“one size fits all”-does it? vidudala v.t.s. prasad, ph.d head research and development...

“One Size Fits All”-Does It?

Vidudala V.T.S. Prasad, Ph.DHead

Research and DevelopmentBasavatarakam Indo-American Cancer Hospital

and Research InstituteRoad No.14, Banjara HillsHyderabad-500034, India

Cell: 9618207495, e-mail: [email protected]

[email protected] Helpline: 9989524365

mailto:[email protected]

Our Group

• Dr. Guru Prasad • Dr. Ram Prasad • Padma • Satish• Satish Kumar • Ravi• Shiva Satish• Ph.D Students: Sarika, Srivani and Padma

• Dr. Saritha (Volunteer Researcher)

Research Oral Cancer (OC)

Low incidence and low Priority accorded by the developed Countries, as judged

by the publications.

3.5% (M+F) of publications as compared to over 10% of female BC

Why Oral Cancer?

In India, it is one of the most prevalent Cancers, especially in males

Coupled with the low priority status of the OC in Developed Countries, the onus to address OC is on us, but not on US and others.

Paucity of gender and site specific data, on global perspective

Polymorphims

Drug Metabolism

Ultra Responders/Poor Responders/Non-Responders

Functional Consequences of Polymorphisms

Complications

Poor/No Clinical Outcome

Adverse Drug

Reactions

Disease Susceptibility

/Resistance

Receptor Sensitivity

Drug Transport Polymorphisms

A case for setting up specific data bases (DBs)

Polymorphisms

GlucosylcerebrosidaseLipoxygenasesFAS and FASLTP53 CASPs, SULT1A1 CYP3A5 etc.,

Epigenetic aspects of gene regulatory aspects and

Expression Profiles

Cell Culture

Selective Cellular Death

Epigenetic Mechanisms

CP

CERAMIDESphinganineCerS

UV therapy4-HPR

PaclitaxelEtoposide

SDZ PSC833AnthracyclinesVincs alkaloids

Ceramide kinase

SP

Sphingosine

Sphingolyase

Glu/Gal-CerGCB

Sphingosine kinase

TamoxifenToremifene

MifepristoneCyclosporin AKetoconazole

VerapamilPPMP

NB-DNJ

UV radiationCD95

AnthracyclinesAra-CTNF-α

DT GM-CSF

Sphingomyelin

SMas

e

Fatty acid + Sphinganine

Ser + Palm CoA

CerS

De novo pathway Salvage pathway

SM sy

ntha

se

Ceramidases

CERT/GTsCSLs

Growth factorsCytokines

Lipid phosphatases

ELP & HXD

SP lyase

S/G-transferases

Pro-apoptotic

CERAMIDE Glu-Cer SM CP SP

Glucosylceramide synthaseSphingomyelin synthase

Ceramide kinase Sphingosine kinase/ Ceramidase

Anti-apoptotic Mitogenic Anti-apoptotic, Pro-proliferative

Ratio of sphingolipids decides cellular fate

Pro-sur vival

Glucosyl cerebrosidase

Sphingomyelinase

Cer -Phosphatase

SP lyase

Pro-sur vival

Arachidonic acid Lipoxygenases

Inflammation and Cancer In 1863, German physician Rudolf Virchow hypothesized that certain

classes of irritants, together with the tissue injury and inflammation, promote enhanced cell proliferation.

In 1918, Yamagiwa and Ichikawa, who showed that repeated painting of coal tar onto rabbits' ears causes carcinomas.

the world’s first man-made cancer on the ears of a rabbitRudolf Virchow

FAS and FASL promoter SNPs Gene Loci: FAS 10q24.1; FASL 1q23

The SNPs of the FAS -1377 G>A, block the binding of Sp1 transcription factor and

FAS -670 A>G SNPs, STAT1 transcriptional factor binding site,

leading to down regulation of the FAS gene expression (Huang et al., 1997 and Sibley et al., 2003).

The FASL -844 T>C SNP at the binding site for CAAT/enhancer binding protein. The CC variant was shown to upregulate FASL gene compared to the TT variant (Wu et al., 2003).

Various ethnic groups have been shown to harbor variants of the FAS and FASL. All cancers have genetic basis and genetic pre-disposition to cancer is well established (Robson and Offit 2007 and Tan 2009).

FAS-FASL and Apoptosisnduction of Cell Death: Trimerization of the Fas receptor by Fas ligand results in activation of caspase 8 (FLICE/MACH1), mediated by the adapter protein Fas-associated death domain (FADD)/mediator of receptor-induced toxicity (MORT1). Active caspase 8 is then responsible for activation of downstream caspases and cell death. DNA-damaging agents, such as doxorubicin, can result in increased Fas expression via a p53-dependent pathway and hence induce killing by the Fas/Fas ligand pathway, if the newly synthesized Fas engages Fas ligand. Other modes of cellular stress, such as removal of simple media supplements like mercaptoethanol, can also result in enhanced Fas expression.

Our Data Caucasians Chinese Askhenzi Jews

Hetero %

Homo %

Hetero %

Homo %

Hetero %

Homo %

Hetero %

Homo %

GBA VAL394LEU

3 0 0.3 0-- -- -- --

GBA ASP409HIS 3 0 0 0 -- -- -- --GBA

ASN370SER 0 0 0.5 00.7 0 4.3 0

GBA LEU444PRO 0 0 0 0

1.1 0 2.4 05 LOX -292C >

T17 0 5 0 -- -- -- --

12 LOX 835 A>G 32.5 0.5 45 14 51 25 -- --FAS -1377 G>A 24 9 17 0.4 47 11 -- --

P 53 215 G>C 39 24 42 10 -- -- -- --P 53 216 bp

delition 8 22 17 2 -- -- -- --Variations in Genotypes Among Different Ethnic Populations

Genetic Variants Affecting Drug Response

1A219%

2D63%

2E110%

3A4/542%

2C92C19 26%

1A25%

2D624%

2E11%

3A4/551%

2C92C1919%

Primary CYP 450 Enzymes in Drug Metabolism

% of total enzyme

% of drugs metabolized

Biotransformation of Tamoxifen,pro-drug to active drug

CYP 3A4/5 converts TAM to N-desmethyl tamoxifen, whereas the generation of 4-hydroxy tamoxifen and ENDOXIFEN are predominantly catalyzed by CYP2D6. CYP2C19, CYP2C9, and

CYP2B6 play less important roles in tamoxifen metabolism in vitro at therapeutically relevant concentrations. Jin, Y. et al. J Natl Cancer Inst 2005;97:30-39

Gene and Variant Caucasians African-Americans Asians

CYP2D6*3 2% 0 0

CYP2D6*4 12-21% 2% 1%

CYP2D6*5 2-7% 4% 6%

CYP2D6*10 1-2% 6% 51%

CYP2D6*17 0 34% 0%

CYP2D6*2xN 1-5% 2% 0-2%

CYP2C9*2 8-14% 1% 0%

CYP2C9*3 4-16% 1-2% 2-3%

CYP2C9*5 - 1.7% -

CYP2C9*6 - 0.6% -

CYP2C19*2 15% 17% 30%

CYP2C19*3 0.04% 0.40% 5%

The table below lists common drug metabolism gene variants and their frequencies in major ethnic groups.

Adapted from Blue Cross Blue Shield Special report

Germline mutations of BRCA1 and BRCA2

A very high frequency: 31.6 %; non-Jewish Americans of Spanish ancestry from the San Luis Valley, Colorado

(Mullineaux et al. 2003).

Moderate: 16.4% in India (Vaidhyanathan)

Low Frequency: 1.13–5.9%;white Americans, the Spanish from Spain, Polish, Iranian, Pakistani and Turkish women (Grzybowska et al.2002; Shih et al. 2002; Guran et al. 2005; Weitzel et al. 2005; Mehdipour et al. 2006; Rashid et al. 2006).

Absence of the 185delAG mutation: Chinese and Japanese families with breast cancer (Ikeda et al. 2001; Zhi et al. 2002).

Other Genetic Variations among different populations

• G6PD: Specific mutations are found in Indians and Africans.

• ALDH 1: Deficient activity in Orientals (Chinese& Japanese) results in high sensitivity to alcohol.

• Sickle cell anaemia: A mutation in sickle cell anaemia is not found across the globe but in specific geographical regions like Africa and Asia, mostly.

Asian Belly

Specific fat depots are influenced by ethnicity and gender

Kohli et al., 2009, Obesity Jr. DOI 10 1038/oby, 2010. 94; Liu et al., 2011, BMC Public Health, 11, 500

Cancer may occur in any part of the body

Dr. V. V. T. S Prasad, Ph.D, Chief, R&D, E mail :[email protected] , Cell: 09618207495

Increased risk of buccal mucosa cancer for females but not for males

FASL homozygous variant decreases risk of Female cancers while those of FAS variants alters the risk divergently

SULT1A heterozygous variant decreases Oral Cancer Risk but increase the Cancer Risk for females

The CYPA35*3 homozygous variant offers protection against breast cancer but not that of oral cancer

TP53 E-4 215G>C heterozygous variant increases Tongue Cancer risk in males but the homozygous variant increase risk of tongue and BM cancers in males. Intron 6 G>A het variant confers protection against tongue cancer in males

TP53 intron 3 homozygous variant lowers risk of both tongue and BM cancers in females

15-LOX promoter polymorphism (-292C>T) increases risk of the female cancers, though the degree of the risk varies for each of the cancers

12-LOX 835A>G heterozygous variant increases breast cancer but decreases risk of Cervical and Ovarian Cancers, whereas the homozygous variant increases risk for BC, Cx and OC cancers.

Rising Incidence of Breast cancer in India

www.breastcancerindia.net/statistics

Age shift: Breast cancer now is more common in 30’s and 40’s


Ceramide, Ceramide-1-Phosphate and LOXs* LOX mutation &

cancers

ROS Inflammation

Cell Death FAS/FASL, CASPases

*Cer and CP upregulate 12-LOX pathway and generate 12-HETE involved in cell proliferation, inflammation, VEGF) expression.

Ceramide elevates 12-hydroxyeicosatetraenoic acid levels and upregulates 12-lipoxygenase in rat primary hippocampal cell cultures containing predominantly astrocytes. Vidudala V.T.S. Prasad *, Kassem Nithipatikom, David R. Harder. Neurochemistry International 53 (2008) 220–229. CP manuscript is in review

Our Research, Mitochondria and Cancer

MembranePotential

Inhibits mt function

Personalized Medicine

“Here is my genomic sequence”

Sensitivity of cells even from same organ differs to anti-cancer agents

Annexin-V-FITC Propidium Iodide CAL-27 48hrs

Med

ium

con

trol

Tam

oxif

en

SCC9 48hrs

Annexin-V-FITC Propidium Iodide OverlayF

-1

A) B)Overlay

F

-1Ta

mox

ifen

P-1

Annexin-V-FITCM

ediu

m c

ontr

ol Overlay

MCF-7 48hrs

F-1

Tam

oxif

enMCF-10A 48hrs

Annexin-V-FITC Propidium Iodide P

-1C) D)

Propidium Iodide Overlay

Your Genes DictateYour Response

Genomics

“One Size Doesn’t Fit All”

CAL-27 Vs. SCC-9 apoptosis

0.00

1.00

2.00

3.00

4.00

5.00

6.00

F-1 25ul Curcumin100uM

Tam 50ul P-1 100ul

24H

48H

CAL-27 Vs. SCC-9 cell death

0.00

0.50

1.00

1.502.00

2.50

3.00

3.50


Tam 50ul P-1 100ul

24H

48H

MCF-7 Vs. MCF-10A apoptosis

0.00

0.50

1.00

1.50

2.00

2.50


Tam 50ul P-1 100ul

24H

48H

MCF-7 Vs. MCF-10A cell death

0.000.501.001.502.002.503.003.504.00


Tam 50ul P-1 100ul

24H

48H

Ratio of cell death

One-way Anova*p 0.05 **p0.005***p0.001

Fig. 3: Cytotoxic extract mediated cell death in breast cancer cell lines

0102030405060708090

100

Con

trol

FE

0.05

FE

0.1

FE

0.15

FE

0.2

Tam

0.2

PE

0.2

FE

0.1T

am0.

2

PE

0.2T

am0.

2

Treatment

% D

ead

cel

ls

MCF-7

MDAMB-435

ZR-75

**

*

*****

CYP2D6 Alleles in South Indians(% Allele frequency)

CYP2D6 Allele

TN Kerala Karnataka

AP South India

*3 0.0 0.0 0.0 0.0 0.0*4 6.1 7.5 4.8 10.8 7.3

*5 1.1 1.7 1.1 1.4 1.9

*10 12.9 7.0 11.2 9.0 10.2

Theophilus et al., Biol Pharm Bull, 29(8) 1655-1658, 2006

Note: Existence of CYP2D6 PM phenotype in south Indian population is also reported based on dextromethorphan and its metabolite levels in urine Abraham, B.K., et al., Acta Pharma Sin 21 (6) 494-4980

“Every individual is different from another and hence should be considered as a different entity. As many variations are there in the Universe, all are seen in Human being”

Charak Samhita

Most Drugs

Do Not Work Similarly in All Patients

The tiny difference in human genome translates into 3 million separate “spelling” differences in a genome of 3 billion bases, creates wide variety of phenotypesgh

Obvious enough!!!

Menacing !

Gotram

• Science of Genetics behind the Hindu Gotram System

• People within the gotra are regarded as kin Gotra is the lineage or clan assigned to a Hindu at birth

• The Gotra is a system which associates a person with his most ancient or root ancestor in an unbroken male lineage.

• to avoid cousin marriages which have been proved to increase the risk of genetic disorders in the off springs

The Jewish Rabbi as a DB

Concerns

• Privacy Issues• Ethical aspects• Integrity• Accuracy• Ownership• Genetic discrimination

The volume of information held in genetic research databases and quick access magnify these concerns.

India Needs G-P-L-M -Omics DBs more than any other countries

• Close Marriages– Caste– Distantly Related– Within family

– What we need is not only genetic DBs but also disease specific DBs----- Diabetes Mellitus, Cardiac Diseases and Cancer to start with

Late than Never

Let’s Develop Data Bases that Caters to the Needs of Diverse India

Let all Indians, “Have and Have Nots”, Reap the Benefits of

Biotechnological Advancements, alike.

Let us Light the Lamp of Knowledgeand Drive Away Ignorance

Sooner the BetterDhanyawad

Databases

• A ‘database’ is any methodical or systematic collection of data, structured that allows accessibility to individual or collective elements of that database .

• The human genetic research databases have been created primarily for the purposes of medical or other human research.

Variant India USA USA USA Brazil China Korea Spain

Gln/Gln (AA)

59.5 17 37 40.9 22.5 23.7 31.4 19

Gln/Arg (AG)

39.6 49.3 50.5 45.5 37.5 51 49.4 47

Arg/Arg (GG)

0.9 33.7 13.5 13.6 40 25.3 19.3 34

Gln/Arg (AG) +

Arg/Arg (GG)

40.5 83 64 59.1 77.5 76.3 68.7 81

Population / Gender

IndianFemal

e(100%)

PredominantlyCaucasians (88%),

Female (41% )

Caucasians

Female(52%)

Blacks(52%)

Brazilian

Female (69% )

ChineseFemale (37.2%)

KoreansFemale

(62.0% )

Spain Male

(100%)

Reference Our Study Gong et al., 2007 Goodman

et al., 2004

Goodman et al.,

2004

Fridman et al.,

2005

Tan et al.,

2007

Kim et al.,

2010

Quintana et al., 2006

Variations in the frequencies of the ALOX 12 polymorphism (A835G; Gln261Arg) in different populations (%)

Samples Parameter Frequency

AA

N

(%)

AG

N

(%)

GG

N

(%)

AG +GG

N

(%)

A allele

N

(%)

G Allele

N

(%)

Male, N =151 104

(68.9)

46

(30.4)

1

(0.7)

47

(40.1)

254

(84)

48

(16)

Female , N=166 94

(56.6)

69

(41.6)

3

(1.8)

72

(43.4)

257

(77)

76

(23)

p-value 0.03* 0.28 0.025* 0.50 0.02*

12-LOX polymorphism in control males and females

* Statistically significant (p<0.05); N = Number of samples

Three Billion Big

3 million ‘spelling’ variations, Just differ by 0.1%, 99.9 identical

ALOX1212-LOX ALOX12

Proliferation

12-LOX influences Cancer Related Processes

Adhesion

That tiny 0.1% difference in human genome translates into 3 million separate “spelling” differences in a genome of 3 billion bases, accounting for wide variety of phenotypes

Prevalence

Population Indian Ashkenazi Jews

Non-Jewish Americans of

SpanishAllele

Frequency 16.4% 18.0% 31.6%

Vaidyanathan et al., 2009 J. Biosci. 34(3)415–422

CYP450 genotypes: Patient classifications

1) Extensive metabolizers (EM) = 2 good copies

2) Intermediate metabolizers (IM) = 1 defective copy

3) Poor metabolizers (PM) = 2 defective copies

4) Ultra-rapid metabolizers (UM) = 3+ good copies

SULT1A1 Prevalence Populatio

n Turkish Caucasian African

American

Japanese

Chinese Korean

Allele Frequency

23.8% 36.5% 29.4% 16.0% 8.0% 12.4%

R&D Data (2010-Present )

Homozygous

Heterozygous Mutated

Normals 3.3% 21.7% 25.0%Breast cancer 6.7% 53.3% 60%Ovarian Cancer 13.3% 46.7% 60%

Arslan, 2010 Biochem genet 48:987-994

MTHFR Prevalence

Kumar et al., 2005 J Hum Genet 50:655-63

Population Indian Caucasian Chinese

Japanese

Frequency of

homozygous mutation

2.16 % 8.9% 16.9% 15.6%

R&D Data (2010-present )

Homozygous

Heterozygous Homo+Het

Normals 0.5% 6.0% 6.5%

Colorectal cancer 0% 13.8% 13.8%

Acute Lymphoblastic

Leukemia 1.5% 4.3% 5.8%

UGT1A1*28Mutation: Seven TA repeat sequence in the

promoter region

Locus: Chr 2q37

Impact of Mutation: Decrease enzyme production, leading to reduced glucuronidation (Iyer et al., 1998 and Iyer et al., 2002)

Drug Major Condition

Clinical Implication

Comment

Irinotecan Colorectal cancerDecreased UGT1A1 activity may increase the risk of toxicity

Genotyping is useful for dosage regimens >250 mg/m2.

Lee and McLeod, 2011 J Pathol; 223: 15–27

FDA advisory Committee’s Recommendation. Oct 18, 2006

Tamoxifen label should be updated to reflect the fact postmenopausal women with ER positive breast cancer who are CYP2D6 poor metabolizers with tamoxifen treatment (by genotype or drug interactions) are at increased risk for breast cancer recurrence.

The recommendation has not been withdrawn to the best of my knowledge

DPDMutation: *2A Exon-14-skipping

Gene location: Chromosome 1p22

Impact of Mutation: Nonfunctional enzyme

Drug Major Condition Clinical Implication

Comment

5-Fluorouracil

Colorectal, stomach,pancreaticcancer

DPD deficiency is associated withhigher risk of toxicity

Phenotypingmay be needed in some cases.

Lee and McLeod, 2011 J Pathol; 223: 15–27

Metabolic pathways of pyrimidines and dihydropyrimidine dehydrogenase (DPD)

Tanaka et al., 2005 Nagoya J. Med. Sci. 67. 117-124

DPD Prevalence

Population

Caucasian

African American

Finnish Dutch

Allele Frequency

3-5%(Jane et al.,

2007)

8%(Saif et al.,

2007)

2.2%(Eidens et al.,

2009)

1.2% (Eidens et al., 2009)

R&D data indicates the prevalence of the mutation in Indian population.

R&D Data (2010-Present )

Homozygous Heterozygous Mutated

0% 5.8% 5.8%

UGT1A1 PrevalencePopulatio

n African Europea

nAsian R&D Data

(2010-present )

Allele Frequency

43% 39% 16% Work in progress

Beutler et al., 1998 Proc Natl Acad Sci USA; 95:8170-74

Need for Data Bases pertinent to Diverse India

Age shift: Breast cancer now is more common in 30’s and 40’s


Rising Incidence of Breast cancer in India


“Every individual is different from another and hence should be considered as a different entity. As many variations are there in the Universe, all are seen in Human being”

Charak Samhita

Other Genetic Variations among different populations

• G6PD: Specific mutations are found in Indians and Africans.

• ALDH 1: Deficient activity in Orientals (Chinese& Japanese) results in high sensitivity to alcohol.

• Sickle cell anaemia: A mutation in sickle cell anaemia is not found across the globe but in specific geographical regions like Africa and Asia, mostly.

Many Races, Many Faces with Varied

features

Yet, human DNA sequence is 99.9% identical, differs by just 0.1% but

still -----

Variant India USA USA USA Brazil China Korea SpainGln/Gln

(AA)59.5 17 37 40.9 22.5 23.7 31.4 19

Gln/Arg (AG)

39.6 49.3 50.5 45.5 37.5 51 49.4 47

Arg/Arg (GG)

0.9 33.7 13.5 13.6 40 25.3 19.3 34

Gln/Arg (AG) +

Arg/Arg (GG)

40.5 83 64 59.1 77.5 76.3 68.7 81

Population / Gender

IndianFemale(100%)

Predominantly Caucasians

(88%),Female (41% )

CaucasianFemale(52%)

Blacks(52%)

BrazilFemale (69% )

ChineseFemale (37.2%)

KoreansFemale (62.0%

)

Spain Male

Reference Present Study

Gong et al., 2007

Goodman et al., 2004

Goodman et al., 2004

Fridman et al., 2003

Tan et al., 2007

Kim et al.,

2010

Quintana et al., 2006

Table 2: Variations in the frequencies of the ALOX 12 polymorphism (A835G; Gln261Arg) in different populations

HGP: The most ambitious project in biological science was envisaged to spell out the human

genome in toto.

In other words, the project was meant to sequence the complete human genome of 3 billion bases

What does it mean!


features

Yet, human DNA sequence is 99.9% identical, differs by just 0.1%

http://nihroadmap.nih.gov/epigenomics/epigeneticmechanisms.asp

-- Sun Kim group at IU -- 86

Your Genes DictateYour Response

“One Size Doesn’t Fit All”

The Human Genome Program of the US DOE

• Human Genome Project started as US component 1990 US$3billion 15-year effort to find the estimated 80,000 human genes and determine the sequence of the 3-billion DNA building blocks that underlie all life's diversity.

• A new goal focuses on identifying regions of the human genome that differ from person to person. Our DNA sequences are estimated to be 99.9% identical genetically - these DNA sequence variations can have a major impact on how our bodies respond to disease; environmental insults, such as bacteria, viruses, and toxins; and drugs and other therapies.

• http://www.er.doe.gov/production/ober/HELSRD_top.html

What does it mean!


features


That tiny 0.1% difference in human genome translates into 3 million separate “spelling” differences in a genome of 3 billion bases, accounting for wide variety of phenotypes

Does it matter in practicing medicine?

What does it mean!


features


Pharmacogenomics

Personalized Medicine

Right Drug(s) @ Right Dose, and no ADRs

Meta

bolic

pathways

Identification of

polymorphisms

“Best Fit”

However, 0.1% difference in human genome translates into 3 million separate “spelling” differences in a genome of 3 billion bases,

accounting for wide variety of phenotypes

What these variations in DNA Sequence can do?

May results in a different phenotype

May impact expression of mRNA/protein

May serve as an unique molecular marker for a given

pathological condition

Genome: All the genetic material in the chromosomes of a particular organism; its size is generally given as its total number of base pairs.

Genomics: the study of genes and their function. Recent advances in genomics are bringing about a revolution in our understanding of the molecular mechanisms of disease, including the complex interplay of genetic and environmental factors. Genomics is also stimulating the discovery of breakthrough healthcare products by revealing thousands of new biological targets for the development of drugs, and by giving scientists innovative ways to design new drugs, vaccines and DNA diagnostics. Genomics-based therapeutics include "traditional" small chemical drugs, protein drugs, and potentially gene therapy.

Much before the advent of human genome Project ---- our Ancient Wisdom

proclaimed that;

“Every individual is different from another and hence should be

considered as a different entity. As many variations are there in the

Universe, all are seen in Human being”

Charak Samhita

How these variations are identified and put to use in practicing medicine!

Association of 12-LOX polymorphism with colorectal cancer.

Subjects (Gender and

Sample Size)

Frequency

AA

N (%)

AG

N (%)

GG

N (%)

AG + GG

N (%)

A allele

N (%)

G Allele

N (%)

Control (M+F, N=317)

Colorectal Cancer

(M+F, N=104) p-

value

OR

CI (at 95%)

198 (62.5) 115 (36.3) 4 (1.3) 119(37.5) 511(81) 123(19)

38 (36.5) 64 (61.5)* 2 (2.0) 66(64)* 140(65)* 68(35)*

0.0001 0.262 0.0001 0.0001 0.0001

2. 9 2.61 2.9 6.3 2.9

1.8-4.6 0.46-14.7 1.83-4.6 4.1-9.7 1.8-4.6

Control (F, N = 166)

Colorectal Cancer

(F, N= 45) p-value

OR

CI (at 95%)

94 (56.6) 69 (41.6) 3 (1.8) 72 (43) 257(77) 75(23)

21 (46.6) 23 (51.1) 1 (2.3) 24(53) 65(72) 25(28)

0.24 0.73 0.234 0.66 0.23

1.5 1.5 1.5 1.1 1.5

0.77-2.92 0.15-15.1 0.77-2.9 0.66-2.0 0.35-2.9

Control (M, N=151) 104 (68.9) 46 (30.4) 1 (0.7) 47 (31) 254(84) 48(16)

Colorectal Cancer,

(M, N=59) p-value

OR

CI (at 95%)

17(28.8) 41(69.5)* 1(1.6) 42(71)* 75(64)* 43(36)*

0.0001 0.154 0.0001 0.041 0.0001

5.5 6.2 5.5 1.8 5.5

2.9-10.6 0.37-102 2.8-10.6 1.0-3.2 2.8-10.6

* Statistically significant (p<0.05).

“one size fits all”-does it? vidudala v.t.s. prasad, ph.d head research and development...

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