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in category cancer biology
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2,861 downloads cancer biology
The U.S. National Toxicology Program (NTP) has carried out extensive rodent toxicology and carcinogenesis studies of radiofrequency radiation (RFR) at frequencies and modulations used in the U.S. telecommunications industry. This report presents partial findings from these studies. The occurrences of two tumor types in male Harlan Sprague Dawley rats exposed to RFR, malignant gliomas in the brain and schwannomas of the heart, were considered of particular interest and are the subject of this report. The findings in this report were reviewed by expert peer reviewers selected by the NTP and National Institutes of Health (NIH). These reviews and responses to comments are included as appendices to this report, and revisions to the current document have incorporated and addressed these comments. When the studies are completed, they will undergo additional peer review before publication in full as part of the NTP's Toxicology and Carcinogenesis Technical Reports Series. No portion of this work has been submitted for publication in a scientific journal. Supplemental information in the form of four additional manuscripts has or will soon be submitted for publication. These manuscripts describe in detail the designs and performance of the RFR exposure system, the dosimetry of RFR exposures in rats and mice, the results to a series of pilot studies establishing the ability of the animals to thermoregulate during RFR exposures, and studies of DNA damage. (1) Capstick M, Kuster N, Kuhn S, Berdinas-Torres V, Wilson P, Ladbury J, Koepke G, McCormick D, Gauger J, and Melnick R. A radio frequency radiation reverberation chamber exposure system for rodents; (2) Yijian G, Capstick M, McCormick D, Gauger J, Horn T, Wilson P, Melnick RL, and Kuster N. Life time dosimetric assessment for mice and rats exposed to cell phone radiation; (3) Wyde ME, Horn TL, Capstick M, Ladbury J, Koepke G, Wilson P, Stout MD, Kuster N, Melnick R, Bucher JR, and McCormick D. Pilot studies of the National Toxicology Program's cell phone radiofrequency radiation reverberation chamber exposure system; (4) Smith-Roe SL, Wyde ME, Stout MD, Winters J, Hobbs CA, Shepard KG, Green A, Kissling GE, Tice RR, Bucher JR, and Witt KL. Evaluation of the genotoxicity of cell phone radiofrequency radiation in male and female rats and mice following subchronic exposure.
1,969 downloads cancer biology
Linde A Miles, Robert L. Bowman, Tiffany R Merlinsky, Isabelle S Csete, Aik Ooi, Robert Durruthy-Durruthy, Michael Bowman, Christopher Famulare, Minal A Patel, Pedro Mendez, Chrysanthi Ainali, Mani Manivannan, Sombeet Sahu, Aaron D Goldberg, Kelly Bolton, Ahmet Zehir, Raajit Rampal, Martin P Carroll, Sara E Meyer, Aaron D. Viny, Ross L. Levine
Myeloid malignancies, including acute myeloid leukemia (AML), arise from the proliferation and expansion of hematopoietic stem and progenitor cells which acquire somatic mutations. Bulk molecular profiling studies on patient samples have suggested that somatic mutations are obtained in a step-wise fashion, where mutant genes with high variant allele frequencies (VAFs) are proposed to occur early in disease development and mutations with lower VAFs are thought to be acquired later in disease progression 1-3. Although bulk sequencing informs leukemia biology and prognostication, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity and clone size, or offer definitive evidence of mutational order. To elucidate the clonal framework of myeloid malignancies, we performed single cell mutational profiling on 146 samples from 123 patients. We found AML is most commonly comprised of a small number of dominant clones, which in many cases harbor co-occurring mutations in epigenetic regulators. Conversely, mutations in signaling genes often occur more than once in distinct subclones consistent with increasing clonal diversity. We also used these data to map the clonal trajectory of each patient and found that specific mutation combinations (FLT3-ITD + NPM1c) synergize to promote clonal expansion and dominance. We combined cell surface protein expression with single cell mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our studies of clonal architecture at a single cell level provide novel insights into the pathogenesis of myeloid transformation and how clonal complexity contributes to disease progression.
1,430 downloads cancer biology
Kiyomi Morita, Feng Wang, Katharina Jahn, Jack Kuipers, Yuanqing Yan, Jairo Matthews, Latasha Little, Curtis Gumbs, Shujuan Chen, Jianhua Zhang, Xingzhi Song, Erika Thompson, Keyur Patel, Carlos Bueso-Ramos, Courtney D. DiNardo, Farhad Ravandi, Elias Jabbour, Michael Andreeff, Jorge Cortes, Marina Konopleva, Kapil Bhalla, Guillermo Garcia-Manero, Hagop Kantarjian, Niko Beerenwinkel, Nicholas Navin, P. Andrew Futreal, Koichi Takahashi
One of the pervasive features of cancer is the diversity of mutations found in malignant cells within the same tumor; a phenomenon called clonal diversity or intratumor heterogeneity. Clonal diversity allows tumors to adapt to the selective pressure of treatment and likely contributes to the development of treatment resistance and cancer recurrence. Thus, the ability to precisely delineate the clonal substructure of a tumor, including the evolutionary history of its development and the co-occurrence of its mutations, is necessary to understand and overcome treatment resistance. However, DNA sequencing of bulk tumor samples cannot accurately resolve complex clonal architectures. Here, we performed high-throughput single-cell DNA sequencing to quantitatively assess the clonal architecture of acute myeloid leukemia (AML). We sequenced a total of 556,951 cells from 77 patients with AML for 19 genes known to be recurrently mutated in AML. The data revealed clonal relationship among AML driver mutations and identified mutations that often co-occurred (e.g., NPM1/FLT3-ITD, DNMT3A/NPM1, SRSF2/IDH2, and WT1/FLT3-ITD ) and those that were mutually exclusive (e.g., NRAS/KRAS, FLT3 -D835/ITD, and IDH1/IDH2 ) at single-cell resolution. Reconstruction of the tumor phylogeny uncovered history of tumor development that is characterized by linear and branching clonal evolution patterns with latter involving functional convergence of separately evolved clones. Analysis of longitudinal samples revealed remodeling of clonal architecture in response to therapeutic pressure that is driven by clonal selection. Furthermore, in this AML cohort, higher clonal diversity (≥4 subclones) was associated with significantly worse overall survival. These data portray clonal relationship, architecture, and evolution of AML driver genes with unprecedented resolution, and illuminate the role of clonal diversity in therapeutic resistance, relapse and clinical outcome in AML.
1,097 downloads cancer biology
Ludmil B. Alexandrov, Jaegil Kim, Nicholas J. Haradhvala, Mi Ni Huang, Alvin WT Ng, Yang Wu, Arnoud Boot, Kyle R Covington, Dmitry A Gordenin, Erik N. Bergstrom, S M Ashiqul Islam, Núria López-Bigas, Leszek J. Klimczak, John R McPherson, Sandro Morganella, Radhakrishnan Sabarinathan, David A. Wheeler, Ville Mustonen, the PCAWG Mutational Signatures Working Group, Gad Getz, Steven G. Rozen, Michael R. Stratton
Somatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.
825 downloads cancer biology
Michele Olivieri, Tiffany Cho, Alejandro Álvarez-Quilón, Kejiao Li, Matthew J. Schellenberg, Michal Zimmermann, Nicole Hustedt, Silvia Emma Rossi, Salomé Adam, Henrique Melo, Anne Margriet Heijink, Guillermo Sastre-Moreno, Nathalie Moatti, Rachel Szilard, Andrea McEwan, Alexanda K. Ling, Almudena Serrano-Benitez, Tajinder Ubhi, Irene Delgado-Sainz, Michael W. Ferguson, Grant W. Brown, Felipe Cortés-Ledesma, R. Scott Williams, Alberto Martin, Dongyi Xu, Daniel Durocher
The response to DNA damage is critical for cellular homeostasis, tumor suppression, immunity and gametogenesis. In order to provide an unbiased and global view of the DNA damage response in human cells, we undertook 28 CRISPR/Cas9 screens against 25 genotoxic agents in the retinal pigment epithelium-1 (RPE1) cell line. These screens identified 840 genes whose loss causes either sensitivity or resistance to DNA damaging agents. Mining this dataset, we uncovered that ERCC6L2, which is mutated in a bone-marrow failure syndrome, codes for a canonical non-homologous end-joining pathway factor; that the RNA polymerase II component ELOF1 modulates the response to transcription-blocking agents and that the cytotoxicity of the G-quadruplex ligand pyridostatin involves trapping topoisomerase II on DNA. This map of the DNA damage response provides a rich resource to study this fundamental cellular system and has implications for the development and use of genotoxic agents in cancer therapy.
653 downloads cancer biology
We report the integrative analysis of more than 2,600 whole cancer genomes and their matching normal tissues across 39 distinct tumour types. By studying whole genomes we have been able to catalogue non-coding cancer driver events, study patterns of structural variation, infer tumour evolution, probe the interactions among variants in the germline genome, the tumour genome and the transcriptome, and derive an understanding of how coding and non-coding variations together contribute to driving individual patient's tumours. This work represents the most comprehensive look at cancer whole genomes to date. NOTE TO READERS: This is an incomplete draft of the marker paper for the Pan-Cancer Analysis of Whole Genomes Project, and is intended to provide the background information for a series of in-depth papers that will be posted to BioRixv during the summer of 2017.
588 downloads cancer biology
Pancreatic ductal adenocarcinoma (PDAC) is composed of stromal, immune and epithelial cells. Transcriptomic analysis of the epithelial compartment allows a binary classification into mainly two phenotypic subtypes, classical and basal-like. However, little is known about the intra-tumor heterogeneity of the epithelial component. Growing evidences suggest that this two side phenotypic segregation is not so clear and that both could coexist in a single tumor. In order to elucidate this hypothesis, we performed single-cell transcriptomic analyses using combinational barcoding on epithelial cells from 6 different classical PDAC obtained by Endoscopic Ultrasound (EUS) with Fine Needle Aspiration (FNA). In order to purify the epithelial compartment, PDAC were grown as Biopsy Derived Pancreatic Cancer Organoids. Single cell transcriptomic analysis allowed the identification of 4 main cell clusters present in different proportions in all tumors. Remarkably, although these tumors were classified as Classical, one of the clusters corresponded to a basal-like. These results depict the unanticipated high heterogeneity of pancreatic cancers and demonstrated that basal-like cells with a high aggressive phenotype are more widespread than expected.
572 downloads cancer biology
Homologous recombination deficiency (HRD) results in impaired double strand break repair and is a frequent driver of tumorigenesis. Here, we used a machine learning approach to develop a sensitive pan-cancer Classifier of HOmologous Recombination Deficiency (CHORD). CHORD employs genome-wide genomic footprints of somatic mutations characteristic for HRD and that discriminates BRCA1- and BRCA2-subtypes. Analysis of a metastatic pan-cancer cohort of 3,504 patients revealed HRD to occur at a frequency of 6% with highest rates for ovarian cancer (30%), comparable frequencies for breast, pancreatic and prostate cancer (12-13%) and incidental cases in other cancer types. Ovarian and breast cancer were equally driven by BRCA1- and BRCA2-type HRD, whereas for prostate, pancreatic and urinary tract cancers BRCA2-type HRD was predominant. Biallelic inactivation of BRCA1, BRCA2, RAD51C and PALB2 were found as the most common genetic causes of HRD (60% of all CHORD-HRD cases), with RAD51C and PALB2 inactivation resulting in BRCA2-type HRD. Loss of heterozygosity (LOH) was found to be the main inactivating mechanism in ovarian, breast and pancreatic cancer, whereas for prostate cancer deep deletions (primarily of BRCA2) are also a major cause. From the remaining 40% of CHORD-HRD patients, 35% had a monoallelic mutation in one of the HRD associated genes, suggesting that the second allele could be inactivated by epigenetic or regulatory mechanisms. For only 5% of CHORD-HRD patients, no mutations were identified that could explain the HRD phenotype. Taken together, our results demonstrate that broad genomics-based HRD testing is valuable for cancer diagnostics and could be used for patient stratification towards treatment with e.g. poly ADP-ribose polymerase inhibitors (PARPi).
555 downloads cancer biology
The WNT pathway is a fundamental regulator of intestinal homeostasis and hyperactivation of WNT signaling is the major oncogenic driver in colorectal cancer (CRC). To date, there are no described mechanisms that bypass WNT dependence in intestinal tumors. Here, we show that while WNT suppression blocks tumor growth in most organoid and in vivo CRC models, the accumulation of CRC-associated genetic alterations enables drug resistance and WNT-independent growth. In intestinal epithelial cells harboring mutations in KRAS or BRAF, together with disruption of p53 and SMAD4, transient TGFβ exposure drives YAP/TAZ-dependent transcriptional reprogramming and lineage reversion. Acquisition of embryonic intestinal identity is accompanied by a permanent loss of adult intestinal lineages, and long-term WNT-independent growth. This work delineates genetic and microenvironmental factors that drive WNT inhibitor resistance, identifies a new mechanism for WNT-independent CRC growth and reveals how integration of associated genetic alterations and extracellular signals can overcome lineage-dependent oncogenic programs.
555 downloads cancer biology
Chenchen Pan, Oliver Schoppe, Arnaldo Parra-Damas, Ruiyao Cai, Mihail Ivilinov Todorov, Gabor Gondi, Bettina von Neubeck, Alireza Ghasemi, Madita Alice Reimer, Javier Coronel, Boyan K. Garvalov, Bjoern Menze, Reinhard Zeidler, Ali Ertürk
Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer.
531 downloads cancer biology
To understand the architecture of a tissue it is necessary to know both the cell populations and their physical relationships to one another. Single-cell RNA-Seq (scRNA-Seq) has made significant progress towards the unbiased and systematic characterization of the cell populations within a tissue, as well as their cellular states, by studying hundreds and thousands of cells in a single experiment. However, the characterization of the spatial organization of individual cells within a tissue has been more elusive. The recently introduced "spatial transcriptomics" method (ST) reveals the spatial pattern of gene expression within a tissue section at a resolution of one thousand 100 µm spots, each capturing the transcriptomes of ~10-20 cells. Here, we present an approach for the integration of scRNA-Seq and ST data generated from the same sample of pancreatic cancer tissue. Using markers for cell-types identified by scRNA-Seq, we robustly deconvolved the cell-type composition of each ST spot, to generate a spatial atlas of cell proportions across the tissue. Studying this atlas, we found that distinct spatial localizations accompany each of the three cancer cell populations that we identified. Strikingly, we find that subpopulations defined in the scRNA-Seq data also exhibit spatial segregation in the atlas, suggesting such an atlas may be used to study the functional attributes of subpopulations. Our results provide a framework for creating a tumor atlas by mapping single-cell populations to their spatial region, as well as the inference of cell architecture in any tissue.
501 downloads cancer biology
Steven M. Corsello, Rohith T Nagari, Ryan D Spangler, Jordan Rossen, Mustafa Kocak, Jordan G Bryan, Ranad Humeidi, David Peck, Xiaoyun Wu, Andrew A Tang, Vickie M Wang, Samantha A Bender, Evan Lemire, Rajiv Narayan, Philip Montgomery, Uri Ben-David, Yejia Chen, Matthew G Rees, Nicholas J. Lyons, James M. McFarland, Bang T Wong, Li Wang, Nancy Dumont, Patrick J. O’Hearn, Eric Stefan, John G Doench, Heidi Greulich, Matthew Meyerson, Francisca Vazquez, Aravind Subramanian, Jennifer A Roth, Joshua A. Bittker, Jesse S. Boehm, Christopher C Mader, Aviad Tsherniak, Todd R. Golub
Anti-cancer uses of non-oncology drugs have been found on occasion, but such discoveries have been serendipitous and rare. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. To accomplish this, we used PRISM, which involves drug treatment of molecularly barcoded cell lines in pools. Relative barcode abundance following treatment thus reflects viability of each cell line. We found that an unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines. Moreover, the killing activity of the majority of these drugs was predictable based on the molecular features of the cell lines. Follow-up of several of these compounds revealed novel mechanisms. For example, compounds that kill by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing is dependent on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which kills cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, whose killing is dependent on high expression of the multi-drug resistance gene ABCB1. These results illustrate the potential of the PRISM drug repurposing resource as a starting point for new oncology therapeutic development. The resource is available at https://depmap.org.
445 downloads cancer biology
Moritz Gerstung, Clemency Jolly, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez Rosado, Daniel Rosebrock, Thomas J Mitchell, Yulia Rubanova, Pavana Anur, Kaixian Yu, Maxime Tarabichi, Amit G. Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vázquez-García, Kerstin Haase, Lara Jerman, Subhajit Sengupta, Geoff Macintyre, Salem Malikić, Nilgun Donmez, Dimitri G. Livitz, Marek Cmero, Jonas Demeulemeester, Steven E Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. L. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S. Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Yuan, Wenyi Wang, Quaid D. Morris, Paul T. Spellman, David C Wedge, Peter Van Loo, on behalf of the PCAWG Evolution and Heterogeneity Working Group, the PCAWG network
Cancer develops through a process of somatic evolution. Here, we reconstruct the evolutionary history of 2,778 tumour samples from 2,658 donors spanning 39 cancer types. Characteristic copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma, are found amongst the earliest events in tumour evolution. The early phases of oncogenesis are driven by point mutations in a restricted set of cancer genes, often including biallelic inactivation of tumour suppressors. By contrast, increased genomic instability, a more than three-fold diversification of driver genes, and an acceleration of mutational processes are features of later stages. Clock-like mutations yield estimates for whole genome duplications and subclonal diversification in chronological time. Our results suggest that driver mutations often precede diagnosis by many years, and in some cases decades. Taken together, these data reveal common and divergent trajectories of cancer evolution, pivotal for understanding tumour biology and guiding early cancer detection.
420 downloads cancer biology
In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue. To define differences in cellular composition between the normal colon and colorectal cancer, and to map potential cellular interactions between tumor cells and their microenvironment, we profiled transcriptomes of >50,000 single cells from tumors and matched normal tissues of eight colorectal cancer patients. We find that tumor formation is accompanied by changes in epithelial, immune and stromal cell compartments in all patients. In the epithelium, we identify a continuum of five tumor-specific stem cell and progenitor-like populations, and persistent multilineage differentiation. We find multiple stromal and immune cell types to be consistently expanded in tumor compared to the normal colon, including cancer-associated fibroblasts, pericytes, monocytes, macrophages and a subset of T cells. We identify epithelial tumor cells and cancer-associated fibroblasts as relevant for assigning colorectal cancer consensus molecular subtypes. Our survey of growth factors in the tumor microenvironment identifies cell types responsible for increased paracrine EGFR, MET and TGF-β signaling in tumor tissue compared to the normal colon. We show that matched colorectal cancer organoids retain cell type heterogeneity, allowing to define a distinct differentiation trajectory encompassing stem and progenitor-like tumor cells. In summary, our single-cell analyses provide insights into cell types and signals shaping colorectal cancer cell plasticity.
420 downloads cancer biology
The glioblastoma (GBM) recurrence rate is high, despite multimodal treatment including surgery, radiotherapy, chemotherapy, and immunotherapy. Most recurrences occur at the resection margin that is located outside the GBM contrast-enhancing region (C region) of magnetic resonance imaging. However, the nature of the GBM cells that lie outside the C region is unclear. We used single-cell RNA sequencing (scRNA-seq) to compare 12 samples taken from inside and outside the C region from four patients with GBM and identified a cluster of GBM cells outside the C region that exhibited fragmented CNVs in chromosomes such as 1, 10, 12 and 19 (herein termed CNV 4). A transcription factor–transcription cofactor interaction network was constructed to uncover the transcriptional regulatory mechanism of these CNV 4 GBM cells that had prognostic significance (p < 0.05). Furthermore, a sub-cluster of these CNV 4 GBM cells possessed stem cell-like properties and had tumorigenic potential. In parallel, we analyzed peripheral blood mononuclear cells (PBMCs) from four patients with GBM, three patients with epilepsy and three healthy volunteers by scRNA-seq. We identified a novel subtype of proliferative immune cells only in patients with GBM. Overall, our findings indicate that CNV 4 cells might contribute to GBM recurrence and proliferative circulating immune cells are specific to patients with GBM. This study sheds light on a neglected aspect of GBM, and opens new avenues to explore GBM recurrence and immunotherapy. Significance We show that a subset of GBM cells outside the C region possess the properties of stem cell and tumorigenesis potential, which might be responsible for cancer recurrence. Besides, proliferative lymphocytes are specific to the PBMCs of patients with GBM, which could help to develop novel immunotherapy.
391 downloads cancer biology
Gil Friedman, Oshrat Levi-Galibov, Eyal David, Chamutal Bornstein, Amir Giladi, Maya Dadiani, Avi Mayo, Coral Halperin, Meirav Pevsner-Fischer, Hagar Lavon, Reinat Nevo, Yaniv Stein, H. Raza Ali, Carlos Caldas, Einav Nili-Gal-Yam, Uri Alon, Ido Amit, Ruth Scherz-Shouval
Tumors are supported by cancer-associated fibroblasts (CAFs). CAFs are heterogeneous and carry out distinct cancer-associated functions. Understanding the full repertoire of CAFs and their dynamic changes could improve the precision of cancer treatment. CAFs are usually analyzed at a single time-point using specific markers, and it is therefore unclear whether CAFs display plasticity as tumors evolve. Here, we analyze thousands of CAFs using index and transcriptional single-cell sorting, at several time-points along breast tumor progression in mice, uncovering distinct subpopulations. Strikingly, the transcriptional programs of these subpopulations change over time and in metastases, transitioning from an immune-regulatory program to wound healing and antigen-presentation programs, indicating that CAFs and their functions are dynamic. Two main CAF subpopulations are also found in human breast tumors, where their ratio is associated with disease outcome across subtypes, and is particularly correlated with BRCA mutations in triple-negative breast cancer. These findings indicate that the repertoire of CAFs changes over time in breast cancer progression, with direct clinical implications.
382 downloads cancer biology
Visual analysis of histopathology slides of lung cell tissues is one of the main methods used by pathologists to assess the stage, types and sub-types of lung cancers. Adenocarcinoma and squamous cell carcinoma are two most prevalent sub-types of lung cancer, but their distinction can be challenging and time-consuming even for the expert eye. In this study, we trained a deep learning convolutional neural network (CNN) model (inception v3) on histopathology images obtained from The Cancer Genome Atlas (TCGA) to accurately classify whole-slide pathology images into adenocarcinoma, squamous cell carcinoma or normal lung tissue. Our method slightly outperforms a human pathologist, achieving better sensitivity and specificity, with ~0.97 average Area Under the Curve (AUC) on a held-out population of whole-slide scans. Furthermore, we trained the neural network to predict the ten most commonly mutated genes in lung adenocarcinoma. We found that six of these genes - STK11, EGFR, FAT1, SETBP1, KRAS and TP53 - can be predicted from pathology images with an accuracy ranging from 0.733 to 0.856, as measured by the AUC on the held-out population. These findings suggest that deep learning models can offer both specialists and patients a fast, accurate and inexpensive detection
375 downloads cancer biology
Jantzen Sperry, Janel E Le Belle, Michael C Condro, Lea Guo, Daniel Braas, Nathan Vanderveer-Harris, Kristen K.O. Kim, Whitney B Pope, Ajit S. Divakaruni, Albert Lai, Heather Christofk, Harley I Kornblum
Glioblastoma (GBM) metabolism has traditionally been characterized by a dependence on aerobic glycolysis, prompting use of the ketogenic diet as a potential therapy. We observed growth-promoting effects on U87 GBM of both ketone body and fatty acid (FA) supplementation under physiological glucose conditions. An in vivo assessment of the unrestricted ketogenic diet surprisingly resulted in increased tumor growth and decreased animal survival. These effects are abrogated by FAO inhibition using knockdown of carnitine palmitoyltransferase 1 (CPT1). Primary patient GBM cultures revealed significant utilization of FAO regardless of tumorigenic mutational status and decreased proliferation, increased apoptosis, and elevated mitochondrial ROS production with CPT1 inhibition. Metabolomic tracing with 13C-labeled fatty acids showed significant FA utilization within the TCA cycle, indicating that FAO is used for both bioenergetics and production of key intermediates. These data demonstrate important roles for FA and ketone body metabolism that could serve to improve targeted therapies in GBM.
355 downloads cancer biology
Ashley Maynard, Caroline E McCoach, Julia K Rotow, Lincoln Harris, Franziska Haderk, Lucas Kerr, Elizabeth A Yu, Erin L Schenk, Weilun Tan, Alexander Zee, Michelle Tan, Philippe Gui, Tasha Lea, Wei Wu, Anatoly Urisman, Kirk Jones, Rene Sit, Pallav K Kolli, Eric Seeley, Yaron Gesthalter, Daniel D Le, Kevin A Yamauchi, David Naeger, Nicholas J Thomas, Anshal Gupta, Mayra Gonzalez, Hien Do, Lisa Tan, Rafael Gomez-Sjoberg, Matthew Gubens, Thierry Jahan, Johannes R Kratz, David Jablons, Norma Neff, Robert C. Doebele, Jonathan Weissman, Collin M. Blakely, Spyros Darmanis, Trever G Bivona
Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNAseq) of metastatic lung cancer was performed using 44 tumor biopsies obtained longitudinally from 27 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNAseq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNAseq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.
349 downloads cancer biology
Diar Aziz, Neil Portman, Kristine J. Fernandez, Christine Lee, Sarah Alexandrou, Alba Llop-Guevara, Aliza Yong, Ashleigh Wilkinson, C Marcelo Sergio, Danielle Ferraro, Dariush Etemadmoghadam, David Bowtell, kConFab Investigators, Violeta Serra, Paul Waring, Elgene Lim, C. Elizabeth Caldon
Basal-like breast cancers (BLBC) are aggressive breast cancers that respond poorly to targeted therapies and chemotherapies. In order to define therapeutically targetable subsets of BLBC we examined two markers: cyclin E1 and BRCA1 loss. In high grade serous ovarian cancer (HGSOC) these markers are mutually exclusive, and define therapeutic subsets. We tested the same hypothesis for BLBC. Using a BLBC cohort enriched for BRCA1 loss, we identified convergence between BRCA1 loss and high cyclin E1 expression, in contrast to HGSOC in which CCNE1 amplification drives increased cyclin E1 gene expression. Instead, BRCA1 loss stabilized cyclin E1 during the cell cycle. Using siRNA we showed that BRCA1 loss leads to stabilization of cyclin E1 by reducing phospho-cyclin E1-T62, and conversely the overexpression of BRCA1 increased phospho-T62. Mutation of cyclin E1-T62 to alanine increased cyclin E1 stability. We showed that tumors with high cyclin E1/BRCA1 mutation in the BLBC cohort had decreased phospho-T62, supporting this hypothesis. Since cyclin E1/CDK2 protects cells from DNA damage and cyclin E1 is elevated in BRCA1 mutant cancers, we hypothesized that CDK2 inhibition would sensitize these cancers to PARP inhibition. CDK2 inhibition induced DNA damage and synergized with PARP inhibitors to reduce cell viability in BRCA1 mutated cell lines. Treatment of BLBC patient-derived xenograft models with combination PARP and CDK2 inhibition led to tumor regression and increased survival. We conclude that BRCA1 status and high cyclin E1 have potential as predictive biomarkers to dictate the therapeutic use of combination CDK inhibitors/PARP inhibitors in BLBC.
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