Steady states and cellular transitions associated with carcinogenesis and tumorprogression
与癌发生和肿瘤进展相关的稳态和细胞转变
基本信息
- 批准号:10249961
- 负责人:
- 金额:$ 67.07万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-08-08 至 2023-07-31
- 项目状态:已结题
- 来源:
- 关键词:BRAF geneBiologicalBiological AssayBreastCancer ModelCancerousCell Cycle KineticsCell LineCell modelCellsCellular AssayChemicalsCombined Modality TherapyComplementCoupledDataDoseDrug ToleranceDrug resistanceEpidermal Growth Factor Receptor Tyrosine Kinase InhibitorExposure toFRAP1 geneFreedomGenesGenotypeGlioblastomaGoalsGrowthHumanImmunotherapyIsing modelJointsKineticsKnowledgeLawsMaintenanceMalignant NeoplasmsMalignant neoplasm of brainMeasurementMeasuresMelanoma CellMetabolicMetabolismMetastatic MelanomaModelingModificationNatureNeural CrestOutcomeOutputPatientsPharmaceutical PreparationsPhase TransitionPhenotypePhosphoproteinsPhysicsProcessProteinsProteomicsRegimenResearchResistanceResistance developmentScienceSignal TransductionSiteSystemTemperatureTestingTheoretical StudiesTheoretical modelWorkbasecancer cellcancer drug resistancecarcinogenesischemical carcinogencigarette smokecytokinedesigndrug developmentexome sequencingexperimental studygenetic regulatory proteinimprovedin silicoin vivo evaluationinhibitor/antagonistmelanocytemelanomamutantphysical modelprogramsprotein metaboliteresponsetargeted treatmenttheoriestherapy designtranscriptome sequencingtumortumor growthtumor progression
项目摘要
Project Summary/Abstract
Cellular transitions are fundamental to many steps of carcinogenesis and tumor progression. Such transitions
are broadly studied, but general models have been historically limited to qualitative descriptions. This contrasts
with phase transitions in physical systems, which are well characterized within the context of the physico-
chemical laws, and can be partially understood, in a predictive capacity, using simple, precise models such as
the Ising model. Such models are based upon a system of interacting lattice sites. A parameter (e.g.
Temperature) is varied, and the fluctuations of the lattice sites are analyzed as the system approaches and
passes through a critical point. All critical system-specific details are captured in the interactions between the
lattice sites, and the models can yield specific, experimentally verifiable predictions. Ising-like in silico models
have guided theoretical studies of transitions in various gene or protein regulatory networks, although resultant
predictions can be challenging to experimentally test.
We seek a general approach where the experimental input is a statistically large number of single cell
measurements, with many protein and metabolite analytes quantitatively measured per cell. From this data we
capture the fluctuations and thereby determine the analyte-analyte correlations. In an Ising model analogy,
such measurements define the site interactions. These inputs permit straightforward theoretic models for
resolving cellular steady states, transitions between steady states, and for making testable predictions. Studies
of the chemically-induced-carcinogenesis transition provide preliminary data/proof of concept. For Aim 1 we
develop a picture of cancer cell steady states using integrated metabolic and proteomic single cell assays on
cancer models of Glioblastoma Multiforme and Melanoma. In Aims 2 and 3 we expand this approach to two
apparent cellular transitions associated with resistance against targeted therapies: the adaptation of
heterogeneous brain cancers to certain targeted inhibitors, and a drug-induced cellular de-differentiation
observed in melanomas and other tumors in response to immunotherapy and targeted inhibitors. All aims are
joint experiment/theory aims. Aims 2-3 involve in vivo testing of predictions, as well as exome sequencing and
global RNA-seq kinetic studies to complement the single cell kinetic analyses.
Anticipated outcomes of the work include a general, quantitative approach towards describing cellular
transitions associated with cancer. Further, we propose to mine those descriptions of cellular transitions to
identify therapy combinations that are designed to hit targets that drive tumor growth, as well as those that
drive the transition (and thus promote resistance) Preliminary data to support of this goal is provided.
Additionally, guidance for non-continuous therapy dosing (e.g. metronomic or pulsatile regimens) that exploit
knowledge of the kinetics, barriers, and reversibility of the transition to resistance is anticipated
项目总结/文摘
项目成果
期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Raman-guided subcellular pharmaco-metabolomics for metastatic melanoma cells.
- DOI:10.1038/s41467-020-18376-x
- 发表时间:2020-09-24
- 期刊:
- 影响因子:16.6
- 作者:Du J;Su Y;Qian C;Yuan D;Miao K;Lee D;Ng AHC;Wijker RS;Ribas A;Levine RD;Heath JR;Wei L
- 通讯作者:Wei L
Resolution of tissue signatures of therapy response in patients with recurrent GBM treated with neoadjuvant anti-PD1.
- DOI:10.1038/s41467-021-24293-4
- 发表时间:2021-06-29
- 期刊:
- 影响因子:16.6
- 作者:Lu Y;Ng AHC;Chow FE;Everson RG;Helmink BA;Tetzlaff MT;Thakur R;Wargo JA;Cloughesy TF;Prins RM;Heath JR
- 通讯作者:Heath JR
Surface Immobilization of Redox-Labile Fluorescent Probes: Enabling Single-Cell Co-Profiling of Aerobic Glycolysis and Oncogenic Protein Signaling Activities.
- DOI:10.1002/anie.201803034
- 发表时间:2018-09-03
- 期刊:
- 影响因子:0
- 作者:Li Z;Cheng H;Shao S;Lu X;Mo L;Tsang J;Zeng P;Guo Z;Wang S;Nathanson DA;Heath JR;Wei W;Xue M
- 通讯作者:Xue M
Single-cell profiling of D-2-hydroxyglutarate using surface-immobilized resazurin analogs.
- DOI:10.1016/j.bios.2021.113368
- 发表时间:2021-10-15
- 期刊:
- 影响因子:12.6
- 作者:Cheng H;Li Z;Guo Z;Shao S;Mo L;Wei W;Xue M
- 通讯作者:Xue M
4D electron microscopy of T cell activation.
T 细胞激活的 4D 电子显微镜。
- DOI:10.1073/pnas.1914078116
- 发表时间:2019
- 期刊:
- 影响因子:11.1
- 作者:Lu,Yue;Yoo,Byung-Kuk;Ng,AlphonsusHC;Kim,Jungwoo;Yeom,Sinchul;Tang,Jau;Lin,MiloM;Zewail,AhmedH;Heath,JamesR
- 通讯作者:Heath,JamesR
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James R. Heath其他文献
Correction: Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19
- DOI:
10.1186/s13073-023-01278-0 - 发表时间:
2024-01-06 - 期刊:
- 影响因子:11.200
- 作者:
Daniela Matuozzo;Estelle Talouarn;Astrid Marchal;Peng Zhang;Jeremy Manry;Yoann Seeleuthner;Yu Zhang;Alexandre Bolze;Matthieu Chaldebas;Baptiste Milisavljevic;Adrian Gervais;Paul Bastard;Takaki Asano;Lucy Bizien;Federica Barzaghi;Hassan Abolhassani;Ahmad Abou Tayoun;Alessandro Aiuti;Ilad Alavi Darazam;Luis M. Allende;Rebeca Alonso-Arias;Andrés Augusto Arias;Gokhan Aytekin;Peter Bergman;Simone Bondesan;Yenan T. Bryceson;Ingrid G. Bustos;Oscar Cabrera-Marante;Sheila Carcel;Paola Carrera;Giorgio Casari;Khalil Chaïbi;Roger Colobran;Antonio Condino-Neto;Laura E. Covill;Ottavia M. Delmonte;Loubna El Zein;Carlos Flores;Peter K. Gregersen;Marta Gut;Filomeen Haerynck;Rabih Halwani;Selda Hancerli;Lennart Hammarström;Nevin Hatipoğlu;Adem Karbuz;Sevgi Keles;Christèle Kyheng;Rafael Leon-Lopez;Jose Luis Franco;Davood Mansouri;Javier Martinez-Picado;Ozge Metin Akcan;Isabelle Migeotte;Pierre-Emmanuel Morange;Guillaume Morelle;Andrea Martin-Nalda;Giuseppe Novelli;Antonio Novelli;Tayfun Ozcelik;Figen Palabiyik;Qiang Pan-Hammarström;Rebeca Pérez de Diego;Laura Planas-Serra;Daniel E. Pleguezuelo;Carolina Prando;Aurora Pujol;Luis Felipe Reyes;Jacques G. Rivière;Carlos Rodriguez-Gallego;Julian Rojas;Patrizia Rovere-Querini;Agatha Schlüter;Mohammad Shahrooei;Ali Sobh;Pere Soler-Palacin;Yacine Tandjaoui-Lambiotte;Imran Tipu;Cristina Tresoldi;Jesus Troya;Diederik van de Beek;Mayana Zatz;Pawel Zawadzki;Saleh Zaid Al-Muhsen;Mohammed Faraj Alosaimi;Fahad M. Alsohime;Hagit Baris-Feldman;Manish J. Butte;Stefan N. Constantinescu;Megan A. Cooper;Clifton L. Dalgard;Jacques Fellay;James R. Heath;Yu-Lung Lau;Richard P. Lifton;Tom Maniatis;Trine H. Mogensen;Horst von Bernuth;Alban Lermine;Michel Vidaud;Anne Boland;Jean-François Deleuze;Robert Nussbaum;Amanda Kahn-Kirby;France Mentre;Sarah Tubiana;Guy Gorochov;Florence Tubach;Pierre Hausfater;Isabelle Meyts;Shen-Ying Zhang;Anne Puel;Luigi D. Notarangelo;Stephanie Boisson-Dupuis;Helen C. Su;Bertrand Boisson;Emmanuelle Jouanguy;Jean-Laurent Casanova;Qian Zhang;Laurent Abel;Aurélie Cobat - 通讯作者:
Aurélie Cobat
C60's smallest cousin
C60 的最小“亲戚”
- DOI:
10.1038/31579 - 发表时间:
1998-06-25 - 期刊:
- 影响因子:48.500
- 作者:
James R. Heath - 通讯作者:
James R. Heath
Protein Catalyzed Capture (PCC) Agents for Antigen Targeting.
用于抗原靶向的蛋白质催化捕获 (PCC) 试剂。
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
M. Idso;B. Lai;Heather D Agnew;James R. Heath - 通讯作者:
James R. Heath
Planar Patch-Clamp Electrodes for Single Cell and Neural Network Studies
- DOI:
10.1016/j.bpj.2009.12.3287 - 发表时间:
2010-01-01 - 期刊:
- 影响因子:
- 作者:
John M. Nagarah;Daniel A. Wagenaar;James R. Heath - 通讯作者:
James R. Heath
Stereochemical engineering of a peptide macrocycle allosteric inhibitor of phospho-Akt2 controls cell penetration by fine-tuning macrocycle-cell membrane interactions
磷酸 Akt2 肽大环变构抑制剂的立体化学工程通过微调大环 - 细胞膜相互作用来控制细胞渗透
- DOI:
10.26434/chemrxiv-2021-kldh7 - 发表时间:
2021 - 期刊:
- 影响因子:5.9
- 作者:
Arundhati Nag;A. Mafi;Samir R Das;Mary Beth Yu;Belen Alvarez;W. Goddard;James R. Heath - 通讯作者:
James R. Heath
James R. Heath的其他文献
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- 作者:
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{{ truncateString('James R. Heath', 18)}}的其他基金
Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor: Immunotherapy Combinations (ST-Analytics)
用于指导序贯靶向抑制剂的时空肿瘤分析:免疫治疗组合(ST-Analytics)
- 批准号:
10708901 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
PROJECT 1: TIME-Based Spatiotemporal Cancer Immunograms Predictive for Immunotherapy-Targeted Therapy Sequential Combinations
项目 1:基于时间的时空癌症免疫图预测免疫治疗靶向治疗顺序组合
- 批准号:
10907268 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor: Immunotherapy Combinations (ST-Analytics)
用于指导序贯靶向抑制剂的时空肿瘤分析:免疫治疗组合(ST-Analytics)
- 批准号:
10526101 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
PROJECT 1: TIME-Based Spatiotemporal Cancer Immunograms Predictive for Immunotherapy-Targeted Therapy Sequential Combinations
项目 1:基于时间的时空癌症免疫图预测免疫治疗靶向治疗顺序组合
- 批准号:
10526103 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
PROJECT 1: TIME-Based Spatiotemporal Cancer Immunograms Predictive for Immunotherapy-Targeted Therapy Sequential Combinations
项目 1:基于时间的时空癌症免疫图预测免疫治疗靶向治疗顺序组合
- 批准号:
10708924 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
Data-driven Patient-Specific Agent Based Models of Metastatic Melanoma for Immunotherapy Response Prediction
用于免疫治疗反应预测的数据驱动的基于患者特异性药物的转移性黑色素瘤模型
- 批准号:
10831325 - 财政年份:2022
- 资助金额:
$ 67.07万 - 项目类别:
Nano and biomolecular engineered technologies for neoantigen-specific T cell capture and characterization
用于新抗原特异性 T 细胞捕获和表征的纳米和生物分子工程技术
- 批准号:
10297588 - 财政年份:2021
- 资助金额:
$ 67.07万 - 项目类别:
Nano and biomolecular engineered technologies for neoantigen-specific T cell capture and characterization
用于新抗原特异性 T 细胞捕获和表征的纳米和生物分子工程技术
- 批准号:
10489832 - 财政年份:2021
- 资助金额:
$ 67.07万 - 项目类别:
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