Genomics of Drug Sensitivity in Cancer (GDSC): a Resource for Therapeutic Biomarker Discovery in Cancer Cells

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Detection of Dysregulated Protein Association Networks by High-Throughput Proteomics Predicts Cancer Vulnerabilities

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this ‘interactome mapping by high-throughput quantitative proteome analysis’ (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network impacts to cellular fitness. Furthermore, these aberrant interactions serve as biomarkers predicting drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems

Potent and selective effect of the mir-10b inhibitor MN-anti-mir10b in human cancer cells of diverse primary disease origin

<div><p>Since microRNAs (miRNAs, miRs) have been implicated in oncogenesis, many of them have been identified as therapeutic targets. Previously we have demonstrated that miRNA-10b acts as a master regulator of the viability of metastatic tumor cells and represents a target for therapeutic intervention. We designed and synthesized an inhibitor of miR-10b, termed MN-anti-miR10b. We showed that treatment with MN-anti-miR10b led to durable regression/elimination of established metastases in murine models of metastatic breast cancer. Since miRNA-10b has been associated with various metastatic and non-metastatic cancers, in the present study, we investigated the effect of MN-anti-miR10b in a panel of over 600 cell lines derived from a variety of human malignancies. We observed an effect on the viability of multiple cell lines within each cancer type and a mostly dichotomous response with cell lines either strongly responsive to MN-anti-miR10b or not at all even at maximum dose tested, suggesting a very high specificity of the effect. Genomic modeling of the drug response showed enrichment of genes associated with the proto-oncogene, c-Jun.</p></div

Cell viability.

<p>Representative line graphs of MN-anti-miR10b concentration vs cell viability for multiple cell lines within representative cancer tissues of origin.</p

BRAF and AXL oncogenes drive RIPK3 expression loss in cancer.

Necroptosis is a lytic programmed cell death mediated by the RIPK1-RIPK3-MLKL pathway. The loss of Receptor-interacting serine/threonine-protein kinase 3 (RIPK3) expression and necroptotic potential have been previously reported in several cancer cell lines; however, the extent of this loss across cancer types, as well as its mutational drivers, were unknown. Here, we show that RIPK3 expression loss occurs progressively during tumor growth both in patient tumor biopsies and tumor xenograft models. Using a cell-based necroptosis sensitivity screen of 941 cancer cell lines, we find that escape from necroptosis is prevalent across cancer types, with an incidence rate of 83%. Genome-wide bioinformatics analysis of this differential necroptosis sensitivity data in the context of differential gene expression and mutation data across the cell lines identified various factors that correlate with resistance to necroptosis and loss of RIPK3 expression, including oncogenes BRAF and AXL. Inhibition of these oncogenes can rescue the RIPK3 expression loss and regain of necroptosis sensitivity. This genome-wide analysis also identifies that the loss of RIPK3 expression is the primary factor correlating with escape from necroptosis. Thus, we conclude that necroptosis resistance of cancer cells is common and is oncogene driven, suggesting that escape from necroptosis could be a potential hallmark of cancer, similar to escape from apoptosis

Profile of response across cell lines from different tissues of origin.

<p>The response to MN-anti-miR10b is shown as IC50 (μM), Area Under the dose response Curve (AUC) or Emax (maximum effect observed: minimum cell viability observed across the two maximum doses tested).</p

Network of proteins encoded by the genes found to be predictive of sensitivity to MN-anti-miR10b by elastic net regression together with JUN.

<p>The functional network was built in STRING and kmeans clustering was performed to identify subnetworks (set to 5 clusters in STRING using all evidence of interactions and interaction score of 0.4 or more). Nodes from the EN output that were not found to be connected are excluded for visualization purposes.</p