular dynamic analyses associated promiscuity to unique TCRß-chain features that were enriched within self-reactive MAIT cells of healthy individuals. Thus, self-reactive recognition of MR1 represents a functionally relevant indication of MAIT TCR crossreactivity, suggesting a potentially broader role of MAIT cells in immune homeostasis and diseases, beyond microbial immunosurveillance.

Targeting CCR7-PI3Kγ overcomes resistance to tyrosine kinase inhibitors in ALK-rearranged lymphoma.

Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) show potent efficacy in several ALK-driven tumors, but the development of resistance limits their long-term clinical impact. Although resistance mechanisms have been studied extensively in ALK-driven non-small cell lung cancer, they are poorly understood in ALK-driven anaplastic large cell lymphoma (ALCL). Here, we identify a survival pathway supported by the tumor microenvironment that activates phosphatidylinositol 3-kinase γ (PI3K-γ) signaling through the C-C motif chemokine receptor 7 (CCR7). We found increased PI3K signaling in patients and ALCL cell lines resistant to ALK TKIs. PI3Kγ expression was predictive of a lack of response to ALK TKI in patients with ALCL. Expression of CCR7, PI3Kγ, and PI3Kδ were up-regulated during ALK or STAT3 inhibition or degradation and a constitutively active PI3Kγ isoform cooperated with oncogenic ALK to accelerate lymphomagenesis in mice. In a three-dimensional microfluidic chip, endothelial cells that produce the CCR7 ligands CCL19/CCL21 protected ALCL cells from apoptosis induced by crizotinib. The PI3Kγ/δ inhibitor duvelisib potentiated crizotinib activity against ALCL lines and patient-derived xenografts. Furthermore, genetic deletion of CCR7 blocked the central nervous system dissemination and perivascular growth of ALCL in mice treated with crizotinib. Thus, blockade of PI3Kγ or CCR7 signaling together with ALK TKI treatment reduces primary resistance and the survival of persister lymphoma cells in ALCL.

p140Cap inhibits ß-Catenin in the breast cancer stem cell compartment instructing a protective anti-tumor immune response.

The p140Cap adaptor protein is a tumor suppressor in breast cancer associated with a favorable prognosis. Here we highlight a function of p140Cap in orchestrating local and systemic tumor-extrinsic events that eventually result in inhibition of the polymorphonuclear myeloid-derived suppressor cell function in creating an immunosuppressive tumor-promoting environment in the primary tumor, and premetastatic niches at distant sites. Integrative transcriptomic and preclinical studies unravel that p140Cap controls an epistatic axis where, through the upstream inhibition of ß-Catenin, it restricts tumorigenicity and self-renewal of tumor-initiating cells limiting the release of the inflammatory cytokine G-CSF, required for polymorphonuclear myeloid-derived suppressor cells to exert their local and systemic tumor conducive function. Mechanistically, p140Cap inhibition of ß-Catenin depends on its ability to localize in and stabilize the ß-Catenin destruction complex, promoting enhanced ß-Catenin inactivation. Clinical studies in women show that low p140Cap expression correlates with reduced presence of tumor-infiltrating lymphocytes and more aggressive tumor types in a large cohort of real-life female breast cancer patients, highlighting the potential of p140Cap as a biomarker for therapeutic intervention targeting the ß-Catenin/ Tumor-initiating cells /G-CSF/ polymorphonuclear myeloid-derived suppressor cell axis to restore an efficient anti-tumor immune response.

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

MOTIVATION: The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging. RESULTS: We developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. We give a new perspective of mechanism interpretation, specifically, we define novel model aggregations and we identify unanticipated molecular associations with response to clinically approved therapies. AVAILABILITY AND IMPLEMENTATION: CONNECTOR is freely available under GNU GPL license at https://qbioturin.github.io/connector and https://doi.org/10.17504/protocols.io.8epv56e74g1b/v1.

Single-Cell RNAseq Data QC and Preprocessing.

The first step in single-cell RNAseq data analysis is the evaluation of the overall quality of the cell transcriptome and the preparation of the single-cell transcription data for clustering. In this chapter, we describe one of the possible approaches to perform single-cell data preprocessing for 3' end single-cell RNAseq transcriptomics data.

Single-Cell RNAseq Complexity Reduction.

An important step in single-cell RNAseq data analysis is the preparation of the single cell transcription data for cell sub-population partitioning. In this chapter, we describe how to perform complexity reduction for 3' end single-cell RNAseq transcriptomics data.

Functional-Feature-Based Data Reduction Using Sparsely Connected Autoencoders.

Single-cell RNA sequencing (scRNA-seq) allows for the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents the initial step for the identification of different cell types to investigate the cell subpopulation structure of a biological sample. However, it is possible that the clustering aggregation features do not perfectly match the underlying biology since scRNA-seq data are characterized by high noise. In this chapter, we describe a functional feature-driven data reduction approach, which could provide a better link among cell clusters and their underlying cell biology.

Single-Cell RNAseq Clustering.

Single-cell RNA sequencing (scRNA-seq) allows the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents the initial step for the identification of different cell types to investigate the cell subpopulation organization of a sample. In this chapter, we describe how to approach the clustering of single-cell RNAseq transcriptomics data using various clustering tools, and we provide some information on the limitations affecting the clustering procedure.

Using "Galaxy-rCASC": A Public Galaxy Instance for Single-Cell RNA-Seq Data Analysis.

rCASC is a modular workflow providing an integrated environment for single-cell RNA-seq (scRNA-Seq) data analysis exploiting Docker containers to achieve functional and computational reproducibility. It was initially developed as an R package usable also through a Java GUI. However, the Java frontend cannot be employed when running rCASC on a remote server, a typical setup due to the significant computational resources commonly needed to analyze scRNA-Seq data.To allow the use of rCASC through a graphical user interface on the client side and to harness the many advantages provided by the Galaxy platform, we have made rCASC available as a Galaxy set of tools, also providing a dedicated public instance of Galaxy named "Galaxy-rCASC." To integrate rCASC into Galaxy, all its functions, originally implemented as a set of Docker containers to maximize reproducibility, have been extensively reworked to become independent from the R package functions that launch them in the original implementation. Furthermore, suitable Galaxy wrappers have been developed for most functions of rCASC. We provide a detailed reference document to the use of Galaxy-rCASC with insights and explanations on the platform functionalities, parameters, and output while guiding the reader through the typical rCASC analysis workflow of a scRNA-Seq dataset.

Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering.

BACKGROUND: Spatial transcriptomics (ST) combines stained tissue images with spatially resolved high-throughput RNA sequencing. The spatial transcriptomic analysis includes challenging tasks like clustering, where a partition among data points (spots) is defined by means of a similarity measure. Improving clustering results is a key factor as clustering affects subsequent downstream analysis. State-of-the-art approaches group data by taking into account transcriptional similarity and some by exploiting spatial information as well. However, it is not yet clear how much the spatial information combined with transcriptomics improves the clustering result. RESULTS: We propose a new clustering method, Stardust, that easily exploits the combination of space and transcriptomic information in the clustering procedure through a manual or fully automatic tuning of algorithm parameters. Moreover, a parameter-free version of the method is also provided where the spatial contribution depends dynamically on the expression distances distribution in the space. We evaluated the proposed methods results by analyzing ST data sets available on the 10x Genomics website and comparing clustering performances with state-of-the-art approaches by measuring the spots' stability in the clusters and their biological coherence. Stability is defined by the tendency of each point to remain clustered with the same neighbors when perturbations are applied. CONCLUSIONS: Stardust is an easy-to-use methodology allowing to define how much spatial information should influence clustering on different tissues and achieving more stable results than state-of-the-art approaches.

MET∆14 promotes a ligand-dependent, AKT-driven invasive growth.

MET is an oncogene encoding the tyrosine kinase receptor for hepatocyte growth factor (HGF). Upon ligand binding, MET activates multiple signal transducers, including PI3K/AKT, STAT3, and MAPK. When mutated or amplified, MET becomes a "driver" for the onset and progression of cancer. The most frequent mutations in the MET gene affect the splicing sites of exon 14, leading to the deletion of the receptor's juxtamembrane domain (MET∆14). It is currently believed that, as in gene amplification, MET∆14 kinase is constitutively active. Our analysis of MET in carcinoma cell lines showed that MET∆14 strictly depends on HGF for kinase activation. Compared with wt MET, ∆14 is sensitive to lower HGF concentrations, with more sustained kinase response. Using three different models, we have demonstrated that MET∆14 activation leads to robust phosphorylation of AKT, leading to a distinctive transcriptomic signature. Functional studies revealed that ∆14 activation is predominantly responsible for enhanced protection from apoptosis and cellular migration. Thus, the unique HGF-dependent ∆14 oncogenic activity suggests consideration of HGF in the tumour microenvironment to select patients for clinical trials.

Extracellular Vesicles Derived From Plasma of Patients With Neurodegenerative Disease Have Common Transcriptomic Profiling.

OBJECTIVES: There is a lack of effective biomarkers for neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia. Extracellular vesicle (EV) RNA cargo can have an interesting potential as a non-invasive biomarker for NDs. However, the knowledge about the abundance of EV-mRNAs and their contribution to neurodegeneration is not clear. METHODS: Large and small EVs (LEVs and SEVs) were isolated from plasma of patients and healthy volunteers (control, CTR) by differential centrifugation and filtration, and RNA was extracted. Whole transcriptome was carried out using next generation sequencing (NGS). RESULTS: Coding RNA (i.e., mRNA) but not long non-coding RNAs (lncRNAs) in SEVs and LEVs of patients with ALS could be distinguished from healthy CTRs and from other NDs using the principal component analysis (PCA). Some mRNAs were found in commonly deregulated between SEVs of patients with ALS and frontotemporal dementia (FTD), and they were classified in mRNA processing and splicing pathways. In LEVs, instead, one mRNA and one antisense RNA (i.e., MAP3K7CL and AP003068.3) were found to be in common among ALS, FTD, and PD. No deregulated mRNAs were found in EVs of patients with AD. CONCLUSION: Different RNA regulation occurs in LEVs and SEVs of NDs. mRNAs and lncRNAs are present in plasma-derived EVs of NDs, and there are common and specific transcripts that characterize LEVs and SEVs from the NDs considered in this study.

Circulating Extracellular Vesicles Contain Liver-Derived RNA Species as Indicators of Severe Cholestasis-Induced Early Liver Fibrosis in Mice.

Aims: Biliary diseases represent around 10% of all chronic liver diseases and affect both adults and children. Currently available biochemical tests detect cholestasis but not early liver fibrosis. Circulating extracellular vesicles (EVs) provide a noninvasive, real-time molecular snapshot of the injured organ. We thus aimed at searching for a panel of EV-based biomarkers for cholestasis-induced early liver fibrosis using mouse models. Results: Progressive and detectable histological evidence of collagen deposition and liver fibrosis was observed from day 8 after bile duct ligation (BDL) in mice. Whole transcriptome and small RNA sequencing analyses of circulating EVs revealed differentially enriched RNA species after BDL versus sham controls. Unsupervised hierarchical clustering identified a signature that allowed for discrimination between BDL and controls. In particular, 151 microRNAs (miRNAs) enriched in BDL-derived EVs were identified, of which 66 were conserved in humans. The liver was an important source of circulating EVs in BDL animals as evidenced by the enrichment of several hepatic mRNAs, such as Albumin and Haptoglobin. Interestingly, among experimentally validated miRNAs, miR192-5p, miR194-5p, miR22-3p, and miR29a-3p showed similar enrichment patterns also in EVs derived from 3,5-diethoxycarboncyl-1,4-dihydrocollidine-treated (drug-induced severe cholestasis) but not in mice with mild phenotype or non-cholestatic liver fibrosis. Innovation: A panel of mRNAs and miRNAs contained in circulating EVs, when combined, indicates hepatic damage and fibrosis in mice and represents promising biomarkers for human severe cholestasis-induced liver fibrosis. Conclusion: Analysis of EV-based miRNAs, in combination with hepatic injury RNA markers, can detect early cholestatic liver injury and fibrosis in mice. Antioxid. Redox Signal. 36, 480-504.

Regulation of CD45 phosphatase by oncogenic ALK in anaplastic large cell lymphoma.

Anaplastic Large Cell Lymphoma (ALCL) is a subtype of non-Hodgkin lymphoma frequently driven by the chimeric tyrosine kinase NPM-ALK, generated by the t (2,5)(p23;q35) translocation. While ALK+ ALCL belongs to mature T cell lymphomas, loss of T cell identity is observed in the majority of ALCL secondary to a transcriptional and epigenetic repressive program induced by oncogenic NPM-ALK. While inhibiting the expression of T cell molecules, NPM-ALK activates surrogate TCR signaling by directly inducing pathways downstream the TCR. CD45 is a tyrosine phosphatase that plays a central role in T cell activation by controlling the TCR signaling and regulating the cytokine responses through the JAK/STAT pathway and exists in different isoforms depending on the stage of T-cell maturation, activation and differentiation. ALK+ ALCL cells mainly express the isoform CD45RO in keeping with their mature/memory T cell phenotype. Because of its regulatory effect on the JAK/STAT pathway that is essential for ALK+ ALCL, we investigated whether CD45 expression was affected by oncogenic ALK. We found that most ALK+ ALCL cell lines express the CD45RO isoform with modest CD45RA expression and that NPM-ALK regulated the expression of these CD45 isoforms. Regulation of CD45 expression was dependent on ALK kinase activity as CD45RO expression was increased when NPM-ALK kinase activity was inhibited by treatment with ALK tyrosine kinase inhibitors (TKIs). Silencing ALK expression through shRNA or degradation of ALK by the PROTAC TL13-112 caused upregulation of CD45RO both at mRNA and protein levels with minimal changes on CD45RA, overall indicating that oncogenic ALK downregulates the expression of CD45. CD45 repression was mediated by STAT3 as demonstrated by ChIP-seq data on ALCL cells treated with the ALK-TKI crizotinib or cells treated with a STAT3 degrader. Next, we found that knocking-out CD45 with the CRISPR/Cas9 system resulted in increased resistance to ALK TKI treatment and CD45 was down-regulated in ALCL cells that developed resistance in vitro to ALK TKIs. Overall, these data suggest that CD45 expression is regulated by ALK via STAT3 and acts as a rheostat of ALK oncogenic signaling and resistance to TKI treatment in ALCL.