{ Jefry Lagrange Stuart Weinberg Daniel Zegel CMACS Jan 2012 Cell Signaling Pathway Workshop – Pancreatic Cancer HMGB1 – RAGE – Cyclin E pathway.

Slides:



Advertisements
Similar presentations
BL TIER 3 TIER 3 Identify suitable experimental procedures for measuring rates of reactions Identify the factors affecting the rate of a reaction Calculate.
Advertisements

Factors Affecting the Rate of a Chemical Reaction
Biology of cultured cells conti- Part 4 By : Saib al owini.
Lab 7: Cell Division: Mitosis and Meiosis. Chapter 12/13 - Cell Cycle, Meiosis, and Sexual cycles AIM: Describe how the cell cycle is regulated. Are there.
An Intro To Systems Biology: Design Principles of Biological Circuits Uri Alon Presented by: Sharon Harel.
Evaluating Existing in vitro Endocrine Data Jeff Pregenzer, Director of Endocrine Studies, CeeTox.
CELL TO CELL COMMUNICATION Part 2. Transduction: Cascades relay signals Signal transduction involves multiple steps Multistep pathways can amplify a signal.
THE CONTROL OF GENE EXPRESSION. GENE EXPRESSION – THE OVERALL PROCESS BY WHICH GENETIC INFORMATION FLOWS FROM GENES TO PROTEINS PROKARYOTES ARE BEST TO.
The interaction between the Wnt –and Notch-pathways in colorectal cancer development by: John Grünberg The aim is to study the interaction between the.
Review Enzymes are specific to a substrate Based on shape (lock & key) Enzymes are NOT consumed or changed by catalyzed reaction Great for speeding up.
D ISCOVERING REGULATORY AND SIGNALLING CIRCUITS IN MOLECULAR INTERACTION NETWORK Ideker Bioinformatics 2002 Presented by: Omrit Zemach April Seminar.
Acquired Capabilities Hanrahan and Weinberg, “Hallmarks of Cancer,” Cell, 2000.
CHEMICAL KINETICS AND EQUILIBRIUM Conner Forsberg.
Extracting Essential Features of Biological Networks Natalie Arkus, Michael P. Brenner School of Engineering and Applied Sciences Harvard University.
Limiting factors Factors affecting the rate of reactions.
 Definition of metabolism  Definition of a substrate  Characteristics of metabolic pathways  Why we need metabolic pathways.
Tumor genetics Minna Thullberg
Biological Oscillations Using the Goodwin Oscillator as a model of negative feedback J. Watrous Biology Department St. Joseph’s University July, 2008.
 Background information › PTEN (function, connection with breast cancer)  Objective  Experimental Approach and Results  Conclusion  Future research.
e/animations/hires/a_cancer5_h.html
Section 6.4 ~ Ideas of Risk and Life Expectancy Introduction to Probability and Statistics Ms. Young.
Cell Cycle.
The control of blood sugar 1. Blood sugar levels are higher than normal after a meal is digested. 2.
Chapter 11: Cell Communication. Essential Knowledge 2.e.2 – Timing and coordination of physiological events are regulated by multiple mechanisms (11.1).
Insights into normal cell biology Targets for diagnosis and follow-up
Response: Cell signaling leads to regulation of transcription or cytoplasmic activities Chapter 11.4.
Chemical Reactions. Cornell Notes  Title your notes: Chemical Reactions Notes  Add topics and summary after re-reading the notes.
AP Biology The Cell Cycle Part 1. One cell becoming two.
ENZYMES. Vocabulary(4 slides are review from last day) Metabolism Anabolic Pathways Catabolic Pathways Free Energy Activation Energy Catalysts.
WJEC GCE BIOLOGY Inhibitors and Enzyme Action Graphs to show the effects of Inhibitors on Enzyme Action 3.2.
Enzymes.  Proteins play major roles in the cell, but none as important as making up enzymes.  Enzymes permit reactions to occur at rates of thousands.
 Regulation of Cell Number and Cancer Cells Special Limited Edition Packet Tuesday, November 10,
Reaction Rates AP chapter Reaction Rates Describe how quickly concentration of reactants or products are changing Units typically  M/  t for aqueous.
Presentable Market Data. Understanding three views of the current market allows Buyers to maximize their ability to evaluate properties, receiving the.
INTRINSIC APOPTOSIS PATHWAY INTRINSIC APOPTOSIS PATHWAY Marieta Garib Aisha Green Linda Miranda.
The Cell Cycle and Cancer AP Biology. Cell Cycle Numerous genes control the cell cycle They regulate the progression through checkpoints. A sensor detects.
Chapter 12: The Cell Cycle
Hybrid Functional Petri Net model of the Canonical Wnt Pathway Koh Yeow Nam, Geoffrey.
Copyright©2000 by Houghton Mifflin Company. All rights reserved. 1 Chemical Kinetics The area of chemistry that concerns reaction rates.
Cell to Cell Communication
Lecture 10: Cell cycle Dr. Mamoun Ahram Faculty of Medicine
Enzymes. What are they? Globular Proteins: This is important in explaining how heat can denature them – think tertiary structure Biological catalysts:
Introduction Nancy Griffeth. Outline What will we be doing Why I think computational biology is fun.
Inhibition Nucleic Acids Enzyme Structure Temp/ pH Enzymes Enzyme/Sub strate conc
Enzymes: They do all the work! Enzymes  Proteins  Help chemical reactions happen  reduce activation energy  increase rate of reaction.
Enzymes Catalyst – substance that speeds up the rate of a chemical reaction Enzymes – proteins that act as biological catalysts (speed up chemical reactions.
Relationship Between STAT3 Inhibition and the Presence of p53 on Cyclin D1 Gene Expression in Human Breast Cancer Cell Lines Introduction STAT3 and p53.
3.A.2 Cell Division Part I The Cell Cycle and Mitosis In eukaryotes, heritable information is passed to the next generation via processes that include.
Cell Cycle Regulation Chapter – Pt. 1 Pgs Objective: I can describe and how the cell cycle is regulated and controlled to occur at certain.
Gene Expression (Epigenetics) Chapter 19. What you need to know The functions of the three parts of an operon. The role of repressor genes in operons.
10.3 Regulating the Cell Cycle. 2 Which of the cells depicted in the line graph below are most likely cancerous?
Unit 4 - Immunology and Public Health CfE Higher Human Biology Specific Cellular Defences.
Acquired Capabilities
Transversal calibration of Geiger Cells
Control of Gene Expression
Regulation of the Cell Cycle & Cancer
Supplementary Table. Gene expression profiling reveals a decrease in NFkB-driven gene signature pattern upon treatment with MLN4924. Gene ID Name Treated/
Chap. 16 Problem 1 Cytokine receptors and RTKs both form functional dimers on binding of ligand. Ligand binding activates cytosolic kinase domains which.
Cell Signaling.
U01L04: ENZYMES.
Dan Gordon  Gastroenterology  Volume 114, Issue 4, (April 1998)
Regulation of the Cell Cycle
Graphs to show the effects of Inhibitors on Enzyme Action
Cancer and the Cell Cycle
VH Prove out tests with data available
C. Some factors are: 1. pH 2. Temperature
U01L04: ENZYMES.
Overview of molecular JAK signaling.
Presentation transcript:

{ Jefry Lagrange Stuart Weinberg Daniel Zegel CMACS Jan 2012 Cell Signaling Pathway Workshop – Pancreatic Cancer HMGB1 – RAGE – Cyclin E pathway

Ligand – HMGB1 Receptor – RAGE (Receptor for Advanced Glycation End-Products) Target – Cyclin E (CE) The binding of HMGB1 to RAGE is known to initiate three major pathways: apoptosis, DNA repair, cell proliferation via admittance to S Phase. The Characters and the Plot

HMGB1 is active as two forms: a secreted cytokine a nuclear non-histone transcription factor protein The Plot thickens

HMGB1 Pathway

Abstract of HMGB1 wire model

HMGB1 and RAGE is over-expressed in many cancers HMGB1 and RAGE is over-expressed in many cancers Higher concentrations of HMGB1 with RAGE at 10 5 (Cancer cell rate) - activation time is quickest. Higher concentrations of HMGB1 with RAGE at 10 5 (Cancer cell rate) - activation time is quickest.

RAGE 10 5 _ HMGB1 concentrations

Earliest activation time approx 28 Seconds _ HMGB highest probability Earliest activation time approx 28 Seconds _ HMGB highest probability 10 4, 10 3 concentrations follow, then , 10 3 concentrations follow, then 10 5 However after several seconds 10 4 & 10 3 increase rapidly However after several seconds 10 4 & 10 3 increase rapidly Concentrations 10 2, 10 1, & 1 lag expectedly Concentrations 10 2, 10 1, & 1 lag expectedly Observations

RAGE 10 4 _ HMGB1 concentrations

10 4 earliest activation time at 28 sec but at a lower probability than at RAGE earliest activation time at 28 sec but at a lower probability than at RAGE & 10 5 follow with the next highest probability 10 6 & 10 5 follow with the next highest probability Around 88 seconds 10 6 is the greatest chance of first CE activation Around 88 seconds 10 6 is the greatest chance of first CE activation Observations

RAGE 10 3 _ HMGB1 concentrations

At RAGE 10 3 – HMGB1 concentrations above 10 3 saturate the receptor dropping off quickly At RAGE 10 3 – HMGB1 concentrations above 10 3 saturate the receptor dropping off quickly HMGB activates CE next and also drops off HMGB activates CE next and also drops off Conclusions

RAGE 10 2 _ HMGB1 concentrations

First activation most probable not until around 150 seconds First activation most probable not until around 150 seconds 10 5 first activation followed by first activation followed by most probable to start activating closer together as RAGE concentration is lowered most probable to start activating closer together as RAGE concentration is lowered Observations

RAGE 10 1 _ HMGB1 concentrations

RAGE at 10 1 –Activation time slows greatly RAGE at 10 1 –Activation time slows greatly Probability of activation at a given time decreases Probability of activation at a given time decreases Observations

CE activates soonest with “higher” overall concentrations of HMGB1 and RAGE CE activates soonest with “higher” overall concentrations of HMGB1 and RAGE As RAGE is reduced and our ligand HMGB1 is still at high concentrations first activation of CE is delayed As RAGE is reduced and our ligand HMGB1 is still at high concentrations first activation of CE is delayed RAGE expression appears to have the greater impact on CE first activation RAGE expression appears to have the greater impact on CE first activation Below around 600 RAGE there is no activation of CE even with a very high HMGB1 Below around 600 RAGE there is no activation of CE even with a very high HMGB1 Conclusions

More data would be better More data would be better Graphs difficult to analyze Graphs difficult to analyze Simulations take too long Simulations take too long Certain parameters and reactions not congruent with biological model – i.e. non- degrading ligand Certain parameters and reactions not congruent with biological model – i.e. non- degrading ligand Issues, concerns, problems