Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 62,933 bioRxiv papers from 279,142 authors.
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in category cancer biology
2,037 results found. For more information, click each entry to expand.
3,811 downloads cancer biology
Stefan C. Dentro, Ignaty Leshchiner, Kerstin Haase, Maxime Tarabichi, Jeff Wintersinger, Amit Deshwar, Kaixian Yu, Yulia Rubanova, Geoff Macintyre, Ignacio Vázquez-García, Kortine Kleinheinz, Dimitri G. Livitz, Salem Malikic, Nilgun Donmez, Subhajit Sengupta, Jonas Demeulemeester, Pavana Anur, Clemency Jolly, Marek Cmero, Daniel Rosebrock, Steven E Schumacher, Yu Fan, Matthew Fittall, Ruben M. Drews, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Hongtu Zhu, David J. Adams, Gad Getz, Paul C. Boutros, Marcin Imielinski, Rameen Beroukhim, S. Cenk Sahinalp, Yuan Ji, Martin Peifer, Inigo Martincorena, Florian Markowetz, Ville Mustonen, Ke Yuan, Moritz Gerstung, Paul T. Spellman, Wenyi Wang, Quaid D Morris, David C. Wedge, Peter Van Loo
Continued evolution in cancers gives rise to intra-tumour heterogeneity (ITH), which is a major mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. Here, we extensively characterise ITH across 2,778 cancer whole genome sequences from 36 cancer types. We demonstrate that nearly all tumours (95.1%) with sufficient sequencing depth contain evidence of recent subclonal expansions and most cancer types show clear signs of positive selection in both clonal and subclonal protein coding variants. We find distinctive subclonal patterns of driver gene mutations, fusions, structural variation and copy-number alterations across cancer types. Dynamic, tumour-type specific changes of mutational processes between subclonal expansions shape differences between clonal and subclonal events. Our results underline the importance of ITH and its drivers in tumour evolution and provide an unprecedented pan-cancer resource of extensively annotated subclonal events, laying a foundation for future cancer genomic studies.
3,810 downloads cancer biology
Background: Ketogenic diets (KDs) have gained popularity among patients and researchers alike due to their putative anti-tumor mechanisms. However, the question remains which conclusions can be drawn from the available human data thus far concerning the safety and efficacy of KDs for cancer patients. Methods: A realist review utilizing a matrix-analytical approach was conducted according the RAMESES publication standards. All available human studies were systematically analyzed and supplemented with results from animal studies. Evidence and confirmation were treated as separate concepts. Results: 29 animal and 24 human studies were included in the analysis. The majority of animal studies (72%) yielded evidence for an anti-tumor effect of KDs. Evidential support for such effects in humans was weak and limited to individual cases, but a probabilistic argument shows that the available data strengthen the belief in the anti-tumor effect hypothesis at least for some individuals. Evidence for pro-tumor effects was lacking completely. Conclusions: Feasibility of KDs for cancer patients has been shown in various contexts. The probability of achieving an anti-tumor effect seems greater than that of causing serious side effects when offering KDs to cancer patients. Future controlled trials would provide stronger evidence for or against the anti-tumor effect hypothesis.
3,653 downloads cancer biology
Robert J. Nichols, Franziska Haderk, Carlos Stahlhut, Christopher J. Schulze, Golzar Hemmati, David Wildes, Christos Tzitzilonis, Kasia Mordec, Abby Marquez, Jason Romero, Daphne Hsieh, Gert Kiss, Elena S. Koltun, Adrian L. Gill, Mallika Singh, Mark A. Goldsmith, Jacqueline A. M. Smith, Trever G. Bivona
Oncogenic alterations in the RAS-RAF-MEK-ERK pathway, including mutant forms of KRAS, BRAF, and loss of the tumor suppressor and RAS GTPase-activating protein (GAP) NF1, drive the growth of a wide spectrum of human cancers. While BRAF and MEK inhibitors are effective in many patients with oncogenic BRAF V600E, there are no effective targeted therapies for individuals with cancers driven by other pathway alterations, including oncogenic KRAS, non-V600E BRAF, and NF1 loss. Here, we show that targeting the PTPN11/SHP2 phosphatase with a novel small molecule allosteric inhibitor is effective against cancers bearing nucleotide-cycling oncogenic RAS (e.g. KRAS G12C), RAS-GTP dependent oncogenic BRAF (e.g. class 3 BRAF mutants), or NF1 loss in multiple preclinical models in vitro and in vivo. SHP2 inhibition suppressed the levels of RAS-GTP and phosphorylated ERK in these models and induced growth inhibition. Expression of a constitutively active mutant of the RAS guanine nucleotide exchange factor (GEF) SOS1 rescued cells from the effects of SHP2 inhibition, suggesting that SHP2 blockade decreases oncogenic RAS-RAF-MEK-ERK signaling by disrupting SOS1-mediated RAS-GTP loading. Our findings illuminate a critical function for SHP2 in promoting oncogenic RAS activation and downstream signaling in cancers with nucleotide-cycling oncogenic RAS, RAS-GTP dependent oncogenic BRAF, and NF1 loss. SHP2 inhibition thus represents a rational, biomarker-driven therapeutic strategy to be tested in patients with cancers of diverse origins bearing these oncogenic drivers and for which current treatments are largely ineffective.
3,540 downloads cancer biology
Anna S. Nam, Kyu-Tae Kim, Ronan Chaligne, Franco Izzo, Chelston Ang, Ghaith Abu-Zeinah, Nathaniel D. Omans, Justin Taylor, Alessandro Pastore, Alicia Alonso, Marisa Mariani, Juan R. Cubillos-Ruiz, Wayne Tam, Ronald Hoffman, Joseph M. Scandura, Raul Rabadan, Omar Abdel-Wahab, Peter Smibert, Dan A. Landau
Defining the transcriptomic identity of clonally related malignant cells is challenging in the absence of cell surface markers that distinguish cancer clones from one another or from admixed non-neoplastic cells. While single-cell methods have been devised to capture both the transcriptome and genotype, these methods are not compatible with droplet-based single-cell transcriptomics, limiting their throughput. To overcome this limitation, we present single-cell Genotyping of Transcriptomes (GoT), which integrates cDNA genotyping with high-throughput droplet-based single-cell RNA-seq. We further demonstrate that multiplexed GoT can interrogate multiple genotypes for distinguishing subclonal transcriptomic identity. We apply GoT to 26,039 CD34+ cells across six patients with myeloid neoplasms, in which the complex process of hematopoiesis is corrupted by CALR-mutated stem and progenitor cells. We define high-resolution maps of malignant versus normal hematopoietic progenitors, and show that while mutant cells are comingled with wildtype cells throughout the hematopoietic progenitor landscape, their frequency increases with differentiation. We identify the unfolded protein response as a predominant outcome of CALR mutations, with significant cell identity dependency. Furthermore, we identify that CALR mutations lead to NF-KB pathway upregulation specifically in uncommitted early stem cells. Collectively, GoT provides high-throughput linkage of single-cell genotypes with transcriptomes and reveals that the transcriptional output of somatic mutations is heavily dependent on the native cell identity.
3,462 downloads cancer biology
Fiona M Behan, Francesco Iorio, Emanuel Gonçalves, Gabriele Picco, Charlotte M Beaver, Rita Santos, Yanhua Rao, Rizwan Ansari, Sarah Harper, David Adam Jackson, Rebecca McRae, Rachel Pooley, Piers Wilkinson, David Dow, Carolyn Buser-Doepner, Euan A Stronach, Julio Saez-Rodriguez, Kosuke Yusa, Garnett Mathew
Functional genomics approaches can overcome current limitations that hamper oncology drug development such as lack of robust target identification and clinical efficacy. Here we performed genome-scale CRISPR-Cas9 screens in 204 human cancer cell lines from 12 cancer-types and developed a data-driven framework to prioritise cancer therapeutic candidates. We integrated gene cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritise new oncology targets in defined tissues and genotypes. Furthermore, we took one of our most promising dependencies, Werner syndrome RecQ helicase, and verified it as a candidate target for tumours with microsatellite instability. Our analysis provides a comprehensive resource of cancer dependencies, a framework to prioritise oncology targets, and nominates specific new candidates. The principles described in this study can transform the initial stages of the drug development process contributing to a new, diverse and more effective portfolio of oncology targets.
3,329 downloads cancer biology
Virtually all tumors are genetically heterogeneous, containing subclonal populations of cells that are defined by distinct mutations. Subclones can have unique phenotypes that influence disease progression, but these phenotypes are difficult to characterize: subclones usually cannot be physically purified, and bulk gene expression measurements obscure interclonal differences. Single-cell RNA-sequencing has revealed transcriptional heterogeneity within a variety of tumor types, but it is unclear how this expression heterogeneity relates to subclonal genetic events - for example, whether particular expression clusters correspond to mutationally defined subclones. To address this question, we developed an approach that integrates enhanced whole genome sequencing (eWGS) with the 10x Genomics Chromium Single Cell 5' Gene Expression workflow (scRNA-seq) to directly link expressed mutations with transcriptional profiles at single cell resolution. Using bone marrow samples from five cases of primary human Acute Myeloid Leukemia (AML), we generated WGS and scRNA-seq data for each case. Duplicate single cell libraries representing a median of 20,474 cells per case were generated from the bone marrow of each patient. Although the libraries were 5' biased, we detected expressed mutations in cDNAs at distances up to 10 kbp from the 5' ends of well-expressed genes, allowing us to identify hundreds to thousands of cells with AML-specific somatic mutations in every case. This data made it possible to distinguish AML cells (including normal-karyotype AML cells) from surrounding normal cells, to study tumor differentiation and intratumoral expression heterogeneity, to identify expression signatures associated with subclonal mutations, and to find cell surface markers that could be used to purify subclones for further study. The data also revealed transcriptional heterogeneity that occurred independently of subclonal mutations, suggesting that additional factors drive epigenetic heterogeneity. This integrative approach for connecting genotype to phenotype in AML cells is broadly applicable for analysis of any sample that is phenotypically and genetically heterogeneous. NOTE: AAP and SRW contributed equally to this work.
3,245 downloads cancer biology
Ludmil Alexandrov, Young Seok Ju, Kerstin Haase, Peter Van Loo, Iñigo Martincorena, Serena Nik-Zainal, Yasushi Totoki, Akihiro Fujimoto, Hidewaki Nakagawa, Tatsuhiro Shibata, Peter J. Campbell, Paolo Vineis, David H Phillips, Michael R. Stratton
Tobacco smoking increases the risk of at least 15 classes of cancer. We analyzed somatic mutations and DNA methylation in 5,243 cancers of types for which tobacco smoking confers an elevated risk. Smoking is associated with increased mutation burdens of multiple distinct mutational signatures, which contribute to different extents in different cancers. One of these signatures, mainly found in cancers derived from tissues directly exposed to tobacco smoke, is attributable to misreplication of DNA damage caused by tobacco carcinogens. Others likely reflect indirect activation of DNA editing by APOBEC cytidine deaminases and of an endogenous clock-like mutational process. The results are consistent with the proposition that smoking increases cancer risk by increasing the somatic mutation load, although direct evidence for this mechanism is lacking in some smoking-related cancer types.
3,188 downloads cancer biology
UCSC Xena is a visual exploration resource for both public and private omics data, supported through the web-based Xena Browser and multiple turn-key Xena Hubs. This unique archecture allows researchers to view their own data securely, using private Xena Hubs, simultaneously visualizing large public cancer genomics datasets, including TCGA and the GDC. Data integration occurs only within the Xena Browser, keeping private data private. Xena supports virtually any functional genomics data, including SNVs, INDELs, large structural variants, CNV, expression, DNA methylation, ATAC-seq signals, and phenotypic annotations. Browser features include the Visual Spreadsheet, survival analyses, powerful filtering and subgrouping, statistical analyses, genomic signatures, and bookmarks. Xena differentiates itself from other genomics tools, including its predecessor, the UCSC Cancer Genomics Browser, by its ability to easily and securely view public and private data, its high performance, its broad data type support, and many unique features.
3,016 downloads cancer biology
The target profiles of many drugs are established early in their development and are not systematically revisited at the time of FDA approval. Thus, it is often unclear whether therapeutics with the same nominal targets but different chemical structures are functionally equivalent. In this paper we use five different phenotypic and biochemical assays to compare approved inhibitors of cyclin-dependent kinases 4/6 - collectively regarded as breakthroughs in the treatment of hormone receptor-positive breast cancer. We find that transcriptional, proteomic and phenotypic changes induced by palbociclib, ribociclib, and abemaciclib differ significantly; abemaciclib in particular has advantageous activities partially overlapping those of alvocidib, an older polyselective CDK inhibitor. In cells and mice, abemaciclib inhibits kinases other than CDK4/6 including CDK2/Cyclin A/E - implicated in resistance to CDK4/6 inhibition - and CDK1/Cyclin B. The multi-faceted experimental and computational approaches described here therefore uncover under-appreciated differences in CDK4/6 inhibitor activities with potential importance in treating human patients.
2,940 downloads cancer biology
Geoff Macintyre, Teodora E. Goranova, Dilrini De Silva, Darren Ennis, Anna M. Piskorz, Matthew Eldridge, Daoud Sie, Liz-Anne Lewsley, Aishah Hanif, Cheryl Wilson, Suzanne Dowson, Rosalind M. Glasspool, Michelle Lockley, Elly Brockbank, Ana Montes, Axel Walther, Sudha Sundar, Richard Edmondson, Geoff D. Hall, Andrew Clamp, Charlie Gourley, Marcia Hall, Christina Fotopoulou, Hani Gabra, James Paul, Anna Supernat, David Millan, Aoisha Hoyle, Gareth Bryson, Craig Nourse, Laura Mincarelli, Luis Navarro Sanchez, Bauke Ylstra, Mercedes Jimenez-Linan, Luiza Moore, Oliver Hofmann, Florian Markowetz, Iain A. McNeish, James D. Brenton
Genomic complexity from profound copy-number aberration has prevented effective molecular stratification of ovarian and other cancers. Here we present a method for copy-number signature identification that decodes this complexity. We derived eight signatures using 117 shallow whole-genome sequenced high-grade serous ovarian cancer cases, which were validated on a further 497 cases. Mutational processes underlying the copy-number signatures were identified, including breakage-fusion-bridge cycles, homologous recombination deficiency and whole-genome duplication. We show that most tumours are heterogeneous and harbour multiple signature exposures. We also demonstrate that copy number signatures predict overall survival and changes in signature exposure observed in response to chemotherapy suggest potential treatment strategies.
2,856 downloads cancer biology
The architecture of normal and diseased tissues strongly influences the development and progression of disease as well as responsiveness and resistance to therapy. We describe a tissue-based cyclic immunofluorescence (t-CyCIF) method for highly multiplexed immuno-fluorescence imaging of formalin-fixed, paraffin-embedded (FFPE) specimens mounted on glass slides, the most widely used specimens for histopathological diagnosis of cancer and other diseases. t-CyCIF generates up to 60-plex images using an iterative process (a cycle) in which conventional low-plex fluorescence images are repeatedly collected from the same sample and then assembled into a high dimensional representation. t-CyCIF requires no specialized instruments or reagents and is compatible with super-resolution imaging; we demonstrate its application to quantifying signal transduction cascades, tumor antigens and immune markers in diverse tissues and tumors. The simplicity and adaptability of t-CyCIF makes it an effective method for pre-clinical and clinical research and a natural complement to single-cell genomics.
2,795 downloads cancer biology
Exosomes are man-sized vesicles shed by all cells, including cancer cells. Exosomes can serve as novel liquid biopsies for diagnosis of cancer with potential prognostic value. The exact mechanism/s associated with sorting or enrichment of cellular components into exosomes are still largely unknown. We reported Glypican-1 (GPC1) on the surface of cancer exosomes and provided evidence for the enrichment of GPC1 in exosomes from patients with pancreatic cancer. Several different laboratories have validated this novel conceptual advance and reproduced the original experiments using multiple antibodies from different sources. These include anti-GPC1 antibodies from ThermoFisher (PA5-28055 and PA-5-24972), Sigma (SAB270028), Abnova (MAB8351, monoclonal antibodies clone E9E), EMD Millipore (MAB2600-monoclonal antibodies), SantaCruz, and R&D Systems (BAF4519). This report complements such independent findings and report on the specific detection of Glypican-1 on the exosomes derived from the serum of pancreas cancer patients using multiple antibodies. Additionally, the specificity of the antibodies to GPC1 was determined by western blot and Protein Simple analyses of pancreatic cancer cells and their exosomes. Interestingly, our results highlight a specific enrichment of high molecular weight GPC1 on exosomes, potentially contributed by heparan sulfate and other glycosylation modifications.
2,734 downloads cancer biology
Background: Drug repurposing can speed up access to new therapeutic options for cancer patients. With more than 2000 drugs approved worldwide and 6 relevant targets per drug on average, the potential is quantitatively important. In this paper, we have attempted to quantify the number of non-cancer drugs supported by either preclinical or clinical cancer data. Methods: A PubMed search was performed to identify non-cancer drugs which could be repurposed in one or more cancer types. Drugs needed at least one peer-reviewed article showing an anticancer effect in vitro, in vivo or in humans. Results: A total of 235 eligible non-cancer drugs were identified (Table 1). Main characteristics of the drugs are summarized in Table 2. 67 (29%) are on the WHO list of essential medicines and 176 (75%) are off-patent. 133 (57%) had human data in cancer patient(s). Four were listed in clinical guidelines, namely thalidomide, all-trans retinoic acid, zoledronic acid and non-steroidal anti-inflammatory drugs (NSAID). Several drugs have shown a survival benefit in randomized trials such as cimetidine (colorectal cancer), progesterone (breast cancer) or itraconazole (lung cancer). Several other drugs induced responses in rare tumours, like clarithromycin, timolol or propranolol. Conclusion: We have found that the number of off-patent repurposing opportunities is large and increasing. Joint non-commercial clinical development (academics, governments, charities) may bring new therapeutic options to patients at low cost, especially in indications for which the industry has no incentive to invest in.
2,718 downloads cancer biology
Jessica N Spradlin, Xirui Hu, Carl C Ward, Scott M Brittain, Michael D. Jones, Lisha Ou, Milton To, Andrew Proudfoot, Elizabeth Ornelas, Mikias Woldegiorgis, James A Olzmann, Dirksen E Bussiere, Jason R Thomas, John A Tallarico, Jeffrey M McKenna, Markus Schirle, Thomas J Maimone, Daniel K Nomura
Nimbolide, a terpenoid natural product derived from the Neem tree, impairs cancer pathogenicity across many types of human cancers; however, the direct targets and mechanisms by which nimbolide exerts its effects are poorly understood. Here, we used activity-based protein profiling (ABPP) chemoproteomic platforms to discover that nimbolide reacts with a novel functional cysteine crucial for substrate recognition in the E3 ubiquitin ligase RNF114. Nimbolide impairs breast cancer cell proliferation in-part by disrupting RNF114 substrate recognition, leading to inhibition of ubiquitination and degradation of the tumor-suppressors such as p21, resulting in their rapid stabilization. We further demonstrate that nimbolide can be harnessed to recruit RNF114 as an E3 ligase in targeted protein degradation applications and show that synthetically simpler scaffolds are also capable of accessing this unique reactive site. Our study highlights the utility of ABPP platforms in uncovering unique druggable modalities accessed by natural products for cancer therapy and targeted protein degradation applications.
2,621 downloads cancer biology
Henry Lee-Six, Peter Ellis, Robert J. Osborne, Mathijs A Sanders, Luiza Moore, Nikitas Georgakopoulos, Franco Torrente, Ayesha Noorani, Martin Goddard, Philip Robinson, Tim H. H. Coorens, Laura O’Neill, Christopher Alder, Jingwei Wang, Rebecca C Fitzgerald, Matthias Zilbauer, Nicholas Coleman, Kourosh Saeb-Parsy, Inigo Martincorena, Peter J. Campbell, Michael R. Stratton
The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic changes and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we whole genome sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.
2,593 downloads cancer biology
Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, Alexandra Danyi, Jeroen de Ridder, Carla van Herpen, Martijn P. Lolkema, Neeltje Steeghs, Gad Getz, Quaid D Morris, Lincoln D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net
In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of the time a cancer patient presents with metastatic tumour and no obvious primary. Challenges also arise when distinguishing a metastatic recurrence of a previously treated cancer from the emergence of a new one. Here we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types. Our classifier achieves an accuracy of 91% on held-out tumor samples and 82% and 85% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced classifier accuracy. Our results have immediate clinical applicability, underscoring how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of cell-free circulating tumour DNA.
2,574 downloads cancer biology
Recent studies have identified prevalent subclonal architectures within many cancer types. However, the temporal evolutionary dynamics that produce these subclonal architectures remain unknown. Here we measure evolutionary dynamics in primary human cancers using computational modelling of clonal selection applied to high throughput sequencing data. Our approach simultaneously determines the subclonal architecture of a tumour sample, and measures the mutation rate, the selective advantage, and the time of appearance of subclones. Simulations demonstrate the accuracy of the method, and revealed the degree to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from gastric and lung cancers revealed that detectable subclones consistently emerged early during tumour growth and had considerably large fitness advantages (>20% growth advantage). Our quantitative platform provides new insight into the evolutionary history of cancers by facilitating the measurement of fundamental evolutionary parameters in individual patients.
2,567 downloads cancer biology
Aurelie Kamoun, Aurélien de Reyniès, Yves Allory, Gottfrid Sjödahl, A. Gordon Robertson, Roland Seiler, Katherine A Hoadley, Hikmat Al-Ahmadie, Woonyoung Choi, Clarice S. Groeneveld, Mauro A. A. Castro, Jacqueline Fontugne, Pontus Eriksson, Qianxing Mo, Jordan Kardos, Alexandre Zlotta, Arndt Hartmann, Colin P. Dinney, Joaquim Bellmunt, Thomas Powles, Núria Malats, Keith S. Chan, William Y. Kim, David J McConkey, Peter C. Black, Lars Dyrskjot, Mattias Höglund, Seth P. Lerner, Francisco X Real, François Radvanyi, The Bladder Cancer Molecular Taxonomy Group
Muscle-Invasive Bladder Cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, yielding diverse sets of subtypes. This diversity hampers the clinical application of such knowledge. Here, we report the results of a large international effort to reach a consensus on MIBC molecular subtypes. Using 1750 MIBC transcriptomes and a network-based analysis of six independent MIBC classification systems, we identified a consensus set of six molecular classes: Luminal Papillary (24%), Luminal Non-Specified (8%), Luminal Unstable (15%), Stroma-rich (15%), Basal/Squamous (35%), and Neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics. This consensus system offers a robust framework that will enable testing and validating predictive biomarkers in future clinical trials.
2,547 downloads cancer biology
Jianhua Yin, Zhisheng Li, Chen Yan, Enhao Fang, Ting Wang, Hanlin Zhou, Weiwei Luo, Qing Zhou, Jingyu Zhang, Jintao Hu, Haoxuan Jin, Lei Wang, Xing Zhao, Jiguang Li, Xiaojuan Qi, Wenbin Zhou, Chen Huang, Chenyang He, Huanming Yang, Karsten Kristiansen, Yong Hou, Shida Zhu, Dongxian Zhou, Ling Wang, Michael Dean, Kui Wu, Hong Hu, Guibo Li
The tumor microenvironment is composed of numerous cell types, including tumor, immune and stromal cells. Cancer cells interact with the tumor microenvironment to suppress anticancer immunity. In this study, we molecularly dissected the tumor microenvironment of breast cancer by single-cell RNA-seq. We profiled the breast cancer tumor microenvironment by analyzing the single-cell transcriptomes of 52,163 cells from the tumor tissues of 15 breast cancer patients. The tumor cells and immune cells from individual patients were analyzed simultaneously at the single-cell level. This study explores the diversity of the cell types in the tumor microenvironment and provides information on the mechanisms of escape from clearance by immune cells in breast cancer.
2,433 downloads cancer biology
CRISPR-Cas9 genome editing enables high-resolution detection of genetic vulnerabilities of cancer cells. We conducted a genome-wide CRISPR-Cas9 screen in RNF43 mutant pancreatic ductal adenocarcinoma (PDAC) cells, which rely on Wnt signaling for proliferation, and discovered a unique requirement for a WNT7B-FZD5 signaling circuit. Our results highlight an underappreciated level of functional specificity at the ligand-receptor level. We derived a panel of recombinant antibodies that reports the expression of nine out of ten human Frizzled receptors and confirm that WNT7B-FZD5 functional specificity cannot be explained by protein expression patterns. We developed two human antibodies that target FZD5 and robustly inhibited the growth of RNF43 mutant PDAC cells grown in vitro and as xenografts, providing strong orthogonal support for the functional specificity observed genetically. Proliferation of a patient-derived PDAC cell line harboring a RNF43 variant previously associated with PDAC was also selectively inhibited by the FZD5 antibodies, further demonstrating their use as a potential targeted therapy.
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