Bhalerao Kaustubh D

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ABSTRACT

The cantilever-based BioMEMS sensorrepresents one instancefrom many competingideas of biosensor technology based on Micro Electro Mechanical Systems.The advancementof BioMEMSfrom laboratory -scale experimentstoapplications

in the field will require standardization of their components and manufacturingprocedures as well as frameworks to evaluate their performance.

Reliability, the likelihood with which a system performs its intended task, is acompact mathematical description of its performance. The mathematical and statisticalfoundation of systems-reliability has been applied to the cantilever-basedBioMEMS sensor. The sensor is designed to detect one aspect of human ovariancancer, namely the over-expression of the folate receptor surface protein (FR ).Even as the application chosen is clinically motivated, the objective of this study

was to demonstrate the underlying systems-based methodology used to design,develop and evaluate the sensor. The framework development can be readily extendedto other BioMEMS-based devices for disease detection and will have animpact in the rapidly growing $30 bn industry.

The Unified Modeling Language (UML) is a systems-based framework for designand development of object-oriented information systems which has potentialapplication for use in systems designed to interact with biological environments.The UML has been used to abstract and describe the application of the biosensor,to

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identify key components of the biosensor, and the technology needed to link themtogetherina coherent manner. The useofthe frameworkis also demonstratedincomputationofsystemreliabilityfromfirst principlesasafunctionofthestructureand materials of the biosensor.

The outcomes of applying the systems-based framework to the study are thefollowing:

Characterizing the cantilever-based MEMS device for disease (cell) detection. Development of a novel chemical interface between the analyte and the sensorthat provides a degree of selectivity towards the disease. Demonstrating the performance and measuring the reliability of the biosensorprototype, and Identification of opportunities in technological development in order to furtherrefine the proposed biosensor.Application of the methodology to design develop and evaluate the reliability

of BioMEMS devices will be beneficial in the streamlining the growth of theBioMEMS industry, while providing a decision-support tool in comparing andadopting suitable technologies from available competing options.

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ACKNOWLEDGMENTS

Iwould like to thank my advisers, Drs. A.B.O. Soboyejo,W.O. Soboyejo, S.C.Leeand K.C.Tingfor supportingand guiding thisproject.I am indebtedto theirgenerosity with their time,resources and enthusiasm. Through their adviceIhave

learned not only proper scientific methodology, but also their personal philosophyand insight into a multidisciplinary project likely to affect all of mankind.Drs. A.B.O. Soboyejo allowed me the benefit of his constant guidance and overallsupervision. Dr. Ting provided the theoretical framework to initiate the systems-based analysis for the research. The execution of this project would have been extremelydifficultwithoutthe laboratory supportbyDr.W.O. Soboyejoat PrincetonUniversity and the Princeton Materials Institute. Equally valuable was the laboratory

facility and training provided by Dr. Lee and his research associate Mr. JohnShapiro at the Davis Heart&Lung Institute.

Working together has allowed me to make friends with my colleagues, SteveMwenifumbo, Chris Milburn and Dr. Sadhana Sharma who helped me with someof the crucial experiments at various stages in this project. I would like to speciallythank Ms. Jessica Prenger for proofreading and editing the first draft of thisdocument, spotting the errors and inconsistencies in the document.

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Last,butnottheleast,Iwouldliketothankthe National Science Foundationforhaving financially supported this research as well as my education. This researchwould not have been possible without the support.

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To my parentsNetra and Deepakwho believedI was capableof completing this degree.

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VITA

February09 1978 .......................... Dateof Birth

August1999 ...............................B.E.Civil Engineering,Pune University

June2001 ..................................M.S.Food, Agricultural

and Biological Engineering,

The Ohio State University

June 2001 -December 2001 . . . . . . . . . . . . . . . . .Visiting researcher,Princeton University

January 2002 -June 2004 ................... Research Associate,The Ohio State University

PUBLICATIONS

Research Publications

Bhalerao K. D., Soboyejo A. B. O. and Soboyejo W. O., Modeling of fatigue inpolysilicon MEMS structures. Journal of Material Science, 38:4157-4161, 2003.

Soboyejo A.B.O.,BhaleraoK.D.and SoboyejoW.O., Reliability AssessmentofPolysilicon MEMS Structures under Mechanical Fatigue Loading. Journal of Material

Science, 38:4163-4167, 2003.

Bhalerao K. D., Shen W., Soboyejo A.B.O. and Soboyejo W. O., A probabilisticmultiparameter method for the modeling of fatigue crack growth in concrete.Journal of Cement and Concrete Composites, 25, 6, pp. 573-605, 2003.

Lou J., Bhalerao K. D., Soboyejo A. B. O. and SoboyejoW. O., An investigation offracture initiation and resistance-curve behavior in concrete. Journal of CementandConcrete Composites, 25, 6, pp. 607-615, 2003.

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TABLE OF CONTENTS

Page

Abstract......................................... ii

Acknowledgments .................................. iv

Dedication....................................... vi

Vita ........................................... vii

ListofFigures ..................................... xii

ListofTables ...................................... xix

Chapters:

1. INTRODUCTION................................ 1

1.1 Micro Electro-Mechanical Systems (MEMS) . . . . . . . . . . . . . . 1

1.2 MEMSBased Biosensors ......................... 7

1.3 BioMEMSinthe healthcareindustry .................. 9

1.4 Point-of-Care devices .......................... 10

1.5 Materials issues and BioMEMS reliability . . . . . . . . . . . . . . . 12

1.6Asystems-basedapproach ....................... 14

1.7 Objectives, significanceandscope ................... 16

2. MOTIVATIONIN DISEASE DETECTION .................. 19

2.1 Early detection and managementof cancer . . . . . . . . . . . . . . 20

2.2 Cancerbiologyina nutshell ....................... 24

2.2.1 Thecellcycle ........................... 25


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2.2.2 Apoptosis............................. 28

2.2.3Tumorigenesis .......................... 29

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2.3 The folatereceptor moleculeand cancer ................ 35

2.4 Asensor to detect the over-expression of the folate receptor . . . . 39

2.5 Integrating biological information for disease detection . . . . . . . 40

2.5.1 The folate receptor as a parameter in cancer detection . . . 42

3.THE SYSTEMS-BASED APPROACH ..................... 47

3.1The necessity of a new formalized systems engineering frameworkforbiosystems engineering. ................... 49

3.2

The benefitsofsystemsthinking .................... 51

3.3Object Oriented Analysis and Design (OOA/D) . . . . . . . . . . . 52

3.4The UnifiedModelingLanguage(UML) ............... 53

3.5UMLfor bio-nanodevicedesign .................... 56

4.MECHANICAL TRANSDUCTION USING A MICRO-CANTILEVERSYSTEM ..................................... 60

4.1Choiceof transducers .......................... 61

4.2Mechanical modeling of the cantilever system . . . . . . . . . . . . 65

4.2.1 Staticmoderesponse ...................... 66

4.2.2 Dynamicmoderesponse .................... 69

4.3 Benefits and limitations dynamic detection . . . . . . . . . . . . . . 72

4.4 Bounds in the sensitivity of cantilever detection . . . . . . . . . . . 74

4.5 Numerical simulations for reliability of the sensor . . . . . . . . . . 77

4.6 Implicationsforsinglecell detection .................. 79

5. BUILDINGTHE RECOGNITIONLAYER .................. 83


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5.1 Techniques and considerations for folic acid conjugation . . . . . . 85

5.2 Aprotocol to conjugate folic acid to a sensor surface . . . . . . . . 89

5.2.1 Step 1: Pretreatment of the Si/Tisurfaces . . . . . . . . . . . 89

5.2.2 Step 2: Silanization of the hydroxylated titanium layer . . . 91

5.2.3 Step3: DeploymentofFolicAcid ............... 93

5.3ELISA tests to ensure the presence of folic acid . . . . . . . . . . . . 94

5.4Tests recommended for further confirmation . . . . . . . . . . . . . 96

6.RELIABILITY MODELING AND EVALUATION . . . . . . . . . . . . . . 99

6.1 The mathematical foundations of systems reliability . . . . . . . . . 100

6.2 Reliability development for the cantilever sensor . . . . . . . . . . 106

6.3 Construction and testing of the sensor prototype . . . . . . . . . . . 109

6.4 Evaluationoftheprototype .......................111

6.5 Resultsand Implications .........................112

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7. FUTUREWORKAND CONCLUSION ...................120

7.1 Thedesigncycle .............................120

7.1.1 Improvements in the transducer layer . . . . . . . . . . . . . 121

7.1.2 Improvements in the recognition layer . . . . . . . . . . . . 122

7.1.3 Improvements in the representation layer . . . . . . . . . . 124

7.2 Applicationsinotherareas .......................125

7.3 The future of the cantilever based biosensor -conclusion . . . . . . 126

Bibliography.. . . . . . .. . . . . . .. . . . . . .. . . .. . .. . . .. . . . .

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LIST OF FIGURES

FigurePage

1.1The Nanoguitar. The above picture, taken with a scanning electronmicroscope, is a structure made out of crystalline silicon usingmicrofabrication techniques. The guitar is 10 m long, or aboutthe sizeofa humanred blood cell. It has6 strings, each the sizeof 50 nanometers, or 100 atoms wide. This structure was made byCornell University as a demonstration of their proficiency in creatingmicron-scaled devices with individual features in the nano-scalerange. Photo credits: D. Carr and H. Craighead, Cornell. .......... 31.2Mechanical motion due to electrostatic forces. Schematic showshow mechanical motion is derived from electrical energy by means

of electrostatic forces. Plate Ais fixed to the structure while elementB is movable. An alternating potential applied by D produces aperiodic attractive force between Aand B, which is balanced by thespring C. This produces oscillations in Bwhich can be harnessed formechanical motion. ............................. 41.3A MEMS micromotor. A microscopic photograph shows a motorbased on the electrostatic motion generation scheme described. Thefixed elements are shown as flat blocks on the top and the right side,while the movable element is shaped like the sector of the circle. Thecomb like structure provides an interface for electrostatic attraction.The restoring force is provided by the fixed beam shown enlarged.This device has been used to study fatigue in MEMS motors by observing

the surface evolution at the base of the notch in the supportbeam. .................................... 5xii


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1.4Piezoelectric stage for the AFM tip. This schematic shows the methodologyused for actuating an AFM cantilever tip. The silicon AFMtip is mounted atop a piezoelectric stage that is actuated by meansof an alternating current. The stage contracts and expands due tothe piezo effect and causes the cantilever to oscillate. When the

frequency of the stage equals that of the natural frequency of thecantilever (in the condition known as resonance) the efficiency ofmechanical motionisthehighest. ..................... 62.1Breast cancer survival. A conceptual graph showing the percentageof breast cancer survivors as a function of the stage in whichthey received treatment. The untreated survival rate fits an inverseGompertz model.[72] ........................... 232.2Phases of the cell cycle. Immediately after the Mor Mitosis phase,the cell enters the G1

(Gap1)phasein whichitproducestheproteinsnecessary for proceeding into the Sor Synthesis phase. Followingthe Sphase, the cell grows some more in the G2or Gap2phase beforeitprogressesinto mitotic division. The cell cycleis controlledbynumerousproteinsresponsiblefortheprogressionaswellas qualitycontrolofthereproductiveprocess. .................... 262.3Apoptosis through the caspase cascade. When the protein complexp53 detects an irreparable DNA damage, it upregulates Bax whichperforates the mitochondria. This releases cytochrome p450 that activated

the apoptosis protease activation factor APAF1. This triggersthe caspase cascade which leads to chromatin fragmentation. Subsequently,the cell sheds its matter in the form of small membrane-bound vesicles called blebs.......................... 302.4The raspathway. The epidermal growth factor (EGF) attached to itsreceptor on a cell wall (EFR) triggering the Guanine Exchange Factor(GEF) to phosphorylate the ras-bound Guanosine di-phosphate(rasGDP) and converting it to ras-bound Guanosine tri-phosphate(rasGTP). This then triggers the Mitogen Activating Protein (MAP)cascade of nuclear division. The ras is a substrate for the inactivating

enzyme GTPase which converts rasGTP back to rasGDP.A mutatedras gene does not provide an able substrate and produces asustained MAP signal leading torepeated nuclear division. . . . . . . 32xiii


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2.5The structure of folic acid. The folic acid molecule comprises of3 distinct moieties, the 6-methylpterin and L-glutamic acid, joinedtogether by a p-aminobenzoic acid linkage. The pterin head is thebiologically active component of folic acid and is recognized by thefolate antibodies. The a

carboninthe glutamic acid endis ideal forchemical attachment of folic acid to other molecules. . . . . . . . . . . 362.6The decision-making process in diagnostics. AUnified ModelingLanguagerepresentationoftheprocessof decision-makingfortreatmentof a disease. The physician draws upon multiple informationsources including the judgment of a pathologist before making adecision. New diagnostic devices will extend the capabilities of apathologist only if they can provide molecular and pathway informationintegrated with a systems biology framework in a completepackage.(The conventionsforUMLrepresentationare discussedinthenext chapter). .............................. 43

2.7Apart of the folate receptor subsystem. The FR-aprotein extendsthe properties of the FR-.with a hydrophobic tail. It is used bythe RFC to increase trans-membrane transport of folic acid. The expressionof folic acid is controlled at the mRNA level through interactionsof hormones with the promoter regions. There also exists anegative feedbackcontrolgovernedbythepresenceoffolicacidandmediated by cytosolic proteins (shown in double-headed arrows). . . 453.1A partial list of UML symbols. Objects are defined by their attributesand methods available. Objects are related to other objects

if they call methods of other objects, are extensions of other objectsor are subsets (parents) of other objects. They can be linked sequentially,conditionallyorprocedurally. ................... 55xiv


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3.2AUnifiedMarkupLanguage(UML)based representationofabiosensor.The recognition layer recognizes the biological analyte. Thisis usually a nano-scale component such as a biologically relevantmolecule. Examples include antibodies (for detecting antigens), single-stranded DNA oligonucleotide sequences (for pathological gene detection)

or even moleculesresponsible for biochemical functionality(such as folic acid to bind cancer cells). The transduction layer interfaceswith the recognition layer and converts the energy changesin the recognition layer into electrical energy that encodes informationabout analyte. The representation layer is a calibration on thisenergy conversion that indicates the encoded information. . . . . . . 594.1The transducer. The transducer attributes and methods are listedin the class description (top). The transducer component (indicatedwith the box and two smaller boxes on the left side) consists of threecomponents,all connectedin series. Thesearethemain energy conversiondevice and its input and output interfaces. . . . . . . . . . . . 62

4.2The Information Conversion Layer. The choice of information conversiondevicesisgovernedbytheinputandoutputinterfacesofthebiosensor. Since the input is due to a bio-chemical process (attachmentof folic acid to the folate receptor) and the output is encodedin electrical energy, it is possible that several transducer layers arerequired in series to accommodate the input and output. . . . . . . . 644.3The AFM cantilever structure. The cantilever structure used inatomicforcemicroscopyisusually fabricatedfrom siliconandhasasharptipforscanningthe surfaceonitsfreeend. ............ 664.4Deflection caused due to Stoneys stresses. Surface tension on one

sideofthe cantilever surface exertsa moment aboutthe neutral axisof the cantilever structure, causing it to acquire a curvature. . . . . . 674.5Adiscrete, undamped oscillator. An object of mass msuspendedfrom a spring having a modulus of elasticity k. It will oscillate undampedand unforced at a frequency fgiven in Equation 4.3. . . . . 70xv


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4.6Statistical analysis of cantilever resonance frequencies. Figureshowsthe histogram ofthe cantilever resonance frequencies and the Q-Qnormal plot for the samples. The Shapiro-Wilk test confirms that thesample does not comefromanormal distribution (p-valueis smallerthan0.05). .................................. 76

4.7Computing the Influence Line Diagram. The cantilever beam isloaded at point Awithaunitload. .................... 774.8The Influence Line Diagram for point B. The X axis is the ratiox

L, where xis the distance of the load from the fixed end and Lis

the length of the cantilever beam. The Yaxis is the load multiplierperceivedby the cantilever at point B. .................. 79

4.9Theoretical detection reliability of the cantilever structure. Therandom number simulation shows the reliability of the cantileversensorin detectingupto4cells. The stiffness normalizedfrequencychange is the left hand side of Equation 4.21. 1 through 4 cellsare shown in progressively heavier line thicknesses. The region of=10%probability of occurrence and thus high sensitivity and reliabilityis shown. The graph can be used to determine the minimum

frequency change that needs to be observed for a given confidencelevel of detection. Alternatively, it provides an estimate on the confidencelevel of detection of up to4cells based on an observed frequencyresponse............................... 804.10Cells on a cantilever. The photograph shows two cells attached tothe cantilever, on close to the fixed end and the other just behindthe sharp tip. It may be possible that the cell prefers to attach inthe concavities provided by the structure in order to minimize itssurface energy................................. 825.1Various recognition schemes. The folic acid molecule belongs to

the class of molecules relevant to biological function which can bethought of as analogs of biological signaling mechanisms. Thesemoleculesin turn operatebyaspecific molecular lock-and-key mechanism.This provides recognition by means of an affinity-based distinction.The UML representation scheme shows a possible way ofclassifyingdifferentrecognition schemes. Thecreationofa databasewith components in each of the categories shown above will enablethe simulation of devices with different recognition layers. . . . . . . 84xvi


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5.2Conjugation chemistry schemes. Different conjugation chemistryschemes to connect organic molecules to metallic/silicon surfacescanberepresentedasthree-partorgano-metallic linkers which haveone end connecting to the organic molecule and the other to metal.The are physically connected using (typically) a polymer such as

PEG. Open diamond-headed arrows signify aggregation or instantiation.Thus the disulfide linker is an instance of the organic binder. 865.3The silanization process. Titanium has a protective oxide layer. Itis made reactive by hydrolyzation. The hydrated surface is thencombined with a suitable silane forming the Si-O-Tistructure. . 885.4

ELISA test to detect presence of folic acid. Figure shows a box-whiskers plot representing the ELISA test for folic acid. Group 1representsthesignalduetofolicacid. Control1isthenegative controlfor when folic acidis absent, Control2is the non-specific bindingof the secondary antibody when folic acid is present and Control3 is the non-specific binding of the secondary antibody when folicacid is absent. The box-whisker plot shows the mean of the readingand the 25 and 75 percentile values with the horizontal lines and theextreme values seen in the data using the error bars. The averageblankreadingwas0.038 units.(notshown) ............... 976.1The reliability of a component. Acomponent object receives a certaininput and produces a certain output. The output may be a random

variable that obeysa certain distribution. Thereliabilityof thatobject under the given input can be defined as the proportion of acceptableoutput. The level of acceptance is pre-determined based onperformance criteria. ............................1016.2Components in series. The failure of any component leads to thefailureoftheentiresystem. ........................1036.3Components in parallel. Only the failure of all components leadstothe failureoftheentiresystem. .....................1046.4AUML representation of the final sensor assembly. Figure shows

the abstract 3-component biosensor being fully represented by concreteinstances for the different components. . . . . . . . . . . . . . . 110xvii


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6.5KB cells attached on cantilevers. Afew cantilevers are shown withcells attached to them. The cells are marked with white circles. . . . . 1156.6Reliability of the frequency drops. The figure shows the frequencydrops seen with KB cells superimposed on the relevant curves obtained

for the reliability of the cantilever. The X-axis denotes theprobability of exceeding the frequency drop seen. The points areclustered towards the low reliability region because the cells prefertostick closetothe fixedendofthe cantilever.1through4cellcurves are shown with progressively thicker lines. . . . . . . . . . . . 1176.7Cells on the rear side of the cantilever. Cells seem likely to attach tothe rear side of cantilever surfaces. Top two picture are of the samecantilever with two different focal depths showing the cells at twodifferent levels. ...............................118xviii


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LIST OFTABLES

TablePage

4.1

Specifications for cantilever structures. ................. 744.2Probability of detection for prior data. Reliability is given by subtractingthe Probability of Exceedence from 100. Stiffness normalizedfrequency changes greater than 0.0025 indicate 90% reliabilityof detection of at least one cell. A factor of 1.24 was included tocorrect for the continuous beam resonance model. . . . . . . . . . . . 826.1Cantilevers exposed to FR-aoverexpressed cells.. The tests weredesignatedTP -True PositiveandFN -FalseNegativepurely basedon the frequency reading. These designations are made at the system

level. At the transducer level, cantilever4 correctly showed theabsenceofcells,butthisis consideredasaFalseNegativeatthesystemlevel. Additionally, some cantilevers showedafrequencydrop,possibly due to cells attached on the rear side of the cantilever invisibleto the microscope. Ideally, all the cantilevers should havedetected the presence of the FR-overexpressed cells. . . . . . . . . . . 1136.2Cantilevers exposed to FR-anon-upregulated cells. The tests aredesignated FP -False Positive if they showed a frequency drop Thetests with frequency increases are phenomena that need further explanation.Ideally, no cantilever should have registered a frequencydrop. .....................................114

6.3Calculating the selectivity of the sensor. The test results are summarizedabove. TheTrue Positive (TP), False Negatives (FN) andFalse Positives(FP)areobtainedfromthe tests.True Negatives(TN)are indeterminable owing to the unexplained phenomenon of frequencyincreases...............................119xix


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CHAPTER1

INTRODUCTION

1.1 Micro Electro-Mechanical Systems (MEMS)The pursuit of deeper understanding of the world around is the prime motivation

behind science, while being ableto experimentally validatea hypothesisisits underlying philosophy.Arigorous scientificstudy demandsthe formulationofa hypothesis regarding a phenomenon and the ability of a scientist to be able tovalidate the hypothesis based on gathered data from well-designed experiments.The design of experiments for technological development is conducted from thepragmatic point-of-view of gaining optimal results at a minimal cost. It implicitlyassumes that suitable tools exist in order to conduct the experiment. However,most successful experimental demonstrations are a consequence of developing oradapting suitable tools. The progress of science, thus, depends upon the development

and effective application of new tools and techniques. This fact is obvious toeveryone contributing to science, including the segment of the industry that suppliestools for scientific analysis. The race to develop better technology islargelymotivatedbythe dependenceof scienceon suitable toolsandisin turnresponsiblefor the proper progress of science.

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Engineering developments that find a wide range of applications in the developmentof tools for validating existing hypotheses and enabling new ones arefrequently referred to as platform technologies. They are the foundations on whichsubsequent scientific investigation is built. An example of such a platform tech

nologyis microfabrication. Microfabrication is an engineering development thatallows the construction of structures with well-controlled micron-scaled features.Almost all modern day electronics has been made possible using microfabricationto create integrate circuits and other semiconductor devices commonly known aschips. Microfabrication utilizes processes such as photolithography,chemical andphysical etching reactions to develop features and metal deposition techniques tocreate superficial coatings. Microfabrication technology has been engineered formass production. It relies on materials such as silicon, silicon dioxide, silico

n nitride,gallium arsenide etc. Silicon is the most common material used in micro-fabrication and has been the material used for the cantilever structure usedinthisproject. Experts in the field of microfabrication have shown remarkable skill bycreating very complex structures as seen in Figure 1.1.

With the refinement of microfabrication processing and a great deal of creativity,this technology has grown to a point where it can be used to realize not onlysolid state semiconducting devices (as in transistors and integrated circuits) or

highly controlled immovable structures, but also micron-scale devices that can beused to generate mechanical motion, or alternatively harness information from mechanicalmotion. The inter-conversion between electrical energy and mechanicalenergy has allowed the development of a whole host of micro electro-mechanicalsystems (MEMS) based devices such as gyroscopes, accelerometers, optical switches

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Figure 1.1: The Nanoguitar. The above picture, taken with a scanning electronmicroscope, is a structure made out of crystalline silicon using microfabricationtechniques. The guitar is 10 m long, or about the size of a human red bloodcell. It has 6 strings, each the size of 50 nanometers, or 100 atoms wide. Thisstructure was madeby Cornell Universityasa demonstrationof theirproficiency

in creating micron-scaled devices with individual features in the nano-scale range.

Photo credits: D. Carr and H. Craighead, Cornell.

and even consumer electronics such as digital light processing (DLP) based pro-jectors[53].

One of the strategies to produce mechanical work out of electrical energy isby using pulsed electrostatic fields to produce periodic attractive forces. Figure

1.2 shows an example of such a scheme. In this method, an alternating currentis applied between the fixed plate A and the movable element B. This producesan electrostatic force of attraction between A and B as shown by the dotted arrow.The movable element B is attached to the structure by means of an elasticspring element C. This element provides the restoring force for B. When an alternatingpotential is applied through D, the movable element will oscillate leadingto mechanical motion. The micron-scale size of the element Bmake it feasible forelectrostatic forces to cause such motion.3


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BACDFigure 1.2: Mechanical motion due to electrostatic forces. Schematic shows howmechanical motion is derived from electrical energy by means of electrostaticforces. Plate A is fixed to the structure while element B is movable. An alternatingpotential applied by Dproduces a periodic attractive force between Aand

B, which is balanced by the spring C. This produces oscillations in Bwhich can beharnessed for mechanical motion.

One such actual device is shown in Figure 1.3 below. Silicon has been usedsuccessfully in solid state electronics which have no moving parts. However,whenusedasastructural materialformoving elements,itbringswith itselfawidearrayof mechanical reliability issues such as fatigue and fracture. This particular devicehas been used to test fatigue in MEMS materials under different conditions . [10,

64,80]

Asecond and perhaps morerelevant(regarding cantilever devices) scheme forgenerating mechanical motion is using piezoelectric devices. Piezoelectric devicesare crystals of materials such as lead-zirconiate-titaniate that expand or contractas a result of an applied electric potential. The application of periodic potentialseffectively causes periodic motion, which can be used as a motive force in MEMS

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Figure1.3: AMEMS micromotor.Amicroscopic photograph showsamotor basedon the electrostatic motion generation scheme described. The fixed elements areshown as flat blocks on the top and the right side, while the movable element isshaped like the sector of the circle. The comb like structure provides an interface

for electrostatic attraction. The restoring force is provided by the fixed beamshown enlarged. This device has been used to study fatigue in MEMS motors byobserving the surface evolution at the base of the notch in the support beam.

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devices. Piezoelectric devices vibrating in the range of audible frequencies areused in buzzers in small electronic devices such as watches. They are also used inthe atomic force microscope (AFM) to impart oscillatory motion to cantilever tips

as shown in Figure 1.4

AFMTipPiezoelectricStageFigure 1.4: Piezoelectric stage for the AFM tip. This schematic shows the methodologyused for actuating an AFM cantilever tip. The silicon AFM tip is mountedatop a piezoelectric stage that is actuated by means of an alternating current.Thestage contracts and expands due to the piezo effect and causes the cantilever tooscillate. When the frequency of the stage equals that of the natural frequency

ofthe cantilever (in the condition known as resonance) the efficiency of mechanicalmotion is the highest.

The MEMS technology is one example of an engineering technology that is

rapidly developing tools to push the limits of science everyday. One of the areas

where it is going to enable great strides is in the field of biology. MEMS technology

has potentially successful applications in biosensing as described in the following

section.

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1.2 MEMS Based BiosensorsThe quest for deeper understanding of the workings of biological systems motivatestheneedfor suitable toolsto interrogate biological machinery. Diseasestatesin living beings typically are the result of a malfunction in the bio-molecularmachinery

of living tissue. The tools needed to investigate bio-molecular systems andtheir abnormalities inside living tissue must therefore correspond to the size-scaleof the systems themselves. To that end, advances in microfabrication and MEMStechnology have opened up numerous opportunities for engineers to design andfabricate tools suitable for deployment in investigating live tissue. Several classesof tools that interface with living tissue at the cellular level have been developed,and have been variously called Micro Electro Mechanical Systems for BiologicalApplications, or BioMEMS for short. Several successful devices are already onthe

shelves, while several morepromising ones are on the horizon. These devicesincludesensors for physical and biochemical properties, actuators used in surgicalapplications or in drug delivery systems used as therapeutics[93].

The field of BioMEMS sensors has rapidly expanded in the last few years andpromises to maintain this growth for some time as the technology involved getsmore and more refined and as the understanding of biology creates the opportunityfor more versatile and efficient devices. Under the broad umbrella of the NationalNanotechnology Initiative[6] , the BioMEMS research is expected to growowing to aggressive support by United States government technology policy. Relev

antnational institutes such as the National Institutes of Health, the NationalScience Foundation, and the United States Department of Agriculture are a partof the National Nanotechnology Initiative and have announced initiatives in the

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areas of biological agent detection and diagnostic devices for the health care industry.Similar programs have been instituted by the European Union and otherparts of the world.

That MEMS technologies willrevolutionize several industries including healthcare

,is an optimistic forcastalso shared by industry experts. The investment bankUBSWarburgLLC estimatesa$28.8 billion market for BioMEMS based systemsfortheyear2005withan estimatedcompoundgrowthrateofabout17%.[3]Apartof this market is due to the applicability of BioMEMS based devices as sensors indiagnostic tools as well as feedback controls in drug delivery systems. Similarsystemscan be developed for monitoring agricultural and food pathogens. Anotherthrust area for BioMEMS sensors is their application in countering biological warfare.Since BioMEMS are compact and very sensitive sensors, they are an ideal

candidate for detection of biological warfare agents in a combat theater or evencivilian areas.

Coupledwithrecent developmentsin nanotechnologyand biotechnology(collectivelyreferred to as bionanotechnology), microfabrication and MEMS technologycan usher a large number of possibilities in biological sensing. Molecular andcellular biologyprovidesavast arrayofprefabricated nanoscale functional componentssuch as proteins, nucleic acids and other relevant smaller molecules. Micro-fabrication and materials technology provide the necessary tools to organize andintegrate these nanoscale components into useful microscale devices. The advanta

gesof such devices include high sensitivity to analytes, low production costs (albeithigh development costs) and high portability. Such technology is well-suitedfor application in disease detection.

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1.3 BioMEMS in the healthcare industryMedical practitioners appreciate the effect on patient anxiety and patient discomfortin disease diagnostics such as in clinical endoscopy [82] and personalblood sugar testing in diabetes. In general, medical procedures, especially those

that need to be carried out periodically should be designed to cause minimum discomfortfor the patient. BioMEMS devices, being miniature in size can potentiallybe implantedinthe patientto eliminatetherepetitive tasksof manual intervention.

The example of such a device is the conceptual implantable insulin deliverysystem, which monitors blood-sugar levels and computes the insulin bolus basedon a closed-loop feedback control[19]. The rationale for in-dwelling medical devicessuch as the conceptual insulin delivery system is that they improve the qualityof life of the patient by circumventing the painful task of testing for bloodsugar and the subsequent injection of insulin. These devices are not only lifest

yle-improving devices, but in some cases, life-saving applications. While such complete,multi-component, controlled drug delivery systems are not yet a clinicalreality, individual components such as blood-glucose monitors andimplantablepumps that can be controlled from outside via radio frequency telemetry have alreadybeendevelopedandarein variousstagesof clinical investigation.[17,21,78]

Even though the field of BioMEMS and allied fields such as bionanotechnologylook promising for a wide array of human problems, developing the technologyitself is an expensive undertaking. Much research is still being done in refining

manufacturing techniques and much more research yet needs to be done in interfacingthese devices with biological systems. Issues such as sensor biocompatibility,response time and accuracy are some of the key issues that still need to be

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resolved. The cost of development of a robust, accurate, versatile sensor is highfrom a technological development point of view as well as from the subsequentclinical testing. This seemingly prohibitive cost limits the areas of applicationsfor which BioMEMS-based devices may be initially developed. The first applicatio

nsfor such devices will be in the healthcare industry, especially in the areas inwhich effective and potentially life-saving diagnosis is still intractable usingconventionaldiagnostic techniques. Cancer management is one such area that couldespecially benefit from the application of BioMEMS sensor technology. The otherareas are management of cardiovascular disease and control of immune systemdiseases such as diabetes and AIDS.

One applicationthe BioMEMS sensor technologycanbe developedisaportable,low-cost Point-of-Care device enabling quick and early detection of cancer as adecision

tool in subsequent cancer therapy or to provide closed-loop monitoring controlto therapy delivering systems.

1.4 Point-of-Care devicesPoint-of-Care devices seemto have evolvedfromrobotized tissue sample analysisand are designed for outreach towards the intended beneficiaries of the devices,viz. the patients. These sensors would work primarily in the in vitro domain,i.e. analyzing tissue samples that have been removed from the body into acontainer.

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The volume of biochemical and pathological testing has gone up due to multipleimprovements in health care services. This factor compounded with the reductionin the number of skilled tissue analysts and pathologists, large-scale, automatedtesting has become an economic and practical solution. Further, advancesin information technologyhave enabledthecreationof centralrepositoriesfortest

results that can be easily accessed over the Internet. The miniaturization of suchrobotized analysis devices and their connectivity with information systems haveenabled the concept of a bedside or Point-of-Care clinic. Such devices are beingdesigned to be operated by local care-givers without much initial training. Theycan also be easily connected to the Internet so that this data may be accessiblefora central storage and analysis system.

The natural application of BioMEMS technology is in small, portable, low-costsensors that could be developed as screening tools for different diseases. BioME

MStechnology leverages existing micromachining technology that goes into the manufacturingofCoupled Metal Oxide Semiconductor (CMOS) based electronics. Thus,the advantages of capital infrastructure and large-scale industrialization of themanufacturing processes, the low production costs and the suitability for miniaturizationcould be utilized.

Such systems are usually designed to be disposable and self-contained to eliminatethe need for expensive pathology laboratory infrastructure and trained professio

nalsfor diagnosing disease. They can also be designed for screening populationsfor propensity towards certain diseases. Such systems will be extremelybeneficial in developing societies where the outreach and economic feasibility of

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Point-of-Care devices will favor their adoption as diagnostics and screening devices.Further, once the technology becomes less costly to access, it will find adaptabilityandapplicationinotherareasthatrequirebiosensing,e.g. plantand animalhealth sensing, environmental sensing, food quality monitoring and also in the

area of biological and chemical contaminant detection.

1.5 Materials issues and BioMEMS reliabilityWhile BioMEMS technology is appealing in the limitless possibilities it offers,it also burdens the end user with the task of making the right choice for the application.The quality of this decision, is only as good as the yardstick. The choice oftechnology influencesthe qualityofthe outcomeandrequires careful deliberation.

One of the hurdles common to all biomedical diagnostic products and proceduresis biological complexity. Disease states such as cancer cannot be completelyand effectively defined by single parameter biological states[68]. Diagnoses and

prognoses need to be made using multiple molecular parameters[2]. Diagnosticsystems must be capable of interrogating multiple parameters simultaneously andover time for a complete picture of the state of the living being. Consequently,the decision systems that govern therapeutic systems must be able to analyze suchmulti-parameter data sets in order to produce a therapeutic service.

Micro-and nano-scale devices enabled by micromachining and nanotechnologyindeed make possible a whole array of in-dwelling sensors for continuouslymonitoring and versatile in vivo assays. An obstacle in the development anddeployment

of such in-dwelling sensors is their unreliable performance due to bioincompatibility,bio-fouling and poorly understood failure mechanisms. These are

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significant materials issues that need to be solved with systems-level engineeringsolutions. This particular technical difficulty makes the development costs of thesesensors far exceed the marginal benefit derived from them. Until difficulties such

as sensor degradation are overcome, in vivo sensing in this fashion may be far toouneconomical from an engineering standpoint.

Nevertheless, these same sensor technologies can be very effectively used in exvivo sensing. The materials issues of bio-fouling and sensor fragility are stillmajorobstacles, but could perhaps be circumvented using allied technologies such as microfluidicseparation. Designing the sensors to be disposable sidesteps the issuesof mechanical reliability and durability under continuous operation conditions.However the materials and mechanical design should still reflect a cognizance of

manufacturing and nominal handling stresses.

The design of MEMS devices from the point of material reliability is an importanttopic and it has been reviewed in detail with respect to mechanical fatigue invarious test specimens.[10] This work demonstrates how empirical quantificationof MEMS material reliability can be achieved in the absence of poorly understoodfailuremechanisms.Thistypeofresearchrepresents investigationsintooneparticularfailure mechanism in the devices. Several such modes of failure have been investigatedbytheMEMScommunity. However,duetothe absenceof standardized

procedures for material and structural testing, the data coming from the differentcommunities is scattered over multiple size scales, from the mechanistic modelstothe system level models forreliability.Aphysically based statistical framework fororganizing electro-mechanical failure data into a homogenous representation hasbeen demonstrated.[83]

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However, in the case of BioMEMS, the reliability of the system must includematerialand electro-mechanicalreliabilityaswellasthereliabilityofthe operationof the biological components of the system. In fact, the accuracy and precisionofthe biological sensing is of paramount importance. A systems-based frameworkis necessary to represent the construction of BioMEMS devices so that it becomes

easy to construct the system, to analyze different components for their reliabilityand to eventually establish a methodology for optimizing their operation.

1.6 Asystems-based approachThe comparison between different BioMEMS sensorsrequires the developmentof performance metrics and evaluation procedures in order to facilitate comparisonbetween different devices. The systems-based approach involves converting thematerial, mechanical and biological dataintoacoherent information space suitable

for further analysis and decision-making.

The number of devices that have been deployed in the field are far fewer incomparison with the number of potential candidate technologies that are beingdeveloped for various applications. This implies that sooner or later, a mammotheffort must be undertaken to document the performance of such devices and makethis information available to potential end users. As several BioMEMS based devicesbecome available, the end user will require metrics for effective decision-making about the choice between available technologies, and their performanceunder various situations.

Diagnostics used in the health careindustry arebound to increase in sophistication,and somemaybe capableof measuring multiple parametersatthemolecular

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level. The information from parameters will have to be represented and interpretedin a holistic framework, making practitioners capable of basing their decisionson multiple inputs. Unless the bioinformatics-based framework is standardized,the opportunity for transition from conventional pathology to an integratedmolecular analysis-based diagnostic framework will be poor. This opportunity

cost can be mitigated to some degree if forward-looking standards and protocolsare established while the industry is still relatively young.

The systematic analysis of existing technologies, potential applications and deviceevaluation, and reliability characterization techniques could streamline thedesignprocessin this quickly maturing field. Knowledgerepresentation, informationintegration and analysis, decision support and system optimization are theaspects of a holistic systems-based approach to device design. The essential stepsin a such an approach are:

The adoption of a suitable tool to visualize and communicate the design ofthe device. Development of a library of abstract classes of device components and processes. Development of a library of existing components and processes as instancesof the abstract classes developed above. Development of a library of protocols and interfaces between the differentcomponents and protocols. Conducting research to determine the various failure modes of the components,processes and interaction protocols.15


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Evaluating the reliability of the individual components from a mechanisticpoint of view as well as the reliability of the whole system from a stochasticpoint of view. Ascribing performance ratings for the various components, processes andinteraction protocols and, Documentingandmaking accessibleallthis informationinawaythatiswell

suited for computer-aided development and for exchange over the Internet.This approach will help the efficient streamlining of collective knowledge in theMEMS world and will enable faster and more cost-effective development, whileat the same time provide documentation in a way that is easily available to theend user of the technology. The intention of the author has been to document thisresearch in the steps described above.

1.7 Objectives, significance and scopeThe main objective behind this research is to develop and demonstrate a unifiedsystems-basedapproachtosolving materials,designandreliability estimation

problems. Owing to the multidisciplinary nature of this research, integrating severaldisparate components intoa coherent system, each chapteris writtenasa separatelogical subunit with its own literature survey and significant contributions,both in theoretical development and laboratory experimentation.

The clinical motivation behind the development of a BioMEMS sensor for cancerdetectionhasbeen explainedinChapter2.As mentioned earlier,itiscrucialtochoose an application for a problem that is as yet intractable by other means, and

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for which nanotechnology and BioMEMS technology show great promise. Themotivation behind the sensor is the early detection of cancer. Specifically, todetectthe cells of those cancers which show an over-expression of the cell-surface proteinknown as folate receptor. Such cancers include almost 70% of ovarian cancers,

the nasopharyngeal carcinoma and a small percentage of brain tumors.

Subsequently, Chapter3 outlines the systems engineering approach taken tomanage this project, identifies development requirements, and builds a platformto characterize the biosensor. The concepts of a standardized documentation tooland its merits are also developed in the chapter. One of the outcomes is an illustrationof how this particular design can be modified to suit other applications,

i.e. applications in detection of diseases other than the type of cancer mentioned

above. One of the benefits of systems engineering is the ability to transform traditionalcomponent level data into the information space, where further analysiscan be performed using the tools of information technology. In the current absenceof sufficient systems-level information from various biosensor devices, it is alittleunrealistic to perform any decision support analysis. The scope of this approachhas been limited to demonstrating how material, mechanical and system reliabilitydata can be effectively captured into the information space using the UnifiedModeling Language (UML).Translating experimental data intoa coherent computer

database for component reliability, though crucial, is only the first step in aneffective systems analysis for optimization or decision support. Thus any systems-level optimization or decision support is outside the scope of this study.Chapter4details the materials and mechanics models fora cantilever structurewhich was used in this study. Itdemonstrates how the material and mechanical

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reliability of a sensor may be quantified from a mechanistic point of view. Further,it also shows how a mechanistic model for failure can be extended into thestochastic spaceto obtaina better understandingof the devicereliability. Atthispoint, the mechanics model is still devoid of the biochemistry of the cancer. i.e. the

mechanistic model does not take into account the difference between a cancerousand a non-cancerous cell.

Chapter5discusses the chemical modifications that are necessary to make thesensor specific for a particular type of cancer. This includes the details of the developmentof the folate surface chemistry that was developed for this sensor andthe subsequent tests that were carried out to ascertain its effectiveness.

Chapter6 deals with characterizing thereliabilityof the biosensorprototypeby combiningtheresultsof chapters4and5. The mathematicalandprobabilisticfoundations of reliability along with its treatment of multicomponent systems ar

erevisited. The development of stochastic models from mechanistic processes aregiven for the BioMEMS sensor of interest.

This represents one iteration of the design cycle in the development of a cantileverbiosensor. Finally Chapter7concludes witha discussionof future opportunitieswith respect to the refinement of the current sensor as well as parallelapplications in other areas of interest.

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CHAPTER2

MOTIVATION IN DISEASE DETECTION

Cancer, although a familiar disease of modern times, is by no means a recentdevelopment. Cancers of various forms have been described in the writings or

pictures of ancient civilizations such as those of Asia, South America and Egypt.Hippocrates(ca400BC) wasthe first oneto theorize cancerasa diseaseduetonaturalcauses. Some writings from the Middle Ages also suggested that cancer wasan inherited disease in their reference to cancer families or cancer houses.[31]

The first scientific enquiry into cancer dates from 1775 and is generally attributedto Sir Percival Pott, an English physician who observed that scrotal cancerwas caused in men in their twenties who were or had been chimney sweeps. Herecommended frequent washing and changing of clothes to reduce the exposureto the carcinogen. Thus he was the first to demonstrate not only a putative carcin

ogenfor scrotal cancer but also that cancer maybe caused many years aftertheexposure to the carcinogen. This corroboration was made without any knowledgeof tumor biology.[86]

Later,Virchows declaration, Omnis cellulae cellula (Every cell arises from anothercell)in1858then established cancerasacellular diseaseandlaidthe scientificfoundation for the study of cancer as a cellular disease.[25] The understandingof

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cancer has progressed considerably. From blaming the Gods of Ancient Egypt, toa disease caused due to the imbalance of bodily humor in the Middle Ages, cancertodayis understoodasa cellular disease causeddueto specific genetic conditions.As more was discovered about the genetic basis and evolution of cancer, it became

evident that the silver bullet to cure cancer is quite elusive and that cancer shouldbe looked at as a chronic disease that needs to be managed.[102]

2.1 Early detection and management of cancerTheincreased understandingofthegeneticbasisfor cancerhasledtoashiftinthe paradigm for cancer treatment. Without disregarding the possibility of a cureforthe disease,researchersare exploringthe possibilityof utilizingthe knowledgeof tumor biology in order to manage the disease, controlling its proliferation andmitigatingpainandsufferingduetoit.Theideaof cancer managementwasrecognized

by the American Association for Cancer Research (AACR) in 1998 and wassubsequently declared as the emergent direction. Since then several studiesrelatedto various forms of cancer have been carried out to establish a set of best practicesin the managementof cancerin both early and advanced stages.[15,16,20,47,48]The goal of management of cancer at an advanced stage is to alleviate pain andsuffering caused due to cancer as well as to slow down or stop its proliferation.Another aspect of advanced stage cancer management is the alleviation of sideeffects caused due to the treatment measures. Management of multiple facets ofthe diseaseisa multidisciplinary undertakingwhich involvesthestudyoftheprogression

of cancer, the effect of this progression on other systems in the body, and

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the palliative measures needed toreduce the suffering caused due to thediseaseand its subsequent treatment strategy.

Successful management of early cancer involves being able to pre-empt the diseasebyscreeningforpopulationswithapropensityforthe diseaseorby detecting

the disease as soon as possible. This is made possible by looking for the presenceor absence of certain biomarkers which are typically caused by known genetic disorders.[84, 102] The outcome of such largely affects the mode of treatment that isused. Typical intervention strategies include prophylactic surgery, chemopreventionor even lifestyle changes. Such strategies are effective in reducing the risk ofdeveloping the full blown disease because cancer is caused due to a series of geneticmutations and not by a single mutation alone. Pivotal to these procedures

however, is the effective and early detection techniques to determine the risk ofcancer for a given individual. The National Cancer Institute has recognized theimportanceofearlydetectionand considersit synonymouswithreductioninmortalityduetocancer[5].Itis importanttonote however,thatduetothe natureoftheproblemandthe ethics involvedin screening asymptomatic populations,noscientificallyvalidated numbers are available on the reduction in risk of cancer dueto early detection and early intervention. Alarge number of tests are underway,nevertheless, that evaluate the risk of cancer in populations with certain lifestyles.The large gap between epidemiological studies of cancer and the corresponding

etiological mechanisms has not been scientifically validated and rests largely onobservational evidence.

The detectionofsolid tumorsisavastlydifferentproblemthanthe detectionofsystemic cancers such as leukemia. Solid tumors go undetected much longer and

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thereforehaveahigher likelihoodofreachingan advancedstage withoutintervention.Thethree most fatal cancers as estimatedin the year 2000 -breast, colon andlung cancers-are all solid tumors [27]. Their onset and progression is not easilydetected.

Early detection of cancer is thought to reduce mortality. As a testament to thebenefits of early detection, the five-year survival rates in cervical cancer have goneup from 59% in 1950 to 73% in 1999 chiefly due to a readily accessible diagnosticprocedure -thePAP smear. The most common male cancer, prostate cancer,alsohasaremarkablehigh five-year survival rateof 98.4%owingtothedevelopmentofdiagnosticsfortheProstateSpecificAntigen(PSA)whichisabloodserumbiomarker related to the presence of the cancer.[37] The exceptionally high survivalrate is also greatly helped by the fact that prostate cancer is a slow-growingtumor and is only mildly invasive. Apart from such observational evidence, it is

noteasytopredictthereductioninriskduetoearly detection.Thereare however,some quasi-experimental mathematical models that predict survival as a functionof the time of detection. One such example, as seen in Figure 2.1, is the applicationof the inverse Gompertz model [72] to the percentage of surviving patientsfor breast cancer. It is not possible to ascertain the natural history of the onset oftumors when patients comein fora diagnosis. The Inverse Gompertz modelisdefinedastheprobabilityof survivalofa patient diagnosedwith cancer overtime.Mathematically, it is defined as:

%S

=100(1-acT)(2.1)

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where,%Sis the percentage of survival,ais the maximum reliability as T.

8i.e. when there is no cancer.cis the stage of the cancer diagnosedTis the time after diagnosis

The inverse Gompertz model, due to ethical considerations, cannot model situationssuch as survival under untreated conditions.

Figure 2.1: Breast cancer survival. Aconceptual graph showing the percentage ofbreast cancer survivorsasa functionofthe stagein whichtheyreceivedtreatment.The untreated survival rate fits an inverse Gompertz model. [72]

Significant prognostic information can also come from diagnostic devices forcancer, which can help in making treatment decisions. One of the characteristics

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of solid tumors after they have metastasized is that they secrete factors that preventthe growth of blood vessels, thereby controlling the growth of the metastatictumors[7,40,73]. Simultaneously,they continueto secrete factorssuchastheVascularEndothelial Growth Factor (VEGF) to promote the growth of blood vessels to

aid the main tumor[30, 95]. Subsequently, if this tumor is detected and surgicallyremoved, the restriction to growth on the metastatic sites (the mets)is removed,and these start proliferating[7, 18]. If a diagnostic is able to detect the presenceof such mets before the surgery, it may lead to another, more suitable course oftreatment.

Thusagood diagnosticdevicemusthavetheabilitytonotonlydetecttheonsetof disease as early as possible, but also to be able to provide information to m

akea prognosis and influence the treatment strategy to be adopted.

Even though the etiology of cancer can be mostly defined in the manifestationof genetic disorders, and perhaps the most convincing diagnosis of cancer can bemade through the observation of systematic genetic mutations, it is not entirelypractical to detect the onset of the disease at the genetic level. The genetic disordersare carried through and amplified as variations in the transcriptome and theproteome. It is in these translations of the genetic disorders that cancer can be effectively

diagnosed[102]. The relationship between genetic disorders and canceras an uncontrolled growth of cells is explored in the next section.

2.2 Cancer biology in a nutshellCancer is an uncontrolled proliferation of cells caused by malfunctions in certaincellular subsystems. The most important advances in our understanding of

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the biology of cancer come from the field of molecular genetics. The genetic basisof cancer was collectively inferred from epidemiological studies which pointed outthe proclivity of cancers in certain families or in certain demographic communities

with presumably similar genes. Studies of families that have a high incidence ofacertain kind of cancer have led to information about the genetic defects that maybe causing the disease. Advances in techniques of molecular cloning and characterizationhave led to the identification of genetic defects, e.g. in the Rb gene thatcause diseaseslike Retinoblastomaor Li-Fraumenisyndrome causedduetoadefectivep53 gene. Genes such as the Rb and the p53 are important in the regulationof the cell cycle and form the genetic basis of cancer as a cellular disease.

2.2.1 The cell cycle

Under normal conditions, cells divide at fixed rates maintaining a delicate balancebetween the process of cell reproduction and programmed cell death (apoptosis).Inanadultorganism,therateofcellreproductionis almostnearlyequaltothat of apoptosis, thereby maintaining an equilibrium in the cellularmass. Cellularproliferation occurswhen eithertherateofreproduction outpaces apoptosisortheprocessof apoptosisis stalled. Both theseprocessesofreproduction andapoptosisarecontrolledbyindividual cellular subsystems that arevery tightly integrated. Inadditiontothesetwoprocesses,acellalsohas pathwaysforhaltingandrestartingthe cell cycles and detecting and repairing errors in the DNA replication. Figure

2.2 shows the different stages in a cell cycle.25


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The CellCycleSTOPSTOPSTOPMMitosisG1Gap 1G2Gap 2SSynthesisCells thatstop dividingG0Figure 2.2: Phases of the cell cycle. Immediately after the Mor Mitosis phase, thecell enters the G1(Gap 1) phase in which it produces the proteins necessary for

proceeding into the Sor Synthesis phase. Following the Sphase, the cell growssome more in the G2orGap2phase beforeitprogresses into mitotic division. Thecell cycle is controlled by numerous proteins responsible for the progression aswell as quality control of the reproductive process.

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After a cell is newly created by mitotic division, it goes through a phase ofgrowth. This phase is known as the G1phase or the Gap 1 phase. The cell producesthe proteins required for the next phase, the Sphase. Alternatively if itintends to differentiate into a terminal configuration (terminal differentiation

, i.e.it will not divide again, e.g. brain cells) or if it becomes quiescent for sometime

(e.g. liver cells) the cell is said to enter the G0phase. The Sphase is also knownas the Synthesis phase. Here the DNA of the cell is unzipped and reproduced toform two sets of DNA. Subsequently in the G2phase, the Gap 2 phase, the cellgoes through another period of growth to produce proteins enough for two cells.In the last phase, the M

or Mitosis phase, the cell divides into two by separatingthe two copies of the DNA to two ends of the cell and constricting the cell so thattwo identical copies of the cell are produced.The progression of the cell through the cell cycle is controlled by cellular subsystemsinvolving various proteins as their components. The main proteins responsiblefor the transition of the cell from one phase to another are the G1,SandMphase cyclins. Their levels rise and fall in sync with the cell cycle. These cyclinsactivate the cyclin-dependent kinases (CDKs) by binding to them. The concentrati

onof the CDKs remains more or less constant, but because they get activated bythe cyclins, their activity mirrors the period of the cyclins.

There are multiple check points in the cell cycle which ensure the timing andquality of cell reproduction. A few critical checkpoints between the cell cyclephases have been shown as the STOP signs in Figure 2.2. Between G1and Sand between Sand G2there exist proteins that check for damaged DNA. In caseof reparable damage, certain other DNA repair mechanisms are activated. If the

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DNAdamageisbeyondrepair,thecell cyclingis stoppedandtheprocessofapoptosis(programmed cell death) is triggered. Without the presence of tight controlon the cell cycle, cell division can continue indefinitely leading to undesirable proliferation.The loss of or defects in the cell cycle checkpoints are associated withdifferent cancers.

2.2.2 ApoptosisOne of the moreessential mechanisms in place to ensurethe proper progressionof life is, ironically,the process of programmed or controlled cell death also knownas apoptosis. Apoptosis differs from other cell death processes like necrosis, suchas seen whena cellis injured. Apoptosisisa painlessprocess whichis completelytransparent to the larger organism in that it is neither pro-inflammatory nor isitpro-immune. Inflammatoryresponsesareof course accompaniedbyan awarenesson the part of the larger organism.

One of the better studied apoptotic pathways involves the caspase cascade.Whether the cell lives or dies is determined by the balance between two proteinsthe bcl2 and the Bax. If bcl2 is in higher concentration in the cell, the cell lives. Ifthe concentration of Bax goes up, it leads to the perforation of the mitrochondria theorganelles that generate energy for the cellular processes. This in turn triggersthe caspase cascade which leads to chromosomal fragmentation and eventually theself-destruction of the cells. This method can be triggered by several mechanisms.

Some of these include[1]:

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1. Cell deathdueto factors secretedbycytotoxicTcellsinan immuneresponse.These factors are signaled through the cell wall through the various deathreceptors.2. Cell death due to detachment from its position. This prevents the cells fromgrowing in places different from wherethey aresupposed to grow. In metastaticcancer, this feature gets disabled, allowing cancer cells to spread to other

parts of the body and grow there.3. Cell death due to irreparable DNA damage.This process is an importantcheckpointinthecellcyclewhichpreventsDNAdamagefrom accumulating.The molecule p53 has the capability of triggering apoptosis in the presence ofirreparable DNA damage as shown in Figure 2.3.

2.2.3 TumorigenesisTight regulation requires a certain level of complexity. As seen above, the cellcycleandcelldeatharebothtightlyregulatedprocesses.Themultiple checkpointsin the complex cell cycle provide an opportunity to control the cell cycle to a

veryhighdegree.The mechanismsaresetupinsuchawaysoasto minimizethe chanceofacellprocessgoingawry. However,cellprocessesdogoawryandleadtomanydifferent diseases. Tumorigenesis -or the development of tumors is primarily relatedto the accumulation and manifestation of genetic disorders.

The two types of controls in the cells can be broadly thought of as those thatstimulategrowthby forcing theprogressionof the cell cycle, and those that checkgrowth through their ability to curb the cycle or induce apoptosis (programmed

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DNA damagep53BaxUpregulatesproductionof BaxMitochondriaCytochromep450APAF1ActivationCaspase -9FurthercaspasecascadeApoptosisChromatin fragmentationand cell blebbing

Figure 2.3: Apoptosis through the caspase cascade. When the protein complexp53 detects an irreparable DNA damage, it upregulates Bax which perforates themitochondria. This releases cytochrome p450 that activated the apoptosis proteaseactivation factor APAF1. This triggers the caspase cascade which leads to chromatinfragmentation. Subsequently, the cell sheds its matter in the form of smallmembrane-bound vesicles called blebs.

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celldeath).Thegrowthpromoting controlsactthrougha sequenceofgeneswhichare typically called oncogenes. The National Cancer Institute defines oncogenesas:Genes which can potentially induce neoplastic transformation. (Fromwww.cancer.gov)

These genes can be endogenous to humans or they could be virally acquired. Suchgenes also include growth factors and growth factor receptors, kinases and transcriptionfactors.

The ras gene is an example of an oncogene in the epidermal growth factor(EGF) pathway. The ras gene is found responsible in cancers of the breast, lungand colon.[81, 97]. It is present endogenously and can be mutated by free radicals,radiation or carcinogens. It is also possible that mutated copies of the gene may beacquired through viral infections.

The gene is a mediator for the GTPase molecule, i.e. it is responsible for theinactivation of the guanosine tri-phosphate (GTP) with GTPase. A mutated rasdoes not provide a suitable interface for GTPase, thus notpermitting it to performits enzymatic activity. An accumulation of uncleaved ras bound GTP providesa sustained growth signal to the downstream MAP cascade, which is ultimatelyresponsible for nuclear division. Thusa mutated ras isa positivepressure towardscell division without the proper checks and balances and increases the likelihoodof developing cancer. [29,38]Aschematic of the ras pathway is shown in Figure

2.4.The genes responsible for negative control on the cell cycle are called tumorsuppressor genes. The National Cancer Institute thesaurus defines tumor suppressorgenes as:

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Cell WallEGFEGFRGEFrasGDPNucleusPPrasGTPPPPMAP cascadeTriggers nuclear divisionGTPPPPGTPaseras substrateMutated rascannot be cleavedFigure 2.4: The raspathway. The epidermal growth factor (EGF) attached to itsreceptor on a cell wall (EFR) triggering the Guanine Exchange Factor (GEF) tophosphorylate the ras-bound Guanosine di-phosphate(rasGDP) and converting

it to ras-bound Guanosine tri-phosphate(rasGTP). This then triggers the MitogenActivating Protein (MAP) cascade of nuclear division. The ras isa substrate fortheinactivating enzyme GTPase which converts rasGTP back to rasGDP.A mutatedras gene does not provide an able substrate and produces a sustained MAP signalleading torepeated nuclear division.

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Genes whose loss or deactivation leads to neoplastic transformation. (Fromwww.cancer.gov)

The definitionof tumor suppressor genes could include genes thatareresponsiblefor DNA damage repair and genes that promote apoptosis.

The protein complex p53 is an example of a tumor suppressor gene that canhalt the cell cycle in presence of DNA damage and trigger apoptosis if required.Many cancers with severe prognoses have no functional p53 molecules or have amutated p53 gene. The loss of the p53 gene leads to an accumulation of geneticdefects which pass through thereduplicationprocess unchecked.

In some rare cases, the p53 gene is missing from a child at birth, leaving thechild vulnerable to unchecked genetic mutations. Such children are said to beafflicted with the Li Fraumeni syndrome, wherethey develop multiple cancers earlyin life. Genes such as p53 are known as tumor suppressor genes.

Mutations in the DNA occur due to radiation, free radicals from oxidationproductsand carcinogens. These occurrencesareregularin nature. The functionofthe cell cycle checkpoints is to ensure that these mutations are not carried over inthe reproductive process. In case of mutated cyclins that fail to respond to thesignalstohaltthecycle,thecellgetsforcedintothenextphase, withoutappropriatelyresponding to the halt signal. The integrity of the cell DNA is lost in the processand the subsequent cell is defective in some way. If allowed to progress, such alesion may evolve into cancer. Genes that promote uncontrolled cell division are

known as oncogenes.

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In order for cancer to evolve out of DNA lesions or mutations, two conditionsneed to be satisfied. First of all, relevant tumor suppressor genes and gene repairmechanisms such as p53 and Rb need to be disabled. Next an oncogene mustbe produced, either by a carcinogen, viral DNA or due to radiation, by inducingmutation in a gene. This insight was brought about by the so called two-hit hypo

thesis[52] which states that a minimum of two mutations, one on each allele ofthe Rb tumor suppressor gene must be present in order to develop Retinoblastoma.While thereareseveral exceptions to the two-hit hypothesis[66], it has neverthelessprovidedagreat dealof insightin the eventual evolutionof cancer.

The genetic mechanisms behind cellular proliferation have been illustrated herewith a view to build an appreciation for the complexity in the evolution of canceras well as to demonstrate the various stages of the disease where diagnosis, pro

gnosisand intervention may be possible. The study of various pathways in differentcancers is an ongoing effort around the world leading to new insights every daytowards developing the elusive cure for cancer.

While it may appear that the detection of the presence or absence, or even abnormalbehavior of certain genes may be the key to detecting cancer, the technologiesavailable today to carry out such a diagnosis are not entirely practical.Technologies such as fluorescence in-situ hybridization (FISH), spectral karyotyping(SKY) and comparative genomic hybridization (CGH) are the current tools ofchoice to detect genetic abnormalities for the purpose of screening populations

for their proclivity towards different cancers. All the aforementioned tools relyon genetic hybridization with molecular probes that fluoresce in certain ways to

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determine genetic abnormalities. As such, their resolution depends of the accuracyof the fluorescence detector, and it is seen that seldom do such technologiesgive better resolution than detecting the mismatch of a few thousand base pairs.This is not sufficient to detect point mutations and other small mutations. DNA

amplification using techniques such as polymerase chain reaction (PCR) may helpcircumvent the problem to some degree, but the diagnostic becomes expensive andmuch more technically demanding to be viable as a rapid screening tool.

Since genes must express as proteins in order to carry out their function, as anindirect method of detecting genetic defects, one can detect the presence of defectiveproteins. Proteins are easier to detect and there exist suitable laboratorytechniques such as Western blots and the Enzyme Ligated Immunosorbent Assay(ELISA). The ELISA technique especially is easy to execute and deliver resultsquickly and inexpensively. A MEMS based sensor that can provide the simplicity

of an ELISA test and the portability of the MEMS technology is an effectiveformula in developing a vast array of biosensor devices.

Asimilar strategy has been used in the development of a biosensor for cancer.In rapidly reproducing cells, the demand for folic acid goes up significantly intheprocess described below. This fact can be exploited to detect cancer in an earlystage.

2.3 The folate receptor molecule and cancerFolic acid (also known as folate or pteroylglutamic acid) is a water soluble vitamin

of the B-complex group. The structure of folic acid (C19H19N7O6)is shownin Figure 2.5.

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HNHHCNCNCNCCNCOHNCCHCCCCCCONHCCOOHCCCOHHHOHHHHHHHHHPortion recognized by antibody aswell as the folate receptorIdeal carbonfor attachmentAttachment to thiscarbon rendersfolic acid inactive

!"PterinGlutamineFigure 2.5: The structure of folic acid. The folic acid molecule comprises of 3distinct moieties, the 6-methylpterin and L-glutamic acid, joined together by apaminobenzoicacid linkage. The pterin head is the biologically active component offolic acid and is recognized by the folate antibodies. The acarbon in the glutamicacid end is ideal for chemical attachment of folic acid to other molecules.

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Mammals, being incapable of synthesizing folic acid, must obtain it from theirdietary intake. The biologically active form of folic acid is called 5,6,7,8-tetrahydrofolate(THF). Reduced folates are co-enzymes in a number of biochemical pathways involvingthe transportof1carbon units like methyl(-CH3), formyl(-CH2-)and

formimino(-CH=NH). As such, they are utilized in the synthesis of the DNAbases thymine and the purines[92]. This makes folate especially important to theSphase of the cell cycle, when the DNA is being synthesized. In fact, chemotherapeuticdrugs such as methotrexate used in the treatment of cancer are analogs tofolic acid and are effective due to the displacement of folic acid from the cellularpathway, thus disabling the reproduction of the DNA.

In cancer, when the cells are going through rapid Sphases, the demand onfolic acid goes up significantly. The cell is triggered to replicate its DNA beforeit has a chance to mature sufficiently. The cell absorbs folic acid from blood bymeans of specialized molecules on the cell surface called the folate receptors.As thename suggests, these molecules are responsible for the uptake of folic acid fromthe blood into the inside of the cell where it becomes available for the Sphase.

Itmaybepossiblethatthe observationthatmethotrexateisafolateanalog,coupledwith the selectively increased uptake of folate by malignant cells led to theidea that folate could be used as a targeting moiety for various anti-cancer drugs.In the last few years, folic acid has become a popular and promising strategy fordelivering cytotoxic drugs to malignant tissues. The folic acid molecule has beentagged to imaging agents[94], radionucleides[67], chemotherapeutic agents[49],gene therapy vectors[24, 41, 61, 71] and other devices such as antibodies[54].

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There are four types of folate receptors, labeled, FR-, FR-


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, FR-.andFR-.

. The first two(-aand -


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)are present on the cell surface, anchored bya glycosyl-phospatidylinositol anchor[99]. Theremaining two types(-.and -0)are secreted due to the absence of an anchor structure. The folate receptor-ahasbeen seen present normally in the largest amount in the choroid plexus, lungs,kidneysandthethyroid.Ithasbeen seenin4outof6metastaticbrain tumors[96].

It is not seen in the liver, muscles, cerebrum, cerebellum and the spinal cord underimmunoassys. It is seen in4 out of6metastatic brain tumors,[96] malignantand benign lesions in the human female genital tract[43] and nasopharyngeal carcinoma.[46,75]Itcanalsobe secretedfromreceptor-richcellsandhasbeen consideredan important serological marker for ovarian cancer[60]. In general, FR-aisoften over-expressed in malignancies of epithelial origin and may be present asacell surface receptor or a soluble entity[36].

The transport of folic acid across the cell wall is mediated by the low-affinity,high capacity transporter protein called the reduced folate carrier (RFC). Thisisa 46 kDa membrane protein. However, this molecule has a low affinity towardsfolic acid. The dissociation constant(Kd)is approximately50-200M. The folatereceptor itself does not contribute to folate transport, but owing to its high affinitytowards folic acid[Kd0.1

-1nM], aids the RFC in internalizing folic acidacross the cell wall. While the exact mechanism of folate transport is yet to beelucidated,itis seenthatrelativelylarge moleculessuchas ferritin(443kDa)hasbeeninternalized by this mechanism[36].

The knowledge of folate-mediated endocytosis is not essential to the developmentof a folate-receptor sensor, except to ensure that a small molecule such as

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folic acid is indeed visible to cell surface receptors and is sufficient to immobilizethe cell on a folate-coated surface.

2.4 Asensor to detect the over-expression of the folate receptorHuman nasopharyngeal carcinoma (called KB cells) is the preferred model system

that has been most extensively studied with regard to the overexpression ofthe folatereceptor. Early experiments to characterize this phenomenon usedimmunostainingtechniques using the MOv18 and MOv19 antibodies to determinethe distributionofthe folatereceptorindifferent malignant tissues[60].Ithasbeenobserved that the amount of folate receptor on the cell surface goes up as the malignancyadvances[43, 96]. Further, it was also shown that the affinity of the folatereceptor is reduced in folate deprived conditions, even when the abundance ofthe receptor increases, suggesting possibly a different isomer expressed in folatedeprived malignant cells.[33]. With advances in the detection of gene transcript

s,it was shown that the expression of the folate receptor gene is downregulated asthe malignancy advances[99]. These seemingly contradictory evidences could bereconciled by the observation that the half-life of the mRNA transcript is reducedin folate-replete conditions[75,103]. Possible developmentof folatereceptorisoformslacking the cell-membrane-binding domains can lead to the secretion of thefolate receptor into the blood stream similar to the folate binding cleavage proteinfound in human milk[99]. It is possible that such secreted folate receptor may be

an important blood-serum biomarker for ovarian cancer[96].

It is also possible, that in the earliest stages of cancer, when the immune systemis able to destroy cells producing chimeric proteins, apoptotic fragments of cells

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bearing large numbers of folate receptors may also be found in the blood stream.Ifasensor wereableto detect suchreceptor-overexpressed cell fragments,it wouldbe an extremely early signal for an evolving tumor. Nevertheless, even with thecurrent knowledge, it is clear that the folate receptor is an important prognostic

marker and possibly also a reporter on the efficacy of the chosen treatment.

There exist several ways in which the folate receptor can be detected: differentgel systems can be used to detect the quantity of protein or mRNA in a tissue, antibodiescan be directed to the folate receptor, and different imaging agents can beconjugatedto folic acid, etc.[36,45,60]. Thisresearchpresentsyet another possibilityofdetecting cells with overexpressed cell-surface folatereceptors. Thedesignrational of the sensor, its construction and evaluation is discussed in subsequent

chapters.

2.5 Integrating biological information for disease detectionIn cancer as in any other patho-physiological condition, biosensors and sensingmechanisms have been the cornerstone of gathering information for disease diagnosisand prognosis. Mammograms, body scans, pap smears, various biopsiesand stainingproceduresanda multitudeof blood testshave becomeprogressivelyeffectiveinprovidingthe necessary informationtomake decisionsregardingtreatmentmodalities in cancers.

As technology allowsacloser look into the molecular mechanisms that underlydisease, it becomes increasingly clear that most diseases such as cancer are the

resultof a series of molecular malfunctions[52]. Even though there exists the (theoretical)capability of detecting single molecule events in the progression of disease,

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the relevance of the detected molecule to the systemic disease is not always clear.The connection between the different aspects of disease and their molecular underpinningsis possible by casting the known information in a Systems Biologyframework. Understanding the disease from the perspective of molecules to genes

to pathways and how it affects the disease prognosis is the next avenue in pathologyand in biology at large[26, 51].

This holistic understanding of disease from the molecular to the eventual andconsequential demographic characteristicshelpsthe medical communityindevelopingbetter strategies in disease prevention, detection and, when required, intervention.In an appreciation for systems biology, future diagnostic and prognosticdevices must necessarily incorporate the implications of systems biology in theirdecision-making schemes. The conventional method for making a diagnosis or

prognosisis that certain testsare performed suchas symptomatic behavior,pathophysiologicalexamination of biopsies, visual evidence of tumors etc, which thepathologist integrates, and based on his/her experience confersa diagnosis anda prognosis upon the results.

The sheer volume of molecular and pathway information being created by thescientific community can quickly overwhelm any pathologist in its specificity fordisease as well as its potential for complex interactions leading to undocumentedeffects.Itisdifficultto understandhowa physicianmaybeabletokeepabreastofall new disease information as well as the various treatment modalities availabl

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