Spatially organized multicellular immune hubs in human colorectal cancer.

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd individuals. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across tumors from affected individuals and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T cell-attracting chemokines. By identifying interacting cellular programs, we reveal the logic underlying spatially organized immune-malignant cell networks.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

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.

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies.

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

A Curated Resource for Phosphosite-specific Signature Analysis.

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset.

The most common mutation in human melanoma, BRAF(V600E), activates the serine/threonine kinase BRAF and causes excessive activity in the mitogen-activated protein kinase pathway. BRAF(V600E) mutations are also present in benign melanocytic naevi, highlighting the importance of additional genetic alterations in the genesis of malignant tumours. Such changes include recurrent copy number variations that result in the amplification of oncogenes. For certain amplifications, the large number of genes in the interval has precluded an understanding of the cooperating oncogenic events. Here we have used a zebrafish melanoma model to test genes in a recurrently amplified region of chromosome 1 for the ability to cooperate with BRAF(V600E) and accelerate melanoma. SETDB1, an enzyme that methylates histone H3 on lysine 9 (H3K9), was found to accelerate melanoma formation significantly in zebrafish. Chromatin immunoprecipitation coupled with massively parallel DNA sequencing and gene expression analyses uncovered genes, including HOX genes, that are transcriptionally dysregulated in response to increased levels of SETDB1. Our studies establish SETDB1 as an oncogene in melanoma and underscore the role of chromatin factors in regulating tumorigenesis.

Distinct genetic profiles of extracranial and intracranial acral melanoma metastases.

BACKGROUND: There is limited knowledge of the genetic alterations in acral melanoma metastases at different anatomic sites. Here, we characterized the genetic abnormalities of metastases in a 51-year-old man with stage IIIC heel melanoma who developed concomitant brain and cutaneous metastases in spite of multiple treatment modalities. METHODS: Melanoma cells were isolated following palliative resection of the patient's cortical tumor and biopsy of cutaneous thigh metastasis. Mutational analysis using polymerase chain reaction amplification and BLAST, as well as exome sequencing (160 Mb coverage) was performed on the tumors, cell lines generated thereof and normal lymph nodes. RESULTS: All specimens had neuroblastoma RAS viral oncogene homolog Q61K mutations. There was a 40-fold higher somatic mutation frequency in the brain metastasis compared to the cutaneous metastasis. The former showed truncations of DNA mismatch repair genes (MLH1 and MSH2), and non-canonical BRAF (v-raf murine sarcoma viral oncogene homolog B1), PIK3CA and NF-1 mutations not observed in the extracranial lesion. Genomic profiling of each cell line was concordant with the respective original tumor tissue. CONCLUSIONS: We present the mutational differences between brain and cutaneous acral melanoma metastases in a patient with concomitant lesions. Further genetic and functional studies are needed to understand the biology of metastatic disease appearing at different sites.

A cellular and spatial atlas of TP53 -associated tissue remodeling in lung adenocarcinoma.

TP53 is the most frequently mutated gene across many cancers and is associated with shorter survival in lung adenocarcinoma (LUAD). To define how TP53 mutations affect the LUAD tumor microenvironment (TME), we constructed a multi-omic cellular and spatial tumor atlas of 23 treatment-naïve human lung tumors. We found that TP53 -mutant ( TP53 mut ) malignant cells lose alveolar identity and upregulate highly proliferative and entropic gene expression programs consistently across resectable LUAD patient tumors, genetically engineered mouse models, and cell lines harboring a wide spectrum of TP53 mutations. We further identified a multicellular tumor niche composed of SPP1 + macrophages and collagen-expressing fibroblasts that coincides with hypoxic, pro-metastatic expression programs in TP53 mut tumors. Spatially correlated angiostatic and immune checkpoint interactions, including CD274 - PDCD1 and PVR - TIGIT , are also enriched in TP53 mut LUAD tumors, which may influence response to checkpoint blockade therapy. Our methodology can be further applied to investigate mutation-specific TME changes in other cancers.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity.

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF).

Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single-cell profiling methods, such as single-cell RNA-seq (scRNA-seq), and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single-cell profiles provide rich molecular information, they can be challenging to collect routinely and do not have spatial resolution. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage adversarial machine learning to develop SCHAF (Single-Cell omics from Histology Analysis Framework), to generate a tissue sample's spatially-resolved single-cell omics dataset from its H&E histology image. We demonstrate SCHAF on two types of human tumors-from lung and metastatic breast cancer-training with matched samples analyzed by both sc/snRNA-seq and by H&E staining. SCHAF generated appropriate single-cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct MERFISH measurements. SCHAF opens the way to next-generation H&E2.0 analyses and an integrated understanding of cell and tissue biology in health and disease.

Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems.

Methods for highly multiplexed RNA imaging are limited in spatial resolution and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to the mouse brain, which yielded the readout of thousands of genes, including splice variants. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in the neurons of the mouse hippocampus, revealing patterns across multiple cell types, layer-specific cell types across the mouse visual cortex, and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus, ExSeq enables highly multiplexed mapping of RNAs from nanoscale to system scale.

A single-cell and spatial atlas of autopsy tissues reveals pathology and cellular targets of SARS-CoV-2.

The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.

A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Author Correction: A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Randomized trial of 10 days of decitabine ± bortezomib in untreated older patients with AML: CALGB 11002 (Alliance).

Novel treatment strategies are needed for older patients with acute myeloid leukemia (AML). This randomized phase 2 trial compared the efficacy and safety of 20 mg/m2 of IV decitabine on days 1 to 10 alone (arm A) with those of 1.3 mg/m2 of subcutaneous bortezomib (arm B) on days 1, 4, 8, and 11 for up to 4 10-day cycles followed by monthly 5-day cycles. Previously untreated AML patients age ≥60 years (excluding those with FLT3 mutations and favorable-risk cytogenetics) without restrictions in performance status (PS) or organ function were eligible. Median age was 72.4 years (range, 60.5-92.3 years); 31 patients (19%) had baseline PS ≥2, 35 (22%) had an antecedent hematological disorder, 58 had (39%) adverse cytogenetics, and 7 (5%) and 23 (14%) had abnormal cardiac or renal function. There were no statistically significant differences in overall survival (OS) or responses between the 2 treatment arms. The overall response rate (complete remission + complete remission with incomplete blood count recovery) was 39% (n = 64), with median OS of 9.3 months. Nineteen responders (31%) underwent allogeneic stem cell transplantation. The most common adverse event was febrile neutropenia, and there were no unexpected toxicities. Adding bortezomib to decitabine did not improve outcomes, but responses were better than those in previous trials using 5-day decitabine cycles. This trial was registered at www.clinicaltrials.gov as #NCT01420926.

Viral-mediated coexpression of Pdx1 and p48 regulates exocrine pancreatic differentiation in mouse ES cells.

Embryonic stem cells (ES) can spontaneously activate a pancreatic differentiation program in vitro, although with low efficiency. The aim was to improve such process by using viral mediated gene transduction. In this study, we have examined the suitability of using viral vectors to express key transcriptional factors involved in pancreatic development. ES cell lines that constitutively express Pdx1, a homeodomain protein involved in both exocrine and endocrine pancreatic development and differentiation, were established using a lentiviral vector. These cells were additionally infected with an adenovirus expressing p48, a bHLH factor that is also crucial for pancreatic development and acinar differentiation. Quantitative RT-PCR analysis demonstrated an increase in the expression of exocrine genes, including those coding for both digestive enzymes and transcription factors. Immunocytochemical staining also revealed an increase in the number of amylase-expressing cell clusters. However, other important genes involved in acinar cell maturation (i.e., Mist1) were not modulated under these conditions, suggesting that the cells display features of immature exocrine cells or because of an uncoupled gene expression of the exocrine differentiation program. Importantly, this effect was selective for the acinar lineage as the expression of a large set of endocrine markers remained unchanged. Therefore, combined expression of key genes involved in pancreatic development may be a promising approach to generate mature pancreatic exocrine cells.

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.