Cancer is often seen as a disease of mutations and chromosomal abnormalities. However, some cancers, including pediatric rhabdoid tumors (RTs), lack recurrent alterations targetable by current drugs and need alternative, informed therapeutic options. To nominate potential targets, we performed a high-throughput small-molecule screen complemented by a genome-scale CRISPR-Cas9 gene-knockout screen in a large number of RT and control cell lines. These approaches converged to reveal several receptor tyrosine kinases (RTKs) as therapeutic targets, with RTK inhibition effective in suppressing RT cell growth in vitro and against a xenograft model in vivo. RT cell lines highly express and activate (phosphorylate) different RTKs, creating dependency without mutation or amplification. Downstream of RTK signaling, we identified PTPN11, encoding the pro-growth signaling protein SHP2, as a shared dependency across all RT cell lines. This study demonstrates that large-scale perturbational screening can uncover vulnerabilities in cancers with "quiet" genomes.

Despite the success of approved systemic therapies for estrogen receptor alpha (ER)-positive breast cancer, drug resistance remains common. We hypothesized that secreted factors from the human tumor microenvironment could modulate drug resistance. We previously screened a library of 297 recombinant-secreted microenvironmental proteins for the ability to confer resistance to the anti-estrogen fulvestrant in 2 ER(+) breast cancer cell lines. Herein, we considered whether factors that enhanced drug sensitivity could be repurposed as therapeutics and provide leads for drug development. Screening data revealed bone morphogenic protein (BMP)4 as a factor that inhibited cell growth and synergized with approved anti-estrogens and cyclin-dependent kinase 4/6 inhibitors (CDK4/6i). BMP4-mediated growth inhibition was dependent on type I receptor activin receptor-like kinase (ALK)3-dependent phosphorylation (P) of mothers against decapentaplegic homolog (SMAD/P-SMAD)1 and 5, which could be reversed by BMP receptor inhibitors and ALK3 knockdown. The primary effect of BMP4 on cell fate was cell-cycle arrest, in which RNA sequencing, immunoblot analysis, and RNA interference revealed to be dependent on p21(WAF1/Cip1) upregulation. BMP4 also enhanced sensitivity to approved inhibitors of mammalian target of rapamycin complex 1 and CDK4/6 via ALK3-mediated P-SMAD1/5 and p21 upregulation in anti-estrogen-resistant cells. Patients bearing primary ER(+) breast tumors, exhibiting a transcriptomic signature of BMP4 signaling, had improved disease outcome following adjuvant treatment with anti-estrogen therapy, independently of age, tumor grade, and tumor stage. Furthermore, a transcriptomic signature of BMP4 signaling was predictive of an improved biologic response to the CDK4/6i palbociclib, in combination with an aromatase inhibitor in primary tumors. These findings highlight BMP4 and its downstream pathway activation as a therapeutic opportunity in ER(+) breast cancer.-Shee, K., Jiang, A., Varn, F. S., Liu, S., Traphagen, N. A., Owens, P., Ma, C. X., Hoog, J., Cheng, C., Golub, T. R., Straussman, R., Miller, T. W. Cytokine sensitivity screening highlights BMP4 pathway signaling as a therapeutic opportunity in ER(+) breast cancer.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Synthetic lethality-an interaction between two genetic events through which the co-occurrence of these two genetic events leads to cell death, but each event alone does not-can be exploited for cancer therapeutics(1). DNA repair processes represent attractive synthetic lethal targets, because many cancers exhibit an impairment of a DNA repair pathway, which can lead to dependence on specific repair proteins(2). The success of poly(ADP-ribose) polymerase 1 (PARP-1) inhibitors in cancers with deficiencies in homologous recombination highlights the potential of this approach(3). Hypothesizing that other DNA repair defects would give rise to synthetic lethal relationships, we queried dependencies in cancers with microsatellite instability (MSI), which results from deficient DNA mismatch repair. Here we analysed data from large-scale silencing screens using CRISPR-Cas9-mediated knockout and RNA interference, and found that the RecQ DNA helicase WRN was selectively essential in MSI models in vitro and in vivo, yet dispensable in models of cancers that are microsatellite stable. Depletion of WRN induced double-stranded DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models required the helicase activity of WRN, but not its exonuclease activity. These findings show that WRN is a synthetic lethal vulnerability and promising drug target for MSI cancers.

Purpose Cell-free DNA (cfDNA) offers the potential for minimally invasive genome-wide profiling of tumor alterations without tumor biopsy and may be associated with patient prognosis. Triple-negative breast cancer (TNBC) is characterized by few mutations but extensive somatic copy number alterations (SCNAs), yet little is known regarding SCNAs in metastatic TNBC. We sought to evaluate SCNAs in metastatic TNBC exclusively via cfDNA and determine if cfDNA tumor fraction is associated with overall survival in metastatic TNBC. Patients and Methods In this retrospective cohort study, we identified 164 patients with biopsy-proven metastatic TNBC at a single tertiary care institution who received prior chemotherapy in the (neo)adjuvant or metastatic setting. We performed low-coverage genome-wide sequencing of cfDNA from plasma. Results Without prior knowledge of tumor mutations, we determined tumor fraction of cfDNA for 96.3% of patients and SCNAs for 63.9% of patients. Copy number profiles and percent genome altered were remarkably similar between metastatic and primary TNBCs. Certain SCNAs were more frequent in metastatic TNBCs relative to paired primary tumors and primary TNBCs in publicly available data sets The Cancer Genome Atlas and METABRIC, including chromosomal gains in drivers NOTCH2, AKT2, and AKT3. Prespecified cfDNA tumor fraction threshold of >/= 10% was associated with significantly worse metastatic survival (median, 6.4 v 15.9 months) and remained significant independent of clinicopathologic factors (hazard ratio, 2.14; 95% CI, 1.4 to 3.8; P .001). Conclusion We present the largest genomic characterization of metastatic TNBC to our knowledge, exclusively from cfDNA. Evaluation of cfDNA tumor fraction was feasible for nearly all patients, and tumor fraction >/= 10% is associated with significantly worse survival in this large metastatic TNBC cohort. Specific SCNAs are enriched and prognostic in metastatic TNBC, with implications for metastasis, resistance, and novel therapeutic approaches.

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Childhood high-risk neuroblastomas with MYCN gene amplification are difficult to treat effectively(1). This has focused attention on tumor-specific gene dependencies that underlie tumorigenesis and thus provide valuable targets for the development of novel therapeutics. Using unbiased genome-scale CRISPR-Cas9 approaches to detect genes involved in tumor cell growth and survival(2-6), we identified 147 candidate gene dependencies selective for MYCN-amplified neuroblastoma cell lines, compared to over 300 other human cancer cell lines. We then used genome-wide chromatin-immunoprecipitation coupled to high-throughput sequencing analysis to demonstrate that a small number of essential transcription factors-MYCN, HAND2, ISL1, PHOX2B, GATA3, and TBX2-are members of the transcriptional core regulatory circuitry (CRC) that maintains cell state in MYCN-amplified neuroblastoma. To disable the CRC, we tested a combination of BRD4 and CDK7 inhibitors, which act synergistically, in vitro and in vivo, with rapid downregulation of CRC transcription factor gene expression. This study defines a set of critical dependency genes in MYCN-amplified neuroblastoma that are essential for cell state and survival in this tumor.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

This Letter is being retracted owing to issues with Fig. 1d and Supplementary Fig. 31b, and the unavailability of original data for these figures that raise concerns regarding the integrity of the figures. Nature published two previous corrections related to this Letter(1,2). These issues in aggregate undermine the confidence in the integrity of this study. Authors Michael Foley, Monica Schenone, Nicola J. Tolliday, Todd R. Golub, Steven A. Carr, Alykhan F. Shamji, Andrew M. Stern and Stuart L. Schreiber agree with the Retraction. Authors Lakshmi Raj, Takao Ide, Aditi U. Gurkar, Anna Mandinova and Sam W. Lee disagree with the Retraction. Author Xiaoyu Li did not respond.

Drug resistance to approved systemic therapies in estrogen receptor-positive (ER+) breast cancer remains common. We hypothesized that factors present in the human tumor microenvironment (TME) drive drug resistance. Screening of a library of recombinant secreted microenvironmental proteins revealed fibroblast growth factor 2 (FGF2) as a potent mediator of resistance to anti-estrogens, mTORC1 inhibition, and phosphatidylinositol 3-kinase inhibition in ER+ breast cancer. Phosphoproteomic analyses identified ERK1/2 as a major output of FGF2 signaling via FGF receptors (FGFRs), with consequent up-regulation of Cyclin D1 and down-regulation of Bim as mediators of drug resistance. FGF2-driven drug resistance in anti-estrogen-sensitive and -resistant models, including patient-derived xenografts, was reverted by neutralizing FGF2 or FGFRs. A transcriptomic signature of FGF2 signaling in primary tumors predicted shorter recurrence-free survival independently of age, grade, stage, and FGFR amplification status. These findings delineate FGF2 signaling as a ligand-based drug resistance mechanism and highlights an underdeveloped aspect of precision oncology: characterizing and treating patients according to their TME constitution.