Preclinical Drug Development Research Articles

Evaluation of a Three-Dimensional Primary Human Hepatocyte Spheroid Model: Adoption and Industrialization for the Enhanced Detection of Drug-Induced Liver Injury.

Drug-induced liver injury is a leading cause of compound attrition during both preclinical and clinical drug development, and early strategies are in place to tackle this recurring problem. Human-relevant in vitro models that are more predictive of hepatotoxicity hazard identification, and that could be employed earlier in the drug discovery process, would improve the quality of drug candidate selection and help reduce attrition. We present an evaluation of four human hepatocyte in vitro models of increasing culture complexity (i.e., two-dimensional (2D) HepG2 monolayers, hepatocyte sandwich cultures, three-dimensional (3D) hepatocyte spheroids, and precision-cut liver slices), using the same tool compounds, viability end points, and culture time points. Having established the improved prediction potential of the 3D hepatocyte spheroid model, we describe implementing this model into an industrial screening setting, where the challenge was matching the complexity of the culture system with the scale and throughput required. Following further qualification and miniaturization into a 384-well, high-throughput screening format, data was generated on 199 compounds. This clearly demonstrated the ability to capture a greater number of severe hepatotoxins versus the current routine 2D HepG2 monolayer assay while continuing to flag no false-positive compounds. The industrialization and miniaturization of the 3D hepatocyte spheroid complex in vitro model demonstrates a significant step toward reducing drug attrition and improving the quality and safety of drugs, while retaining the flexibility for future improvements, and has replaced the routine use of the 2D HepG2 monolayer assay at GlaxoSmithKline.

The Alzheimer\u2019s disease drug development landscape

BackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disease leading to dementia. The field has made significant progress over the last 15 years. AD diagnosis has shifted from syndromal, based on signs and symptoms, to a biomarker construct based on the pathological hallmarks of the disease: amyloid β deposition, pathologic tau, and neurodegeneration. Numerous genetic risk factors for sporadic AD have been identified, providing further insight into the molecular underpinnings of the disease. For the last two decades, however, drug development for AD has been proven to be particularly challenging. Here, we provide a unique overview of the drug development landscape for AD. By comparing preclinical and clinical drug development pipelines, we aim to describe trends and differences regarding target classes and therapeutic modalities in preclinical and clinical development.MethodsWe analyzed proprietary and public databases and company websites for drugs in preclinical development for AD by the pharmaceutical industry and major clinical trial registries for drugs in clinical development for AD. Drugs were categorized by target class and treatment modality.ResultsWe found a higher proportion of preclinical interventions targeting molecular pathways associated with sporadic AD genetic risk variants, compared to clinical stage interventions. These include apolipoprotein E (ApoE) and lipids, lysosomal/endosomal targets, and proteostasis. Further, we observed a trend suggesting that more traditional therapeutic modalities are developed for these novel targets, while more novel treatment modalities such as gene therapies and enzyme treatments are in development for more traditional targets such as amyloid β and tau. Interestingly, the percentage of amyloid β targeting therapies in preclinical development (19.2%) is even higher than the percentage in clinical development (10.7%), indicating that diversification away from interventions targeting amyloid-beta has not materialized. Inflammation is the second most popular target class in both preclinical and clinical development.ConclusionsOur observations show that the AD drug development pipeline is diversifying in terms of targets and treatment modalities, while amyloid-targeting therapies remain a prominent avenue of development as well. To further advance AD drug development, novel companion diagnostics are needed that are directed at disease mechanisms related to genetic risk factors of AD, both for patient stratification and assessment of therapeutic efficacy in clinical trials.

Current and emerging mass spectrometry methods for the preclinical development of metal-based drugs: a critical appraisal.

This Trends article highlights the multiple ways in which the state-of-the-art molecular mass spectrometry can support the preclinical development of novel metal-based anticancer drugs. Examples from the recent literature-beyond routine characterization applications-are presented to illustrate what analytical and experimental design challenges are to be addressed to facilitate the translation of promising drug candidates to clinical practice.

Validating Multivariate Classification Algorithms in Raman Spectroscopy-Based Osteosarcoma Cellular Analysis

Raman microspectroscopy has been widely demonstrated as an ideal analytical tool for preclinical drug development and clinical applications. However, it is still not easy to accurately identify the subtle spectral variations in different biological samples, which requires a feasible combination between novel spectra collection instrumentation and effective data mining algorithms. In this study, three distinct multivariate classification approaches, which were principal component analysis-linear discriminant analysis (PCA-LDA), support vector machine (SVM), and principal component analysis-support vector machine (PCA-SVM), were validated and compared for obtaining reliable and chemically significant results from the analysis of bio-spectral data. Their performances were evaluated by classifying the spectral characteristics of osteosarcoma cells treated with N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT) from untreated cells. Based on the discriminated spectral variations, the results indicate that PCA combined with the radial basis function (RBF) kernel SVM model achieved the highest classification accuracy. In general, this study confirms that PCA-SVM algorithm improves the automatic processing accuracy and efficiency of micro-Raman spectroscopy, which may be adopted in further cell screening and analysis applications.

Application of LDH assay for therapeutic efficacy evaluation of ex vivo tumor models

The current standard preclinical oncology models are not able to fully recapitulate therapeutic targets and clinically relevant disease biology, evidenced by the 90% attrition rate of new therapies in clinical trials. Three-dimensional (3D) culture systems have the potential to enhance the relevance of preclinical models. However, the limitations of currently available cellular assays to accurately evaluate therapeutic efficacy in these models are hindering their widespread adoption. We assessed the compatibility of the lactate dehydrogenase (LDH) assay in 3D spheroid cultures against other commercially available readout methods. We developed a standardized protocol to apply the LDH assay to ex vivo cultures, considering the impact of culture growth dynamics. We show that accounting for growth rates and background release levels of LDH are sufficient to make the LDH assay a suitable methodology for longitudinal monitoring and endpoint assessment of therapeutic efficacy in both cell line-derived xenografts (xenospheres) and patient-derived explant cultures. This method has the added value of being non-destructive and not dependent on reagent penetration or manipulation of the parent material. The establishment of reliable readout methods for complex 3D culture systems will further the utility of these tumor models in preclinical and co-clinical drug development studies.

Functional in vitro assessment of modified antibodies: Impact of label on protein properties.

Labelling of therapeutic antibodies with radionuclides or fluorophores is routinely used to study their pharmacokinetic properties. A critical assumption in utilizing labelled therapeutic antibodies is that the label has no unfavourable effects on antibody charge, hydrophobicity, or receptor affinity. Ideally, the labelled protein should not have any significant deviations from the physiological properties of the original molecule. This article describes an established quality in vitro assessment workflow for labelled antibodies that ensures better prediction of changes in antibody pharmacokinetic (PK) properties after modifications. This analysis package considers degradation and aggregation analysis by size-exclusion chromatography, changes in neonatal-Fc-receptor (FcRn) affinity, and heparin interaction. FcRn binding is important for antibody recycling and half-life extension, whereas heparin affinity provides estimates on the rate of endocytosis through unspecific cell surface binding. Additionally, mass spectrometric analysis to determine the degree of labelling (DoL) completes the package and the combined analysis data allow to predict the label contribution to the PK properties of the modified antibody. This analytical strategy for labelling 11 IgGs has been investigated using 2 different IgG1 constructs and applying 7 different types of labels. Each labelling resulted in a change in the physicochemical properties of the protein. Not only can the DoL of modified IgGs lead to a change in protein properties, but the type of label also can. Furthermore, it was demonstrated that the labelling process can also influence the behaviour of labelled mAbs. An identical label on different constructs of IgG1 can cause different affinities for FcRn and heparin. Considering the assessment data, only 6 of the 11 modified antibodies from this study can be recommended for subsequent experiments. In conclusion, a suitability assessment of labelled antibodies prior to any pharmacokinetic studies is essential to reduce cost, allocate resources and reduce the number of animal experiments during pre-clinical drug development.

Predictivity of standardized and controlled permeation studies: Ex vivo – In vitro – In vivo correlation for sublingual absorption of propranolol

In preclinical drug development, ex vivo and in vitro permeability studies are a decisive element for specifying subsequent development steps. In this context, reliability, physiological alignment and appropriate in vivo correlation are mandatory for predictivity regarding drug absorption. Especially in oromucosal drug delivery, these prerequisites are not adequately met, which hinders its progressive development and results in the continuous need for animal experiments. To address current limitations, an innovative, standardized, and controlled ex vivo permeation model was applied. It is based on Kerski diffusion cells embedded in automated sampling and coupled to mass spectrometric quantification under physiologically relevant conditions. This study aimed to evaluate the predictivity of the developed model using porcine mucosa (ex vivo) in relation to data of sublingual propranolol absorption (in vivo). In addition, the usefulness of biomimetic barriers (in vitro) as a replacement for porcine mucosa was investigated. Therefore, solubility and permeability studies considering microenvironmental conditions were conducted and achieved good predictivity (R2 = 0.997) for pH-dependent permeability. A multiple level C correlation (R2 ≥ 0.860) between obtained permeability and reported pharmacokinetic animal data (AUC, Cmax) was revealed. Furthermore, a point-to-point correlation was demonstrated for several sublingual formulations. The successful IVIVC confirms the standardized ex vivo model as a viable alternative to animal testing for estimating the in vivo absorption behavior of oromucosal pharmaceuticals.

Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs

We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately 8 days post-tumour injection. Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article, we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development.

Detecting Novel Ototoxins and Potentiation of Ototoxicity by Disease Settings.

Over 100 drugs and chemicals are associated with permanent hearing loss, tinnitus, and vestibular deficits, collectively known as ototoxicity. The ototoxic potential of drugs is rarely assessed in pre-clinical drug development or during clinical trials, so this debilitating side-effect is often discovered as patients begin to report hearing loss. Furthermore, drug-induced ototoxicity in adults, and particularly in elderly patients, may go unrecognized due to hearing loss from a variety of etiologies because of a lack of baseline assessments immediately prior to novel therapeutic treatment. During the current pandemic, there is an intense effort to identify new drugs or repurpose FDA-approved drugs to treat COVID-19. Several potential COVID-19 therapeutics are known ototoxins, including chloroquine (CQ) and lopinavir-ritonavir, demonstrating the necessity to identify ototoxic potential in existing and novel medicines. Furthermore, several factors are emerging as potentiators of ototoxicity, such as inflammation (a hallmark of COVID-19), genetic polymorphisms, and ototoxic synergy with co-therapeutics, increasing the necessity to evaluate a drug's potential to induce ototoxicity under varying conditions. Here, we review the potential of COVID-19 therapies to induce ototoxicity and factors that may compound their ototoxic effects. We then discuss two models for rapidly detecting the potential for ototoxicity: mammalian auditory cell lines and the larval zebrafish lateral line. These models offer considerable value for pre-clinical drug development, including development of COVID-19 therapies. Finally, we show the validity of in silico screening for ototoxic potential using a computational model that compares structural similarity of compounds of interest with a database of known ototoxins and non-ototoxins. Preclinical screening at in silico, in vitro, and in vivo levels can provide an earlier indication of the potential for ototoxicity and identify the subset of candidate therapeutics for treating COVID-19 that need to be monitored for ototoxicity as for other widely-used clinical therapeutics, like aminoglycosides and cisplatin.

Comparative analysis of molecular fingerprints in prediction of drug combination effects.

Application of machine and deep learning methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel computational solutions in relation to established techniques. To this end, we compare rule-based and data-driven molecular representations in prediction of drug combination sensitivity and drug synergy scores using standardized results of 14 high-throughput screening studies, comprising 64 200 unique combinations of 4153 molecules tested in 112 cancer cell lines. We evaluate the clustering performance of molecular representations and quantify their similarity by adapting the Centered Kernel Alignment metric. Our work demonstrates that to identify an optimal molecular representation type, it is necessary to supplement quantitative benchmark results with qualitative considerations, such as model interpretability and robustness, which may vary between and throughout preclinical drug development projects.

Multimodal platform for assessing drug distribution and response in clinical trials.

Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy. Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial. PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib. The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

Selected Articles from This Issue

In this First Disclosure, Smith and colleagues describe ASN004, a Dolaflexin-containing antibody drug conjugate targeting the 5T4 oncofetal antigen expressed on a wide range of tumors. ASN004 contains a scFv-Fc antibody and a Auristatin F Hydroxypropylamide payload with a drug-to-antibody ratio of 10-12. In a single dose study, 1 mg/kg achieved complete tumor regression in a cervical cancer model. ASN004 was also shown to have greater activity than the HER2-targeted trastuzumab-DM1 in a gastric model with high HER2 expression despite low 5T4 expression. Pharmacokinetics revealed low free payload drug and dose-dependent exposure. Their results support the continued clinical development of ASN004.In this First Disclosure, Duranti and colleagues outline a single-chain diabody targeting the hERG1 potassium channel and the β1 subunit of integrin receptors (scDb-hERG1-β1). The diabody bound with high affinity to the two proteins only when they were linked together and spared normal cells. The scDb-hERG1-β1 was antiproliferative against tumor spheroids through inhibition of AKT and HIF-1α signaling. The diabody also showed a favorable pharmacokinetic and toxicologic profile when injected into mice. Taken together, the disclosure provides evidence for the continued clinical development of scDb-hERG1-β1.VEGF inhibitors and immune therapies have continued to create favorable outcomes for renal cell carcinoma (RCC) patients. For those who don't respond to these therap. options, Yang and colleagues hypothesized mTOR inhibition will remain a salvage option either by itself or in combined therapy. A recent clinical trial demonstrated mTOR inhibition combined with the vascular agent BNC105P failed to show increased efficacy compared to mTOR inhibition alone. In this study, they demonstrate the transcriptomic gene signatures of patients from that clinical study that correlated with benefit with mTOR inhibition. Their findings were then validated using the phase III CheckMate 025 study.There remains an urgent need for new drug discovery in pediatric cancer with an added goal of reducing long-term toxicity. In this article, Vassal and colleagues underline the outcome of a pediatric cancer international multistakeholder meeting to develop a consensus set of requirements for preclinical drug development in pediatric cancers. The recommendations include the use of cell-based and mouse models as well as proof-of-concept data packages for clinical development. They are designed to represent the minimum guidelines necessary for the international development of drugs for pediatric cancer within the new regulatory environment set up by the RACE act.

Harnessing the power of microphysiological systems for COVID-19 research

The pharmaceutical industry is constantly striving for innovative ways to bridge the translational gap between preclinical and clinical drug development to reduce attrition. Substantial effort has focused on the preclinical application of human-based microphysiological systems (MPS) to better identify compounds not likely to be safe or efficacious in the clinic. The Coronavirus 2019 (COVID-19) pandemic provides a clear opportunity for assessing the utility of MPS models of the lungs and other organ systems affected by the disease in understanding the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and in the development of effective therapeutics. Here, we review progress and describe the establishment of a global working group to coordinate activities around MPS and COVID-19 and to maximize their scientific, human health, and animal welfare impacts.

SARS-CoV-2 Antiviral Therapy.

SUMMARYThe development of effective antiviral therapy for COVID-19 is critical for those awaiting vaccination, as well as for those who do not respond robustly to vaccination. This review summarizes 1 year of progress in the race to develop antiviral therapies for COVID-19, including research spanning preclinical and clinical drug development efforts, with an emphasis on antiviral compounds that are in clinical development or that are high priorities for clinical development. The review is divided into sections on compounds that inhibit SARS-CoV-2 enzymes, including its polymerase and proteases; compounds that inhibit virus entry, including monoclonal antibodies; interferons; and repurposed drugs that inhibit host processes required for SARS-CoV-2 replication. The review concludes with a summary of the lessons to be learned from SARS-CoV-2 drug development efforts and the challenges to continued progress.

Integrated Microscopy and Metabolomics to Test an Innovative Fluid Dynamic System for Skin Explants In Vitro.

The in vitro models are receiving growing attention in studies on skin permeation, penetration, and irritancy, especially for the preclinical development of new transcutaneous drugs. However, synthetic membranes or cell cultures are unable to effectively mimic the permeability and absorption features of the cutaneous barrier. The use of explanted skin samples maintained in a fluid dynamic environment would make it possible for an in vitro experimentation closer to in vivo physiological conditions. To this aim, in the present study, we have modified a bioreactor designed for cell culture to host explanted skin samples. The preservation of the skin was evaluated by combining light, transmission, and scanning electron microscopy, for the histo/cytological characterization, with nuclear magnetic resonance spectroscopy, for the identification in the culture medium of metabolites indicative of the functional state of the explants. Our morphological and metabolomics results demonstrated that fluid dynamic conditions ameliorate significantly the structural and functional preservation of skin explants in comparison with conventional culture conditions. Our in vitro system is, therefore, reliable to test novel therapeutic agents intended for transdermal administration in skin samples from biopsies or surgical materials, providing predictive information suitable for focused in vivo research and reducing animal experimentation.

Progress and Challenges in the Use of a Liver-on-a-Chip for Hepatotropic Infectious Diseases.

The liver is a target organ of life-threatening pathogens and prominently contributes to the variation in drug responses and drug-induced liver injury among patients. Currently available drugs significantly decrease the morbidity and mortality of liver-dwelling pathogens worldwide; however, emerging clinical evidence reveals the importance of host factors in the design of safe and effective therapies for individuals, known as personalized medicine. Given the primary adherence of cells in conventional two-dimensional culture, the use of these one-size-fit-to-all models in preclinical drug development can lead to substantial failures in assessing therapeutic safety and efficacy. Advances in stem cell biology, bioengineering and material sciences allow us to develop a more physiologically relevant model that is capable of recapitulating the human liver. This report reviews the current use of liver-on-a-chip models of hepatotropic infectious diseases in the context of precision medicine including hepatitis virus and malaria parasites, assesses patient-specific responses to antiviral drugs, and designs personalized therapeutic treatments to address the need for a personalized liver-like model. Second, most organs-on-chips lack a monitoring system for cell functions in real time; thus, the review discusses recent advances and challenges in combining liver-on-a-chip technology with biosensors for assessing hepatocyte viability and functions. Prospectively, the biosensor-integrated liver-on-a-chip device would provide novel biological insights that could accelerate the development of novel therapeutic compounds.

Fed-batch production assessment of a tetravalent bispecific antibody: A case study on piggyBac stably transfected HEK293 cells

The transition from preclinical biological drug development into clinical trials requires an efficient upscaling process. In this context, bispecific antibody drugs are particularly challenging due to their propensity to form aggregates and generally produce low titers. Here, the upscaling process for a tetravalent bispecific antibody expressed by a piggyBac transposon-mediated stable HEK293 cell pool has been evaluated. The project was performed as a case study at Testa Center, a non-GMP facility for scale-up testing of biologics in Sweden, and encompassed media adaptation strategies, fed-batch optimization and a novel antibody purification technology. The cell pool was adapted to different culture media for evaluation in terms of cell viability and titers compared to its original Expi293 Expression Medium. These parameters were assessed in both sequential stepwise adaption and direct media exchanges. By this, a more affordable medium was identified that did not require stepwise adaptation and with similar titers and viability as in the Expi293 Expression Medium. Fed-batch optimizations resulted in culture densities reaching up to 20 × 106 viable cells/mL with over 90 % viability 12 days post-inoculum, and antibody titers three times higher than corresponding batch cultures. By implementing a novel high-speed protein A fiber technology (Fibro PrismA) with a capture residence time of only 7.5 s, 8 L of supernatant could be purified in 4.5 h without compromising the purity, structural integrity and function of the bispecific antibody. Results from this study related to medium adaptation and design of fed-batch protocols will be highly beneficial during the forthcoming scale-up of this therapeutic antibody.

Utilizing feline oral squamous cell carcinoma patients to develop NQO1-targeted therapy

Developing effective therapies for the treatment of advanced head-and-neck squamous cell carcinoma (HNSCC) remains a major challenge, and there is a limited landscape of effective targeted therapies on the horizon. NAD(P)H:quinone oxidoreductase 1 (NQO1) is a 2-electron reductase that is overexpressed in HNSCC and presents as a promising target for the treatment of HNSCC. Current NQO1-targeted drugs are hindered by their poor oxidative tolerability in human patients, underscoring a need for better preclinical screening for oxidative toxicities for NQO1-bioactivated small molecules. Herein, we describe our work to include felines and feline oral squamous cell carcinoma (FOSCC) patients in the preclinical assessment process to prioritize lead compounds with increased tolerability and efficacy prior to full human translation. Specifically, our data demonstrate that IB-DNQ, an NQO1-targeted small molecule, is well-tolerated in FOSCC patients and shows promising initial efficacy against FOSCC tumors in proof-of-concept single agent and radiotherapy combination cohorts. Furthermore, FOSCC tumors are amenable to evaluating a variety of target-inducible couplet hypotheses, evidenced herein with modulation of NQO1 levels with palliative radiotherapy. The use of felines and their naturally-occurring tumors provide an intriguing, often underutilized tool for preclinical drug development for NQO1-targeted approaches and has broader applications for the evaluation of other anticancer strategies.

Abstract 3014: A preclinical platform of PDX-derived cell lines as a tool for pharmacological screening and functional studies

Abstract Despite considerable progress in understanding the biology and genetics of cancer progression, the development of effective therapies against cancer need physiological and predictive preclinical models. In this context, patient-derived xenograft (PDX) models has become a standard tool as they reproduce accurately the behavior of tumor of origin, in term of histological and molecular phenotype and response to chemotherapy. Although PDXs in vivo models are indispensable for preclinical studies, they suffer from some limitations due to study costs related to tumor maintenance on mice, variable engraftment rate, growth delay and limited throughput for large-scale drug screening. To address this problem and propose a time a cost effective preclinical screening tool, we developed a panel of PDX-derived low-passage 2D cell lines as a convenient in vitro pre-screening platform to profile compound activity. Different PDX models including breast, lung, colon, melanoma, glioblastoma and hepatoblastoma were tested for their capacity to generate cell lines maintaining the characteristics of the parental PDX tumor and usable for in vitro assays. Today, we succeeded with a series of 50 PDX models with 83% success rate. Tumor cells isolated from PDX tumor tissue were cultured under different media and matrix conditions, allowing at least 5 passages in culture. A Short Tandem Repeat (STR) comparison profile was done with the parental PDX before performing a master bank. We performed short term 2D cytotoxicity assays and long term colony assays to compare cell lines in vitro drug sensitivity with their parental PDX in vivo drug response and overall, the results show that this panel reproduced the drug response profile of the original PDXs with chemotherapies, PARP inhibitors, an ADC (T-DM1) and FGFR-targeting therapies. Moreover, cellular models engrafted back onto mice showed in vivo response to chemotherapies similar to that of the parental PDX confirming the identical behavior of cell line/PDX couples. As the use of cellular models is still considered as a standard for early preclinical test to evaluate drug response before moving to in vivo assays, our PDX-derived cell line platform appeared to be a robust and relevant tool. Furthermore, since the main concern when using in vitro models is the representativeness of the results obtained when transposed to in vivo models, the similarities between cell lines and parental PDX should maximize success of further in vivo preclinical drug development. Citation Format: Olivier Deas, Sophie Banis, Kathleen Flosseau, Lea Sinayen, Enora Le Ven, Jean-Gabriel Judde, Stefano Cairo. A preclinical platform of PDX-derived cell lines as a tool for pharmacological screening and functional studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3014.

Abstract SY17-02: Multiantigen vaccines for colon cancer prevention

Abstract Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the US when men and women are combined. While overall CRC incidence has declined over the years, there has been an increase in CRC diagnosis in young and middle-aged adults. The US Preventive Services Task Force has recently issued draft recommendations for CRC screening to begin at 45 years of age instead of the previously recommended age of 50 for asymptomatic healthy individuals, who are at average risk of CRC, i.e. without a family history of hereditary CRC syndromes such as Lynch syndrome and familial adenomatous polyposis, or with no prior diagnosis of CRC, adenomatous polyps, inflammatory bowel disease. While the evidence supports that CRC-screening and early detection confers a substantial benefit, additional CRC prevention strategies can greatly help reduce the cancer burden in the US and around the world. A number of previous studies have shown that the use of nonsteroidal anti-inflammatory drugs (NSAIDs) reduces the risk of cancers, including CRC. However, their extended use can be associated with serious side effects, including gastrointestinal bleeding. Safer and more efficacious preventive approaches are needed for durable long-term CRC prevention. The majority of newly diagnosed CRC are non-familial (sporadic) and non-hypermutated/microsatellite-stable (MSS). Compared to CRC with high microsatellite instability, MSS CRC and adenomas have significantly lower somatic mutation frequencies, thus lower neoantigen load. Furthermore, MSS CRC have generally lower levels of tumor-infiltrating lymphocytes (TILs), higher density of myeloid derived suppressor cells (MDSC), and downregulation of HLA molecules. These are characteristic of immunologically “cold” tumors, making it highly challenging to immunologically control tumor growth. If cancer vaccines can successfully prime the immune system, in particular before the development of invasive cancer, vaccine-induced adaptive antitumor immunity may render “cold” tumors “hot” and achieve a favorable tumor control. One of the key questions, however, is what tumor antigens can be targeted by vaccines if tumors have lower levels of neoantigens that are known to elicit robust antitumor immune responses. Another approach for cancer vaccine-mediated immune priming is to target tumor associated antigens (TAAs). Unlike tumor-specific neoantigens, TAAs are self-antigens that are overexpressed in tumors, but may also be expressed in normal cells at various levels. Therefore, it is highly critical to identify T cell epitopes that break tolerance and help elicit effective antitumor immunity. Clinically beneficial antitumor immunity is characterized by high-density infiltrates of effector CD8+ cytotoxic T lymphocytes and effector memory T cells and the low abundance of immunosuppressive elements (e.g. regulatory T cells, MDSC, and M2-polarized tumor-associated macrophages) in the tumor microenvironment. Disis and colleagues from University of Washington have previously established a systematic and stepwise approach to identify Th1-selective epitopes for efficacious cancer vaccines while eliminating Th2-epitopes. They have shown cancer vaccines targeting TAAs thus developed could elicit robust Th1 immune response associated with antitumor effects. The NCI PREVENT Cancer Preclinical Drug Development Program (PREVENT) is a peer-reviewed agent development program focused on preclinical development of innovative interventions, including cancer vaccines and drugs, for precision cancer prevention-interception towards clinical applications (https://prevention.cancer.gov/major-programs/prevent-cancer-preclinical). PREVENT and Disis team collaborated on the development of a multi-antigen multi-peptide colon cancer vaccine, named Colovac, for immunoprevention of CRC. It consists of highly immunogenic Th1-promoting epitopes from three TAAs that are selected through CRC genomic database and literature search. TAAs selected are overexpressed in CRC, known to play a role in CRC oncogenesis, and associated with poor disease outcomes. This presentation will cover the background of Colovac development, preclinical antitumor efficacy data on Colovac used alone or in combination with naproxen, characterization of immune correlates of protection, and current ongoing development efforts toward clinical trials. Citation Format: Shizuko Sei. Multiantigen vaccines for colon cancer prevention [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr SY17-02.