Custom Library Research Articles

Discovering selective antiferroptotic inhibitors of the 15LOX/PEBP1 complex noninterfering with biosynthesis of lipid mediators

Programmed ferroptotic death eliminates cells in all major organs and tissues with imbalanced redox metabolism due to overwhelming iron-catalyzed lipid peroxidation under insufficient control by thiols (Glutathione (GSH)). Ferroptosis has been associated with the pathogenesis of major chronic degenerative diseases and acute injuries of the brain, cardiovascular system, liver, kidneys, and other organs, and its manipulation offers a promising new strategy for anticancer therapy. This explains the high interest in designing new small-molecule-specific inhibitors against ferroptosis. Given the role of 15-lipoxygenase (15LOX) association with phosphatidylethanolamine (PE)-binding protein 1 (PEBP1) in initiating ferroptosis-specific peroxidation of polyunsaturated PE, we propose a strategy of discovering antiferroptotic agents as inhibitors of the 15LOX/PEBP1 catalytic complex rather than 15LOX alone. Here we designed, synthesized, and tested a customized library of 26 compounds using biochemical, molecular, and cell biology models along with redox lipidomic and computational analyses. We selected two lead compounds, FerroLOXIN-1 and 2, which effectively suppressed ferroptosis invitro and invivo without affecting the biosynthesis of pro-/anti-inflammatory lipid mediators invivo. The effectiveness of these lead compounds is not due to radical scavenging or iron-chelation but results from their specific mechanisms of interaction with the 15LOX-2/PEBP1 complex, which either alters the binding pose of the substrate [eicosatetraenoyl-PE (ETE-PE)] in a nonproductive way or blocks the predominant oxygen channel thus preventing the catalysis of ETE-PE peroxidation. Our successful strategy may be adapted to the design of additional chemical libraries to reveal new ferroptosis-targeting therapeutic modalities.

Several cell-intrinsic effectors drive type I interferon-mediated restriction of HIV-1 in primary CD4+ T cells

Type I interferon (IFN) upregulates proteins that inhibit HIV within infected cells. Prior studies have identified IFN-stimulated genes (ISGs) that impede lab-adapted HIV in cell lines, yet the ISG(s) that mediate IFN restriction in HIV target cells, primary CD4+ Tcells, are unknown. Here, we interrogate ISG restriction of primary HIV in CD4+ Tcells by performing CRISPR-knockout screens with a custom library that specifically targets ISGs expressed in CD4+ Tcells. Our investigation identifies previously undescribed HIV-restricting ISGs (HM13, IGFBP2, LAP3) and finds that two factors characterized in other HIV infection models (IFI16 and UBE2L6) mediate IFN restriction in Tcells. Inactivation of these five ISGs in combination further diminishes IFN's protective effect against diverse HIV strains. This work demonstrates that IFN restriction of HIV is multifaceted, resulting from several effectors functioning collectively, and establishes a primary cell ISG screening model to identify both single and combinations of HIV-restricting ISGs.

Non-Intrusive Load Monitoring Using Identity Library Based on Structured Feature Graph and Group Decision Classifier

Non-intrusive load monitoring (NILM) is performed to realize intelligent power consumption. A load identification algorithm which is flexible for various households is required to realize automatic NILM. An approach of NILM proposed in this paper is general for most types of loads and exclusive for different users. In this paper, inspired by the knowledge graph holding strong power for knowledge representing, a load feature graph that preserves sufficient information is constructed. The graph provides a net relation between load types and features, which is the basis of load knowledge reasoning. After transforming current and voltage into structured images and data according to the net relation, the convolutional neural networks and combined Support Vector Machines are used to classify images and data respectively. Furthermore, to minimize running time, a customized load identity library focusing on the individual user is proposed. Considering requirements of different computing power resources, above processes are deployed on the architecture of end-cloud collaboration. The experimental results on NILM datasets demonstrate that the proposed method outperforms most of the existing methods in the recognition accuracy and supports for different types of users.

Abstract 417: Targeting aurora kinase b overcomes acquired resistance to met-tyrosine kinase inhibitor in met-amplified lung cancer

Abstract Mesenchymal-epithelial transition factor receptor (MET) mediated signaling emerged as an important clinical target for the treatment of many cancer types including non-small cell lung cancer. MET amplification is prevalent in 2%~4% of primary lung cancer and 15%~50% of EGFR-mutated lung cancer resistant to EGFR inhibitors. Currently, MET-targeting drugs have been actively investigated in these MET-amplified lung cancers. However, the acquired resistance mechanism for MET-targeted therapy remains unknown. Our study aims to provide effective treatment for overcoming MET-TKI-acquired resistance in MET-amplified non-small cell lung cancer. To discover the resistance mechanism, we established the resistant cell line (PR-S2) by chronic exposure of MET-amplified lung cancer cells (H1993) to MET kinase inhibitor, PHA665752. Through high-throughput screening of a custom library of 276 compounds, we found that Aurora kinase B (AURKB) inhibitor, barasertib was more sensitive to the PR-S2 cells than H1993 cells. AURKB inhibition by barasertib induced apoptotic cell death with G2/M arrest and polyploid cell formation in the PR-S2 cells. The expression of p-AURKB was increased with no change in the expression of p-histone H3, a major product of AURKB in the PR-S2 cells. AURKB knockdown using multiple siRNA sequences increases the sensitivity to PHA665752 in the PR-S2 cells. In mRNA sequencing data analysis, we found the expression of signal transducer and activator of transcription 3 (STAT3) was elevated in the PR-S2 cells compared to the H1993 cells. We confirmed increased STAT3 expression in both protein and mRNA levels in the PR-S2 cells. p-STAT3 expression was decreased after barasertib treatment in the PR-S2 cells. However, in the immunoprecipitation assay, there was no direct interaction between AURKB and STAT3. To know the target of STAT3, we checked the mRNA expression of downstream genes of STAT3. The expression of BCL-2, one of the downstream targets of STAT3 and the central apoptosis regulator, was highly upregulated in the resistant cells. The siRNA-mediated knockdown of STAT3 expression decreased BCL2 expression in the PR-S2 cells, whereas not in the H1993 cells. Furthermore, we investigated apoptosis-related gene expressions and found that the BH3-only proapoptotic member of the BCL-2 protein family, BIM was significantly decreased in the PR-S2 cells. AURKB inhibition induced BIMEL accumulation and reduced p-BIM expression. Collectively, our study suggests that AURKB activation induces resistance to MET-TKI through anti-apoptosis mechanism with upregulation of STAT3/BCL2 axis in MET-amplified lung cancer cells. Citation Format: Yura Choi, Mihwa Hwang, Sunshin Kim, Jae J. Song, Youngjoo Lee. Targeting aurora kinase b overcomes acquired resistance to met-tyrosine kinase inhibitor in met-amplified lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 417.

Abstract 227: In vivo functional genomics screen to uncover tumor intrinsic negative regulators of NK cell-mediated tumor cell killing

Abstract Natural killer cells are innate immune cells whose activity is gated by activating and inhibitory receptors that bind ligands on potential target cells. NK cell gene signatures are associated with improved survival in several indications, and NK cell therapies have shown some encouraging results in the clinic. These data highlight the relevance of this cell type in anti-tumor immunity and has given rise to interest in amplifying NK responses to cancer as a complementary therapeutic strategy to current T cell based immunotherapies. The goal of this project is to identify tumor cell intrinsic negative regulators of NK cell-mediated tumor cell killing through in vivo CRISPR/Cas9 screening, with identification of both PD-1 blockade-dependent and -independent regulators. The syngeneic B16F10 model in C57Bl6 mice was used with or without NK depletion and with or without anti-PD1 treatment, with a custom library of 900 genes split into four subpools (one guide per gene per subpool). B16F10 cells were transduced in vitro and inoculated into mice ten days after spinfection. On day 14 after inoculation, tumors were harvested and subsequently the gDNA was isolated and sequenced. QC analysis indicated good guide recovery and screen performance. There were several hits from this screen that were depleted in the NK+ context but not in the NK depleted context, indicating their potential role in regulating NK mediated cell killing. Of the hits, several expected genes scored including B2M which is a known negative regulator of NK cell killing. Validation efforts include confirmation of dropout in other models as well as in vitro co-culture assays to assess enhanced NK killing of single gene KO cells. The hits identified in the screen will increase our understanding of anti-tumor immunity and serve as potential novel Oncology targets. Citation Format: Kayla Duval, Elsa Krall, Federica Piccioni, Maria Monberg, Marianne Spatz, Tobias Ehrenberger, Nicole Follmer. In vivo functional genomics screen to uncover tumor intrinsic negative regulators of NK cell-mediated tumor cell killing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 227.

Abstract 1696: Systematic identification of pathways associated with antibody drug conjugate sensitivity in breast cancer

Abstract Antibody drug conjugates (ADC) are emerging as paradigm-changing precision therapeutics. Sacituzumab Govitecan (SG), which combines a Topoisomerase I (TOP1) inhibitor payload (SN38) with hRS7, an antibody targeting the tumor-selective antigen TROP2, is proving to be a successful cancer therapeutic for some highly refractory cancers including triple negative breast cancer (TNBC). However, mechanisms and biomarkers of sensitivity and resistance to SG remain poorly understood. Prior clinical trials have identified positive correlations between TROP2 expression and better outcome for metastatic TNBC patients receiving SG. Additionally, patient-derived specimen analyses by our group identified mutations in both TROP2 and TOP1 in post-progression metastatic lesions, suggesting multifaceted resistance mechanisms. To systematically interrogate ADC sensitivity mechanisms, we utilized genome-wide CRISPR-Cas9 knockout screening to identify novel regulators mediating SG sensitivity in human TNBC cells. Interactome analysis of top SG sensitizing hits showed clustered pathways of interest, including DNA repair/replication, mTORC1/metabolism, and endosome trafficking/sorting. The top druggable hit sensitizing to SG was PARP1, encoding the poly (ADP-ribose) polymerase 1 that is a key enzyme required for single-strand break repair pathways and for DNA replication fork stability. Conversely, the very top SG resistance-inducing hit in the genome was PARG, encoding the glycohydrolase that opposes PARP enzymatic activity. Furthermore, the synergistic lethality between TOP1 and PARP1 was confirmed in experiments combining SG with PARP inhibitor treatment of TNBC cell lines. In addition, to identify SG/ADC specific genes and pathways, we performed a secondary round of CRISPR screens using a custom library comprising top hits discovered in the primary screen, treating cells in parallel with either SG or cytotoxic payload SN38 alone. Pathway analysis of genes selectively modulating sensitivity to SG but not SN38 revealed novel mediators involved in TROP2 turnover and recycling. We then performed validation and mechanistic studies to elucidate how specific genetic permutations regulate antibody delivery and sensitivity to SG. In conclusion, through a systematic approach using CRISPR screening, we identified several novel resistance and sensitizing pathways that are implicated in ADC delivery and target protein turnover. We are currently prioritizing the druggable genes and pathways in preparation for proof-of-concept studies combining ADCs with select targeted therapeutics to achieve greater tumor killing efficacy. Citation Format: Bogang Wu, Sheng Sun, Nayana Thimmiah, Aiko Nagayama, James Coates, Win Thant, David Li, John Doench, Aditya Bardia, Leif Ellisen. Systematic identification of pathways associated with antibody drug conjugate sensitivity in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1696.

An efficient repeat masking library for the genomic data of coconut and related trees

Abstract Even though repeat masking using custom designed libraries significantly improves the genome annotation and gene prediction, such libraries for palm trees are yet to be designed and made accessible to the researchers. In this study, a repeat library was designed and validated for use in coconut and related palm genomes. Coconut genome with chromosome-level assembly was used to design independent libraries for tall and dwarf ecotypes, which were subsequently merged. Efficiency of the combined de novo library in genome annotation and gene prediction was assessed in comparison with the conventional libraries (Dfam+RepBase), using RepeatMasker. De novo library had 76.3 % efficiency in coconut genomes compared to 3.51 % in custom libraries and number of genes predicted was reduced from an average of 193,099 to 31,022. In date palm, oil pam and sago palm also, combined library gave higher repeat masking and reduced the number of genes predicted. The de novo library can be accessed at http://www.kau.in/repeat-libraries.

Anti-hyperglycemic fraction from Alternanthera sessilis L. leaves gets elucidated following bioassay-guided isolation and mass spectrometry

The anecdotal use of Alternanthera sessilis L. as a relief for diabetes has been known in the Philippines for generations, and antidiabetic activity of similar varieties in other countries is likewise documented. However, the compounds responsible for this activity remain unclear. This study aims to isolate the anti-hyperglycemic fraction of local A. sessilis leaves and identify the compounds in this fraction. Methanol extract of A. sessilis leaves and its hexane, ethyl acetate (ASE), and water fractions were administered to alloxan-induced diabetic mice. ASE (250mg/kg) had the highest anti-hyperglycemic activity at 6-h post-treatment (25.81%±12.72%), with almost similar blood glucose reduction rate as metformin (30.13±3.75%, p=0.767). Repeated fractionation employing chromatographic separation techniques followed by in vivo anti-hyperglycemic assay yielded partially purified subfractions. A. sessilis ethyl acetate subfraction 4-2 (100mg/kg) displayed remarkable suppression of blood glucose rise in diabetic mice at 6-h post-treatment (26.45±3.75%, p<0.0001), with comparable activity with metformin (100mg/kg, 27.87±5.65%, p=0.652). Liquid chromatography/mass spectrometry showed eight distinct peaks, with four peaks annotated via the Traditional Chinese Medicine library and custom library for A. sessilis. Among these, luteolin, apigenin, ononin, and sophorabioside were identified as putative compounds responsible for the anti-hyperglycemic activity. This result provided basis for the reported anecdotal claims and potential utility of the local variety of A. sessilis leaves as sources of anti-hyperglycemic agents.

QuickFaaS: Providing Portability and Interoperability between FaaS Platforms

Serverless computing hides infrastructure management from developers and runs code on-demand automatically scaled and billed during the code’s execution time. One of the most popular serverless backend services is called Function-as-a-Service (FaaS), in which developers are often confronted with cloud-specific requirements. Function signature requirements, and the usage of custom libraries that are unique to cloud providers, were identified as the two main reasons for portability issues in FaaS applications, leading to various vendor lock-in problems. In this work, we define three cloud-agnostic models that compose FaaS platforms. Based on these models, we developed QuickFaaS, a multi-cloud interoperability desktop tool targeting cloud-agnostic functions and FaaS deployments. The proposed cloud-agnostic approach enables developers to reuse their serverless functions in different cloud providers with no need to change code or install extra software. We also provide an evaluation that validates the proposed solution by measuring the impact of a cloud-agnostic approach on the function’s performance, when compared to a cloud-non-agnostic one. The study shows that a cloud-agnostic approach does not significantly impact the function’s performance.

Integrated High-Throughput Drug Profiling and CRISPR Screening Identify Novel Pathway Vulnerabilities of Leukemic Stem Cells in Chronic Myeloid Leukemia

Despite BCR-ABL-targeting tyrosine kinase inhibitors (TKIs) have dramatically improved the management of chronic myeloid leukemia (CML) patients, TKIs fail to eradicate leukemic stem cells (LSCs). CML-LSCs are recognized as BCR-ABL-kinase activity independent and responsible for TKI-resistance and relapse upon treatment discontinuation. Systematic mapping of druggable signaling pathways enables the identification of novel CML-LSCs effectively targeting drugs, which is critical to enhance the achievement of sustained treatment free remission in CML patients. We implemented ex-vivo drug testing of 80 targeted drugs and 18 drug combinations across 10 000-fold concentration, to evaluate drug sensitivity profiles of primary CML-LSCs and progenitors (CD34+ cells) from twenty patients in addition to CD34+ cells from three healthy donors. We identified novel drug vulnerabilities of CML-LSCs including VEGFR-, CDK2/WEE-, MDM2-, and PI3K/mTOR- inhibitors. Combination of imatinib with idasanutlin, venetoclax, AZD1775 and dexamethasone led to synergistic inhibition of CML-LSCs. To delineate the phenotype-specific sensitivity profile of CML CD34+ cells, we applied ex-vivo flowcytometry-based drug screening approach to bone marrow samples from ten CML patients using a custom library of 20 drugs. We identified specific sensitivity of CML CD34+CD38- cells to mepacrine, RG7112, idasanutlin, and navitoclax. In particular, mepacrine showed striking ability to induce differentiation of CML-LSCs, which was further validated in a separate cohort of primary CML samples and cell lines. To characterize the mechanisms of action of the discovered drugs, we applied genome-scale CRISPR screening in CML cells to identify potential sensitizing and resistance targets for five selected drugs. Imatinib, dasatinib, and tivozanib showed a similar profile of resistance and sensitizing genes, while AZD1775 and mepacrine had unique profiles. We identified knockout targets that confer BCR-ABL1-independent resistance common to different TKIs including mediator complex (MED23, MED26, CCNC), and apoptosis related (APAF1) genes in addition to other genes with uncharacterized role in CML, such as KCTD5 and EIF2AK1. On the other hand, knockout of certain genes was associated with increased sensitivity to specific drugs such as IGF1R-dasatinib and SPNS1-mepacrine associations. KCTD5 was consistently identified as the top resistance gene to all tested TKIs, and therefore we next investigated the potential role of KCTD5 in CML pathogenesis and TKI resistance. In RNA sequencing data, KCTD5 was significantly downregulated in CML-CD34+ cells compared to healthy counterparts. Using co-immunoprecipitation, we revealed that KCTD5 directly interacts with BCR-ABL and mediate TKI-induced ubiquitination by E3 ligase, as shown by WB assay, that can destine BCR-ABL for subsequent degradation. Knockout of KCTD5 was associated with decreased ubiquitination of BCR-ABL and resistance to imatinib in CML cell lines and primary CML-CD34+ cells. Furthermore, combination of TKI with deubiquitinase inhibitors induced enhanced TKI sensitivity in KCTD5-KO cells. In conclusion, we discovered novel mechanisms of primary TKI-resistance and drug vulnerabilities of CML-LSCs, which potentially enable eradication of LSCs in CML patients and hence pave the way for the achievement of functional cure in CML patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Making Complex Cancer Reports Easier Using Self-Built Interactive Templates

Abstract Surgical pathology reports are becoming increasingly complex, especially with neoplastic cases. Pathologists need to verify all elements are addressed in the CAP synoptics, order proper reflex molecular testing or immunohistochemistry depending on care standards and institutional guidelines, and address key points in the report for clinicians. For example, breast cancer cases at our institution need repeat biomarkers for all cases status post neoadjuvant therapy, oncotype reflex testing for pT2N0, estrogen receptor positive tumors, and tumor bed size with residual tumor burden calculations for all breast cancer only after neoadjuvant chemotherapy. For residents and faculty alike, these expansive reports are challenging, especially for those new to the institution’s policies and conventions. Previous workflow included using Microsoft Word documents with previously signed out cases had significant risk for errors that stem from new updates in the CAP protocols, missing or different reflex testing from the previous case, and updated institutional guidelines. We set out to create a customized library of decision support and interactive templates using a software called PhraseExpander. We created PhraseExpander templates for all cancer resections. The templates included the associated synoptics required for accreditation by CAP, implemented automated staging using logic statements, and provided conditional reminders when reflex testing was indicated. Variable labels were utilized to help clarify notes in the CAP synoptic such as how to grade specific tumors and how many high-power fields to count. The tools were distributed to all surgical pathology fellows, residents, and select faculty who expressed interest in participating. The templates were successfully implemented into the routine workflow for surgical pathology sign out. End-user feedback was overwhelmingly positive. First year and upper level residents appreciate the detailed descriptions on how to complete the report, most notably the reflex molecular testing reminders and many conditional aspects such as in our breast cancer reports. Fellows and attendings have also appreciated these aspects as well as the automated staging and reminders to do administrative tasks, such as adding the case to the Laboratory Information System tumor registry. Interactive templates with built in conditions and calculators are powerful tools that can be used for generating the increasingly complex reports in pathology. They provide pathologists real-time and non-interruptive clinical decision support, allow them to spend less time typing and reduce reliance on remembering the required reflex testing. The most notable disadvantage in coding these complex templates is the considerable build and maintenance time. We plan to expand use to flow cytometry reports, biopsy reports, and routine non-neoplastic cases while incorporating labels to assist in resident education.

Identification of Selective PPAR-γ Modulators by Combining Pharmacophore Modeling, Molecular Docking, and Adipogenesis Assay.

The clinically used glitazones (rosiglitazone and pioglitazone) for type 2 diabetes mellitus therapy have been linked to serious side effects such as fluid retention, congestive heart failure, weight gain, bone loss, and an increased risk of bladder cancer. The complete activation of PPAR-γ receptors in target tissues is linked to these effects. Many studies have demonstrated that partial PPAR-γ activators (GW0072, PAT5A, GQ16) give equivalent therapeutic benefits to full PPAR-γ agonists without the associated side effects. These breakthroughs cleared the path for the development of partial agonists or selective PPAR-γ modulators (SPPARγMs). This study combined pharmacophore modeling, molecular docking, and an adipogenesis experiment to identify thiazolidine analogs as SPPARMs/partial agonists. A custom library of 220 molecules was created and virtual screened to discover 90 compounds as SPPARγMs/ partial agonists. The chosen eight compounds were synthesized and tested for adipogenesis using 3T3L1 cell lines. These compounds' partial agonistic activity was evaluated in 3T3L1 cell lines by comparing their capacity to stimulate PPAR-γ mediated adipogenesis to that of a full agonist, rosiglitazone. The findings of the adipogenesis experiment demonstrate that all eight compounds examined had a partial potential to stimulate adipogenesis when compared to the full agonist, rosiglitazone. The current investigation identified eight possible PPAR-γ partial agonists or SPPARγMs that may be effective in the treatment of type 2 diabetes mellitus.

A custom library construction method for super-resolution ribosome profiling in Arabidopsis

BackgroundRibosome profiling, also known as Ribo-seq, is a powerful technique to study genome-wide mRNA translation. It reveals the precise positions and quantification of ribosomes on mRNAs through deep sequencing of ribosome footprints. We previously optimized the resolution of this technique in plants. However, several key reagents in our original method have been discontinued, and thus, there is an urgent need to establish an alternative protocol.ResultsHere we describe a step-by-step protocol that combines our optimized ribosome footprinting in plants with available custom library construction methods established in yeast and bacteria. We tested this protocol in 7-day-old Arabidopsis seedlings and evaluated the quality of the sequencing data regarding ribosome footprint length, mapped genomic features, and the periodic properties corresponding to actively translating ribosomes through open resource bioinformatic tools. We successfully generated high-quality Ribo-seq data comparable with our original method.ConclusionsWe established a custom library construction method for super-resolution Ribo-seq in Arabidopsis. The experimental protocol and bioinformatic pipeline should be readily applicable to other plant tissues and species.

The deubiquitinase USP7 promotes HNSCC progression via deubiquitinating and stabilizing TAZ

Dysregulated abundance, location and transcriptional output of Hippo signaling effector TAZ have been increasingly linked to human cancers including head neck squamous cell carcinoma (HNSCC). TAZ is subjected to ubiquitination and degradation mediated by E3 ligase β-TRCP. However, the deubiquitinating enzymes and mechanisms responsible for its protein stability remain underexplored. Here, we exploited customized deubiquitinases siRNA and cDNA library screen strategies and identified USP7 as a bona fide TAZ deubiquitinase in HNSCC. USP7 promoted cell proliferation, migration, invasion in vitro and tumor growth by stabilizing TAZ. Mechanistically, USP7 interacted with, deubiquitinated and stabilized TAZ by selectively removing its K48-linked ubiquitination chain independent of canonical Hippo kinase cascade. USP7 potently antagonized β-TRCP-mediated ubiquitin-proteasomal degradation of TAZ and enhanced its nuclear retention and transcriptional output. Importantly, overexpression of USP7 correlated with TAZ upregulation, tumor aggressiveness and unfavorable prognosis in HNSCC patients. Pharmacological inhibition of USP7 significantly suppressed tumor growth in both xenograft and PDX models. Collectively, these findings identify USP7 as an essential regulator of TAZ and define USP7-TAZ signaling axis as a novel biomarker and potential therapeutic target for HNSCC.

MODL-04. Drug screening in Disorders with Abnormal DNA Damage Response/Repair (DADDR) andin vivo validation

INTRODUCTION: Disorders with Abnormal DNA Damage Response/Repair (DADDRs) are inherited conditions caused by constitutional mutations of DNA damage response and repair genes and are characterized by an increased cancer risk. Furthermore, affected individuals also show an elevated risk of secondary neoplasms as well as excessive toxicity, poor therapy response and increased mortality when treated with standard radiation and chemotherapy regimens. The main aim of this project is to screen for potential novel chemotherapeutic approaches for these cancer entities, and to employ faithful PDX models for in vivo validation. METHODS: In vitro drug screening was performed using a custom library composed of 345 compounds targeting 61 different proteins. For two specific DADDRs, Li-Fraumeni syndrome (LFS) and Constitutional Mismatch Repair Deficiency (CMMRD), two cancerous (glioblastoma and medulloblastoma) and one non-cancerous cell lines were selected to model each of these conditions. Performance of each drug was assessed based on its efficacy (sensitivity score) and genotoxicity (micronucleus assay). For DADDR PDX model establishment tumor material from DADDR patients is currently being injected orthotopically (brain tumors) or subcutaneously (non-brain tumors) into NSG mice. Following engraftment and expansion, the PDX models will be characterized molecularly and compared with original patient material. RESULTS AND OUTLOOK: In vitro screening revealed n=26 drugs that fulfilled the following criteria: a) favorable toxicity in cancerous cell lines compared to non-cancerous cell lines, b) little to no genotoxic effect in non-cancerous cell lines. These characteristics qualify them as potentially suitable candidates for novel therapeutic approaches specifically for DADDR patients. The hits included inhibitors of ATM/ATR, CHK1/CHK2, DHFR, mTOR and PI3K, as well as microtubule-associated compounds. Combination testing and further validation of these hits using disease-specific in vitro and in vivo PDX models is ongoing.

Impact of AR-V7 and other androgen receptor splice variant expression on outcomes of post-prostatectomy salvage therapy.

274 Background: Radiotherapy (RT) with or without androgen deprivation therapy (ADT) plays a key role in salvage therapy of prostate cancer recurrent after prostatectomy. However, not all patients benefit from salvage therapy, and there is an unmet need for biomarkers to distinguish responders from non-responders. Prostate cancer depends on androgen receptor (AR) signaling, and expression of AR splice variants (ARVs) that enable androgen-independent AR signaling is associated with resistance to ADT in the metastatic setting. Recent in vitro data suggest that ARVs also mediate DNA repair after irradiation, suggesting that ARV expression may also be a biomarker of RT resistance. However, the landscape of ARVs in primary prostate cancer and its effect on treatment outcomes remain unexplored. Here we hypothesize that ARVs are detectable in primary prostate cancer and may modulate response to salvage RT + ADT. Methods: We retrospectively identified 46 prostate cancer patients treated with prostatectomy followed by salvage RT+ ADT at a single institution from 1995 to 2012. The indication for salvage therapy was biochemical failure after undetectable post-operative PSA in 72%, gross local recurrence in 17%, and persistently elevated PSA after surgery in 11%. Median RT dose was 64.8 Gy, and all patients received concurrent ADT. We comprehensively interrogated the landscape of ARVs by performing ultra-deep targeted RNA-seq of archival formalin-fixed paraffin-embedded prostatectomy samples. Using a custom library of &gt; 3000 primers spanning all AR exons and introns, we evaluated 21 native splice junction sites and 20 splice variants with a mean depth of coverage of &gt; 5000x. Decipher score was also evaluated. We tested for association between splice variant expression and clinical outcomes using the log-rank test and Cox proportional hazards model. Results: In total, 76% of patients had one or more detectable AR splice variants. The most commonly detected variants were AR-45 in 41%, AR-V9 in 20%, and AR-V7 in 13%. At a median follow-up of 33.8 months, biochemical progression-free survival (BPFS) at 3 years was 60%, distant metastasis-free survival was 90%, and overall survival was 100%. Among detected splice variants, only AR-V7 was associated with differential clinical outcomes, with a median BPFS of 10.9 months in AR-V7 positive vs 73.4 months in AR-V7 negative patients ( p = 0.0020, HR 5.23, 95% CI 1.62-16.87). Conclusions: Using ultra-deep targeted RNA-Seq, we provide among the first comprehensive descriptions of the ARV landscape in primary prostate cancer. Moreover, we show that detectable AR-V7 in prostatectomy specimens was associated with inferior outcomes following salvage RT+ADT, suggesting for the first time that AR-V7 may modulate outcomes for localized as well as metastatic disease. Ongoing work includes comparison with Decipher score and validation in independent cohorts.

Characterization of Monoclonal Antibody Glycan Heterogeneity Using Hydrophilic Interaction Liquid Chromatography-Mass Spectrometry.

Glycosylation is a critical quality attribute of monoclonal antibody (mAb) therapeutics. Hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) is an invaluable technology for the characterization of protein glycosylation. HILIC/MS-based glycan analysis relies on the library search using Glucose Units (GU) and accurate mass (AM) as the primary search parameters for identification. However, GU-based identifications are gradient-dependent and are not suitable for applications where separation gradients need to be optimized to analyze complex samples or achieve higher throughput. Additionally, the workflow requires calibration curves (using dextran ladder) to be generated for each analysis campaign, which in turn, are used to derive the GU values of the separated glycan species. To overcome this limitation, we employed a two-step strategy for targeted glycan analysis of a mAb expressed in Chinese Hamster Ovary (CHO) cells. The first step is to create a custom library of the glycans of interest independent of GU values (thereby eliminating the need for a calibration curve) and instead uses AM and retention time (RT) as the primary search variables. The second step is to perform targeted glycan screening using the custom-built library. The developed workflow was applied for targeted glycan analysis of a mAb expressed in CHO for 1) cell line selection 2) characterizing the day-wise glycan evolution in a model mAb during a fed-batch culture, 3) assessing the impact of different media conditions on glycosylation, and 4) evaluating the impact of two different process conditions on glycosylation changes in a model mAb grown in a bioreactor. Taken together, the data presented in this study provides insights into the sources of glycan heterogeneity in a model mAb that are seen during its commercial manufacturing.

Complete Transcriptome Analysis by 5'-End Single-Cell RNA-Seq with Random Priming.

Single-cell transcriptome analysis reveals heterogeneous cell types in complex tissues and leads to unexpected biological findings when compared to bulk populations. However most of the methods focus on the 3'-end of polyadenylated transcripts using droplet-based technology. To achieve complete transcriptome, we describe single-cell 5'-end transcriptome protocol with random primed-cDNA harvesting on the Fluidigm C1™ platform which can isolate and process up to 96 cells from a single run with custom library preparation. The method enables detection of Transcription Start Site (TSS) at the single-cell resolution yielding a more comprehensive overview of gene regulatory elements governing in the EpiSC-like cell (EpiLC) including non-polyadenylated RNA and enhancer RNA activities.

Oligo Pools as an Affordable Source of Synthetic DNA for Cost-Effective Library Construction in Protein- and Metabolic Pathway Engineering.

The construction of custom libraries is critical for rational protein engineering and directed evolution. Array‐synthesized oligo pools of thousands of user‐defined sequences (up to ∼350 bases in length) have emerged as a low‐cost commercially available source of DNA. These pools cost ≤10 % (depending on error rate and length) of other commercial sources of custom DNA, and this significant cost difference can determine whether an enzyme engineering project can be realized on a given research budget. However, while being cheap, oligo pools do suffer from a low concentration of individual oligos and relatively high error rates. Several powerful techniques that specifically make use of oligo pools have been developed and proven valuable or even essential for next‐generation protein and pathway engineering strategies, such as sequence‐function mapping, enzyme minimization, or de‐novo design. Here we consolidate the knowledge on these techniques and their applications to facilitate the use of oligo pools within the protein engineering community.

A Python Library for the Jupyteo IDE Earth Observation Processing Tool Enabling Interoperability with the QGIS System for Use in Data Science

This paper describes JupyQgis – a new Python library for Jupyteo IDE enabling interoperability with the QGIS system. Jupyteo is an online integrated development environment for earth observation data processing and is available on a cloud platform. It is targeted at remote sensing experts, scientists and users who can develop the Jupyter notebook by reusing embedded open-source tools, WPS interfaces and existing notebooks. In recent years, there has been an increasing popularity of data science methods that have become the focus of many organizations. Many scientific disciplines are facing a significant transformation due to data-driven solutions. This is especially true of geodesy, environmental sciences, and Earth sciences, where large data sets, such as Earth observation satellite data (EO data) and GIS data are used. The previous experience in using Jupyteo, both among the users of this platform and its creators, indicates the need to supplement its functionality with GIS analytical tools. This study analyzed the most efficient way to combine the functionality of the QGIS system with the functionality of the Jupyteo platform in one tool. It was found that the most suitable solution is to create a custom library providing an API for collaboration between both environments. The resulting library makes the work much easier and simplifies the source code of the created Python scripts. The functionality of the developed solution was illustrated with a test use case.