Predictive biomarkers will allow the selection of lung cancer patients who may need more
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Predictive biomarkers will allow the selection of lung cancer patients who may need more aggressive screening and treatment. Predictive Biomarkers for Lung Cancer . Current Status / Perspectives: . Although curative resection of patients with early-stage lung CA are performed, the risk

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Predictive biomarkers will allow the selection of lung cancer patients who may need more

aggressive screening and treatment

Predictive Biomarkers for Lung Cancer

Current Status / Perspectives:

Although curative resection of patients with

early-stage lung CA are performed, the risk

of relapse remains substantial

Indicates that there may be micro-invasion/metastasis have not been

detected by general imaging and/or

pathological examinations


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Predictive Biomarkers for Lung Cancer cancer patients who may need more

Intended Goals:

  • Defining categories or tumor subsets that may

    improve the diagnostic classification of lung

    tumors

  • Identifying specific genes, proteins, or accessory

    cells that could serve as targets for improved

    diagnosis and/or therapy

  • Associating biomarkers with clinical outcomes


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  • Poor study design / analysis

  • Assay variability

  • Lack of standardization protocols

Predictive Biomarkers for Lung Cancer

Hurdles:

There are no biomarkers universally recommended to help in the clinical management of lung cancer today.


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Predictive Biomarkers for Lung Cancer cancer patients who may need more

Challenges:

  • Single biomarker approach has not been proven to

    have strong predictive potential in lung cancer

  • Use of molecular and nano-IVD technologies bring

    a key promise for identification of clinically

    meaningful biomarkers

  • Clinical validation of candidate biomarkers

    remains a major challenge


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Predictive Biomarkers for Lung Cancer cancer patients who may need more

Challenges:

  • Use of biomarkers for early detection of

    lung cancer is promising but still methodologically

    challenging

  • Clinical management of lung cancer will most

    probably first benefit from use of biomarkers

  • Development of new therapeutic options for lung

    cancer will stimulate identification and clinical

    validation of new biomarkers


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Predictive or diagnostic modelling cancer patients who may need more

  • Tissue based.

  • Serum or urinary based

  • Cellular based

Use of one or more biomarkers to determine prognosis

or response to treatment beyond usual clinical criteria


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Overview of Genomic Approach cancer patients who may need more

  • DNA / RNA microarray

  • MicroRNA microarray

  • Single nucleotide polymorphism (SNPs)

  • Epigenetic (e.g. methylation) profiling


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Metagene Analysis in NSCLA cancer patients who may need more

Potti et al,

NEJM, 2006


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Metagene Analysis in NSCLA cancer patients who may need more

Application of the lung metagene model to refine the assessment of risk and guide the use of adjuvant chemotherapy in Stage 1A NSCLC

Potti et al,

NEJM, 2006


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Unique Micro RNA Profile in Lung cancer patients who may need more

Cancer Diagnosis and Prognosis

  • miRNAs are small non-coding RNAs which

  • play key roles in regulating the translation

  • and degradation of mRNAs

  • Genetic and epigenetic alteration may

  • affect miRNA expression, thereby

  • leading to aberrant target gene(s)

  • expression in cancers

  • Yanaihara et al, Cancer Cell, 2006:

  • - miRNA profiles of 104 pairs of primary

  • lung cancers and corresponding non-

  • cancerous lung tissues were analyzed by

  • miRNA microarrays

  • - 43 miRNAs showed statistical differences


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Unique Micro RNA Profile in Lung cancer patients who may need more

Cancer Diagnosis and Prognosis

  • Yanaihara et al, Cancer Cell, 2006:

  • - miRNA profiles of 104 pairs of primary

  • lung cancers and corresponding non-

  • cancerous lung tissues were analyzed by

  • miRNA microarrays

  • - 43 miRNAs showed statistical differences

  • A univariate Cox proportional hazard

  • regression model with a global permutation

  • test indicated that expression of the miRNAs

  • has-mir-155 and has-let-7a-2 was related to

  • adenocarcinoma patient outcome

  • Lung adenocarcinoma patients with

  • either high has-mir-155 or reduced

  • has-let-7a-2 expression had poor survival


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Overview of Proteomic Approach cancer patients who may need more


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Spectra from human normal lung and NSCLC tissues cancer patients who may need more

NL

Relative Intensity

LC

*

*

*

*

*

8000

10500

13000

3000

5500

(Mass/Charge)


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Cluster analysis between Tumor and Normal lung cancer patients who may need more

(82 signals)


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Kaplan-Meier survival curves based on 15 MS peaks cancer patients who may need more

1.0

Good Prognosis Group

Poor Prognosis Group

0.8

0.6

Survival

0.4

P < 0.0001

0.2

50

0

Time in Months

0

10

20

30

40


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Grand Serology: Pedigreed database cancer patients who may need more


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Clinical Correlations in NSCLC (interim data) cancer patients who may need more

Clinical Correlations in Esophageal Cancer (interim data)


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Cellular Biomarkers cancer patients who may need more

  • Circulating cancer cells (EpCAM+ cells)

  • Endothelial progenitor cells (CD133+VEGFR2+ cells)

  • Hemangiocytes (CXCR4+VEGFR1+ myelomonocytic

    precursor cells; pro-angiogenic; pre-metastatic niche)

  • Stromal cells (pericytes, myofibroblasts)


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Assembly cancer patients who may need more

Incorporation

Recruitment

Differentiation

Chemokine

(SDF-1)

Mobilization

Niche Migration

(endosteal  vascular)

CXCR4+VEGFR1+

CD133+VEGFR2+

Neo-angiogenic Niche

Inflammation

Tumor, Ischemia

Regenerating Tissue

Hypoxia

Wound Healing

Bone marrow

Bone marrow

Pro

Pro

-

-

angiogeic

angiogeic

Endothelial

Endothelial

hematopoietic

hematopoietic

progenitors

progenitors

stem/progenitor cells

stem/progenitor cells


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Hypothesis cancer patients who may need more

“NSCLC is associated with an elevated

hemangiogenic profile, therefore, surgical

removal of primary tumor may normalize

this dysregulation in hemangiogenesis”


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Assessment of Hemangiogenic Biomarkers in NSCLC cancer patients who may need more

Schema:

EPCs


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Angiogenic Activity cancer patients who may need more

HUVEC-Based Functional Angiogenic Scale

5

4

3

2

1

0

0: Well separated HUVECs

1: Cells begin to migrate and align

2: Visible capillary tubes; no sprouting

3: Sprouting of new capillary tubes

4: Polygonal structures begin to form

5: Presence of complex mesh-like structures


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Functional Angiogenic Scale cancer patients who may need more


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Circulating CD133 cancer patients who may need more+VEGFR2+Endothelial

Progenitor Cells


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Plasma SDF-1 Levels cancer patients who may need more


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Predictive Modelling cancer patients who may need more

  • Permit risk stratification.

  • Customize treatment

    Less extensive surgery

    Rational drug selection

    Monitoring response to therapy.


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Circulating Hematopoietic Progenitor Cells cancer patients who may need more


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Intraplatelet VEGF-A Levels cancer patients who may need more


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. cancer patients who may need more

Cancer-Testis Genes are expressed and are markers of poor outcome in pulmonary adenocarcinoma

Ali O. Gure,CCR 2005


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