Genome scale CRISPR Cas9a knockout screen reveals genes that control glioblastoma susceptibility to the alkylating agent temozolomide.

Glioblastoma is the most fatal of all primary human brain tumors with 14 months median survival. The mainstay therapy for this tumor involves temozolomide, surgery, radiotherapy and tumor treating electric field. Cancer resistance to commonly available chemotherapeutics remains a major challenge in glioblastoma patients receiving treatment and unfavorably impact their overall survival and outcome. However, the lack of progress in this area could be attributed to lack of tools to probe unbiasedly at the genome wide level the coding and non-coding elements contribution on a large scale for factors that control resistance to chemotherapeutics. Understanding the mechanisms of resistance to chemotherapeutics will enable precision medicine in the treatment of cancer patients. CRISPR Cas9a has emerged as a functional genomics tool to study at genome level the factors that control cancer resistance to drugs. Recently, we used genome wide CRISPR-Cas9a screen to identify genes responsible for glioblastoma susceptibility to etoposide. We extended our inquiry to understand genes that control glioblastoma response to temozolomide by using genome scale CRISPR. This study shows that the unbiased genome-wide loss of function approach can be applied to discover genes that influence tumor resistance to chemotherapeutics and contribute to chemoresistance in glioblastoma.

Translocon-associated Protein Subunit SSR3 Determines and Predicts Susceptibility to Paclitaxel in Breast Cancer and Glioblastoma.

PURPOSE: Paclitaxel (PTX) is one of the most potent and commonly used chemotherapies for breast and pancreatic cancer. Several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for glioblastomas. Despite the widespread use of PTX for breast cancer, and the initiative to repurpose this drug for gliomas, there are no predictive biomarkers to inform which patients will likely benefit from this therapy. EXPERIMENTAL DESIGN: To identify predictive biomarkers for susceptibility to PTX, we performed a genome-wide CRISPR knockout (KO) screen using human glioma cells. The genes whose KO was most enriched in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort using progression-free survival. RESULTS: Combination of CRISPR screen results with outcomes from patients with taxane-treated breast cancer led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with susceptibility to PTX in breast cancer cells, glioma cells, and in multiple intracranial glioma xenografts models. KO of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. Mechanistically, SSR3 confers susceptibility to PTX through regulation of phosphorylation of ER stress sensor IRE1α. CONCLUSIONS: Our hypothesis generating study showed SSR3 as a putative biomarker for susceptibility to PTX, warranting its prospective clinical validation.

NSUN6, an RNA methyltransferase of 5-mC controls glioblastoma response to temozolomide (TMZ) via NELFB and RPS6KB2 interaction.

Nop2/Sun RNA methyltransferase (NSUN6) is an RNA 5-methyl cytosine (5mC) transferase with little information known of its function in cancer and response to cancer therapy. Here, we show that NSUN6 methylates both large and small RNA in glioblastoma and controls glioblastoma response to temozolomide with or without influence of the MGMT promoter status, with high NSUN6 expression conferring survival benefit to glioblastoma patients and in other cancers. Mechanistically, our results show that NSUN6 controls response to TMZ therapy via 5mC-mediated regulation of NELFB and RPS6BK2. Taken together, we present evidence that show that NSUN6-mediated 5mC deposition regulates transcriptional pause by accumulation of NELFB and the general transcription factor complexes (POLR2A, TBP, TFIIA, and TFIIE) on the preinitiation complex at the TATA binding site to control translation machinery in glioblastoma response to alkylating agents. Our findings open a new frontier into controlling of transcriptional regulation by RNA methyltransferase and 5mC.

Ultrashort single-pulse laser ablation of stainless steel, aluminium, copper and its dependence on the pulse duration.

In this work, we investigate single-pulse laser ablation of bulk stainless steel (AISI304), aluminium (Al) and copper (Cu) and its dependence on the pulse duration. We measured the reflectivity, ablation thresholds and volumes under the variation of pulse duration and fluence. The known drop of efficiency with increasing pulse duration is confirmed for single-pulse ablation in all three metals. We attribute the efficiency drop to a weakened photomechanically driven ablation process and a stronger contribution of photothermal phase explosion. The highest energetic efficiency and precision is achieved for pulse durations below the mechanical expansion time of 3-5 ps, where the stress confinement condition is fulfilled.

Ribosomal protein S11 influences glioma response to TOP2 poisons.

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We and others had shown that a subset of glioblastomas, the most malignant of all primary brain tumors in adults, is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, and 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 led to resistance to etoposide and doxorubicin and impaired the induction of proapoptotic gene APAF1 following treatment. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from gliomas and multiple other cancers.

Pooled In Vitro and In Vivo CRISPR-Cas9 Screening Identifies Tumor Suppressors in Human Colon Organoids.

Colorectal cancer (CRC) is characterized by prominent genetic and phenotypic heterogeneity between patients. To facilitate high-throughput genetic testing and functional identification of tumor drivers, we developed a platform for pooled CRISPR-Cas9 screening in human colon organoids. Using transforming growth factor ß (TGF-ß) resistance as a paradigm to establish sensitivity and scalability in vitro, we identified optimal conditions and strict guide RNA (gRNA) requirements for screening in 3D organoids. We then screened a pan-cancer tumor suppressor gene (TSG) library in pre-malignant organoids with APC-/-;KRASG12D mutations, which were xenografted to study clonal advantages in context of a complex tumor microenvironment. We identified TGFBR2 as the most prevalent TSG, followed by known and previously uncharacterized mediators of CRC growth. gRNAs were validated in a secondary screen using unique molecular identifiers (UMIs) to adjust for clonal drift and to distinguish clone size and abundance. Together, these findings highlight a powerful organoid-based platform for pooled CRISPR-Cas9 screening for patient-specific functional genomics.

Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC-Peptide Binding Data Set.

Knowing whether a protein can be processed and the resulting peptides presented by major histocompatibility complex (MHC) is highly important for immunotherapy design. MHC ligands can be predicted by in silico peptide-MHC class-I binding prediction algorithms. However, prediction performance differs considerably, depending on the selected algorithm, MHC class-I type, and peptide length. We evaluated the prediction performance of 13 algorithms based on binding affinity data of 8- to 11-mer peptides derived from the HPV16 E6 and E7 proteins to the most prevalent human leukocyte antigen (HLA) types. Peptides from high to low predicted binding likelihood were synthesized, and their HLA binding was experimentally verified by in vitro competitive binding assays. Based on the actual binding capacity of the peptides, the performance of prediction algorithms was analyzed by calculating receiver operating characteristics (ROC) and the area under the curve (AROC). No algorithm outperformed others, but different algorithms predicted best for particular HLA types and peptide lengths. The sensitivity, specificity, and accuracy of decision thresholds were calculated. Commonly used decision thresholds yielded only 40% sensitivity. To increase sensitivity, optimal thresholds were calculated, validated, and compared. In order to make maximal use of prediction algorithms available online, we developed MHCcombine, a web application that allows simultaneous querying and output combination of up to 13 prediction algorithms. Taken together, we provide here an evaluation of peptide-MHC class-I binding prediction tools and recommendations to increase prediction sensitivity to extend the number of potential epitopes applicable as targets for immunotherapy.

ERAP1 overexpression in HPV-induced malignancies: A possible novel immune evasion mechanism.

Immune evasion of tumors poses a major challenge for immunotherapy. For human papillomavirus (HPV)-induced malignancies, multiple immune evasion mechanisms have been described, including altered expression of antigen processing machinery (APM) components. These changes can directly influence epitope presentation and thus T-cell responses against tumor cells. To date, the APM had not been studied systematically in a large array of HPV+ tumor samples. Therefore in this study, systematic expression analysis of the APM was performed on the mRNA and protein level in a comprehensive collection of HPV16+ cell lines. Subsequently, HPV+ cervical tissue samples were examined by immunohistochemistry. ERAP1 (endoplasmic reticulum aminopeptidase 1) was the only APM component consistently altered - namely overexpressed - in HPV16+ tumor cell lines. ERAP1 was also found to be overexpressed in cervical intraepithelial neoplasia and cervical cancer samples; expression levels were increasing with disease stage. On the functional level, the influence of ERAP1 expression levels on HPV16 E7-derived epitope presentation was investigated by mass spectrometry and in cytotoxicity assays with HPV16-specific T-cell lines. ERAP1 overexpression did not cause a complete destruction of any of the HPV epitopes analyzed, however, an influence of ERAP1 overexpression on the presentation levels of certain HPV epitopes could be demonstrated by HPV16-specific CD8+ T-cells. These showed enhanced killing toward HPV16+ CaSki cells whose ERAP1 expression had been attenuated to normal levels. ERAP1 overexpression may thus represent a novel immune evasion mechanism in HPV-induced malignancies, in cases when presentation of clinically relevant epitopes is reduced by overactivity of this peptidase.

CRISPR library designer (CLD): software for multispecies design of single guide RNA libraries.

BACKGROUND: Genetic screens using CRISPR/Cas9 are a powerful method for the functional analysis of genomes. RESULTS: Here we describe CRISPR library designer (CLD), an integrated bioinformatics application for the design of custom single guide RNA (sgRNA) libraries for all organisms with annotated genomes. CLD is suitable for the design of libraries using modified CRISPR enzymes and targeting non-coding regions. To demonstrate its utility, we perform a pooled screen for modulators of the TNF-related apoptosis inducing ligand (TRAIL) pathway using a custom library of 12,471 sgRNAs. CONCLUSION: CLD predicts a high fraction of functional sgRNAs and is publicly available at https://github.com/boutroslab/cld.