Methods in molecular biology vol 1606 molecular profiling methods and protocols 2nd edition

Methods in
Molecular Biology 1606

Virginia Espina Editor

Molecular
Profiling
Methods and Protocols
Second Edition


Methods

in

Molecular Biology

Series Editor
John M. Walker
School of Life and Medical Sciences
University of Hertfordshire
Hatfield, Hertfordshire, AL10 9AB, UK

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Molecular Profiling
Methods and Protocols
Second Edition

Edited by

Virginia Espina
Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA


Editor
Virginia Espina
Center for Applied Proteomics and Molecular Medicine
George Mason University
Manassas, VA, USA

ISSN 1064-3745    ISSN 1940-6029 (electronic)
Methods in Molecular Biology
ISBN 978-1-4939-6989-0    ISBN 978-1-4939-6990-6 (eBook)
DOI 10.1007/978-1-4939-6990-6
Library of Congress Control Number: 2017937315
© Springer Science+Business Media LLC 2017
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Dedication
This book is proudly dedicated to Mary Anne and Len Schiff, for their initial faith in my
future scientific career, and to my husband Tito; my children Ben, Paul, and Emily; and my
favorite future scientist Olivia, for always listening to my ideas.
Virginia Espina

v


Preface
The first edition of Molecular Profiling (published in 2012) was at the forefront of the personalized medicine movement. The first edition included reviews of genomics and genomic
profiling, technologies which in the intervening years have rapidly evolved into routine
clinical assays for detecting mutations. Mass spectrometry for protein profiling has also
evolved into sensitive and specific multiple reaction monitoring assays, enabling quantification of proteins without antibody-based methods, while tumor staging and grading and
tissue preservation continue to be important aspects of molecular profiling. As you can see
from these examples, staying current in molecular profiling requires lifelong learning and
incorporating “routine” laboratory analyses with cutting-edge technologies. Hence, when
Professor John Walker, editor for the Methods in Molecular Biology series, inquired as to my
interest in editing an updated version of this book, I was honored that the readers found
the first edition informative and that there was sufficient, continuing interest in molecular
profiling for an updated version. However, I also knew that the second edition would
require many updates to the protocol chapters to reflect the current state of the art in
molecular profiling.
The purpose of this revised volume is to provide both an update on technology and an
accelerated tutorial to assist students, entrepreneurs, new investigators, and established
investigators who want to quickly become versed in, and immersed in, the entire process

from discovery to clinical trial validation and commercial public benefit. The aims of the first
and second edition are the same: to span the full spectrum of molecular profiling from tumor
staging and grading through biomarker discovery to commercialization. The practical guides
are not limited to experimental methods. I have included tutorials on tumor staging, ethics,
patents and intellectual property, product development, innovative clinical trial designs, and
grant writing tips for investigators seeking funding in translational research.
Molecular Profiling, second edition, includes 17 new chapters and 9 revised/updated
chapters. The new chapters cover some “tried-and-true” laboratory methods such as PCR
and scanning electron microscopy. The second edition also includes updated versions of
antibody validation and Western blotting. I had two reasons for including these “standard,”
often kit-based, laboratory methods: (1) understanding the science behind the “kits” can
help solve many problems encountered in assay development, and (2) the book is intended
for a wide audience, including students and physician-scientists. The 17 new chapters cover
laboratory methods relevant to human disease: microsatellite analysis, somatic mutation
analysis, proteomic bioinformatics, microscopic imaging, preservation of bone tissue for
molecular profiling, glycomics, metabolomics, immunohistochemistry, FISH, ELISA
development, and multiple reaction monitoring mass spectrometry.
Chapters 1–3 introduce the reader to clinical medicine through a primer on tumor
staging and grading, ethics in medicine, and clinical trial design. These chapters have been
updated to address the current relevant information and issues. For example, the chapter
on clinical trials discusses examples of innovative trial design in which data generated during
the clinical trial can be used to modify therapies administered to the patients as the trial is
accruing patients.

vii


viii

Preface

A set of core chapters (4–23) covering genomics, proteomics, imaging, and bioinformatics illustrate current laboratory protocols for generating data relevant to molecular
medicine. Each of these disciplines is complementary, and the grouping simply provides a
means for differentiating the classes of molecular analytes. An emphasis is placed on tissue-­
based molecular profiling, which is the core of personalized medicine. Although many of
the techniques discussed in this volume use commercially available reagents and instrumentation, it is imperative for the user/reader to understand the principles and nuances of these
techniques, because they are designed for use with irreplaceable human tissue specimens.
The three topics covered in Chapters 24–26 are a unique aspect of this volume of the
Methods in Molecular Biology series. These latter chapters discuss, in a narrative or tutorial style,
real-world needs in personalized molecular medicine. The narrative chapters are designed to
provide the reader with a well-rounded discussion of intellectual property issues in biotechnology, human subjects research requirements, tips for grant writing in translational research, and
an overview of technology transfer (patent) issues. As with the protocol chapters, important
points are highlighted in the Notes section for each of the narrative chapters.
I hope that the readers of this second edition of Molecular Profiling will use it as a practical guide at the lab bench as well as in the classroom. The intended readership spans the
range of scientists, pathologists, oncologists, residents, biotechnologists, medical students,
and nurses involved in clinical trial research.
I would like to express my sincere gratitude to my editorial assistant, Emily Espina, who
provided excellent grammar editing. I truly appreciate, and thank, all my authors for their
time and effort in compiling and submitting new and updated chapters. Their collective
contributions and input have greatly expanded the scope and depth of the book. I thank
Lance Liotta, my co-editor on the first edition, who supported me with the utmost respect
and trust, while I pursued this solo editing endeavor.
I anticipate that this revised volume will attract new investigators, and invigorate experienced researchers, who can apply their creative talents to realize the promise of individualized molecular medicine. I hope you find this revised edition a useful and informative guide
for your molecular profiling adventures.
Manassas, VA, USA

Virginia Espina


Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
  1 Tumor Staging and Grading: A Primer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Stacy M. Telloni
  2 Innovations in Clinical Trial Design in the Era of Molecular Profiling . . . . . . . .
Julia D. Wulfkuhle, Alexander Spira, Kirsten H. Edmiston,
and Emanuel F. Petricoin III
  3 Personalized Medicine: Ethical Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
G. Terry Sharrer
  4 Antibody Validation by Western Blotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Michele Signore, Valeria Manganelli, and Alex Hodge
  5 Scanning Electron Microscopy Sample Preparation and Imaging . . . . . . . . . . .
Jenny Ngoc Tran Nguyen and Amanda M. Harbison
  6 One-Step Preservation and Decalcification of Bony Tissue
for Molecular Profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Claudius Mueller, Michael G. Harpole, and Virginia Espina
  7 Application of Hydrogel Nanoparticles for the Capture, Concentration,
and Preservation of Low-Abundance Biomarkers . . . . . . . . . . . . . . . . . . . . . . .
Ruben Magni and Alessandra Luchini
  8 Using Laser Capture Microdissection to Isolate Cortical Laminae
in Nonhuman Primate Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Brian A. Corgiat and Claudius Mueller
  9 Western Blot Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Brianna Kim
10 ELISA for Monitoring Nerve Growth Factor . . . . . . . . . . . . . . . . . . . . . . . . . .
Justin B. Davis
11 Reverse Phase Protein Microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Elisa Baldelli, Valerie Calvert, Alex Hodge, Amy VanMeter,
Emanuel F. Petricoin III, and Mariaelena Pierobon
12 Clustering and Network Analysis of Reverse Phase Protein Array Data . . . . . . .

Adam Byron
13 PCR: Identification of Genetic Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . .
Amanda M. Harbison and Jenny Ngoc Tran Nguyen
14 Microsatellite Analysis for Identification of Individuals Using Bone
from the Extinct Steller’s Sea Cow (Hydrodamalis gigas) . . . . . . . . . . . . . . . . .
Jeffery F. Warner, Michael G. Harpole, and Lorelei D. Crerar

ix

1
19

37
51
71

85

103

115
133
141
149

171
193

205

x

Contents

15 Somatic DNA Mutation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Anthony O’Grady and Robert Cummins
16 Optimization of Immunostaining for Prospective Image Analysis . . . . . . . . . . .
Scott M. Lawrence and Yelena G. Golubeva
17 Fluorescence In Situ Hybridization of Cells, Chromosomes,
and Formalin-Fixed Paraffin-Embedded Tissues . . . . . . . . . . . . . . . . . . . . . . . .
Ahmad Alamri, Jun Yeb Nam, and Jan K. Blancato
18 High-Resolution Image Stitching as a Tool to Assess Tissue-Level
Protein Distribution and Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Bryan A. Millis and Matthew J. Tyska
19 Mass Spectrometry-Based Biomarker Discovery . . . . . . . . . . . . . . . . . . . . . . . .
Weidong Zhou, Emanuel F. Petricoin III, and Caterina Longo
20 Quantitative Mass Spectrometry by Isotope Dilution and Multiple
Reaction Monitoring (MRM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Paul Russo, Brian L. Hood, Nicholas W. Bateman, and Thomas P. Conrads
21 LC-Mass Spectrometry for Metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Allyson L. Dailey
22 Metabolomic Bioinformatic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Allyson L. Dailey
23 Stable Isotope Quantitative N-Glycan Analysis by Liquid Separation
Techniques and Mass Spectrometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Stefan Mittermayr, Simone Albrecht, Csaba Váradi,
Silvia Millán-Martín, and Jonathan Bones
24 Grant Writing Tips for Translational Research . . . . . . . . . . . . . . . . . . . . . . . . .
Lindsay Wescott, Michael Laskofski, Donna Senator, and Carly Curran

25 Inventions and Patents: A Practical Tutorial . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hina Mehta, Lille Tidwell, and Lance A. Liotta
26 Product Development and Commercialization of Diagnostic or Life Science
Products for Scientists and Researchers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Meghan M. Alonso

219
235

265

281
297

313
333
341

353

367
379

399

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409


Contributors
Ahmad Alamri  •  Lombardi Comprehensive Cancer Center, Georgetown University

Medical Center, Washington, DC, USA; Department of Clinical Laboratories Sciences,
College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
Simone Albrecht  •  NIBRT—The National Institute for Bioprocessing Research &
Training, Dublin, Ireland
Meghan M. Alonso  •  IMUA Services, Medical Invention and Device Development
Consulting, Carlsbad, CA, USA
Elisa Baldelli  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Nicholas W. Bateman  •  DOD Gynecologic Cancer Center of Excellence, Annandale, VA,
USA
Jan K. Blancato  •  Lombardi Comprehensive Cancer Center, Georgetown University
Medical Center, Washington, DC, USA; Georgetown Lombardi Comprehensive Cancer
Center, Fisher Center for Hereditary Cancer and Clinical Genomics Research,
Georgetown University, Washington, DC, USA
Jonathan Bones  •  NIBRT—The National Institute for Bioprocessing Research &
Training, Dublin, Ireland
Adam Byron  •  Cancer Research UK Edinburgh Centre, Institute of Genetics
and Molecular Medicine, University of Edinburgh, Edinburgh, UK
Valerie Calvert  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Thomas P. Conrads  •  Inova Dwight and Martha Schar Cancer Institute, Falls Church,
VA, USA; Gynecologic Cancer Center of Excellence, Women’s Health Integrated Research
Center, Annandale, VA, USA
Brian A. Corgiat  •  Center for Applied Proteomics and Molecular Medicine, George
Mason University, Manassas, VA, USA
Lorelei D. Crerar  •  Department of Biology, George Mason University, Fairfax, VA, USA
Robert Cummins  •  Department of Pathology, RCSI Education & Research Center, Royal
College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
Carly Curran  •  Office of Sponsored Programs, George Mason University, Fairfax, VA, USA
Allyson L. Dailey  •  Department of Chemistry and Biochemistry, George Mason

University, Manassas, VA, USA
Justin B. Davis  •  Department of Chemistry and Biochemistry, George Mason University,
Manassas, VA, USA
Kirsten H. Edmiston  •  Departement of Surgery, Inova Fairfax Hospital Cancer Center,
Falls Church, VA, USA
Virginia Espina  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Yelena Golubeva  •  Medimmune, Gaithersburg, MD, USA
Amanda M. Harbison  •  Northern Virginia Community College, Manassas, VA, USA

xi


xii

Contributors

Michael G. Harpole  •  Center for Applied Proteomics and Molecular Medicine, George
Mason University, Manassas, VA, USA
Alex Hodge  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Brian L. Hood  •  DOD Gynecologic Cancer Center of Excellence, Annandale, VA, USA
Brianna Kim  •  Ceres Nanosciences, Manassas, VA, USA
Michael Laskofski  •  Office of Sponsored Programs, George Mason University, Fairfax,
VA, USA
Scott M. Lawrence  •  Frederick National Laboratory for Cancer Research, Leidos
Biomedical Research, Inc., Frederick, MD, USA
Lance A. Liotta  •  Center for Applied Proteomics and Molecular Medicine, George Mason
Univesity, Manassas, VA, USA
Caterina Longo  •  Dermatology and Skin Cancer Unit, Arcispedale S Maria Nuova

IRCCS, Reggio Emilia, Italy
Alessandra Luchini  •  Center for Applied Proteomics and Molecular Medicine, George
Mason University, Manassas, VA, USA
Ruben Magni  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Valeria Manganelli  •  Department of Experimental Medicine, Sapienza University of
Rome, Rome, Italy
Hina Mehta  •  Office of Technology Transfer, George Mason Univesity, Fairfax, VA, USA
Silvia Millán-Martín  •  NIBRT—The National Institute for Bioprocessing Research &
Training, Dublin, Ireland
Bryan A. Millis  •  Department of Cell and Developmental Biology, Vanderbilt University,
Nashville, TN, USA
Stefan Mittermayr  •  NIBRT—The National Institute for Bioprocessing Research &
Training, Dublin, Ireland
Claudius Mueller  •  Center for Applied Proteomics and Molecular Medicine, George
Mason University, Manassas, VA, USA
Jun Yeb Nam  •  Daegu Catholic University Medical Center, Daegu, South Korea
Jenny Ngoc Tran Nguyen  •  Northern Virginia Community College, Manassas, VA, USA
Anthony O’Grady  •  Department of Pathology, RCSI Education & Research Centre,
Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
Emanuel F. Petricoin III  •  Center for Applied Proteomics and Molecular Medicine,
George Mason University, Manassas, VA, USA
Mariaelena Pierobon  •  Center for Applied Proteomics and Molecular Medicine, George
Mason University, Manassas, VA, USA
Paul Russo  •  Center for Applied Proteomics and Molecular Medicine, George Mason
Univesity, Manassas, VA, USA
Donna Senator  •  Office of Sponsored Programs, George Mason University, Fairfax, VA, USA
G. Terry Sharrer  •  Retired Curator of Health Sciences Smithsonian Institution,
Washington, DC, USA
Michele Signore  •  Istituto Superiore di Sanità, Rome, Italy

Alexander Spira  •  Virginia Cancer Specialists, Falls Church, VA, USA
Stacy M. Telloni  •  Duke Cancer Institute, Raleigh, NC, USA
Lille Tidwell  •  Tidwell Medical Technologies, LLC, Durham, NC, USA


Contributors

xiii

Matthew J. Tyska  •  Department of Cell and Developmental Biology, Vanderbilt
University, Nashville, TN, USA
Amy VanMeter  •  Center for Applied Proteomics and Molecular Medicine, George Mason
University, Manassas, VA, USA
Csaba Váradi  •  NIBRT—The National Institute for Bioprocessing Research & Training,
Dublin, Ireland
Jeffery F. Warner  •  Department of Biology, George Mason University, Fairfax, VA, USA
Lindsay Wescott  •  Office of Sponsored Programs, George Mason University, Fairfax,
VA, USA
Julia D. Wulfkuhle  •  Center for Applied Proteomics and Molecular Medicine,
George Mason University, Manassas, VA, USA
Weidong Zhou  •  Center for Applied Proteomics and Molecular Medicine, George Mason
Univesity, Manassas, VA, USA


Chapter 1
Tumor Staging and Grading: A Primer
Stacy M. Telloni
Abstract
Cancer staging and grading are used to predict the clinical behavior of malignancies, establish appropriate
therapies, and facilitate exchange of precise information between clinicians. The internationally accepted

criterion for cancer staging, the tumor-node-metastasis (TNM) system, includes: (1) tumor size and local
growth (T), (2) extent of lymph node metastases (N), and (3) occurrence of distant metastases (M).
Clinical stage is established before initiation of therapy and is determined by physical examination, laboratory findings, and imaging studies. Pathologic stage is determined following surgical exploration of disease
and histologic examination of tissue. The TNM classification system has evolved over 70 years to accommodate increasing knowledge about cancer biology. Molecular technologies such as genomic and proteomic profiling of tumors could eventually be incorporated into the TNM staging system. This chapter
describes the current TNM system using breast, lung, ovarian, and prostate cancer examples.
Key words Breast cancer, Grade, Lung cancer, Lymph node, Metastasis, Prostate cancer, Ovarian
cancer, Stage, Tumor

1  Introduction
Tumor staging and grading are critical for the practice of clinical
oncology because these classifications serve as the starting point for
patient care. During the staging/grading process, malignancies are
categorized according to anatomic location and pathologic characteristics. The most recent seventh edition of the TMN staging system
was adopted from the American Joint Committee on Cancer in 2010.
Cancer stage refers to the anatomic extent of the disease spread.
Stage I through III diseases are considered curable using surgery,
radiation, chemotherapy, and hormonal/biologic therapies. Stage
IV disease is considered incurable. The internationally accepted
criterion for establishing stage is the tumor-node-metastasis
(TNM) system, which includes (a) tumor size and local growth
(T), (b) extent of lymph node metastases (N), and (c) occurrence
of distant metastases (M). Cancers are categorized as primary
tumor size between T0 and T4, nodes between N0 and N3, and
Virginia Espina (ed.), Molecular Profiling: Methods and Protocols, Methods in Molecular Biology, vol. 1606,
DOI 10.1007/978-1-4939-6990-6_1, © Springer Science+Business Media LLC 2017

1


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Stacy M. Telloni

metastases between M0 and M1. Generally, as the size of the primary untreated cancer (T) increases, regional lymph node involvement (N) and distant metastasis (M) become more frequent.
Common sites for solid tumor metastases include lymph nodes, the
lung, bone, liver, brain, and bone marrow [1]. The following is a
very basic TNM schema [1, 2]:
Primary Tumor (T)
TX: Tumor cannot be assessed
T0: No evidence of primary tumor
Tis: Carcinoma in situ
T1, T2, T3, T4: Increasing size and/or local extent of tumor
Regional Lymph Nodes (N)
NX: Regional lymph nodes cannot be assessed
N0: No evidence of disease in lymph nodes
N1, N2, N3: Increasing disease involvement of regional lymph
nodes
Distant Metastasis (M)
MX: Distant metastasis cannot be assessed
M0: No distant metastasis
M1: Distant metastasis
Solid tumor malignancies are staged only once, at the time of
initial diagnosis. Cancers can be assigned both a clinical and pathologic stage. Clinical stage is established before initiation of therapy
and is based on physical examination, laboratory findings, and
imaging studies. Pathologic stage is determined using tumor tissue
procured through surgical exploration of disease [2]. Pathologic
stage is particularly significant for cancers which are not easily classified in a clinical setting, such as ovarian carcinoma [3]. Both clinical and pathologic stages should be documented in every patient’s
permanent medical record.

2  Description of Stage and Grade [2, 3]

2.1  Tumor Stages

Stage I: Tumor limited to organ of origin, without nodular or vascular spread.
Stage II: Local spread of tumor into surrounding tissue and
regional lymph nodes. The lesion is resectable, but there is
sometimes uncertainty about completeness of removal due to
tumor microinvasion into surrounding tissue.


Tumor Staging and Grading

3

Stage III: Extensive primary tumor with invasion into deeper
structures and lymph nodes. The lesion is operable, but oftentimes gross disease is left behind.
Stage IV: Evidence of distant metastasis beyond tumor organ of
origin.
2.2  Tumor Grades

Tumor grade must be assigned by certified pathologists and is
based on histology and architecture. By definition, malignant
tumors invade the basement membrane and extracellular matrix to
invade surrounding tissue with indistinct borders [4]. Additional
microscopic evidence of abnormal, or malignant, behavior includes
giant tumor cells, high numbers of mitoses, nucleoli and chromatin morphology, unusual mitoses, aneuploidy, and nuclear pleomorphism [1, 4].
In general, low-grade cancers are well differentiated, resembling
healthy cellular counterparts, and high-grade cancers are anaplastic
and disorderly. The most poorly differentiated part of the tumor
determines overall tumor grade with the exception of prostate cancers [3]. In general, high-grade cancers are more clinically aggressive
than low-grade cancers. Most grading systems divide tumors into

three or four grades according to cellular differentiation [2]:
GX: Grade cannot be evaluated
G1: Well differentiated
G2: Moderately differentiated
G3–G4: Poorly differentiated
Using cancer grading and staging in addition to other clinical
data, clinicians can construct nomograms to predict treatment outcomes, cure rates, and disease-free survival times. Following is a
discussion of specific cancer staging and grading for lung, prostate,
breast, and ovarian cancers. Clinical staging information is from
the seventh (2010) edition of the American Joint Committee on
Cancer’s (AJCC) Staging Manual [2].

3  Cancer Classification Examples
3.1  Lung Cancer
Clinical
Staging Workup

Lung cancer is one of the most common malignancies in the Western
hemisphere and the leading cause of cancer death in men and women
[2, 5]. Stage of lung carcinomas at diagnosis remains, in general, the
most important prognostic factor for patients [2, 6]. Patients with
clinically suspected lung carcinoma should receive detailed history
and physical exam, complete blood count, chemistry profile, staging
positron emission tomography (PET)/CT scan, and magnetic resonance imaging (MRI) of the brain for stage II disease or higher.
PET/CT scans are used to show pattern of disease spread and also


4

Stacy M. Telloni

demonstrate tumor metabolic activity by uptake of fludeoxyglucose.
Suspicious lesions at distant sites may be biopsied [5]. Lung cancer
spreads locally into other mediastinal structures and also to intrathoracic, scalene, and supraclavicular lymph nodes. Distant sites of lung
cancer metastases include the liver, adrenal glands, contralateral lung,
and brain [2].
Primary tumor tissue must be procured for confirmation of
pathology and definition of histology. Tissue may be collected either
through bronchoscopy for central lesions or CT-guided needle
biopsy for peripheral lesions. Thoracentesis should also be performed in patients with pleural effusions to determine whether the
effusion cells are malignant or paramalignant and exudative with
negative cytology. Scalene and intrathoracic lymph nodes that appear
irregular or enlarged on CT scan could also be sampled using mediastinoscopy. This regional lymph node sampling is critical for construction of the best sequence of treatment for patients, which
includes surgery, radiation, chemotherapy, and sometimes targeted
therapies [5, 7, 8] (see Table 1 for specific TMN staging criteria).
Small-cell lung carcinoma (SCLC), a common subtype of
lung cancer, is frequently described using a two-stage system
rather than TNM staging [5, 6, 9]. SCLC tends to be disseminated at the time of diagnosis, with only 25% of patients presenting with “limited” disease [5]. SCLC is considered “limited”
when it is confined to an area which can be safely treated with
definitive radiation doses. In general, “limited” SCLC corresponds to stages I through III in the TNM system, and “extensive” SCLC corresponds to stage IV disease [2]. All patients
diagnosed with SCLC must have brain and bone imaging because
disease most commonly metastasizes to these sites [5].
3.1.1  Histology
and Grading

Lung cancers are classified using light microscopy with routinely
stained (hematoxylin and eosin) preparations. Immunostains
(IHC) are used to distinguish NSCLC subtypes, most generally
adenocarcinoma and squamous cell carcinoma. Adenocarcinomas
stain positive on IHC for thyroid transcription factor-1 (TTF-1)

and squamous cell carcinomas stain negative for TTF-1, positive
for p63. New biomarkers, or genetic mutations, have arisen as an
important classification for advanced NSCLC as well. These markers, which are both prognostic and predictive, include the a­ naplastic
lymphoma kinase (ALK) fusion oncogene and the epidermal
growth factor receptor (EGFR) mutation. Both are targetable with
currently available tyrosine kinase inhibitor therapy.
Adenocarcinomas are glandular tumors which produce mucin
and are usually located at the periphery of the lung. These tumors are
graded according to number and appearance of glandular structures
(Fig. 1a). Well-differentiated tumors consist of distinctive gland structures throughout 90% of the tumor mass. The glands resemble a
healthy lung tissue, with tall columnar or mucinous epithelium,


Tumor Staging and Grading

5

Table 1
TNM classification and stage grouping for NSCLC
Stage

Grouping

Descriptions

Stage IA

T1a, N0, M0
T1b, N0, M0

T1a: Tumor 2 cm or less
T1b: Tumor >2–3 cm in greatest dimension

Stage IB

T2a, N0, M0

T2a: Tumor >3 and ≤5 cm in greatest dimension
T2b: Tumor >5 but ≤7 cm in greatest dimension

Stage IIA

T2b, N0, M0
T1a, N1, M0
T1b, N1, M0
T2a, N1, M0

N1: Metastasis to ipsilateral peribronchial and/or ipsilateral hilar
lymph nodes and intrapulmonary nodes including involvement
by direct extension of the primary tumor

Stage IIB

T2b, N1, M0
T3, N0, M0

T3: Tumor >7 cm or invades any one of the following: chest wall,
diaphragm, phrenic nerve, mediastinal pleura, parietal
pericardium, or tumor in the main bronchus <2 cm distal to the
carina but without involvement of the carina, or associated

atelectasis or obstructive pneumonitis of the entire lung or
separate tumor nodule(s) in the same lobe

Stage IIIA

T1a, N2, M0
T1b, N2, M0
T2a, N2, M0
T2b, N2, M0
T3, N1, M0
T3, N2, M0
T4, N0, M0
T4, N1, M0

N2: Metastasis to ipsilateral mediastinal and/or subcarinal lymph
node(s)

Stage IIIB

T1a, N3, M0
T1b, N3, M0
T2a, N3, M0
T2b, N3, M0
T3, N3, M0
T4, N2, M0
T4, N3, M0

N3: Metastasis to contralateral mediastinal, contralateral hilar,
ipsilateral or contralateral scalene, or supraclavicular lymph
node(s)

T4: Tumor of any size that invades any of the following:
mediastinum, heart, great vessels, trachea, esophagus, vertebral
body, carina or separate tumor nodules in different ipsilateral
lobes

Stage IV

Any T, any N,
M1a or M1b

M1a: Separate tumor nodules in a contralateral lobe; tumor with
pleural nodules or malignant pleural (or pericardial) effusion
M1b: Distant metastases

Used with permission of the American Joint Committee on Cancer (AJCC), Chicago, Illinois. The original and primary
source for this information is the AJCC Cancer Staging Manual, seventh edition (2010) published by Springer
Science + Business Media

eosinophilic cytoplasm, basal nuclei, and prominent nucleoli. A key
variant of well-differentiated adenocarcinoma is the invasive mucinous
type (formerly bronchioalveolar carcinoma), characterized by blandappearing tumor cells growing continuously along alveolar walls [9].
Poorly differentiated adenocarcinomas have glandular or acinar structures throughout at least 50% of the tumor mass and usually contain
solid stromal areas with atypical mucinous cells [6, 9].
Squamous cell cancers commonly arise from epithelial cells in
the proximal tracheobronchial tree and may therefore present with


6

Stacy M. Telloni

Fig. 1 NSCLC histology. (a) Adenocarcinomas are usually located at the periphery of the lung and graded according
to the number and appearance of glandular structures. (b) Area of a normal lung epithelium adjacent to squamous
cell carcinoma in situ. Squamous cell carcinomas are graded based on proportion of intercellular bridges and other
characteristics of keratinization. Courtesy of William Funkhouser, MD (with permission of Springer)

signs of airway obstruction [5, 6]. These carcinomas are
­characterized microscopically by the presence of intercellular desmosomes, or “intercellular bridges,” and also keratin production
(Fig. 1b) [6, 9]. Grade 1 or well-differentiated tumors have sheets
of cells with ample eosinophilic cytoplasm, round nuclei, prominent nucleoli, and well-defined cellular borders with intercellular
bridges. These well-differentiated tumors may contain concentric
laminated deposits of amorphous, keratinous material called “squamous pearls” [6, 9]. Areas of comedo-like necrosis characterize
grade 2 tumors. Grade 3 tumors are poorly differentiated and cells
tend to grow in confluent sheets. Cells are characterized by bizarre
nuclei, cytological atypia, increased mitotic figures, and areas of
necrosis and/or hemorrhage [6].
Neuroendocrine carcinomas stain positive for synaptophysin
and chromogranin A and are further subdivided according to cellular differentiation. Neuroendocrine tumor types include carcinoid tumors and SCLC, which is the most poorly differentiated
variant [6, 9]. Microscopically, SCLC cells are primitive appearing
with scant cytoplasm, granular chromatin, and high mitotic activity. Encrustation, with basophilic deposition of DNA within blood
vessel walls, is a distinctive histological feature of SCLC (Fig. 2).
3.2  Prostate Cancer
Clinical
Staging Workup

Initial diagnosis of prostate cancer is usually based on abnormal
digital rectal exam (DRE) or an elevated prostate-specific antigen
(PSA) blood level. Prostate biopsy, often obtained transrectally
with ultrasound guidance, is necessary for a definitive diagnosis of
prostate adenocarcinoma. Approximately ten-core needle biopsies

are procured to evaluate all potentially affected lobes of the prostate [10, 11].
Staging prostate cancer is based on primary tumor size (clinical
T stage), serum PSA level, Gleason score, and extent of disease


Tumor Staging and Grading

7

Fig. 2 Small-cell lung carcinoma (SCLC). This histology demonstrates poor differentiation. SCLC cells are primitive appearing with scant cytoplasm, granular
chromatin, and high mitotic activity. Courtesy of William Funkhouser, MD (with
permission of Springer)

spread. The risk of local prostate cancer progressing over the short
term is low [10, 11]; therefore, many patients with low-risk lesions
choose watchful waiting over aggressive staging and treatment.
When more advanced disease is suspected, staging studies should
include transrectal ultrasound and/or pelvic magnetic resonance
imaging (MRI). For evaluation of distant metastases, PET scans
and radionuclide bone scan may be used. Prostate adenocarcinoma
most commonly metastasizes to distant lymph nodes and the bone,
but lung and liver metastases are common in late-stage disease [2]
(see Table 2 for specific TMN staging criteria).
3.2.1  Histology and
Grading

The vast majority of prostate cancers are epithelial adenocarcinomas,
although variants include neuroendocrine tumors, stromal tumors,
and mesenchymal tumors such as leiomyosarcoma or sarcomatoid
carcinoma [12, 13]. Prostatic intraepithelial neoplasia [14] is considered a premalignant lesion [13]. Low-grade PIN is characterized

by a slight increase in cellularity with irregular spacing of epithelial
cells. High-grade PIN displays a marked increase in cellularity with
nuclear enlargement and hyperchromasia. Both low-and high-grade
PIN demonstrate preservation of the basal cell layer [11, 13].
Prostate adenocarcinomas are graded using the Gleason system,
which classifies specimens between one and five based on glandular
architecture and cellular cytomorphology [10–12]. Higher grades of
prostate cancer have the most aberrant glandular morphology.
Several clinical trials have validated the prognostic value of the
Gleason system, with higher scores predicting widespread disease
and worse prognosis [11, 13]. Pathologists report both primary and
secondary scores, with the primary score representing the most


8

Stacy M. Telloni

Table 2
TNM classification and stage grouping for prostate adenocarcinoma
Stage

Grouping

Descriptions

I

T1a-c or T2a, N0, M0, PSA <10,
Gleason ≤6

T1–2a, N0, M0, PSA X, Gleason X

T1a: Tumor incidental histologic finding in 5% or
less of prostate tissue resected
T1b: Tumor incidental histologic finding in more
than 5% of tissue resected
T1c: Tumor identified by needle biopsy
T2a: Tumor involves one half of one lobe or less
N0: No regional lymph node metastasis
M0: No distant metastasis

IIA

T1a-c or T2a, N0, M0, PSA <20,
Gleason ≤7
T1a-c, N0, M0, PSA 10–20, Gleason
≤6
T2b, N0, M0, PSA <20, Gleason ≤7
T2b, N0, M0, PSA X, Gleason X

T2b: Tumor involves more than one half of one
lobe but not both lobes

IIB

T2c, N0, M0, any PSA, any Gleason
T2c: Tumor involves both lobes. Tumor extends
T1–2, N0, M0, PSA ≥ 20 OR Gleason
through the prostate capsule
≥8

III

T3, N0, M0, any PSA, any Gleason

IV

T4: Tumor is fixed or invades adjacent structures
T4, N0, M0, any PSA, any Gleason
except seminal vesicles: bladder neck, external
Any T, N1, M0, any PSA, any Gleason
sphincter, rectum, levator muscles, and/or
Any T, any N, M1, any PSA, any
pelvic wall
Gleason
N1: Metastasis in regional lymph node(s)
M1: Distant metastasis

T3: Tumor extends through the prostate capsule

Used with permission of the American Joint Committee on Cancer (AJCC), Chicago, Illinois. The original and primary
source for this information is the AJCC Cancer Staging Manual, seventh edition (2010) published by Springer
Science + Business Media

common histological grade in the specimen and the secondary score
reflecting the second most common grade. The primary and secondary scores are added to yield overall Gleason score. Thus,
Gleason scores between 1 and 3 represent well-differentiated adenocarcinomas, and scores between 8 and 10 represent poorly differentiated cancers [11, 12].
Generally, Gleason pattern one tissue contains simple round
glands with uniform size, shape, and spacing. The nuclei and
nucleoli are markedly enlarged. Gleason pattern two tumors show

more variation in glandular size and shape and appear incompletely
circumscribed. Haphazardly separated glands among bands of
fibrous stroma characterize pattern three, the most common
microscopic pattern of prostate adenocarcinoma. Pattern four
tumor cells are organized into closely packed or fused glands,
which invade the stroma with ragged infiltrative edges. Gleason
pattern five tumors contain solid sheets of anaplastic cells with
comedo-like necrosis in cribriform nests [12, 13].


Tumor Staging and Grading

3.3  Breast Cancer
Clinical
Staging Workup

9

Breast cancer is usually discovered either through screening
­mammography or detection of a breast lump [2, 15]. Abnormal
mammogram findings include breast masses, microcalcifications,
asymmetries between the breasts, and architectural distortions.
Malignant breast lumps typically present in women over 30 years
old as asymptomatic, painless masses which are fixed to surrounding tissue [16]. Patients with an abnormal mammogram and/or
suspicious breast mass must undergo large-core needle biopsies
for pathologic diagnosis. Approximately ten-core biopsies are preferred, each with diameter between 14 and 18 gauge and length
between 1 and 3 cm. For women without palpable masses, mammogram or ultrasound guidance is used to precisely localize the
lesion [15, 16].
Extensive use of screening mammography has led to increased
diagnoses of noninvasive breast carcinoma or ductal carcinoma in

situ (DCIS) [14, 15]. DCIS encompasses a wide spectrum of diseases with multiple staging and treatment options. In general,
DCIS has low metastatic potential but must be completely excised
with either radical mastectomy or lumpectomy to prevent local
recurrence [14, 17–19]. The most important prognostic factors
influencing local recurrence of DCIS include lesion size, adequacy
of resection, histologic grade, and patient age [15]. It is therefore
important for surgeons to obtain a wide surgical margin, preferably
10 mm in each dimension. In addition, pathologists must examine
biopsy tissue for areas of microscopic stromal invasion or microinvasion. The AJCC Cancer Staging Manual classifies microinvasion
as T1mic, a subset of T1 breast cancer [2]. Sentinel lymph node
biopsy and axillary lymph node dissections are not necessary with
DCIS unless the patient has high-grade disease or documentation
of microinvasion [17–19].
Invasive breast cancers require complete operative excision
plus sentinel lymph node biopsy and/or axillary lymph node dissection (ALND). Important operative findings for staging include
the size of the primary tumor and presence of chest wall invasion.
If the primary tumor is invasive and sentinel lymph node biopsy is
positive, ALND should be considered to evaluate for metastases.
Breast lymphatics drain by way of three major routes: axillary,
transpectoral, and internal mammary. Any other lymph node
metastases, with the exception of supraclavicular spread, are considered metastatic disease (M1) [2].
Additional workup for suspected breast carcinoma might include
supplementary breast imaging, chest imaging, and laboratory work
with complete blood count and liver function tests. Breast ultrasound is useful to assess primary lesions in women with dense breasts,
precisely locate breast masses, and evaluate ipsilateral axillary lymph
nodes. Breast MRI can be used to evaluate for occult disease, either
in the ipsilateral or contralateral breast, and to screen for synchronous breast lesions [15, 16]. Women with advanced-­stage cancer


10

Stacy M. Telloni

should have a CT scan of the chest, abdomen, and pelvis and p
­ ossibly
radionuclide bone scan [15]. The most common sites of breast cancer metastasis are the bone, brain, liver, and lung [2] (see Table 3 for
specific TMN staging criteria).
3.3.1  Histology and
Grading

Adenocarcinoma, which may be either noninvasive or invasive, is
the most common histologic type of breast cancer. The noninvasive adenocarcinomas include DCIS and lobular carcinoma in situ
(LCIS) [15]. The most common histologic type of invasive breast
adenocarcinoma is ductal carcinoma, NOS (not otherwise

Table 3
TNM classification and stage grouping for breast adenocarcinoma
Stage

Grouping

Descriptions

0

Tis, N0, M0

Tis: Ductal or lobular carcinoma in situ
N0: No regional lymph node metastasis
M0: No distant metastasis

IA

T1, N0, M0

T1: Tumor 2 cm or less in greatest dimension

IB

T1, N0, M0
T0, N1mi, M0

N1mi: Micrometastases greater than 0.2 mm (more than 200
cells) but not greater than 2 mm

IIA

T0, N1, M0
T1, N1, M0
T2, N0, M0

T2: Tumor more than 2 cm but not more than 5 cm in greatest
dimension
N1: Metastasis in up to three axillary lymph nodes and/or
internal mammary lymph nodes with metastases detected by
sentinel lymph node biopsy but not clinically detected

IIB

T2, N1, M0

T3, N0, M0

T3: Tumor more than 5 cm in greatest dimension

IIIA

T0, N2, M0
T1, N2, M0
T2, N2, M0
T3, N1, M0
T3, N2, M0

N2: Metastases in 4–9 axillary lymph nodes or in clinically
detected internal mammary lymph nodes in the absence of
axillary lymph node metastases

IIIB

T4, N0, M0
T4, N1, M0
T4, N2, M0

T4: Tumor of any size with direct extension to the chest wall or skin

IIIC

Any T, N3, M0

N3: Metastases in ten or more axillary lymph nodes; or in
infraclavicular lymph nodes; or in clinically detected ipsilateral

internal mammary lymph nodes in the presence of one or more
positive level I or II axillary nodes; or in more than three
axillary lymph nodes with micrometastases or macrometastases
by sentinel lymph node biopsy but not clinically detected; or in
ipsilateral supraclavicular lymph nodes

IV

Any T, Any N, M1

M1: Distant metastasis

Used with permission of the American Joint Committee on Cancer (AJCC), Chicago, Illinois. The original and primary
source for this information is the AJCC Cancer Staging Manual, seventh edition (2010) published by Springer
Science + Business Media


Tumor Staging and Grading

11

specified); however, other subtypes of invasive disease include
infiltrating lobular, mucinous, medullary, and papillary carcinoma.
Familiar subtypes of breast cancer that do not represent special
pathologic categories include Paget’s disease and inflammatory
carcinoma. Paget’s disease of the nipple is a variant of high-grade
DCIS in subareolar breast ducts but can also be associated with
invasive carcinoma [15]. Inflammatory carcinoma is a clinical
diagnosis and considered an aggressive variant of infiltrating ductal carcinoma, NOS [14].
Breast cancer grading is applicable for DCIS and all invasive

carcinomas [2, 20]. DCIS is graded on a three-tiered system based
on nuclear characteristics. Grade 1 or low-grade DCIS cells contain small, round, and uniform nuclei with evenly dispersed
­chromatin (Fig.  3a). Cribriform and micropapillary architectures
are common, and neoplastic cells form geometric bulbous projections around which the cells are polarized [14]. Grade 3 or highgrade DCIS tumor cells are pleomorphic with high
nuclear-cytoplasmic ratio, coarse chromatin, and large nucleoli
(Fig. 3b). Mitoses are frequent, and necrosis often occurs in the
center of ducts surrounded by a solid pattern of neoplastic cells
[14]. The presence of necrosis within DCIS automatically qualifies
the specimen as grade 2 or 3 [20].
Invasive breast carcinoma (Fig. 4) is graded based on three histologic components: (1) extent of gland and tubule formation, (2)
degree of nuclear pleomorphism, and (3) number of mitotic figures.
Pathologists assign between one and three points in each of these
dimensions, with one point for the most differentiated histology and
three points for the least differentiated histology. In the tubule/
gland formation category, one point is given for tubule formation in
more than 75% of the tumor mass and three points are given for
tubule formation in less than 10% of the tumor mass [14, 20].

Fig. 3 Breast ductal carcinoma in situ (DCIS). (a) Grade 1 solid breast DCIS cells contain small, round nuclei
with evenly dispersed chromatin. (b) Grade 3 breast DCIS cells show nuclear pleomorphism and coarse chromatin. Courtesy of Chad Livasy, MD (with permission of Springer)


12

Stacy M. Telloni

Fig. 4 Poorly differentiated, infiltrating ductal carcinoma of the breast showing
cells with high mitotic rates and high-grade nuclei. Courtesy of Chad Livasy, MD
(with permission of Springer)

Likewise, nuclear pleomorphism is assessed with one point for small,
regular, and uniform nuclei and three points for marked variation
among nuclei. Low numbers of mitotic figures receive one point and
high numbers receive three points. The final Nottingham grade for
invasive breast carcinoma is determined by totaling points, with lowgrade carcinomas between three and five total points and high-grade
carcinomas between eight and nine total points [20].
3.4  Ovarian Cancer
Clinical
Staging Workup

Ovarian cancer is notoriously asymptomatic until it metastasizes,
but there is no reliable screening method for this disease. Therefore,
the majority of patients present with symptoms of advanced disease
such as bloating, abdominal or pelvic pain, and early satiety [21–
24]. Routine pelvic exams may sometimes reveal earlier stage carcinomas presenting as solid, irregular, and fixed adnexal masses in
postmenopausal women. Suspected ovarian cancer cases should
have a transvaginal ultrasound to more accurately determine tumor
size and consistency, solid versus cystic [25]. Additional workup
for metastatic ovarian cancer includes chest imaging, serum chemistries, and liver function tests [25]. Women with suspected ovarian
cancer should also have serum glycoprotein CA-125 measurement.
CA-125 levels are useful in evaluating the success of future treatments including surgery, radiation, or chemotherapy.
Abdominopelvic CT or MRI may also demonstrate sites of metastatic disease. The most common sites for ovarian spread include
the peritoneum, diaphragmatic, and liver surfaces; however, peritoneal ovarian lesions are not classified as distant metastases. M1
disease is characterized by metastases to the liver, lung, skeleton
parenchyma, supraclavicular nodes, and axillary nodes [2].


Tumor Staging and Grading

13

Surgery is necessary for ovarian cancer cytoreduction and also
plays a role in definitive staging [21–24]. Surgical staging should
include the following: (1) aspiration and cytologic evaluation of
ascites; (2) inspection of the upper abdomen, bowel surfaces,
omentum, appendix, and pelvic organs with resection of suspicious
lymph nodes; (3) pelvic and para-aortic lymph node dissection for
patients with suspicious nodules outside the pelvis; and (4) total
abdominal hysterectomy, bilateral salpingo-oophorectomy, and
partial omentectomy [21, 25]. An experienced gynecologic oncologist should perform this extensive surgery, with a pathologist
available for frozen specimen interpretation.
Epithelial ovarian cancer may spread using any of three primary pathways. First, the tumor can penetrate the ovarian capsule
and directly invade adjacent structures such as the uterus, bladder,
rectum, or pelvic peritoneum. Second, tumors can spread via lymphatics to the pelvic or para-aortic lymph nodes. Finally, ovarian
tumor cells can escape into the peritoneal cavity and spread through
the abdomen using peristalsis and the diaphragm’s respiratory
motions [21] (see Table 4 for specific TMN staging criteria).
3.4.1  Histology and
Grading

Ovarian tumor histology and grading are especially valuable for predicting prognosis and planning treatment of early-stage ovarian cancers [25]. Histopathologic subtypes of ovarian cancer include
epithelial, malignant germ cell tumors, and sex cord-stromal tumors.
Epithelial tumors are the most common ovarian malignancies. Sex
cord-stromal tumors, including granulosa cell tumors, are extremely
rare and arise from the ovarian stroma and/or sex cord derivatives
[26]. While epithelial tumors usually occur in postmenopausal
women, many types of germ cell and sex cord-stromal tumors occur
in younger women. Different types of ovarian cancer present with
unique symptoms depending on histology; however, tumor grading
criteria are usually applied to epithelial tumors [26, 27].

Epithelial tumors arise as adenocarcinomas from the transformation of ovarian coelomic epithelium and surrounding stroma
[21–24]. Histologic subtypes of epithelial tumors include high-­
grade serous, mucinous, endometrioid, clear-cell, and low-grade
serous carcinomas [22–24]. Serous carcinoma, the most common
subtype of epithelial ovarian tumor, has a mixture of cystic, papillary, or solid growth patterns which infiltrate surrounding fibrotic
stroma (Fig. 5). Psammoma bodies, or small areas of calcification
around products of cellular breakdown, are common in serous carcinomas. Mucinous carcinomas are large, multilocular cystic tumors
composed of columnar cells with stratified nuclei and coarse chromatin. Endometrioid carcinomas have glandular or papillary architecture and resemble endometrial adenocarcinomas. Clear-cell
carcinomas are characterized by cells that are cuboidal or polygonal
with abundant cytoplasmic glycogen, and central vesicular nuclei
characterize clear-cell carcinomas. Although all malignant epithelial