Supplementary Figure S1-4 and Supplementary Table S1-3

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

Supplementary Figure 1. miR-21 mimic suppresses expression of ANKRD46, DDAH1 and RECK. SKHep1 cells were transfected with miR-21 or negative mimic. RNA was isolated and expression of ANKRD46, DDAH1 and RECK was assessed by qPCR. (Mean, {plus minus} SD, n=3).

Supplementary Data 1. Excel sheet with fold change in gene expression following anti-miR-21 treatment.

PDF - 6591K, Tumor growth curves utilizing median ATVs of the 48 CRC PDXs: Tumor growth curves for all 48 patient-derived CRC tumors in mice engrafted SC, and which were treated with aflibercept SC injection (2x/week, 25 mg/kg), vehicle (SC injection, 2x/week), or bevacizumab (IV injection, 2x/week, 25 mg/kg) for a total of 3 weeks. Tumor measurements were recorded twice per week. Error bars represent MAD.

Supplementary Figure 4. Pathway analysis of gene expression changes following anti-miR-21 treatment. SKHep1 cells treated with anti-miR-21 were subjected to microarray gene expression analysis. Changes in cellular processes (top) and pathways (bottom) upon anti-miR-21 treatment are shown.

supplemental methods, data and figures

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Supplementary Figure 2. Anti-miR-21 treatment causes limited caspase 3/7 activation in non-transformed cell lines. Caspase 3/7 activation after treatment of SKHep1, IMR-90, and WI-38 cells with MM control or anti-miR-21 for 72 hours. (Mean, {plus minus} SEM, n=3).

Background The identification of cancer-specific T cell receptor (TCR) sequences is paramount to the advancement of cancer immunotherapies. Recent studies and clinical trials have shown that monoclonal T cell therapy is prone to immune evasion of cancer cells by loss of HLA heterozygosity and low antigen heterogeneity. Cocktail T cell therapy which comprises of TCRs corresponding to multiple HLAs and antigens has been proposed to improve the efficacy of adoptive cell transfer therapy. In addition to CD8+ cytotoxic T cells, neoantigen-specific CD4+ T cells, while identified as important for immunotherapy-induced anti-tumor responses, remain a largely untapped therapeutic resources due to the challenging nature of identification and isolation. Hence, a rapid and high-throughput discovery of both CD8+ and CD4+ TCRs against multiples Class I and II HLAs and cancer antigens is an urgent need. We engineered peptide-bound major histocompatibility complex (pMHC) proteins as capture agents for cancer-specific T cells. The design of these single-chain-trimers (SCTs) enables high-throughput multiplexing for identification and isolation of cancer-targeting CD4+ and CD8+ T cells from multiple patients against large panels of cancer antigens. We applied the technology to identify CD8+ and CD4+ TCRs against oncogenic proteins E6 and E7 from HPV-16, which is the leading cause of cervical cancer. Methods A panel of 200+ Class I SCTs and 100+ Class II SCTs were designed and expressed in a high-throughput platform. PBMCs from precancerous HPV-16+ patients with cervical lesions were collected and enriched with CD8+ and CD4+ T cells. A large pool of 200+ Class I SCT tetramer pool with barcode as antigen identifier was used to capture cancer-specific CD8+ T cells. A computational analysis pipeline was established to pair TCR α and β. HLA-matching cognate antigen was assigned to each TCR pair after UMI count correction and noise removal. The antigen-specific TCRs are subsequently sequenced, validated for functionality, and analyzed for therapeutic applications. Results We identified 43 CD8+ TCR pairs against E6 and E7 oncoproteins from HPV-16 and they are in progress for pre-clinical validation. Conclusions The SCT platform enables rapid identification of cancer-specific CD+ and CD4+ T cells and allows detailed characterization of anti-tumor T cells for which alternative solutions are extremely limited. We applied the technology to PBMCs extracted from HPV-16 related precancerous patients in a clinical trial and discovered cancer-specific TCRs. In summary, the application of the SCT technology is of high value to the fundamental and clinical immune-oncology studies.

PDF - 115K, Legends to Supplementary Figures. Supplementary Table S1. Characteristics of 48 patient-derived colon cancer tumor xenografts. Supplementary Table S2. Evaluation of statistical differences between treatment(s) groups at the terminal point.

PDF - 6683K, Tumor growth curves utilizing mean ATVs of the 48 CRC PDXs: Tumor growth curves for all 48 patient-derived CRC tumors in mice engrafted SC, and which were treated with aflibercept SC injection (2x/week, 25 mg/kg), vehicle (SC injection, 2x/week), or bevacizumab (IV injection, 2x/week, 25 mg/kg) for a total of 3 weeks. Tumor measurements were recorded twice per week. Error bars represent standard error of the mean.

Abstract The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data. We have developed IMMUcan scDB (https://immucanscdb.vital-it.ch), a fully integrated scRNA-seq database exclusively dedicated to human cancer and accessible to nonspecialists. IMMUcan scDB encompasses 144 datasets on 56 different cancer types, annotated in 50 fields containing precise clinical, technological, and biological information. A data processing pipeline was developed and organized in four steps: (i) data collection; (ii) data processing (quality control and sample integration); (iii) supervised cell annotation with a cell ontology classifier of the TME; and (iv) interface to analyze TME in a cancer type–specific or global manner. This framework was used to explore datasets across tumor locations in a gene-centric (CXCL13) and cell-centric (B cells) manner as well as to conduct meta-analysis studies such as ranking immune cell types and genes correlated to malignant transformation. This integrated, freely accessible, and user-friendly resource represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNA-seq data for discovery and validation studies. Significance: The IMMUcan scDB database is an accessible supportive tool to analyze and decipher tumor-associated single-cell RNA sequencing data, allowing researchers to maximally use this data to provide new insights into cancer biology.

PDF - 44K, Distribution of the tumor origin across PDX models: Of the 48 PDX tumors, 8 were derived from primary patient tumors, 36 from metastatic sites, 1 from a site of recurring disease, and 1 of unknown anatomical origin. All of the primary tumors (8/8) were associated with phenotype A where aflibercept is more efficacious than bevacizumab. PDX tumors that originated from metastatic tumors were represented in both phenotypes A (30/39) and B (9/9).

Supplementary Tables 1 and 2. Supplementary Table 1: Fold de-repression of miR-21 target genes after anti-miR-21 treatment. Supplementary Table 2: Taqman Primer and Probes

Supplementary Figure Legends. Figure legends for Supplementary Figures 1, 2, 3, and 4.

PDF - 107K, Genomic characterization of PDX models: 48 PDX tumors comprising similar mutational patterns of KRAS, BRAF, PIK3CA, and PTEN have been reported in several other publications.

Supplementary Figure 3. HMBG1 and LDH are induced upon miR-21 inhibition. SKHep1, HepG2 and Hep3B cells were treated with anti-miR-21 or MM control and extracellular HMBG1 and LDH activity was quantified. (Mean, {plus minus} SEM, n=3)

We assessed the utility of mRNAs in extracellular vesicles as biomarkers for inhibition of YAP1/TEAD signaling by the TEAD central pocket inhibitor. The field of liquid biopsies is of enormous interest for noninvasive monitoring of cancer progression and response to treatment. Extracellular Vesicles (EVs) such as exosomes, microvesicles, and apoptotic bodies, are nanoparticles found in all biological fluids. These cell-derived, small secreted vesicles convey biological information, either by surface-to-surface interaction or by shuttling bioactive molecules to a recipient cell’s cytoplasm. Because EVs harbor the cargos of their original cells, their contents may be useful as biomarkers to follow drug activity. (F. Urabi et al., 2020). We compared the effects of YAP1/TEAD inhibitor treatment on intracellular and EV-encapsulated mRNAs in three compound-sensitive tumor cell lines (and one insensitive cell line) based on TEAD inhibitor IC50 assay profiles. Cell lines were treated at four doses of YAP1/TEAD inhibitor (0.0 µM, 0.3 µM, 1.0 µM & 3.0 µM) for 24h. EVs and intracellular RNAs were isolated and profiled by RNAseq. To estimate YAP1/TEAD pathway activity, we used a transcriptomic signature identified previously by our group (L. Calvet et al., 2022) and we showed that the effects of YAP1/TEAD inhibitor treatment on the YAP1/TEAD score in intracellular mRNAs corresponded to a decrease of the score in EV-secreted RNAs. In addition, we ran an unbiased analysis to identify single transcripts in the EVs that were modulated by YAP1/TEAD inhibitor. One of the best markers identified by regression analysis was CYR61, that is part of the signature and is a well-established downstream target of YAP/TEAD pathway. In conclusion, these results suggest that the YAP1/TEAD signature in EV mRNAs represents a relevant PD biomarker to monitor YAP1/TEAD inhibitor activity and could potentially serve as a noninvasive liquid biopsy-based biomarker detection in the clinic. Citation Format: Manoel Nunes, Emmanuel Spanakis, Wilson Dos-Santos-Bele, Emilia Rabia, Stephane Soubigou, Gaelle Muzard, Odette Dos-Santos, Jack Pollard, Angela Hadjipanayis, Fabien Delahaye, Olivier Venier, Laurent Debussche, Don Jackson, Colette Dib, Iris Valtingojer, Matteo Cesaroni. Tumor-derived Extracellular Vesicles as a potential PD biomarker for TEAD central pocket binder activity in liquid biopsy [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 3367.