Combinatorial Technology Research Articles

The giant leap to humankind

Penny (2009) urges that biologists stress more strongly the biological continuity between great apes and humans. Besides stressing genetic similarities, he suggests that great apes also share psychological capacities, including language and tool use. I argue that he underestimates the psychological differences. There is no evidence that great apes have anything approaching human language, or human technological capacity. A main ingredient of human cognition is recursion, which lifted communication to true combinatorial language and simple tool use to advanced combinatorial technology. Recursion may also explain the combinatorial structure of human memory, imagination, and theory of mind. Part of the key, as Penny recognises, may lie in the trajectory of human brain growth, but there is still much to understand in how micro-tweaking of the genome achieved such dramatic differences between ape and human.

Discovery of Peptidic Ligands against the SARS-CoV-2 Spike Protein and Their Use in the Development of a Highly Sensitive Personal Use Colorimetric COVID-19 Biosensor.

In addition to efficacious vaccines and antiviral therapeutics, reliable and flexible in-home personal use diagnostics for the detection of viral antigens are needed for effective control of the COVID-19 pandemic. Despite the approval of several PCR-based and affinity-based in-home COVID-19 testing kits, many of them suffer from problems such as a high false-negative rate, long waiting time, and short storage period. Using the enabling one-bead-one-compound (OBOC) combinatorial technology, several peptidic ligands with a nanomolar binding affinity toward the SARS-CoV-2 spike protein (S-protein) were successfully discovered. Taking advantage of the high surface area of porous nanofibers, immobilization of these ligands on nanofibrous membranes allows the development of personal use sensors that can achieve low nanomolar sensitivity in the detection of the S-protein in saliva. This simple biosensor employing naked-eye reading exhibits detection sensitivity comparable to some of the current FDA-approved home detection kits. Furthermore, the ligand used in the biosensor was found to detect the S-protein derived from both the original strain and the Delta variant. The workflow reported here may enable us to rapidly respond to the development of home-based biosensors against future viral outbreaks.

Peptide Designs for Use in Caries Management: A Systematic Review

The objective of this study was to review the design methods that have been used to create peptides for use in caries management. Two independent researchers systematically reviewed many in vitro studies in which peptides were designed for use in caries management. They assessed the risk of bias in the included studies. This review identified 3592 publications, of which 62 were selected. Forty-seven studies reported 57 antimicrobial peptides. Among them, 31 studies (66%, 31/47) used the template-based design method; 9 studies (19%, 9/47) used the conjugation method; and 7 studies (15%, 7/47) used other methods, such as the synthetic combinatorial technology method, the de novo design method and cyclisation. Ten studies reported mineralising peptides. Seven of these (70%, 7/10) used the template-based design method, two (20%, 2/10) used the de novo design method, and one study (10%, 1/10) used the conjugation method. In addition, five studies developed their own peptides with antimicrobial and mineralising properties. These studies used the conjugation method. Our assessment for the risk of bias in the 62 reviewed studies showed that 44 publications (71%, 44/62) had a medium risk and that 3 publications had a low risk (5%, 3/62). The two most common methods for developing peptides for use in caries management that were used in these studies were the template-based design method and the conjugation method.

Large-scale group classification decision making method and its application with trust–interest dual factors in social network

The wide application of computer technology promotes the development of large-scale group decision making. However, with the increase of the number of people involved in decision-making, the complexity of group decision making process is also expanded. In this paper, we propose a large-scale group classification decision making method with trust–interest dual factors in social network, which reduce the dimension of large group based on the deep mining of social network between decision makers, and aggregate the fuzzy decision information in the form of cloud model to get the decision results. Specifically, we define the elastic modularity and the utility function to describe the trust-characteristic and interest-characteristic of subgroups, divide the experts into high-trust communities and high-interest coalitions with the corresponding algorithm respectively. We set the preference of expert in subgroup as cloud droplet, and the preference of the subgroup is gathered in the form of cloud model. The merged subgroup of isolated decision maker is determined according to the preference membership matrix between the preference of isolated decision maker and each subgroup. The feasibility of the method is verified by the combinatorial technology selection for ultra-low emission transformation of large coal-fired power plants.

(Invited, Digital Presentation) The Challenge of Automated High-Throughput Experiments on a Variety of Powder Libraries

In recent years, "Materials Genome Initiative (MGI)", "Materials Informatics (MI)", and "Process Informatics (PI)" research have attracted much attention as keywords for high-throughput materials discovery. Much of the MI and PI research that has been published so far emphasizes data mining, statistics, machine learning, and predictive analytics. The MGI proposed by the US government in 2011 indicated that material innovation requires "experimental tools" in addition to "computational tools" and "digital data. "Experimental tools" means the creation of big data using automated high-throughput synthesis, evaluation and analysis systems, but there are not many examples of this development. In order to promote highly accurate materials discovery, a three-way relationship is important. And in order to improve the overall speed of exploration, all processes need to be accelerated. In the production of ceramic powder, which is also the synthesis process of dielectrics, the crystalline phase and grain size vary depending on the raw material manufacturer, purity, sintering atmosphere, sintering temperature, and other conditions. These have a great impact on the physical properties. It is important to create a data set that includes not only composition, phase identification results, lattice parameters, and physical property data, but also detailed experimental process conditions. If the data can be collected in a unified high-throughput experimental environment, it will greatly contribute to data interpolation in MI and PI research. We expect that combining the data obtained from high-throughput automated experiments with the data-driven research found in MI and PI will accelerate more accurate research. To achieve this goal, we are continuing to work on the development of combinatorial technology, a high-throughput synthesis, evaluation, and analysis technique for multi-component ceramic powders. For the preparation of powder samples consisting of a vast number of combinations, we have developed two methods based on wet processes.1)2) These devices allow us to synthesize 100 samples per day, reducing the amount of raw material used per sample to about 1/1000. This has the advantage of not only increasing the high-throughput but also reducing the excessive use of raw materials. After the library is created, the crystal structure needs to be evaluated. In recent years, the high-speed detectors of experimental X-ray diffractometers have made it possible to obtain X-ray diffraction patterns in a short time. In 2014, Gregoire et al. developed a technique to simultaneously collect synchrotron XRD and XRF data for a group of multi-component thin film samples. They developed a technique to collect the data and showed that they could collect at least 5000 patterns per day in less than 18 seconds per sample3). Furthermore, Kusune et al. matched the synchrotron thin-film XRD patterns with the Inorganic Crystal Structure Database (ICSD) using an on-the-fly method, and greatly improved the classification accuracy of structural phases overlapping in the three-component reaction diagram.4) The use of XRD patterns for informatics is often discussed between phase information, lattice constants and physical properties, but crystallographic information such as fractional coordinates should be added to the data set if genomic machine learning is to be promoted. In order to obtain the diffraction intensities for high-throughput synthesized samples, which are necessary for structural refinement, collaboration with synchrotron radiation is required. We propose a high-throughput crystallographic information collection process combined with efficient measurement tools and an automated structure refinement program.5,6) 1) K. Fujimoto et al., Measurement Science and Technology 16 41-45 (2005).2) K. Fujimoto et al., Solid State Ionics 177 2639-2642 (2006).3) J. M. Gregoire et al., Journal of Synchrotron Radiation, 21(6), 1262-1268 (2014).4) Aaron Gilad Kusne et al., Scientific Report, 4: 6367 (2014).5) A. Aimi et al., ACS Combinatorial Science 22(1) 35-41 (2020).6) K. Fujimoto et al., ACS Combinatorial Science 22(12) 734-737 (2020).

The Use of Plant Fibers for Oligosaccharide Production with Libraries Constructed by Combinatorial Enzyme Technology

: Combinatorial chemistry involves the chemical or biological synthesis of libraries of the diverse structural population of a template molecule and the screening for the variants expressing desirable target properties. The approach has been a focus of research activity in modern drug discovery and biotechnology for accelerating the discovery and development of novel therapeutic and bioactive compounds. This review describes the application of combinatorial chemistry in enzyme technology as a novel technique and invention developed in our laboratory to construct oligosaccharide libraries in the conversion of plant fibers. The theory, mechanism, development, and application of this combinatorial enzyme approach are presented for the first time. The potential food and non-food uses of oligosaccharides are described. Citrus pectin and wheat insoluble fiber have been used as substrates for combinatorial enzyme reactions. Generation of libraries of structural variants of pectic oligosaccharides (oligoGalA) and feruloyl oligosaccharides (FOS) demonstrates the feasibility and usefulness of the technique in the transformation of plant biomass to value- added products.

Combinatorial technology revitalized by DNA-encoding.

Combinatorial chemistry invented nearly 40 years ago was welcomed with enthusiasm in the drug research community. The method offered access to a practically unlimited number of new compounds. The new compounds however are mixtures, and methods had to be developed for the identification of the bioactive components. This was one of the reasons why the method could not providethe expected cornucopia of new drugs. Among the different screening methods, two approaches seem to offer the best results. One of them is based on the intrinsic property of the combinatorial split and pool solid‐phase synthesis: One compound forms on each bead of the solid support. Different methods have been developed to encode the beads and identify the structure of compounds formed on them. The most important method applies DNA oligomers for encoding. As a second approach in screening, DNA‐encoded combinatorial libraries are synthesized omitting the solid support and the mixtures are screened in solution using affinity binding methods. Libraries containing billions and even trillions of components are synthesized and successfully tested, which led to the identification of a significant number of new leads.

Kerr effect microscope combined with a pulse magnet to observe high-entropy alloys fabricated using combinatorial technology

Kerr effect microscope combined with a pulse magnet to observe high-entropy alloys fabricated using combinatorial technology

Fabrication of NiAl intermetallic alloy integrated materials chips with continuous one-dimensional composition gradients by plasma spray deposition and laser remelting

Integrated materials chips (IMCs) contain a multitude of discrete materials with varying compositions on a single substrate to enable the rapid screening of material properties, and therefore offer the potential for accelerating the speed of materials research and development. The present work proposes a combinatorial technology based on conventional plasma spray (PS) deposition and laser remelting (LR), and employs the proposed technology to develop Ni-Al intermetallic alloy IMCs with a continuous composition gradient yielding various homogeneous compositions with unique microstructures and microhardness values along the length. The experimental results demonstrate that the proposed technology can effectively promote the discovery of relationships between the composition, microstructure, and the inherent properties of materials.

Developing an Injectable Nanofibrous Extracellular Matrix Hydrogel With an Integrin αvβ3 Ligand to Improve Endothelial Cell Survival, Engraftment and Vascularization.

Endothelial cell (EC) transplantation via injectable collagen hydrogel has received much attention as a potential treatment for various vascular diseases. However, the therapeutic effect of transplanted ECs is limited by their poor viability, which partially occurs as a result of cellular apoptosis triggered by the insufficient cell-extracellular matrix (ECM) engagement. Integrin binding to the ECM is crucial for cell anchorage to the surrounding matrix, cell spreading and migration, and further activation of intracellular signaling pathways. Although collagen contains several different types of integrin binding sites, it still lacks sufficient specific binding sites for ECs. Previously, using one-bead one-compound (OBOC) combinatorial technology, we identified LXW7, an integrin αvβ3 ligand, which possessed a strong binding affinity to and enhanced functionality of ECs. In this study, to improve the EC-matrix interaction, we developed an approach to molecularly conjugate LXW7 to the collagen backbone, via a collagen binding peptide SILY, in order to increase EC specific integrin binding sites on the collagen hydrogel. Results showed that in the in vitro 2-dimensional (2D) culture model, the LXW7-treated collagen surface significantly improved EC attachment and survival and decreased caspase 3 activity in an ischemic-mimicking environment. In the in vitro 3-dimensional (3D) culture model, LXW7-modified collagen hydrogel significantly improved EC spreading, proliferation, and survival. In a mouse subcutaneous implantation model, LXW7-modified collagen hydrogel improved the engraftment of transplanted ECs and supported ECs to form vascular network structures. Therefore, LXW7-functionalized collagen hydrogel has shown promising potential to improve vascularization in tissue regeneration and may be used as a novel tool for EC delivery and the treatment of vascular diseases.

Extracellular Matrix Mimicking Nanofibrous Scaffolds Modified With Mesenchymal Stem Cell-Derived Extracellular Vesicles for Improved Vascularization.

The network structure and biological components of natural extracellular matrix (ECM) are indispensable for promoting tissue regeneration. Electrospun nanofibrous scaffolds have been widely used in regenerative medicine to provide structural support for cell growth and tissue regeneration due to their natural ECM mimicking architecture, however, they lack biological functions. Extracellular vesicles (EVs) are potent vehicles of intercellular communication due to their ability to transfer RNAs, proteins, and lipids, thereby mediating significant biological functions in different biological systems. Matrix-bound nanovesicles (MBVs) are identified as an integral and functional component of ECM bioscaffolds mediating significant regenerative functions. Therefore, to engineer EVs modified electrospun scaffolds, mimicking the structure of the natural EV-ECM complex and the physiological interactions between the ECM and EVs, will be attractive and promising in tissue regeneration. Previously, using one-bead one-compound (OBOC) combinatorial technology, we identified LLP2A, an integrin α4β1 ligand, which had a strong binding to human placenta-derived mesenchymal stem cells (PMSCs). In this study, we isolated PMSCs derived EVs (PMSC-EVs) and demonstrated they expressed integrin α4β1 and could improve endothelial cell (EC) migration and vascular sprouting in an ex vivo rat aortic ring assay. LLP2A treated culture surface significantly improved PMSC-EV attachment, and the PMSC-EV treated culture surface significantly enhanced the expression of angiogenic genes and suppressed apoptotic activity. We then developed an approach to enable “Click chemistry” to immobilize LLP2A onto the surface of electrospun scaffolds as a linker to immobilize PMSC-EVs onto the scaffold. The PMSC-EV modified electrospun scaffolds significantly promoted EC survival and angiogenic gene expression, such as KDR and TIE2, and suppressed the expression of apoptotic markers, such as caspase 9 and caspase 3. Thus, PMSC-EVs hold promising potential to functionalize biomaterial constructs and improve the vascularization and regenerative potential. The EVs modified biomaterial scaffolds can be widely used for different tissue engineering applications.

Abstract PR08: Leveraging single-cell epigenomics to uncover regulatory programs in lung adenocarcinoma

Abstract A hallmark of cancer development is the loss of cellular identity due to the dysregulation of regulatory networks that maintain functional, differentiated states. Chromatin state has been linked to this control of cellular identity and developmental processes; however, the mechanisms by which these regulatory landscapes are disrupted during cancer progression are not well understood. To this end, we leveraged an optimized single-cell ATAC-sequencing (scATAC-seq) strategy using a combinatorial indexing-based technology to assess chromatin state changes that occur in a mouse model of lung adenocarcinoma (LUAD). We utilized a well-established LUAD mouse model in which mice conditionally express the KrasG12D mutation and lose p53 expression in alveolar type II cells following Cre-mediated recombination, termed the KP model. In this model, KP tumors progress from early-stage hyperplasias to metastatic, advanced adenocarcinomas without acquiring additional somatic mutations, suggesting that these phenotypic transitions may be driven in part by epigenetic mechanisms. Using scATAC-seq, we profiled 16,044 normal lung, primary KP tumor, and metastatic cells to assess chromatin state changes across LUAD progression. We found that LUAD tumor evolution was characterized by a heterogeneous epigenomic continuum that was associated with loss of alveolar identity and progression to metastasis. Interestingly, we identified a reproducible metastatic state that was homogeneous, suggesting that cancer cells funnel towards a stable epigenetic state. In addition, we utilized novel computational tools to assess combinatorial transcription factor (TF)-driven programs that delineate stages of cancer progression in the KP model. From these analyses, we identified a clear transition point that corresponded to progressive gain of RUNX2 transcription factor activity. Using CRISPR activation and knockout strategies, we found that RUNX2 regulated the chromatin accessibility of several regulatory programs involved in extracellular matrix remodeling, suggesting that RUNX2 signaling is a critical event in LUAD progression and metastasis. In addition, gene signatures derived from this RUNX-activated state were highly predictive of survival in human LUAD. Together, these results demonstrated the power of single-cell epigenomics to identify TF-driven regulatory programs as key biomarkers of tumor progression. This abstract is also being presented as Poster A40. Citation Format: Lindsay M. LaFave, Vinay Kartha, Sai Ma, Kevin Meli, Isabella Del Priore, Caleb Lareau, Venkat Sanker, Santiago Naranjo, Peter Westcott, Zachary Chiang, Alison Brack, Travis Law, Aviv Regev, Jason D Buenrostro, Tyler Jacks. Leveraging single-cell epigenomics to uncover regulatory programs in lung adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR08.

Implementation of digital manufacturing technologies: Antecedents and consequences

The use of digital manufacturing technologies (DMTs) is changing the face of the manufacturing landscape and enhancing the competitiveness of firms. However, its implementation is still a relatively unexplored phenomenon and demands attention. The purpose of this study is to determine the role played by technological context, organizational context, and environmental context of firms in the implementation of the DMTs. A hypothesized model is proposed and tested using survey-based data from the International Manufacturing Strategy Survey VI comprising 931 firms across developed and developing countries. The proposed research model gains support from the technology–organization–environment framework and the combinatorial technology evolution theory, which together provide a holistic understanding of the technology implementation process in terms of its enablers and performance outcomes. We find that although the organizational context and environmental context impact DMTs' implementation, these impacts are mediated through the technological context of the firm. Moreover, the implementation of these technologies has a significant impact on firm performance in terms of flexibility, design, delivery, and quality performance. Contributing to the empirical research gap in the domain of DMTs’ implementation, this study also generates insights for practitioners about the complementarity of the technological, organizational, and environmental factors that together enable the implementation of DMTs and enhance firm performance.

Modification of phage display technique for improved screening of high-affinity binding peptides

The phage display technique is a combinatorial technology in which random peptides are displayed on the surface of the phage; it is widely used to identify high-affinity peptides that bind to a target protein. However, this technique presents several problems due to non-specific binding of the phages and steric hindrance caused by blocking agents. To overcome these problems, we tested two modified methods and compared their screening performance with that of the conventional method. We used poly-His-tagged human epidermal growth factor receptor 2 (HER2) as a target protein and silica-coated magnetic particles (MPs) with an immobilized nickel-nitrilotriacetic acid ligand as a solid matrix. Modified method #1 (#M1) included two negative selection steps against a blocking agent (bovine serum albumin) and nude Ni-NTA MPs, after the positive selection step using immobilized HER2 on MPs in the absence of BSA. Modified method #2 (#M2) allowed the binding of phages and HER2 in solution prior to immobilizing HER2 on the MP surface. The negative selection procedure was the same between them. The binding affinity of the phages screened by #M1 and #M2 was evaluated by phage ELISA. Two phages from #M2 (#M2-4 and 5) showed the highest binding, and between them #M2-5 was selected for affinity maturation by inserting a hairpin-structured peptide between the two #M2-5 peptides. SPR study showed the HER2-binding affinity was indeed improved by ca. 2000-fold to become comparable with that of the intact antibody (trastuzumab). The modified biopanning methods combined with the dimerization maturation can be an effective way to develop antibody-mimicking peptides for affinity binding.

Abstract PR08: Combinatorial CRISPR-Cas9 reveals many cancer synthetic lethal interactions are private to cell type

Abstract We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbation coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with multiplexed guide RNAs in two cell lines, testing 23,652 combinations. Numerous therapeutically relevant interactions were identified, most private to one cell line. These patterns replicated with combinatorial drugs at 80% precision. Thus, cellular context will be critical to synthetic-lethal therapies. Here, we combined multiplex targeting with array-based oligonucleotide synthesis to create dual-gRNA libraries covering up to 105 defined gene pairs. We conducted genetic interaction screens by transducing the dual-gRNA lentiviral library into a population of cells stably expressing Cas9, maintaining these cells in exponential growth over the course of four weeks, then sampling the relative changes in gRNAs at days 3, 14, 21 and 28 post-transduction. To robustly quantify gene fitness and genetic interactions, we developed a computational analysis framework that integrates all samples across the multiple days of the experiment. Using this method we evaluated all pairwise gene knockout combinations among a panel of 73 genes divided between tumor-suppressor genes (TSG) and cancer-relevant drug targets (DT), a subset of which were also verified oncogenes. Experiments were performed in two cancer cell lines: HeLa, a cervical cancer cell line driven by Human Papilloma Virus (HPV); and A549, a lung cancer cell line driven by KRAS G12S mutation. With nine gRNA pairs per combination, the library comprised 23,652 double gene knockout constructs and 657 single gene constructs; testing two replicates in each cell line yielded a total of 94,608 unique tests of interaction. Measurements of gene fitness (fg) were well correlated between biological replicates in the same cell line; Pearson r=0.96, p = 4.2×(10)^(-40), as were the π scores for significant genetic interactions; r = 0.75 p = 7.7×(10)^(-12). Moreover, we observed a significant correlation between the number of genetic interactions identified for a gene and its single gene fitness (HeLa: r = 0.77, p = 3.4×(10)^(-10); A549: r = 0.45, p = 0.0018), suggesting that network hubs may have increased functional importance to cancer cells relative to genes with fewer interactions; such a relationship has been previously observed in model organisms but not before in humans5. Interestingly, we found that the genetic interactions identified from these data were remarkably different between cell lines. A total of 97 synthetic-lethal (negative) genetic interactions were identified in either HeLa or A549 cells. Of these, only 12 were identified in both cell lines, while the remaining 85 interactions were private to a cell line (HeLa: 40 of 52, A549: 45 of 57). We next sought to validate these findings, and in particular the discrepancies across cell lines. We selected ten pairs of DT genes for which a synthetic-lethal genetic interaction had been identified in only one of the two cell lines. Rather than simply reproduce the dual CRISPR knockout experiment (gene-gene interaction), our goal was to examine the viability of cells exposed to drugs inhibiting the corresponding gene products (drug-drug interaction). In total, drug-drug assays validated eight of ten interactions when tested in the cell line for which the interaction had been first observed by dual CRISPR (80% precision or positive predictive value). In contrast, when the same ten gene pairs were tested in the other cell line that had not been implicated by dual CRISPR knockout, only two showed a negative genetic interaction by drug-drug assay (80% negative predictive value). Thus, the differences in genetic interaction across cell lines seen by systematic CRISPR could be largely reproduced as drug-drug interactions in small-scale assays. In summary, we have introduced a combinatorial CRISPR-Cas9 genetic interaction mapping technology that successfully identifies many therapeutically-relevant genetic interactions in cancer and shows the great importance of cellular context on the architecture of the genetic interaction network. Recognizing that there will be great diversity in genetic interaction between different tumors it will be important to perform these studies across a large number of samples, which is enabled by the high-throughput method we have developed. Citation Format: John Paul Shen, Dongxin Zhao, Roman Sasik, Jens Luebeck, Amanda Birmingham, Ana Bojorquez-Gomez, Jason Kreisberg, Trey Ideker, Prashant Mali. Combinatorial CRISPR-Cas9 reveals many cancer synthetic lethal interactions are private to cell type [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr PR08.

Abstract 3039: Combinatorial CRISPR-Cas9 gene knockout to enable genetic interaction mapping in human cells

Abstract Genetic interactions, in particular negative or ‘synthetic-lethal’ interactions for which simultaneous disruption of two genes causes cell killing, have implications for therapeutic development. The feasibility of this approach has been demonstrated with the recent approval of the drug olaparib, an inhibitor of PARP1, specifically for tumors with loss-of-function mutations in BRCA1/2. However, beyond olaparib, further applications of synthetic-lethal cancer therapy have been limited by poor understanding of the important genetic interactions in a cancer cell, and how these vary from one cancer type to another or from patient to patient. To enable systematic mapping of these genetic interaction networks, we developed a CRISPR-Cas9 screening methodology for knocking out single and pairs of genes in high-throughput. Here, we combined multiplex targeting with array-based oligonucleotide synthesis to create dual-gRNA libraries covering up to 10^5 defined gene pairs. In these libraries, each construct bears two gRNAs, with each gRNA designed to target either a gene or a scrambled non-targeting sequence absent from the genome. We conducted genetic interaction screens by transducing the dual-gRNA lentiviral library into a population of cells stably expressing Cas9, maintaining these cells in exponential growth over the course of four weeks, then sampling the relative changes in gRNAs at days 3, 14, 21 and 28 post-transduction. To robustly quantify gene fitness and genetic interactions, we developed a computational analysis framework that integrates all samples across the multiple days of the experiment. Using this method we evaluated all pairwise gene knockout combinations among a panel of 73 genes divided between tumor-suppressor genes (TSG) and cancer-relevant drug targets (DT); including negative controls this amounted to a total of 23,652 combinations. Experiments were performed in three cancer cell lines: HeLa, A549 and 293T. In total 162 therapeutically relevant interactions were identified, of which 146 (90.1%) were private to one cell line. None of the interactions were observed in all three cell lines. These patterns replicated in low throughput assays with combinatorial drugs at 80% precision. In summary, we have introduced a combinatorial CRISPR-Cas9 genetic interaction mapping technology that successfully identifies many therapeutically-relevant genetic interactions in cancer and shows the great importance of cellular context on the architecture of the genetic interaction network. Recognizing that there will be great diversity in genetic interaction between different tumors it will be important to perform future studies across a large number of samples, which is enabled by the high-throughput method we have developed. Citation Format: John Paul Shen, Dongxin Zhao, Roman Sasik, Jens Luebeck, Ana Bojorquez-Gomez, Katherine Licon, Trey Ideker, Prashant Mali. Combinatorial CRISPR-Cas9 gene knockout to enable genetic interaction mapping in human cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3039. doi:10.1158/1538-7445.AM2017-3039

Highlights of This Issue

Death receptor present on the plasma membrane of cancer cells can be activated by chemical compounds to induce cell apoptosis. Shih and his colleagues developed the one-bead two-compound (OB2C) ultra-high throughput screening method for the discovery of synthetic death ligands against cancer cells. They discovered LLS2, a novel galectin-1 inhibitor that can kill a variety of cancer cells. They also found LLS2 exhibits synergistic activity with paclitaxel in vitro and in vivo. These results indicated that OB2C combinatorial technology is a highly efficient drug-screening platform and LLS2 discovered through this method can be further optimized for anti-cancer drug development.Indole-based tambjamine analogues is a new group of potent anion transporters. In this study, Manuel-Manresa, Korrodi-Gregório and colleagues demonstrated the mechanism of these novel natural-derived tambjamine analogues in lung cancer cells. Treatment of Indole-based tambjamine analogues resulted in dysregulation of BCL2 and BIRC5/surviving genes which suggested the apoptotic pathway induction demonstrated by pro-apoptotic markers and by a decrease towards the pro-survival members of the Bcl-2 proteins. This apoptosis might be activated by the p38 MAPK through ROS cellular stress induction. Significant therapeutic effect of these compounds was observed in subcutaneous and orthotopic lung cancer mice models indicating a good potential for clinical development.Tissue biopsy analysis of genomic alterations is the standard of care for molecular profiling. Circulating tumor DNA (ctDNA) biopsies detect alterations in blood, non-invasively. Chae, Davis and colleagues report high overall concordance in paired tissue and ctDNA biopsies, but relatively low concordance when mutations were detected (excluding wild type/wild type genes). Mutations with high allele frequently were more likely to be concordant. Importantly, over half of mutations detected using each platform were not detected in the other technique. These results highlight the potential need to use both tissue and blood biopsies to understand the complex biology of breast cancer.Patient derived xenografts (PDXs) in colorectal cancer (CRC) are robust preclinical models, essential for drug discovery. While multiple factors (tumor source, grade, stage, acquisition strategy, genotype, time to implantation, and prior therapy) have been assumed to affect PDX engraftment, they have not been systematically studied. Here, using 90 CRC patient specimens subcutaneously implanted into immunodeficient mice (50 established PDXs), Katsiampoura, Raghav and colleagues found that tissue acquisition strategy (surgery vs. biopsy) was the only key determinant for successful PDX engraftment. These findings contrast with current notions and can help streamline PDX modelling protocols allowing for pervasive integration in CRC translational research.

A Novel Galectin-1 Inhibitor Discovered through One-Bead Two-Compound Library Potentiates the Antitumor Effects of Paclitaxel in vivo.

Through the one-bead two-compound (OB2C) ultra-high-throughput screening method, we discovered a new small-molecule compound LLS2 that can kill a variety of cancer cells. Pull-down assay and LC/MS-MS indicated that galectin-1 is the target protein of LLS2. Galectin-1 is known to be involved in the regulation of proliferation, apoptosis, cell cycle, and angiogenesis. Binding of LLS2 to galectin-1 decreased membrane-associated H-Ras and K-Ras and contributed to the suppression of pErk pathway. Importantly, combination of LLS2 with paclitaxel (a very important clinical chemotherapeutic agent) was found to exhibit synergistic activity against several human cancer cell lines (ovarian cancer, pancreatic cancer, and breast cancer cells) in vitro Furthermore, in vivo therapeutic study indicated that combination treatment with paclitaxel and LLS2 significantly inhibits the growth of ovarian cancer xenografts in athymic mice. Our results presented here indicate that the OB2C combinatorial technology is a highly efficient drug screening platform, and LLS2 discovered through this method can be further optimized for anticancer drug development. Mol Cancer Ther; 16(7); 1212-23. ©2017 AACR.

Discovery and Characterization of a Potent and Specific Peptide Ligand Targeting Endothelial Progenitor Cells and Endothelial Cells for Tissue Regeneration

Endothelial progenitor cells (EPCs) and endothelial cells (ECs) play a vital role in endothelialization and vascularization for tissue regeneration. Various EPC/EC targeting biomolecules have been investigated to improve tissue regeneration with limited success often due to their limited functional specificity and structural stability. One-bead one-compound (OBOC) combinatorial technology is an ultrahigh throughput chemical library synthesis and screening method suitable for ligand discovery against a wide range of biological targets, such as integrins. In this study, using primary human EPCs/ECs as living probes, we identified an αvβ3 integrin ligand LXW7 discovered by OBOC combinatorial technology as a potent and specific EPC/EC targeting ligand. LXW7 overcomes the major barriers of other functional biomolecules that have previously been used to improve vascularization for tissue regeneration and possesses optimal stability, EPC/EC specificity, and functionality. LXW7 is a disulfide cyclic octa-peptide (cGRGDdvc) containing unnatural amino acids flanking both sides of the main functional motif; therefore it will be more resistant to proteolysis and more stable in vivo compared to linear peptides and peptides consisting of only natural amino acids. Compared with the conventional αvβ3 integrin ligand GRGD peptide, LXW7 showed stronger binding affinity to primary EPCs/ECs but weaker binding to platelets and no binding to THP-1 monocytes. In addition, ECs bound to the LXW7 treated culture surface exhibited enhanced biological functions such as proliferation, likely due to increased phosphorylation of VEGF receptor 2 (VEGF-R2) and activation of mitogen-activated protein kinase (MAPK) ERK1/2. Surface modification of electrospun microfibrous PLLA/PCL biomaterial scaffolds with LXW7 via Click chemistry resulted in significantly improved endothelial coverage. LXW7 and its derivatives hold great promise for EPC/EC recruitment and delivery and can be widely applied to functionalize various biological and medical materials to improve endothelialization and vascularization for tissue regeneration applications.

Monoclonal Antibodies and Antibody Like Fragments Derived from Immunised Phage Display Libraries.

Morbidity and mortality associated with infectious diseases are always on the rise, especially in poorer countries and in the aging population. The inevitable, but unpredictable emergence of new infectious diseases has become a global threat. HIV/AIDS, severe acute respiratory syndrome (SARS), and the more recent H1N1 influenza are only a few of the numerous examples of emerging infectious diseases in the modern era. However despite advances in diagnostics, therapeutics and vaccines, there is need for more specific, efficacious, cost-effective and less toxic treatment and preventive drugs. In this chapter, we discuss a powerful combinatorial technology in association with animal immunisation that is capable of generating biologic drugs with high affinity, efficacy and limited off-site toxicity, and diagnostic tools with great precision. Although time consuming, immunisation still remains the preferred route for the isolation of high-affinity antibodies and antibody-like fragments. Phage display is a molecular diversity technology that allows the presentation of large peptide and protein libraries on the surface of filamentous phage. The selection of binding fragments from phage display libraries has proven significant for routine isolation of invaluable peptides, antibodies, and antibody-like domains for diagnostic and therapeutic applications. Here we highlight the many benefits of combining immunisation with phage display in combating infectious diseases, and how our knowledge of antibody engineering has played a crucial role in fully exploiting these platforms in generating therapeutic and diagnostic biologics towards antigenic targets of infectious organisms.