liquid biopsy

1. NEWER DIAGNOSTIC TOOLS IN
ONCOLOGY
DR. R. RAJKUMAR D.M.
CONSULTANT MEDICAL ONCOLOGIST
VELAMMAL SPECIALITY HOSPITAL & VELAMMAL
MEDICAL COLLEGE HOSPITAL

2. CASE 1
63/MALE
MULIPLE BONE METS
COLONOSCOPY –ANAL VERGE POLP
UPPER GI SCOPY – ANTRAL GASTRITIS
SERUM PSA- 10.59

10. CASE 2
• 64/ MALE
• CHRONIC ALCHOLIC
• EVALUATED OUTSIDE
• CA HEAD OF PANCREAS
SMV ENGULFEMENT
PERIPANCREATIC NODES

12. CASE 3
• 66 YRS/ MALE
• PARAPARESIS -
COMPRESSIVE
MYELOPATHY
• RENAL MASS WITH
SKELETAL / LUNG METS

13. CASE 3

14. CASE 3

15. CASE 3

16. CASE 4

23. TISSUE --- THE ISSUE !

28. LIQUID BIOPSY: NON-INVASIVE APPROACHES TO DIAGNOSTICS
What is liquid biopsy?
A liquid biopsy is a liquid biomarker that can be isolated from body fluids, such as
blood, saliva, urine, ascites, or pleural effusion. Like a tissue biopsy, it is a
representative of the tissue from which it has spread.
Liquid biopsies have become more clinically useful in recent years due to the ability to
pair tests on circulating tumor cells with genomic tests.
Sample to Insight
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29. Why Liquid Biopsy?
LIMITATIONS OF
TISSUE BIOPSY:
D Cancer is a heterogeneous disease
•
•
Molecular properties differ within a tumor
Primary tumor biopsy may not reflect
current disease condition
Therapy causes changes in tumor cells•
D Biopsy is invasive
• May not be feasible based on patient condition or tumor
accessibility
Impractical for periodic monitoring for progression/
recurrence
•
D Biopsy tissue is limited
•
•
Greater demand due to molecular
profiling
Surgery is costly
Liquid biopsy addresses all these limitations!Sample to Insight
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30. LIQUID BIOPSY AS A GAME CHANGER
Liquid biopsy -can be captured and
characterized for biomarkers, similar to
tissue
Allows early disease detectionD
Allows evaluation of metastasis in real-time and monitoring of the actual
treatment response
D
Enables investigation of primary tumors and metastases through
simple, non-invasive blood tests
D
Enables assessment of tumor heterogeneity and monitoring of tumor
dynamics
D
Enables study of the “tumor dormancy” phenomenonD
Is much faster than classical biopsy testingD
Can be cheaper than classical biopsy testingD
.
Sample to Insight
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31. LIQUID BIOPSY: CIRCULATING BIOMARKERS FOR CANCER
Tumors shed both intact cells (resulting in circulating tumor cells) as well as cellular components,
such as nucleic acids (resulting in cell-free DNA or RNA).
Liquid biopsies
ctNA
(circulating
tumor
nucleic
acids)
CTCs
(circulating
tumor cells)
Exosomes
Small membrane-derived
vesicles (40–100 nm)
contain various molecules such
as signal proteins, microRNAs,
mRNAs, lipids, and exoDNA.
Cancer cells released
from primary tumor mass
into the bloodstream
ctDNA (circulating tumor
DNA), miRNAs, mRNA, &
long non-coding RNA
CTC ctNA, mainly ctDNA Exosome vesicle, exoDNA,
miRNA, and lncRNA
Samples: blood, serum/plasma, urine, CSF, saliva
Sample to Insight
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32. CIRCULATING TUMOR CELLS (CTCS)
•
•
Formed by cell detachment from the primary tumor mass
Detected in the blood of patients with solid tumors, including breast, prostate, lung,
and colon.
CTC enumeration serves as a marker for tumor growth as well as for defining tumor
aggressiveness. Higher CTC counts mean negative cancer prognosis.
•
CTCs are extremely rare (~1 per 1 ml of blood), so optimization of CSC isolation and enrichment
steps is essential.
CURRENT TECHNOLOGIES TO DETECT, CAPTURE, AND
ISOLATE CTCS
•
EpCAM-affinity based: CellSearch® system, AdnaTest BreastCancerDetect, CTC-Chip, Dynal®, MACS® (magnetic-
activated cell sorting system), MagSweeper, On-Q-Ity, CTC-ETI
Physical properties-based: ISET (isolation by size of epithelial tumor cells), ScreenCell®, ApoStream™, density gradient
centrifugation
Other methods: FAST (Fiber-optic array scanning technology), EPISPOT (Epithelial immunospot), flow cytometry
(FACS), PRO Onc Assay
•
•
LIMITATIONS:
• EpCAM-affinity based methods: have low sensitivity, selection bias, and poor specificity (false negative and positive)
• Physical properties-based methods: are elementary and imprecise, with low specificity
Sample to Insight
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33. CHARACTERIZATION OF CTCS AND CHALLENGES
CTC molecular characterization
•
•
Based on antibodies: EpCAM, cytokeratins (CK8, CK18, CK19), CD45-negative. Examples include CellSearch.
Based on transcripts: Rely on transcripts, performed on the total RNA extracted from blood by RT-PCR. Examples
include AdnaTest BreastCancerDetect.
Based on functions: Protein-based assays such as the EPISPOT (Epithelial ImmunoSPOT) assay
Whole-genome amplifications: Single-cell studies targeting CTC heterogeneity, or pooling CTCs to study the
whole tumor cell population
•
•
• CTCs are extremely rare Sensitivity is directly linked to its potential clinical benefit at early stages of the
disease.
• CTCs are fragile Can easily vanish or morphology can be damaged during extraction from blood.
Requires the isolation of all types of CTC without any loss.
Requires broad-spectrum, specific cocktail of cell surface epithelial
and mesenchymal markers covering all potential CTC phenotypes.
• CTCs are heterogeneous
As a modern personalized, non-invasive, predictive test, its clinical validity has been debated, and much effort is still
needed to answer the question of whether CTCs represent a potential surrogate marker for clinical endpoints.
Sample to Insight
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Current clinical utility of CTCs
Challenges

34. Analysis of CTCs
Yu et al. (2011) J Cell Biol

35. CTC - identification
Green – cytokeratin (CK)
Red – EpCAMBlue – DAPI (Nucleus)
Composite staining showing all three
features
CTC images courtesy : Datar Genetics, Mumbai, India

36. CTC – cut off levels
5 CTCs/7.5 mL blood:
• Metastatic breast cancer
• Metastatic prostate cancer
3 CTCs/7.5 mL blood:
• Metastatic colorectal cancer

37. CTC – in vitro chemosensitivity (2)
Baseline 3 hrs 6 hrs 9 hrs Baseline 3 hrs 6 hrs 9 hrsDrug
-ve
control
Carbo-
platin
Cisplatin
Adria-
mycin
Cape-
citabine
Drug
Paclitaxel
Docetaxel
Epirubicin
Cyclophosph
amide
5 FU
Results within 9 hours

38. Number of CTC Before New Therapy Predicts Progression
Free Survival and Overall Survival

39. Number of CTC at First Follow Up Predicts Progression Free
Survival and Overall Survival

40. • The levels of baseline CTC are independent prognostic markers of
outcomes (both progression free survival and overall survival)
• Elevated levels of CTC at First Follow-Up predict both short
progression free survival and overall survival—may indicate that pt.
is receiving futile therapy.
• CTC levels give reliable estimates of disease progression much
earlier than with traditional imaging methods (3-4 weeks vs. 8-12
weeks)

41. • Circulating tumor cell (CTC)
detection may assist
monitoring of radiotherapy
(RT) response in patients with
glioma
• A telomerase-based CTC assay
has been previously described
to be effective in glioma
(MacArthur, et al. 2014).
• We present interim results of
a prospective trial in patients
with high grade glioma
undergoing RT and serial CTC
analysis MacArthur, KM et al. Cancer Res 2014;74:2152-2159

42. • CTCs in patients with glioma were reliably and serially detected, irrespective
of tumor mutation statuses (IDH, EGFR, EGFRvIII mutations, etc.)
• Increasing CTC trend was found to be significantly associated with
progression by 6 months follow-up (p=0.02)
• CTC levels were sensitive to disease burden changes as a result of RT, re-
resection, or progression
• Case A below illustrates how CTC levels in this patient matched radiologic
evidence of initial disease response and eventual progression:

43. CIRCULATING TUMOR DNA (CTDNA)
Mechanisms of tumor DNA shedding: released passively, shed
consciously for tumor propagation, or from CTCs but not the primary tumor
Tumor cells
• Under normal physiologic circumstances, apoptotic and necrotic debris
are cleared by infiltrating phagocytes.
• Tumor cells are large and multiply quickly so the phagocyte process
does not happen efficiently within the tumor mass, leading to the
accumulation of cellular debris and its release into the circulation.
ctDNA reflects disease progression and treatment responses
Mutations, methylation, DNA integrity, microsatellite alterations, and viral DNA can be detected in ctDNA in the blood of
patients with tumors, including bladder, breast, cervical, colorectal, hepatocellular carcinoma, lung, non-Hodgkin’s
lymphoma, melanoma, ovarian, pancreatic, and prostate.
Sample to Insight
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Apoptosis Necrosis/secretion
Normal circulating NA
Exosome
free circulating DNA
Small RNA

44. CIRCULATING TUMOR NUCLEIC ACIDS (CTNA)
Circulating nucleic acids as noninvasive biomarkers for human disease
Types of cell-free nucleic acids
•
•
•
•
DNA (defined as cell-free DNA, cfDNA)
miRNA (microRNA)
mRNA
Long non-coding RNAs (lncRNAs)
D Biology of cell-free NA and clinical utilities
• Cell-free NAs are released from both healthy and tumor cells into circulation through various cell
physiological events such as apoptosis, necrosis, and secretion
Increased levels of circulating nucleic acids (DNA, mRNA, and miRNA) in the blood reflect pathological
processes
The mechanism that lead to the increase of cfNA during cancer development and progression are still not
well understood
•
•
D Cell-free vs. CTCs
• Shorter half-life (CTCs: 1–2.4 hr vs. ctNAs: <1.5 hr)
• Higher levels than CTCs (>50-fold increase)
.
Sample to Insight
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45. CIRCULATING TUMOUR DNA (CTDNA)
• ctDNA is tumour DNA that has been
shed into the bloodstream
• ctDNA can be present in 0.01% - >90%
of the total Cell Free DNA (cfDNA)
• The amount of ctDNA is related to the
tumour burden and varies between
patients with different clinical
presentations
Diaz and Bardelli, 2014 Journal of Clincial Oncology 32

46. ctDNA Collection
• ctDNA has a very short half life
ranging from 15 minutes to
several hours
• It is stable in plasma at -80ºc
• Blood can be sampled in ETDA
tubes but the plasma has to
isolated and stored at -80ºc
within one hour of collection
• Preservative tubes can be used
to stabilise the cfDNA in blood
for up to 4 days at room
temperature.

47. CIRCULATING TUMOR DNA (CTDNA) Detection and Issues
METHODS FOR DETECTING
CIRCULATING TUMOR DNA
D Based on the discrimination of ctDNA from normal
cfDNA by the presence of mutations: point mutations,
copy number variations, chromosomal rearrangements,
and methylation patterns
CTDNA ASSAY ISSUES
D
D
D
D
D
Sensitivity: sometimes extremely low levels of ctDNA (1.0%) are present
Assay standardization: procedures need to be standardized
DNA extraction: the pre-analytical phases of cfDNA need to be better defined
Quantification: accurate quantification is needed
Variability of assay platform: different platform assays have different assay sensitivity and specificity,
and analytical approach
Sample to Insight
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48. FFPE VERSUS CTDNA
• FFPE SAMPLES
• Tumour DNA extracted from fixed biopsy
samples or tumour resections
• Problems with quality of DNA due to
fixation
• Mixture of normal and tumour DNA
• Long time to process by histopathologists.
• Macrodissected to enrich tumour content
• Some patients have no tumour sample
available
• The sample represents the tumour at one
fixed time point
• CTDNA SAMPLES
• ctDNA shed directly from tumour
• Extracted from the plasma component of
whole blood
• Large fragment sizes possible
• Small quantities extracted ~ 30ng/ 5ml
plasma
• Separate out plasma within a few hours of
receipt of blood sample.
• Serial samples can be taken at various time
points during the patient’s treatment

49. ctDNA Workflow
Blood sample taken in
Cell Save preservative
tubes
Sample arrives in lab and
spun to isolate the plasma
Plasma is stored at -80ºc
Sample is extracted
on the same day as
the downstream
process set up due
to ctDNA instability
ctDNA is extracted
from the plasma
using the QIAamp
Circulating Nucleic
Acid on the QIAVac
system
Set up:
Pyrosequencing
Next-generation
sequencing
Quantative PCR
BEAMing
Digital PCR

50. CIRCULATING CELL-FREE RNA (CFRNA)
mRNAS
• RNA released into the circulation is stable, implying that it is protected from
degradation by its packaging into exosomes
The level of exosomal RNA implies genetic information•
miRNAs
•
•
•
miRNAs are ~21 nt, have potential to serve as diagnostic markers
miRNA expression is frequently deregulated in cancer
In blood, miRNAs are highly stable, because most of them are included in
apoptotic bodies, microvesicles, or exosomes and can withstand known mRNA
degradation factors
LONG NON-CODING RNAS (LNCRNAS)
• Play regulatory roles in cancer progression and metastasis
• The long non-coding PCA3 RNA-based urine test is the first FDA-approved test
for the diagnosis of prostate cancer patients
Sample to Insight
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51. EXOSOMES AS CIRCULATING CANCER BIOMARKERS
Exosomes: small membrane vesicles (30–100 nm) , secreted by
most cell types into the bloodstream.
Functional biomolecules:
• DNA fragments (exosomal DNA,
exoDNA)
Proteins and/or peptides
mRNA(exoRNA)
microRNA(miRNA)
Lipids
•
•
•
•
D Exosomes play a central role in cell-to-cell communication.
D The majority of DNA associated with tumor exosomes is double-stranded, representing whole
genomic DNA.
D Biological molecules (protein, RNA, and miRNA) contained in exosomes are well protected by a
lipid bilayer membrane that confers a high degree of stability.
Sample to Insight
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52. EXOSOME ISOLATION METHODS AND
CHALLENGES
CHALLENGES:
•
•
Many current protocols to isolate vesicles use ultracentrifugation
Long processing time, and the process is unreproducible and not selective for tumor exosomes
Rolfo, C. et al. (2014) “Liquid biopsies in lung cancer: the new ambrosia of researchers.”Biochimica et Biophysica Acta 1846, 539.
Sample to Insight
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54. • FOR MORE THAN A CENTURY, CANCERS HAVE BEEN
CLASSIFIED BY THE ORGAN OR TISSUE
– WITH THERAPIES GEARED TO THOSE SPECIFIC AREAS
• AS MORE IS LEARNED ABOUT THE BASIC BIOLOGICAL
PROCESSES IN CANCERS, A NEW PERSPECTIVE HAS
EMERGED
• THE SHIFT FROM AN ORGAN-FOCUSED TO A GENE-
FOCUSED APPROACH TO CANCER IS ALREADY HAVING A
PROFOUND EFFECT ON THE WAY CANCER IS TREATED
A NEW TAXONOMY OF CANCER
FROM ORGANS TO MOLECULES
➞ Genomics and the Future of Cancer Treatment
According to the President of the Dana Farber Cancer
Institute, we may soon look at the concept of “organ-based”
cancer types as ancient history.

55. A NEW TAXONOMY OF CANCER
FROM ORGANS TO MOLECULES

56. INTRATUMORAL & INTERMETASTATIC
CLONAL HETEROGENEITY
HETEROGENEITY WITHIN SINGLE PATIENT
Gerlinger M, Rowan AJ, Horswell S et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England Journal of
Medicine, 366(10), 883-892 (2012).

57. INTERPATIENT TRANSCRIPTOMIC HETEROGENEITY
Breast Cancer
Transcriptomic landscape of breast cancers through mRNA sequencing. Scientific Reports 2, Article number: 264. 14 February 2012

58. Interpatient Genetic Heterogeneity
Breast Cancer – 40 Cancer Genes Across 100 Tumors
Stephens et al, Nature 2012; Shah et al. Nature 2012; Ellis et al. Nature 2012; Banerji et al. Nature 2012

59. Interpatient Epigenetic Heterogeneity
Breast Cancer
PNAS March 15, 2011 vol. 108 no. 11 4364-4369

60. Breast Cancer
Genomic analysis
Hampton OA, Den Hollander P, Miller CA et al. A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line
yields insights into the evolution of a cancer genome. Genome Research, 19(2), 167-177(2009).

61. Genomic Era of Medicine
NGS continues to drive down the cost of sequencing
Moore’s LawCostperRawMegabase
ofDNASequence(US$)
$1,000 genome
Newer NGS systems
$1M genome
$10K genome
2008
Helicos
BioSciences
2008
First tumor:normal
genome sequenced
Massively parallel sequencing
2009
Illumina GAIIX,
SOLiD 3.0
2011
Ion Torrent PGM
PacBio RS
Illumina MiSeq
2010
Illumina HiSeq 2000
Oxford Nanopore
2001
IHGSC reports the
sequence of the first
human genome
Capillary electrophoresis Sanger sequencing
2005
454 pyrosequencing
GS-20
2007
ABI/SOLiD
sequencer
2006
Solexa/Illumina
sequencer
2005
Start of NGS
2007
Entry of NGS
into the market
2012 - 2013
HiSeq 2500
Ion Torrent Proton
NextSeq
2014
HiSeq X Ten
Adapted from: MacConaill LE. Existing and emerging technologies for tumor genomic profiling. Journal of Clinical Oncology, 31(15), 1815-1824 (2013).

62. B. NGS / Massively parallel sequencing (MPS)
A
G
NGS
>100x–1000x
amplicon
AAAACCAGAGTCTAGCACCTTCTCATCAGGAGCAG
AAACCAGAGTCTAGCACCTTCTCATCAGGAGCAAC
AACCAGAGTCTAGCACCTTCTCATCAGGAGCAACG
ACCAGAGTCTAGCACCTTCTCATCAGCAGCAACGT
ACCAGAGTCTAGCACCTTCTCATCAGGAGCAGCGT
CCAGAGTCTAGCACCTTCTCATCAGGAGCAACGTC
GAGTCTAGCACCTTCTCATCAGGAGCAACGTCTGC
CTAGCACCTTCTCATCAGGAGCAGCGTCTGCCTTC
TAGCACCTTCTCATCAGAAGCAACGTCTGCCTTCG
AGCACCTTCTCATCAGGAGCAACGTCTGCCTTCGC
CCCTTCTCATCAGGAGCAGCGTCTGCCTTCGCTAG
ACCTTCTCATCAGTAGCAACGTCTGCCTTCGCTAG
CTTCTCATCAGGAGCAACGTCTGCCTTCGCTAGGC
ATCAGGAGCAGCGTCTGCCTTCGCTAGGCTGACAT
ATCAGGAGCAACGTCTGCCTTCGCTAGGCTGACAT
TCAGGAGCAGCGTCTGCCTTCGCTAGGCTGACATC
GAGCAACGTCTGCCTTCGCTAGGCTGACATCGCGG
GAGCAACGTCTGCCTTCGCTAGGCTGACATCGCGG
AACGTCTGCCTTCGCTAGGCTGACATCGCGGGACC
AACGTCTGCCTTCGCTAGGCTGACATCGCGGGACC
AAAACCAGAGTCTAGCACCTTCTCATCAGGAGCAGCGTCTGCCTTCGCTAGGCTGACATCGCGGGACC
VARIANT
GENE
SEQUENCE
A
G
amplicon
A. Capillary sequencing
Bi-directional
2x
NGS vs. Sanger

63. Clinical Laboratory Analysis
Sanger vs NGS cost of sequencing per run
100
1000
10000
100000
1000000
10000000
100 1000 10000 100000 1000000
Number of Base Pairs Sequenced
NGS is more cost-
effective
compared to Sanger per
run
NGS
Sanger
CostofSequencingperRun
Goal is to utilize NGS platform as a
cost-effective and financially-
sustainable technology in clinical labs
Lab specific

64. Characterization of Cancer Genomes
Technologies
Adapted from: Clinical Implementation of Comprehensive Strategies to Characterize Cancer Genomes: Opportunities and Challenges
MacConaill, et al. Cancer Discovery 2011;1:297-311.
ddPCR
, ddPCR

65. Genomic Alterations in Cancer
Major classes
TS, tumor suppressor
CML, chronic myelogenous leukemia
Macconaill LE, Garraway LA. Clinical implications of the cancer genome. Journal of Clinical Oncology, 28(35), 5219-5228 (2010).

66. Genomic Alterations in Cancer
Major classes
TS, tumor suppressor
CML, chronic myelogenous leukemia
Macconaill LE, Garraway LA. Clinical implications of the cancer genome. Journal of Clinical Oncology, 28(35), 5219-5228 (2010).

67. Genomic Alterations in Cancer
Major classes
TS, tumor suppressor
CML, chronic myelogenous leukemia
Macconaill LE, Garraway LA. Clinical implications of the cancer genome. Journal of Clinical Oncology, 28(35), 5219-5228 (2010).

68. • Sequenced leukemia genome vs. matched normal
(skin) genome
• 8 new mutations discovered in AML
• Most in coding genes
• Out of millions of total SNPs!
• “Most of these genes would not have been candidates
for directed sequencing on the basis of current
understanding of cancer.”
WGS
A new era in cancer genomics
All Normal
Variants
All Tumor
Variants
Unique
Somatic
Variants
Ley TJ, Mardis ER, Ding L et al. DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature, 456(7218), 66-72 (2008)

69. • WGS is a snapshot
• Certain mutations reflect paternal and/or maternal germline variation
• Additional somatic mutations accumulate through life
• “Driver” mutations cause cancer, “passenger” mutations are carried along
• Additional drivers evolve and diversify the cancer
• Some alter aggressiveness…
• …which may be treatable
• Others may alter treatment response, leading to relapse
Germline Cancer
(Primary)
Somatic
Cancer
(Metastasis)
Treatme
nt
Cancer Genomes Are Dynamic
Cancer genomes
are not static.
In cancer, one
snapshot is not
enough.
Relapse

70. Molecularly Informed Clinical Trials
Umbrella study design
Single Cancer Type
Molecular
Target #1
Molecular
Target #2
Molecular
Target #3
Molecular
Target #4
Molecular
Target #5
Therapeutic
Agent #1
Therapeutic
Agent #2
Therapeutic
Agent #3
Therapeutic
Agent #4
Therapeutic
Agent #5

71. Molecularly Informed Clinical Trials
Basket study design
Single therapeutic agent
Specific genetic or
molecular abnormality
Lung
Cancer
Colorectal
Cancer
Breast
Cancer
Prostate
Cancer
Renal
Cancer

72. Molecularly Informed Clinical Trials
Basket study example
▶ Identify mutations/amplifications/translocations in patient tumor sample
– eligibility determination
▶ Assign patient to relevant agent/regimen
NCI’s MATCH (Molecular Analysis for Therapy CHoice)
Genetic
sequencing
Actionable
mutation
detected
Study
agent
Stable
disease,
complete or
partial
response
(CR+PR)
Progressive
disease
(PD)
Continue on study
agent until
progression
Check for
ADDITIONAL
actionable
mutations
No additional
actionable
mutations, or
withdraw consent
Off study
MATCH Study Design
YES
NO
Adapted from http://deainfo.nci.nih.gov/advisory/ncab/164_1213/Conley.pdf

73. CONVENTIONAL CANCER TREATMENT:
Rx
Treatment
Chemotherapy
Dx
Diagnosis
Stage, Grade,
IHC
Rx
Treatment:
Pathway
targeted
therapy
PERSONALIZED CANCER TREATMENT
→

74. Cho WC (ed): An omics perspective on cancer research. New York, NY: Springer 2010