predictive biomarkers for lung cancer current status / perspectives: although curative resection of...
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Predictive Biomarkers for Lung Cancer
Current Status / Perspectives: Although curative resection of patients withearly-stage lung CA are performed, the riskof relapse remains substantial
Indicates that there may be micro-invasion/metastasis have not been detected by general imaging and/orpathological examinations
Predictive biomarkers will allow the selection of lung cancer patients who may need moreaggressive screening and treatment
Predictive biomarkers will allow the selection of lung cancer patients who may need moreaggressive screening and treatment
Predictive Biomarkers for Lung Cancer
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
Predictive Biomarkers for Lung Cancer
Hurdles:
There are no biomarkers universally recommended to help in the clinical management of lung cancer today.
Probable valid biomarkers Candidate biomarkers General trends
Poor study design / analysis Assay variability Lack of standardization protocols
Predictive Biomarkers for Lung Cancer
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
Predictive Biomarkers for Lung Cancer
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
Predictive or diagnostic modelling
• 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
Overview of Genomic Approach
DNA / RNA microarray
MicroRNA microarray
Single nucleotide polymorphism (SNPs)
Epigenetic (e.g. methylation) profiling
Metagene Analysis in NSCLA
Potti et al,NEJM, 2006
Metagene Analysis in NSCLA
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
Unique Micro RNA Profile in LungCancer 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
Unique Micro RNA Profile in LungCancer Diagnosis and Prognosis
• 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
• 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
• Lung adenocarcinoma patients with either high has-mir-155 or reduced has-let-7a-2 expression had poor survival
Overview of Proteomic Approach
(Mass/Charge)
3000 5500 8000 10500 13000
Rel
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e In
tens
ity
NL
LC
Spectra from human normal lung and NSCLC tissues
* *
**
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Cluster analysis between Tumor and Normal lung (82 signals)
0 10 20 30 40
50
Poor Prognosis Group
P < 0.0001
Good Prognosis Group1.0
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0
Kaplan-Meier survival curves based on 15 MS peaks
Time in Months
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rviv
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Grand Serology: Pedigreed database
NY-ESO-1:Survival proportions
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NY-ESO-1 posNY-ESO-1 neg
P value P value summary Are the survival curves sig different?
0.0049**Yes
OS
p53:Survival proportions
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P value P value summary Are the survival curves sig different?
0.8334nsNo
OS
Clinical Correlations in NSCLC (interim data)
NY-ESO-1:Survival proportions
0 1000 2000 3000 400065.067.570.072.575.077.580.082.585.087.590.092.595.097.5
100.0102.5105.0
NY-ESO-1 posNY-ESO-1 neg
P value P value summary Are the survival curves sig different?
0.8060nsNo
OS
p53:Survival proportions
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P value P value summary Are the survival curves sig different?
0.0005***Yes
OS
Clinical Correlations in Esophageal Cancer (interim data)
Cellular Biomarkers
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)
Pro-angiogeic
Bone marrow
Endothelial progenitorshematopoietic
stem/progenitor cells
Pro-angiogeic
Bone marrow
Endothelial progenitorshematopoietic
stem/progenitor cells
InflammationTumor, Ischemia
Regenerating TissueHypoxia
Wound Healing
CXCR4+VEGFR1+ CD133+VEGFR2+
Neo-angiogenic Niche
Chemokine(SDF-1)
Mobilization
Recruitment
Differentiation
Incorporation
Assembly
Niche Migration(endosteal vascular)
Hypothesis
“NSCLC is associated with an elevated hemangiogenic profile, therefore, surgical removal of primary tumor may normalize
this dysregulation in hemangiogenesis”
Plasma
Functional angiogenic activity (HUVEC-based angiogenic scale)
ELISA
Flowcytometry CEP (CD133+VEGFR2+)
Cells
LysateHematopoietic colony-
forming assay
VEGF, SDF-1
Figure 5. Schema
Plasma
Functional angiogenic activity (HUVEC-based angiogenic scale)
ELISA
Flowcytometry CEP (CD133+VEGFR2+)
Cells
LysateHematopoietic colony-
forming assay
VEGF, SDF-1
Figure 5. Schema
Assessment of Hemangiogenic Biomarkers in NSCLC
Schema:
EPCs
Angiogenic Activity
0: Well separated HUVECs1: Cells begin to migrate and align 2: Visible capillary tubes; no sprouting3: Sprouting of new capillary tubes 4: Polygonal structures begin to form5: Presence of complex mesh-like structures
HUVEC-Based Functional Angiogenic Scale
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Functional Angiogenic Scale
Pre-op baseline2 weeks post -op
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Figure 4
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Figure 6Pre-op baseline2 weeks post -op
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Figure 4
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Figure 6Pre-op baseline2 weeks post -op
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Figure 6Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
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Figure 4
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Figure 6Pre-op baseline2 weeks post -op
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Figure 4
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Figure 6Pre-op baseline2 weeks post -op
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Figure 6Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
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Circulating CD133+VEGFR2+ EndothelialProgenitor Cells
Pre-op baseline2 weeks post -op
C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Functional
Angiogenic
Scale
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Figure 4
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Circulating CD133+VEFR2+ EPCs
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Figure 5 Pre-op baseline2 weeks post -op
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Circulating
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Figure 6Pre-op baseline2 weeks post -op
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Figure 4
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Circulating CD133+VEFR2+ EPCs
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Figure 5 Pre-op baseline2 weeks post -op
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Circulating
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Figure 6Pre-op baseline2 weeks post -op
p<0.05*
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Circulating
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(per ml peripheral blood)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 251 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Circulating
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Figure 6Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
p<0.05*
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Pre-op baseline2 weeks post -op
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Figure 4
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Circulating CD133+VEFR2+ EPCs
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Figure 5 Pre-op baseline2 weeks post -op
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Circulating
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Figure 6Pre-op baseline2 weeks post -op
p<0.05*
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Figure 4
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Circulating CD133+VEFR2+ EPCs
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Figure 5 Pre-op baseline2 weeks post -op
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Circulating
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Figure 6Pre-op baseline2 weeks post -op
p<0.05*
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Circulating
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(per ml peripheral blood)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 251 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Circulating
HPCs
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Figure 6Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
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Plasma SDF-1 Levels
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Figure 7Pre-op baseline2 weeks post -op
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Predictive Modelling
Permit risk stratification.Customize treatment
Less extensive surgery
Rational drug selection
Monitoring response to therapy.
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Figure 5 Pre-op baseline2 weeks post -op
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Figure 5 Pre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -op
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Figure 8Pre-op baseline2 weeks post -opPre-op baseline2 weeks post -op
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Intraplatelet VEGF-A Levels
.
Cancer-Testis Genes are expressed and are markers of poor outcome in pulmonary
adenocarcinoma
Ali O. Gure,CCR 2005