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Perabo F, Chandhasin C, Yoo S, Rosario JD, Chen YK, Filvaroff E, Stafford JA, Quake S, Clarke MF. Abstract 3720: TACH101, a first-in-class inhibitor of KDM4 histone lysine demethylase for the treatment of diffuse large B-cell lymphoma. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-3720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma (NHL) in the US accounting for about 22% of newly diagnosed cases of B-cell NHL. It is considered to be more aggressive and to have worse prognosis due to low response to existing treatments. KDM4 is a family of histone demethylases that can drive tumor growth by regulating transcription, cell cycle, and DNA replication/repair. Overexpression of KDM4 alters post-translational histone modification and is associated with many types of cancer, including DLBCL. TACH101 is a novel, potent small molecule inhibitor of KDM4 that is being developed for treatment of advanced cancers, including DLBCL.
Methods: TACH101 was evaluated in vitro and in vivo using cancer cell lines and patient-derived organoid (PDO) and xenograft (PDX) models of DLBCL.
Results: TACH101 is a reversible, α-ketoglutarate competitive, selective and potent inhibitor of KDM4 isoforms A-D with IC50 values < 0.100 μM for all four isoforms. An initial screen using a 301-cell line panel showed that DLBCL cell lines are sensitive to TACH101 (IC50 < 10 nM). In an additional panel of DLBCL cell lines, TACH101 inhibited proliferation in a dose-dependent manner in all DLBCL cell lines, independent of molecular subtype, with mean IC50’s of 0.03 ± 0.01 μM in ABC DLBCL cell lines (n=6); 0.02 ± 0.01 μM in GCB DLBCL cell lines (n=7) and 0.02 ± 0.01 μM in PMBL DLBCL cell lines (n=2). In OCI-LY19 DLBCL xenografts in vivo, TACH101 was well tolerated and inhibited tumor growth by 55% to 100%, depending on dosing regimen (either QD or BID following a 3 days on/4 days off schedule). In PK studies, TACH101 exhibited low clearance, moderate volume of distribution, and good oral bioavailability in mouse, rat, and dog. Moreover, treatment with TACH101 resulted in little or no inhibitory effects on CYP enzymes. Toxicity studies in rats and dogs identified potential target tissues and provided safety guidance for the use of TACH101 in human studies.
Conclusions: The KDM4 inhibitor, TACH101, had compelling activity in preclinical DLBCL models, suggesting that TACH101 could be an effective therapy for DLBCL. Preparations to advance the drug into clinical trials are underway.
Citation Format: Frank Perabo, Chandtip Chandhasin, Sanghee Yoo, Joselyn Del Rosario, Young K. Chen, Ellen Filvaroff, Jeffrey A. Stafford, Stephen Quake, Michael F. Clarke. TACH101, a first-in-class inhibitor of KDM4 histone lysine demethylase for the treatment of diffuse large B-cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3720.
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Perabo F, Chandhasin C, Dang V, Del Rosario J, Chen YK, Filvaroff E, Stafford J, Quake S, Clarke MF. Inhibition of cancer stem cells with TACH101, a first-in-class inhibitor of KDM4 histone lysine demethylase. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.e15105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e15105 Background: Cancer stem cells (CSCs) are believed to be responsible for both therapy resistance and metastasis. Until now, these resistant CSCs have not been well-characterized, and potential treatments targeting these cells have yet to be identified. Epigenetic modifiers, such as KDM4 histone demethylase, have been shown to play an important role in CSC renewal and maintenance. TACH101 is a novel, first-in-class pan inhibitor of KDM4 that has promising pre-clinical and pharmacologic properties as a possible cancer therapeutic. Methods: Effects of TACH101 on CSC population were evaluated in the colorectal cancer SU60 xenograft model. Mice engrafted with SU60 cells were treated with TACH101 or vehicle. The day after the last dose, tumors from each group were dissociated into single cells and used to perform (1) flow cytometry analysis of the tumorigenic cell population using markers CD44 and EpCAM, (2) single cell gene expression analysis using quantitative reverse transcription polymerase chain reaction (RT-qPCR), and (3) functional tumorigenicity assays (limiting dilution assays). Results: TACH101 administration reduced SU60 tumor growth by 62% compared to vehicle-treated mice (p < 0.0005). Flow cytometry analysis of SU60 tumor cells showed the proportion of cells with cancer stem cell features (CD44HighEpCAM+) was 2.5-fold lower in TACH101-treated mice as compared to vehicle-treated animals. Single cell gene expression analysis followed by hierarchical clustering based on expression of immature and mature cell markers showed that TACH101-treated tumors had a significant reduction in the proportion of progenitor-like cells (p = 0.01) and an increase in number of both intermediate-like and differentiated-like cells although the increase was not significant (p = 0.07). In limiting dilution assay experiments, result showed that tumors were bigger/grew faster in animals receiving tumor cells derived from vehicle-treated animals compared to TACH101-treated animals. Furthermore, TACH101 was shown to reduce the number of tumor-initiating cancer stem cells by 4.4-fold. Further evaluation of TACH101 across additional xenograft models including esophageal, gastric, breast, and lymphoma showed tumor growth inhibition of up to 100%. TACH101 demonstrated favorable cell permeability, good oral bioavailability, and high metabolic stability. Toxicity studies in rats and dogs identified potential target tissues and provided safety guidance for the use of TACH101 in human trials. Conclusions: TACH101 inhibited proliferation of and tumor initiation by CSCs. As therapy resistance and metastatic dissemination are grave consequences of CSC activity, TACH101 provides a novel approach to eradicating this population and shows broad applicability as a potential therapeutic agent. Preparations to advance TACH101 into clinical trials are underway.
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Affiliation(s)
| | | | - Van Dang
- Tachyon Therapeutics, San Francisco, CA
| | | | | | | | | | - Stephen Quake
- Departmets of Bioengineering and Applied Physics, Stanford University, Palo Alto, CA
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Perabo F, Chandhasin C, Yoo S, Dang V, Del Rosario J, Chen YK, Stafford J, Quake S, Clarke MF. TACH101, a first-in-class pan-inhibitor of KDM4 for treatment of gastrointestinal cancers. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.4_suppl.132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
132 Background: TACH101 is a novel, potent small molecule inhibitor of KDM4, a novel epigenetic target for cancer therapy. KDM4 is a family of histone lysine demethylases that, when overexpressed, drives key processes linked to cancer. Validation of KDM4 as a driver gene was confirmed across gastrointestinal tumor types including esophageal, colon and gastric cancers, and is associated with formation of aggressive tumors. Methods: TACH101 was evaluated in in vitro and in vivo studies including cell inhibition assays, patient-derived xenograft (PDX) and organoid models, and bioinformatics analyses studies. Results: In vitro, TACH101 treatment potently inhibited cell proliferation in cell lines and organoid models representing esophageal, CRC, and gastric cancers. TACH101 induced apoptosis in human CRC (HT-29) and esophageal (KYSE-150) cancer cell lines (EC50s 0.033 - 0.092 µM). Further evaluation using a panel of > 300 cell lines from different tumor types showed potent activity of TACH101 against gastric cancer and CRC. In gastric cancer, 2D cell viability inhibition assays conducted on a panel of 11 gastric cancer cell lines showed 9/11 (82%) were sensitive to TACH101 treatment (IC50 0.004 - 0.072 µM); in PDX models, 4/5 (80%) were sensitive to TACH101 treatment (IC50 0.007 - 0.039 µM). In CRC, bioinformatics analysis indicated increased TACH101 sensitivity in cell lines with MSI-H status (IC50 1-150 nM). Sensitivity of MSI-H CRC to TACH101 was further confirmed in a panel of 14 CRC PDX models and 7 CRC organoid models in culture-based viability inhibition assays. In PDX models, 5/5 (100%) characterized as MSI were sensitive to TACH101 treatment (IC50 0.001 - 0.014 µM), whereas 4/8 (50%) characterized as MSS were sensitive to TACH101 (IC50 0.003 - 0.270 µM). In patient derived CRC organoid models, 3/3 (100%) characterized as MSI were sensitive to TACH101 treatment (IC50 0.022 - 0.149 µM) whereas 0/3 (0%) characterized as MSS were sensitive (IC50 > 10 µM). In vivo, TACH101 triggered effective tumor control (≥70%) in xenograft models of CRC (SU60), esophageal (KYSE-150) and gastric (GXA-3036) cancers. Pharmacologic studies showed TACH101 demonstrated favorable cell permeability, good oral bioavailability, and high metabolic stability. Conclusions: Preclinical work on TACH101 KDM4 inhibitor demonstrates compelling data and applicability as a potential therapy for gastrointestinal cancers. Preparations to advance TACH101 into clinical trials are underway.
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Affiliation(s)
| | | | | | - Van Dang
- Tachyon Therapeutics, San Francisco, CA
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Friebel TR, Quake S, Abdelrahman M. A handy test to objectify post-operative free gracilis muscle flap texture. Int J Surg 2022; 98:106246. [PMID: 35121165 DOI: 10.1016/j.ijsu.2022.106246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 11/29/2022]
Affiliation(s)
- T R Friebel
- Plastic and Reconstructive Surgery Department, James Cook University Hospital, Middlesbrough, United Kingdom
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Chua Y, Quake S, Prasad K, El-Saify W. 560 Case Report: A Very Rare Case of Incidentaloma of a Large Adrenal Cavernous Haemangioma. Br J Surg 2021. [DOI: 10.1093/bjs/znab259.299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Introduction
Incidentaloma are asymptomatic and unanticipated adrenal tumours found on radiological imaging for unrelated diagnostic inquiries. Adrenal cavernous haemangioma is a rare, differentiated and benign tumour arising from the endothelial layer of blood vessels. This is a rare phenomenon with only 66 cases reported in the literature between 1955 and 2018.
Case Details
This is a case of a 79-year-old Caucasian gentleman who presented in March 2020 with vague abdominal discomfort and anaemia on a background of multiple co-morbidities including in particular, an asymptomatic left 5.6cm adrenal incidentaloma found in 2014. A computed tomography scan of abdomen-pelvis in June 2020 revealed progression in size of the incidentaloma to 20.8cm. Biochemical tests confirmed non-functioning adrenal tumour. The patient underwent open left adrenalectomy, left nephrectomy, splenectomy and distal pancreatectomy. The diagnosis of adrenal cavernous haemangioma was subsequently made on histopathological examination. Post-operatively, our patient made a good physiological recovery.
Discussion
There are no established diagnostic and treatment guidelines for adrenal cavernous haemangioma. Larger tumours are often treated surgically to exclude malignancies and to prevent potential complications as well as symptom relief. Literature reviews showed that most cases were surgically managed, and diagnoses were made through histology post-operatively.
Conclusions
Adrenal cavernous haemangioma typically present as incidentalomas which require further investigations. They are very rare non-functioning benign tumours that can be difficult to be differentiated from other adrenal malignancies.
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Affiliation(s)
- Y Chua
- James Cook University Hospital, Middlesbrough, United Kingdom
| | - S Quake
- James Cook University Hospital, Middlesbrough, United Kingdom
| | - K Prasad
- James Cook University Hospital, Middlesbrough, United Kingdom
| | - W El-Saify
- James Cook University Hospital, Middlesbrough, United Kingdom
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Chowdhury S, Bhandari M, Quake S, Ahmed I, Ibrahim B. 783 Digital Weekend Handover an Effective Documentation. Br J Surg 2021. [DOI: 10.1093/bjs/znab259.804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Abstract
Aim
To assess quality of completion for weekend handover for surgical weekend and to plan and design a Digital handover, the implementation and effect of which is studied.
Method
Data collection from TRAKCARE for documentation completion criteriae including diagnosis, further investigations to chase (e.g., bloods, imaging), discharge plans, escalation and DNAR status identified.
First cycle collected in August 2020 for pre-implementation status and standard. Second cycle was collected after implementation and raising awareness about new system in October 2020.
Exclusion criteria: patients discharged prior to weekend
Results
32 (10f 22m) and 22 (9 f 13m) patients were studied in first and second cycle with a respective median length stay of 243 hours and 161.5 hours. Handover entries had improved from 40.6% completion rate to 77.3% these included a diagnosis and management plan. Required blood investigation plans were recorded in 54.5% patients (previously 9.4%). Escalation plans including DNACPR and ceiling of care were improved from 25% to 31%.
Conclusions
Digital Medical recording left a gap in documentation for weekend ward rounds when personnels are thinned and busy. To optimize clinical care, the use of a E weekend handover has improved documentation greatly. Future Ongoing project includes improving escalation plans further.
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Affiliation(s)
- S Chowdhury
- North Tees Hospital, Stockton, United Kingdom
| | - M Bhandari
- North Tees Hospital, Stockton, United Kingdom
| | - S Quake
- James Cook University, Middlesborough, United Kingdom
| | - I Ahmed
- North Tees Hospital, Stockton, United Kingdom
| | - B Ibrahim
- North Tees Hospital, Stockton, United Kingdom
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Yoo S, Chandhasin C, Rosario JRD, Chen YK, Stafford J, Quake S, Perabo F, Clarke MF. Abstract 2128: TACH101, a first-in-class pan inhibitor of KDM4 histone lysine demethylases. Cancer Res 2021. [DOI: 10.1158/1538-7445.am2021-2128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Alterations in epigenetic control can cause defective post-translational histone modification and dysregulation of gene activity leading to cancer development. Overexpression of KDM4, a demethylase of histone lysine 9 methyl 2/3 and lysine 36 methyl 2/3 (H3K9me2/3 and H3K36me2/3), is documented in a variety of cancers and is linked to aggressive disease and poor clinical outcomes. TACH101 is a novel first-in-class, selective and potent pan KDM4 inhibitor with favorable pharmacologic properties.
Methods: TACH101 was evaluated using in vitro and in vivo studies including cell-proliferation assays in multiple cancer cell lines and patient-derived organoid models, apoptotic and cell cycle analyses, pharmacology studies in various animal species, and efficacy studies in xenograft tumor models.
Results: Inhibition mechanism studies demonstrated TACH101 to be a reversible, α-ketoglutarate competitive, selective and potent inhibitor of KDM4 isoforms A-D with IC50 values less than 0.100 μM for all four isoforms. In vitro, TACH101 demonstrated potent increase of H3K36me3 levels (EC50 <0.001 μM, HTRF) in KYSE-150 cell line engineered to overexpress KDM4C and showed potent anti-proliferative activity in multiple cell lines in OncoPanel. Sub-micromolar levels of TACH101 induced apoptosis in human colorectal (HT-29), esophageal (KYSE-150), and triple negative breast cancer (MDA-MB-231) cell lines with EC50s ranging from 0.033-0.092 µM. TACH101 effects on cell cycle demonstrated a dose-dependent increase in the proportion of cells in S-phase at 24 and 48 hours relative to control: TACH101 at 0.01 μM concentration yielded fold increase of 1.7 and 2.1, and at 0.1 μM concentration yielded fold increase of 2.1 and 3.2. In vivo, TACH101 triggered effective tumor growth control in xenograft models including colorectal, esophageal, gastric, breast, and lymphoma with tumor growth inhibition of up to 100%. Flow cytometric analysis performed on single cells isolated from vehicle and TACH101-treated tumors showed a significant 2.5-fold reduction in population of tumorigenic cells (CD44high; EpCAM+) compared to vehicle control, indicating TACH101 may prevent self-renewal of cancer stem cells. This was corroborated in a study evaluating TACH101 effects on tumor initiating cell (TIC) frequency in colorectal tumors where TACH101 treatment reduced TIC frequency by 4.4-fold. Pharmacologic studies showed plasma protein binding of TACH101 to be ≥99% bound in mouse, rat, dog, and human. PK studies showed TACH101 exhibited low clearance, moderate volume of distribution, and good oral bioavailability in mouse, rat, and dog. Moreover, treatment with TACH101 resulted in little or no inhibitory effects on CYP enzyme activities.
Conclusions: TACH101 is a potent pan inhibitor of KDM4 that is suggestive of broad potential in cancer treatment. Further preclinical evaluation is ongoing to advance the molecule into clinical trials.
Citation Format: Sanghee Yoo, Chandtip Chandhasin, Joselyn R. Del Rosario, Young K. Chen, Jeff Stafford, Stephen Quake, Frank Perabo, Michael F. Clarke. TACH101, a first-in-class pan inhibitor of KDM4 histone lysine demethylases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2128.
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Cui L, Moraga I, Lerbs T, Van Neste C, Wilmes S, Tsutsumi N, Trotman-Grant AC, Gakovic M, Andrews S, Gotlib J, Darmanis S, Enge M, Quake S, Hitchcock IS, Piehler J, Garcia KC, Wernig G. Tuning MPL signaling to influence hematopoietic stem cell differentiation and inhibit essential thrombocythemia progenitors. Proc Natl Acad Sci U S A 2021; 118:e2017849118. [PMID: 33384332 PMCID: PMC7812794 DOI: 10.1073/pnas.2017849118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Thrombopoietin (TPO) and the TPO-receptor (TPO-R, or c-MPL) are essential for hematopoietic stem cell (HSC) maintenance and megakaryocyte differentiation. Agents that can modulate TPO-R signaling are highly desirable for both basic research and clinical utility. We developed a series of surrogate protein ligands for TPO-R, in the form of diabodies (DBs), that homodimerize TPO-R on the cell surface in geometries that are dictated by the DB receptor binding epitope, in effect "tuning" downstream signaling responses. These surrogate ligands exhibit diverse pharmacological properties, inducing graded signaling outputs, from full to partial TPO agonism, thus decoupling the dual functions of TPO/TPO-R. Using single-cell RNA sequencing and HSC self-renewal assays we find that partial agonistic diabodies preserved the stem-like properties of cultured HSCs, but also blocked oncogenic colony formation in essential thrombocythemia (ET) through inverse agonism. Our data suggest that dampening downstream TPO signaling is a powerful approach not only for HSC preservation in culture, but also for inhibiting oncogenic signaling through the TPO-R.
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Affiliation(s)
- Lu Cui
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305
| | - Ignacio Moraga
- HHMI, Stanford University School of Medicine, Stanford, CA 94305
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305
- School of Life Sciences, University of Dundee, Dundee DD15EH, United Kingdom
| | - Tristan Lerbs
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305
| | - Camille Van Neste
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305
| | - Stephan Wilmes
- School of Life Sciences, University of Dundee, Dundee DD15EH, United Kingdom
| | - Naotaka Tsutsumi
- HHMI, Stanford University School of Medicine, Stanford, CA 94305
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305
| | - Aaron Claudius Trotman-Grant
- HHMI, Stanford University School of Medicine, Stanford, CA 94305
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305
| | - Milica Gakovic
- HHMI, Stanford University School of Medicine, Stanford, CA 94305
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305
- School of Life Sciences, University of Dundee, Dundee DD15EH, United Kingdom
| | - Sarah Andrews
- York Biomedical Research Institute, Department of Biology, University of York, Heslington, YO10 5DD York, United Kingdom
| | - Jason Gotlib
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, CA 94305
| | - Spyros Darmanis
- Department of Bioengineering, School of Bioengineering and Medicine, Stanford University, Stanford, CA 94305
- Microchemistry, Proteomics, Lipidomics and NGS Department Genentech Inc., South San Francisco, CA, 94080
| | - Martin Enge
- Department of Bioengineering, School of Bioengineering and Medicine, Stanford University, Stanford, CA 94305
- Department of Oncology-Pathology Karolinska Institutet, 171 64 Stockholm, Sweden
| | - Stephen Quake
- Department of Bioengineering, School of Bioengineering and Medicine, Stanford University, Stanford, CA 94305
| | - Ian S Hitchcock
- York Biomedical Research Institute, Department of Biology, University of York, Heslington, YO10 5DD York, United Kingdom
| | - Jacob Piehler
- Department of Biology and Center for Cellular Nanoanalytics (CellNanOs), University of Osnabrück, Barbarastraße 11, 49076 Osnabrück, Germany
| | - K Christopher Garcia
- HHMI, Stanford University School of Medicine, Stanford, CA 94305;
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305
| | - Gerlinde Wernig
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305;
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305
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Bergamaschi A, Ku J, Ning Y, Collin F, Ellison C, Phillips T, McCarthy E, Wang W, Antoine M, Haan D, Scott A, Lloyd P, Guler G, Ashworth A, Quake S, Levy S. Abstract 783: Epigenomic detection of multiple cancers in plasma derived cell free DNA. Cancer Res 2020. [DOI: 10.1158/1538-7445.am2020-783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Our feasibility study employed a novel genomic detection methodology that enriches 5-hydroxymethylcytosine (5hmC) loci in cell free DNA (cfDNA) from the plasma of cancer patients using click chemistry coupled with sequencing and machine learning based classification methods. These classification methods were developed to detect the presence of disease in the plasma of cancer and control subjects. Cancer and control patient cfDNA cohorts were accrued from multiple sites consisting of 48 breast, 55 lung, 32 prostate and 2 pancreatic datasets consisting of 41 and 53 cancer subjects (Set 1 and 2). In addition, a control cohort of 260 subjects (non-cancer) was employed to match cancer patient demographics (age, sex and smoking status) in a case-control study design.
Methods: Machine learning methods, applied to each cancer case cohort individually, with a balancing non-cancer cohort, were able to classify cancer and control samples. Measures of predictive performance using 5-fold cross validation coupled with out-of-fold Area Under the Receiver Operating Characteristic Curve (AUROC) measures were employed. Gene sets selected as part of biomarker discovery were further analyzed for disease relevance using pathway analysis tools (GSEA, mSigDB).
Results: 260 controls and 229 cancers from four disease types (breast, lung, pancreas and prostate) were analyzed; more than 60% of cancer patients had early stage disease (I or II). Predictive performance, employing AUROC measures, was established for breast (0.89), lung (0.84), pancreas (set 1 - 0.95 and 2 - 0.93) and prostate (0.83). The genes defining each of these predictive models were enriched for pathways relevant to disease specific etiology, notably in the control of gene regulation in these same pathways. The breast cancer cohort consisted primarily of stage I and II patients including tumors < 2 cm and these samples exhibited a higher prediction probability score. The prostate cancer cohort consisted of both indolent and aggressive disease sample and prediction performance was equally high for both (AUROC for indolent vs aggressive was 0.81 and 0.77, respectively).
Conclusions: These findings suggest that 5hmC changes in cfDNA enable non-invasive detection of early stage breast, pancreatic, prostate, and lung cancers. Furthermore, 5hmC profiling in cfDNA may enable the prediction of clinically relevant features such as tumor size in breast adenocarcinoma or indolent disease in prostate cancer. Finally, this study identified a suite of 5hmC biomarkers that may be further validated in larger, and more diverse, patient cohorts.
Citation Format: Anna Bergamaschi, Jeremy Ku, Yuhong Ning, Francois Collin, Chris Ellison, Tierney Phillips, Erin McCarthy, Wendy Wang, Michael Antoine, David Haan, Aaron Scott, Paul Lloyd, Gulfem Guler, Alan Ashworth, Stephen Quake, Samuel Levy. Epigenomic detection of multiple cancers in plasma derived cell free DNA [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 783.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | - Alan Ashworth
- 2UCSF Helen Diller Family Comprehensive Cancer Cent, San Francisco, CA
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Peterson LS, Stelzer IA, Tsai AS, Ghaemi MS, Han X, Ando K, Winn VD, Martinez NR, Contrepois K, Moufarrej MN, Quake S, Relman DA, Snyder MP, Shaw GM, Stevenson DK, Wong RJ, Arck P, Angst MS, Aghaeepour N, Gaudilliere B. Multiomic immune clockworks of pregnancy. Semin Immunopathol 2020; 42:397-412. [PMID: 32020337 PMCID: PMC7508753 DOI: 10.1007/s00281-019-00772-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 10/31/2019] [Indexed: 12/15/2022]
Abstract
Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy "immune clock" is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth.
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Affiliation(s)
- Laura S Peterson
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Ina A Stelzer
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Amy S Tsai
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Mohammad S Ghaemi
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoyuan Han
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Kazuo Ando
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Nadine R Martinez
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kevin Contrepois
- Stanford Metabolic Health Center, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Center for Genomics and Personalized Medicine, Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Mira N Moufarrej
- Department of Bioengineering, Stanford University School of Engineering, Stanford, CA, USA
| | - Stephen Quake
- Department of Bioengineering, Stanford University School of Engineering, Stanford, CA, USA
| | - David A Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Michael P Snyder
- Stanford Center for Genomics and Personalized Medicine, Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Gary M Shaw
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David K Stevenson
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald J Wong
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Petra Arck
- Department of Obstetrics and Fetal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Martin S Angst
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Brice Gaudilliere
- Department of Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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11
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Wang W, Mas A, Monleón J, Quake S, Simon C. Single cell RNAseq analyses of uterine fibroids and fibroid-free myometria reveal previously unidentified cell type and state. Fertil Steril 2019. [DOI: 10.1016/j.fertnstert.2019.07.1001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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12
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Paranathala M, Quake S, Prasad M. P16 Relation of timing of surgery to outcome from traumatic acute subdural haematoma. J Neurol Psychiatry 2019. [DOI: 10.1136/jnnp-2019-abn.94] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
ObjectivesAcute subdural haemorrhage (ASDH) is a neurosurgical emergency with high mortality and morbidity rates. Time to surgical intervention is implicated as an important factor affecting patient outcomes, however, more recent studies do not support this. We aimed to determine the correlation between time interval to surgery and outcome of patients with traumatic ASDH.MethodsWe retrospectively reviewed consecutive ASDH patients who underwent haematoma evacuation in the period between 2010 and 2016 at this tertiary neurosurgical centre. 49 patients were included for the analysis. Patient data was extracted from theatre records, patient notes and electronic records.ResultsThe median time interval from injury to surgery was 403 min (6 hours 43 min) with road traffic accident being the commonest mechanism of injury. 20 of 49 (34.7%) patients underwent evacuation within five hours from time of injury. Of these, 12 (41.4%) had good recovery (GOS 5), versus 15 (51.7%) amongst the 29 patients who underwent operation after five hours. Spearman rank correlation test (rs=0.07375) showed no statistically significant correlation between time interval to surgery and patient outcomes as measured by GOS. The overall mortality rate of evacuated patients at JCUH was 8.16% and the majority had good functional status, 55.1% with GOS 5.ConclusionsLonger time interval of more than four hours from injury to surgical intervention was not associated with higher mortality rate, or worse functional outcome.
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13
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Ker DFE, Wang D, Sharma R, Zhang B, Passarelli B, Neff N, Li C, Maloney W, Quake S, Yang YP. Identifying deer antler uhrf1 proliferation and s100a10 mineralization genes using comparative RNA-seq. Stem Cell Res Ther 2018; 9:292. [PMID: 30376879 PMCID: PMC6208050 DOI: 10.1186/s13287-018-1027-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 08/24/2018] [Accepted: 09/30/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Deer antlers are bony structures that re-grow at very high rates, making them an attractive model for studying rapid bone regeneration. METHODS To identify the genes that are involved in this fast pace of bone growth, an in vitro RNA-seq model that paralleled the sharp differences in bone growth between deer antlers and humans was established. Subsequently, RNA-seq (> 60 million reads per library) was used to compare transcriptomic profiles. Uniquely expressed deer antler proliferation as well as mineralization genes were identified via a combination of differential gene expression and subtraction analysis. Thereafter, the physiological relevance as well as contributions of these identified genes were determined by immunofluorescence, gene overexpression, and gene knockdown studies. RESULTS Cell characterization studies showed that in vitro-cultured deer antler-derived reserve mesenchyme (RM) cells exhibited high osteogenic capabilities and cell surface markers similar to in vivo counterparts. Under identical culture conditions, deer antler RM cells proliferated faster (8.6-11.7-fold increase in cell numbers) and exhibited increased osteogenic differentiation (17.4-fold increase in calcium mineralization) compared to human mesenchymal stem cells (hMSCs), paralleling in vivo conditions. Comparative RNA-seq identified 40 and 91 previously unknown and uniquely expressed fallow deer (FD) proliferation and mineralization genes, respectively, including uhrf1 and s100a10. Immunofluorescence studies showed that uhrf1 and s100a10 were expressed in regenerating deer antlers while gene overexpression and gene knockdown studies demonstrated the proliferation contributions of uhrf1 and mineralization capabilities of s100a10. CONCLUSION Using a simple, in vitro comparative RNA-seq approach, novel genes pertinent to fast bony antler regeneration were identified and their proliferative/osteogenic function was verified via gene overexpression, knockdown, and immunostaining. This combinatorial approach may be applicable to discover unique gene contributions between any two organisms for a given phenomenon-of-interest.
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Affiliation(s)
- Dai Fei Elmer Ker
- Department of Orthopaedic Surgery, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Dan Wang
- Department of Orthopaedic Surgery, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
- Department of Stomatology, Tenth People’s Hospital of Tongji University, 301 Yanchang Road, Shanghai, 200072 China
| | - Rashmi Sharma
- Department of Bioengineering, Stanford University, Shriram Center 443 Via Ortega, Stanford, CA 94305 USA
| | - Bin Zhang
- Department of Orthopaedic Surgery, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Ben Passarelli
- Scientific Computing Core, Calico Life Sciences LLC, 1170 Veterans Blvd., South San Francisco, CA 94080 USA
| | - Norma Neff
- Department of Bioengineering, Stanford University, Shriram Center 443 Via Ortega, Stanford, CA 94305 USA
| | - Chunyi Li
- State Key Lab for Molecular Biology of Special Economic Animals, 4899 Juye Street, Changchun, 130112 Jilin China
| | - William Maloney
- Department of Orthopaedic Surgery, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Stephen Quake
- Department of Bioengineering, Stanford University, Shriram Center 443 Via Ortega, Stanford, CA 94305 USA
- Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, CA 94305 USA
- Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, MD 20815 USA
| | - Yunzhi Peter Yang
- Department of Orthopaedic Surgery, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
- Department of Bioengineering, Stanford University, Shriram Center 443 Via Ortega, Stanford, CA 94305 USA
- Department of Material Science and Engineering, Stanford University, 496 Lomita Mall, Stanford, CA 94305 USA
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14
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Wang W, Vilella F, Moreno I, Pan W, Quake S, Simon C. Single cell RNAseq provides a molecular and cellular cartography of changes to the human endometrium through the menstrual cycle. Fertil Steril 2018. [DOI: 10.1016/j.fertnstert.2018.07.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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15
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Su T, Stanley G, Sinha R, D'Amato G, Das S, Rhee S, Chang AH, Poduri A, Raftrey B, Dinh TT, Roper WA, Li G, Quinn KE, Caron KM, Wu S, Miquerol L, Butcher EC, Weissman I, Quake S, Red-Horse K. Single-cell analysis of early progenitor cells that build coronary arteries. Nature 2018; 559:356-362. [PMID: 29973725 PMCID: PMC6053322 DOI: 10.1038/s41586-018-0288-7] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 05/29/2018] [Indexed: 01/26/2023]
Abstract
Arteries and veins are specified by antagonistic transcriptional programs. However, during development and regeneration, new arteries can arise from pre-existing veins through a poorly understood process of cell fate conversion. Here, using single-cell RNA sequencing and mouse genetics, we show that vein cells of the developing heart undergo an early cell fate switch to create a pre-artery population that subsequently builds coronary arteries. Vein cells underwent a gradual and simultaneous switch from venous to arterial fate before a subset of cells crossed a transcriptional threshold into the pre-artery state. Before the onset of coronary blood flow, pre-artery cells appeared in the immature vessel plexus, expressed mature artery markers, and decreased cell cycling. The vein-specifying transcription factor COUP-TF2 (also known as NR2F2) prevented plexus cells from overcoming the pre-artery threshold by inducing cell cycle genes. Thus, vein-derived coronary arteries are built by pre-artery cells that can differentiate independently of blood flow upon the release of inhibition mediated by COUP-TF2 and cell cycle factors.
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Affiliation(s)
- Tianying Su
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Geoff Stanley
- Program in Biophysics, Stanford University, Stanford, CA, USA
| | - Rahul Sinha
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Gaetano D'Amato
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Soumya Das
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Siyeon Rhee
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Andrew H Chang
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Aruna Poduri
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Brian Raftrey
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Thanh Theresa Dinh
- Veterans Affairs Palo Alto Health Care System and The Palo Alto Veterans Institute for Research, Palo Alto, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Walter A Roper
- Veterans Affairs Palo Alto Health Care System and The Palo Alto Veterans Institute for Research, Palo Alto, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Guang Li
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kelsey E Quinn
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kathleen M Caron
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sean Wu
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lucile Miquerol
- Aix-Marseille Université, CNRS UMR 7288, IBDM, Marseille, France
| | - Eugene C Butcher
- Veterans Affairs Palo Alto Health Care System and The Palo Alto Veterans Institute for Research, Palo Alto, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Irving Weissman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Stephen Quake
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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16
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Regev A, Teichmann SA, Lander ES, Amit I, Benoist C, Birney E, Bodenmiller B, Campbell P, Carninci P, Clatworthy M, Clevers H, Deplancke B, Dunham I, Eberwine J, Eils R, Enard W, Farmer A, Fugger L, Göttgens B, Hacohen N, Haniffa M, Hemberg M, Kim S, Klenerman P, Kriegstein A, Lein E, Linnarsson S, Lundberg E, Lundeberg J, Majumder P, Marioni JC, Merad M, Mhlanga M, Nawijn M, Netea M, Nolan G, Pe'er D, Phillipakis A, Ponting CP, Quake S, Reik W, Rozenblatt-Rosen O, Sanes J, Satija R, Schumacher TN, Shalek A, Shapiro E, Sharma P, Shin JW, Stegle O, Stratton M, Stubbington MJT, Theis FJ, Uhlen M, van Oudenaarden A, Wagner A, Watt F, Weissman J, Wold B, Xavier R, Yosef N. The Human Cell Atlas. eLife 2017; 6:e27041. [PMID: 29206104 DOI: 10.1101/121202] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 11/30/2017] [Indexed: 05/28/2023] Open
Abstract
The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
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Affiliation(s)
- Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, United States
- Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
- Howard Hughes Medical Institute, Chevy Chase, United States
| | - Sarah A Teichmann
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, United States
- Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
- Department of Systems Biology, Harvard Medical School, Boston, United States
| | - Ido Amit
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Christophe Benoist
- Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, United States
| | - Ewan Birney
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Bernd Bodenmiller
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland
| | - Peter Campbell
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
| | - Piero Carninci
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - Menna Clatworthy
- Molecular Immunity Unit, Department of Medicine, MRC Laboratory of Molecular Biology, University of Cambridge, Cambridge, United Kingdom
| | - Hans Clevers
- Hubrecht Institute, Princess Maxima Center for Pediatric Oncology and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Bart Deplancke
- Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Ian Dunham
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - James Eberwine
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
| | - Roland Eils
- Division of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany
| | - Wolfgang Enard
- Department of Biology II, Ludwig Maximilian University Munich, Martinsried, Germany
| | - Andrew Farmer
- Takara Bio United States, Inc., Mountain View, United States
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, and MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Berthold Göttgens
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
- Wellcome Trust-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, United States
- Massachusetts General Hospital Cancer Center, Boston, United States
| | - Muzlifah Haniffa
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Martin Hemberg
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Seung Kim
- Departments of Developmental Biology and of Medicine, Stanford University School of Medicine, Stanford, United States
| | - Paul Klenerman
- Peter Medawar Building for Pathogen Research and the Translational Gastroenterology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
| | - Arnold Kriegstein
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, United States
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, United States
| | - Sten Linnarsson
- Laboratory for Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Emma Lundberg
- Science for Life Laboratory, School of Biotechnology, KTH Royal Institute of Technology, Stockholm, Sweden
- Department of Genetics, Stanford University, Stanford, United States
| | - Joakim Lundeberg
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - John C Marioni
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Miriam Merad
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, United States
| | - Musa Mhlanga
- Division of Chemical, Systems & Synthetic Biology, Institute for Infectious Disease & Molecular Medicine (IDM), Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Martijn Nawijn
- Department of Pathology and Medical Biology, GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Mihai Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Garry Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, United States
| | - Dana Pe'er
- Computational and Systems Biology Program, Sloan Kettering Institute, New York, United States
| | | | - Chris P Ponting
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen Quake
- Department of Applied Physics and Department of Bioengineering, Stanford University, Stanford, United States
- Chan Zuckerberg Biohub, San Francisco, United States
| | - Wolf Reik
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Epigenetics Programme, The Babraham Institute, Cambridge, United Kingdom
- Centre for Trophoblast Research, University of Cambridge, Cambridge, United Kingdom
| | | | - Joshua Sanes
- Center for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
| | - Rahul Satija
- Department of Biology, New York University, New York, United States
- New York Genome Center, New York University, New York, United States
| | - Ton N Schumacher
- Division of Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Alex Shalek
- Broad Institute of MIT and Harvard, Cambridge, United States
- Institute for Medical Engineering & Science (IMES) and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States
- Ragon Institute of MGH, MIT and Harvard, Cambridge, United States
| | - Ehud Shapiro
- Department of Computer Science and Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Padmanee Sharma
- Department of Genitourinary Medical Oncology, Department of Immunology, MD Anderson Cancer Center, University of Texas, Houston, United States
| | - Jay W Shin
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - Oliver Stegle
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Michael Stratton
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | | | - Fabian J Theis
- Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Center Munich, Neuherberg, Germany
- Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Matthias Uhlen
- Science for Life Laboratory and Department of Proteomics, KTH Royal Institute of Technology, Stockholm, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Danish Technical University, Lyngby, Denmark
| | | | - Allon Wagner
- Department of Electrical Engineering and Computer Science and the Center for Computational Biology, University of California, Berkeley, Berkeley, United States
| | - Fiona Watt
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, United Kingdom
| | - Jonathan Weissman
- Howard Hughes Medical Institute, Chevy Chase, United States
- Department of Cellular & Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
- California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, United States
- Center for RNA Systems Biology, University of California, San Francisco, San Francisco, United States
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, United States
| | - Ramnik Xavier
- Broad Institute of MIT and Harvard, Cambridge, United States
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, United States
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Boston, United States
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, United States
| | - Nir Yosef
- Ragon Institute of MGH, MIT and Harvard, Cambridge, United States
- Department of Electrical Engineering and Computer Science and the Center for Computational Biology, University of California, Berkeley, Berkeley, United States
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17
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Regev A, Teichmann SA, Lander ES, Amit I, Benoist C, Birney E, Bodenmiller B, Campbell P, Carninci P, Clatworthy M, Clevers H, Deplancke B, Dunham I, Eberwine J, Eils R, Enard W, Farmer A, Fugger L, Göttgens B, Hacohen N, Haniffa M, Hemberg M, Kim S, Klenerman P, Kriegstein A, Lein E, Linnarsson S, Lundberg E, Lundeberg J, Majumder P, Marioni JC, Merad M, Mhlanga M, Nawijn M, Netea M, Nolan G, Pe'er D, Phillipakis A, Ponting CP, Quake S, Reik W, Rozenblatt-Rosen O, Sanes J, Satija R, Schumacher TN, Shalek A, Shapiro E, Sharma P, Shin JW, Stegle O, Stratton M, Stubbington MJT, Theis FJ, Uhlen M, van Oudenaarden A, Wagner A, Watt F, Weissman J, Wold B, Xavier R, Yosef N. The Human Cell Atlas. eLife 2017; 6:e27041. [PMID: 29206104 PMCID: PMC5762154 DOI: 10.7554/elife.27041] [Citation(s) in RCA: 1151] [Impact Index Per Article: 164.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 11/30/2017] [Indexed: 12/12/2022] Open
Abstract
The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
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Affiliation(s)
- Aviv Regev
- Broad Institute of MIT and HarvardCambridgeUnited States
- Department of BiologyMassachusetts Institute of TechnologyCambridgeUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
| | - Sarah A Teichmann
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
- Cavendish Laboratory, Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
| | - Eric S Lander
- Broad Institute of MIT and HarvardCambridgeUnited States
- Department of BiologyMassachusetts Institute of TechnologyCambridgeUnited States
- Department of Systems BiologyHarvard Medical SchoolBostonUnited States
| | - Ido Amit
- Department of ImmunologyWeizmann Institute of ScienceRehovotIsrael
| | - Christophe Benoist
- Division of Immunology, Department of Microbiology and ImmunobiologyHarvard Medical SchoolBostonUnited States
| | - Ewan Birney
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
| | - Bernd Bodenmiller
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
- Institute of Molecular Life SciencesUniversity of ZürichZürichSwitzerland
| | - Peter Campbell
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
- Department of HaematologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Piero Carninci
- Cavendish Laboratory, Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Division of Genomic TechnologiesRIKEN Center for Life Science TechnologiesYokohamaJapan
| | - Menna Clatworthy
- Molecular Immunity Unit, Department of Medicine, MRC Laboratory of Molecular BiologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Hans Clevers
- Hubrecht Institute, Princess Maxima Center for Pediatric Oncology and University Medical Center UtrechtUtrechtThe Netherlands
| | - Bart Deplancke
- Institute of Bioengineering, School of Life SciencesSwiss Federal Institute of Technology (EPFL)LausanneSwitzerland
| | - Ian Dunham
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
| | - James Eberwine
- Department of Systems Pharmacology and Translational TherapeuticsPerelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Roland Eils
- Division of Theoretical Bioinformatics (B080)German Cancer Research Center (DKFZ)HeidelbergGermany
- Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuantHeidelberg UniversityHeidelbergGermany
| | - Wolfgang Enard
- Department of Biology IILudwig Maximilian University MunichMartinsriedGermany
| | - Andrew Farmer
- Takara Bio United States, Inc.Mountain ViewUnited States
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, and MRC Human Immunology Unit, Weatherall Institute of Molecular MedicineJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Berthold Göttgens
- Department of HaematologyUniversity of CambridgeCambridgeUnited Kingdom
- Wellcome Trust-MRC Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Nir Hacohen
- Broad Institute of MIT and HarvardCambridgeUnited States
- Massachusetts General Hospital Cancer CenterBostonUnited States
| | - Muzlifah Haniffa
- Institute of Cellular MedicineNewcastle UniversityNewcastle upon TyneUnited Kingdom
| | - Martin Hemberg
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
| | - Seung Kim
- Departments of Developmental Biology and of MedicineStanford University School of MedicineStanfordUnited States
| | - Paul Klenerman
- Peter Medawar Building for Pathogen Research and the Translational Gastroenterology Unit, Nuffield Department of Clinical MedicineUniversity of OxfordOxfordUnited Kingdom
- Oxford NIHR Biomedical Research CentreJohn Radcliffe HospitalOxfordUnited Kingdom
| | - Arnold Kriegstein
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell ResearchUniversity of California, San FranciscoSan FranciscoUnited States
| | - Ed Lein
- Allen Institute for Brain ScienceSeattleUnited States
| | - Sten Linnarsson
- Laboratory for Molecular Neurobiology, Department of Medical Biochemistry and BiophysicsKarolinska InstitutetStockholmSweden
| | - Emma Lundberg
- Science for Life Laboratory, School of BiotechnologyKTH Royal Institute of TechnologyStockholmSweden
- Department of GeneticsStanford UniversityStanfordUnited States
| | - Joakim Lundeberg
- Science for Life Laboratory, Department of Gene TechnologyKTH Royal Institute of TechnologyStockholmSweden
| | | | - John C Marioni
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Miriam Merad
- Precision Immunology InstituteIcahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Musa Mhlanga
- Division of Chemical, Systems & Synthetic Biology, Institute for Infectious Disease & Molecular Medicine (IDM), Department of Integrative Biomedical Sciences, Faculty of Health SciencesUniversity of Cape TownCape TownSouth Africa
| | - Martijn Nawijn
- Department of Pathology and Medical Biology, GRIAC Research InstituteUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
| | - Mihai Netea
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenThe Netherlands
| | - Garry Nolan
- Department of Microbiology and ImmunologyStanford UniversityStanfordUnited States
| | - Dana Pe'er
- Computational and Systems Biology ProgramSloan Kettering InstituteNew YorkUnited States
| | | | - Chris P Ponting
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular MedicineUniversity of EdinburghEdinburghUnited Kingdom
| | - Stephen Quake
- Department of Applied Physics and Department of BioengineeringStanford UniversityStanfordUnited States
- Chan Zuckerberg BiohubSan FranciscoUnited States
| | - Wolf Reik
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
- Epigenetics ProgrammeThe Babraham InstituteCambridgeUnited Kingdom
- Centre for Trophoblast ResearchUniversity of CambridgeCambridgeUnited Kingdom
| | | | - Joshua Sanes
- Center for Brain Science and Department of Molecular and Cellular BiologyHarvard UniversityCambridgeUnited States
| | - Rahul Satija
- Department of BiologyNew York UniversityNew YorkUnited States
- New York Genome CenterNew York UniversityNew YorkUnited States
| | - Ton N Schumacher
- Division of ImmunologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
| | - Alex Shalek
- Broad Institute of MIT and HarvardCambridgeUnited States
- Institute for Medical Engineering & Science (IMES) and Department of ChemistryMassachusetts Institute of TechnologyCambridgeUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
| | - Ehud Shapiro
- Department of Computer Science and Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
| | - Padmanee Sharma
- Department of Genitourinary Medical Oncology, Department of Immunology, MD Anderson Cancer CenterUniversity of TexasHoustonUnited States
| | - Jay W Shin
- Division of Genomic TechnologiesRIKEN Center for Life Science TechnologiesYokohamaJapan
| | - Oliver Stegle
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
| | - Michael Stratton
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
| | | | - Fabian J Theis
- Institute of Computational BiologyGerman Research Center for Environmental Health, Helmholtz Center MunichNeuherbergGermany
- Department of MathematicsTechnical University of MunichGarchingGermany
| | - Matthias Uhlen
- Science for Life Laboratory and Department of ProteomicsKTH Royal Institute of TechnologyStockholmSweden
- Novo Nordisk Foundation Center for BiosustainabilityDanish Technical UniversityLyngbyDenmark
| | | | - Allon Wagner
- Department of Electrical Engineering and Computer Science and the Center for Computational BiologyUniversity of California, BerkeleyBerkeleyUnited States
| | - Fiona Watt
- Centre for Stem Cells and Regenerative MedicineKing's College LondonLondonUnited Kingdom
| | - Jonathan Weissman
- Howard Hughes Medical InstituteChevy ChaseUnited States
- Department of Cellular & Molecular PharmacologyUniversity of California, San FranciscoSan FranciscoUnited States
- California Institute for Quantitative Biomedical ResearchUniversity of California, San FranciscoSan FranciscoUnited States
- Center for RNA Systems BiologyUniversity of California, San FranciscoSan FranciscoUnited States
| | - Barbara Wold
- Division of Biology and Biological EngineeringCalifornia Institute of TechnologyPasadenaUnited States
| | - Ramnik Xavier
- Broad Institute of MIT and HarvardCambridgeUnited States
- Center for Computational and Integrative BiologyMassachusetts General HospitalBostonUnited States
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel DiseaseMassachusetts General HospitalBostonUnited States
- Center for Microbiome Informatics and TherapeuticsMassachusetts Institute of TechnologyCambridgeUnited States
| | - Nir Yosef
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
- Department of Electrical Engineering and Computer Science and the Center for Computational BiologyUniversity of California, BerkeleyBerkeleyUnited States
| | - Human Cell Atlas Meeting Participants
- Broad Institute of MIT and HarvardCambridgeUnited States
- Department of BiologyMassachusetts Institute of TechnologyCambridgeUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
- Wellcome Trust Sanger Institute, Wellcome Genome CampusHinxtonUnited Kingdom
- EMBL-European Bioinformatics InstituteWellcome Genome CampusHinxtonUnited Kingdom
- Cavendish Laboratory, Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Department of Systems BiologyHarvard Medical SchoolBostonUnited States
- Department of ImmunologyWeizmann Institute of ScienceRehovotIsrael
- Division of Immunology, Department of Microbiology and ImmunobiologyHarvard Medical SchoolBostonUnited States
- Institute of Molecular Life SciencesUniversity of ZürichZürichSwitzerland
- Department of HaematologyUniversity of CambridgeCambridgeUnited Kingdom
- Division of Genomic TechnologiesRIKEN Center for Life Science TechnologiesYokohamaJapan
- Molecular Immunity Unit, Department of Medicine, MRC Laboratory of Molecular BiologyUniversity of CambridgeCambridgeUnited Kingdom
- Hubrecht Institute, Princess Maxima Center for Pediatric Oncology and University Medical Center UtrechtUtrechtThe Netherlands
- Institute of Bioengineering, School of Life SciencesSwiss Federal Institute of Technology (EPFL)LausanneSwitzerland
- Department of Systems Pharmacology and Translational TherapeuticsPerelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Division of Theoretical Bioinformatics (B080)German Cancer Research Center (DKFZ)HeidelbergGermany
- Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuantHeidelberg UniversityHeidelbergGermany
- Department of Biology IILudwig Maximilian University MunichMartinsriedGermany
- Takara Bio United States, Inc.Mountain ViewUnited States
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, and MRC Human Immunology Unit, Weatherall Institute of Molecular MedicineJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
- Wellcome Trust-MRC Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUnited Kingdom
- Massachusetts General Hospital Cancer CenterBostonUnited States
- Institute of Cellular MedicineNewcastle UniversityNewcastle upon TyneUnited Kingdom
- Departments of Developmental Biology and of MedicineStanford University School of MedicineStanfordUnited States
- Peter Medawar Building for Pathogen Research and the Translational Gastroenterology Unit, Nuffield Department of Clinical MedicineUniversity of OxfordOxfordUnited Kingdom
- Oxford NIHR Biomedical Research CentreJohn Radcliffe HospitalOxfordUnited Kingdom
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell ResearchUniversity of California, San FranciscoSan FranciscoUnited States
- Allen Institute for Brain ScienceSeattleUnited States
- Laboratory for Molecular Neurobiology, Department of Medical Biochemistry and BiophysicsKarolinska InstitutetStockholmSweden
- Science for Life Laboratory, School of BiotechnologyKTH Royal Institute of TechnologyStockholmSweden
- Department of GeneticsStanford UniversityStanfordUnited States
- Science for Life Laboratory, Department of Gene TechnologyKTH Royal Institute of TechnologyStockholmSweden
- National Institute of Biomedical GenomicsKalyaniIndia
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUnited Kingdom
- Precision Immunology InstituteIcahn School of Medicine at Mount SinaiNew YorkUnited States
- Division of Chemical, Systems & Synthetic Biology, Institute for Infectious Disease & Molecular Medicine (IDM), Department of Integrative Biomedical Sciences, Faculty of Health SciencesUniversity of Cape TownCape TownSouth Africa
- Department of Pathology and Medical Biology, GRIAC Research InstituteUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenThe Netherlands
- Department of Microbiology and ImmunologyStanford UniversityStanfordUnited States
- Computational and Systems Biology ProgramSloan Kettering InstituteNew YorkUnited States
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular MedicineUniversity of EdinburghEdinburghUnited Kingdom
- Department of Applied Physics and Department of BioengineeringStanford UniversityStanfordUnited States
- Chan Zuckerberg BiohubSan FranciscoUnited States
- Epigenetics ProgrammeThe Babraham InstituteCambridgeUnited Kingdom
- Centre for Trophoblast ResearchUniversity of CambridgeCambridgeUnited Kingdom
- Center for Brain Science and Department of Molecular and Cellular BiologyHarvard UniversityCambridgeUnited States
- Department of BiologyNew York UniversityNew YorkUnited States
- New York Genome CenterNew York UniversityNew YorkUnited States
- Division of ImmunologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
- Institute for Medical Engineering & Science (IMES) and Department of ChemistryMassachusetts Institute of TechnologyCambridgeUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
- Department of Computer Science and Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
- Department of Genitourinary Medical Oncology, Department of Immunology, MD Anderson Cancer CenterUniversity of TexasHoustonUnited States
- Institute of Computational BiologyGerman Research Center for Environmental Health, Helmholtz Center MunichNeuherbergGermany
- Department of MathematicsTechnical University of MunichGarchingGermany
- Science for Life Laboratory and Department of ProteomicsKTH Royal Institute of TechnologyStockholmSweden
- Novo Nordisk Foundation Center for BiosustainabilityDanish Technical UniversityLyngbyDenmark
- Hubrecht Institute and University Medical Center UtrechtUtrechtThe Netherlands
- Department of Electrical Engineering and Computer Science and the Center for Computational BiologyUniversity of California, BerkeleyBerkeleyUnited States
- Centre for Stem Cells and Regenerative MedicineKing's College LondonLondonUnited Kingdom
- Department of Cellular & Molecular PharmacologyUniversity of California, San FranciscoSan FranciscoUnited States
- California Institute for Quantitative Biomedical ResearchUniversity of California, San FranciscoSan FranciscoUnited States
- Center for RNA Systems BiologyUniversity of California, San FranciscoSan FranciscoUnited States
- Division of Biology and Biological EngineeringCalifornia Institute of TechnologyPasadenaUnited States
- Center for Computational and Integrative BiologyMassachusetts General HospitalBostonUnited States
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel DiseaseMassachusetts General HospitalBostonUnited States
- Center for Microbiome Informatics and TherapeuticsMassachusetts Institute of TechnologyCambridgeUnited States
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18
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Cai S, Kalisky T, Sahoo D, Dalerba P, Feng W, Lin Y, Qian D, Kong A, Yu J, Wang F, Chen EY, Scheeren FA, Kuo AH, Sikandar SS, Hisamori S, van Weele LJ, Heiser D, Sim S, Lam J, Quake S, Clarke MF. A Quiescent Bcl11b High Stem Cell Population Is Required for Maintenance of the Mammary Gland. Cell Stem Cell 2016; 20:247-260.e5. [PMID: 28041896 DOI: 10.1016/j.stem.2016.11.007] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Revised: 09/12/2016] [Accepted: 11/04/2016] [Indexed: 12/31/2022]
Abstract
Stem cells in many tissues sustain themselves by entering a quiescent state to avoid genomic insults and to prevent exhaustion caused by excessive proliferation. In the mammary gland, the identity and characteristics of quiescent epithelial stem cells are not clear. Here, we identify a quiescent mammary epithelial cell population expressing high levels of Bcl11b and located at the interface between luminal and basal cells. Bcl11bhigh cells are enriched for cells that can regenerate mammary glands in secondary transplants. Loss of Bcl11b leads to a Cdkn2a-dependent exhaustion of ductal epithelium and loss of epithelial cell regenerative capacity. Gain- and loss-of-function studies show that Bcl11b induces cells to enter the G0 phase of the cell cycle and become quiescent. Taken together, these results suggest that Bcl11b acts as a central intrinsic regulator of mammary epithelial stem cell quiescence and exhaustion and is necessary for long-term maintenance of the mammary gland.
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Affiliation(s)
- Shang Cai
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Tomer Kalisky
- Department of Bioengineering, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Debashis Sahoo
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pediatrics, Department of Computer Science and Engineering, University of California San Diego, San Diego, CA 92123-0984, USA
| | - Piero Dalerba
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology & Cell Biology, Columbia University, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
| | - Weiguo Feng
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA; Cancer Institute, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Yuan Lin
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA; Cancer Institute, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Dalong Qian
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Angela Kong
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Jeffrey Yu
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Flora Wang
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Elizabeth Y Chen
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Ferenc A Scheeren
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Angera H Kuo
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Shaheen S Sikandar
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Shigeo Hisamori
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Linda J van Weele
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Diane Heiser
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Sopheak Sim
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Jessica Lam
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Stephen Quake
- Department of Bioengineering, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Michael F Clarke
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA 94305, USA.
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19
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Corey DM, Kowarsky M, Rosental B, Ishizuka K, Palmeri K, Sinha R, Voskoboynik A, Quake S, Weissman I. Developmental Regulated Cell Death Programs Account for Colony Elimination and Unstable Mixed-Chimerism in B. Schlosseri: Implications for Allogeneic Graft Survival. Biol Blood Marrow Transplant 2016. [DOI: 10.1016/j.bbmt.2015.11.780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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20
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Li Y, Pan W, Connolly I, Nagpal S, Reddy S, Quake S, Gephart MH. BMET-15TUMOR CELL FREE DNA IN CEREBRAL SPINAL FLUID REFLECTS TREATMENT RESPONSE IN LEPTOMENINGEAL METASTASIS. Neuro Oncol 2015. [DOI: 10.1093/neuonc/nov208.15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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21
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Zambon A, Zoso A, Gagliano O, Magrofuoco E, Fadini GP, Avogaro A, Foletto M, Quake S, Elvassore N. High Temporal Resolution Detection of Patient-Specific Glucose Uptake from Human ex Vivo Adipose Tissue On-Chip. Anal Chem 2015; 87:6535-43. [PMID: 26041305 DOI: 10.1021/ac504730r] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Human tissue in vitro models on-chip are highly desirable to dissect the complexity of a physio-pathological in vivo response because of their advantages compared to traditional static culture systems in terms of high control of microenvironmental conditions, including accurate perturbations and high temporal resolution analyses of medium outflow. Human adipose tissue (hAT) is a key player in metabolic disorders, such as Type 2 Diabetes Mellitus (T2DM). It is involved in the overall energy homeostasis not only as passive energy storage but also as an important metabolic regulator. Here, we aim at developing a large scale microfluidic platform for generating high temporal resolution of glucose uptake profiles, and consequently insulin sensitivity, under physio-pathological stimulations in ex vivo adipose tissues from nondiabetic and T2DM individuals. A multiscale mathematical model that integrates fluid dynamics and an intracellular insulin signaling pathway description was used for assisting microfluidic design in order to maximize measurement accuracy of tissue metabolic activity in response to perturbations. An automated microfluidic injection system was included on-chip for performing precise dynamic biochemical stimulations. The temporal evolution of culture conditions could be monitored for days, before and after perturbation, measuring glucose concentration in the outflow with high temporal resolution. As a proof of concept for detection of insulin resistance, we measured insulin-dependent glucose uptake by hAT from nondiabetic and T2DM subjects, mimicking the postprandial response. The system presented thus represents an important tool in dissecting the role of single tissues, such as hAT, in the complex interwoven picture of metabolic diseases.
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Affiliation(s)
- Alessandro Zambon
- †Department of Industrial Engineering, University of Padova, Padova 35131, Italy.,‡Venetian Institute of Molecular Medicine, Padova, 35129 Italy
| | - Alice Zoso
- †Department of Industrial Engineering, University of Padova, Padova 35131, Italy.,‡Venetian Institute of Molecular Medicine, Padova, 35129 Italy
| | - Onelia Gagliano
- †Department of Industrial Engineering, University of Padova, Padova 35131, Italy.,‡Venetian Institute of Molecular Medicine, Padova, 35129 Italy
| | - Enrico Magrofuoco
- †Department of Industrial Engineering, University of Padova, Padova 35131, Italy.,‡Venetian Institute of Molecular Medicine, Padova, 35129 Italy
| | | | - Angelo Avogaro
- §Department of Medicine, University of Padova, Padova 35128, Italy
| | - Mirto Foletto
- ∥Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova 35124, Italy
| | - Stephen Quake
- ⊥Bioengineering and Applied Physics, Stanford University, Stanford, California 94305, United States.,#Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, United States
| | - Nicola Elvassore
- †Department of Industrial Engineering, University of Padova, Padova 35131, Italy.,‡Venetian Institute of Molecular Medicine, Padova, 35129 Italy
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Huang Q, Briggs BR, Dong H, Jiang H, Wu G, Edwardson C, De Vlaminck I, Quake S. Taxonomic and functional diversity provides insight into microbial pathways and stress responses in the saline Qinghai Lake, China. PLoS One 2014; 9:e111681. [PMID: 25365331 PMCID: PMC4218802 DOI: 10.1371/journal.pone.0111681] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2014] [Accepted: 09/29/2014] [Indexed: 11/19/2022] Open
Abstract
Microbe-mediated biogeochemical cycles contribute to the global climate system and have sensitive responses and feedbacks to environmental stress caused by climate change. Yet, little is known about the effects of microbial biodiversity (i.e., taxonmic and functional diversity) on biogeochemical cycles in ecosytems that are highly sensitive to climate change. One such sensitive ecosystem is Qinghai Lake, a high-elevation (3196 m) saline (1.4%) lake located on the Tibetan Plateau, China. This study provides baseline information on the microbial taxonomic and functional diversity as well as the associated stress response genes. Illumina metagenomic and metatranscriptomic datasets were generated from lake water samples collected at two sites (B and E). Autotrophic Cyanobacteria dominated the DNA samples, while heterotrophic Proteobacteria dominated the RNA samples at both sites. Photoheterotrophic Loktanella was also present at both sites. Photosystem II was the most active pathway at site B; while, oxidative phosphorylation was most active at site E. Organisms that expressed photosystem II or oxidative phosphorylation also expressed genes involved in photoprotection and oxidative stress, respectively. Assimilatory pathways associated with the nitrogen cycle were dominant at both sites. Results also indicate a positive relationship between functional diversity and the number of stress response genes. This study provides insight into the stress resilience of microbial metabolic pathways supported by greater taxonomic diversity, which may affect the microbial community response to climate change.
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Affiliation(s)
- Qiuyuan Huang
- Department of Geology and Environmental Earth Science, Miami University, Oxford, Ohio, United States of America
- Department of Microbiology, University of Georgia, Athens, Georgia, United States of America
| | - Brandon R. Briggs
- Department of Geology and Environmental Earth Science, Miami University, Oxford, Ohio, United States of America
| | - Hailiang Dong
- Department of Geology and Environmental Earth Science, Miami University, Oxford, Ohio, United States of America
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing, China
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
| | - Hongchen Jiang
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
| | - Geng Wu
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
| | - Christian Edwardson
- Department of Microbiology, University of Georgia, Athens, Georgia, United States of America
| | - Iwijn De Vlaminck
- Departments of Bioengineering and Applied Physics, Stanford University and the Howard Hughes Medical Institute, Stanford, California, United States of America
| | - Stephen Quake
- Departments of Bioengineering and Applied Physics, Stanford University and the Howard Hughes Medical Institute, Stanford, California, United States of America
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23
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Jiang N, He J, Weinstein J, Penland L, Saaki S, He X, Dekker C, Wilson P, Greenberg H, Davis M, Fisher D, Quake S. High Throughput Sequencing of the Human Antibody Repertoire in Response to Influenza Vaccination (58.14). The Journal of Immunology 2012. [DOI: 10.4049/jimmunol.188.supp.58.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Abstract
Despite the many advances in personal genome analysis, the immunoglobulin repertoire of the genome, while central to human health, is in practice extraordinarily challenging to measure and analyze. There are several reasons for this, including the facts that each B cell contains a distinct antibody sequence encoded in its genome, that the antibody repertoire is not constant but changes over time, and the high similarity between antibody sequences. We have addressed this challenge by using high-throughput long read sequencing to perform immunogenetic characterization of expressed human antibody repertoires. Informatic analysis of large numbers of antibody heavy chain sequences from individual subjects allowed us to perform global characterizations of isotype distributions, clonal lineage structure of the repertoire and age-related mutational activity. With influenza vaccination as a specific stimulus, we used lineage analysis to measure the clonal structure and mutational distribution of individuals’ repertoires; analysis of this data showed that elderly subjects have a decreased number of lineages but an increased pre-vaccination mutation load in their repertoire and that some of these subjects have an oligoclonal character to their repertoire in which the diversity of the lineages is greatly reduced relative to younger subjects. These analyses may ultimately be useful as metrics to measure vaccine response and to further understand impaired immune function in aging.
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Affiliation(s)
- Ning Jiang
- 1Bioengineering, Stanford University, Stanford, CA
- 2Biomedical Engineering, University of Texas at Austin, Austin, TX
| | - Jiankui He
- 1Bioengineering, Stanford University, Stanford, CA
| | | | | | - Sanae Saaki
- 4Department of Medicine, Stanford University Sch. of Med., Stanford, CA
| | - Xiaosong He
- 4Department of Medicine, Stanford University Sch. of Med., Stanford, CA
| | - Cornelia Dekker
- 5Department of Pediatrics, Stanford University Sch. of Med., Stanford, CA
| | - Patrick Wilson
- 7Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL
| | - Harry Greenberg
- 4Department of Medicine, Stanford University Sch. of Med., Stanford, CA
| | - Mark Davis
- 3Department of Immunology and Microbiology, Stanford University Sch. of Med., Stanford, CA
| | - Daniel Fisher
- 8Department of Applied Physics, Stanford University, Stanford, CA
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25
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Koh W, Fan C, Blumenfeld Y, Wong R, El-Sayed Y, Kogut E, Quake S. 730: Profiling maternal plasma cell-free RNA by RNA-sequencing: a comprehensive approach. Am J Obstet Gynecol 2012. [DOI: 10.1016/j.ajog.2011.10.748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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26
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Quake S. Biological Large Scale Integration. Biophys J 2012. [DOI: 10.1016/j.bpj.2011.11.2337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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27
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Abstract
AbstractWe illustrate the concept of noninvasive determination of the fetal genome by shotgun sequencing maternal plasma. The approach is based on molecular counting of alleles in maternal cell-free DNA: the inheritance of paternal haplotypes can be determined by counting paternal specific alleles present on each of the paternal haplotypes; the inheritance of maternal haplotypes can be revealed by counting the alleles on each maternal haplotype and determining the relative representation of the two maternal haplotypes. The concept was experimentally proven by sequencing a synthetic mixture of genomic DNA samples from a child and her mother, whose whole-genome haplotypes (defined by ~800,000 SNPs), together with those of the father, were previously determined. Light sequencing (0.25x) of such sample containing ~16% child’s DNA enabled the inheritance of parental haplotypes to be correctly resolved over most part of the genome, and partially resolved when prior knowledge of paternal whole-genome haplotypes is absent. Translating this approach to maternal plasma DNA samples, together with increased sequencing depth and phase knowledge of additional numbers of parental SNPs, should enable clinically practical sequencing of the fetal genome.
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28
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Verpoorte S, Northrup MA, Yager P, Quake S, Landers J. Microtechnology in the clinical laboratory: will it solve analytical problems, and when will it make an impact? Clin Chem 2010; 56:508-14. [PMID: 20167692 DOI: 10.1373/clinchem.2009.138719] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Sabeth Verpoorte
- Groningen Research Institute of Pharmacy, University of Groningen, the Netherlands
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29
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Spletter ML, Liu J, Liu J, Su H, Giniger E, Komiyama T, Quake S, Luo L. Lola regulates Drosophila olfactory projection neuron identity and targeting specificity. Neural Dev 2007; 2:14. [PMID: 17634136 PMCID: PMC1947980 DOI: 10.1186/1749-8104-2-14] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2007] [Accepted: 07/16/2007] [Indexed: 11/25/2022] Open
Abstract
Background Precise connections of neural circuits can be specified by genetic programming. In the Drosophila olfactory system, projection neurons (PNs) send dendrites to single glomeruli in the antenna lobe (AL) based upon lineage and birth order and send axons with stereotyped terminations to higher olfactory centers. These decisions are likely specified by a PN-intrinsic transcriptional code that regulates the expression of cell-surface molecules to instruct wiring specificity. Results We find that the loss of longitudinals lacking (lola), which encodes a BTB-Zn-finger transcription factor with 20 predicted splice isoforms, results in wiring defects in both axons and dendrites of all lineages of PNs. RNA in situ hybridization and quantitative RT-PCR suggest that most if not all lola isoforms are expressed in all PNs, but different isoforms are expressed at widely varying levels. Overexpression of individual lola isoforms fails to rescue the lola null phenotypes and causes additional phenotypes. Loss of lola also results in ectopic expression of Gal4 drivers in multiple cell types and in the loss of transcription factor gene lim1 expression in ventral PNs. Conclusion Our results indicate that lola is required for wiring of axons and dendrites of most PN classes, and suggest a need for its molecular diversity. Expression pattern changes of Gal4 drivers in lola-/- clones imply that lola normally represses the expression of these regulatory elements in a subset of the cells surrounding the AL. We propose that Lola functions as a general transcription factor that regulates the expression of multiple genes ultimately controlling PN identity and wiring specificity.
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Affiliation(s)
- Maria Lynn Spletter
- Howard Hughes Medical Institute, Department of Biological Sciences, Stanford University, Stanford, California 94305, USA
| | - Jian Liu
- Howard Hughes Medical Institute, Department of Bioengineering, Stanford University, Stanford, California 94305, USA
- Department of Biomedical Engineering, Emory University, Atlanta, Georgia 30322, USA
| | - Justin Liu
- Howard Hughes Medical Institute, Department of Biological Sciences, Stanford University, Stanford, California 94305, USA
| | - Helen Su
- Howard Hughes Medical Institute, Department of Biological Sciences, Stanford University, Stanford, California 94305, USA
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Edward Giniger
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Takaki Komiyama
- Howard Hughes Medical Institute, Department of Biological Sciences, Stanford University, Stanford, California 94305, USA
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Stephen Quake
- Howard Hughes Medical Institute, Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Liqun Luo
- Howard Hughes Medical Institute, Department of Biological Sciences, Stanford University, Stanford, California 94305, USA
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Quake S. At the interface of physics and biology. Biotechniques 2007; 43:19. [PMID: 17695250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023] Open
Affiliation(s)
- Stephen Quake
- Department of Bioengineering, Howard Hughes Medical Institute, Stanford University, Palo Alto, CA, USA
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Quake S. Biological Large Scale Integration. CHEM-ING-TECH 2006. [DOI: 10.1002/cite.200650512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Liu J, Williams BA, Gwirtz RM, Wold BJ, Quake S. Enhanced Signals and Fast Nucleic Acid Hybridization By Microfluidic Chaotic Mixing. Angew Chem Int Ed Engl 2006. [DOI: 10.1002/ange.200503830] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Liu J, Williams BA, Gwirtz RM, Wold BJ, Quake S. Enhanced Signals and Fast Nucleic Acid Hybridization By Microfluidic Chaotic Mixing. Angew Chem Int Ed Engl 2006; 45:3618-23. [PMID: 16639763 DOI: 10.1002/anie.200503830] [Citation(s) in RCA: 50] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jian Liu
- California Institute of Technology, Pasadena, CA 94305, USA
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Abstract
Polymerase chain reaction (PCR) has revolutionized a variety of assays in biotechnology. The ability to implement PCR in disposable and reliable microfluidic chips will facilitate its use in applications such as rapid medical diagnostics, food control testing, and biological weapons detection. We fabricated a microfluidic chip with integrated heaters and plumbing in which various forms of PCR have been successfully demonstrated. The device uses only 12 nL of sample, one of the smallest sample volumes demonstrated to date. Minimizing the sample volume allows low power consumption, reduced reagent costs, and ultimately more rapid thermal cycling.
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Affiliation(s)
- Jian Liu
- Department of Chemistry, California Institute of Technology, Pasadena, 91125, USA
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Chiu CS, Kartalov E, Unger M, Quake S, Lester HA. Single-molecule measurements calibrate green fluorescent protein surface densities on transparent beads for use with 'knock-in' animals and other expression systems. J Neurosci Methods 2001; 105:55-63. [PMID: 11166366 DOI: 10.1016/s0165-0270(00)00354-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Quantitative aspects of synaptic transmission can be studied by inserting green fluorescent protein (GFP) moieties into the genes encoding membrane proteins. To provide calibrations for measurements on synapses expressing such proteins, we developed methods to quantify histidine-tagged GFP molecules (His6-GFP) bound to Ni-NTA moieties on transparent beads (80-120 microm diameter) over a density range comprising nearly four orders of magnitude (to 30000 GFP/microm2). The procedures employ commonly available Hg lamps, fluorescent microscopes, and CCD cameras. Two independent routes are employed: (1) single-molecule fluorescence measurements are made at the lowest GFP densities, providing an absolute calibration for macroscopic signals at higher GFP densities; (2) known numbers of His6-GFP molecules are coupled quantitatively to the beads. Each of the two independent routes provides linear data over the measured density range, and the two independent methods agree with root mean square (rms) deviation of 11-21% over this range. These satisfactory results are obtained on two separate microscope systems. The data can be corrected for bleaching rates, which are linear with light intensity and become appreciable at intensities > approximately 1 W/cm2. If a suitable GFP-tagged protein can be chosen and incorporated into a 'knock-in' animal, the density of the protein can be measured with an absolute accuracy on the order of 20%.
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Affiliation(s)
- C S Chiu
- Division of Biology, California Institute of Technology, 91125, Pasadena, CA, USA
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Abstract
We have demonstrated a microfabricated single-molecule DNA sizing device. This device does not depend on mobility to measure molecule size, is 100 times faster than pulsed-field gel electrophoresis, and has a resolution that improves with increasing DNA length. It also requires a million times less sample than pulsed-field gel electrophoresis and has comparable resolution for large molecules. Here we describe the fabrication and use of the single-molecule DNA sizing device for sizing and sorting DNA restriction digests and ladders spanning 2-200 kbp.
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Affiliation(s)
- H P Chou
- Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA
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