Tracking the Origin of Metastatic Prostate Cancer
Online Supplementary Information
Table of Contents
Supplementary text .................................................................................................................. 1
Patient ....................................................................................................................................... 1
Tissue preparation and histological examination ................................................................. 1
Laser capture microdissection ................................................................................................ 2
DNA extraction ......................................................................................................................... 2
Construction of sequencing libraries...................................................................................... 2
Processing of sequence data .................................................................................................... 2
Identification of copy-number alterations, break-point regions, and similarity................ 3
Supplementary figures ............................................................................................................. 5
Supplementary table ................................................................................................................ 8
References ................................................................................................................................. 9
Supplementary Text
Patient
In this study we examined one case of metastatic prostate cancer in which the patient
underwent radical prostatectomy including pelvic lymphadenectomy at the Karolinska
University Hospital, Stockholm, Sweden, in 2011. The patient presented with elevated serum
prostate-specific antigen (PSA) of 16 ng/ml, and preoperative biopsies revealed a total cancer
extent of 6 mm with Gleason score 4+5=9. The preoperative clinical stage was T2. At the first
postoperative visit to the urology clinic, serum PSA was 0.5 ng/ml and the patient was
considered to have generalized disease. Treatment with bicalutamide was initiated and serum
PSA declined to immeasurable levels (<0.05 ng/ml). Since then the patient has been treated
intermittently with bicalutamide and his serum PSA has varied accordingly. On his last visit
in February 2014, his serum PSA was <0.05 ng/ml.
Tissue preparation and histological examination
The prostate, seminal vesicles, and lymph nodes were cut and totally embedded as previously
described [1]. Microscopic examination of the prostate revealed a bilateral conventional
adenocarcinoma with Gleason score 4+3=7 and tertiary Gleason pattern 5. Metastatic
adenocarcinoma was observed bilaterally in the lymph nodes. The tumor in the prostate
extended from the apex to the base and the maximum extent measured 47 mm  30 mm.
Extraprostatic extension, especially in the area around the base, and bilateral seminal vesicle
invasion were observed. The main tumor originated from the peripheral zone. A small
separate tumor focus was also found in the transition zone. The postoperative stage was
pT3bN1. The slides were reviewed and cancer tissue was outlined with Indian ink. For
genetic analysis, 45 morphologically distinct foci were identified, including conventional
adenocarcinoma (both from the peripheral zone and the transition zone), intraductal
carcinoma (IDC), high-grade prostatic intraepithelial neoplasia, and atrophy. Areas with
extraprostatic extension and seminal vesicle invasion were also included (Supplementary
Table 1). The paraffin blocks were sectioned in 10-m serial sections and mounted on UVtreated membrane slides. The slides were stained with hematoxylin and eosin and stored at
4C before laser capture microdissection (LCM). Immunohistochemical staining for alphamethylacyl-CoA-racemase (AMACR) and p63 was performed according to standard
protocols.
1
Laser capture microdissection
Cells dissected by LCM (Zeiss) were collected in adhesive capsules. The original slides were
examined under a microscope during dissection to ensure that the correct areas were
collected. In some cases the focus was examined, marked, and cut using the LCM microscope
but instead of being catapulted into the adhesive capsule, it was transferred to the capsule
using a sharp knife. In this way larger areas of cells were collected, yielding larger amounts of
DNA, in a shorter period of time. All tumor foci comprised 80–100% tumor cells. Six foci
were excluded because of morphological variation after resectioning. Two samples of normal
tissue were also collected, one containing epithelial cells and the other containing stromal
cells. Photographs were taken before and after dissection. The dissected samples were kept in
a box protected from light at room temperature (18–22C) until they were prepared for DNA
extraction. This study was approved by the Regional Ethics Committee, Stockholm
(registration number 2010/710-31/2).
DNA extraction
Genomic DNA extracted from laser-captured cells was prepared using a QIAamp DNA Micro
Kit (Qiagen) according to the manufacturer’ instructions. The samples were eluted in RNAsefree water and stored at 18C before further genome analysis. Sample quantities were
measured using a Qubit 2.0 fluorometer. The amount of DNA extracted from the samples
varied from 1.3 to 51.6 ng, depending on the size and quality of the dissected area. Six
samples were lost because of manufacturing flaws (leakage from the adhesive capsules during
extraction).
Construction of sequencing libraries
Sequencing libraries for the fresh-frozen primary tissue (SWE-54A), right/left lymph-node
metastases (SWE-54B/SWE-54C), and blood were constructed using an in-house protocol [2].
A ThruPLEX kit (Rubicon Genomics) was chosen to prepare laser-captured tissues according
to a standard protocol because of its superior performance with minute amounts of material.
Library preparation failed for four samples (5_PZ_T1, 6_PZ_T1, 32_PZ_T4, 33_PZ_T4).
Processing of sequence data
Samples SWE-54A–C were processed previously [3]. Adapters were removed and
overlapping reads from the ThruPLEX libraries were merged using SeqPrep software (v. 1.1)
[4] without boosting base qualities. BWA (v. 0.6.2) [5] was used to map the reads to human
2
reference genome GRCh37. SAMtools (v. 0.1.18) [6] was used for various purposes such as
BAM file sorting and sequence quality filtering. Quality metrics were generated via the Picard
(v. 1.84) toolkit [7]. Realignment and recalibration were subsequently performed using the
Genome Analysis toolkit (v. 2.4.7) [8].
Identification of copy-number alterations, break-point regions, and similarity
To infer somatic phylogenetic relationship between the tissues analyzed we adopted a similar
approach to that of Navin et al. [9] with modifications. This involved five basic steps.
1. Identification of a set of genomic regions for a minimum set of reads mapping within
each region.
2. Calculation of log2 ratios relative to a germline DNA source (non-tumor tissue or
blood) for each focus and GC normalization to remove sequencing library preparation
biases.
3. Smoothing and segmentation for identification of break-point regions (BPRs) marking
the start of an amplification or deletion event.
4. Use of BPRs to infer the somatic phylogenetic relationship between all profiled
tissues.
Identification
of a set of genomic regions for a minimum set of reads mapping within each
region
The first region was defined by starting from chromosome 1 and expanding until 75 reads
were accounted for. This process was iteratively continued to the end of chromosome 1 and
for each chromosome separately. Reads mapping in large regions with poor mappability [10]
and regions reported to perform poorly [9] were removed. These regions were subsequently
removed from the final list. DNA from stromal tissue was used to prevent tumor-associated
copy-number alterations (CNAs) from inflating/deflating the number of reads. The stromal
DNA was subsampled to match the sample with the lowest number of uniquely mapping
reads (median of all samples 5 879 978, range 4 779 694–10 542 513). To validate the
robustness of the regions, only those containing 35 reads or more using the epithelial normal
DNA were kept for CNA estimation [9]. This yielded ~45 000 regions with a median size of
~55 kb, a sensitivity limit below the median size of focal CNA events in cancer (deletions 700
kb, amplifications 900 kb) [11].
3
Calculating log2 ratios relative to a germline DNA source for each region and performing
GC normalization to remove library preparation biases
The fresh-frozen primary tumor (SWE-54A) and lymph-node metastases (SWE-54B,C) were
compared to the blood sample, processed simultaneously using the same library preparation
protocol [2]. The tissue foci were compared to the normal epithelial tissue, all prepared using
the Rubicon ThruPLEX kit. Only uniquely mapping single-end reads were accounted for, as
the presence of paired-end is an indication of low read quality, causing SeqPrep to fail
because of merging of short fragments obtained from formalin-fixed, paraffin-embedded
tissues. GC normalization was carried out using the lowess function in R [12]. Visual
inspection confirmed removal of GC biases for all libraries except focus 11_PZ_T1, for which
obvious artifacts remained. This sample was excluded from further processing.
Smoothing and segmentation for BPR identification
The R package DNAcopy [13] was used to smooth and segment the log2 ratios with setting
“prune” to undo local trends in the data. The R package ggplot2 [14], was used to visualize
the CNA data. Obvious false positives, fluctuating around zero with ~10% change in copy
number were removed from downstream processing.
Use of BPRs to infer somatic phylogenetic relationships
To avoid false positives emanating from repetitive regions, any BPRs starting within 10 kb
after the end of a filtered repetitive region (described above) were removed. BPRs starting at
the first region of each chromosome were also removed, as they did not contain any
discriminative information. Adjacent BPRs within 100 kb were labeled as the same event,
which yielded a total of 385 BPRs. Nine foci contained fewer than five BPRs and were
excluded, leaving 25 tissue foci for further analysis, and 28 samples in total with SWEA/B/C. Of the BPRs detected in the right and left lymph-node metastases, 80% were found in
both (62 events). This set of BPRs was used to infer similarity to the two metastases. In
addition, because prostate cancer progression commonly occurs in evolutionary leaps [15], we
used events present in two or more areas to obtain a robust set of BPRs for construction of a
phylogenetic tree. The Euclidean distances for the BPR matrix were fed into the neighborjoining algorithm available in the R package APE [16] to construct the phylogenetic tree.
4
Supplementary Figures
Supplementary Fig. 1 – Whole-mount sections of radical prostatectomy specimen from
patient SWE-54. Cancer tissue is outlined with black Indian ink. Areas harvested by
laser-capture microdissection are marked with dashed lines and numbered.
Histopathological features are listed in Supplementary Table 1. E = extraprostatic
extension. HV, VV = seminal vesicles. II, III = lymph nodes.
5
SP3 53-11
6V
HE
SP353-11
5V
HE
SP353-1 1
6H
HE
SP353-11
HE
5H
30
23
24
21
40
39
16
SP353-11
HE
7V
SP353-11
HE
7H
44
SP353-11
4H
HE
SP353-11
4V
HE
20
25
26
19
22
17
SP353-11
HE
8M
SP353-11
HE
8V
38
SP353-11
HE
8M
18
43
SP353-11
3
HE
45
15
42
14
13
11
12
35
SP353-11
HE
HV
34
10
SP353-11
HE
VV
31
29
SP353-11
HE
2
37
32
9
8
1
28
33
7 6
5
27
4
2
41
3
36
SP353-11
HE
1V
0.0
SP353-11
HE
1M
0.2
0.4
0.6
0.8
Proportion LN-Met
break-point regions
SP353-11
HE
1H
SP353-11
HE
II
SP353-11
HE
III
Failed during preparatio n/QC
Contained <5 BPRs
Supplementary Fig. 2 – Schematic map of the whole-mount sections including somatic
similarity to the metastases for each area investigated. The annotation for each region is
available in Supplementary Table 1. Areas that failed sample preparation, library
preparation, or sequencing quality control are colored light grey. Areas containing
fewer than five break-point regions were excluded from the phylogenetic analysis and
are colored dark grey.
6
Supplementary Fig. 3 – Copy-number alterations used for break point analysis for
8_T1_IDC (intraductal carcinoma), SWE-54C (lymph-node metastasis), 21_PZ_T1
(perineural invasion), SWE-54A (previously profiled fresh-frozen primary tissue), and
area 20_PZ_T1 (highly related to SWE-54A).
7
Supplementary Table
Supplementary Table 1 – Tissue areas investigated using laser-capture microdissection
Areas
Histopathological feature
1–29
Main tumor
7–9
Intraductal carcinoma
30–34
Separate foci in peripheral and transitional zone
10, 18
Extraprostatic extension
27–29
Seminal vesicle invasion
35–39
High grade PIN
40–42
Atrophy
43–44
Benign prostatic hyperplasia
45
Basal cell hyperplasia (with spots of squamous cell metaplasia)
46
Normal tissue, epithelial cells
47
Normal tissue, stromal cells
8
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