Patient-Derived Cancer Models Research Articles

Creation and Validation of Patient-Derived Cancer Model Using Peritoneal and Pleural Effusion in Patients with Advanced Ovarian Cancer: An Early Experience.

Background: The application of personalized cancer treatment based on genetic information and surgical samples has begun in the field of cancer medicine. However, a biopsy may be painful for patients with advanced diseases that do not qualify for surgical resection. Patient-derived xenografts (PDXs) are cancer models in which patient samples are transplanted into immunodeficient mice. PDXs are expected to be useful for personalized medicine. The aim of this study was to establish a PDX from body fluid (PDX-BF), such as peritoneal and pleural effusion samples, to provide personalized medicine without surgery. Methods: PDXs-BF were created from patients with ovarian cancer who had positive cytology findings based on peritoneal and pleural effusion samples. PDXs were also prepared from each primary tumor. The pathological findings based on immunohistochemistry were compared between the primary tumor, PDX, and PDX-BF. Further, genomic profiles and gene expression were evaluated using DNA and RNA sequencing to compare primary tumors, PDXs, and PDX-BF. Results: Among the 15 patients, PDX-BF was established for 8 patients (5 high-grade serous carcinoma, 1 carcinosarcoma, 1 low-grade serous carcinoma, and 1 clear cell carcinoma); the success rate was 53%. Histologically, PDXs-BF have features similar to those of primary tumors and PDXs. In particular, PDXs-BF had similar gene mutations and expression patterns to primary tumors and PDXs. Conclusions: PDX-BF reproduced primary tumors in terms of pathological features and genomic profiles, including gene mutation and expression. Thus, PDX-BF may be a potential alternative to surgical resection for patients with advanced disease.

Focal adhesion kinase-YAP signaling axis drives drug-tolerant persister cells and residual disease in lung cancer

Targeted therapy is effective in many tumor types including lung cancer, the leading cause of cancer mortality. Paradigm defining examples are targeted therapies directed against non-small cell lung cancer (NSCLC) subtypes with oncogenic alterations in EGFR, ALK and KRAS. The success of targeted therapy is limited by drug-tolerant persister cells (DTPs) which withstand and adapt to treatment and comprise the residual disease state that is typical during treatment with clinical targeted therapies. Here, we integrate studies in patient-derived and immunocompetent lung cancer models and clinical specimens obtained from patients on targeted therapy to uncover a focal adhesion kinase (FAK)-YAP signaling axis that promotes residual disease during oncogenic EGFR-, ALK-, and KRAS-targeted therapies. FAK-YAP signaling inhibition combined with the primary targeted therapy suppressed residual drug-tolerant cells and enhanced tumor responses. This study unveils a FAK-YAP signaling module that promotes residual disease in lung cancer and mechanism-based therapeutic strategies to improve tumor response.

Patient-derived castration-resistant prostate cancer model revealed CTBP2 upregulation mediated by OCT1 and androgen receptor

BackgroundProstate cancer is dependent on androgen receptor (AR) signaling, and androgen deprivation therapy (ADT) has proven effective in targeting prostate cancer. However, castration-resistant prostate cancer (CRPC) eventually emerges. AR signaling inhibitors (ARSI) have been also used, but resistance to these agents develops due to genetic AR alterations and epigenetic dysregulation.MethodsIn this study, we investigated the role of OCT1, a member of the OCT family, in an AR-positive CRPC patient-derived xenograft established from a patient with resistance to ARSI and chemotherapy. We conducted a genome-wide analysis chromatin immunoprecipitation followed by sequencing and bioinformatic analyses using public database.ResultsGenome-wide analysis of OCT1 target genes in PDX 201.1 A revealed distinct OCT1 binding sites compared to treatment-naïve cells. Bioinformatic analyses revealed that OCT1-regulated genes were associated with cell migration and immune system regulation. In particular, C-terminal Binding Protein 2 (CTBP2), an OCT1/AR target gene, was correlated with poor prognosis and immunosuppressive effects in the tumor microenvironment. Metascape revealed that CTBP2 knockdown affects genes related to the immune response to bacteria. Furthermore, TISIDB analysis suggested the relationship between CTBP2 expression and immune cell infiltration in prostate cancer, suggesting that it may contribute to immune evasion in CRPC.ConclusionsOur findings shed light on the genome-wide network of OCT1 and AR in AR-positive CRPC and highlight the potential role of CTBP2 in immune response and tumor progression. Targeting CTBP2 may represent a promising therapeutic approach for aggressive AR-positive CRPC. Further validation will be required to explore novel therapeutic strategies for CRPC management.

A Path to Persistence after EGFR Inhibition.

Residual cancer cells persist even after targeted therapies, serving as a reservoir for the subsequent acquisition of genetic alterations that lead to acquired drug resistance and tumor relapse. These initial drug-tolerant persisters (DTP) are phenotypically heterogenous with transient phenotypes attributed to epigenetic, metabolic, and cell-cycle changes. DTPs are responsible for the inevitable relapse seen in EGFR-mutant non-small cell lung cancer (NSCLC) despite high initial response to tyrosine kinase inhibitor (TKI) treatment. While past in vitro studies identified diverse drivers of drug-tolerant persistence to EGFR TKIs in NSCLC, the resultant phenotypic plasticity is not well understood and in vivo models of persistence are lacking. In this issue of Cancer Research, Hu and colleagues used patient-derived xenograft models of EGFR-mutant lung cancer treated with the third-generation TKI osimertinib to investigate mechanisms of persistence at the time of maximal response. Using bulk and single-cell RNA sequencing, the authors identified a DTP transcriptional cluster mediated by the key neuroendocrine lineage transcription factor ASCL1, which triggers an epithelial-to-mesenchymal transition transcriptional program. ASCL1 overexpression increased osimertinib tolerance in vitro as well, apparently independent of its role in neuroendocrine differentiation. Interestingly, the ability of ASCL1 to induce persistence was context dependent as this occurred only in epigenetically permissive cells. Overall, these findings contribute to our understanding of DTP heterogeneity seen after osimertinib treatment and provide insights into potential therapeutic targets. See related article by Hu et al., p. 1303.

Abstract LB053: A novel BRAF-specific allosteric inhibitor that effectively targets acquired RAFi-resistant BRAF(V600E) cancers and RAS-mutated cancers in vitro and in vivo

Abstract Targeting hyperactive RAS-RAF-MEK-ERK signaling for treating cancers has achieved a promising outcomes, and a number of RAS/RAF inhibitors have been applied to clinical cancer treatment. However, these inhibitors have only a short-term efficacy and their effectiveness is abrogated by acquired drug resistance in less than one year. For those resistant/refractory RAS/RAF-mutated cancers, there’s no effective therapeutics available in clinic. In this study, we developed a novel BRAF-specific inhibitor that docks on an allosteric site on BRAF kinase domain. This inhibitor effectively killed both primary and drug-resistant cancer cell lines with RAS mutation or BRAF(V600E) mutation in vitro and inhibited the growth of xenografted cancers derived from these cell lines in vivo without apparent toxicity. Mechanistically, we found that although this inhibitor blocked the catalytic activity of BRAF in vitro kinase assay, it triggered a super high ERK signaling through improving BRAF/CRAF heterodimerization and hence induced cellular apoptosis of cancer cells with RAS mutation or BRAF(V600E) mutation. Surprisingly, there’s no drug resistance occurring when treating cancer cells with RAS mutation or BRAF(V600E) mutation at a low concentration. To further evaluate the efficacy of this BRAF against RAS/RAF-mutated cancers in vivo, we constructed a series of pancreatic patient-derived xenograft cancer models with Kras G12D or G12V mutations, and found that our BRAF inhibitor exhibited a comparable or much better efficacy than Kras G12D-specific inhibitor on theses PDX models. Altogether, our data indicated that our BRAF-specific allosteric inhibitor may serve as a good therapeutic drug for treating BRAF(V600E)/RAS- cancers, particularly those resistant/refractory cancers, though it still need further evaluations via clinical trials. Citation Format: Jiancheng Hu. A novel BRAF-specific allosteric inhibitor that effectively targets acquired RAFi-resistant BRAF(V600E) cancers and RAS-mutated cancers in vitro and in vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB053.

A Stem-like Patient-Derived Ovarian Cancer Model of Platinum Resistance Reveals Dissociation of Stemness and Resistance.

To understand chemoresistance in the context of cancer stem cells (CSC), a cisplatin resistance model was developed using a high-grade serous ovarian cancer patient-derived, cisplatin-sensitive sample, PDX4. As a molecular subtype-specific stem-like cell line, PDX4 was selected for its representative features, including its histopathological and BRCA2 mutation status, and exposed to cisplatin in vitro. In the cisplatin-resistant cells, transcriptomics were carried out, and cell morphology, protein expression, and functional status were characterized. Additionally, potential signaling pathways involved in cisplatin resistance were explored. Our findings reveal the presence of distinct molecular signatures and phenotypic changes in cisplatin-resistant PDX4 compared to their sensitive counterparts. Surprisingly, we observed that chemoresistance was not inherently linked with increased stemness. In fact, although resistant cells expressed a combination of EMT and stemness markers, functional assays revealed that they were less proliferative, migratory, and clonogenic-features indicative of an underlying complex mechanism for cell survival. Furthermore, DNA damage tolerance and cellular stress management pathways were enriched. This novel, syngeneic model provides a valuable platform for investigating the underlying mechanisms of cisplatin resistance in a clinically relevant context, contributing to the development of targeted therapies tailored to combat resistance in stem-like ovarian cancer.

Abstract 6910: CancerModels.org: An open global cancer research platform for patient-derived cancer models

Abstract CancerModels.Org (www.cancermodels.org) is a research platform that standardises, harmonizes and integrates the complex and diverse data associated with Patient-Derived Cancer Models (PDCMs) for the cancer community. The portal publishes over 7500 models - covering patient-derived xenografts (PDX), organoids and cell lines - across 13 cancer types, including rare pediatric PDX models and models from minority ethnic backgrounds. A total of over 90 million data points are made available across a variety of data types, such as clinical metadata, molecular data and treatment-based information, which makes CancerModels.Org the largest free-to-consumer and open-access resource of this kind. Over the course of the last twelve months, the platform has been enhanced with new functionality and an updated user interface to cater for a more varied set of use cases. Users can now search for models of interest by exploring molecular data summaries for models of specific cancer types, as well as by using the intuitive search and faceted filtering options of the web interface. The data is also accessible via REST API, hence enabling offline analyses. The underpinning data model was augmented with additional dimensions and covers gene expression, gene mutation, copy number alteration, biomarkers, patient treatment and drug dosing studies. For an improved prioritization of PDCMs we performed knowledge enrichment by linking to external resources, such as publication platforms, cancer-specific annotation tools (COSMIC, CIViC, OncoMX, OpenCRAVAT, ClinGen), and raw data archives (ENA, EGA, GEO, dbGAP). More recently, we added immune-related features of tumors (HLA, MSI, TMB) and image data (also accessible via EMBL-EBI’s BioImage archive). Finally, to streamline model and data submission, we made available a Metadata dictionary and a Metadata validation service. Future work will focus on the curation of rare models with rich accessible metadata and data, new data visualizations, integration of new data types and resources, as well as devising a model quality rating using user feedback. These developments will maximize utility and improve reusability of models and data, and reduce barriers to model and data sharing. CancerModels.Org is deeply integrated into the general patient-derived cancer models landscape, underpinning or contributing to the data and/or software infrastructure of some of the long-running consortia, such as EUROPDX and PDXNet. The resource is freely available under an Apache 2.0 license (https://github.com/PDCMFinder). Citation Format: Zinaida Perova, Mauricio Martinez, Tushar Mandloi, Marcelo Rios Almanza, Steven Neuhauser, Dale Degley, Debra Krupke, Carol Bult, Helen Parkinson. CancerModels.org: An open global cancer research platform for patient-derived cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6910.

Abstract 6429: Critical role of elevated TMEM176B gene expression in humanized patient-derived xenografts mouse models of triple negative breast cancer

Abstract Objective: In the cancer research, a highly promising in vivo platform for personalized treatment involves the adoption of an advanced approach—specifically, the grafting of patient-derived xenografts (PDX) onto humanized mouse models. These models capture distinctive aspects of interaction with the human immune system and the tumor microenvironment (TME). In this study, we have engineered humanized triple-negative breast cancer (TNBC) PDX models to observe alterations in differentially expressed genes, thereby enhancing our understanding of the intricacies of personalized treatment in this context. Method: We utilized two TNBC PDX models established for the humanized models, where CD34+ hematopoietic stem cells were transplanted into immunodeficient mice. RNA sequencing was performed to identify altered gene expression in humanized PDX models compared to NSG PDXs. Additionally, we generated stable cell lines overexpressing TMEM176B in MDAMB231 and Hs578T cells, and we knocked down TMEM176B in 4T1 cells using recombinant techniques Results: In the humanized model, the growth of PDX tumors did not show a significantly faster or markedly different rate compared to previous studies. However, upon conducting RNA sequencing in the PDX model, the expression of the TMEM176B gene was consistently downregulated. Consequently, we transfected and observed that the increased expression of TMEM176B in MDAMB231 and Hs578T cell lines resulted in enhanced cell proliferation in vitro. Transplanting MDAMB231 cells overexpressing TMEM176B into athymic nude mice resulted in accelerated tumor growth. The study further investigates the expression of TMEM176B in an immune-competent environment by knocking down the gene in 4T1 cells or transplanting the control group into a balb/c mouse model. Tumors with TMEM176B knockdown exhibited inhibited growth, increased CD3+ T cell infiltration, and significant inhibition when treated with anti-PD-L1 compared to the control group. Conclusion: This research demonstrates the utility of PDX models, particularly humanized PDX models, in studying the complexities of cancer biology and the tumor microenvironment. The findings regarding TMEM176B and its role in tumorigenesis and immune responses in triple-negative breast cancer provide valuable insights for further research and potential therapeutic interventions. Citation Format: Yujeong Her, Jihui Yun, Woohang Heo, Jong-Il Kim, Han-Byoel Lee, Wonshik Han, Hyeong-Gon Moon. Critical role of elevated TMEM176B gene expression in humanized patient-derived xenografts mouse models of triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6429.

Abstract 5911: In vivo efficacy of a novel peptide-conjugated drug in patient-derived xenograft models of breast cancer

Abstract Introduction: Antibody and peptide-conjugated drugs are rapidly entering the clinic for the treatment of patients with early and advanced breast cancer. These drugs are designed to achieve more targeted delivery of cytotoxic agents to tumor cells with robust clinical activity. ARB-1-6, a sortilin (SORT1) targeted peptide conjugated to the cytotoxic agent MMAE, has demonstrated pre-clinical activity and tolerability in cell line xenografts of breast cancer. To further characterize its spectrum of antitumor activity and biomarker correlates we evaluated ARB-1-6 in a collection of clinically and genomically annotated breast cancer patient-derived xenografts (PDX). Methods: Breast cancer PDX models were generated and propagated under IRB approved protocols [14-8358]. ARB-1-6 was dosed in tumor-bearing SCID mice by tail vein injection at 3 mg/kg weekly x 4 doses. Tumor volume was measured twice weekly until day 35 or until models reached humane endpoints, after which tumors were collected. Animals were weighed regularly and assessed for treatment-related toxicity. Results: 7 models (5 TN and 2 HR) have completed efficacy assessment to date. 3/7 models were derived from treatment naïve patients while 4/7 were derived from pre-treated patients (Table 1). Complete response (mRECIST) was seen in 5/7 (71.4%) models with stable disease occurring in 2/7 (28.6%). ARB-1-6 was well tolerated with no weight loss observed. Complete tumor regression was seen in a PDX derived from a patient with clinical resistance to a TROP2 antibody drug conjugate (ADC). Antitumor activity was observed in models with low SORT1 RNA expression; SORT1 IHC and other correlatives studies are underway. Conclusion: ARB-1-6 demonstrates substantial preclinical activity in PDX models at doses that are well tolerated in mice. Treatment of additional models is ongoing. Full results and correlative analyses including relationships between antitumor activity and target protein expression will be presented. PDX Model Characteristics and Patient Treatment PDX Subtype Pt. Treatment 1 TN AC-T 2 TN FEC-D, Gem+Carbo 3 TN AC-T 4 TN No 5 TN No 6 HR No 7 HR TC, ET, Cape, Gem+Cis, TROP2-ADC Citation Format: Mitchell J. Elliott, Meghan Mcguire, Jennifer Silvester, Chantal Tobin, Samah El Ghamrasni, Francine Lui, Andrew Zhai, Ozge Yoluk, Aron Broom, Tracy Stone, Glenn Butterfoss, Serban Popa, Tianyu Lu, Chris Ing, David White, David W. Cescon. In vivo efficacy of a novel peptide-conjugated drug in patient-derived xenograft models of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5911.

Abstract 4737: The combination of the BET inhibitor JQ1 and gemcitabine induces regressions in gemcitabine resistant patient-derived xenograft models of pancreatic cancer

Abstract Efforts to develop targeted therapies for drug resistant tumors have been relatively unsuccessful. The 5-year survival for patients with advanced pancreatic cancer is ~3%. Gemcitabine is usually combined with nab-paclitaxel as a standard of care for treatment of locally advanced or metastatic pancreatic ductal adenocarcinoma (PDAC). However, no chemotherapeutic regimens thus far evaluated have been curative. We developed the first PDAC patient-derived xenograft (PDX) models in which resistance against gemcitabine was acquired in vivo. We used RNA-seq and ingenuity pathway analysis to compare expression profiles of paired parent vs gemcitabine resistant PDX models. This comparison suggested a previously unreported mechanism for gemcitabine resistance, involving aberrations of cholesterol biosynthesis and lipid metabolism pathways. We also made the unexpected observation that gemcitabine-resistant PDAC models derived from primary tumors have high levels of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2), an enzyme essential to cholesterol biosynthesis and rate limiting in ketogenesis. Notably, the BET bromodomain inhibitor JQ1 decreases HMGCS2 levels; and BET inhibitors + gemcitabine exert synergistic cytotoxicity in gemcitabine-resistant PDAC cells. We determined that the BET bromodomain inhibitor JQ1 + gemcitabine induces regressions of two in vivo gemcitabine-resistant tumor models which we developed directly from primary human tumor tissue. These mechanism-based studies suggest that inhibiting HMGCS2 represents a novel approach to therapy for PDAC. We propose that combining gemcitabine with agents that decrease levels of HMGCS2 comprises effective treatment for patients with drug resistant PDAC. Citation Format: Aubrey L. Miller, Samuel C. Fehling, Eric Josh Brown, Eric O. Heard, Tracy L. Gamblin, Rebecca B. Vance, Karina J. Yoon. The combination of the BET inhibitor JQ1 and gemcitabine induces regressions in gemcitabine resistant patient-derived xenograft models of pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4737.

Abstract 907: ScreenDL: A transfer learning framework integrating tumor omics and functional drug screening for personalized clinical drug response prediction

Abstract Precision oncology hinges on accurate prediction of patient-specific treatment response from tumor molecular inputs. While deep learning (DL) models achieve state-of-the-art response prediction in cell lines, existing methods do not readily translate to the clinic where training data is limited. Here, we have developed and validated ScreenDL, a novel DL framework designed explicitly for use in clinical precision oncology applications. The underlying architecture of ScreenDL consists of two fully connected branches dedicated to learning rich embeddings of a drug’s chemical structure and a tumor’s transcriptomic profile respectively. These tumor omic and drug molecular embeddings are fed into a shared response prediction subnetwork which outputs predicted ln(IC50) values. The ScreenDL training schema incorporates three phases, each designed to improve clinical response prediction: (1) an initial pretraining phase leverages large-scale cell line pharmacogenomic datasets to extract patterns/relationships linking tumor omics and drug response; (2) subsequent transfer learning integrates pharmacogenomic data from patient-derived models of cancer, adapting the pretrained model to a more patient-relevant context; (3) patient-level omics and drug screening data (e.g., from matched patient-derived organoid (PDO) models) is integrated through patient-specific fine-tuning, generating a patient-specific response prediction model. Importantly, biomaterial from surgical tumor resection is often available for organoid establishment and patient-specific drug screening in practical clinical scenarios. To assess the utility of our ScreenDL framework for clinical response prediction, we applied ScreenDL to predict treatment response in 50 advanced/metastatic triple negative breast cancer (TNBC) patient-derived xenograft models (PDX). We leveraged tumor omics profiles for each PDX and drug screening data from matched PDX-derived organoids (PDxOs), mirroring the combination of patient-level tumor omic characterization and functional drug screening in matched PDOs, a protocol currently being piloted in Functional Precision Oncology trials at the University of Utah Huntsman Cancer Institute. After cell line pretraining, ScreenDL achieves a modest median Pearson correlation per drug of 0.15 relative to 0.03 for the leading compared model. However, transfer learning and subsequent PDX-specific fine-tuning significantly improve performance, producing median Pearson correlations per drug of 0.39 and 0.51, respectively. These results demonstrate the ability of our ScreenDL framework to dramatically improve response prediction in clinically relevant domains, bringing DL-based precision treatment selection closer to clinical application. Citation Format: Casey Sederman, Tonya Di Sera, Yi Qiao, Xiaomeng Huang, Bryan E. Welm, Alana L. Welm, Gabor Marth. ScreenDL: A transfer learning framework integrating tumor omics and functional drug screening for personalized clinical drug response prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 907.

Abstract 6909: KRASG12C inhibitor resistance in patient-derived non-small cell lung cancer models

Abstract Introduction: One quarter of lung adenocarcinomas (LUAD) harbor KRAS-mutations, with KRASG12C accounting for the majority (40%). GDP-KRASG12C inhibitors (G12Ci) have been developed for this patient cohort, and two of these are approved for clinical use in the US. While response rates to G12Ci tested in clinical trials have been between 35-50%, studies have identified mechanisms of adaptive resistance to these novel agents, limiting their use as monotherapies. However, primary (intrinsic) resistance to these compounds has not been explored extensively. We leveraged our patient-derived xenograft (PDX) and xenograft-derived organoid (XDO) development programs to study primary resistance to the novel G12Ci, AZD4625. Methods: Twelve KRASG12C PDX models were established which recapitulated patient tumor histology, and genomic, transcriptomic, and methylome profiles. From these 12 PDX, six long-term (passage >10) XDO were generated. PDX were treated with AZD4625 chronically for four weeks as well as in an acute dosing pharmacodynamic study, where tumors were harvested for further analysis. Results: The AZD4625 drug screen in our PDX models reproduced the G12Ci response rate observed in clinical trials. Four of twelve tumor models reduced in size on treatment, while the remainder were considered resistant as these tumors increased in size on treatment. Sensitive tumors became necrotic while those resistant remained proliferative. XDO models recapitulated their originating PDX genomic alterations, histology, as well as responses to AZD4625. During the acute pharmacodynamic screen in our PDX models, we observed a decrease in pERK1/2 and pS6 protein expression in sensitive but not resistant models, despite acute DUSP6 gene expression decreases in every model. Global proteomic analysis highlighted differences between each model. Conclusion: PDX and XDO are useful models to study resistance to this novel class of inhibitor, with the KRASG12C NSCLC PDX models exhibiting a treatment response rate that is similar to those observed in clinical trials. Global proteomics suggests uniqueness of each model in our cohort, hinting that a universal combination of specific targeted agents to treat KRASG12C LUAD tumors may be insufficient. Citation Format: Joshua C. Rosen, Nhu-An Pham, Quan Li, Pinjiang Cao, Katrina Hueniken, Takamasa Koga, Nikolina Radulovich, Alex Koers, Michael Niedbala, Sarah Ross, Adrian Sacher, Ming-Sound Tsao. KRASG12C inhibitor resistance in patient-derived non-small cell lung cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6909.

Abstract 1871: Discovery and characterization of NXV01c, an EGFR × cMET bispecific nanobody drug conjugate with potent anti-tumor activity

Abstract EGFR and cMET are proven cancer targets co-expressed in diverse tumor types. EGFR × cMET bispecific antibody has been approved for the treatment of NSCLC, supporting a simultaneous targeting strategy. In addition to this dual targeting benefit, bispecific antibody drug conjugates (ADCs) targeting EGFR and cMET have also been developed to further improve anti-tumor activity and tissue selectivity. Sufficient target affinity, good cellular internalization and high tumor infiltration are critical for an ADC to mediate therapeutic activity. To this end, we developed the first EGFR × cMET bispecific nanobody conjugated with monomethyl auristatin E (MMAE) as payload (NXV01c). Lead nanobodies against EGFR and cMET were respectively selected from immune libraries by phage display, followed by highly efficient humanization and optimization by neoX’s computation platform. The bispecific nanobody with Fc (NXV01) was constructed by “knobs-into-holes” heterodimerization and then homogeneously conjugated with MMAE via a lysosomal cleavable valine-citrulline dipeptide linker. The resulting bispecific nanobody drug conjugate (NDC), NXV01c, was evaluated in multiple tumor cell lines and tumor xenograft models. NXV01, the pre-conjugate bispecific nanobody, bound EGFR and cMET with nanomolar potency (BLI) and inhibited the phosphorylation of cellular EGFR and cMET with nanomolar IC50 (ELISA). Moreover, it did not activate cellular cMET. Importantly, the NDC NXV01c is highly homogeneous: it has an average DAR of 3.87 and >95% of NXV01c has a DAR of 4. To examine stability of conjugation, NXV01C was incubated in human plasma (37°C) for 14 days, the maximum free drug release rate (by LC/MS/MS) is 0.68%, which is much lower than that of DS8201. In vitro, NXV01c was rapidly internalized into H1975 cells which co-expressed EGFR and cMET. It inhibited the growth of H1975 (lung) and SNU5 (gastric) cancer cells with picomolar activity but spared normal keratinocytes. NXV01c also inhibited the proliferation of additional cell lines derived from lung, gastric, esophageal, and liver cancer, and the level of inhibition positively associated with the expression density of both targets. In an H1975 cell line-derived xenograft model, NXV01C exhibited potent and dose-dependent anti-tumor activity. Treatments at 3 and 10 mg/kg once per week for 2 weeks led to shrinkage and complete regression of tumor, respectively. In patient-derived xenograft models of NSCLC and esophageal cancer, NXV01C led to tumor regression and elimination without noticeable toxic effects. EGFR × cMET bispecific nanobody drug conjugate NXV01c has favorable drug-like properties and demonstrated superior anti-tumor effect in vitro and in vivo. The results suggest NXV01C can be an effective solution for EGFR/cMET bearing tumors commonly found in diverse malignancies. Citation Format: Ran Wu, Puwei Yuan, Yang Xie, Jianxiu Guo, Fei Zhang, Fan Liu, Taylor B. Guo. Discovery and characterization of NXV01c, an EGFR × cMET bispecific nanobody drug conjugate with potent anti-tumor activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1871.

Abstract 5935: Non-allosteric inhibition of enolase 1 sensitizes triple-negative breast cancer for checkpoint inhibitors

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer that commonly returns and spreads. Currently, very few options are available for TNBC treatment. Cancer cells exploit glycolytic machinery for the Warburg effect and aerobic glycolysis. Enolase 1 (ENO1) is the glycolytic enzyme expressed in most tissues, and many cancer cells have higher expression. Apart from the glycolytic role in the cytosol, ENO1 also plays different roles in cancer cells, including as a surface receptor. Method: non-allosteric chemical inhibition was developed and tested in vitro for its efficacy and target validation. Subsequently, in vivo examinations were conducted on emerging small molecules in syngeneic and patient-derived murine models of breast cancer to unveil their anti-tumor efficacy. Results: Our non-allosteric small molecule inhibitor, SU212, binds to ENO1 and restricts its movement within cells. SU212 treatment leads to the accumulation of ENO1 in the nucleus where it restrains the activity of c-Myc. The treatment causes the production of truncated ENO1 called myc promoter-binding protein 1 (MBP-1), which limits the activity of c-Myc. Stand-alone treatment of SU212 restrains the tumor progression and metastasis in orthotopic syngeneic and PDX mouse models. Combining SU212 and Anti-PD1 significantly inhibits tumor growth and metastasis in mouse models. C-Myc is linked to protein transcription that aids immune resistance and tumor evasion of immune surveillance. Suppression of c-Myc activity via SU212 treatment sensitizes the TNBC tumors for anti-PD1 therapy. Conclusions: This study provides compelling preclinical data for further development of SU0212 as an immune therapy sensitizer for the treatment of TNBC. Citation Format: Dhanir Tailor, Fernando Jose Garcia-Marques, Abel Bermudez, Wenqi Li, Arpit Dheeraj, Sharon J. Pitteri, Sanjay V. Malhotra. Non-allosteric inhibition of enolase 1 sensitizes triple-negative breast cancer for checkpoint inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5935.

Abstract 1904: Preclinical development of MGC026, a glycan-linked, exatecan-based antibody-drug conjugate (ADC) targeting B7-H3 for solid cancer

Abstract Introduction: Antibody-drug conjugates (ADCs) have emerged as an important class of therapeutic agents for the treatment of cancer. A duocarmycin-based B7-H3-targeted DNA-alkylating ADC, vobramitamab duocarmazine (vobra duo), has shown encouraging clinical activity in the treatment of metastatic castration-resistant prostate cancer. Given the broad spectrum of tumor indications addressable by targeting B7-H3, we developed MGC026, an ADC incorporating a B7-H3-targeting antibody and a novel glycan-linked topoisomerase 1 inhibitor (TOP1i). With distinct mechanisms of action, vobra duo and MGC026 can address different cancers, tumor stages, or be used in combination with alternate agents to enhance their clinical utility. Methods: MGC026 is comprised of the cleavable linker-payload, bicyclononyne carbamoyl sulfamide Val-Ala-PABC exatecan (SYNtecan E™) site-specifically conjugated at asparagine 297 of the heavy chain through enzymatic glycan remodeling and metal-free click chemistry, using Synaffix’s GlycoConnect™ technology. In vivo efficacy studies were conducted in immunodeficient mice with human tumor cell-line or patient-derived xenografts to identify the spectrum of MGC026-sensitive tumors and the relationship between exposure and antitumor activity. A toxicology study was conducted in cynomolgus monkeys in which MGC026 was administered by 15-minute IV infusion once every three weeks. Pharmacokinetic (PK) analysis and detailed toxicology evaluation was performed. Results: MGC026 demonstrated specific, dose-dependent in vivo antitumor activity toward B7-H3-positive tumor xenografts representing lung, pancreatic, and prostate cancers, head and neck squamous cell carcinoma, and melanoma. Additionally, MGC026 demonstrated antitumor activity toward B7-H3-positive patient-derived xenograft models of lung and prostate cancer, with additional indications under investigation. MGC026, administered to cynomolgus monkeys at dose levels of 10, 30, and 50 mg/kg every 3 weeks for a total of 3 doses, exhibited approximate dose-proportional PK and high stability in circulation. MGC026 was well tolerated, with no lung toxicity observed, and the highest dose level tested (50 mg/kg) was declared as the highest non-severely toxic dose. Conclusions: MGC026 exhibited a favorable preclinical profile, with potent in vivo activity toward B7-H3-expressing tumor xenografts representing a range of cancer indications. MGC026 was tolerated in cynomolgus monkeys, a relevant toxicology model, at exposure levels exceeding those required for antitumor activity. These data support clinical development of MGC026 for the treatment of B7-H3-expressing solid cancers. Citation Format: Juniper A. Scribner, Jennifer G. Brown, Thomas Son, Linda Jin, Carroll McKenzie, Viktoriya Nam, Curtis Bush, Dienis Quinonez, James Tamura, Sergey Gorlatov, Hua Li, Shelley Butler, Ezio Bonvini, Deryk Loo. Preclinical development of MGC026, a glycan-linked, exatecan-based antibody-drug conjugate (ADC) targeting B7-H3 for solid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1904.

Abstract 3317: KRASmulti inhibitor BI 3706674 shows efficacy in KRAS-driven preclinical models of cancer that supports clinical testing in patients with tumors harbouring KRASG12V mutations and KRAS wild-type amplifications

Abstract Alterations in KRAS are a main cancer driver. Amplifications of the KRAS wild-type (wt) allele account for ~7% of all KRAS-driven cancers and are frequent in gastric (~5%), esophageal (~13%) and gastroesophageal junction cancers (~12%). KRASG12V mutations account for ~28% of pancreatic cancers, 9% of colorectal cancers and 6% of lung adenocarcinoma. There is an urgent medical need to identify targeted therapies for these frequent KRAS alterations. Herein, we describe BI 3706674, a novel, potent and orally bioavailable small molecule inhibitor of the KRAS oncogene for clinical testing in patients with tumors harboring KRASG12V mutations and KRAS wild-type amplifications. BI 3706674 binds non-covalently to multiple KRAS mutant alleles, including the KRAS wt allele, in the GDP-bound state and thereby disrupts oncogenic signaling. Importantly, BI 3706674 is highly selective for KRAS vs HRAS or NRAS, and it is therefore expected to be well-tolerated in normal tissues. In two large cancer cell line panels (PRISM and Horizon), BI 3706674 shows sensitivity across a wide range of KRAS alleles (KRAS wt amplifications and KRAS mutations e.g., G12A/C/D/V, G13D and Q61H). The strongest sensitivity was observed for cell lines with KRAS wt amplifications (relative copy number (CN) of > 10) followed by cell lines with KRASG12V mutations along with significant pharmacodynamic (PD) biomarker modulation (e.g., down-regulation of DUSP6 mRNA). In vivo, BI 3706674 was well-tolerated and showed dose-dependent efficacy in cell line-derived and patient-derived xenograft models of human gastric cancer with KRAS wt CN > 10 and diverse tumor types with KRASG12V mutations. A twice daily oral dose of 30 mg/kg induced significant tumor regression and PD biomarker modulation. Combination of BI 3706674 with standard of care therapies and novel agents are being tested in preclinical models to guide clinical development. Results of the ongoing pre-clinical analysis will be shared. A Phase I clinical trial is in preparation in patients with advanced solid cancers harboring KRASG12V mutations and KRAS wt amplifications to evaluate safety, tolerability, pharmacokinetic and pharmacodynamic properties, and efficacy of BI 3706674. Citation Format: Antonio Tedeschi, David H. Peng, Fiorella Schischlik, Lorenz Herdeis, Otmar Schaaf, Valeria Santoro, Daniel Gerlach, Fabio Savarese, Jesse Lipp, Christian Haslinger, Francesca Rocchetti, Johannes Popow, Heinrich J. Huber, Birgit Wilding, Matthias Treu, Julian Fuchs, Joachim Broeker, Tobias Wunber, Michael Gmachl, Klaus Rumpel, Matthew Rees, Melissa Ron, Jennifer Roth, Mariah Williams, Charles Deckard, Vandhana Ramamoorthy, Joseph R. Daniele, Jaffer A. Ajani, Funda Meric-Bernstam, Scott Kopetz, Michael Kim, Don L. Gibbons, Christopher P. Vellano, Joseph R. Marszalek, Timothy P. Heffernan, Darryl McConnell, Mark Pearson, Norbert Kraut, Dorothea Rudolph. KRASmulti inhibitor BI 3706674 shows efficacy in KRAS-driven preclinical models of cancer that supports clinical testing in patients with tumors harbouring KRASG12V mutations and KRAS wild-type amplifications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3317.

Abstract 2047: Scale up and scale down approaches for screening of 3D patient-derived cell models

Abstract 3D cell culture is becoming more prevalent as scientists work to better model human physiology using in vitro systems. However, differences in handling 3D cell cultures compared to traditional 2D cell lines have limited adoption of 3D techniques in compound and cell therapy screening experiments. To facilitate use of patient-derived 3D tumoroid models, we developed protocols for both scale up and scale down of these models in Gibco™ OncoPro™ Tumoroid Culture Medium. OncoPro Tumoroid Culture Medium is a serum-free, conditioned medium-free culture medium designed to promote the growth of patient-derived 3D cancer models (tumoroids, cancer organoids). OncoPro medium is compatible with a suspension culture approach for easier handling compared to traditional embedded culture formats. We studied the growth of tumoroids in different flask sizes during suspension culture to optimize scale up for downstream assays. Tumoroid growth rates and morphologies were consistent across non-tissue culture treated flask sizes, and viable cell yield increased with surface area during scale up. In some cases, as many as 100 × 106 dissociated tumoroid cells can be recovered from a single Nunc™ TripleFlask™ after a week of growth. After scaling up, tumoroids were dissociated and seeded in multiwell plates to test multiple screening conditions (compound identity, compound concentration) in parallel. Dissociated cells were seeded in 96-well plates using both manual and automated liquid handling (Tecan Fluent 780). Due to the tendency of 3D cell models to aggregate and fall out of solution, initial seeding in a 96-well flat bottom plate resulted in high well-to-well variability. Optimization of cell seeding protocols led to standard deviations in tumoroid metabolic activity, number, and size that were comparable to manual seeding, with a coefficient of variation of less than 3% between wells for multiple tumoroid lines when automation was implemented. Generally, variability in cell seeding was lower when using the optimized, automated cell seeding protocol compared to manual methods. After seeding, cells were grown for three days to form tumoroids prior to the addition of compounds. At this time point, there was low well-to-well variability in tumoroid metabolic activity (CV<2%). Compounds and reagents to analyze cell health could also be added using automated liquid handling prior to analysis on plate readers or high-content imaging platforms. Citation Format: Colin Paul, Anthony Chatman, Amber Bullock, Xiaoyu Jenny Yang, Garrett Wong, Brittany Balhouse, Chris Yankaskas, Erik Willems, Matt Dallas, David Kuninger. Scale up and scale down approaches for screening of 3D patient-derived cell models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2047.

Abstract 2839: The mouse models of human cancer database (MMHCdb)

Abstract The laboratory mouse plays a pivotal role as an experimental system for investigations into the genetic and genomic basis of cancer susceptibility, initiation, and progression and for preclinical research on novel treatment strategies for cancer. Advances in mouse models include humanized mice, transplant compliant mouse strains, and panels of genetically diverse mice (e.g., Diversity Outbred and Collaborative Cross). The distributed and heterogenous nature of information about these model systems presents a significant challenge to finding and aggregating information about mouse models and to identifying the most relevant models for a particular research question. The Mouse Models of Human Cancer database (http://tumor.informatics.jax.org) is an expertly curated FAIR-compliant knowledgebase that applies community annotation standards and nomenclature standards for genes, alleles, and strains to support accurate and comprehensive search results for mouse models of human cancer. The data in MMHCdb are curated from peer-reviewed scientific publications and direct data submissions from individual investigators and large-scale programs. A primary focus of the resource is to reflect the impact that genetic background has on the cancer-related characteristics of mouse models. The database includes information on spontaneous and genetically engineered cancer models as well as Patient Derived Xenografts and diversity panels. The database supports faceted searching for models by multiple criteria including, tumor type, genetic background of the mouse model, somatic mutations, and publication. Model descriptions include summaries of observed frequencies of tumors observed in the model and histopathology images. Information in MMHCdb is linked to cancer model data from other bioinformatics resources including the Patient Derived Cancer Models database (PDCM), PathBase, the Gene Expression Omnibus (GEO), and ArrayExpress. MMHCdb is supported by NCI R01 CA089713 Citation Format: Dale A. Begley, Debra M. Krupke, Emily Jocoy, Steven B. Neuhauser, Carol J. Bult. The mouse models of human cancer database (MMHCdb) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2839.

Abstract 6915: Integrated proteogenomic analysis for the NCI patient-derived cancer model repository

Abstract Background: Studying protein expression involved in cancer from patient-derived xenografts (PDX) enhances understanding of tumorigenesis and may shed light on patient therapeutic decisions. Recently, mass spectrometry-based proteomics sequencing techniques have enabled the acquisition of high-throughput PDX protein/phosphoprotein expression profiles and paved a way for investigating oncogenic signaling pathways and their interactions in different tumor histologies. Integrated analysis of these proteomic data with existing biomarkers derived from whole exome and RNAseq data will provide the community with a rich resource for translational research. Materials and methods: iTRAQ-based proteomics/phospho-proteomics data, with 11 Tandem Mass Tag (TMT) channels, were processed and median-normalized at gene level. The gene expression data were derived from tximport and DESeq2 from of RNA-Seq. In addition, whole exome sequencing (WES) data were used to compute mutations and copy number profiles. For data visualization, the R Bioconductor package ComplexHeatmap was used extensively. Results: PDX proteomics/phospho-proteomics data were analyzed alongside with gene expression, copy number and mutational profiles for several cancer types, revealing vivid molecular regulation for many cancer-related pathways. A moderate yet significant Spearman correlation coefficient of over 0.45 and 0.5 was observed between proteomics and RNA-Seq data at gene and pathway level, respectively. The PDX protein and gene expression pattern from common cancer regulatory pathways of bladder (BLCA, n=32 models), colon (COAD, n=82), lung (NSCLC, n=32), pancreatic (PAAD, n=52), metastatic breast cancer (CSNOS) (n=16) and other histologies were aggregated and discussed at the model level. EGFR, MET and cell-cycle genes CDKN2A and CDKN2B exhibited significant positive correlation among copy number, gene expression and protein expression profiles. Protein and gene expression profiles of PAM50 genes were shown for CSNOS samples, to further sub-classify or correct misclassification. Further analysis using proteomics/phospho-proteomics data with CNA identified several trans-regulatory events. Lastly, we identified RTN1 as a potential biomarker, exhibiting lower expression in sensitive rare-tumor PDX models prior to Axitinib and Vandetanib treatment. Conclusions: With the multi-omics datasets comprising proteomics/phospho-proteomics, RNA-Seq and WES datasets from the NCI Patient Derived Models Repository cohort, we were able to query some important cancer biological processes at a higher resolution. In addition, we revealed gene- and pathway-level regulatory differences from various histologies. Overall, the multi-omics data from PDX models showed promising recapitulation of original tumor activity and should continue to serve as an amenable and scalable drug screening platform for pre-clinical trials. Citation Format: Peter I. Wu, Li Chen, Yuri Kotliarov, Jianwen Fang, Yingdong Zhao, Yvonne Evrard, Lijun Chen, Shahanawaz Jiwani, Biswajit Das, Chris A. Karlovich, Hui Zhang, Lisa McShane, Melinda G. Hollingshead, Mickey Williams, James H. Doroshow. Integrated proteogenomic analysis for the NCI patient-derived cancer model repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6915.

Abstract 6907: Micro-implantation of patient tumor samples into the avian embryo, a fast and reliable alternative in vivo technology for preclinical studies on melanoma and follicular lymphoma

Abstract Despite recent efforts to develop reliable and predictive patient-derived cancer models, drug attrition rates in oncology remain high. Moreover, conventional models such as patient-derived xenograft (PDX) mouse models face major cost and time limitations, not supporting real-time clinical decision making. To overcome such limitation, ONCOFACTORY developed a proprietary PDX platform enabling the engraftment of small size tumor biopsy samples within targeted tissue of the avian embryo at early stage of development, to conduct preclinical proof of efficacy studies and provide PDX clinical trial solution helping with patient’s selection prior to clinical phase II/III. On one hand, we performed prospective co-clinical trial aiming to evaluate the utility of the AVI-PDXTM model in predicting the response to standard therapy, consisting of BRAF and MEK inhibitors, for patient with metastatic melanoma harboring BRAF mutations. Skin biopsy samples were implanted into specific tissue driving tumor formation under the skin of avian embryos. On the other hand, we conducted a retrospective cohort study with 20 follicular lymphoma (FL) patient samples divided into “partial” and “complete” responders to the standard immuno-chemotherapy RCHOP regimen to establish FL AVI-PDXTM, and examine sensitivity to RCHOP in ovo. Twenty-four hours post-implantation, avian melanoma and FL replicas were respectively exposed to BRAFi/MEKi or RCHOP and their vehicles, over 24h. Then, embryos were harvested, and tumor response was examined by measuring tumor volume using light sheet microscopy. Alongside, in independent series of avian embryos implanted with FL samples, tumors were harvested for single-cell transcriptomic analyses to explore mechanism of response to RCHOP. For melanoma, we provide the proof of concept that the AVI-PDXTM reliably predict sensitivity or resistance to BRAF and MEK inhibitors within days, matching patient clinical outcome observed in clinic. For FL, we showed that the FL-AVI-PDXTM efficiently captures clinical response to RCHOP in a heterogenous cohort of patients, enabling to discriminate partial and complete responder within short-time frame. Next, we identified a robust genetic signature reflecting exposure of tumoral cells to RCHOP and showed that drug-mediated targeting of one of these genes with a chemotherapy resulted in strong potentiation of RCHOP. Thus, we provide evidence of the high predictive power of the AVI-PDXTM models allowing fast and reproducible generation of tumors replicas from small size patient tumor samples. This places the AVI-PDXTM as a valuable tool for clinical research to rationalize patient inclusion in clinical trials but also for the design of personalized medicine assays. Citation Format: Clelia Costechareyre, Loraine Jarrosson, Marjorie Lacourrege, Romain Teinturier, Julie Caramel, Manon Zala, Stéphane Dalle, Pierre Sujobert, Céline Delloye-Bourgeois, Frédéric Berget, Valérie Castellani. Micro-implantation of patient tumor samples into the avian embryo, a fast and reliable alternative in vivo technology for preclinical studies on melanoma and follicular lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6907.