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EVALUATION OF AUTOMATIC CLASS III DESIGNATION FOR

MSK-IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets)

DECISION SUMMARY

A. DEN Number:

DEN170058

B. Purpose for Submission:

De novo request for evaluation of automatic class III designation for the MSK-IMPACT

C. Measurand:

Somatic single nucleotide variants, insertions, deletions, and microsatellite instability in

genes in human genomic DNA obtained from formalin-fixed, paraffin-embedded tumor

tissue.

Refer to Appendix 1a for complete list of hotspot mutations and Appendix 1b for complete

list of genes included in this assay.

D. Type of Test:

Next generation sequencing tumor profiling test

E. Applicant:

Memorial Sloan Kettering (MSK)

F. Proprietary and Established Names:

MSK-IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets)

G. Regulatory Information:

1. Regulation section:

21 CFR 866.6080

2. Classification:

Class II

3. Product code:

PZM

4. Panel:

Pathology

H. Indications for Use:

1. Indications for Use:

The MSK-IMPACT assay is a qualitative in vitro diagnostic test that uses targeted next

generation sequencing of formalin-fixed paraffin-embedded tumor tissue matched with

normal specimens from patients with solid malignant neoplasms to detect tumor gene

alterations in a broad multi gene panel. The test is intended to provide information on

somatic mutations (point mutations and small insertions and deletions) and microsatellite

instability for use by qualified health care professionals in accordance with professional

guidelines, and is not conclusive or prescriptive for labeled use of any specific

therapeutic product. MSK-IMPACT is a single-site assay performed at Memorial Sloan

Kettering Cancer Center.

2. Special conditions for use statement(s):

For prescription use.

For in vitro diagnostic use.

3. Special instrument requirements:

Illumina HiSeq™ 2500 Sequencer (qualified by MSK)

I. Device Description:

A description of required equipment, software, reagents, vendors, and storage conditions

were provided, and are described in the product labeling (MSK-IMPACT manual). MSK

assumes responsibility for the device.

1. Sample Preparation:

The tumor volume and minimum tumor content needed to obtain sufficient DNA for

testing to achieve the necessary quality performance are shown in the Table 1 below:

Table 1. Specimen Handling and Processing for Validated Specimen Types

Tissue

Type

Volume

Minimum Tumor

Proportion

Macrodissection

requirements

(Based on tumor

proportion)

Limitations

Storage

FFPE

sections

5-20

unstained

sections,

microns

thick

More than 10% of tumor

cells;

sections containing

>20% viable tumor are

preferred.

For MSI testing, >25%

tumor cells.

Yes,

macrodissection

to obtain non-

neoplastic tissue

for analysis

Archival paraffin-

embedded material

subjected to acid

decalcification is

unsuitable for analysis

because acid

decalcification severely

damage nucleic acids.

Room

temp

Genomic DNA is extracted from tissue specimens per protocol. DNA is quantified and

concentrated if necessary. The amount of DNA required to perform the test is 100-250ng.

DNA is run in singlicate. DNA shearing is conducted per protocol and a quality control

check is performed. Average fragment size should be ~200bp. Sheared DNA is stored at

-20°C if not proceeding directly to Library Preparation. The DNA can be stored at 37°C

for 10-20 minutes, stored at 2–8°C for 24 hours, or at –20°C for longer periods.

2. Library Preparation:

Sequence libraries are prepared using KAPA Biosystems Library Preparation Reagents

by first producing blunt-ended, 5’-phosphorylated fragments. To the 3’ ends of the

dsDNA library fragments, dAMP is added (A-tailing). Next, dsDNA adapters with

3’dTMP is ligated to the A-tailed library fragments. Library fragments with appropriate

adapter sequences are amplified via ligation-mediated pre-capture PCR. A quality control

check on the amplified DNA libraries is performed: Samples should be a smear; average

fragment size with the peak at ~200bp; and concentration between 5-300ng/μL to ensure

adequate hybridization for capture.

3. Hybrid Capture NGS:

Library capture is conducted using NimbleGen Capture reagents. Pooled sequencing

libraries are hybridized to the vendor oligo pool. Capture beads are used to pull down the

complex of capture oligos and genomic DNA fragments. Unbound fragments are washed

away. The enriched fragment pool is amplified by ligation mediated-PCR. The success of

the enrichment is measured as a quality control step: Samples should be a smear, average

fragment size with the peak at ~300bp; the concentration of the amplified DNA library

should be 5-45ng/μL; the LM-PCR yield should be ≥ 250ng. Reactions can be stored at

4°C until ready for purification, up to 72 hours.

4. Sequencing and Data Analysis:

Sequencing is conducted with the Illumina HiSeq2500 Sequencing Instruments and

reagents and PhiX Control v3. The sequencing process uses multiple quality checks.

a) Data Management System (DMS): Automated sample tracking and archival of run-

associated metadata (barcode, run name, samples accession number, patient medical

record number, source (class), specimen type, and panel version) is conducted with

the following key functions: Tracking sample status through various stages of data

analysis; tracking iterations of analysis applied to a given sample; recording versions

of databases and algorithms used in analysis; archival of selected pipeline output files

(FASTQ, BAM, VCF) and sequencing run statistics (e.g., cluster density, %clusters

passing filter, unassigned read indices).

b) Demultiplexing and FASTQ generation: The analysis pipeline uses software

provided by Illumina. Two FASTQ files are generated per samples corresponding to

full length forward and reverse reads. Demultiplexing quality control includes quality

metrics for per-base sequence quality, sequence content, GC content and sequence

length distribution, relative percentages of unmatched indices.

c) Indexing QC check: The potential for index contamination is managed by

demultiplexing all sequencing reads for all possible barcodes. If the number of reads

> 15,000 for any unused barcodes, then those reads are analyzed with the pipeline and

the fingerprint SNPs are used to identify which of the barcodes used in the pool could

be causing the appearance of extra reads.

d) Read alignment and BAM generation: Spurious adapter sequences are trimmed

prior to read alignment. Reads are aligned in paired-end mode to the hg19 b37

version of the human genome. Aligned reads are written to a Sequence Alignment

Map (SAM) file, which is then converted into Binary Alignment Map (BAM) format.

PCR duplicates are removed. Each base within a read is assigned a base quality score

by the sequencing software, which reflects the probability an error was made with the

base call. To account for systemic biases that may not accurately reflect the actual

error probabilities observed empirically, the analysis pipeline uses another tool to

adjust the reported quality scores based on the selected covariates. Reassigned quality

scores are subject to a threshold of 20, corresponding to a 1/100 chance of error.

e) Sample QC checks: The baits used for hybridization capture include custom

intergenic and intronic probes targeting >1000 regions throughout the genome

containing common single nucleotide polymorphisms (SNPs). The unique

combination of SNPs specific to a given sample serves as a ‘fingerprint’ for the

identity of the corresponding patient, and serves to identify potential sample mix-ups

and contamination between samples and barcodes. QC checks involving the use of

these ‘fingerprint’ SNPs are detailed below:

i. Sample mix-up check: The analysis pipeline computes the ‘percent discordance’

between a reference and query sample, defined as the percent of homozygous

sites in the reference sample that are homozygous for the alternate allele in the

query sample. The expected discordance between tumors and their respective

matched normal should be low (<5%). Conversely, the expected discordance

between samples from different patients should be high (~ 25%). Pairs of samples

from the same patient with > 5% discordance (“unexpected mismatches”) and

from different patients with <5% discordance (“unexpected matches”) are

flagged.

ii. Sample contamination checks: Alternate alleles (percent heterozygous) at

homozygous SNP sites (fingerprint SNPs) are assessed. A sample is flagged for

review if the average minor allele frequency at these SNPs exceeds 2%.

iii. Check for presence of tumor in normal: Normal samples are expected to be free

of known SNVs and insertions and deletions (indels) that are commonly

(somatically) recurrent in tumor samples. As a first pass check, the pipeline

genotypes normal samples at several known ‘hotspot’ locations derived from

somatic mutation catalogs. If a known tumor-specific mutation (i.e. BRAF

V600E) is detected with mutation frequency > 1% in a normal sample, the normal

sample is flagged for review and possible exclusion from analysis. Tumor

samples with matched normal controls excluded due to possible tumor

contamination will be considered as unmatched tumor samples for subsequent

analyses.

f) Mutation calling – SNVs and Indels: The analysis pipeline identifies two classes of

mutations: (1) single nucleotide variants (SNVs) and (2) indels. Paired sample

mutation calling is performed on tumor samples and their respective matched normal

controls. In instances where a matched normal sample is unavailable, or where the

matched normal sample was sequenced with low coverage (< 50X), tumor samples

will be considered as unmatched samples, and will be compared against a standard,

in-batch pooled FFPE normal control for mutation calling. Filtering is performed to

remove low quality sequence data, sources of sequencing artifacts, and germline

results.

i. Analysis of pooled FFPE positive and negative controls: data from controls is

used to confirm lack of contamination as well as analytical sensitivity.

ii. Filters on sample coverage: A sequence coverage ≥ 100X is required to achieve

95% power to detect mutations with underlying variant frequency of 10% or

greater. To ensure that at least 98% of targeted exons meet this coverage, a per

sample coverage requirement has been conservatively set at ≥ 200X. A lower

coverage threshold for the matched normal is set at 50X.

iii. Filtering for high confidence mutations: Raw SNV and indel calls are subjected to

a series of filtering steps to ensure only high-confidence calls are admitted to the

final step of manual review. These parameters include (1) evidence of it being a

somatic mutation (i.e., ratio between mutation frequencies in the tumor and

normal samples to be ≥ 5.0); (2) whether the mutation is a known hotspot

mutation (refer to Appendix 1a for details); (3) reference on in house ‘standard

normal’ based on common artifacts; (4) technical characteristics that use coverage

depth (DP), number of mutant reads (AD), mutation frequency (VF).

The filtering scheme and threshold are shown in Figure 1 below. The threshold

values for the filtering criteria were established based on paired-sample mutation

analysis on replicates of normal FFPE samples, and optimized to reject all false

positive SNVs and almost all false positive indel calls from the reference dataset.

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