This document discusses genomic oncology and personalized medicine, using lung cancers as a model. It summarizes several key technologies that enable genomic oncology like cDNA microarrays, array CGH, and next generation sequencing. It provides examples of how these technologies have been used to classify cancers like diffuse large B-cell lymphoma and myelodysplastic syndrome, and identify genetic mutations that can guide targeted therapies for cancers like EGFR-mutated lung cancer.
1. Genomic Oncology and Personalized
Medicine
-Using lung cancers as a model
Chung-Che (Jeff) Chang, M.D., Ph.D.
Director, Hematology and Molecular Pathology Lab.
Florida Hospital
Professor of Pathology
College of Medicine
University of Central Florida
E-mail: c.jeff.chang.md@flhosp.org
Phone: 407-303-1879
2. Image courtesy of Nature,
issue: Feb. 15, 2001
Thirty Years
to create a
“Strategic
Inflection” in
Cancer
Research
.
The -OMICS
Revolution
3. GENOMIC ONCOLOGY AND
PERSONALIZED MEDICINE--
DEFINITION
To optimize cancer patient care using specific
and targeted therapies applying human
genome data
4. Major Technologies Enabling Genomic
Oncology
cDNA microarray: profiling thousands of genes
simultaneously (transcriptomics).
Array-based comparative genomic hybridization
(Array CGH) or single nucleotide polymorphism
array (SNP array): determining the gene copy
number alternation/loss of heterozygosity across the
whole genome (genomics).
Next generation sequencing technologies: point
mutations, insertions, deletion, gene fusions across
the whole genome (exomics, genomics)
Bioinformatics
5. Gene Expression
Profiling by cDNA
microarray
-Landmark paper for
genomic oncology
“Distinct Types of DLBCL Identified
By Gene Expression Profiling.”
Nature, 2000; 403:503.
Diffuse large
B-cell lymphoma
(DLBCL)
B-cells
Non-neoplastic
B-cells
GC B
DLBCL
Activated B
DLBCL
6. cDNA microarray
Germinal Center (GC) B-cell gene expression
profiles have better prognosis than Activated
B-cells.
Alizadeh et al. Nature, 2000, 403: 503-511.
8. Expression Pattern A: Germinal Center B-
cell
Positive for at least
one:
CD10
Bcl-6
Negative for
BOTH:
MUM-1
CD138
9. Expression Pattern B: Activated
Germinal Center B-cell
Positive for at
least one:
CD10
Bcl-6
Positive for at
least one:
MUM-1
CD138
10. Expression Pattern C:
Activated non-Germinal Center B-cell
Negative for
BOTH:
CD10
Bcl-6
Positive for at
least one:
MUM-1
CD138
11. 0
.2
.4
.6
.8
1
0 20 40 60 80 100 120
Pattern B or C
Pattern A
P = 0.055,
log-rank test
Time (months)
Cum.Survival
Chang, AJSP, 2004;28:464
0
.2
.4
.6
.8
1
0 20 40 60 80 100 120
Time (months)
Pattern C
Pattern B
Pattern A
P < 0.008,
log-rank test
Cum.Survival
All patients Low clinical risk patients
12. Array-based Comparative Genomic Hybridization (Array
CGH) or Single Nucleotide Polymorphism array (SNP array)
to Determine the Gene Copy Number Alternation in Cancers
13. Plasmablastic Lymphoma (PL)
HIV, oral cavity, described in 1997
Considered as a subtype of diffuse large B-cell
lymphoma (DLBCL)
Immunophenotypically identical to plasma cell
myeloma (PCM):
CD20-, CD138+, PAX5-, CD56+
(Vega, Chang et al, Mod Pathol 2005)
16. Without clinical information, differentiation of
PL and extramedullary plasma cell myeloma is
very difficult, if not possible, based on
morphology and/or IHC
Clinically very important: treatment and
prognosis of myeloma and lymphoma are very
different
How about the relationship between DLBCL,
PL and PCM at genomic level?
18. At genomic level, PL is more closed to
DLBCL or DLBCL occurring in HIV+
patients than to PCM supporting the current
classification scheme and the treatment
approaches.
20. Feero WG et al. N Engl J Med
2010;362:2001-2011.
21. Myelodysplastic Syndromes (MDS) Biomarker
and Mechanism Discovery by NGS
Clonal hematopoietic stem cell diseases
Peripheral cytopenias, hypercellular marrow and
dysplasia
No accurate diagnostic/prognostic biomarkers
for the early stage of MDSs
22. p38MAPK representing the hub of the 10 mutated genes (shaded ones)
detected by RNA-seq through IPA analysis. Chang Lab unpublished data
23. Control MDS patients
Shahjahan, Chang et al, Am J Clin Pathol, 2008;130:635
P38 MAPK is highly activated in MDS as compared to controls
24. The whole genome/transcriptome sequencing results
indicate that p38 MAPK pathway may play an
important role in the pathogenesis of MDS.
P38 MAPK inhibitors may help a subset of MDS
patients who carry mutations leading to over-
activation of the p38 MAPK pathway.
25. Genomic Oncology Diagnosis of Lung Cancers
Morphologic diagnosis is
the base for characterizing
cancers but more genomic
info is needed for patient
management
EGFR/ALK/ROS1/KRAS
etc mutation status is
needed for the
individualized treatment
for lung cancer patients.
26.
27. EGFR Tyrosine Kinase Domain
Mutations
TK domain
Exons 18-24
Amino acids 718-94
200 mutations have
been identified
90% are in exon 19 or
21
42. • Average number of driver mutations varies across tumor
types
• Most tumors have two to six, indicating that the number of
driver mutations required during oncogenesis is relatively
small.
• Highest (6 mutations per tumor) in UCEC, LUAD and
LUSC, and the lowest (2 mutations per tumor) in AML,
BRCA, KIRC and OV.
• Clinical association analysis identifies genes having a
significant effect on survival.
• Laying the groundwork for developing new diagnostics
and individualizing cancer treatment.
43. • Cluster-of-cluster
assignments (COCA)
• 11/28 lung squamous
samples reclassified as
lung adenoCa
• Merging of colon and
rectal Ca into a single
group
• BRCA: (BRCA/
Luminal, ER+/HER+) and
(BRCA/basal, Triple-)
• COCA classification
differs from tissue-of-
origin-classification in
only 10% of all samples.
• Reflecting tumor biology
and clinical outcome.
Cell. 2014
