Table Of ContentSunil R. Lakhani · Stephen B. Fox
Editors
Molecular
Pathology
in Cancer
Research
Molecular Pathology in Cancer Research
Sunil R. Lakhani • Stephen B. Fox
Editors
Molecular Pathology
in Cancer Research
Editors
Sunil R. Lakhani Stephen B. Fox
UQ Centre for Clinical Research Director of Pathology
The Royal Brisbane and Women’s Hospital Peter MacCallum Cancer Centre
University of Queensland and Pathology Professorial Fellow
Queensland University of Melbourne
Brisbane, QLD, Australia Melbourne, VIC, Australia
ISBN 978-1-4939-6641-7 ISBN 978-1-4939-6643-1 (eBook)
DOI 10.1007/978-1-4939-6643-1
Library of Congress Control Number: 2016958971
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Introduction: Setting the Scene,
Morphology to Molecular
Revolution and/or evolution is a constant theme in pathology, but never has it been
more pertinent than today with the adoption by diagnostic laboratories of a number
of new key technologies. Borne out of the research environment, these have driven
significant changes in laboratory practice and changes in workforce especially in
the field of cancer diagnostics. The increase in our understanding underlying the
biology of cancer has spawned a new generation of tests using previously unused
“tissue” sources with levels of detection that only a few years ago would have seen
inconceivable. Thus, we are now able to identify DNA sequence mutations using
whole-genome approaches in single cells isolated from peripheral blood, assess the
underlying aetiology of tumours from their mutational signatures and perform
methylation and expression analysis with profiles that give prognostic and/or pre-
dictive information.
Much of our increased knowledge have been underpinned by platform enablers
such as autopsy and tissue banking which have become disciplines of their own, with
the emergence of speciality expertise that is needed to provide appropriately col-
lected, processed and stored samples for molecular interrogation in cancer research.
The changes in the use of new methods and applications in the pathology of
cancer are in many ways analogous to the introduction of the microscope in Paris in
the 1840s when morphology challenged conventional wisdom and the use of clini-
cal classification of tumours. Thus, the applications from the technologies and tech-
niques outlined in this book in a similar manner raise fundamental questions on
tumour classification, biology and therapeutics. Indeed for the classification of
tumours, there is a similar discourse around whether tumours should be genomi-
cally “binned” or whether conventional morphology should continue to be used.
There is emerging data to demonstrate close similarities between tumours of vastly
different origins but look, behave and respond to therapeutic targets in the same
manner. This discussion will continue over the coming decade, but it is likely that a
combination of conventional and innovative technologies will be used to go from a
v
vi Introduction: Setting the Scene, Morphology to Molecular
standard classification system to more of an ontology definition of tumours with all
the ancillary information that this provides. A highly thought-provoking and pro-
vocative “future scoping” further explores how pathology and the revolution in
technology and platform enablers may change the face of pathology across not only
the neoplastic diseases but throughout all pathology.
Melbourne, VIC, Australia Stephen B. Fox
Brisbane, QLD, Australia Sunil R. Lakhani
Contents
Molecular Diagnostics: Translation from Discovery
to Clinical Practice .......................................................................................... 1
Fares Al-Ejeh and Andrew V. Biankin
Biobanking in Cancer Research .................................................................... 27
Lisa Devereux, Heather Thorne, and Stephen B. Fox
Cytogenetics: Methodologies .......................................................................... 51
Chiyan Lau
Cytogenetics: Applications ............................................................................. 67
Chiyan Lau
Genomic Analysis ............................................................................................ 83
Sally M. Hunter, Amy E. McCart Reed, Ian G. Campbell,
and Kylie L. Gorringe
Gene Expression Analysis: Current Methods .............................................. 107
Zhi Ling Teo, Peter Savas, and Sherene Loi
Gene Expression Analysis: Applications ....................................................... 137
Peter Savas, Zhi Ling Teo, and Sherene Loi
Methods Used for Noncoding RNAs Analysis .............................................. 151
Marjan E. Askarian-Amiri, Darren J. Korbie, Debina Sarkar,
and Graeme Finlay
Applications of Non-coding RNA in the Molecular Pathology
of Cancer .......................................................................................................... 177
Keerthana Krishnan and Nicole Cloonan
Proteomics Methods ........................................................................................ 219
Keith Ashman, Greg Rice, and Murray Mitchell
vii
viii Contents
The Clinical Application of Proteomics ........................................................ 239
Keith Ashman, Murray Mitchell, and Gregory Rice
Analysis of DNA Methylation in Clinical Samples: Methods
and Applications .............................................................................................. 261
Alexander Dobrovic
Clinical Flow Cytometry for Hematopoietic Neoplasms ............................. 279
David Wu, Brent L. Wood, and Jonathan R. Fromm
Bioinformatics Analysis of Sequence Data ................................................... 317
Anthony T. Papenfuss, Daniel Cameron, Jan Schroeder,
and Ismael Vergara
Forgotten Resources – The Autopsy .............................................................. 335
Deborah Smith, Amy McCart Reed, and Sunil R. Lakhani
The Future of Molecular Pathology .............................................................. 349
John S. Mattick
Index ................................................................................................................. 359
Molecular Diagnostics: Translation
from Discovery to Clinical Practice
Fares Al-Ejeh and Andrew V. Biankin
Over the past decade, there has been broad publicity and discussions over the
potential of “personalized medicine” to transform clinical practice in oncology. In
its broad definition, personalized medicine in oncology refers to the use of biomark-
ers to make decisions such as the type of therapies, prognosis, and extent of moni-
toring of disease progression. As such, oncologists have been practicing personalized
medicine throughout modern medicine where patients are treated according to clini-
cal staging and the current understanding of specific cancer behaviors. It may be
argued that even chemotherapy is personalized, not only in terms of using different
chemotherapeutics for different cancer types but also for the concept of using anti-
proliferation cytotoxic drugs against highly, uncontrolled proliferative cancers.
Recent examples of personalized targeted therapies include trastuzumab and
crizotinib. Diagnostic tests for Erbb2 amplification for Herceptin in breast cancer
and ALK-gene fusion for crizotinib in non-small cell lung cancer are required to
identify the patients who would benefit from these treatments. More recently,
genome-wide molecular profiling has accelerated deeper understanding of the
architecture of cancers in general and their heterogeneity in their response to thera-
pies specifically. Transcriptome and genome profiling, and proteome profiling to
some extent, have expounded the heterogeneity of cancers even of similar origins
which has been recognized by clinicians and pathologists for decades. The rapid
growth of molecular profiling has been paralleled with an exponential growth in the
use of the term “personalized medicine” (Fig. 1). The promise made is that such
F. Al-Ejeh (*)
Personalised Medicine, QIMR Berghofer Medical Research Institute, Bancroft Building,
300 Herston Road, Herston, QLD 4006, Australia
e-mail: [email protected]
A.V. Biankin (*)
Institute of Cancer Sciences, Wolfson Wohl Cancer Research Centre, Garscube Estate,
Switchback Road, Bearsden, Glasgow, Scotland G61 1BD, UK
e-mail: [email protected]
© Springer Science+Business Media LLC 2016 1
S.R. Lakhani, S.B. Fox (eds.), Molecular Pathology in Cancer Research,
DOI 10.1007/978-1-4939-6643-1_1
2 F. Al-Ejeh and A.V. Biankin
Fig. 1 PubMed search of “personalized medicine” (http://www.ncbi.nlm.nih.gov/pubmed/?term=
personalized+medicine)
advances in the field would deliver sophisticated diagnostic tests and precise
therapies beyond the “one marker-one drug” model of the past. Accordingly, it may
be more suitable to refer to the new model as “precision medicine” or “precision
oncology” to distinguish from personalized medicine although both terms may be
related.
In this chapter, we will discuss the advances of “omics” technologies particularly
their translation into multiplexed molecular pathological tests, which are central for
personalized/precision oncology. The pathways towards clinical development of
such tests will also be discussed within the current and future regulatory landscapes,
and the perspective of clinical utility and impact on patient management and
benefit.
New Technologies and Their Promise
Cancer molecular diagnostics are based on the analysis of biomarkers such DNA,
RNA, or protein to identify risk or incidence of disease, determine disease progres-
sion (prognostic tests), determine therapy, and/or predict response (predictive or
companion diagnostic tests). Microarrays enable high throughput measurements of
DNA, RNA, or protein and have contributed vastly to our current research practice.
One of the earliest descriptions of the use of “DNA microarrays” or “DNA chips” is
probably the study by Augenlicht et al. in 1987 which measured the relative expres-
sion of each of 4000 complementary DNA (cDNA) sequences from biopsies of
human colonic tissue and in colonic carcinoma cells [1]. A follow-up study focused
on 30 cDNA clones in an attempt to compare the expression profiles between two
genetic groups from patients at high risk for developing colorectal cancer and
