Biognosys (Switzerland)

IntroductionMiscarriages affect 50-70% of all gestations and 15-20% of clinically recognized pregnancies. Recurrent pregnancy loss (RPL) occurs in 1-5% of clinical pregnancies and has an enormous demographic impact. However, the etiologies and molecular pathways of RPL are scarcely understood, and therefore, reliable diagnostic and preventive methods are not yet available. Here, we aimed to discover novel biomarkers for RPL using next-generation proteomics technology to help develop early and effective diagnostic tools.MethodsFirst-trimester blood samples were collected from women with RPL (n=11) and controls with elective termination of pregnancy (n=11) between 6–13 weeks of gestation. After immunodepleting 14 highly abundant proteins, plasma samples were reduced, alkylated, and trypsin digested. For the separation of peptides, nano-flow reversed-phase chromatography was applied, and then mass spectrometric analysis was performed. Differentially abundant (DA) proteins were identified using strict criteria and analyzed by protein network and Gene Ontology (GO) enrichment analyses, and two biomarker candidates (CGB and PAPPA) were validated by immunoassay. Biomarker predictive properties were demonstrated using Receiver Operating Characteristic (ROC) curves. Assessments were performed for all cases and then for two gestational age groups, before and after the start of placental circulation [“early RPL”: gestational weeks (GW) 6–9, “late RPL”: GW 9–13].ResultsAltogether, 651 proteins were identified and quantified across all samples. When comparing “early control” and “late control” samples, 60 proteins [11 predominantly placenta-expressed (PPE)] were DA. When analyzing all cases, 50 DA proteins were found in RPL (top 3 down: PZP, PSG9, CGB; top 3 up: C4BPA, HBA, HBB), among which 11 PPE proteins were found, all downregulated. Enriched GO terms included ‘placental function’, ‘oxidative processes’, ‘immune function’, and ‘blood coagulation’ related biological processes. When cases were split into early and late RPL groups, 40 DA proteins were identified in early RPL (top 3 down: SHBG, CGB, CGA; top 3 up: C4BPA, SAMP, C4BPB) and 90 in late RPL (top 3 down: PZP, PAPPA, PSG9; top 3 up: THBS1, ECM1, HBB), among which only 15 were shared by both RPL groups. In early RPL, only ‘placental function’ and ‘immune function’ related biological processes were enriched, while in late RPL the top enriched GO terms included ‘placental function’, ‘oxidative processes’, ‘immune function’, ‘blood coagulation’, ‘angiogenesis’, ‘cell migration’, and ‘blood circulation’ related biological processes. Among GO terms, only ‘placental function’ related biological processes were enriched when early- and late RPL DA proteins were analyzed together. Furthermore, the areas under the ROC curves were >0.9 for two protein candidates in all RPL, for five proteins in early RPL, and for ten proteins in late RPL. Among these candidates, CGB and PAPPA were validated by immunoassay which showed a good correlation with MS data (RCGB=0.795 and RPAPPA=0.965).ConclusionWe discovered distinct as well as shared molecular pathways associated with RPL pathogenesis before and after the start of placental circulation and identified novel biomarkers for these pathways which have outstanding discriminative properties. Our results may facilitate a better understanding of the molecular pathways of RPL. However, larger clinical studies are needed to investigate whether the identified biomarkers also have predictive power for RPL before pregnancies fail and to test drugs for the modulation of the identified disease pathways and the prevention of RPL. Our findings highlight the importance of the maternal immune system in maintaining successful pregnancy and suggest that targeting immune pathways may offer novel therapeutic approaches for RPL.

BK polyomavirus (BKPyV) affects 10%-30% of kidney-transplant recipients receiving immunosuppressive therapy, potentially leading to nephropathy, graft dysfunction, graft loss, and increased mortality. Despite the medical need, no targeted therapies exist. This first-in-human trial evaluated the safety, tolerability, pharmacokinetics, and immunogenicity of potravitug, a novel fully human antibody against BKPyV. This partially randomized, single-blinded, and placebo-controlled trial enrolled 40 healthy participants randomized (3:1) to receive either single or multiple ascending doses (SAD/MAD) of potravitug or placebo intravenously. In the SAD phase, 16 participants were enrolled in 4 cohorts (n = 4 each) with escalating doses of 100, 500, 1000, and 2000 mg. In the MAD phase, 24 participants were enrolled in 3 consecutive cohorts (n = 8 each) with escalating doses of 500, 1000, and 2000 mg administered four times at four-week intervals. The primary outcome was incidence, frequency, and severity of treatment-emergent adverse events (TEAEs). Secondary outcomes included pharmacokinetic parameters and incidence of anti-drug antibodies. The exvivo neutralization capacity was an exploratory pharmacodynamic outcome. In SAD cohorts, 17 TEAEs occurred in 7 (58.3%) active and 3 in 2 (50.0%) placebo recipients. In MAD cohorts, 49 TEAEs occurred in 13 (72.2%) active and 21 in 5 (83.3%) placebo recipients. No dose-limiting toxicities or anti-drug antibodies were detected, indicating a favorable safety profile. Dose-proportional increases in Cmax and AUC, with a half-life characteristic of monoclonal antibodies, were observed. Based on pharmacokinetic-pharmacodynamic modeling, a 1000 mg intravenous dose administered four times at four-week intervals is expected to maintain sufficient drug concentrations and receptor occupancy of VP1 (BKPyV major capsid protein) in both the blood and kidney for at least 1 year.

Abstract Tumor-infiltrating B cells and especially B cells organized in tertiary lymphoid structures (TLS) correlate with better prognosis in lung, ovarian and colon cancer patients. TLS are ectopic lymphoid organs which may present B cell follicles of germinal center. B cells in the TLS were found to express typical markers of late-stage maturation, somatic hypermutation and class switch recombination of immunoglobulin genes, indicating a cancer-driven clonal expansion. In some cases, research showed that secreted immunoglobulins of the repertoire were having a direct tumor killing activity. To decipher and then harness the potential of these tumor-trained antibodies, we analyze recombinant cognate repertoires of tumor infiltrating B cells from lung, ovarian and colon cancer surgical resections. We leverage the capabilities of our cutting-edge single-cell microfluidic platform, to extract and clone the comprehensive B cell antibody arsenal from up to a million tumor-derived B cells. The cancer derived antibodies are then expressed as recombinant full-length human IgG maintaining the heavy and light chain pairing of the original B cells. The antibody repertoire obtained as a recombinantly expressed mixture or as individual monoclonals is then screened in a panel of assays designed to identify antibodies with a function of interest. For instance, identification of antibodies showing specific binding to cancer cells. Once identified, the monoclonal antibody is then used to deconvolute novel tumor associated antigens. An initial assessment of the tumor derived antibody repertoire revealed that a typical sample of approximately one cubic centimeter of tumor tissue yielded thousands of antibody-clonotypes. The sequences pattern bore signs of affinity maturation and clonal expansion which may indicate an antigen-driven evolutionary pressure exercised by the tumor and tumor surroundings. Screening the tumor derived antibody repertoire for binding to cancer cell lines, we identified several monoclonal antibodies specifically binding to cancer cells. In vitro, these antibodies show anti-tumor activity with several mechanisms of actions: direct growth inhibition or via effector functions (antibody-dependent cell-mediated cytotoxicity). Some antibodies are strongly internalized and meditate killing when coupled to a toxic payload. The tumor antigens of the antibodies are currently being evaluated as potential therapeutic targets. These promising results may lead us to discover novel tumor pathways and contribute to our further understanding of B cell biology in cancer. Citation Format: Matthieu Delince, Carlo Zimarino, Julia Steiger, Pattraporn Satitsuksanoa, Justina Rutkauskaite, Eveline Keller, Leandra Zehnder, Lorenza Ferretti, Simone Schmitt, Christoph Esslinger. Mining tumor B cell repertoires for the identification of novel antibody target pairs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6036.

Abstract In NSCLC, the identification of circulating predictive biomarkers is critical to improve patient selection. Circulating biomarkers have the advantage of accessibility of samples but challenges arise in detecting disease-relevant biomarkers in plasma, where low-abundance circulating analytes are often obscured by highly abundant proteins. This underlines the need for highly sensitive, reproducible assays to detect subtle changes. Therefore, developing a sensitive, reproducible method for biomarker discovery in plasma could significantly enhance clinical outcomes for patients with NSCLC. To address this need, we developed a novel workflow combining particle enrichment (P2) and quantitative mass spectrometry (DIA-MS). We deployed this method on plasma samples from a multicentric phase II clinical trial (SAKK17/18)1 in patients with NSCLC. Longitudinal plasma samples were collected at baseline (n=33) and at two post-dose time points (C1D8, n=31 and C2D1, n=31). The samples were subjected to the developed P2 workflow and unbiased mass spectrometry analysis, leading to the quantification of 9283 proteins across all 95 samples. With this depth at plasma proteome profiling, we could cover up to 12 orders of magnitude, detecting low-abundance tissue/cell proteins from leakage events as well as proteins from extracellular vesicles2. We conducted weighted gene correlation network analysis (WGCNA) incorporating plasma protein expression and clinical outcome measures. This analysis identified a cluster of key proteins significantly associated with progression-free survival (PFS), including DERL1 and SEPRB, both known to be upregulated in NSCLC, as well as MOSPD1, which has been previously reported to promote epithelial-mesenchymal transition (EMT). To enhance our understanding of the biological context surrounding these plasma proteomic findings, we also incorporated data from two orthogonal methods: 1) the characterization of circulating immune cells from blood samples taken from patients at the same time points, performed using high-dimensional spectral flow cytometry; and 2) the integration of information on cell type markers from published single-cell datasets to delineate potential sources of plasma proteomic signatures. In conclusion, this integrated proteomics approach provides a powerful platform for identifying predictive biomarkers, enabling more precise patient stratification and potentially improving clinical outcomes in NSCLC treatment. 1 Rigutto et al. WCLC 2024 abstract MA09.05 2 Lattmann et al. Cell Mol Life Sci. 2024 Citation Format: Angelica Rigutto, Sandra Schaer, Polina Shichkova, Luca Raess, Arthur Viodé, Christopher Below, Roland Bruderer, Markus Joerger, Jana Musilova, Stefanie Hayoz, Vithersan Somasundaram, Nicolas Nuñez, Nadine Fournier, Joao Lourenço, Raphael Gottardo, Burkhard Becher, Alfredo Addeo, Anurag Gupta, Yuehan Feng, Alessandra Curioni-Fontecedro. Comprehensive plasma profiling in NSCLC patients undergoing IO- and chemotherapy identifies potential proteomic signatures for progression-free survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3306.

Abstract Background: ISB 2001 is the first trispecific antibody that simultaneously targets BCMA and CD38 on MM cells, and CD3 to engage T-cells, forming tumor/immune cell synapses (TICS) that cause tumor cytotoxicity. Since ISB 2001 lacks cross-reactivity to common preclinical toxicology species including monkeys, no preclinical toxicology studies were conducted to inform the FIH dose calculation. The conventional minimal anticipated biological effect level (MABEL) approach for FIH dose derivation for T-cell engagers (TCE) often results in exposing patients to non-therapeutic doses. Instead, we developed a QSP model to predict an optimal FIH dose and efficacious dose range. This informed the design of the ongoing phase 1 dose escalation study of ISB 2001 in RRMM patients (NCT05862012), starting at 5 µg/kg subcutaneously with the initial three single-patient cohorts followed by standard 3+3 cohorts beginning at 150 µg/kg. Method: A QSP model utilizing binding affinities, target expressions, cell counts, and preclinical pharmacokinetic (PK) data was developed to characterize TICS profiles in the tumor compartment. Normalized TICS formation was linked to tumor cytotoxicity, and the model was calibrated with ISB 2001 in vivo efficacy data to enable efficacy predictions. This QSP model was benchmarked with teclistamab’s clinical data to derive the minimal pharmacologically active dose (MPAD) of ISB 2001[1]. The MPAD was further adjusted using in vitro cytokine secretion data to establish the FIH dose, which was preceded by fractionated step-up doses to mitigate potential cytokine release syndrome concerns. Serum concentration of ISB 2001 across doses up to 1200 µg/kg were quantified using a validated electrochemiluminescence assay and compared with the model predictions. Results: No CRS was observed in the FIH cohort, and only one grade 1 case was reported at doses up to 15 µg/kg in third cohort, supporting the QSP model-based FIH dose selection while acknowledging the limited sample size. As predicted, objective tumor responses were observed at dose levels as low as 50 µg/kg, just 10-fold higher than the FIH dose. Measured ISB 2001 serum concentration time profiles across multiple dose levels up to 1200 µg/kg (n=20) aligned well with model simulations. Conclusion: Despite the absence of monkey PK and toxicology data, this QSP-guided approach successfully predicted an optimal FIH dose, clinical PK, safety, and efficacy, while minimizing patient exposure to non-therapeutic doses. With this method, TCEs can be optimized solely for activity against human tumors without requiring cross-reactivity to animal species. Overall, the QSP based FIH calculation approach offers an effective pathway for designing phase 1 studies for future TCEs.

Abstract Molecular profiling of formalin-fixed paraffin-embedded (FFPE) tumors in clinical research is performed with low-plex immunohistochemistry or genome-wide transcriptomics. The application of unbiased, highly multiplexed proteomics to FFPE is limited by sample input requirements, assay throughput and complex bioinformatics. Here we report a proteomic method amenable to low-input FFPE profiling which complements transcriptomics. We applied Biognosys’ mass-spectrometry platform (TrueDiscovery, DIA-MS) to samples encountered in routine histopathology laboratories (e.g. B-cell malignancies [n = 35], and breast, pancreatic and colorectal tumors [n=8]). FFPE samples were deparafinzed, de-crosslinked followed by trypsin digestion, and resulted peptides were analyzed by directDIA. Impact of tissue staining by Hematoxylin and Eosin (H&E) and acid decalcification was also assessed. We compared a deep-proteome workflow on a Thermo Scientific Orbitrap Exploris 480 to a novel high throughput workflow on a Bruker timsTOF HT. The deep-proteome workflow with single-slide FFPE tissues (median area 35mm2) generated comprehensive proteome coverage: ∼12,000 proteins detected overall and ∼7,000 detected in the majority of samples. The high throughput Bruker workflow delivered similar data with 80% less input in 20% of the time. Proteomes from H&E stained, cover-slipped slides were nearly identical to adjacent unstained tissue. Interestingly, proteomics profiling was successful in acid decalcified leukemia bone marrow biopsies whereas RNA was not recoverable. To assess the detection of key tissue biomarkers for therapeutic decision-making, we compiled a list of FDA approved antibody based therapeutic targets and found 20 of 21 were detectable in our samples (e.g. PDL1, PD1, LAG3, CD19, CD20 and CD38). Similarly, >80% of 55 immuno-oncology targets undergoing clinical development were detected. A key effector function of antibody therapeutics is complement-dependent cytotoxicity. The presence of complement components was confirmed by proteomics, however, some were undetectable by transcriptomics. Diffuse Large B-cell Lymphoma samples in this study were molecularly subtyped for a key prognostic, Cell of Origin (COO), using a CLIA validated RNA assay (Lymph2Cx). Well studied proteins (e.g. MUM1 and CD10) showed expected distribution based on patient COO, demonstrating proteomics can recapitulate established subtyping methods. We demonstrate that proteomics profiling can be conducted on single FFPE slides even with pre-processed tissue. This high-throughput workflow enables real-time analysis of Phase I trials or large tissue banks. Furthermore, proteome profiling provides an opportunity to consolidate testing for multiple therapeutic targets instead of serial IHC assays, maximizing the use of precious tissue biopsies. Citation Format: Matthew Loya, Tine Casneuf, Helene Bon, Manling Ma-Edmonds, Angelo Harris, Daniel Martin, Anantharaman Muthuswamy, Dominique Kamber, Martin Mehnert, Amaury Lachaud, Yuehan Feng, Mark Fereshteh, Omar Jabado. Single-slide FFPE proteomic profiling enables therapeutic target quantification and molecular subtyping in non-Hodgkin’s lymphoma and bone marrow tumor biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2990.

Senescence emerged as significant mechanism of aging and age-related diseases, offering an attractive target for clinical interventions. Senescent cells release a senescence-associated secretory phenotype (SASP), including exosomes that may act as signal transducers between distal tissues, propagating secondary or bystander senescence and signaling throughout the body. However, the composition of exosome SASP remains underexplored, presenting an opportunity for novel unbiased discovery. We present a detailed proteomic and lipidomic analysis of exosome SASP using mass spectrometry from human plasma from young and older individuals and from tissue culture of senescent primary human lung fibroblasts. We identified ∼1,300 exosome proteins released by senescent cells induced by three different senescence inducers. In parallel, a human plasma cohort from young (20-26 years) and old (65-74 years) individuals revealed over 1,350 exosome proteins and 171 plasma exosome proteins were regulated when comparing old vs young individuals. Of the age-regulated plasma exosome proteins, we observed 52 exosome SASP factors that were also regulated in exosomes from the senescent fibroblasts, including serine protease inhibitors (SERPINs), Prothrombin, Coagulation factor V, Plasminogen, and Reelin. 247 lipids were identified in exosome samples. Following senescence induction, identified phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins increased significantly indicating cellular membrane changes. Interestingly, significantly changed proteins were related to extracellular matrix remodeling and inflammation, both potentially detrimental pathways that can damage surrounding tissues and even induce secondary senescence. Our findings reveal mechanistic insights and potential senescence biomarkers, enabling a better approach to surveilling the senescence burden in the aging population and offering therapeutic targets for interventions.

Abstract Introduction: Colorectal cancer (CRC) is one of the most common cancers worldwide, and early detection is critical for successful treatment and improved survival rates. However, precancerous and early-stage CRC present significant diagnostic challenges due to the small size of lesions and the very low expression of tumor-specific biomarkers in the bloodstream. Current genomics-based diagnostic methods struggle to detect these lesions, making it imperative to develop more sensitive and specific approaches. Circulating extracellular vesicles (EVs) are emerging as a promising solution for early-stage CRC detection, since EVs are produced by tumor cells as well as the tumor microenviroment and host immune cells. Thus, EVs may offer the means to detect and monitor small early-stage tumors through both direct detection of tumor- associated biomarkers as well through tumor specific host response and tumor microenvironment biomarkers. Methods: To identify novel early-stage CRC specific biomarkers, we performed proteomics analysis on EVs purified from patient plasma using size exclusion chromatography and a proprietary buffer system that enhances EV and corona protein recovery. TrueDiscovery™ Data-independent acquisition (DIA) mass spectrometry (MS) analysis was conducted on 24 pre- cancer/stage 0 and 25 stage 1 CRC patients and 75 normal patient plasma samples. An in-house developed machine learning pipeline was used to identify differentially expressed proteins and model candidate multiplexes to identify those with extremely high diagnostic accuracy (> 0.99). Results: An average of ∼2,500 proteins were identified per sample and included in bioinformatics analysis. Comparative analysis between control patient EVs and either pre- cancerous/Stage 0, or Stage 1 colon cancer EVs using an in-house Machine Learning pipeline identified 336 and 493 differentially expressed proteins for each group (FDR adjusted p-value < 0.001). Of these, the best 17 pre/stage 0 proteins and 53 stage 1 proteins were trained and tested using Support Vector Machine to assess all potential 3-plexes in order to identify those with mean diagnostic accuracy > 99%. This yielded 5 3-plexes in precancer/stage 0 and 34 3-plexes in stage 1 with near perfect diagnostic accuracy. These plexes are currently being assessed in single analyte and multiplex immunoassays with the goal of translating candidate 3-plexes to the clinical. Conclusions: Key biomarkers from CRC patient EVs indicate the potential to detect and diagnose early-stage and low tumor burden cancers using our methods. Interestingly, the most accurate 3-plexes consist of proteins from immune, inflammatory and metabolic processes, suggesting that for the detection of early stage cancer it may be critical to include both tumor and host specific biomarkers. Citation Format: Poorva Mudgal, Cheryl Bandoski, Zachary Opheim, Martin Mehnert, Valesca Anschau, Issa Isaac, Alan Ezrin, Todd Hembrough. Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR013.

SV-BR-1-GM, derived from a patient with grade 2 (moderately differentiated) breast cancer, is a GM-CSF-secreting breast cancer cell line with properties of antigen-presenting cells. SV-BR-1-GM and next-generation versions are covered by several pending and granted patents. We report findings from an open-label phase I, single-arm pilot study with irradiated SV-BR-1-GM cells in 3 breast and 1 ovarian cancer subjects. Inoculations were preceded by lowdose intravenous cyclophosphamide and followed by interferon-alpha2b injections into the SVBR- 1-GM inoculation sites. We assessed both cellular and humoral immune responses, and measured expression levels of SV-BR-1-GM HLA alleles. Treatment was generally safe and well tolerated. Immune responses were elicited universally. Overall survival was more than 33 months for three of the four patients. As previously reported, one patient had prompt regression of metastases in lung, breast, and soft tissue. Following cessation of treatment, the patient relapsed widely, including in the brain. Upon retreatment, rapid tumor response was again seen, including complete regression of brain metastases. Consistent with a role of Class II HLA in contributing to SV-BR-1-GM's mechanism of action, this patient allele-matched SV-BR-1-GM at the HLA-DRB1 and HLA-DRB3 loci. We are in the process of developing next-generation SV-BR-1-GM, expressing patient-specific HLAs. Patent applications were filed in various jurisdictions. Thus far, one is granted, in Japan. A whole-cell immunotherapy regimen with SV-BR-1-GM cells induced regression of metastatic breast cancer. We develop intellectual property based on SV-BR-1-GM's predicted mechanism of action to develop additional whole-cell immunotherapies for cancer patients.

Abstract Introduction: Multi-omics-based strategies in precision medicine, including genomic, transcriptomic and proteomic data, have contributed to the molecular-level characterization of cancers and the identification of novel driver genes, as well as a better comprehension of resistance mechanisms. Patient-derived tumor models, including patient-derived xenograft (PDX) and in vitro 3D organoid counterparts (PDXO), are widely recognized as predictive preclinical cancer models closely recapitulating both tumor complexity and patient response and enabling the study of tumor identity for personalized medicine. Taking advantage of Crown Bioscience large PDX collection, with genomic and phenotypic annotation and pharmacological validation, a series of PDXO models have been established and characterized to be used as scalable and high throughput compatible drug screening platforms. Methods: Drug response in matched PDX and PDXO models were investigated on the functional and systems level through deep whole- and phospho-proteomic analysis. For this purpose, analysis and comparisons were made across dose and time series, the effect of several targeted therapies on protein expression and phosphorylation in both PDX and PDXO tumor models. More specifically, a KRAS inhibitor (AMG510), a BCR-ABL TKI (ponatinib) and an EGFR TKI (afatinib) were tested respectively in a lung NSCLC model carrying KRAS G12C mutation, a colorectal model with RET fusion and a lung NSCLC model with EGFR exon 19 deletion. Results: Based on previous data, a specific relationship between area under the curve (AUC) value of organoid drug dose response and in vivo tumor growth has been observed, irrespective of the drug treatment. To interrogate the pathways involved, both PDX and PDXO models were subjected to deep proteome and phospho-proteome profiling using state-of-the-art mass spectrometry-based workflows. An extensive dataset was generated where 16,797 proteins and 12,578 proteins were robustly quantified in PDX and PDXO models respectively. From the same samples, 35,403 phospho-sites were quantified across all PDX samples while 40,754 phospho-sites were quantified across all PDXO models. These data enabled the validation of known pathways (such as RAF/MEK/ERK, PI3K/AKT) and pinpoint new ones modulated through three small molecule inhibitors each targeting a defined genetic background. Conclusion: The predictivity of organoid cultures was demonstrated to model in vivo drug responses and also to serve as a powerful platform to investigate target identification, mechanism of action and resistance mechanism via functional proteome and phospho-proteome analysis. Citation Format: Martin Mehnert, Xiaoxi Xu, Tobias Treiber, Limei Shang, Leilei Chen, Jessie Wang, Marco Tognetti, Christopher Below, Roland Bruderer, Jakob Vowinckel, Binchen Mao, Wubin Qian, Sheng Guo, Ludovic Bourré, Yuehan Feng. Global mapping of pathway modules and phosphorylation networks in PDX and corresponding organoid (PDXO) models treated with targeted therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 185.