Biology subjects

Tankel, J.

Publications and source records attributed to Tankel, J..

3 recordsLinked to original sources

bioRxiv2025

Optimized large-scale longitudinal biorepository of gastroesophageal adenocarcinoma patient-derived organoids: High-fidelity models for personalized treatment to overcome resistance.

A major limitation in studying gastroesophageal adenocarcinoma (GEA) has been the lack of reliable models that represent the diseases complexity. We present lessons learned from a comprehensive large-scale biobanking effort combining traditional sample collection with several in vitro models including 3-dimensional patient-derived organoids (PDOs), 2-dimensional cancer-associated fibroblasts (CAFs), tumor-infiltrating lymphocytes (TILs) and/or in vivo xenografts. This initiative started in 2018, integrating multiple advanced ex-vivo models such as PDOs, patient-derived xenografts (PDXs) and organoids (PDXOs). This unique resource now includes tumor avatars from over 380 consented patients, making it the largest living GEA biobank in the world. We achieved > 90% success rate in creating per-patient models, including 227 tumor-derived and 203 neighboring normal PDOs. These organoids accurately mirror key features of the original tumors, such as their histology (e.g. microsatellite instability), mutations, and drug response, across treatment points. Notably, PDOs can predict individual patient responses to chemotherapy within five weeks, underscoring their clinical relevance. Furthermore, high-throughput drug screening on PDO subsets generates personalized chemosensitivity profiles for 22 drugs. Through a process of continued refinement of culture techniques and tumor sampling approach, our large-scale comprehensive collection of GEA avatars represents a unique and valuable preclinical experimental resource for precision oncology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/663874v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@f8a032org.highwire.dtl.DTLVardef@dd6fa3org.highwire.dtl.DTLVardef@1cc558corg.highwire.dtl.DTLVardef@492a5_HPS_FORMAT_FIGEXP M_FIG Schematic depiction of GEA live-banking workflow C_FIG

cancer biology↗

bioRxiv2023

Tumour Extracellular Vesicles Induce Neutrophil Extracellular Traps To Promote Lymph Node Metastasis

Lymph nodes (LNs) are frequently the first sites of metastasis. Currently, the only prognostic LN assessment is determining metastasis status. However, there is evidence suggesting that LN metastasis is facilitated by a pre-metastatic niche induced by tumour derived extracellular vehicles (EVs). Therefore, it is important to detect and modify the LN environmental changes. We have previously reported that neutrophil extracellular traps (NETs) can sequester and promote distant metastasis. Here, we first confirmed that LN NETs are associated with reduced patient survival. Next, we demonstrated that NETs deposition precedes LN metastasis and NETs inhibition abolishes LN metastases in animal mode. Furthermore, we discovered that EVs are essential to the formation of LN NETs. Lymphatic endothelial cells secrete CXCL8/2 in response to EVs inducing NETs formation and the promotion of LN metastasis. Our findings are the first to reveal the role of EV induced NETs in LN metastasis and provide potential immunotherapeutic vulnerabilities. Graphic AbstractIllustrative demonstration of the LNs premetastatic niche formation induced by EVs and NETs. Primary tumour constantly secretes EVs, which were actively uptaken by LECs. LECs subsequently secretes CXCL8 or CXCL2 upon EV reception. CXCL8 and CXCL2 are both neutrophil chemoattractants and potent NETs inducers. The following neutrophil recruitment and NETs formation lead to increased LN metastasis burden. O_FIG O_LINKSMALLFIG WIDTH=173 HEIGHT=200 SRC="FIGDIR/small/532413v2_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@c0c371org.highwire.dtl.DTLVardef@15f6a92org.highwire.dtl.DTLVardef@14dbeedorg.highwire.dtl.DTLVardef@131d3eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Data-Independent Acquisition and Quantification of Extracellular Matrix from Human Lung in Chronic Inflammation-Associated Carcinomas

Early events associated with chronic inflammation and cancer involve significant remodeling of the extracellular matrix (ECM), which greatly affects its composition and functional properties. Using lung squamous cell carcinoma (LSCC), a chronic inflammation-associated cancer (CIAC), we optimized a robust proteomic pipeline to discover potential biomarker signatures and protein changes specifically in the stroma. We combined ECM enrichment from fresh human tissues, data-independent acquisition strategies, and stringent statistical processing to analyze Tumor and matched adjacent histologically normal ( Matched Normal) tissues from patients with LSCC. Overall, 1,802 protein groups were quantified with at least two unique peptides, and 56% of those proteins were annotated as extracellular. Confirming dramatic ECM remodeling during CIAC progression, 529 proteins were significantly altered in the Tumor compared to Matched Normal tissues. The signature was typified by a coordinated loss of basement membrane proteins and small leucine-rich proteins. The dramatic increase in the stromal levels of SERPINH1/heat shock protein 47, that was discovered using our ECM proteomic pipeline, was validated by immunohistochemistry (IHC) of Tumor and Matched Normal tissues, obtained from an independent cohort of LSCC patients. This integrated workflow provided novel insights into ECM remodeling during CIAC progression, and identified potential biomarker signatures and future therapeutic targets. Statement of significance of the studyThe extracellular matrix (ECM) is a complex scaffolding network composed of glycoproteins, proteoglycans and collagens, which binds soluble factors and, most importantly, significantly impacts cell fate and function. Alterations of ECM homeostasis create a microenvironment promoting tumor formation and progression, therefore deciphering molecular details of aberrant ECM remodeling is essential. Here, we present a multi-laboratory and refined proteomic workflow, featuring i) the prospective collection of tumor and matched histologically normal tissues from patients with lung squamous cell carcinoma, ii) the enrichment for ECM proteins, and iii) subsequent label-free data-independent acquisition (DIA)-based quantification. DIA is a powerful strategy to comprehensively profile and quantify all detectable precursor ions contained in the biological samples, with high quantification accuracy and reproducibility. When combined with very stringent statistical cutoffs, this unbiased strategy succeeded in capturing robust and highly confident proteins changes associated with cancer, despite biological variability between individuals. This label-free quantification workflow provided the flexibility required for ongoing prospective studies. Discussions with clinicians, surgeons, pathologists, and cancer biologists represent an opportunity to interrogate the DIA digitalized maps of the samples for newly formulated questions and hypotheses, thus gaining insights into the continuum of the disease and opening the path to novel ECM-targeted therapies.

cancer biology↗