Science - USA (2022-04-22)

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Degasperiet al.,Science 376 , eabl9283 (2022) 22 April 2022 2 of 15


GEL commonICGC common
Hartwig common

GEL rareICGC rare
Hartwig rare

0

5

10

15

20

Number of common and rare SBS signatures
GELICGC
Hartwig

0 500 1000150020002500

0

5

10

15

20

Number of rare SBS signatures and samples
(Pearson corr. 0.76)

samples in each organ

GELICGC
Hartwig

cohort
GEL
ICGC
Hartwig

Total WGS samples
ICGC
3001
Hartwig 3417
12222 GEL

A
1000

2000

3000

samples

SNVs

DNVs

100

102
103
101

10104

1056
107

100

102
103
101

104
10105

1067

Skin Lung
Esophagus
StomachColorectalBladder

Liver
Head_neck

Oral_Oropharyngeal

UterusOvaryBiliaryKidney
Pancreas

BreastProstate

Bone_SoftTissue

CNS
Lymphoid

NET
Myeloid

GEL

Clustering on
mutational profiles
Exclusion of
atypical profiles

(12,222 WGS) (3,001 WGS)
ICGC Hartwig
(3,417 WGS)

Breast Ovary Stomach Uterus Breast Ovary Stomach Uterus Breast Ovary Stomach Uterus

Samples with
commonprofiles

All
samples

Extraction
of commonsignatures

Identify samplesthat contain
additional rare
signatures

Common
Organ-specific
Signatures

Rare
Organ-SpecificSignatures

Total SBS signatures
across organs (757)
135 GELcommon

180 GELrare

135 ICGCcommon

58 ICGCrare

135 Hartwigcommon

114 Hartwigrare

For each organin each cohort

0 500 1000150020002500

0

5

10

15

20

Number of common SBS signatures and samples
(Pearson corr. 0.14)

samples in each organ

GELICGC
Hartwig

B

C

D G

E

F

signatures in each organ

common signatures in each organ

rare signatures in each organ

Organ-specificsignatures
of all three
cohorts
(757)

PatternsDistinct
(187)

Clustering
to determine
Distinct Patterns

Recurrent
Distinct
Patterns(88)

Mixed
Distinct
Patterns(29)

Singleton
Distinct
Patterns(70)

Clustering into
RecurrentReference
Signatures (74)

Determine
composition
Referenceby other
Signatures

Variants of
Recurrent
Reference
Signatures
(24)

Known
signatures
from
other studies
(8)

Additional
previously
unreported
(38)

Reference
Signatures(120 SBS
signatures)

82 QC green SBS signatures 38 QC amber and red SBS signatures

Fig. 1. Whole-genomeÐsequenced cancers across three independent cohorts:
GEL, ICGC, and HMF.(A) WGS cases included in analyses. (B)Numberofsamples
and mutational burden of somatic single-nucleotide variants (SNVs) and double-
nucleotide variants (DNVs) across 21 whole-genomeÐsequenced tumor types from
the GEL, ICGC, and HMF cohorts. Not all tumor types (e.g., esophagus, head and
neck, oropharyngeal) are represented in all three cohorts. (C) Schematic
representation of the workflow of mutational signature analysis. Three cohorts (GEL,
ICGC, and HMF) were evaluated independently. For each organ in each cohort,
mutational catalogs were clustered and samples with atypical catalogs were
excluded from the extraction process. Samples with similar catalogs were subjected


to signature extraction to obtain a set of common organ-specific signatures. These
common signatures were fitted into all samples, highlighting samples with a high
error profile that were subsequently used to identify rare signatures. The pie
chart shows the total number of SBS signatures identified for each independent
extraction of each organ in all three cohorts. (D) Number of common and rare SBS
signatures in each cohort. (E) Common SBS signatures as a function of number
of samples analyzed. (F) Rare SBS signatures as a function of number of samples
analyzed. (G) Procedure to determine the reference signatures from all identified
cohort-organ signatures. Numbers refer to the SBS signature analysis. For details,
see materials and methods.

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