A novel use of biomarkers in the modeling of cancer activity based on the theory of Endobiogeny v1.5

Laura Buehning MD, MPH, Kamyar M. Hedayat, MD, Aarti Sachdevi, Shah Golshan PhD, Jean Claude Lapraz, MD

Presentation by: Kamyar M. Hedayat, MD President, American Society of Endobiogenic Medicine and Integrative Physiology

“Research is to see what everybody else has seen and to think what nobody else has thought.” — Albert Szent-György

(C) 2014 Systems Biology Research Group 1


scanning electron microscope, shows T cells (orange) attached to a tumor cell. http://www.mskcc.org/blog/cancer-immunotherapy-named-science-magazine-breakthrough-year


IF…

Cancer = Abnormal cellular activity

Chemotherapy, Radiation, Surgery = CURE of ALL cancers, EVERY TIME.



!  Short-term survival is improving BUT ! We see more ◦ New onset, late stage cancer IN… ◦ Younger populations WITH… ◦  Increasing relapses and metastasis

Formula from: Hanin, L and Zaider, M. Effects of surgery and chemotherapy on metastatic progression of prostate cancer: Evidence from the natural history of the disease reconstructed through mathematical modeling. Cancers 2011(3):3632-3660


Imaging: Structural Imaging: Functional

PET-CT: Left internal jugular node metastases with extranodal invasion; Akira Kouchiyama, http://commons.wikimedia.org/wiki/File:PET-CT_scanning_of_lymph_node_metastases_in_cancer.jpg

Breast Cancer, Mammography

Astrocytoma, Rt Frontal Lobe, MRI Breast Cancer,: University Medical Imaging Group


Histology

Infiltrating ductal carcinoma of breast

Hematologic, Gross

Circulating tumor cells: A-C: Prostate cancer, D: Metastatic lung cancer; PNAS v.107 (43), 2010

Oncobiologic

Survivn protein and apoptosis regulation

Telomerase and immortality


! Unifactorial—Cancer multifactorial ! Lacks global vision of physiology ! Reactive modality ! Lacks predictive assessment ! Downstream: Does not determine

causative factors


Hematologic: cell-free DNA

DNA Methylation patterns

MicroRNA: Microarray, PCR


http://rams.biop.lsa.umich.edu/research/metabolomics


! Advantages: ◦ Reinforce concept of cancer as complex and

multi-factorial ◦ Nuanced, sensitive and specific ◦  Individualized

!  Shortcoming ◦  STILL Reductionist: views cancer at the level

of the cell


! Evaluate cancer as Systemic disease expressed in cells

! Use GLOBAL systems approach



!  Quantitative !  Function of the parts !  Hierarchy !  Categorical !  Separate !  Independent !  Static !  Control

!  Qualitative !  Function of the

System !  Relationships !  Individualized !  Interconnected !  Interdependence !  Dynamic !  Creative chaos


Reductionism Holism



Creation of Structure Maintenance of STRUCTURE

Functional adaptation

! Endocrine system !  Sole system to possess:

1) Ubiquity of interaction with each structural element

2) Constancy of regulation of those elements 3) Constancy of regulation of itself


!  The illness ◦  Exogenous factors ◦  Rate of development ◦  Degree Invasiveness

!  The patient ◦  Endogenous factors ◦  Adaptation capability of terrain ◦  Evolution of terrain over time

!  Illness + Patient ◦  Degree of coexistence ◦  Levels of adaptation activities in structure vs. function ◦  Dominance of one over the other


(C) 2014 Systems Biology Research Group

METABOLISM

CATABOLISM ANABOLISM ANABOLISM CATABOLISM

CRH

ACTH

ADRENALS

LHRH

FSH LH

GONADS

TRH

TSH

THYROID

GHRH

GH PL

PANCREAS πΣ

αΣ

βΣ

Corticotropic Gonadotropic Thyrotropic Somatotropic

ANS

ENDOCRINE MANAGEMENT

20


The purpose of the Biology of Functions is to quantify the functional abilities of the organism, before and after the effects of adaptation. Because it is in permanent movement, functionality can only be measured by a dynamic, integrated and evolutionary methodology.

--C. Duraffourd and JC Lapraz


ADVANTAGES !  Objective !  Quantitative !  Accurate !  Reproducible !  Minimally invasive

DISADVANTAGES !  Binary !  Reductionist !  Confusion of ◦  Cause vs. Effect ◦  Cause vs. Effect vs.

Mechanism



Origin Biomarker

Bone Marrow

Red blood cell White blood cell, total Neutrophil Lymphocytes Eosinophils Monocytes Basophils Hemoglobin Platelets

Marrow-Blood interaction Erythrocyte sedimentation rate

Bone Stroma Enzymes Osteocalcin Alkaline phosphatase bone isoenzyme

General Enzymes Lactate dehydrogenase Creatine phosphokinase

Endocrine: Pituitary Thyroid stimulating hormone

Electrolytes Potassium Calcium, total serum

70% bone and blood

30% other


DIRECT relationship of biomarkers !  Genital Ratio (GR) ◦  RBC/WBC

!  Genito-Thyroid ◦  % Neutrophils / % Lymphocytes

INDIRECT Relationship of Biomarkers ± Direct indexes ± Indirect indexes !  Catabolism/Anabolism ratio

= Genito-Thyroid / Genital ratio corrected



! Retrospective Case Control Design ◦  92 patients in a single practice ◦ All types of cancers (hematologic and non-

hematologic) ◦ Age and sex-matched controls ◦ Three arm study "  Active Cancer (n=33) "  Cancer remission (n=13) "  Control group (n=46)


! Biology of Functions were available for all 92 patients

! 62 of 150 indexes were selected for relevance to oncobiology

! Paired Wilcoxin Rank Sum ◦ Active Cancer vs. Control ◦ Remission vs. Control

!  Independent Wilcoxin Rank Sum ◦ Active Cancer vs. Remission


Table 1. Baseline Characteristics of Cancer Cases and Matched Controls

N MALES FEMALES AVE AGE STD MIN

AGE MAX AGE

P-VALUE

Cancer Cases 46 19 27 54.15 13.48 9 78

0.705 Control 46 19 27 54.75 13.38 10 84


CANCER DIAGNOSIS MALE FEMALE ACTIVE INACTIVE

Abdominal Sarcoma 1 1 Acute Lymphocytic Leukemia 1 1 B Cell Lymphoma 1 1 Bladder and Ureter Carcinoma 1 1 Breast Carcinoma 13 8 5 Cervical Carcinoma 1 1 Chronic NonHodgkin’s Lymphoma

1 1

Chronic Lymphocytic Leukemia 1 1 2 Colon Carcinoma 5 4 1 Hepatocellular Carcinoma 2 2 Liposarcoma 2 2 Lung Carcinoma 1 1 Melanoma 1 1 Myelodysplastic Syndrome 1 1 Ovarian Carcinoma 1 1 Parathyroid Carcinoma 1 1 Prostate Carcinoma 6 2 4 Renal Cell Carcinoma 1 1 Stomach Carcinoma 1 1 Testicular Carcinoma 1 1 Thalamic Glioblastoma 1 1 Uterine Carcinoma 1 1 TOTAL = 46 19 27 33 13


Adaptation: βMSH/αMSH Index (6-8): It expresses the

relative level of participation of the beta- and alpha-melanocyte stimulating hormones (MSH) in directly stimulating cortisol activity vs. the general adaptation syndrome at the level of the pituitary.

Immunity: !  Proinflammatory index (0.1-0.4): The pro-

inflammatory index looks at the endogenous potential for inflammation due to thyrotropic over-activity and the degree to which cortisol is able to compensate for this


Anabolic Hormones: !  Estrogen fraction #5 (7-20): It expresses the

relative part of estrogens consecrated to the growth of tissues and organs.

!  Comparative Genital Androgeny index (0.1-0.3): It indicates the metabolic activity of androgen receptors at the tissue level and the anabolism of tissue.

Catabolic hormones: !  Thyroid Index (3.5-5.5): It indicates the degree

of efficiency of thyroid hormones in managing the metabolic energetic activity of the cell


Anabolic-Catabolic endocrine harmony: ! Genito-Thyroid Index (1.5-2.5) (=PMN/

Lymphocytes): It expresses the relative activity of the gonads in relationship to that of the thyroid.

Metabolism: ! Catabolism/Anabolism Index (1.8-3): It

expresses the relative catabolic activity in relation to that of anabolic activity within the scheme of global metabolism of the organism


INDEX N TOTAL CASES

MEAN±STD

TOTAL CONTROLS MEAN±STD

PVAL

Estrogen Fraction #5 45 18.64±16.87 10.58±5.30 0.004*

Genito-Thyroid Index 45 3.46±2.68 2.25±0.85 0.005*

Comparative Genital Androgeny 36 2.27±3.81 7.12±11.6 0.007*

Thyroid Index 39 5.17±3.64 3.72±1.73 0.039*

Beta MSH/Alpha MSH Index 39 5.64±3.86 4.11±1.98 0.042*

Catabolism/Anabolism Index 45 6.11±9.95 2.997±1.57 0.050*

Proinflammatory Index 42 1.64±2.80 0.73±0.70 0.056


INDEX N ACTIVE MEAN±STD

CONTROLS MEAN±STD PVAL


Genito-Thyroid Index 32 3.70±3.05 2.32±0.80 0.067

Comparative Genital Androgeny 26 2.75±4.37 8.03±13.3 0.06

Thyroid Index 27 5.90±4.06 3.64±1.98 0.009*

Beta MSH/Alpha MSH Index 27 6.45±4.30 4.00±2.25 0.012*

Catabolism/Anabolism Index 29 6.82±12.11 3.09±1.70 0.198



INDEX N ACTIVE MEAN±STD

CONTROLS MEAN

±STD PVAL

ACTIVE VS

INACTIVE

Estrogen Fraction #5 13 11.68±4.73 9.77±3.96 0.310 0.437

Genito-Thyroid Index 13 2.86±1.32 2.07±0.97 0.006* 0.622 Comparative Genital Androgeny 10 1.03±1.05 4.74±4.21 0.028* 0.568

Thyroid Index 12 3.51±1.58 3.89±0.99 0.433 0.006 Beta MSH/Alpha MSH Index 12 3.83±1.59 4.38±1.20 0.433 0.003

Catabolism/Anabolism Index 14 3.47±1.77 2.85±1.74 0.363 0.910

Proinflammatory Index 13 1.04±1.25 0.74±1.01 0.019* 0.990


INDEX N TOTAL CASES MEAN±STD


PVAL


Genito-Thyroid Index 13 3.56±1.98 2.35±0.81 0.25

Comparative Genital Androgeny 13 2.14±2.95 6.38±12.61 0.24

Thyroid Index 13 5.45±5.66 4.50±2.05 0.64

Beta MSH/Alpha MSH Index 13 5.99±5.97 5.02±2.35 0.70




INDEX N TOTAL CASES MEAN±STD


PVAL

Estrogen Fraction #5 5 20.60±21.18 7.20±1.48 0.23

Genito-Thyroid Index 5 3.51±1.45 2.03±0.64 0.14 Comparative Genital Androgeny 4 2.61±4.28 14.50±21.79 0.07

Thyroid Index 5 6.08±5.23 2.42±1.21 0.23

Beta MSH/Alpha MSH Index 5 6.51±5.18 2.66±1.42 0.23




! Genito-Thyroid index = Neutrophil to Lymphocyte ratio

! Over 400 studies in cancer patients, predictive of mortality

! Also studied in Chronic Heart Failure, Diabetes mellitus, etc.

! Considered a general, non-specific marker of inflammation



!  Genito-Thyroid, as the Neutrophil/Lymphocyte ratio is incorporated into a series of indices that have relevance to numerous disorders, including cancer


Neutrophil to Lymphocyte Ratio = Genito-Thyroid index

Catabolism/Anabolism Index

Cortisol index

Adrenal Cortex Index

Metabolic yield

Somatostatin index

Histamine index

Ischemia Index

!  Theory of Endobiogeny offers a whole-system approach to cancer

!  In a retrospective, case-controlled study of all cancer types, Biology of functions distinguishes cancer patients from controls

!  Future studies should look at homogenous cancer patients vs. controls to better characterize specific cancer types, and sub-groups of responders and non-responders to chemotherapy


Health & Medicine

A novel use of biomarkers in the modeling of cancer activity based on the theory of Endobiogeny v1.5