P4 Medicine  in  Cancer

Transformation  of  healthcare  from f f freactive  to  preventive

Dr. Reza Nekouian

Iran University of Medical Sciences (IUMS) rnekouian@gmail.com

Traditional medical practice has always been “reactive”, meaning that

the doctor intervenes when there is disease.

Theoretical (scale-free networks and complex systems), technological

(highly efficient “omic” technologies) and conceptual (systems biology)

advances of the last decade prelude the transition towards

“anticipatory” medicine centered on health and not disease.

“P4 Medicine” as it is Personalized, Predictive, 

Preventive and Participatory

Transformation  of  healthcare  from reactive  to  preventive

Personalized, Predictive, Preventive and Participatory medicine (P4 Medicine) centered on health

This change will be possible thanks to the advances made in the field of:

medicine (P4 Medicine) centered on health. 

g p

• basic science

• the development of computer tools

• imaging techniques

• the use of concepts of engineering physics

RReductionist eductionist SStrategytrategy

The organism as a whole (anatomy),

to the organs (physiology),

cells (cellular biology),

molecules,

(genes, proteins, lipids and metabolites; molecular biology)

Networks dominate all aspects of human 

health and disease

To understand the mechanisms of disease merely having a listTo understand the mechanisms of disease, merely having a list 

of    “disease genes” is not sufficient. 

O d h h f i f h ll lOne needs the graph or map of connections of the cellular 

components that are influenced by these genes and by the p y g y

products of said genes.

Th i t f ifi lt ti i l l d tiThe existence of specific alterations in molecular and genetic

networks brings into play the possibility that

diseases are not as independent from each other

as they are generally considered.

There is a great number of diseases that despite having differentThere is a great number of diseases that, despite having different

forms of clinical expression, form part of a same network.

Diseasome

The network of human diseases that share common 

ti d l l l tgenetic and molecular elementos

The contemporary classification of diseases is fundamentally 

New approach in the classification of diseases based on four different networks

that interact:

based on clinical presentation (phenotypes)

that interact:

1) Principal molecular abnormality (primary genome or proteome) associated

with the principal phenotype;

2) Modifier genes or proteins of the main phenotype principal (secondary

genome or proteome);

3) Polymorphisms or haplotypes (intermediate phenotype) that influence each

genetic response to stress (inflammation, apoptosis, proliferation, reparation);

4) Environmental determinants.

Based on the confirmation of the pathophysiological relevance of these four

networks new alternatives can be considered for optimizing therapeuticnetworks, new alternatives can be considered for optimizing therapeutic

approaches to disease:

To identify new therapeutic targets (for example, the androgenic receptor in

prostate cancer,

To determine the appropriate dosage of a medication, based on its metabolic

profile,profile,

To establish the ca ses of resistance to treatments or to impro e the to icitTo establish the causes of resistance to treatments or to improve the toxicity

of drugs.

Phenotypic Disease Network

Differences between race and sex.

The Phenotypic Disease Network (PDN) have beenThe Phenotypic Disease Network (PDN) have been 

generated by reviewing the electronic clinical data of 

more than 30 million patients (Medicare)

The PDN study shows that:

1) patients develop diseases that are closer to each other in the

networknetwork

2) progression of the disease along the links of the network is2) progression of the disease along the links of the network is

different between patients of different sexes and different ethnicities

3) patients diagnosed with diseases that have many connections in

th PDN t d t di b f th ff t d b l t dthe PDN tend to die before those affected by less-connected

diseases

4) Diseases that tend to be preceded by others in the PDN tend to

be more connected than diseases that precede others, and they

are associated with higher mortality rates

The phrase “P4 Medicine”

(Personali ed Predicti e Pre enti e and Participator )

P4 Medicine(Personalized, Predictive, Preventive and Participatory)

was coined by David Galas and Leroy Hood.

Biological complexity are studied based on three fundamental

premises:premises:

1) There are two types of biological information:1) There are two types of biological information:

digital genome information and environmental information,

t id th th t difi id di it l i f tioutside the genome, that modifies said digital information

2) biological information is captured, processed, integrated and

t f d b f bi l i l t k (RNA t itransferred by means of biological networks (RNA, proteins,

controlling regions of the genes and small molecules) to the

fmolecular systems that execute vital functions

It is said that P4 Medicine will be “personalized” because it will be based on the

genetic information of each individual;

it will be “predictive” because this personalized information will be able to

determine the risk for certain diseases in each individual;determine the risk for certain diseases in each individual;

It will be “preventive” because, given the prediction of risk, prophylactic

measures will be able to be taken (lifestyle or therapeutic) to decrease risk;

and, last of all, it will be “participative” because many of these prophylactic

interventions will undeniably require the participation of the patient.

Due to such participation, one of the most traditional 

aspects of clinical practice will therefore disappear: 

doctor‐patient paternalism.doctor patient paternalism.

Human Genome Project (HGP) The Cancer Genome Atlas (TCGA) 

Planed in 1984 Started in 1990

Completed in 2003

Started in 2005Expanded into phase II in 2009

Continued up to nowCompleted in 2003 Continued up to now

The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed

large numbers of human tumors to discover molecular aberrations at the DNA,

RNA, protein and epigenetic levels.

The resulting rich data provide a major opportunity to develop an integrated

picture of commonalities, differences and emergent themes across tumor p , g

lineages.

The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA.

Analysis of the molecular aberrations and their functional roles across tumorAnalysis of the molecular aberrations and their functional roles across tumor

types will teach us how to extend therapies effective in one cancer type to others

with a similar genomic profile.

The TCGA Pan-Cancer project assembled data from thousands of patients with

primary tumors occurring in different sites of the body covering 12 tumor typesprimary tumors occurring in different sites of the body, covering 12 tumor types

including:

glioblastoma multiformae (GBM),

lymphoblastic acute myeloid leukemia (LAML),

head and neck squamous carcinoma (HNSC),

( )lung adenocarcinoma (LUAD),

lung squamous carcinoma (LUSC),

breast carcinoma (BRCA),breast carcinoma (BRCA),

kidney renal clear-cell carcinoma (KIRC),

ovarian carcinoma (OV),

bladder carcinoma (BLCA),

colon adenocarcinoma (COAD),

uterine cervical and endometrial carcinoma (UCEC)uterine cervical and endometrial carcinoma (UCEC)

rectal adenocarcinoma (READ).

The Cancer Genome AtlasThe Cancer Genome Atlas (TCGA) (TCGA) 

Catalogue genetic mutations responsible for cancer using genomeCatalogue genetic mutations responsible for cancer, using genome 

sequencing and bioinformatics.

TCGA represents an effort in the War on Cancer that is 

applying high throughput genome analysis techniques to improveapplying high‐throughput genome analysis techniques to improve 

our ability to diagnose, treat, and prevent cancer through a better 

understanding of the genetic basis of this disease.

Counseling 

Cancer Prognosis

Documentation

and intervention

Prognostics tests

Risk factor analysis

tests

Counseling and 

interventionResult

Follow up

Discharge

interventionResult 

Marker  Sample method Reason of measurement

(1)Mutation in BRCA1 and BRCA2 genes

Blood or saliva

PCR and sequencing Identification of women at high risk

(2)Estrogen receptor (ER)/progesterone receptor 

(PR)

Tumor ligand‐bindingAssay, ELISA or

immunohistochemistry(IHC )

Prediction, prognosis(1)

(IHC )

(3)HER‐2/neu Tumor IHC and FISH Prediction, prognosis (2)

(4)Urokinase plasminogen Tumor ELISA Prognosis (3)(4)Urokinase plasminogen activator (uPA) and 

plasminogen activator inhibitor (PAI‐1)

Tumor ELISA Prognosis (3)

(5)G ti di fl id Bl d (5) I hi t h i t diff ti l(5)Gross cystic disease fluid protein (GCDFP‐15) (4)

Blood (5) Immunohistochemistry differential diagnosis 

(6)CA15 3/BR27 29 CA Bl d ELISA P t ti(6)CA15‐3/BR27.29 or CA 27.29

Blood ELISA Postoperative Surveillance and Monitoring(6)

Marker  Sample method Reason of measurement

(7)CEA Blood ELISA Postoperative Surveillance Monitoring (7)

(8)TPA(8) Blood RIA  Post‐operative surveillance, monitoring therapymonitoring therapy

(9)TPS(9) Blood ELISA Post‐operative surveillance, monitoring therapy

(10) Gene signature 

(Oncotype DX)

Tumor RT‐PCR(10) Evaluation of risk of recurrence

(11)Gene Microarray Evaluation of risk of recurrence(11)Gene signature 

(Mammaprint) (11) 

TumorMicroarrayanalysis, 

quantitative RT‐PCR

Evaluation of risk of recurrence

Analysis of tumor markers for breast cancer detectionMarker Mutation in BRCA1 and 

BRCA2 genesGross cystic disease fluid protein 15 

GCDFP‐15ER (1)

Level Positive Increased ER‐negative status (2)

Type variant Qualitative Quantitative Semi‐quantitative or quantitative (based on method)

Target group Women in high‐risk families

Patients with active breast gross cystic disease

In patients with newly diagnosedbreast cancerfamilies disease  breast cancer

Associatedtumor markers

‐ ‐ In combination with established prognostic factors (ie, tumor stage, tumor grade, and number of lymph 

d )node metastases)

Other required method

‐ ‐ ‐

Reason of Identification of women Evaluation of risk of breast cancer Assessment of prognosisReason of measurement

Identification of women who are at high risk of 

developingbreast or ovarian cancer 

Evaluation of risk of breast cancer development

Assessment of prognosis

(1) ER alone is a relatively weak prognostic factor.(2) It is a significant prognostic factor for overall survival and disease-free survival.

Analysis of tumor markers for breast cancer detectionMarker ER & PR HER‐2 expression and/or 

gene amplificationHER‐2 expression and/or gene 

amplification

Level Patients with low ER levels respond to endocrine 

therapy

HER‐2 positive or HER‐2 negative (1)

overexpression of HER2 (3 +by protein or >2.0 FISH ratio by 

gene amplification) (2)

Type of variant Semi‐quantitative or quantitative (based on 

method)

Semi‐quantitative Semi‐quantitative

Target group All patients with breastcancer

All patients with invasivebreast cancer

Patients who want to benefit From anthracycline‐based yadjuvant chemotherapy

Associated tumor markers ‐ ‐ ‐

Other required method ‐ ‐ ‐

Reason of measurement Identification of patients with breast cancer that can be treated with hormone 

therapy

Selection of patients that may be treated

With trastuzumab (only HER‐2 positive patients)

Prediction of responseto specific chemotherapeutic 

agents

(1) HER-2 positivity was defined as IHC staining of 3+ (uniform and intense membrane staining of > 30% of invasive cancer cells), a FISH value > 6 HER-2 gene copies per nucleus, or a FISH ratio (HER-2/CEP 17) of > 2.2HER-2 negativity was defined as an IHC score of 0 or 1+, a FISH value of <4 HER-2 gene copies per nucleus, or a FISH ratio of < 1.8.(2) These patients have greater benefit from anthracycline based adjuvant therapy(2) These patients have greater benefit from anthracycline-based adjuvant therapy.

Analysis of tumor markers for breast cancer detectionCA15‐3 or BR27.29 or MUC‐1 uPA & PAI‐1GCDFP‐15Markerassays

Sustained increases in marker concentrations (4)

low levels of both uPA and PAI‐1(2)& high levels of either uPA or PAI‐1(3)

PositiveLevel

( )

QuantitativeQuantitativeQualitativeType of variant

patients with advanced   breast cancer especially in patients with non‐assessable disease

Patients with newlydiagnosed, lymph node‐negative breast cancer

Patients with ovarian metastasis

Target group

non assessable diseasenegative breast cancer

‐‐(It is a strong and  independent prognostic factor)

‐Associated tumor markers

Radiology, history and physical ‐‐Other required methodexamination

Monitoring chemotherapyIdentification of patients that do not need or are unlikely to benefit from adjuvant chemotherapy.

Differential diagnosis (1)

Reason of measurement

py

(1) Because a differential diagnosis between primary and metastatic tumors may be difficult in poorly differentiated ovarian neoplasms, breast carcinoma markers (Gross cystic disease fluid protein 15 GCDFP-15) is helpful in establishing the primary site of origin. (2) Lymph node–negative patients with low levels of both uPA and PAI-1 have a low risk of disease relapse and thus

b d f th t i d ff t d t f dj t h thmay be spared from the toxic adverse effects and costs of adjuvant chemotherapy.(3) Lymph node-negative women with high levels of either uPA or PAI-1 should be treated with adjuvant chemotherapy(4) It is indicative of progressive disease. Caution should be used when interpreting a risingCA27.29 or CA 15-3 level during the first 4 to 6 weeks of a new therapy, given that spurious early rises may occur.

Analysis of tumor markers for breast cancer detectionTPA & TPSTPA & TPS (3)CEA (1)Marker

DecreasedIncreasedSustained increases in marker concentrations  (2)

Level

QuantitativeQuantitativeQuantitativeType of variant

P ti t ith d dP ti t ith id fti t ith d d b tT t Patient with advanced disease

Patients with no evidence of disease

patients with advanced   breast cancer especially in patients with non‐

assessable disease

Target group

Maybe useful if CA 15‐3,   BR 27 29 CEA

‐‐Associated tumor markersBR 27. 29 or CEA are not 

elevated.

‐‐Radiology, history and physical examination

Other required method

Monitoring therapyPost‐operative surveillanceand risk of recurrence and 

staging

Monitoring chemotherapyReason of measurement

(1) As a marker for breast cancer CEA is generally less sensitive than CA 15 3/BR 27 29 but on occasion it can be(1) As a marker for breast cancer, CEA is generally less sensitive than CA 15-3/BR 27.29 but on occasion, it can be informative when levels of MUC-1-related markers remain below the cutoff point. It is reasonable to evaluate one of the MUC-1 assays and CEA initially in a patient with metastatic disease. If the MUC-1 assay is elevated, there appears to be no role for monitoring CEA, but if not, then CEA levels may provide supplementary information to the clinician in addition to clinical and radiographic investigations. (2) It is indicative of progressive disease. Caution should be used when interpreting a rising CEA level during the first 4(2) It is indicative of progressive disease. Caution should be used when interpreting a rising CEA level during the first 4 to 6 weeks of a new therapy, given that spurious early rises may occur. (3) In clinical uses in certain countries, but value not validated by a high-level evidence study.

Analysis of tumor markers for breast cancer detection

MammaPrint assay  (3)Oncotype DXMarker

?Low & high recurrence score (RS) (1Level

QuantitativeQuantitative (2)Type of variant

Lymph node–negative primary breast cancerLymph node–negative, ER‐positive patients receiving

adjuvant tamoxifen

Target group

Independent of other possible prognostic factors ‐ (RS is an independent predictor of patient Associated tumor  p p p g(age,

node status, tumor diameter, grade, vascular invasion, ER status, type of primary surgery, use of adjuvant chemotherapy, and/or hormone therapy) 

?

( p p poutcome)markers

‐‐Other required method

Evaluation of risk of recurrencePrediction of recurrence& outcomeReason of measurement

(1) A low RS predicts good outcome in patients treated with adjuvant tamoxifen (patients predicted to have a goodoutcome may be able to avoid having to undergo treatment with adjuvant chemotherapy), a high RS is found to be associated with favourable outcome in patients treated with either neoadjuvant or adjuvant chemotherapy (ie, patients with high recurrence score appear to derive greater benefit from chemotherapy than those with low scores).(2) This test uses RT-PCR to measure the expression 21 genes (16 cancer associated and five control genes). Based ( ) p g ( g )on the expression of these genes, a recurrence score (RS) was calculated that predicted low, intermediate and high riskof distant metastasis.(3) It is a gene expression profiling platform measured by quantitative RT-PCR. The precise clinical utility and appropriate application of the MammaPrint assay is under investigation.

Chasing molecular markers of breast cancer in different stages

BRC

A1&B

ER

-ne

Low E

Over-expre

High u

CA15-

High R

S

TPA &

TPAGC

GCBR

CA

2 mutatio

egative status

ER & PR

ession of HE

R2

uPA & PAI-1

-3 & CEA

oncotype DX

& TPS

A & TPS

CD

FP-15

DFP

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n positive

2

Pro

Dia

Tre

Re

Early

ognosis

Late

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ecurrence

Thank youThank you