Background: The ability to identify genetic alterations in cancers is essential for precision medicine however, surgical approaches to obtain brain tumor tissue are invasive. Profiling circulating-tumor DNA (ctDNA) in liquid biopsies has emerged as a promising approach to avoid invasive procedures. Here, we systematically evaluated the feasibility of profiling pediatric brain tumors using ctDNA obtained from plasma, cerebrospinal fluid (CSF) and urine.

Methods: We prospectively collected 564 specimens (257 blood, 240 urine, 67 CSF samples) from 258 patients across all histopathologies. We performed ultra-low pass whole-genome sequencing (ULP-WGS) to assess copy number variations and estimate tumor fraction, and developed a pediatric CNS tumor hybrid-capture panel for deep sequencing of specific mutations and fusions.

Results: ULP-WGS detected copy-number alterations in 9/46 (20%) CSF, 3/230 (1.3%) plasma, 0/153 urine samples. Sequencing detected alterations in 3/10 (30%) CSF, 2/74 (2.7%) plasma, 0/2 urine samples. The only positive results were in high-grade tumors. However, most samples had insufficient somatic mutations (median 1, range 0-39) discoverable by the sequencing panel to provide sufficient power to detect tumor fractions of greater than 0.1%.

Conclusions: Children with brain tumors harbor very low levels of ctDNA in blood, CSF and urine, with CSF having the most DNA detectable. Molecular profiling is feasible in a small subset of high-grade tumors. The level of clonal aberrations per genome is low in most of tumors, posing a challenge for detection using whole genome or even targeted sequencing methods. Substantial challenges therefore remain to genetically characterize pediatric brain tumors from liquid biopsies.

Keywords: Circulating tumor DNA; Hybrid capture sequencing; ULP-WGS; liquid biopsy; pediatric brain tumors.

Accurate DNA sequencing is crucial in biomedicine. Underlying the most accurate methods is the assumption that a mutation is true if altered bases are present on both strands of the DNA duplex. We now show that this assumption can be wrong. We establish that current methods to prepare DNA for sequencing, via 'End Repair/dA-Tailing,' may substantially resynthesize strands, leading amplifiable lesions or alterations on one strand to become indiscernible from true mutations on both strands. Indeed, we discovered that 7-17% and 32-57% of interior 'duplex base pairs' from cell-free DNA and formalin-fixed tumor biopsies, respectively, could be resynthesized in vitro and potentially introduce false mutations. To address this, we present Duplex-Repair, and show that it limits interior duplex base pair resynthesis by 8- to 464-fold, rescues the impact of induced DNA damage, and affords up to 8.9-fold more accurate duplex sequencing. Our study uncovers a major Achilles' heel in sequencing and offers a solution to restore high accuracy.

Cancer dependency maps, which use CRISPR/Cas9 depletion screens to profile the landscape of genetic dependencies in hundreds of cancer cell lines, have identified context-specific dependencies that could be therapeutically exploited. An ideal therapy is both lethal and precise, but these depletion screens cannot readily distinguish between gene effects that are cytostatic or cytotoxic. Here, we employ a diverse panel of functional genomic screening assays to identify NXT1 as a selective and rapidly lethal in vivo-relevant genetic dependency in MYCN-amplified neuroblastoma. NXT1 heterodimerizes with NXF1 and together they form the principle mRNA nuclear export machinery. We describe a previously unrecognized mechanism of synthetic lethality between NXT1 and its paralog NXT2: their common essential binding partner NXF1 is lost only in the absence of both. We propose a potential therapeutic strategy for tumor-selective elimination of a protein that, if targeted directly, is expected to cause widespread toxicity.

Brain metastases are refractory to therapies that control systemic disease in patients with human epidermal growth factor receptor 2 (HER2+) breast cancer, and the brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for brain metastatic breast cancer growth may introduce liabilities that can be exploited for therapy. Here, we assessed how metabolism differs between breast tumors in brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in brain. We determine that this phenotype is an adaptation to decreased lipid availability in brain relative to other tissues, resulting in a site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase (FASN) reduces HER2+ breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies.

Exciting therapeutic targets are emerging from CRISPR-based screens of high mutational-burden adult cancers. A key question, however, is whether functional genomic approaches will yield new targets in pediatric cancers, known for remarkably few mutations, which often encode proteins considered challenging drug targets. To address this, we created a first-generation pediatric cancer dependency map representing 13 pediatric solid and brain tumor types. Eighty-two pediatric cancer cell lines were subjected to genome-scale CRISPR-Cas9 loss-of-function screening to identify genes required for cell survival. In contrast to the finding that pediatric cancers harbor fewer somatic mutations, we found a similar complexity of genetic dependencies in pediatric cancer cell lines compared to that in adult models. Findings from the pediatric cancer dependency map provide preclinical support for ongoing precision medicine clinical trials. The vulnerabilities observed in pediatric cancers were often distinct from those in adult cancer, indicating that repurposing adult oncology drugs will be insufficient to address childhood cancers.

Although genomic analyses predict many noncanonical open reading frames (ORFs) in the human genome, it is unclear whether they encode biologically active proteins. Here we experimentally interrogated 553 candidates selected from noncanonical ORF datasets. Of these, 57 induced viability defects when knocked out in human cancer cell lines. Following ectopic expression, 257 showed evidence of protein expression and 401 induced gene expression changes. Clustered regularly interspaced short palindromic repeat (CRISPR) tiling and start codon mutagenesis indicated that their biological effects required translation as opposed to RNA-mediated effects. We found that one of these ORFs, G029442-renamed glycine-rich extracellular protein-1 (GREP1)-encodes a secreted protein highly expressed in breast cancer, and its knockout in 263 cancer cell lines showed preferential essentiality in breast cancer-derived lines. The secretome of GREP1-expressing cells has an increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth-inhibitory effect of GREP1 knockout. Our experiments suggest that noncanonical ORFs can express biologically active proteins that are potential therapeutic targets.

Selective targeting of aneuploid cells is an attractive strategy for cancer treatment¹. However, it is unclear whether aneuploidy generates any clinically relevant vulnerabilities in cancer cells. Here we mapped the aneuploidy landscapes of about 1,000 human cancer cell lines, and analysed genetic and chemical perturbation screens^2-9 to identify cellular vulnerabilities associated with aneuploidy. We found that aneuploid cancer cells show increased sensitivity to genetic perturbation of core components of the spindle assembly checkpoint (SAC), which ensures the proper segregation of chromosomes during mitosis¹⁰. Unexpectedly, we also found that aneuploid cancer cells were less sensitive than diploid cells to short-term exposure to multiple SAC inhibitors. Indeed, aneuploid cancer cells became increasingly sensitive to inhibition of SAC over time. Aneuploid cells exhibited aberrant spindle geometry and dynamics, and kept dividing when the SAC was inhibited, resulting in the accumulation of mitotic defects, and in unstable and less-fit karyotypes. Therefore, although aneuploid cancer cells could overcome inhibition of SAC more readily than diploid cells, their long-term proliferation was jeopardized. We identified a specific mitotic kinesin, KIF18A, whose activity was perturbed in aneuploid cancer cells. Aneuploid cancer cells were particularly vulnerable to depletion of KIF18A, and KIF18A overexpression restored their response to SAC inhibition. Our results identify a therapeutically relevant, synthetic lethal interaction between aneuploidy and the SAC.

n the originally published version of this paper, the CHMP4B sgRNA sequence listed in the STAR Methods section was incorrect. Theincorrect sequence was 50-TCGATGGCACAAGCCATGAA, which is an sgRNA designed to targetCHMP2A. The correctCHMP4B-targeting sgRNA sequence that was used in the experiments for this paper is 50- TATCAACCATCGAGTTCCAG. This change does notaffect the data or conclusions of the study and now appears in the paper online.

The authors apologize for any inconvenience this error may have caused.

 

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate. Information-rich assays, such as gene-expression profiling, have generally not permitted efficient profiling of a given perturbation across multiple cellular contexts. Here, we develop MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines. We combine it with Cell Hashing to further multiplex additional experimental conditions, such as post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and enable prediction of long-term cell viability from short-term transcriptional responses to treatment.