Phenotypic screening: the future of antibody discovery

True-T - Improving T-cell response quantification with holistic artificial intelligence based prediction in immunohistochemistry images

The immune response associated with oncogenesis and potential oncological ther- apeutic interventions has dominated the field of cancer research over the last decade. T-cell lymphocytes in the tumor microenvironment are a crucial aspect of cancer's adaptive immunity, and the quantification of T-cells in specific can- cer types has been suggested as a potential diagnostic aid. However, this is cur- rently not part of routine diagnostics. To address this challenge, we present a new method called True-T, which employs artificial intelligence-based techniques to quantify T-cells in colorectal cancer (CRC) using immunohistochemistry (IHC) images. True-T analyses the chromogenic tissue hybridization signal of three widely recognized T-cell markers (CD3, CD4, and CD8). Our method employs a pipeline consisting of three stages: T-cell segmentation, density estimation from the segmented mask, and prediction of individual five-year survival rates. In the first stage, we utilize the U-Net method, where a pre-trained ResNet-34 is em- ployed as an encoder to extract clinically relevant T-cell features. The segmenta- tion model is trained and evaluated individually, demonstrating its generalization in detecting the CD3, CD4, and CD8 biomarkers in IHC images. In the second stage, the density of T-cells is estimated using the predicted mask, which serves as a crucial indicator for patient survival statistics in the third stage. This ap- proach was developed and tested in 1041 patients from four reference diagnostic institutions, ensuring broad applicability. The clinical effectiveness of True-T is demonstrated in stages II-IV CRC by offering valuable prognostic information that surpasses previous quantitative gold standards, opening possibilities for po- tential clinical applications. Finally, to evaluate the robustness and broader ap- plicability of our approach without additional training, we assessed the universal accuracy of the CD3 component of the True-T algorithm across 13 distinct solid tumors.

Deep Mining of Complex Antibody Phage Pools

An important, and rapidly growing class of drugs are antibodies which can be discovered through phage display technology. In this technique, antibodies are typically first enriched through consecutive rounds of selection on a target antigen with amplification in bacteria between each selection round. Thereafter, a subset of random individual clones is analyzed for binding in a screening procedure. This results in discovery of the most abundant antibodies in the pool. However, there are multiple factors affecting the enrichment of antibodies during the selection resulting in a very complex output pool of antibodies. A few antibodies are present in many copies and others only in a few copies, where the most abundant antibodies are not necessarily the functionally best ones. In order to utilize the full potential of the output from a phage display selection, and enable discovery of low abundant, potentially functionally important clones, deep mining technologies are needed. In this chapter, two methods for deep mining of an antibody pool are described, protein depletion and antibody blocking. The methods can be applied both when the target is a single antigen and on complex antigen mixtures such as whole cells and tissues.

Entrectinib, a new multi-target inhibitor for cancer therapy

Clinical practice shows that when single-target drugs treat multi-factor diseases such as tumors, cardiovascular system and endocrine system diseases, it is often difficult to achieve good therapeutic effects, and even serious adverse reactions may occur. Multi-target drugs can simultaneously regulate multiple links of disease, improve efficacy, reduce adverse reactions, and improve drug resistance. They are ideal drugs for treating complex diseases, and therefore have become the main direction of drug development. At present, some multi-target drugs have been successfully used in many major diseases. Entrectinib is an oral small molecule inhibitor that targets TRK, ROS1, and ALK. It is used to treat locally advanced or metastatic solid tumors with NTRK1/2/3, ROS1 and ALK gene fusion mutations. It can pass through the blood-brain barrier and is the only TRK inhibitor clinically proven to be effective against primary and metastatic brain diseases. In 2019, entrectinib was approved by the FDA to treat adult patients with ROS1-positive metastatic non-small cell lung cancer. Case reports showed that continuous administration of entrectinib was effective and tolerable. In this review, we give a brief introduction to TKK, ROS1 and ALK, and on this basis, we give a detailed and comprehensive introduction to the mechanism of action, pharmacokinetics, pharmacodynamics, clinical efficacy, tolerability and drug interactions of entrectinib.

Induction of Genes Implicated in Stress Response and Autophagy by a Novel Quinolin-8-yl-nicotinamide QN523 in Pancreatic Cancer

Using a cytotoxicity-based phenotypic screen of a highly diverse library of 20,000 small-molecule compounds, we identified a quinolin-8-yl-nicotinamide, QN519, as a promising lead. QN519 represents a novel scaffold with drug-like properties, showing potent in vitro cytotoxicity in a panel of 12 cancer cell lines. Subsequently, lead optimization campaign generated compounds with IC50 values < 1 μM. An optimized compound, QN523, shows significant in vivo efficacy in a pancreatic cancer xenograft model. QN523 treatment significantly increased the expression of HSPA5, DDIT3, TRIB3, and ATF3 genes, suggesting activation of the stress response pathway. We also observed a significant increase in the expression of WIPI1, HERPUD1, GABARAPL1, and MAP1LC3B, implicating autophagy as a major mechanism of action. Due to the lack of effective treatments for pancreatic cancer, discovery of novel agents such as the QN series of compounds with unique mechanism of action has the potential to fulfill a clear unmet medical need.

Single B cell technologies for monoclonal antibody discovery

Monoclonal antibodies (mAbs) are often selected from antigen-specific single B cells derived from different hosts, which are notably short-lived in ex vivo culture conditions and hence, arduous to interrogate. The development of several new techniques and protocols has facilitated the isolation and retrieval of antibody-coding sequences of antigen-specific B cells by also leveraging miniaturization of reaction volumes. Alternatively, mAbs can be generated independently of antigen-specific B cells, comprising display technologies and, more recently, artificial intelligence-driven algorithms. Consequently, a considerable variety of techniques are used, raising the demand for better consolidation. In this review, we present and discuss the major techniques available to interrogate antigen-specific single B cells to isolate antigen-specific mAbs, including their main advantages and disadvantages.

Evaluation of Immuno-Rolling Circle Amplification for Multiplex Detection and Profiling of Antigen-Specific Antibody Isotypes

Antibody characterization is essential for understanding the immune system and development of diagnostics and therapeutics. Current technologies are mainly focusing on the detection of antigen-specific immunoglobulin G (IgG) using bulk singleplex measurements, which lack information on other isotypes and specificity of individual antibodies. Digital immunoassays based on nucleic acid amplification have demonstrated superior performance by allowing the detection of single molecules in a multiplex and sensitive manner. In this study, we demonstrate for the first time an immuno-rolling circle amplification (immuno-RCA) assay for the multiplex detection of three antigen-specific antibody isotypes (IgG, IgA, and IgM) and its integration with microengraving. To validate this approach, we used the autoimmune disease immune-mediated thrombotic thrombocytopenic purpura (iTTP) as the model disease with anti-ADAMTS13 autoantibodies as the diagnostic target molecules. To identify the anti-ADAMTS13 autoantibody isotypes, we designed a pool of three unique antibody-oligonucleotide conjugates for identification and subsequent amplification and visualization via RCA. To validate this approach, we first confirmed an assay specificity of >88% and a low limit of detection of 0.3 ng/mL in the spiked buffer. Subsequently, we performed a dilution series of an iTTP plasma sample for the multiplex detection of the three isotypes with higher sensitivity compared to an enzyme-linked immunosorbent assay. Finally, we demonstrated single-cell analysis of human B cells and hybridoma cells for the detection of secreted antibodies using microengraving and achieved a detection of 23.3 pg/mL secreted antibodies per hour. This approach could help to improve the understanding of antibody isotype distributions and their roles in various diseases.

Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing

Therapeutic antibodies are transforming the treatment of cancer and autoimmune diseases. Today, a key challenge is finding antibodies against new targets. Phenotypic discovery promises to achieve this by enabling discovery of antibodies with therapeutic potential without specifying the molecular target a priori. Yet, deconvoluting the targets of phenotypically discovered antibodies remains a bottleneck; efficient deconvolution methods are needed for phenotypic discovery to reach its full potential. Here, we report a comprehensive investigation of a target deconvolution approach based on pooled CRISPR/Cas9. Applying this approach within three real-world phenotypic discovery programs, we rapidly deconvolute the targets of 38 of 39 test antibodies (97%), a success rate far higher than with existing approaches. Moreover, the approach scales well, requires much less work, and robustly identifies antibodies against the major histocompatibility complex. Our data establish CRISPR/Cas9 as a highly efficient target deconvolution approach, with immediate implications for the development of antibody-based drugs.

Efficient deconvolution of antibody targets is needed for phenotype-based discovery. Here, the authors investigate a deconvolution approach based on pooled CRISPR Cas9 to achieve 97% deconvolution success rate.

Actinomycin D inhibits the expression of the cystine/glutamate transporter xCT via attenuation of CD133 synthesis in CD133+ HCC

Liver cancer is one of the most frequently occurring types of cancer with high mortality rate. Hepatocellular carcinoma (HCC) frequently metastasizes to lung, portal vein, and portal lymph nodes and most HCCs show strong resistance to conventional anticancer drugs. Cancer stem cells (CSCs) are considered to be responsible for resistance to therapies. Hence, recent advancements in the use of liver cancer stem cells (LCSCs) are rapidly gaining recognition as an efficient and organized means for developing antitumor agents. We aimed to use a non-target-based high-throughput screening (HTS) approach to specifically target α-fetoprotein (AFP)⁺/cluster of differentiation (CD)133⁺ HCC present in mixed populations of HCC cells and hepatocytes. Herein, we identified actinomycin D (ActD) as a potential antitumor agent that significantly inhibits activity of LCSCs without affecting the co-cultured hepatocytes. To determine the mechanism of ActD-induced tumor-specificity in LCSC, we applied various cell-based assay models in vitro. In fact, ActD significantly increased reactive oxygen species (ROS) accumulation and DNA damage in Huh7 HCC cells, but not in Fa2N-4 cells, immortalized hepatocytes. Treatment of spheroid-forming LCSCs with ActD effectively decreased spheroid formation and the CD133⁺ HCC cell population. Importantly, these ActD-mediated effects are a result of inhibition of cystine/glutamate transporter xCT expression, via attenuation of CD133 synthesis. These results indicate that ActD suppresses stemness and malignant properties in HCC cells through destabilization of xCT, by inhibition of CD133 expression in LCSCs. The effects of ActD on LCSCs provide novel therapeutic strategies for targeting cancer stem-like cells in liver cancer.

Identification of radiation-induced EndMT inhibitors through cell-based phenomic screening

Radiation‐induced pulmonary fibrosis (RIPF) triggers physiological abnormalities. Endothelial‐to‐mesenchymal transition (EndMT) is the phenotypic conversion of endothelial cells to fibroblast‐like cells and is involved in RIPF. In this study, we established a phenomic screening platform to measure radiation‐induced stress fibers and optimized the conditions for high‐throughput screening using human umbilical vein endothelial cells (HUVECs) to develop compounds targeting RIPF. The results of screening indicated that CHIR‐99021 reduced radiation‐induced fibrosis, as evidenced by an enlargement of cell size and increases in actin stress fibers and α‐smooth muscle actin expression. These effects were elicited without inducing serious toxicity in HUVECs, and the cytotoxic effect of ionizing radiation (IR) in nonsmall cell lung cancer was also enhanced. These results demonstrate that CHIR‐99021 enhanced the effects of IR therapy by suppressing radiation‐induced EndMT in lung cancer.

Production and characterization of monoclonal antibody against a triple negative breast cancer cell line

Breast cancer is the most prevalent malignancy among women around the world such that more than 1,400,000 new cases are being diagnosed each year. Despite immense studies over many years on diagnosis and treatment of breast cancer, about 30% of treated patients will relapse and require subsequent therapy. By development of hybridoma technology, murine monoclonal antibodies (MAbs) against several human tumor-associated antigens have been produced and characterized in many laboratories. The purpose of these studies is to generate effective monoclonal antibodies that could be useful in tumor diagnosis and therapy. In this study, splenic lymphocytes of immunized BALB/c mouse with a new established breast cancer cell line (Pari-ICR cell line, established in Shiraz Institute for Cancer Research) were fused with the mouse myeloma cell line SP2/0 in the presence of polyethylene glycol. We generated a panel of monoclonal antibodies against the newly established cell line. The hybrid cultures were screened by flow cytometry. Hybridomas that produced antibody to surface antigens of immunizing cell line but not to Human Gingival Fibroblasts, adipose stem cells, and leucocytes isolated from peripheral blood were selected and cloned by limiting dilution method. The 1E3 clone (IgG2a type) that displayed clonal stability was further analyzed for specificity by flow cytometry. MAb 1E3 showed weak to strong reactivity to other cell lines compared with Pari-ICR cell line. Antigen identification was performed by a workflow consisting of immunoaffinity purification, SDS-PAGE, Western blotting, and mass spectrometry analysis. The target of 1E3 mAb was identified as NCAM1. In conclusion, using the antibody-based strategy we identified NCAM1 as a potential therapeutic target and biomarker for breast cancer.

A novel inhibitory anti-invasive MAb isolated using phenotypic screening highlights AnxA6 as a functionally relevant target protein in pancreatic cancer

Background:

Discovery and validation of new antibody tractable targets is critical for the development of new antibody therapeutics to address unmet needs in oncology.

Methods:

A highly invasive clonal variant of the MDA-MB-435S cell line was used to generate monoclonal antibodies (MAbs), which were screened for anti-invasive activity against aggressive cancer cells in vitro. The molecular target of selected inhibitory MAb 9E1 was identified using immunoprecipitation/liquid chromatography-tandem mass spectrometry. The potential anti-tumour effects of MAb 9E1 were investigated in vitro together with immunohistochemical analysis of the 9E1 target antigen in normal and cancer tissues.

Results:

MAb 9E1 significantly decreases invasion in pancreatic, lung squamous and breast cancer cells and silencing of its target antigen, which was revealed as AnxA6, leads to markedly reduced invasive capacity of pancreatic and lung squamous cancer in vitro. IHC using MAb 9E1 revealed that AnxA6 exhibits a high prevalence of membrane immunoreactivity across aggressive tumour types with restricted expression observed in the majority of normal tissues. In pancreatic ductal adenocarcinoma, high AnxA6 IHC score correlated with the presence of tumour budding at the invasive front of tumours (P=0.082), the presence of perineural invasion (P= <0.0001) and showed a weak correlation with reduced survival (P=0.2242).

Conclusions:

This study highlights the use of phenotypic hybridoma screening as an effective strategy to select a novel function-blocking MAb, 9E1 with anti-cancer activity in vitro. Moreover, through characterisation of the 9E1 target antigen, AnxA6, our findings support further investigation of AnxA6 as a potential candidate target for antibody-mediated inhibition of pancreatic cancer.

Opportunities and challenges in phenotypic drug discovery: an industry perspective

Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.

In vivo phenotypic screening: clinical proof of concept for a drug repositioning approach

In vivo phenotypic screening and drug repositioning are strategies developed as alternatives to underperforming hypothesis-driven molecular target based drug discovery efforts. This article reviews examples of drugs identified by phenotypic observations and describes the use of the theraTRACE^®in vivo screening platform for finding and developing new indications for discontinued clinical compounds. Clinical proof-of-concept for the platform is exemplified by MLR-1023, a repositioned compound that has recently shown significant clinical efficacy in Type 2 diabetes patients. These findings validate an in vivo screening approach for drug development and underscore the importance of alternatives to target and mechanism based strategies that have failed to produce adequate numbers of new medicines.

Phenotypic Assessment and the Discovery of Topiramate

The role of phenotypic assessment in drug discovery is discussed, along with the discovery and development of TOPAMAX (topiramate), a billion-dollar molecule for the treatment of epilepsy and migraine.

Generation of a monoclonal antibody recognizing the CEACAM glycan structure and inhibiting adhesion using cancer tissue-originated spheroid as an antigen

Spheroids cultured directly from tumours can better reflect in vivo tumour characteristics than two-dimensional monolayer culture or three-dimensional culture of established cell lines. In this study, we generated antibodies by directly immunizing mice with primary-cultured living spheroids from human colorectal cancer. We performed phenotypic screening via recognition of the surface of the spheroids and inhibition of their adhesion to extracellular matrices to identify a monoclonal antibody, clone 5G2. The antibody inhibited cell migration in two-dimensional culture and promoted cell detachment. Western blotting and immunohistochemistry detected the 5G2 signal in many colorectal cancer spheroids, as well as patient tumours, but failed to detect in various cell lines examined. We found that 5G2 recognized the Le^a and Le^c on N-glycan, and their major carrier proteins were CEACAM5 and CEACAM6. Pre-incubation of the spheroids with 5G2 impaired translocation of integrin β4 from the lateral membrane to the contact interface between the extracellular matrix when embedded in it. As we successfully obtained a functional antibody, which antigen was glycan structures and lost in cell lines, cancer tissue-originated spheroids can be a useful antigen for generating novel anti-cancer antibodies.