**THE HUMAN CANCER GENOME PROJECT**

**[A PROPOSAL FOR A TECHNICAL DEMONSTRATION PROJECT]{.underline}**

**23 AUGUST 2005**

**Introduction**

A working group consisting of cancer biologists, oncologists, and
members of NHGRI-funded genome centers was convened to discuss and
propose a small-scale project designed to initiate systematic DNA
sequence-based analysis of cancer genomes. The working group includes
research teams that have been sequencing candidate genes from a number
of different tumor types for the past few years with funding from
various (including private) sources. Thus, a major aim of the group was
to bring significant collective experience to bear in assisting the
respective staff members of NCI and NHGRI in the technical planning
stages of the recently announced Human Cancer Genome Project. In this
brief document, the working group proposes a simple two-part research
plan that should provide an ample platform to assess the overall
strategy, methods, technology, infrastructure, and software that will be
used in the subsequent pilot project. Furthermore, the proposed
demonstration project will allow the genome centers, and NCI and NHGRI
staff, an opportunity to better investigate and understand the issues of
sample collection, patient informed consent, data release, prospects for
discovery of significant mutations, and the need for a coherent and
comprehensive data product.

**Goals**

The primary goals of the demonstration project are:

1\) to evaluate and compare methods, data production pipelines, software
and sample types for the discovery of relevant mutations and
polymorphisms in relevant regions of cancer genomes,

2\) to make discoveries that illustrate the potential of a systematic
approach to tumor genotyping.

**Research plan**

The demonstration project will consist of two parts. The first part
addresses the goal to illustrate the potential of a systematic approach
to tumor genotyping. Here, we aim to generate DNA sequence data for 1000
selected genes from a well-characterized, high-quality set of
approximately 200 DNA samples obtained from tumor biopsies of the same
type. In addition to providing a platform for generating data from an
important human cancer, this part of the project will serve as a test
bed for the sequence-producing pipelines currently in place at the three
largest NHGRI-funded genome centers. While all three centers utilize
largely similar methods and technology, a better understanding of
seemingly minor tactical differences will be important in establishing
the best practices for cancer genome analysis on a much larger scale.

The second part of the demonstration project addresses the goal to
compare methods and sample types and will aim to sequence a smaller set
of genes (\~50) from a much more diverse set of patient samples,
representing several major tumor types. This will allow a reasonable
evaluation of sample collection issues specific to certain tumor types,
an analysis of sample preparation issues, and an investigation of tumor
heterogeneity.

As described below in greater detail, the sequencing proposed in both
parts of the plan includes some overlap in the data produced between the
three participating genome centers. This approach will provide the basis
for an assessment of data quality and an opportunity to compare software
tools and other tactical differences. Note also that the two parts will
run concurrently. We expect that this demonstration project could be
started almost immediately and completed within one year from
initiation.

*[Part A]{.underline}: Study 1000 genes in 190 DNA samples from
non-small cell lung cancer biopsies.*

In Part A, the three centers will sequence 1000 genes (coding exons
only) from 190 (i.e. two 96-well plates plus control DNAs)
well-characterized patient samples of one tumor type. Based on a number
of factors, including primarily the current availability of
appropriately consented patient samples, the working group strongly
recommends that non-small cell lung cancer (NSCLC; mostly
adenocarcinomas but a number of squamous and large cell carcinomas may
be included as well) be utilized for this part of the project. In
addition to sample availability, NCSLC was chosen because it is the
leading cause of cancer-related death in the US and worldwide annually.
Furthermore, NSCLC is under-funded relative to other tumor types (e.g.
breast and prostate), it is a major solid tumor type (as opposed to
liquid tumors such as leukemia), and both DFCI/Broad Institute and
MSKCC/Wash U have ongoing re-sequencing projects in progress that
already attest to the feasibility of the project.

Purified DNA from several hundred biopsy samples will be provided by
pathology laboratories at Dana Farber Cancer Institute, Memorial
Sloan-Kettering Cancer Center, and Washington University's Siteman
Cancer Center. The three genome centers will evaluate the sample DNAs
and subsequently will develop a "gold set" of 190 tumor DNA samples to
be used for sequencing. DNA from matched normal tissue samples also will
be prepared.

For each of the samples to be included in the 190 "gold set", we will
obtain three types of samples: native DNA from the tumor sample, whole
genome amplified ("WGA"; see below) DNA from the tumor sample and native
DNA from normal tissue. Each of these samples will be analyzed by
high-density genotyping using Affymetrix 500K SNP arrays. In addition to
the value of detecting either loss or amplification of biologically
interesting genomic regions in the samples, the resulting data will
answer two important quality-control questions that will qualify each
sample trio for subsequent analysis: 1) is the tumor sample sufficiently
free from stromal contamination that might obscure somatic mutation
detection? 2) is there genotypic identity between the native DNA, the
amplified DNA and the normal DNA? Genotypic identity both ensures the
integrity of the amplification process and provides sample
identification of the normal sample, which will be used to confirm the
somatic status of mutations and distinguish them from polymorphisms.

To confirm tumor purity, data from the SNP arrays are used in two ways:
to look for LOH

over a minimum of one chromosomal arm, and to look at overall copy
number changes by performing histogram analysis. LOH disappears below
90% tumor content as a result of shortcomings in genotype-calling
software when attempting to determine genotypes in mixed samples. The
histogram analysis looks at the frequency of SNPs with a certain copy
number (using log2 ratios of raw copy number) within a sample. For each
sample, the log2 ratio is median-averaged over a moving window of 15
SNPs. Histogram analysis is performed using a set of equally-spaced bins
on the median-averaged values and plotted. Samples that have only one
broad peak are not useable, as this indicates that contaminating DNA
from surrounding normal tissue is obscuring other copy number changes.
Samples containing copy number changes should contain a main peak (two
copies) plus additional peaks for the copy number changes.

The second analysis is a straightforward test that confirms that
genotypes are identical between each sample derivative, and that sample
mix up or gross error in whole genome amplification has not occurred.
The reproducibility of genotype calls on the arrays has been shown to
exceed 99.5%. Therefore, we should expect near perfect concordance of
genotypes between the amplified and unamplified DNA, and perfect
concordance of genotypes (in the majority of the genome that has not
undergone loss in the tumors) between the tumor and the normal samples.

These data will be generated for all samples in this project by the
Broad Institute as they already have established a high-capacity SNP
array pipeline and a close working relationship with Affymetrix in
product and lab process development. All data will be made available to
the other participating centers through a common database. All qualified
DNA samples will be dispensed into 96-well microtiter trays to each of
the three centers.

Most of the early and ongoing projects in cancer re-sequencing using
directed PCR amplification have already required us to address the issue
of sample abundance, which becomes a more pressing problem with
increasing numbers of genes to be assayed. In order to investigate
alternatives, various procedures for amplifying genomic DNA ("whole
genome amplification" or WGA) have been attempted, with appropriate
comparisons to the corresponding native (un-amplified) DNA using a range
of assays to gauge the fidelity of representation. These efforts have
resulted in our adaptation of the currently accepted WGA method that
entails isothermal amplification using random oligos (typically hexamers
or heptamers) and phi29 polymerase, in a multiple strand displacement
process. Phi29 polymerase is a highly processive polymerase of viral
origin, with an associated proofreading activity. Typical amplification
results in a \>1000 fold increase in genomic DNA following an overnight
incubation. Amplification success is typically assayed by PCR with
standardized primer pairs (single band product must be obtained from a
majority of primer pairs), Taqman assay (proper copy number of specific
loci relative to expectation) and/or by SNP assay (genotype compared to
un-amplified matched controls).

Data supporting the use of the phi29 WGA method include extensive
comparisons of sequence data (error rate of 9.5 x 10^-6^ in 500 kb),
high-density Affymetrix microarray SNP genotype data (error rate \<0.2%
based on analysis of 10,000 SNPs), and reproducible measures of gene
dosage (based on 43,000 element cDNA microarray CGH analysis) using
native (non-WGA) and WGA-amplified genomic DNA samples. Overall,
evaluation of data from these assays has established that the estimated
error rates between amplified and unamplified samples are low and not
significantly different than the error rate observed between unamplified
samples. Although phi29 shows a reproducible amplification bias that is
significantly linked to regional GC content, simply performing
comparisons using similarly amplified normal controls normalizes this
bias. (Bredel et al., Journal of Molecular Diagnostics 7: 171-182 (2005)
and Paez, JG et al., Nucleic Acids Research 32: e71 (2004)). Smaller
studies have investigated WGA using Taqman, pyrosequencing and
microsatellite marker assays from degraded clinical samples (Holbrook et
al., J. Biomolecular Techniques 16: 125-133 (2005) or single sperm cells
(Jiang et al., Nucleic Acids Research 33, e91 (2005)), and Affymetrix
SNP arrays using bloods (Tzvetkov et al., Electrophoresis 26: 710-715
(2005)). In all studies, the use of WGA was validated with high
concordance to results obtained from corresponding un-amplified
controls.

In summary, we plan to utilize phi29 WGA for the genomic samples
described in this research plan, at least at the first pass. We
recognize that there may be new approaches to WGA that are either
published or become commercially available during the execution of this
project. If so, we will investigate these in a manner similar to those
described above and in comparison to our phi29-amplified data.

The gene list for Part A will consist of 1000 genes selected mainly
based on the possibility of finding mutations in solid tumors. Several
hundred of these candidates are obvious (e.g. proto-oncogenes, tumor
suppressors, the EGFR pathway, etc.) and many others are less obvious,
however the list will be refined by further deliberation of a small
subcommittee (SC1). We have been provided with a gene list, largely
generated by Alex Lash and Chris Sander at MSKCC, for sequencing
candidate genes in sarcoma samples in a privately funded effort. This
list contains 1472 genes and offers a useful model for our efforts.

As described above, all three genome centers will work from the same
"gold set" of 190 patient samples. The list of 1000 genes will be
divided between the three centers so that each center is responsible for
sequencing 300 unique genes and a common set of 100 genes. The latter
will provide a basis for a comparison of results across the three
centers. Division of the gene list will be done by physical location of
each gene within the genome, and we will take into consideration the
number of amplicons per gene so that the sequencing workload is evenly
distributed across the centers. Sample and sequencing issues will
continue to be refined as needed through the efforts of a second small
subcommittee (SC2).

*[Part B]{.underline}: Study 50 genes in 380 DNA samples from various
tumor types and preparations.*

In this part of the project, the three centers will sequence 50 genes
(exons only) from four 96-well plates (\~380 DNA samples) derived from
four to eight tumor types or cell lines, with some matched normal
controls. To avoid delay, we would propose the use of tumor types that
have already been collected and suitably consented. Among the working
group, there was a strong interest in using several types of carcinoma
(at least four from a list that includes renal, bladder, ovarian,
prostate, colon, breast, and pancreatic), at least one form of leukemia
(likely childhood AML), and a small number of cancer cell lines with
matched normal cell lines. The samples chosen to be included in the
"part B set" would also include some reconstructed mixtures of normal
and tumor DNA from the same patient to better assess sample
heterogeneity issues, some micro-dissected tumors from heterogeneous
tumor types, and some non-WGA treated native DNA (from non-small cell
lung cancers) with corresponding WGA-treated samples, meant to address
any concerns about WGA fidelity. As in the first part of the project,
the three genome centers will evaluate several hundred sample DNAs using
an agreed-upon set of primer pairs and subsequently will develop a final
set consisting of four 96-well microtiter trays to be used for
sequencing. All samples (except for those representing the non-WGA test)
will be amplified using phi29 polymerase, assayed using Affymetrix SNP
arrays, and dispersed to each of the three centers. Here, each of the
three participating genome centers will focus on two of the four 96-well
sample trays (i.e. one common tray to be utilized by all centers).

The gene list for this part of the project represents a basic list of
proto-oncogenes and tumor suppressors. The working group has generated a
current list of 60 genes that can be reduced (if necessary) by SC1.

*[Data release and information sharing]{.underline}*

All sequence traces will be immediately deposited to the Trace Archive
(TA) at NCBI. The centers will develop a common nomenclature for cancer
genome sequences that allows these data to be clearly distinguished from
other human genome traces previously deposited.

All primer sequences will be archived in a common database that can be
accessed by the participating centers and by NHGRI and NCI staff. At
some point, we will make this database accessible to the research
community.

Tactical information, quality assessments, software comparisons and the
like will be shared and managed by SC2 in consultation with NHGRI and
NCI staff.

*[Data analysis and validation]{.underline}*

Analysis of the resulting sequence data for mutation (and SNP) discovery
currently is performed by all three participating genome centers using
slightly different strategies and software tools. For this demonstration
project, one of the goals is to generate a large set of data and
subsequently to assess the different approaches to data analysis, so
that a common approach or common set of tools can be selected (or
developed, if necessary). With regard to analysis tools, there will be
the need for a joint exercise aimed at evaluating, comparing and perhaps
publishing our findings on this comparative approach. The exact nature
of this activity should be the focus of a small working group.

Validation of sequence variants discovered in both parts of the
technical demonstration project can be accomplished using various
approaches. To converge on the best and most efficient approach, we
would propose that the three centers develop a final master set of
candidate genes and samples to be validated. This might consist of 1000
amplicons from Part A, for example. Initial validation would be
performed using MS-based genotyping (Sequenom) on both the tumor and
matching normal DNAs. Any candidates that fail or cannot be validated
using MS would be validated using an alternate approach (e.g.
PyroSequencing, SNPlex, TaqMan).

*[Other issues]{.underline}*

Our intent in developing this proposal and this document was to provide
a basic and straightforward platform for initiating the work that needs
to be done in the short term to get the Human Cancer Genome Project
moving forward. We believe that the plan we have sketched out here
represents an important start on an achievable scale. It is clear that
defining some of the detailed aspects of the plan will still require
some dialogue, both within the working group and subcommittees, and
between the working group, the participating laboratories and the NHGRI
and NCI staff members.

We have not discussed in detail in this document the state of sample
collection with appropriate informed consent of the patient. All of the
participating laboratories are currently sequencing patient samples
collected using consent protocols consistent with the work being
performed. However, we believe that this is an issue that needs
additional discussion to ensure that appropriate and consistent consent
protocols continue to be utilized, especially as the breadth of data to
be released from single samples increases.

For this proposal, in selecting our sequencing targets we have focused
on coding exons only. It is quite possible that in future work, it may
be useful to expand the scope to include putative promoters, non-coding
exons, highly conserved non-coding elements, etc. However, given the
goals of the demonstration project, we felt it best to limit the current
work to well-defined exons.

The project we propose obviously relies on the current state-of-the-art
technology for DNA sequencing (although there is significant room for
improvement and/or optimization of "front-end" processes and development
of software tools specific to targeted re-sequencing). We considered
including other components that might make use of some of the new
sequencing technologies that are currently becoming available, although
ultimately we decided that this would be premature at this stage. While
the new technologies will clearly have an impact in the next few years,
we decided that the demonstration project would be best served by
utilizing the most stable methods and instrumentation. However, we would
advocate that SC2 continue to think about how new sequencing
technologies (e.g. 454, etc.) might be integrated into the mix, perhaps
late in the demonstration project, utilizing the DNA samples and gene
lists that we propose to use in this project.

**Contributors:**

*[Demonstration proposal working group:]{.underline}*

WU: Rick Wilson, Elaine Mardis, Mike Province, Mark Watson, Howard
McLeod

BI: Eric Lander, Bill Sellers, Matt Meyerson, Stacey Gabriel, Jen
Baldwin, Heidi Greulich

BCM: Richard Gibbs, George Weinstock, Marie-Claude Gingras, John
McPherson

MSKCC: Harold Varmus, William Pao, Marc Ladanyi

*[Subcommittee 1 (SC1):]{.underline}*

Harold Varmus (Chair), Matt Meyerson, Bill Sellers, Mark Watson, Howard
McLeod, Marie-Claude Gingras, William Pao, Marc Ladanyi

*[Subcommittee 2 (SC2):]{.underline}*

Rick Wilson (Chair), Elaine Mardis, Richard Gibbs, John McPherson, Jen
Baldwin, Stacey Gabriel