tissue banking, bioinformatics, and electronic medical ... banking... · ment [1]. if a poor...

Hindawi Publishing CorporationJournal of OncologyVolume 2013 Article ID 368751 12 pageshttpdxdoiorg1011552013368751

Review ArticleTissue Banking Bioinformatics and Electronic Medical RecordsThe Front-End Requirements for Personalized Medicine

K Stephen Suh1 Sreeja Sarojini1 Maher Youssif1 Kip Nalley2 Natasha Milinovikj1

Fathi Elloumi2 Steven Russell3 Andrew Pecora1 Elyssa Schecter4 and Andre Goy1

1 The Genomics and Biomarkers Program The JohnTheurer Cancer Center at Hackensack University Medical CenterD Jurist Research Building 40 Prospect Avenue Hackensack NJ 07601 USA

2 Sophic Systems Alliance Inc 20271 Goldenrod Lane Germantown MD 20876 USA3 Siemens Corporate Research IT Platforms Princeton NJ 08540 USA4Research for the Cure Foundation Hillsdale NJ 07642 USA

Correspondence should be addressed to K Stephen Suh ksuhhackensackumcorg

Received 7 February 2013 Revised 3 May 2013 Accepted 7 May 2013

Academic Editor Thomas E Adrian

Copyright copy 2013 K Stephen Suh et alThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs byfocusing on genetics and ldquo-omicsrdquo data obtained frompatient biospecimens and records to guide therapy choices that generate goodclinical outcomes The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations oftissue banking bioinformatics and electronic medical records (EMRs)The analytical power of bioinformatic platforms combinedwith patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to developexperimental strategies using selected patient biospecimens stored in tissue banks For cancer high-quality biospecimens collectedat diagnosis first relapse and various treatment stages provide crucial resources for study designs To enlarge biospecimencollections patient education regarding the value of specimen donation is vital One approach for increasing consent is to offerpublically available illustrations and game-like engagements demonstrating how wider sample availability facilitates developmentof novel therapiesThe critical value of tissue bank samples bioinformatics and EMR in the early stages of the biomarker discoveryprocess for personalized medicine is often overlookedThe data obtained also require cross-disciplinary collaborations to translateexperimental results into clinical practice and diagnostic and prognostic use in personalized medicine

1 Introduction

Research in personalized medicine seeks to achieve optimalclinical outcomes through the use of innovative biomarkerdiscoveries to develop drugs that best suit a specific groupof patients To derive best-fit treatment options for a specificpatient group various signaling pathways are thoroughlyanalyzed to identify altered molecular circuitry that initiatesand maintains the clinical phenotype of the disease Forcancer this altered signaling promotes a cascade ofmolecularevents that is cell- or tissue type-dependent and thisrelationship gives rise to a specific biomarker set that hasa direct association with the cancer phenotype The uniquegenetic profile of an individual patientrsquos cancer will generate

specific gene expression signatures and modifications ofgenesmiRNA proteins and metabolites

Current and future technologies will produce a floodof data not only from the laboratory bench but also fromclinical sources and the association of these data with aspecific cancer phenotype is expected to be more sensitiveand to have a higher specificity that will allow increasinglyaccurate clinical decisionmakingMutations are often associ-ated with specific cancer malignancies and the combinationof well-documented mutations with better-fit drugs has thepotential to provide a good clinical outcome with fewerside effects for patients For example Cyp2D6 genotypingat the time of breast cancer diagnosis provides prognostic

2 Journal of Oncology

information regarding the effectiveness of tamoxifen treat-ment [1] If a poor clinical outcome is predicted thenadditional data and evidence-driven clinical decisions mayallow better alternative therapy options for those patientsWith recent advances the ER PR and Her2 status of breastcancer patients can be used to make therapeutic choicesthat include a customized tamoxifen regimen to preventdisease recurrence [2]Thenext generation of sequencing andldquo-omicsrdquo technologies will continue to improve our ability torecognize cancers improve treatments and track the healthof survivors [3] Scientific data from ldquo-omicsrdquo now representmany pathways and molecular signatures that are directlyinvolved in triggering cancers and these research data can beapplied to diagnosis prognosis and treatment decisions [4]

As the field of personalized medicine evolves scientificand clinical data are expected to converge in a commoncentral database which will facilitate the exchange of datathat can be transformed into valuable information that willaid clinical decisions enable customized treatments and gen-erate new advances for cancer medicineThese developmentswould be cost effective for both patients and health carepractitioners because a proper course of action could beidentified using the stored data which will help avoid theuse of unnecessary tests and ineffective therapies With theimplementation of the Affordable Care Act ldquoObamacarerdquo in2014 economical assays that provide accurate results will beneeded to determine themost effective treatments and ensurethe best outcomes In evaluating the cost of screening assaycosts and the cost effectiveness of drugs must be consideredand should correlate with the cost of biomarker detection inpatient samples [5] Screening assays will provide tools formaking the most accurate clinical decisions such that thecustomized treatment represents a best fit if not a match andtargets molecular changes that occur in the patientrsquos tumorCompanion assays for each targeted drug will maximize thetreatment benefit options for a specific cancer Minimallyinvasive procedures for obtaining small biospecimens frompatients will also help drive down medical costs to satisfythe new regulations The combined scientific and clinicalinformation from each cancer patient can be further analyzedand compared precisely with traditional treatments and anynew treatments with companion diagnostics can be testedin clinical trials Thus elucidating the molecular profile ofeach patient involves testing for robust biomarkers with highsensitivity and specificity for particular cancer phenotypesand requires high-quality biospecimens and well-organizedtissue banking Scientific information must be integratedwith clinical information derived from well-documentedelectronic medical records (EMRs) using informatics toolsalthough to date the importance of this integration hasbeen largely neglected by the research and clinical com-munity In combination tissue banking bioinformatics andEMRs are front-end requirements for enhancing personal-ized medicine and they represent key resources that willdetermine the path of progress in translational research tosupport clinical applications

Bioinformatics encompasses a combination of statisticsmolecular biology and computer science to store and analyzebiological data while tissue banking involves procurement of

tissue or tumor samples during medical procedures and theircollection and storage in a tissue repository By integratingpatient information and experimental results novel biomark-ers can be discovered that may have a major effect on the waypatients receive care and could also greatly influence drug anddiagnostic customization [6] Biomarkers can be proteinsgenes metabolites or evenmethylation patterns that are usedto detect genetic tendencies for specific types of cancers andother diseases (Table 1) [7] Depending on the cancer certaindiagnostic tests are performed and if a given biomarker isfound in a patient sample it will guide the choice of treat-ment In the case ofmelanoma for example a BRAFmutationtest is used to determine if a BRAF V600E mutation exists inthe patient sample and if present that patient will receive acustomized treatment with the drug Zelboraf which is effec-tive only for BRAFV600E-positivemelanomas Nonsmall celllung cancer (NSCLC) patients carrying an ALK mutationare treated with the drug Xalkori which is specific for thistype of mutation whereas NSCLC patients having an EGFRmutation would receive alternative customized treatments

These well-studied biomarkers enhance the ability ofclinicians to determine a course of treatment with minimaltoxicity However there remains a need for technologies toassist with the discovery and transformation of biomarkersto diagnostic uses [7] One approach is the use of aptamerssmall DNARNA oligonucleotides having high selectivity fortheir target which can help avoid the limitations imposed byantibodies in diagnostic applications [8] To initially identifypotential cancer-specific biomarkers biomarker discoveryapplications require bioinformatics data information fromwhich can then be used for analysis of samples stored in tissuebanks Sample quality and the associated clinical informationare also important factors in biomarker discovery becausedata from all components are required to complete thisprocess [9 10] Table 1 includes a list of currently availabledrugs in cancer therapy developed after identifying relevantbiomarkers and companion diagnostics [11ndash41]

Given the variety of data and samples being collected andadvances in personalizedmedicine the importance of collab-orations between scientists and clinicians as well as industryand academia becomes evident Targeted therapies thera-peutic resistance challenges of ldquo-omicsrdquo technologies andeven issues with biomarker-related trials can be approachedonly through collaboration [42] There are scientific uncer-tainties present in all areas under study which medicalresearch alone cannot address However through a transdis-ciplinary scientific methodology these disparate areas canbe combined to offer innovative and unique diagnostic andtreatment plans [6]

2 Importance of Tissue Banking

In the past two decades efforts to create and maintain tissuebanks have provided a foundation for future research towardpersonalized medicine in cancer After potential biomarkershave been identified through the use of bioinformatics andan experimental design has been put into place tissue bankscome into play If for example an institution wants to

Journal of Oncology 3

Table 1 List of biomarkers and personalized medicines with companion diagnostics

Biomarker Cancer type (subtype) Companion diagnostics(company) Drug therapy (company) Reference

HER2 (geneamplification) Breast cancer (HER 2 positive)

lowastlowastSPoT-Light HER2 CISHlowastlowastHercep test (Life TechnologiesNY)

lowastlowastHerceptin trastuzumab(Hoffman La Roche Inc) [13 14]

ALK (chromosomerearrangement)

Nonsmall cell lung cancer(anaplastic lymphoma kinase(ALK) positive advancednonsmall cell lung cancer)

lowastlowastVysis ALK FISH test (AbbottLaboratories Abbott IL)

lowastlowastXalkori crizotinib (Pfizer) [13 15]

EGFR KRAS(mutation)

Colorectal Cancer (expressingmetastatic colorectal carcinomaEGFR)

lowastlowastTherascreen KRAS Test(Qiagen CorporateHeadquarters Nederlandrsquos)

lowastlowastErbitux cetuximab (ImCloneImClone Systems NJ)lowastlowastVectibix panitumumab(Amgen Amgen Inc CA)

[13 16 17]

BRAF V600E(mutation)

Melanoma (metastatic melanomawith BRAFV600E mutation)

lowastlowastCobas 4800 BRAF V600Mutation Test (PanageneCorporate Headquarters Korea)

lowastlowastZelboraf vemurafenib(GenentechRoche) [13 18]

BRCA12 (genetranslocation)

Breast cancer (mediantriple-negative HER2+ andER+HER2minus)

NAlowastVeliparib ABT-888 (Abbott)lowastOlaparib AZD2281 (Abbott) [13 19 20]

PML-RAR (genetranslocation) Acute Promyelocytic Leukemia NA

lowastlowastTrisenox arsenic trioxide(Teva Israel) [13 23]

BCR-ABL (genetranslocation) Chronic myelogenous leukemia NA

lowastlowastGleevec imatinib (Novartis)lowastlowastSprycel dasatinib (BristolMyers Squibb)lowastlowastTasigna nilotinib (Novartis)

[13 24 25]

C kitFIP1L1-PDGFR120572

Chronic myeloid leukemia (Ph+CML) gastrointestinal stromaltumor (GIST)

lowastlowastDAKO C-KIT PharmDx lowastlowastDako North America Inc [26]

CD 20Non-Hodgkins lymphoma(CD20+ follicular B-cellnon-Hodgkinrsquos lymphoma)

lowastRituxan Sensitivity (CD20)Flow cytometry assay

lowastlowastBexxar tositumomab(GlaxoSmithKine) [27]

CD 25 T-cell lymphoma (cutaneousT-cell lymphoma)

lowastONTAK Sensitivity (CD25)Flow Cytometry (QuestDiagnostics)

lowastlowastOntak denileukin diftitox(Marathon BiopharmaceuticalsInc MA)

[28]

CD 30 Refractory Hodgkins lymphomalowastFluorescent microsphereimmunoassay (QuestDiagnostics)

lowastlowastAdcetris brentuximab vedotin(Seattle genetics Inc) CorporateHeadquarters Seattle GeneticsInc WA USA

[29]

TPMT (CD30+ lymphoma)

lowastTPMT Activity LiquidChromatography TandemMassSpectrometry (LCMSMS)(Quest Diagnostics)

lowastlowastTabloid thioguanine(GlaxoSmithKine) [30]

DPD Breast cancer (with TS MTHFRand DPD gene polymorphisms)

lowastPolymerase Chain Reaction(PCR) Single Nucleotide PrimerExtension

lowastlowastXeloda capecitabine (HoffmanLa Roche Inc) [31]

ER-PGR Breast cancer (ER andor PGR+)lowastImmunohistochemistry (IHC)(Quest Diagnostics)

lowastlowastAromasin exemestane (Pfizer) [32]

G6PD

Lymphoma leukemia (lymphoidleukemia (B and T cell)non-Hodgkinrsquos lymphoma(including Burkittrsquos lymphoma)or acute myelogenous leukemia)

NAlowastlowastElitek rasburicase(Sanofi-synthelabo Inc) [33]

ER Breast cancer (low-gradeERminusPR+)

lowastImmunohistochemical Assay(Quest Diagnostics)

lowastNolvadex tamoxifen(AstraZeneca) [34]

ER Breast cancer (ER+) NAlowastArimidex anastrozole(AstraZeneca) [35]

ER Breast cancer (ER+ andor PgR+) NAlowastlowastFaslodex fulvestrant(AstraZeneca) [36]


Table 1 Continued


UGT1A1 Colorectal cancer (UGT1A1lowast28polymorphisms)

lowastFluorescent polymerase chainreaction (PCR) with primersspecific for the 51015840 untranslatedregion of UGT1A1 (Third WaveTechnologies WI)

lowastlowastCamptosar irinotecan (Pfizer) [37]

ERCC1Gastrooesophageal cancer (withERCC1 nuclear proteinexpression)

NA lowastCamptosar irinotecan (Pfizer) [38]

TPMTMetastatic Testicular tumorsMetastatic ovarian tumorsAdvanced bladder cancer

NAlowastPlatinol cisplatin(Bristol-Myers Squibb Company) [39]

TPMT Acute nonlymphocytic leukemias NAlowastlowastTabloid thioguanine(GlaxoSmithKline) [40]

CDK 4 and 6 Breast cancer (luminal estrogenreceptor-ER+ HER2minus) NA lowastPalbociclib PD-0332991 (Pfizer) [41]

lowastThis biomarkers are used for diagnostic and prognostic purposes to determine the proper cause of treatment (investigational diagnostics andor drugs)lowastlowastFDA approved diagnostics andor drugs

examine biomarkers associated with ovarian cancer a queryof the records of the tissue bank will return sample catalognumbers pertaining to ovarian cancer enabling experimentsto commence The most important and potentially problem-atic aspect of a successful tissue bank is the quality of storedsamples Proper procurementmethods sample handling andthe bank itself are crucial since biomarker investigationsperformed using low-quality samples will likely generateerroneous and misleading data [43]

Additionally relatively few patients consent to have theirbiosamples banked possibly due to a lack of understandingregarding the use of their tissue and the concern that theinformation gained could be used against them in the futureTherefore to improve the rate of consent improved educationof the public and patient populations regarding the safetyand value of such donations is needed In addition theconsent process which involves long difficult to understandforms that must be read and understood could be madeless burdensome One approach to improve education wouldbe to employ models for software engagement that havebeen successful in commercial and educational settingsThese include 3D immersive settings that emulate real-worldsituations such as in the Second Life virtual world platformwhere dynamic choices and outcomes can result in goodor bad medical outcomes [44] Some features of multiusergames would likely be of sufficient interest to sustain theattention of a variety of potential donors and increase patientawareness of tissue donation Constructing and deployingthese sorts of educational tools in public and medical venuessuch as in malls and doctorsrsquo offices or in free apps for smartphones or tablets could be of value in informing patientsof the importance of tissue banking as applied to researchdiscoveries and treatment successes To increase the numberand variety of biosamples new approaches can be applied forpatient education and involvement One promising approachfor increasing the rates of consent to donate biospecimens

was inspired by modern online software that encouragesinteractive learning for casual users [45] Such game-likeinterfaces were shown to be useful in medical education andtraining [46] Better-informed patients who consent moreoften will enrich the number and variety of samples in the tis-sue banks whichwill support the data analysis and integratedinformation bases that can lead to discoveries and treatmentsAn example session might involve an individual interactingwith a public kiosk that allows some user input and providesan immersive environment where the user engages anothercharacter who plays the role of a doctor asking for consent touse a tissue sample for research purposes During the game-like session the user could be led through a set of choicesbased on their actions and responses in realistic scenariosThe encounters and selection sequence could be engineeredsuch that consent form issues are clarified Complex issuessuch as biomolecular interactions and genetic conditionscould be illustrated in attractive 3D renderings so as to bettervisualize biological systems and to focus more precisely onwhy certain therapies are suggested During the session theimportance of consenting to donate biospecimens could bereinforced and the user rewarded by illustrations of improvedhealth of other patients based on more complete informationgleaned in part from donated tissue samples The play couldalso educate the potential donor in how such general consentscould eventually be of personal benefit in the event of negativehealth conditions later in their life

While tissue banks archive and provide biospecimensfor translational research and healthcare innovations thereare challenges to be faced before sample procurement fromdonors Obtaining informed donor consent is a major con-sideration as the health care system considers informedconsent to be legally and ethically required to ensure donordata security Moreover informed consent is an autonomousact and by signing the consent the patientdonor confirmsthat heshe understands the risks and benefits of research


is protected from exploitation and learns the purpose ofthe research for which the donations are made [47] Recentresearch by Beskow et al suggests that combining a simplifiedconsent form with supplemental materials aimed at patientswho wish to have additional information about the researchwouldminimize the complications in understanding researchgoals [48] Similarly there are opt-in and opt-out criteriafor participating in specified research Opt-out methodsare ldquopassiverdquo allowing the participantsdonors to decidewhether to be excluded from the research Often the opt-outapproach provides little information to the donor regardingthe exact research goals Opt-out also provides some choicesfor participantsdonors within a limited timeframe whichhelps to procure more samples to accelerate research Theopt-in method signals the willingness of participantsdonorsto take a more active role in the research this methodreceives more public acceptance with more information andparticipant education [47] The broad consent given by aparticipant permits use of their biospecimens and personalmedical information for future unspecified research underappropriate IRB regulations Broad consent is more of aldquogeneralrdquo criterion which allows the donor to be informedabout the various processes involved in tissue bank functionsbut with limited or no information about the nature offuture research Broad consent has advantages over specifiedinformed consent because it allows biospecimens to be usedfor diverse research activities andminimizes the practical dif-ficulties in transporting consent to the context of tissue banks

Patients are more likely to give consent if they have beeneducated with respect to the benefits of tissue banking priorto the hospital visit thus public awareness plays a vital rolein encouraging tissue donation [49] Efforts from communityadvocates and patient advocate groups canmake the consent-ing process ldquopersonalizedrdquo as well This can be accomplishedby individuals that represent patientsdonors and their fami-lies who have already consented and donated biospecimensThese ldquoalumnirdquo groups or individuals can speak in familygatherings or community events and clarify the confusionand fear that may accompany the cancer diagnosis andanticipated medical procedures In the absence of reliableaccurate information misconceptions about additional pro-cedures treatments and tests can deter a patient frommaking a well-informed decision Conversationsmdashwithoutthe confusing medical jargonmdashwith friends and communitymembers who have gone through the experience can helppotential patientsdonors and their families understand theimportance of donation for tissue banking A small friendlyconversation with the ldquoperson next doorrdquo atmosphere canmake it personal enough for the patientdonor to give consentfor tissue banking This type of personal conversation can beadopted for a national stage at patient advocate conferencesor convention The fact that a specific medical conditionbecomes a top search query on the internet on the same day itis described by the national media illustrates the eagerness ofgeneral public and communities to learn when information isdistributed appropriatelyWe expect similar responses as pre-viously mentioned when efforts are provided to the generalpublic and patient communities regarding the importance of

tissue banking and educate about the role of tissue bankingfor innovations related to personalized medicine

Information technology plays a major role in manage-ment of biobanks Biospecimen information and correspond-ingmolecular and clinicopathological data is currently storedprimarily usingXML forweb-based exchange of informationThis system consists of different servers including web appli-cation database authentication and authorization [50] Thesystem connects with other relevant databases within a hospi-tal enabling storage and retrieval of clinical pathological andpersonal data with highly secure access Ensuring security foraccessing records is provided via digital codes or smart cardsfor users The system can be customized depending upon therequirements of the biobank [50] Software interfaces playa role in storage and retrieval of larger data sets associatedwith biospecimens detailing storage location history andstorage time providing easy traceability of samplesThe Labo-ratory Information Management System (LIMS) is a flexibleexpandable and secure software interface used for storingand retrieving large amounts of data generated throughthe processing of biospecimens in research labs [51] Forexample screenings for genetic mutations in an automatedenvironment require data storage retrieval and trackingLIMS helps minimize human errors in data processing bycommunicating with lab equipment robots and databasesand enables easy retrieval of data [51]

The implementation of BIMS (Biobank InformationManagement System) ensures the integration of data fromdifferent sources such as various research institutionswhich may employ different formats and procedures BIMSresolves data integration issues in biobank research througha series of sequential processes Extraction de-identificationconsolidation abstraction and query [52] are individualcomponents that handle and manage data The extractioncomponent receives data from external sources which arecontinuously updated andor are in different formats depend-ing on the system used to generate the data (eg text filesspread sheets) Deidentification attaches a unique identifierto each data item stored in BIMS and separates personallyidentifiable information from clinical and scientific dataConsolidation transforms imported data to a unified format[52] Abstraction supports data presentation and controlwhen researchersusers access the data through queries Theweb-based query interface allows access for retrieval of datafrom the database [52]

Figure 2 illustrates an integrated knowledge environmentthrough which personalized medicine can be approachedWithin this environment clinicians can determine if a patienthas cancer and what course of treatment should be takenBiomarker analysis will provide the information necessary todetermine whether the patient should receive a conventionalor customized treatment plan For example as noted earlierthe small fraction of NSCLC patients carrying a chromosomerearrangement resulting from an ALK mutation will havea poor outcome with conventional therapy but will do wellwith a personalized treatment that includes Xalkori whichis ineffective in a majority of NSCLS patients A focus onsample quality is important in order to support ldquo-omicsrdquodata and technologies with an eye towards clinical trials


[53] All experiments are dependent on the procurementand availability of high-quality viable tissue specimens thusfrom the first step of procurement it is crucial for the sampleto be properly handled [54]

Collection storage and distribution of high quality tissueand blood samples require information supplied by bioinfor-matics data in concert with a reliable EMR system to link clin-ical data of interest A significant key to proper tissue bankinginvolves proper acquisition of samples by pathologists whoare responsible for determining what should be stored inthe tissue bank by identifying the sample nature and originwhich makes pathology central to communication betweenscientists and clinicians [53] As in bioinformatics tissuebanking requires collaborative efforts between academiahealth institutions and pharmaceutical companies

There are many issues however that pertain to tissuebanking including the loss of samples due to traceabilityand documentation errors and the need for coordinationbetweenmultiple disciplines during the entire procedureTheCancer GenomeAtlas Project (anNCI initiative) assessed thequality of samples acquired from dozens of tissue banks andproduced the surprising result that only one percent of thesamples assessed were viable In addition most of the tissuebanks that supplied these samples had no proper catalog ofsamples that were stored in their facilities [55 56]

Well-established labs that have implemented a precisebank setup can maximize their research potential andeventually contribute to affordable health care diagnosticsfor patients as well as clinicians Biobanks such as the UKBiobank Biobanking and Biomolecular Resources ResearchInfrastructure (BBMRI) and Biobank Japan are among thosethat have created networks of organizations that managemillions of patient samples Stored samples can be usedto analyze cancers at various stages down to a molecularlevel Because of the availability of samples from thesebiobanks even for rare cancers there would be no delay forsample collection since samples would already be availablefor experimentation [57] These samples can be used formechanistic studies for investigating the role of biomarkerin disease progression or used with clinical data points andrecords (EMRs) to predict treatment options drug responsesand susceptibility [58 59] By analyzing tumor samplesand applying a comprehensive approach to determining theproper therapeutic regimen [60] each patient will have abetter chance of a good outcome However if a given samplelacks relevant clinical data from the donor experimentalresults will be more difficult to translate into real-practicemedicine [55]

Samples available from tissue banks are used for exper-iments to discover and validate biomarkers to assist intranslational research identify diagnostic and prognostictargets to maximize patient benefit from customized careand contribute to future diagnosis and treatment options[49] The discovery validation and implementation phasesof research on biomarkers require the resources found intissue banks Completion of the process and confirmationof biomarkers will lead to low-cost yet efficient and reliablemedical care that will result in better patient care [49]

3 The Need for Electronic MedicalRecords (EMRs)

EMRs are used to improve patient care and to date their uti-lization has established high-quality practice-based datasetsthat are well suited for scientific research [61 62] A universaluser friendly ldquoGoogle-likerdquo electronic medical record (EMR)system that allows crosstalk between various infrastructuresis needed since novel biomarker discovery is not possibleunless clinical data are linked with patient samples that canbe associated with clinical outcome [63] To support thistype of initiatives at national level NCI has developed anelectronicprogram providing a collection of cancer-relatedinformation known as caBIG andmade it available to severalhospitals and institutions The sole purpose of the caBIGprogram is to assemble EMR files digitally in order forclinicians and scientists to facilitate translational medicineHowever caBIG function requires that an EMR setup be inplace and since many institutions have not yet instituted aproper EMR system caBIG implementation has been slow

Early adopters of EMR technologies include Sweden andDenmark in the EU andKaiser Permanente andTheVeteransHealth Administration in the USA Even at early stage ofEMR development the success of IT implementations bythese organizations is shown in their increased effectivenessin managing clinical data in electronic format Howeverfailed EMR projects in numerous organizations indicate thatthe currently implemented system needs to be revised Themajor issues related to IT implementations are the complexityof managing the infrastructure maintenance of alignmentbetween organizations with different governance managingfunding ensuring involvement of IT staff and managersengagement of vendors and adapting to changes to improveworking methods [64]

In the USA development of EMR will permit integrationof biological data clinical information patient informationand clinical outcomes Large populations or specific groups ofpatientswith selected characteristics could be easily identifiedwith the availability of electronic medical records EMR canprovide a larger number of participants a wide range of infor-mation and lower research costs [65] In genomic researchEMRs facilitate analysis of genetic andmolecular informationfrom large subject populations allowing studies to be morepowerful than smaller cohort studies Even though there aredifficulties associated with using information provided fromEMRs the lower cost of research and faster pace of advance-ment in clinical care help in overcoming the difficulties In theUSA larger EMR databases are being linked to biospecimensprocured from patientsdonors covering a wide range ofdiseases Analysis of biospecimens resulting in identificationof genetic variants or Single Nucleotide Polymorphisms(SNPs) can be correlated and linked with available EHRinformation regarding parameters such as smoking historyobesity cardio vascular diseases and hypothyroidism [65]

A recent study using a descriptive qualitative approachfor exploring the experiences of primary healthcare providerswho use EHRs in their ongoing practice identified factorsthat support and hinder the use of EHRs in healthcareFactors that support the use of EHRs include improvement


in efficiency of patient care and confidence in IT systemsand software whereas factors that hinder the use of EHRsinclude IT challenges related to computer usage such asscanning electronic connectivity and attaining proficiencyin computer use Generally these factors that hinder useof EMRs can be addressed through training to enhancecomputer skills along with consistent use of EMRs and dataentry [66]

To apply innovative approaches in science and to producethe vast amounts of data required for biomarker analysis it isessential to incorporate clinical data which can only bemadeavailable through EMRs [67] Translating scientific discover-ies into medical practice is the most challenging part of per-sonalized medicine but once the scientific information (iebiomarkers mutations pathways and drugs) is integratedwith clinical data (ie survival relapse pathology medica-tionstreatments and response) the translational power ofbioinformatics will be apparent [68] Other EMR advantagesinclude communication between clinicians scientists andother health care providers as well as notification of healthcare practitioners of common chemotherapy-related errors

However there are certain conflicts regarding the ethicalissues related to EMRs Exposure of health records bymistake lack of security of system and stealing can breachthe confidentiality and fidelity of EMRs which might affectthe treatment of patients [68 69] The health personnelwho create the EMRs should be well aware of these issuesThe Affordable Care Act will eventually require EMRs inevery medical institution EMRs require great attention tothe challenges of electronically documenting care the costof building a large-scale EMR system to replace paper notesand the cost of training employees [70] When a universalEMR is in place it will require management in structureddata security data recovery and infrastructure inspectionwhich will be a general requirement for all medical institu-tions [71] Insufficient medical information technology (IT)infrastructure and a lack of digitized clinical data are otherissues that will almost certainly arise Cancer care is complexand to facilitate management of oncology patient records andworkflow detail-intensive data need to be organized inEMRsMany cancer therapies involve substantial patient illness andEMRs are an important clinical tool to improve patient safetysuitability and efficiency as well as patient-centeredness [72]

4 The Use of Bioinformatics and IntegratedKnowledge Environments

Bioinformatics can enable clinicians to answer a fundamentalquestion based on all that is known about an individ-ual patient including disease characteristics lab resultsgenomic proteomic andmetabolomic information what arethe similarities to other patients who had good outcomesand what is the best therapy for this patient with this dis-ease The progression of biomarker discovery is impossiblewithout bioinformatics which connects individual discoveryprocesses including experimental design study executionand bioanalytic analysis Bioinformatics has dramaticallyprogressed in the past decade with more than one million

published articles in oncology research available in PubMed[42] In the sphere of bioinformatics large amounts ofpertinent ldquo-omicsrdquo data and information from the humangenome are available for oncologic approaches to developbiomarker-related therapies The NCI bioinformatics infras-tructure caBIG makes available information from multiplestudies to support new scientific efforts The infrastructurealso contains details of experiments protocols samples usedand specific results which can be easily searched comparedand downloaded from the database NCIrsquos Early Detec-tion Research Network (EDRN) developed this program sothat cancer institutions would have the bioinformatics dataneeded to support their research [73]

The EDRN exists today because of improvements inoncology research in the past decade that have derived fromprogress in bioinformatics The direction from which studiesare approached has been revolutionized by the essential use-fulness of bioinformatic analysis of large-scale experimentaldatasets Nonetheless many cancer researchers are not accus-tomed to using bioinformatics and have not incorporatedthese advantages into their research This will likely changeas researchers grasp more fully the significance of the overlapbetween many areas of cancer research and bioinformaticswith respect to data analysis and interpretation [74]

Translational research has been supported by bioinfor-matics which has provided critical tools for transformingdata into medical practice and has prompted biomarkerbreakthroughs and drug development (Figure 3) The use ofclinically validated biomarkers will also permit developmentof cheaper less invasive tests that will benefit both cliniciansand patients [75] However the entire process will failwithout the availability of properly curated patient clinicalinformation with which to correlate the biomarker dataBioinformatic results cannot be interpreted in the absenceof clinical data and patient history including treatmentphysicianrsquos notes pathology reports and signs and symptoms[76]The failure to implement use of EMRs is a critical aspectthat delays integration of patient records with experimentalresults yet many healthcare facilities still rely on papernotes [77] Often hospital personnel including clinicianslack the training interest or time to learn and understandthe benefits of bioinformatics There is no mystery to thishealth care providers are occupied with patient care andthere is no reimbursement for entering clinical data into adatabase Nonetheless the participation of clinical personnelin bioinformatics research is vital and must be encouraged

Patient EMR information including demographics anddisease characteristics combined with tissue bank-derivedexperimental results can be used to create a personalizedpatient genomic profile or ldquoinformation objectrdquo that canallow clinicians to query integrated bioinformatics systems tocompare each individual patient with current and historicalinformationThe results frommining and comparing patientprofiles can produce an ldquointelligentrdquo picture of the therapiesand treatments that have the highest probabilities for the bestoutcomes Systems to support clinicians must be fast easyto access and must provide clear answers to personalizedmedicine questions


from

BiologyFDA

approval

Clinical trials

Patient examination

Treatment

Patient outcome

cures

Biomaterials

Chemistry

from

to

Targets

Prevention

Drugdiscovery

Bench tests

Genomics andproteomics

Pathology Diagnosis

Prognosis

Research

Biomarkers

Tissue bank

t

EMRs

to

Clinical

Figure 1 The Sophic Systems Alliance Inc diagram shows the integrated ldquoknowledge environmentrdquo that enables clinicians to query criticalinformation from across disparate data sources to find relationships between an individual patientrsquos EMR information

Figure 2 Scenario of a virtual platform that can demonstrate howpatients are asked to donate tissue andor blood samples in real-world situations with a game-like characteristic

To identify optimal therapies for each unique circum-stance clinicians need easy access to ldquointelligencerdquo which isprovided through the integration and correlation of criticalinformation stored in disparate and constantly changing datasources Successful integration requires a three-way align-ment of information stored in the patientrsquos EMR tissue bankpathology test results and genomic information Clinicaldata on patients diseases therapies and outcomes are storedin hospital patient databases and public sources such asNCIrsquos TCGA and TARGET databases To advance the causeof personalized medicine these clinical databases shouldallow easy access to outcomes data for each patient cohortfor specific diseases and associated therapies which alongwith related drug safety and toxicity information (FDA DrugLabels DrugBank) is critical to decision making regardingthe care of each patient (Figure 1)

Kaplan-Meier chart information can also allow cliniciansto quickly and easily review details sources and specificsof evolving information to gain the confidence required

to decide on a specific treatment regimen Bioinformaticsupport for clinicians should integrate the ability to produceKaplan-Meier charts for easy reference The development ofbioinformatics to support personalized medicine has beenunderway in government academic and private hospitalresearch cancer centers for years Progress is being madetoward resolving some of the more complex obstacles fortranslating and integrating disparate data sources Althoughthe current state of bioinformatics is imperfect collabo-rations between government academic and biotech andpharmaceutical companies have produced advances in stan-dards ontologies and vocabularies that support integrationof critical information Currently available flexible data mod-els provide scientific medical and semantic relationshipsbetween critical data elements that are often stored in varioussystems and databases The virtual integration provided bydata models enables querying mining searching retrievingand accessing critical information necessary to support accu-rate decision making

Integration is achieved through community-wide initia-tives HL7 standards enable translation and communicationof patient information stored in EMRs while Gene OntologyandNCIrsquosThesaurus help align vocabularies and terms acrossresearch databases Clinical and biological databases such asthose hosted by the NCBI as well as others such as Reactomeand Sangerrsquos COSMIC mutation database provide evolvingand improving reference databases from which informationcan be mined and aligned with laboratory data sequenceinformation and genetic mutations to help clinicians decideon treatment options with the highest likelihood of positiveoutcomes

The synthesis and analysis of information from thesevarious sources can expose relationships between critical dataelements that provide ldquointelligencerdquo and can identify the besttherapeutic course to deliver the best outcome Academic


Good outcome Bad outcome

Personalized medicine

Bioinformatics Tissue banking EMRs

Biomarker-derived patient selection

OF

Cl

Cl

N

NN

HN

Nonsmall cell lung cancer ALK mutation Xalkori (crizotinib)

Metastatic melanoma BRAF V600E mutation Zelboraf (vemurafenib)

O

N

N

N N

NH

Use of conventional therapyLung cancer chemotherapyAvastin

(Bevacizumab)

Dacarbazine (DTIC) and Temozolomide (Temodar)

O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy

Melanoma surgeryradiationchemotherapy

NH2

NH2

CH3

CH3 CH3

CONH2

Figure 3 Based on the data resulting from the combination of bioinformatics tissue banking and EMRs novel biomarkers can predict if apatient will go through the normal conventional therapy or require a personalized treatment plan based on the type of mutation and canceris present

cancer treatment hospitals (eg MDAndersonMayo Clinic)have led the way in developing software and technologiesthat allow data integration and EMR mining Commercialsoftware companies are delivering innovative ldquoknowledgeenvironmentsrdquo such as Sophicrsquos SCan-MarK Explorer cancerbiomarker database research mining and discovery systemwhich is built on Biomax BioXM technology With softwarelike BioXM experimental designs can focus on predictivebiomarkers that indicate whether a customized treatmentplan is needed for certain patients In biomarker researchscientists examine how biomarkers are formed how theyfunction and how that function relates to patient data [75]Before biomarkers can be adopted for practical use in theformat of assays and for detection by various biosensorspatient information and bioinformatics need to be combinedto generate hypotheses that can be tested using clinical

samples stored in tissue banks [76] Bioinformatics in par-ticular provides an irreplaceable infrastructure to supportaccompanyingmultidisciplinary education and research [77]

In the future bioinformatics will enable the customiza-tion of medical care to the specific genome of each patientrather than providing a single conventional treatment [78]There will be an abundance of information that can onlybe approached through bioinformatic analysis [79] Canceris complicated and biomarkers promise advancement ofearly diagnosis and targeted therapies which would notbe possible without bioinformatics tools In the case ofHodgkinrsquos lymphoma up to 20 of patients will relapse afterreceiving conventional frontline therapy Without bioinfor-matic data analysis to design clinical studies and query ldquo-omicsrdquo information these ldquofingerprintsrdquo of cancer would bedifficult or impossible to find [80] The strategy that should


be adopted is to take potential biomarkers and use them todetermine the diagnosis prognosis and course of therapyfor specific cancers Biomarker discoveries have the capabilityof improving early diagnosis as well as guiding customizedtherapies and enhanced monitoring after treatment [81]Thus the effective use of bioinformatics in clinical settingby analyzing clinical data from EMR along with biomarker-derived diagnostic or prognostic assays can provide clinicaldecision making steps that could be of long-term benefit topatients [80]

5 Conclusions

Health care practitioners need more training in the areas ofbioinformatics and tissue banking and EMR systems needto be in place to provide the necessary components forbiomarker discovery that can lead to customized medicalcare for cancer patients Training can be accomplished by (i)presenting bioinformatics as a helpful toolkit (ii) promotingimproved training of individuals in proper protocols fortissue procurement and storage (iii) encouraging documen-tation of all patient information using EMRs instead of papercharts and (iv) fostering further collaborative efforts betweenclinicians and scientists Methods for providing more infor-mation about the benefits of tissue sample donations andincreasing informed consent can be improved to ensurericher data sources for determining patterns and personaldifferences With these enhancements in place the focuscan be shifted to the discovery of predictive diagnosticand prognostic biomarkers that will allow proper diagnosisof specific cancers increase information about a particulardisease and indicate the direction treatment should takeCommunity-wide efforts for collecting patient informationcreation of well-controlled tissue banks and developmentof new genomic and proteomic technologies will provideclinicians with the building blocks for achieving personalizedmedicine and improving patient treatment outcomes Theseefforts will also provide patients with reduced medical carecosts On the long run adoption and integration of bioinfor-matic tools into routine clinical use will save lives

References

[1] J A de Souza and O I Olopade ldquoCYP2D6 genotyping andtamoxifen an unfinished story in the quest for personalizedmedicinerdquo Seminars in Oncology vol 38 no 2 pp 263ndash2732011

[2] Early Breast Cancer Trialistsrsquo Collaborative Group ldquoEffects ofchemotherapy and hormonal therapy for early breast cancer onrecurrence and 15-year survival an overview of the randomisedtrialsrdquoThe Lancet vol 365 no 9472 pp 1687ndash1717 2005

[3] M Verma ldquoPersonalized medicine and cancerrdquo Journal ofPersonalized Medicine vol 2 no 1 pp 1ndash14 2012

[4] M Dammann and F Weber ldquoPersonalized medicine caughtbetween hope hype and the real worldrdquo Clinics vol 67supplement 1 pp 91ndash97 2012

[5] A J Atherly and D R Camidge ldquoThe cost-effectiveness ofscreening lung cancer patients for targeted drug sensitivitymarkersrdquoBritish Journal of Cancer vol 106 no 6 pp 1100ndash11062012

[6] S Louca ldquoPersonalized medicinemdasha tailored health care sys-tem challenges and opportunitiesrdquo Croatian Medical Journalvol 53 no 3 pp 211ndash213 2012

[7] K S Suh ldquoDiscovery of novel biomarkers for the developmentof personalized medicinerdquo Translational Medicinecinec 2012

[8] A Somasunderam and D G Gorenstein ldquoAptamers as novelreagents for biomarker discovery applicationsrdquo TranslationalMedicinec 2011

[9] S K Suh Y K Remache J S Patel et al ldquoInformatics-guided procurement of patient samples for biomarker discoveryprojects in cancer researchrdquo Cell and Tissue Banking vol 10 no1 pp 43ndash48 2009

[10] S Sarojini A Tamir H Lim et al ldquoEarly detection biomarkersfor ovarian cancerrdquo Journal of Oncology vol 2012 Article ID709049 15 pages 2012

[11] N B la Thangue and D J Kerr ldquoPredictive biomarkers aparadigm shift towards personalized cancer medicinerdquo NatureReviews Clinical Oncology vol 8 no 10 pp 587ndash596 2011

[12] D Slamon W Eiermann N Robert et al ldquoAdjuvant trastuz-umab inHER2-positive breast cancerrdquoTheNewEngland Journalof Medicine vol 365 no 14 pp 1273ndash1283 2011

[13] A T Shaw U Yasothan and P Kirkpatrick ldquoCrizotinibrdquoNatureReviews Drug Discovery vol 10 no 12 pp 897ndash898 2011

[14] M S Kies and P M Harari ldquoCetuximab (imclonemerckbristol-myers squibb)rdquo Current Opinion in InvestigationalDrugs vol 3 no 7 pp 1092ndash1100 2002

[15] R G Amado M Wolf M Peeters et al ldquoWild-type KRAS isrequired for panitumumab efficacy in patients with metastaticcolorectal cancerrdquo Journal of Clinical Oncology vol 26 no 10pp 1626ndash1634 2008

[16] P B Chapman A Hauschild C Robert et al ldquoImprovedsurvival with vemurafenib in melanoma with BRAF V600Emutationrdquo The New England Journal of Medicine vol 364 no26 pp 2507ndash2516 2011

[17] S J Isakoff B Overmoyer N M Tung et al ldquoA phase II trial ofthe PARP inhibitor veliparib (ABT888) and temozolomide formetastatic breast cancerrdquo Journal of Clinical Oncology vol 28supplement 15 2010

[18] C M Annunziata and S E Bates ldquoPARP inhibitors in BRCA1BRCA2 germline mutation carriers with ovarian and breastcancerrdquo F1000 Biology Reports vol 2 no 1 article 10 2010

[19] R S Herbst D Prager R Hermann et al ldquoTRIBUTE a phaseIII trial of erlotinib hydrochloride (OSI-774) combined withcarboplatin and paclitaxel chemotherapy in advanced non-small-cell lung cancerrdquo Journal of Clinical Oncology vol 23 no25 pp 5892ndash5899 2005

[20] G Giaccone R S Herbst C Manegold et al ldquoGefitinib incombination with gemcitabine and cisplatin in advanced non-small-cell lung cancer a phase III trialmdashINTACT 1rdquo Journal ofClinical Oncology vol 22 no 5 pp 777ndash784 2004

[21] S L Soignet P Maslak Z G Wang et al ldquoComplete remissionafter treatment of acute promyelocytic leukemia with arsenictrioxiderdquoThe New England Journal of Medicine vol 339 no 19pp 1341ndash1348 1998

[22] U Rix OHantschel G Durnberger et al ldquoChemical proteomicprofiles of the BCR-ABL inhibitors imatinib nilotinib anddasatinib reveal novel kinase and nonkinase targetsrdquo Blood vol110 no 12 pp 4055ndash4063 2007

[23] M C Muller J E Cortes D W Kim et al ldquoDasatinibtreatment of chronic-phase chronic myeloid leukemia analysisof responses according to preexisting BCR-ABL mutationsrdquoBlood vol 114 no 24 pp 4944ndash4953 2009


[24] T Fischer R M Stone D J DeAngelo et al ldquoPhase IIB trialof oral midostaurin (PKC412) the FMS-like tyrosine kinase 3receptor (FLT3) and multi-targeted kinase inhibitor in patientswith acute myeloid leukemia and high-risk myelodysplasticsyndrome with either wild-type or mutated FLT3rdquo Journal ofClinical Oncology vol 28 no 28 pp 4339ndash4345 2010

[25] A Sartore-BianchiMDelorenzi TGagnon-Kugler et al ldquoNewfrontiers in therapeutic resistance in cancerrdquo Expert Review ofAnticancer Therapy vol 12 no 7 pp 877ndash879 2012

[26] C Fausel ldquoTargeted chronic myeloid leukemia therapy seekinga curerdquo American Journal of Health-System Pharmacy vol 64supplement 24 pp S9ndashS15 2007

[27] M R Chamarthy S C Williams and R M MoadelldquoLymphoma radioimmunotherapy of non-hodgkinrsquos from theldquoMagic Bulletsrdquo to lsquoRadioactive Magic Bulletsrsquordquo Journal ofBiology and Medicin vol 84 pp 391ndash407 2011

[28] F Lansigan D M Stearns and F Foss ldquoRole of denileukindiftitox in the treatment of persistent or recurrent cutaneous T-cell lymphomardquo Cancer Management and Research vol 2 no 1pp 53ndash59 2010

[29] A Younes N L Bartlett J P Leonard and D A KennedyldquoBrentuximab vedotin (SGN-35) for relapsed CD30-positivelymphomasrdquoTheNew England Journal of Medicine vol 363 pp1812ndash1821 2010

[30] S Zhou ldquoClinical pharmacogenomics of thiopurine S-methyltransferaserdquo Current Clinical Pharmacology vol 1 no 1pp 119ndash128 2006

[31] R Largillier M Etienne-Grimaldi J Formento et al ldquoPharma-cogenetics of capecitabine in advanced breast cancer patientsrdquoClinical Cancer Research vol 12 pp 5496ndash5502 2006

[32] C J Fabian ldquoThe what why and how of aromatase inhibitorshormonal agents for treatment and prevention of breast cancerrdquoInternational Journal of Clinical Practice vol 61 no 12 pp 2051ndash2063 2007

[33] S K McBrayer M Yarrington J Qian et al ldquoIntegrative geneexpression profiling reveals G6PD mediated resistance to RNAdirected nucleoside analogues in B-cell neoplasmsrdquo PLoS Onevol 7 no 7 Article ID e41455 2012

[34] L Yang H Tseng C Lin et al ldquoSurvival benefit of tamoxifen inestrogen receptor-negative and progesterone receptor-positivelow grade breast cancer patientsrdquo Journal of Breast Cancer vol15 no 3 pp 288ndash295 2012

[35] M Milani G Jha and D A Potter ldquoAnastrozole use inearly stage breast cancer of post-menopausal womenrdquo ClinicalMedicine Therapeutics vol 1 pp 141ndash156 2009

[36] S A Garnett M Martin G Jerusalem et al ldquoComparingduration of response and duration of clinical benefit betweenfulvestrant treatment groups in theCONFIRM trial applicationof new methodologyrdquo Breast Cancer Research and Treatmentvol 138 pp 149ndash155 2013

[37] X Liu D Cheng Q Kuang G Liu and W Xu ldquoAssociationbetween UGT1A1lowast28 polymorphisms and clinical outcomes ofirinotecan-based chemotherapies in colorectal cancer a meta-analysis in caucasiansrdquo PLOS One vol 8 no 3 Article IDe58489 2013

[38] K R Fareed A Al-Attar I N Soomro et al ldquoTumour regres-sion and ERCC1 nuclear protein expression predict clinicaloutcome in patients with gastro-oesophageal cancer treatedwith neoadjuvant chemotherapyrdquo British Journal of Cancer vol102 no 11 pp 1600ndash1607 2010

[39] J Li W H Wood K G Becker A T Weeraratna and PJ Morin ldquoGene expression response to cisplatin treatment in

drug-sensitive and drug-resistant ovarian cancer cellsrdquo Onco-gene vol 26 no 20 pp 2860ndash2872 2007

[40] B Yuan J Zhang H Wang et al ldquo6-Thioguanine reac-tivates epigenetically silenced genes in acute lymphoblasticleukemia cells by facilitating proteasome-mediated degradationof DNMTrdquo Cancer Research vol 71 no 5 pp 1904ndash1911 2011

[41] R S Finn J Dering D Conklin et al ldquoPD 0332991 a selectivecyclin D kinase 46 inhibitor preferentially inhibits prolifera-tion of luminal estrogen receptor-positive human breast cancercell lines in vitrordquo Breast Cancer Research vol 11 no 5 articleR77 2009

[42] D B Martin and P S Nelson ldquoFrom genomics to proteomicstechniques and applications in cancer researchrdquo Trends in CellBiology vol 11 no 11 pp S60ndashS65 2001

[43] E S Richmond and D Dunn ldquoBiomarkers an overview foroncology nursesrdquo Seminars in Oncology Nursing vol 28 no 2pp 87ndash92 2012

[44] R Christianson ldquoVirtual Patient Encounters Aim to Edu-cate Students in Geriatric Carerdquo The University of TexasSchool of Health Information Sciences at Houston 2009httpwwwuthoustonedusbmistoryhtmid=1852714

[45] A Gorini A Gaggioli C Vigna and G Riva ldquoA second life foreHealth prospects for the use of 3-D virtual worlds in clinicalpsychologyrdquo Journal of Medical Internet Research vol 10 no 3article e21 2008

[46] LondonMedical Students Train in Second Life Virtual HospitaliHealthBeat 2008 httpwwwihealthbeatorgArticles2009330London-Medical-Students-Train-in-Second-Life-Virtual-Hospitalaspx

[47] C M Simon J LrsquoHeureux J C Murray et al ldquoActive choice butnot too active public perspectives on biobank consent modelsrdquoGenetics in Medicine vol 13 pp 821ndash831 2011

[48] L M Beskow J Y Friedman N Chantelle Hardy L Linand K P Weinfurt ldquoDeveloping a simplified consent form forbiobankingrdquo PLoS One vol 5 no 10 Article ID e13302 2010

[49] S Sarojini A Goy A Pecora and K S Suh ldquoProactivebiobanking to improve research and health carerdquo Journal ofTissue Science amp Engineering vol 3 no 2 2011

[50] M Galvagni S Cotrupi and M Barbareschi ldquoBiobanks andinformation technologyrdquo Pathologica vol 100 no 2 pp 116ndash138 2008

[51] C Voegele S V Tavtigian D de Silva S Cuber A Thomasand F le Calvez-Kelm ldquoA Laboratory InformationManagementSystem (LIMS) for a high throughput genetic platform aimed atcandidate gene mutation screeningrdquo Bioinformatics vol 23 no18 pp 2504ndash2506 2007

[52] G Olund P Lindqvist and J E Litton ldquoBIMS an informationmanagement system for biobanking in the 21st centuryrdquo IBMSystems Journal vol 46 no 1 pp 171ndash182 2007

[53] G Bevilacqua F Bosman T Dassesse et al ldquoThe role of thepathologist in tissue banking European consensus expert groupreportrdquo Virchows Archiv vol 456 no 4 pp 449ndash454 2010

[54] P H Riegman M M Morente F Betsou et al ldquoBiobanking forbetter healthcarerdquoMolecular Oncology vol 2 no 3 pp 213ndash2222008

[55] C T Scott T Caulfield E Borgelt et al ldquoPersonal medicinemdashthe new banking crisisrdquoNature Biotechnology vol 30 no 2 pp141ndash147 2012

[56] Institute ofMedicineEstablishing Precompetitive Collaborationsto Stimulate Genomics-Driven Drug Development WorkshopSummary National Academies Press Washington DC USA2011


[57] V P Scholtes J P de Vries L M Catanzariti et al ldquoBiobankingin atherosclerotic disease opportunities and pitfallsrdquo CurrentCardiology Reviews vol 7 no 1 pp 9ndash14 2011

[58] P Hainaut E Caboux G Bevilacqua et al ldquoPathology asthe cornerstone of human tissue banking European consensusexpert group reportrdquo Biopreservation and Biobanking vol 7 no3 pp 157ndash160 2009

[59] R E Hewitt ldquoBiobanking the foundation of personalizedmed-icinerdquo Current Opinion in Oncology vol 23 no 1 pp 112ndash1192011

[60] S Ogino C S Fuchs and E Giovannucci ldquoHow many molec-ular subtypes Implications of the unique tumor principle inpersonalizedmedicinerdquoExpert Review ofMolecularDiagnosticsvol 12 no 6 pp 621ndash628 2012

[61] S Pakhomov S Bjornsen P Hanson and S Smith ldquoQualityperformance measurement using the text of electronic medicalrecordsrdquo Medical Decision Making vol 28 no 4 pp 462ndash4702008

[62] J C Denny R A Miller L R Waitman M A Arrieta and J FPeterson ldquoIdentifying QT prolongation from ECG impressionsusing a general-purpose Natural Language Processorrdquo Interna-tional Journal of Medical Informatics vol 78 supplement 1 ppS34ndashS42 2009

[63] C L Overby P Tarczy-Hornoch J I Hoath I J Kalet and DL Veenstra ldquoFeasibility of incorporating genomic knowledgeinto electronic medical records for pharmacogenomic clinicaldecision supportrdquo BMC Bioinformatics vol 11 no 9 article S102010

[64] eHealth for a healthier Europe httpwwwortivusseDoc-umentsPdfSwedish-EU-Presidency-Report-eHealth-for-a-Healthier-Europepdf

[65] Toward Precision Medicine Building a Knowledge Networkfor Biomedical Research and a New Taxonomy of Diseasehttpwwwucsfedusitesdefaultfileslegacy filesdocumentsnew-taxonomypdf

[66] A L Terry J B Brown L Bestard Denomme A Thind andM Stewart ldquoPerspectives on electronic medical record imple-mentation after two years of use in primary health care practicerdquoThe Journal of the American Board of Family Medicine vol 25pp 522ndash527 2012

[67] P M Blake D A Decker T M Glennon et al ldquoTowardan integrated knowledge environment to support modernoncologyrdquoThe Cancer Journal vol 17 no 4 pp 257ndash263 2011

[68] J L Bernat ldquoEthical and quality pitfalls in electronic healthrecordsrdquo Neurology vol 80 no 11 pp 1057ndash1061 2013

[69] E J Layman ldquoEthical issues and the electronic health recordrdquoHealth Care Manager vol 27 no 2 pp 165ndash176 2008

[70] T H Payne M Perkins R Kalus and D Reilly ldquoThe transitionto electronic documentation on a teaching hospital medicalservicerdquoAnnual SymposiumProceedings vol 2006 pp 629ndash6332006

[71] B Malin and E Airoldi ldquoConfidentiality preserving audits ofelectronic medical record accessrdquo Studies in Health Technologyand Informatics vol 129 part 1 pp 320ndash324 2007

[72] C F Snyder A W Wu R S Miller R E Jensen E T Bantugand A C Wolff ldquoThe role of informatics in promoting patient-centered carerdquo The Cancer Journal vol 17 no 4 pp 211ndash2182012

[73] D J Crichton C A Mattmann MThornquist et al ldquoBioinfor-matics biomarkers of early detectionrdquoCancer Biomarker vol 9no 1ndash6 pp 511ndash530 2010

[74] D Kihara Y D Yang and T Hawkins ldquoBioinformatics resour-ces for cancer research with an emphasis on gene function andstructure prediction toolsrdquo Cancer Informatics vol 2 no 1 pp25ndash35 2006


[76] H Nakagawa ldquoResearch and development for cancer bio-markerrdquo Nippon Rinsho vol 70 no 5 pp 743ndash747 2012

[77] J Y Yang M Q Yang H R Arabnia and Y Deng ldquoGenomicsmolecular imaging bioinformatics and bio-nano-info inte-gration are synergistic components of translational medicineand personalized healthcare researchrdquo BMC Genomics vol 9supplement 2 article I1 2008

[78] G S Ginsburg and H F Willard ldquoGenomic and person-alized medicine foundations and applicationsrdquo TranslationalResearch vol 154 no 6 pp 277ndash287 2009

[79] G H Fernald E Capriotti R Daneshjou K J Karczewskiand R B Altman ldquoBioinformatics challenges for personalizedmedicinerdquo Bioinformatics vol 27 no 13 pp 1741ndash1748 2011

[80] J Li Z Zhang J Rosenzweig Y Y Wang and D W ChanldquoProteomics and bioinformatics approaches for identification ofserum biomarkers to detect breast cancerrdquo Clinical Chemistryvol 48 no 8 pp 1296ndash1304 2002

[81] E Abrahams G S Ginsburg and M Silver ldquoThe personalizedmedicine coalition goals and strategiesrdquo American Journal ofPharmacoGenomics vol 5 no 6 pp 345ndash355 2005


information regarding the effectiveness of tamoxifen treat-ment [1] If a poor clinical outcome is predicted thenadditional data and evidence-driven clinical decisions mayallow better alternative therapy options for those patientsWith recent advances the ER PR and Her2 status of breastcancer patients can be used to make therapeutic choicesthat include a customized tamoxifen regimen to preventdisease recurrence [2]Thenext generation of sequencing andldquo-omicsrdquo technologies will continue to improve our ability torecognize cancers improve treatments and track the healthof survivors [3] Scientific data from ldquo-omicsrdquo now representmany pathways and molecular signatures that are directlyinvolved in triggering cancers and these research data can beapplied to diagnosis prognosis and treatment decisions [4]

As the field of personalized medicine evolves scientificand clinical data are expected to converge in a commoncentral database which will facilitate the exchange of datathat can be transformed into valuable information that willaid clinical decisions enable customized treatments and gen-erate new advances for cancer medicineThese developmentswould be cost effective for both patients and health carepractitioners because a proper course of action could beidentified using the stored data which will help avoid theuse of unnecessary tests and ineffective therapies With theimplementation of the Affordable Care Act ldquoObamacarerdquo in2014 economical assays that provide accurate results will beneeded to determine themost effective treatments and ensurethe best outcomes In evaluating the cost of screening assaycosts and the cost effectiveness of drugs must be consideredand should correlate with the cost of biomarker detection inpatient samples [5] Screening assays will provide tools formaking the most accurate clinical decisions such that thecustomized treatment represents a best fit if not a match andtargets molecular changes that occur in the patientrsquos tumorCompanion assays for each targeted drug will maximize thetreatment benefit options for a specific cancer Minimallyinvasive procedures for obtaining small biospecimens frompatients will also help drive down medical costs to satisfythe new regulations The combined scientific and clinicalinformation from each cancer patient can be further analyzedand compared precisely with traditional treatments and anynew treatments with companion diagnostics can be testedin clinical trials Thus elucidating the molecular profile ofeach patient involves testing for robust biomarkers with highsensitivity and specificity for particular cancer phenotypesand requires high-quality biospecimens and well-organizedtissue banking Scientific information must be integratedwith clinical information derived from well-documentedelectronic medical records (EMRs) using informatics toolsalthough to date the importance of this integration hasbeen largely neglected by the research and clinical com-munity In combination tissue banking bioinformatics andEMRs are front-end requirements for enhancing personal-ized medicine and they represent key resources that willdetermine the path of progress in translational research tosupport clinical applications

Bioinformatics encompasses a combination of statisticsmolecular biology and computer science to store and analyzebiological data while tissue banking involves procurement of

tissue or tumor samples during medical procedures and theircollection and storage in a tissue repository By integratingpatient information and experimental results novel biomark-ers can be discovered that may have a major effect on the waypatients receive care and could also greatly influence drug anddiagnostic customization [6] Biomarkers can be proteinsgenes metabolites or evenmethylation patterns that are usedto detect genetic tendencies for specific types of cancers andother diseases (Table 1) [7] Depending on the cancer certaindiagnostic tests are performed and if a given biomarker isfound in a patient sample it will guide the choice of treat-ment In the case ofmelanoma for example a BRAFmutationtest is used to determine if a BRAF V600E mutation exists inthe patient sample and if present that patient will receive acustomized treatment with the drug Zelboraf which is effec-tive only for BRAFV600E-positivemelanomas Nonsmall celllung cancer (NSCLC) patients carrying an ALK mutationare treated with the drug Xalkori which is specific for thistype of mutation whereas NSCLC patients having an EGFRmutation would receive alternative customized treatments

These well-studied biomarkers enhance the ability ofclinicians to determine a course of treatment with minimaltoxicity However there remains a need for technologies toassist with the discovery and transformation of biomarkersto diagnostic uses [7] One approach is the use of aptamerssmall DNARNA oligonucleotides having high selectivity fortheir target which can help avoid the limitations imposed byantibodies in diagnostic applications [8] To initially identifypotential cancer-specific biomarkers biomarker discoveryapplications require bioinformatics data information fromwhich can then be used for analysis of samples stored in tissuebanks Sample quality and the associated clinical informationare also important factors in biomarker discovery becausedata from all components are required to complete thisprocess [9 10] Table 1 includes a list of currently availabledrugs in cancer therapy developed after identifying relevantbiomarkers and companion diagnostics [11ndash41]

Given the variety of data and samples being collected andadvances in personalizedmedicine the importance of collab-orations between scientists and clinicians as well as industryand academia becomes evident Targeted therapies thera-peutic resistance challenges of ldquo-omicsrdquo technologies andeven issues with biomarker-related trials can be approachedonly through collaboration [42] There are scientific uncer-tainties present in all areas under study which medicalresearch alone cannot address However through a transdis-ciplinary scientific methodology these disparate areas canbe combined to offer innovative and unique diagnostic andtreatment plans [6]

2 Importance of Tissue Banking

In the past two decades efforts to create and maintain tissuebanks have provided a foundation for future research towardpersonalized medicine in cancer After potential biomarkershave been identified through the use of bioinformatics andan experimental design has been put into place tissue bankscome into play If for example an institution wants to











EGFR KRAS(mutation)




[13 16 17]












[13 24 25]










[28]



[29]









G6PD









Table 1 Continued













































from

BiologyFDA

approval

Clinical trials

Patient examination

Treatment

Patient outcome

cures

Biomaterials

Chemistry

from

to

Targets

Prevention

Drugdiscovery

Bench tests


Pathology Diagnosis

Prognosis

Research

Biomarkers

Tissue bank

t

EMRs

to

Clinical













OF

Cl

Cl

N

NN

HN



O

N

N

N N

NH


(Bevacizumab)


O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy


NH2

NH2

CH3

CH3 CH3

CONH2







5 Conclusions


References































































































EGFR KRAS(mutation)




[13 16 17]












[13 24 25]










[28]



[29]









G6PD









Table 1 Continued













































from

BiologyFDA

approval

Clinical trials

Patient examination

Treatment

Patient outcome

cures

Biomaterials

Chemistry

from

to

Targets

Prevention

Drugdiscovery

Bench tests


Pathology Diagnosis

Prognosis

Research

Biomarkers

Tissue bank

t

EMRs

to

Clinical













OF

Cl

Cl

N

NN

HN



O

N

N

N N

NH


(Bevacizumab)


O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy


NH2

NH2

CH3

CH3 CH3

CONH2







5 Conclusions


References






















































































Table 1 Continued













































from

BiologyFDA

approval

Clinical trials

Patient examination

Treatment

Patient outcome

cures

Biomaterials

Chemistry

from

to

Targets

Prevention

Drugdiscovery

Bench tests


Pathology Diagnosis

Prognosis

Research

Biomarkers

Tissue bank

t

EMRs

to

Clinical













OF

Cl

Cl

N

NN

HN



O

N

N

N N

NH


(Bevacizumab)


O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy


NH2

NH2

CH3

CH3 CH3

CONH2







5 Conclusions


References


















































































































from

BiologyFDA

approval

Clinical trials

Patient examination

Treatment

Patient outcome

cures

Biomaterials

Chemistry

from

to

Targets

Prevention

Drugdiscovery

Bench tests


Pathology Diagnosis

Prognosis

Research

Biomarkers

Tissue bank

t

EMRs

to

Clinical













OF

Cl

Cl

N

NN

HN



O

N

N

N N

NH


(Bevacizumab)


O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy


NH2

NH2

CH3

CH3 CH3

CONH2







5 Conclusions


References


























































































OF

Cl

Cl

N

NN

HN



O

N

N

N N

NH


(Bevacizumab)


O

N N

NN

N

O

O

O

Cl

N N

NF

F

H

H

S

Targeted therapy


NH2

NH2

CH3

CH3 CH3

CONH2







5 Conclusions


References























































































5 Conclusions


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