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Diagnosis and treatment of cancer using genomics Joseph G Vockley,1 2 John E Niederhuber1 3 1 Inova Translational Medicine Institute, Inova Fairfax Medical Center, Falls Church, VA 22042, USA 2 Virginia Commonwealth University, School of Medicine, Richmond, VA, USA 3 Johns Hopkins University, School of Medicine, Baltimore, MD, USA Correspondence to: J Vockley Joe. [email protected]

Cite this as: BMJ 2015;350:h1832 doi: 10.1136/bmj.h1832

A B S T RAC T

The field of cancer diagnostics is in constant flux as a result of the rapid discovery of new genes associated with cancer, improvements in laboratory techniques for identifying disease causing events, and novel analytic methods that enable the integration of many different types of data. These advances have helped in the identification of novel, informative biomarkers. As more whole genome sequence data are generated and analyzed, emerging information on the baseline variability of the human genome has shown the importance of the ancestral genomic background in patients with a potential disease causing variant. The recent discovery of many novel DNA sequence variants, advances in sequencing and genomic technology, and improved analytic methods enable the impact of germline and somatic genome variation on tumorigenesis and metastasis to be determined. New molecular targets and companion diagnostics are changing the way geneticists and oncologists think about the causes, diagnosis, and treatment of cancer. Introduction Improvements in sequencing technology have increased the number of sequence variants associated with cancer,1 yet the diagnostic and prognostic relevance of these variants is unknown.2 Modern molecular diagnostic laboratories use at least three different sequencing technologies: Illumina,3 ABI Solid,4 and Roche 454 Pyro-sequencing.5 In addition, other sequencing, polymerase chain reaction (PCR), and array based methods are used to analyze a single nucleotide, gene, exome (see Glossary) or whole genome for variation from the germline sequence. Clinical grade Sanger sequencing is the gold standard for confirming sequence variants identified by newer sequencing technologies.6 Emerging technologies have revolutionized the discovery of new cancer biomarkers. In addition, large government funded programs such as The Cancer Genome Atlas (TCGA; http://cancergenome.nih. gov),7 cancer genome project (CGP; www.sanger.ac.uk/ research/projects/cancergenome), therapeutically applicable research to generate effective treatments (TARGET; https://ocg.cancer.gov/programs/target), and the International Cancer Genome Consortium (ICGC; https://icgc. org) have provided the research community with cancer centric datasets that enable the discovery of novel cancer associated genes and the development of bioinformatic tools for analyzing and visualizing complex genomic data. As sequencing costs decrease, the number of newly discovered sequence based biomarkers increases. This has led to diagnostic and predictive markers that provide more comprehensive information about an individual patient’s tumor, subpopulation of cell types within the tumor, and the potential impact of treatment. The validation of newly discovered biomarkers is paramount to

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GLOSSARY Companion diagnostic test: A diagnostic test developed to evaluate the efficacy of a drug in a specific genomic variant Exome: The protein coding part of the genome; made up of exons Exon: Part of the gene that encodes the protein Genomic ancestry: Sequence variations that associate in a unique manner with a geographic or social group of individuals Laser capture microdissection: Excision of a microscopic portion of a tumor that has uniform physical characteristics with the use of a laser Multigene panels: A group of DNA based tests that are combined in a single diagnostic platform so that tissues can be tested for a defined set of genetic markers PCR based diagnostic methods: amplification of small amounts of DNA through the use of polymerase chain reaction to characterize genomic variants in a small tissue such as a laser capture microdissected piece of a tumor Sequencing depth: Number of times a piece of DNA has been sequenced. The more often it has been sequenced and generated the same result, the greater the confidence that the sequence is correct

making these markers useful to clinicians. Advances in technology and analytic methods continuously change the way scientists and physicians approach cancer as a disease. This review summarizes current genomic diagnostic methods and relevant government regulations in the US and UK. It discusses the limitations of genome based cancer diagnostics and the need to understand sequence variants in the context of the genomic background, particularly as it relates to ancestry and the need for enhanced analytic methods. 1 of 9

STAT E O F T H E A RT R E V I E W Sources and selection criteria We reviewed recent publications in the English language over the course of two months (15 August to 15 October 2014) using open access scientific search engines, such as PubMed and OVID. Searches focused primarily on scientific articles published between 2012 and 2014, although some older publications were referenced to increase the depth of historical knowledge. Articles were chosen for review on the basis of timeliness and impact on cancer diagnostics. We used a variety of terms and synonyms to develop filters for cancer genomics to include cancer genes, cancer diagnostics, cancer syndromes, and diagnostic markers. We used a filter for diagnostic technologies to include whole genome sequencing and cancer, exome and cancer, microarray and cancer, and molecular methods and cancer. We also used a filter for cancer risk to include cancer prognostic or predictive markers, cancer risk, cancer statistics, and cancer analytic methods. The National Cancer Institute’s web page (www.cancer.gov) and the Food and Drug Administration’s webpage (www.fda.gov ) were used to obtain background information and are appropriately annotated. We summarized relevant information on the various aspects of cancer discussed in this review and used information from these articles to generate figures that summarize information about cancer diagnostic and prognostic or predictive markers. Current genome based cancer diagnostics Despite the rapid advances in DNA sequencing technology and cancer centric databases over the past few years, surprisingly few new clinically validated laboratory tests have been developed for the diagnosis of cancer.8 Cancer is still mostly diagnosed and characterized by microscopic examination of a tumor sample by a highly trained pathologist.9 Gene specific tests may be performed on a sample to obtain additional information about the genetic make-up of a tumor, but these results are rarely used for diagnosis in the absence of a pathology review. Genetic tests may be used to assess germline cancer risk,10 as diagnostic or prognostic tests to identify somatic variants for specific types of cancer,11 or to direct drug treatment.12 In the United States, cancer biomarkers are divided into two basic types: those approved by the FDA and laboratory developed tests—which are used only in the laboratory that developed them. The number of laboratory developed tests greatly exceeds the number of FDA approved tests. Table 1 provides a list of the most common FDA approved validated tumor biomarkers in clinical use for prognosis and treatment.11 In addition to genome based diagnostics, recent scientific advances have resulted in several unconventional potential genomic diagnostic markers. These include the identification and analysis of tumor derived or tumor associated circulating cell-free DNA in the peripheral circulation,14 tumor associated DNA methylation patterns,15 tumor associated micro-RNA profiles,16 leukocyte telomere length changes,17 and chromatid breakage rates.18 Some of these markers may eventually be developed into laboratory developed tests or FDA approved biomarkers and be available as common diagnostic tests. For personal use only

Circulating cell-free DNA, which was first identified in 1948,19 has been used to detect the presence of circulating tumor cells. However, the importance of assaying for circulating tumor associated cell-free DNA as an early biomarker for cancer has been recognized only recently.20 The identification of circulating DNA from somatic tumor cells that have been shed from a newly formed tumor and that are undergoing necrosis may represent the best chance for early detection of tumorigenesis or metastasis. In people with a family history of cancer, risk assessment of germline variants is key to the prediction, screening, and early detection of disease. Although databases of cancer associated genes, such as the Sanger Cancer Gene Census,21 contain hundreds of entries, just over a dozen genes are responsible for the major familial cancer syndromes. Germline variation in these genes increases the risk of cancer. In the two hit model of cancer initiation,22 the first cancer causing variant can be contained within the germline, with a somatic mutation in the second allele resulting in cancer. Table 2 lists several hereditary cancer syndromes in which cancer causing variants in the germline increase the risk of cancer.

FDA approval The FDA approval process is complex, time consuming, and labor intensive, and it limits the number of tests that are approved by the FDA annually. Table 3 contains a list of tests approved by the FDA in 2014. Colorguard, which detects the presence of colon cancer in patients’ stool samples, is the first direct to consumer cancer specific molecular diagnostic test. FDA regulations require a test to be performed on a device that is matched to the laboratory method because alterations in laboratory methods and instrumentation can substantially affect the results generated by a diagnostic laboratory. This is particularly true for RNA based tests, for which the method of RNA isolation and generation of a cDNA library (if needed) can result in completely incongruent results if an alternative method is used. Three platforms are commonly used in the testing laboratory: sequencing, microarrays, and semi-quantitative or quantitative analysis. Table 4 contains a list of technologies, instruments, and types of tests commonly used in a molecular diagnostic laboratory. Although other technologies and instruments can be used, these represent the instruments needed to operate a state of the art molecular diagnostic laboratory. Recently the Illumina MiSeqDx instrument became the first next generation sequencing system for in vitro diagnostics to be approved by the FDA.25 Illumina has three ready to use FDA approved tests available: a universal kit for developing laboratory developed tests; the cystic fibrosis 139-variant assay to evaluate a panel of sequence variants at position 139 in the CFTR gene; and the cystic fibrosis clinical sequencing assay for comprehensive variant analysis of the entire CFTR gene.26 Although none of these tests was specifically developed for the diagnosis of cancer, the ability of the universal kit to be used to design and validate laboratory developed tests for cancer or other diseases is recognized. 2 of 9

STAT E O F T H E A RT R E V I E W Table 1 | Food and Drug Administration approved genomic and non-genomic based tests commonly used in the diagnosis of cancer13 Tumor marker ALK gene rearrangements

Cancer type Non-small cell lung cancer, anaplastic large cell lymphoma Liver cancer, germ cell tumors

α fetoprotein β2 microglobulin β human chorionic gonadotropin BCR-ABL fusion gene BRAF mutation V600E CA15-3/CA27.29 CA19-9 CA-125 Calcitonin Carcinoembryonic antigen CD20 Chromogranin A Chromosomes 3, 7, and 9p21 Cytokeratin fragments 21-1 EGF mutation analysis Estrogen receptor (ER)/progesterone receptor (PR) Fibrin/fibrinogen HE4 HER2/neu Immunoglobulins KIT KRAS mutation analysis Lactate dehydrogenase Nuclear matrix protein 22 Prostate specific antigen Thyroglobulin Urokinase plasminogen activator (uPA) and plasminogen activator inhibitor (PAI-1) 5-protein signature (Ova1) 21-Gene signature (oncotype DX) 70-Gene signature (Mammaprint)

Tissue analyzed Tumor Blood

Application Determine treatment and prognosis Diagnose liver cancer and follow response to treatment; assess stage, prognosis, and response to treatment of germ cell tumors Determine prognosis, follow response to treatment

Multiple myeloma, chronic lymphocytic leukemia, lymphoma Choriocarcinoma, testicular cancer Chronic myeloid leukemia Cutaneous melanoma, colorectal cancer Breast cancer Pancreatic cancer, gallbladder cancer, bile duct cancer, gastric cancer Ovarian cancer Medullary thyroid cancer Colorectal cancer, breast cancer Non-Hodgkin’s lymphoma Neuroendocrine tumors Bladder cancer Lung cancer Non-small cell lung cancer Breast cancer

Blood, urine, cerebrospinal fluid Urine or blood Blood or bone marrow Tumor Blood Blood

Bladder cancer Ovarian cancer Breast cancer, gastric cancer, esophageal cancer Multiple myeloma, Waldenstrom’s macroglobulinemia Gastrointestinal stromal tumor, mucosal melanoma Colorectal cancer, non-small cell lung cancer Germ cell tumors Bladder cancer Prostate cancer Thyroid cancer Breast cancer

Urine Blood Tumor

Diagnose disease; assess response to treatment and recurrence Diagnose disease; assess response to treatment and recurrence Colorectal cancer metastasis; breast cancer recurrence and response to treatment Determine whether targeted therapy is appropriate Diagnose disease; assess response to treatment and recurrence Monitor tumor recurrence Monitor tumor recurrence Determine treatment and prognosis Determine whether treatment with hormonal therapy (such as tamoxifen) is appropriate Monitor progression and response to therapy Assess disease progression, monitor recurrence Determine whether treatment with trastuzumab is appropriate

Blood and urine

Diagnose disease, assess response to treatment, monitor recurrence

Tumor

Diagnose and determine treatment

Tumor

Determine whether targeted therapy is appropriate

Blood Urine Blood Tumor Tumor

Assess stage, prognosis, and response to treatment Monitor response to treatment Diagnose disease, assess response to treatment, monitor recurrence Evaluate response to treatment, monitor recurrence Determine aggressiveness of cancer, guide treatment

Ovarian cancer Breast cancer Breast cancer

Blood Tumor Tumor

Preoperative assessment of pelvic mass for suspected ovarian cancer Evaluate risk of recurrence Evaluate risk of recurrence

Blood Blood Blood Blood Blood Urine Blood Tumor Tumor

Assess stage, prognosis, and response to treatment Confirm diagnosis, monitor disease status Predict response to targeted therapies Assess effectiveness of treatment and recurrence Assess effectiveness of treatment

Limitations of genome based cancer diagnosis Next generation sequencing, introduced in 2005 and propelled forward by US government funded projects like The Cancer Genome Atlas, has rapidly evolved and is poised to become an affordable and important tool for the diagnosis of cancer.27‑30 Enabled by DNA sequencing and array based methods that detect mutations in single genes or panels of genes, the identification of disease causing variants in cancer related genes is becoming the new standard for molecular diagnosis of cancer and the characterization of tumors and tumor subtypes. Genomic methods hold great promise for understanding the mechanisms involved in the initiation and progression of cancer through the integrated analysis of multiple types of genomic data such as DNA sequence variants, DNA structural variation, RNA expression levels, DNA methylation patterns, and micro-RNA levels. Methods used by first generation commercial providers of genomic interpretation, such as Foundation Medicine (Cambridge, MA), provided the foundation for highly specialized diagnostic companies that focus on integrated For personal use only

analysis (ParadigmDX, Ann Arbor, MI, USA; Pierian Inc, St Louis, MO, USA). Although the full potential of these methods has yet to be validated, the integration of many types of data increases our understanding of the molecular mechanisms that drive tumor cell biology. An essential component of these complex genomic diagnostic methods is the novel analytic software used for the integrated analysis. In recent years a variety of software tools have emerged from academic groups and small biotechnology companies into the public domain. These analytic tools are designed to interpret whole genome and exome sequence data to aid the diagnosis and treatment of cancer. Ultimately, the goal is to inform the clinician and patient about prognosis and potential treatments that target specific genomic alterations in the tumor, while maximizing the effectiveness of treatment and minimizing toxicity. A risk of using molecular targets for evaluating and characterizing a tumor is the concept that tumors typically contain multiple and genomically different clonal populations of cells.31  32 In addition, each lesion within the tumor is located in a microenvironment,33 which may 3 of 9

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Table 2 | Cancer syndromes caused by familial mutations that result in a heritable predisposition to cancer23 Disease Gene Major cancer types Hereditary breast and ovarian cancer BRCA1, BRCA2 Breast, ovarian, prostate, pancreatic cancer TP53 Breast, brain, adrenocortical cancer; soft tissue carcinoma, Li-Fraumeni syndrome osteosarcoma, leukemia Cowden syndrome PTEN Breast, thyroid, endometrial cancer Lynch syndrome MSH2, MLH1, Colorectal, endometrial, ovarian, renal pelvis, pancreatic, MSH6, PMS2, small intestinal, liver, biliary tract, stomach, brain, breast cancer EPCAM Familial adenomatous polyposis APC Colorectal, small intestinal, non-malignant small intestinal, brain, stomach, bone, skin cancer; multiple non-malignant colon polyps Retinoblastoma RB1 Tumors of the eye (retina), pinealoma, osteosarcoma, melanoma, soft tissue sarcoma Multiple endocrine neoplasia type 1 MEN1 Pancreatic endocrine, parathyroid, pituitary gland cancer Medullary thyroid cancer, pheochromocytoma Multiple endocrine neoplasia type 2 RET VHL Kidney cancer, multiple non-cancerous tumors such as Von Hippel-Lindau syndrome pheochromocytoma

Table 3 | New tests approved by the Food and Drug Administration in 201424 Test Colorguard test (Exact Sciences Corp)

Tumor type Colon cancer

Use At home direct to consumer detection of cancer with 90% accuracy First line primary cancer screen for Human papillomavirus (HPV) (Roche Molecular Cervical cancer Systems) HPV-16 and HPV-18 Therascreen (Qiagen) Colon cancer Determines the potential effectiveness of erbitux Cobas epidermal growth factor receptor (EGFR) Non-small cell lung cancer Determines the potential mutation test (Roche Molecular Systems) effectiveness of Tarceva (erlotinib) Prostate Health Index* (Beckman Coulter) Prostate cancer Disease diagnosis; 3 times more accurate than conventional test (prostate specific antigen)

*Approved for use in Europe, awaiting FDA approval.

Table 4 | Common diagnostic technologies, instruments used in a genomic diagnostic laboratory* † Platform Sequencing

Instrument/system Uses 3500xL and 3730xL capillary electrophoresis Sequencing of single amplicons; SNP and system STR haplotyping; targeted panels, exome and whole genome sequencing; sequencing Ion Torrent PGM Next-Generation sequencer from FFPE (and other suboptimal) samples; MiSEQDx Next-Generation sequencer mutation screening and detection; RNA and HiSeq 2500 Next-Generation whole genome micro-RNA sequencing; methylation analysis sequencer Microarray analysis HiScan microarray system Mid-resolution genome scale microarray analysis; SNP and copy number variation analysis; cytogenomic array analysis, transcriptome analysis; methylation analysis QuantStudio 12K Flex system Single to highly mutiplexed (up to 800 Semi-quantitative targets in one run) semi-quantitative and and quantitative Fluidgm Biomark HD system quantitative real time PCR; digital PCR; SNP analysis CFX96 Touch machine haplotyping; known mutation detection; Luminex 200 bead array platform library prep (a step in the generation of DNA sequences) for NextGen sequencing

*Courtesy Ramaswamy Iyer, Inova Laboratory of Genomic Medicine. †Abbreviations: FFPE=formalin fixed paraffin embedded; PCR=polymerase chain reaction; SNP=single nucleotide polymorphism; STR=short tandem repeat.

vary between different locations within the same organ and from one patient to another. Although laser capture microdissection (see Glossary) and PCR based diagnostic methods (see Glossary) can be used to characterize the different cell types found within a tumor,34‑36 it is not practical to use them for routine diagnosis. It is also not reasonable to assume that cells can be chosen for microdissection solely on the basis of a subjective evaluation of their physical appearance. Studies suggest that stromal fibroblasts play a role in treatment resistance in certain cancer types.37 However, For personal use only

for tumors where multiple cell types are evaluated, typically as part of a research study, it is still not possible to determine how the different cell types within the tumor interact with each other or how they affect treatment. Consequently, for technologic and analytic reasons, the molecular diagnosis of a tumor is typically based on the aggregate of all cell types within a tumor and the microenvironment, and it does not affect the interpretation of diagnostic results. Since 2006, the National Cancer Institute has been funding a consortium of researchers called the Tumor Microenvironment Network (http://tmen.nci.nih.gov/ Pages/Home.aspx) to better understand stromal composition, the role that the microenvironment plays, and the mechanisms of interaction between the tumor and normal stroma. The tumor promoting factor, cathepsin Z protease, which is essential for the proliferation of cancer cells and tumor invasion provides an example of the type of interaction that takes place between a tumor and its environment.38 Interestingly, cell proliferation is regulated by cathepsin Z activity in cancer cells only, whereas tumor invasion requires the production of cathepsin Z by cancer cells and host macrophages. Furthermore, cathepsin Z uses different pathways for these two cellular functions. Although the Tumor Microenvirnoment Network has been funding research on the tumor microenvironment for eight years, biomedical science is no closer to understanding the interaction between tumor and host. Until we better understand the role of the tumor microenvironment and potential therapeutic targets within these cells our knowledge for therapeutic decision making will remain incomplete.

Personalized cancer diagnosis and treatment Individualized cancer treatment is based on knowledge of disease causing variants in cancer related genes, their specific impact on complex cellular communication pathways, and the availability of drugs that can target altered genes or appropriate targets within the altered signaling pathway at the subcellular level. These altered genes, also known as actionable genes, include KRAS, EGFR, BRCA1, and BRCA2. The availability of therapeutic agents and companion diagnostics makes it possible to detect and treat individual patients on the basis of their cancer gene mutation profile,39  40 and many institutions offer such services (www.cancercenter.com, www. mayoclinic.org). A drug that could target the mutated TP53 gene has been the subject of intense research, because mutations in TP53 remain a key for the diagnosis of many cancers. However, to date no such compound has been identified. For this reason, TP53 associated genes such as MDM2, a negative regulator of TP53 transcription,41 have become the target of drug development.42 Unfortunately, MDM2 associates with many other genes in the signal transduction pathways and is thus a target of uncertain clinical efficacy.43 Although several cancer therapies target specific genetic markers (table 5), most lack a companion diagnostic test (see Glossary) that can monitor the effectiveness of this treatment. However, the situation is 4 of 9

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Table 5 | Therapeutic compounds and targeted genes44 Compound Anthracyclines Azathioprine Capecitabine Carboplatin Cetuximab Cisplatin Cyclophosphamide Docetaxel Epirubicin Erlotinib Fluorouracil Gefitinib Gemcitabine Irinotecan/SN-38 Leucovorin Mercaptopurine Methotrexate Oxaliplatin Paclitaxel Platinum compounds Purine analogs Pyrimidine analogs Rituximab Sirolimus Tacrolimus Tamoxifen Tegafur Thioguanine

Gene target CBR3 TPMT DPYD, MTHFR EGFR, ERCC1, MTHFR, XRCC1 EGF, FCGR3A ERCC1, TMEM43, XPC, TP53, XRCC1 GSTP1, MTHFR, SOD2, TP53 EGFR GSTP1 EGFR DPYD, GSTP1, MTHFR, TP53, UMPS EGFR EGFR C8orf34, Vest1, UGT1A1, UGT1A9 UMPS TPMT ATIC, MTHFR, MTRR ERCC1, GSTP1, XRCC1 EGFR, TP53 ERCC1, GSTP1, XRCC1 TPMT DPYD FCGR3A CYP3A5 CYP3A4, CYP3A5 CYP2D6 DPYD, UMPS TPMT

gradually improving, but there is still a great need for companion diagnostic tests. A study published in 2014 described the increased risk of breast cancer in women who are BRCA1/2 negative, have one family member with breast cancer, and carry a loss of function germline variant in the PALB2 gene.45 The risk of breast cancer in these women was similar to the risk for women with a BRCA2 mutation and one family member with breast cancer. Although there are two predominant mutations in the PALB2 gene (c1592del and c3113G-A), the study identifies disease causing variants in every exon (see Glossary) of the gene. This puts the PALB2 gene on the same level as the widely known BRCA1 and BRCA2 genes, which have been proved to increase the risk of breast and ovarian cancer in women.

Regulation of diagnostic devices A commercially available FDA approved test for PALB2 variant(s) will require laboratory accreditation and skilled technical support. It will therefore be some time before a

clinically validated and FDA approved test is available for PALB2. Until then, laboratory developed tests can be used in the laboratories that develop and validate them but cannot be sold as diagnostic tests to other laboratories. New guidelines from the FDA on the use of laboratory developed tests were submitted to the US Congress for review and approval on 31 July 2014.46 The guidelines set out new regulations as to what constitutes a laboratory developed test and how the FDA proposes to regulate these tests. By contrast, pharmacogenomic tests seem to fall into the category of class III diagnostic tests, which include tests that directly affect treatment. At the time of writing, these guidelines have not been enacted into law. Similarly, proposed revisions to the European Commission’s in vitro directive (IVD Directive 98/79/EC), published by the EC on 26 September 2012, were introduced as a regulation rather than a directive.47 They impose a detailed framework for in vitro diagnostic devices, specifically because of rapid and continual advances in the technological and scientific foundation that support such diagnostics. Although these new regulations do not mirror the FDA’s steps towards stabilizing the development and use of laboratory developed tests, they do cover other aspects of the new FDA guidelines. These include medical software, predictive testing, testing for predisposition to a medical condition, and high risk devices that are used only in the institution in which they are manufactured (similar to the FDA targeted laboratory developed tests).

Sequencing based diagnostics Many laboratory tests are developed specifically for cancer diagnostics (http://labtestsonline.org), although some are purely experimental (table 6). Sequencing technology enables targeted testing for single gene variants and the application of multigene panels (see Glossary). Advantages One diagnostic advantage of whole genome sequencing and exome sequencing over tests that evaluate a limited number of genes is their ability to place potential disease causing variants in the context of the biochemical and signaling pathways that determine the properties of cancer cells and normal cells. The TCGA and the PANCAN projects have shown how the accumulation of statistically insignificant data, from various data types across pathways, identifies pathways that are significantly associated with cancer.49 Data on variations in gene sequences, copy numbers, expression levels, DNA methylation, and micro-RNA levels can all be used to identify defects in

Table 6 | Experimental laboratory developed tests currently registered with the National Institutes of Health as part of the genetic testing registry* Condition Familial breast or ovarian cancer Familial papillary thyroid cancer Oligodontia-colorectal cancer syndrome PTEN hamartoma tumor syndrome SDHB related hereditary paraganglioma

Test target BRCA1 Exome sequencing (no single specific target) AXIN2 PTEN

SDHB

Method Sequencing of coding regions Sequencing of coding regions Sequencing of coding regions Deletion/duplication analysis; mutation scanning of coding regions; sequencing of selected exons Deletion/duplication analysis; mutation scanning of coding regions; sequencing of selected exons

*This list is a subset of the 3364 tests for 3444 conditions performed in 205 laboratories.48

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STAT E O F T H E A RT R E V I E W pathways that otherwise would not have been associated with cancer.7 These research insights provide scientists with additional information that may result in diagnostics and therapeutics based on novel pathways, where multiple biomarkers in multiple pathways are simultaneously targeted to overcome the accumulated genomic burden in cells that causes cancer. Another advantage of sequencing based diagnostics is that the technical accuracy of the test can be improved by increasing sequencing depth (see Glossary).50  51 Single gene tests often have 1000× or 2000× sequencing depth of the target, well within the recommended range of 5002000×,52  53 whereas panel gene tests that evaluate the mutation status of dozens or hundreds of genes usually have sequencing depth of about 500×. The recently released UW-OncoPlex test (OncoplexDX, Rockville, MD, USA) is advertised to have 99.2% clinical sensitivity.54 The test simultaneously evaluates 194 clinically related cancer genes for all types of variants at 500× coverage. In addition, it provides a complete analysis and guidelines for therapeutic intervention. Sequencing based panel tests such as Oncoplex are useful because they are easier to analyze and therefore cheaper (typically costing hundreds of dollars) than whole genome sequencing based tests. Panel tests can generate interpreted results in less than 24 hours, whereas whole genome sequencing based diagnostics can take days or weeks to interpret.

Limitations A risk with such panels is that disease causing mutations may fall outside of the genes or specific variants being tested, resulting in negative or inconclusive results. One study of more than 2000 patients with cancer used four different panel tests to identify disease causing variants but found an inconclusive rate of over 25% and a negative rate of almost 70%, despite a 99% analytical sensitivity for the genes included in the panel.55 Whole genome or exome sequencing for cancer diagnostics provides more complete information than panel tests, minimizing the risk that a disease causing variant is not detected because the specific variant is not included on the panel test. Although genomic and exomic sequencing are more inclusive, they lack clinical accuracy because of the depth of the sequence. When deep whole genome sequencing is used to characterize a cancer, sequencing depth is typically 80-100×, far below the 500-2000× depth recommended for sequence based targeted genes and gene panels. In addition, several other technical limitations of whole genome and exome sequencing make them less reliable for cancer diagnostics.56 One way to mitigate the decreased accuracy of these sequencing methods is to include additional datasets that will enhance the analysis. The addition of data on RNA expression, micro-RNA, and DNA methylation can increase the depth of knowledge about a patient’s tumor. However, these data, as well as exome data, are available for only the coding regions of the genome. This is a serious limitation because methylation patterns of promoter or regulatory regions (outside of the coding region) are altered in many cancers. For personal use only

These methods do not provide information on variants that alter DNA structure, chromatin-heterochromatin formation, and regulatory aspects of the genome. Whole genome sequencing is needed to obtain this information. Such integrated analysis is expensive to perform and conflicting data often make interpretation difficult. Nonetheless, as technology and analytic methods improve, these integrative approaches to cancer diagnostics will probably become standard practice.

Costs Despite the claims of the $1000 genome (made by Illumina Inc, the Broad Institute, Washington University Sequencing Center, National Human Genome Institute), whole genome and exome sequencing for the diagnosis of cancer is more expensive than panel based sequencing and still costs more than $1000 (£672; €921). Although the release of Illumina X-10 sequencing technology in 2014 has reduced the cost of research grade whole genome sequencing (40× coverage) to below $1000 for its high volume customers, the total cost including depreciation of equipment, personnel, and data storage and analysis easily exceed $10 000 per sample. Whole genome sequencing of cancer and a normal adjacent tissue costs more than $20 000 per patient. Pharmacogenomic tests Another way to categorize genomic tests is to separate them into those used exclusively for diagnosing cancer or predicting cancer risk, those used to assess the risk of recurrence, those used to predict how the cancer is likely to behave if it develops (cancer prognosis), and those that predict response to therapy. Diagnostic and prognostic genomic tests are different from those that measure the response to therapeutic agents, also known as pharmacogenomic tests.57 A list of pharmacogenomic associations and dosing guidelines can be found at the Pharmacogenomics Knowledgebase (www.pharmgkb.org). It is important to determine the pharmacogenomics of the tumor and the host because somatic mutations in the tumor as well as germline variation in the host may have an impact on treatment. For this reason, pharmacogenomic testing for the treatment of cancer, unlike its use in cardiovascular or neurologic disease, must include an analysis of both tumor tissue and normal unaffected tissue.58 Pharmacogenomic testing is important, not only with regard to specific anti-cancer drugs, but also for the many “support category” drugs used to manage a variety of toxicity effects (dermatologic and gastrointestinal) in the patient, because an altered metabolism can affect the therapeutic index of anti-cancer drugs and the optimal management of toxicity. Most pharmacogenomic tests use FDA approved kits to test for variations in the CYP genes, which are associated with drug metabolism; however, other tests evaluate germline and somatic variation for specific drugs (table 7). There is an argument for the use of whole genome sequencing to profile a comprehensive set of 231 pharmacogenes,59 which has the added benefit of generating sequence information that can be used in research into new biomarkers. 6 of 9

STAT E O F T H E A RT R E V I E W Table 7 | Pharmacogenomic markers in clinical use for chemotherapy or supportive care Markers

Drugs

Adverse effects

Germline

Thiopurine methyltransferase UDP-glucuronosyltransferase 1A1 Glucose-6-phosphate dehydrogenase Cytochrome P450 2D6

Mercaptopurine, tioguanine Irinotecan, nilotinib Rasburicase Codeine, oxycodone; tamoxifen

Neutropenia risk Neutropenia risk; underdosing risk Anemia Altered pain control; altered tumor control

Ruxolitinib Cetuximab, erlotinib, gefitinib, panitumumab Cetuximab, panitumumab Imatinib, dasatinib, nilotinib Imatinib Lapatinib, trastuzumab Vemurafenib Crizotinib

Altered drug activity Altered drug activity Lack of drug activity Altered drug activity Altered drug activity Enhanced drug activity Enhanced drug activity Altered drug activity

Somatic

The importance of ancestral information in cancer molecular diagnostics The various FDA approved and laboratory developed sequence based tests in use, and the sequencing methods that are the technological foundation of these tests, have dramatically improved in recent years. However, despite these improvements, the interpretation of the sequence data is imprecise, particularly with regard to ancestral information (see Glossary).60 The reference genome that is used as a blueprint for genome sequencing,61 which was developed by the National Institutes of Health, was constructed from a limited number of people who lacked ancestral and racial diversity. As a result, when DNA sequences are analyzed, special analytic filters are needed to compensate for the lack of substantial ancestral content derived from deep sequencing.62 Although most experts in DNA sequencing recognize the genomic variation that exists between ancestries, some still dispute the importance of ancestry for diagnosis.63 Although it is well known that the risk of specific cancers is higher in certain populations as a result of germline variations, sequence based diagnostic tests rarely take ancestral information into account. And when this information is taken into account, it is done so only when interpreting the sequence results in relation to risk, not diagnosis and prognosis. The presence of ancestral specific germline mutations can substantially affect risk assessment, diagnosis, and prognosis. This is because a statistically significant increase in cancer related variants in the germline of one population does not increase the risk of cancer in a different population if that population does not share the increase in cancer related germline variants. The figure shows the number of significantly important germline variants identified by whole genome sequencing of a cohort of 681 people of different ancestry.64 As more whole genome sequence information from the general population becomes available, the accuracy and completeness of ancestry specific variation will emerge. Emerging treatments Although genomics are not treatments in the traditional sense, they can affect treatment in several ways. In the For personal use only

field of pharmacogenomics, a limited number of variants in a few genes are associated with how drug are metabolized. To reduce disease burden, decrease adverse affects, and minimize the trial and error method of prescribing drugs it is essential that more drugs associated with genes are developed. Improvements in genomic information that lead to earlier and more accurate diagnosis will decrease the impact of disease. This is best achieved by linking high quality genomic data, data from electronic health records, and outcomes data in a way that helps to associate specific genomic variants with the progression of disease. Earlier detection of disease and better treatment through genomic information are key to better outcomes. Companion diagnostics for drugs are now encouraged, and in some cases required, of companies developing new drug targets. Better systems to collect, store, and link clinical information to genomic information are being developed. Treatment that is tailored to the individual and directed by genomics should improve disease outcomes for patients.





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Number of cancer gene variants per person by ancestry. Box and whiskers plot showing the distribution of the number of non-synonymous genes per subject for each of the six ancestry based subpopulations64 7 of 9

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RESEARCH QUESTIONS How will physicians and patients be informed about the results of genomic tests and therapeutic recommendations? Will personalized genomic characterization of cancers become routine in the community hospital-physician setting or remain the domain of highly specialized academic medical centers and cancer centers? How will proteomics affect the way that genomic data are used? Will it supersede genomics or add to our understanding through integrated analytic approaches? Who will develop the standards—such as ancestral specific reference genomes, a database of minor allele frequency from normal genomes, and an ancestry informed database of disease causing variants—that are needed to make whole genome sequencing more informative? What analytic pipelines will be developed to make the interpretation of integrated genomic datasets routine and reproducible?

Conclusion With the introduction of large scale whole genome sequencing, the availability of large scale cancer specific datasets and detailed ancestral information generated from sequencing of the general population, and the discovery of tumor DNA in the peripheral circulation, the number of biomarkers for diagnosis, prognosis, and risk assessment is set to rise. This should result in an increase in our understanding of the cancer genome over the next few years. As better analytic tools become available to integrate and interpret these complex datasets new therapeutic biomarkers with companion diagnostics will emerge at an increasing rate. A deeper appreciation of the impact of ancestry on cancer needs to translate from basic science into clinical practice. Proteomics is a field of biomarker research that has yet to realize its full potential. Protein biomarkers will inevitably be discovered that change the way we view cancer, perhaps more in the area of prognosis and therapeutics than in cancer risk and diagnosis, because proteins are primarily responsible for cellular processes in both normal and cancer cells. Contributors: JGV performed the literature searches and was the main writer. JEN generated the initial outline for the review, provided feedback on the article’s content, and reviewed the article before submission. JGV is guarantor.

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Competing interests: We have read and understood BMJ policy on declaration of interests and declare the following interests: none. Provenance and peer review: Commissioned; externally peer reviewed. 1 2 3 4

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