Precision proteogenomics reveals pan-cancer impact of germline variants

A icle
P ecision p o eogenomics e eals pan-cance
impac o ge mline a ian s
G aphical abs ac
Highligh s
dP ecision pep idomics e eals ge mline a ian s’ impac on
cance pa ien ’s p o eomes
dGe mline a ian s impac PTMs and p o ein s abili y and
ha e allele-speci ic e ec s
dQTL analyses e eal genes and p o eins unde ge mline
gene ic con ol in cance pa ien s
dPRSs e eal cumula i e impac o common ge mline a ian s
on cance p o eomes
Au ho s
Fe nanda Ma ins Rod igues,
Nadezhda V. Te ekhano a,
Ka hleen J. Imbach, ...,
Edua d Po a-Pa do, Li Ding, Clinical
P o eomic Tumo Analysis Conso ium
Co espondence
[email protected] (Z.H.G.),
ma hew.baile[email p o ec ed] (M.H.B.),
gadge z@b oadins i u e.o g (G.G.),
epo a@ca e as esea ch.o g (E.P.-P.),
[email p o ec ed] (L.D.)
In b ie
P ecision p o eogenomics analysis o
1,064 cance pa ien s ac oss en cance
ypes un eils he ways in which a e and
common ge mline a ian s shape he
cance p o eome; he indings highligh
he con ibu ion o ge mline gene ics in
umo he e ogenei y and oncogenesis.
Ma ins Rod igues e al., 2025, Cell 188, 2312–2335
May 1, 2025 ª2025 The Au ho (s). Published by Else ie Inc.
h ps://doi.o g/10.1016/j.cell.2025.03.026 ll
A icle
P ecision p o eogenomics e eals
pan-cance impac
o ge mline a ian s
Fe nanda Ma ins Rod igues,
1,2,3,31
Nadezhda V. Te ekhano a,
1,2,3,31
Ka hleen J. Imbach,
4,5,31
Ka l R. Clause ,
6,31
My izhi Esai Sel an,
7,8,9,31
Isabel Mendizabal,
10,11,12,32
Yi a Ge en,
6,13,32
Yo Akiyama,
6,32
My anda Mayna d,
6
Tome M. Ya on,
14
Yize Li,
1,2,3
Song Cao,
1,2,3
E ik P. S o s,
1,2,3
Oli ia S. Gonda,
15
Ad ian Gai e-Regue o,
10
Akshay Go indan,
1,2,3
Emily A. Kawale ,
16
Ma hew A. Wyczalkowski,
1,2,3
Robe J. Klein,
7
Be k Tu han,
7
(Au ho lis con inued on nex page)
SUMMARY
We in es iga e heimpac o ge mline a ian s on cance pa ien s’ p o eomes, encompassing1,064 indi iduals
ac oss 10 cance ypes. We in oduced an app oach, ‘‘p ecision pep idomics,’’ mapping 337,469 coding ge m-
line a ian s on o pep ides om pa ien s’ mass spec ome y da a, e ealing hei po en ial impac on pos -
ansla ional modi ica ions, p o ein s abili y, allele-speci ic exp ession, and p o ein s uc u e by le e aging
he ele an p o ein da abases. We iden i ied a e pa hogenic and common ge mline a ian s in cance genes
po en ially a ec ing p o eomic ea u es, including a ian s al e ing p o ein abundance and s uc u e and a -
ian s in kinases (ERBB2 and MAP2K2) impac ing phospho yla ion. P ecision pep idome analysis p edic ed de-
s abilizing e en s in signal- egula o y p o ein alpha (SIRPA) and glial ib illa y acid p o ein (GFAP), ele an o
immunomodula ion and glioblas oma diagnos ics, espec i ely. Genome-wide associa ion s udies iden i ied
quan i a i e ai loci o gene exp ession and p o ein le els, spanning millions o SNPs and housands o p o-
eins. Polygenic isk sco es co ela ed wi h dis al e ec s om isk a ian s. Ou indings emphasize he con i-
bu ion o ge mline gene ics o cance he e ogenei y and high- h oughpu p ecision pep idomics.
INTRODUCTION
The ge mline genome o each indi idual pe son has a unique
combina ion o millions o gene ic a ian s ha in luence i ually
all biological p ocesses h oughou li e, including cance e olu-
ion. Many s udies ha e demons a ed he c i ical impo ance
o ge mline genomics, om cance isk assessmen o he de el-
opmen o ailo ed ea men s.
1
The ea lies ge mline genomics
1
Depa men o Medicine, Washing on Uni e si y in S . Louis, Sain Louis, MO, USA
2
McDonnell Genome Ins i u e, Washing on Uni e si y in S . Louis, Sain Louis, MO, USA
3
Depa men o Gene ics, Washing on Uni e si y in S . Louis, S . Louis, MO 63110, USA
4
Josep Ca e as Leukaemia Resea ch Ins i u e (IJC), Badalona, Ba celona, Spain
5
Uni e si a Au onoma de Ba celona, Ba celona, Spain
6
B oad Ins i u e o MIT and Ha a d, Camb idge, MA, USA
7
Depa men o Gene ics and Genomic Sciences, Icahn School o Medicine a Moun Sinai, New Yo k, NY, USA
8
Cen e o Tho acic Oncology, Tisch Cance Ins i u e, Icahn School o Medicine a Moun Sinai, New Yo k, NY, USA
9
P ecision Immunology Ins i u e, Icahn School o Medicine a Moun Sinai, New Yo k, NY, USA
10
Cen e o Coope a i e Resea ch in Biosciences (CIC bioGUNE), Basque Resea ch and Technology Alliance (BRTA), Bizkaia Technology
Pa k, De io, Spain
11
Ike basque, Basque Founda ion o Science, Bilbao, Spain
12
T ansla ional P os a e Cance Resea ch Lab, CIC bioGUNE-Basu o, Bioc uces Bizkaia Heal h Resea ch Ins i u e, De io, Spain
13
Cance Cen e and Depa men o Pa hology, Massachuse s Gene al Hospi al, Bos on, MA, USA
14
Meye Cance Cen e , Depa men o Medicine, Depa men o Physiology and Biophysics, Weill Co nell Medicine, New Yo k, NY, USA
15
Depa men o Biology, B igham Young Uni e si y, Sal Lake Ci y, UT, USA
16
Applied Bioin o ma ics Labo a o ies, New Yo k Uni e si y Langone Heal h, New Yo k Ci y, NY, USA
17
Depa men o Pa hology, Uni e si y o Michigan, Ann A bo , MI, USA
18
Depa men o Compu a ional Medicine and Bioin o ma ics, Uni e si y o Michigan, Ann A bo , MI, USA
19
Ins i u e o Sys ems Gene ics, NYU G ossman School o Medicine, New Yo k, NY, USA
20
Depa men o Public Heal h Sciences, Uni e si y o Miami Mille School o Medicine, Miami, FL, USA
(A ilia ions con inued on nex page)
ll
OPEN ACCESS
2312 Cell 188, 2312–2335, May 1, 2025 ª2025 The Au ho (s). Published by Else ie Inc.
This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/).
s udies o cance -p one amilies iden i ied highly pene an isk
genes.
2–6
These a ge ed-gene and linkage s udies we e ol-
lowed by a ay-based genome-wide associa ion s udies
(GWASs), which iden i ied many common a ian s (mino allele
equency [MAF] R1%) associa ed wi h issue-speci ic
7,8
o
pan-cance isk.
9
While common isk a ian s ypically ha e
small e ec sizes when seen indi idually, hey disc imina e indi-
iduals a high isk when combined as polygenic isk sco es
(PRSs).
10,11
Fu he mo e, many common ge mline a ian s egu-
la e p oximal and dis al exp ession o genes in speci ic issues
and umo s wi h po en ially addi i e e ec s.
12,13
Wi h ad ances in sequencing echnologies, i has
become easible o iden i y a e and low- equency a ian s
(MAF < 1%) wi h mode a e o high pene ance, associa ed
wi h issue-speci ic
14,15
o o e all cance isk,
16–18
mecha-
nisms and pa hways in umo de elopmen ,
19
umo immune
mic oen i onmen ,
20,21
mu a ional bu den,
22,23
mu a ional sig-
na u es,
24,25
loss o he e ozygosi y (LOH),
19
and clinical a i-
ables such as age o cance onse
16,22
and su i al.
26
Howe -
e , he impac o ge mline a ian s on he cance p o eome
and pos - ansla ional modi ica ion (PTM) landscapes is
poo ly unde s ood, speci ically on oncogenic signaling pa h-
ways and hei impac on cance o ma ion and e olu ion.
We analyzed he pan-cance Clinical P o eomic Tumo Anal-
ysis Conso ium (CPTAC) da ase s om genomic, ansc ip-
omic, p o eomic, ace ylomic, and phosphop o eomic analy es
o gene a e p ecision p o eogenomic p o iles. These da ase s
p o ide a unique esou ce o s udy he impac o ge mline
genomics on molecula oncogenic p ocesses. In eg a i e
mul i-omic analyses e ealed new pu a i e pa hogenic
(P) a e ge mline a ian s in cance p edisposi ion genes
(CPGs). Fu he mo e, common a ian s in hese genes we e
associa ed wi h educed le els o umo supp esso s in bo h
p ima y umo s and no mal adjacen issues (NATs). Addi ion-
ally, common ge mline a ian s a speci ic p o ein phospho y-
la ion and ace yla ion si es in luenced phospho yla ion and
ace yla ion le els o esul ed in he eme gence o new PTM
si es. Ou p ecision pep idomics da a also iden i ied allele-spe-
ci ic p o ein and PTM (ASP) e ec s and ge mline indels associ-
a ed wi h p o ein s abiliza ion, des abiliza ion, o al e na i e
p oduc s. Finally, whole-genome sequencing (WGS) and quan-
i a i e ai loci (QTL) analyses iden i ied common a ian s
a ec ing p o ein exp ession le els in no mal and umo issues,
impac ing cance -associa ed pa hways. Ou esul s highligh
he powe o in eg a i e mul i-omic app oaches o illumina e
he impac o ge mline a ian s ac oss cance pheno ypes,
e ealing impo an biological insigh s in o he ole o ge mline
genomics. These indings sugges ha p ecision p o eoge-
nomics could in o m pa ien isk s a i ica ion and p e en ion
and in e cep ion app oaches.
RESULTS
P ecision pep idomic and PTM analysis o coding
ge mline a ian s
CPTAC p o ides a p o eogenomic da ase ha includes com-
mon and a e ge mline a ian s ac oss 10 cance ypes. We p o-
cessed and analyzed p o eogenomic, clinical, and demog aphic
da a om 1,064 p ospec i ely collec ed umo and ma ching
blood samples, including: whole-exome sequencing (WES),
RNA sequencing (RNA-seq), p o eome, and phosphop o eome
da a om all 10 cance ypes; WGS om se en cance ypes;
and, ace ylome da a om six (Figu e 1A). CPTAC also includes
p o eogenomic da a om pai ed NATs om eigh cance
ypes (n= 548/1,064 cases). All 1,064 ma ching blood samples
passed WES quali y con ol c i e ia and we e used o ge m-
line a ian calling, wi h a e age co e age anging be ween
1053and 3573ac oss a ge egions, and o e all co e age o
253–2803ac oss a p io i ized lis o 160 CPGs (STAR Me hods;
Figu es S1A and S1B; Table S1).
Ka s en K ug,
6
D.R. Mani,
6
Felipe da Veiga Lep e os ,
17
Alexey I. Nes izhskii,
17,18
S e en A. Ca ,
6
Da id Fenyo
¨,
19
Michael A. Gille e,
6
An onio Colap ico,
20,21
An onio Ia a one,
21,22
Ana I. Robles,
23
Kuan-lin Huang,
7,24
Chandan Kuma -Sinha,
17,25
F anc¸ ois Ague ,
6
Alexande J. Laza ,
26
Lewis C. Can ley,
27
U ko M. Ma igo a,
10,11
Zeynep H. Gu¨mu¨sx,
7,8,9,
*Ma hew H. Bailey,
15,
*Gad Ge z,
6,13,28,
*Edua d Po a-Pa do,
4,29,
*Li Ding,
1,2,3,30,33,
*and Clinical
P o eomic Tumo Analysis Conso ium
21
Syl es e Comp ehensi e Cance Cen e , Uni e si y o Miami Mille School o Medicine, Miami, FL, USA
22
Depa men o Neu ological Su ge y, Depa men o Biochemis y and Molecula Biology, Uni e si y o Miami, Mille School o Medicine,
Miami, FL, USA
23
O ice o Cance Clinical P o eomics Resea ch, Na ional Cance Ins i u e, Rock ille, MD, USA
24
Cen e o T ans o ma i e Disease Modeling, Tisch Cance Ins i u e, Icahn Ins i u e o Da a Science and Genomic Technology, Icahn
School o Medicine a Moun Sinai, New Yo k, NY, USA
25
Michigan Cen e o T ansla ional Pa hology, Uni e si y o Michigan, Ann A bo , MI, USA
26
Depa men s o Pa hology and Genomic Medicine, The Uni e si y o Texas MD Ande son Cance Cen e , Hous on, TX, USA
27
Dana Fa be Cance Ins i u e, Bos on, MA, USA
28
Ha a d Medical School, Bos on, MA, USA
29
Ba celona Supe compu ing Cen e (BSC), Ba celona, Spain
30
Si eman Cance Cen e , Washing on Uni e si y in S . Louis, Sain Louis, MO, USA
31
These au ho s con ibu ed equally
32
These au ho s con ibu ed equally
33
Lead con ac
*Co espondence: zeynep.g[email p o ec ed] (Z.H.G.), ma hew.bai[email p o ec ed] (M.H.B.), [email p o ec ed] (G.G.), epo a@
ca e as esea ch.o g (E.P.-P.), lding@wus l.edu (L.D.)
h ps://doi.o g/10.1016/j.cell.2025.03.026
ll
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Cell 188, 2312–2335, May 1, 2025 2313
A icle
A o al o 185,724,997 ge mline a ian s we e called om WES
da a (STAR Me hods). Va ian s we e il e ed and anno a ed, e-
sul ing in 27,104,152 ge mline a ian calls (563,036 unique a -
ian s) in exonic egions (25,474 a ian s pe sample). Indi id-
uals o A ican gene ic ances y (AFR) showed he highes
a e age numbe o exonic ge mline a ian s pe indi idual
(30,510), wi h he lowes being o hose o Eu opean (EUR)
ances y (25,205; Figu e S1C). The ge mline exomes exhibi ed
an a e age ansi ion- ans e sion (TiT ) a io o 2.74%
and >99% conco dance wi h dbSNP (Figu e S1D). We de i ed
ances al (ANC) s a us in o ma ion o 27,104,152 exonic ge m-
line a ian s (STAR Me hods). Th oughou his manusc ip , we
e e o indi idual a ian s in e ms o ANC o de i ed (DER) al-
leles ins ead o majo and mino alleles, espec i ely, acco ding
o hei ANC s a us.
We also cha ac e ized he impac o non-coding a ian s on
gene exp ession and p o ein abundance in 779 CPTAC samples
om se en cance ypes o which WGS da a we e a ailable
(STAR Me hods). Gi en he low-pass na u e o ou WGS da ase ,
we phased and impu ed he geno ypes using GLIMPSE
27
using a
se o high-quali y a ian s om 2,504 un ela ed samples om
Phase 3 o he 1,000 Genomes P ojec , which we e esequenced
o high co e age by he New Yo k Genome Cen e (NYGC).
28
Fo
quali y con ol, a ian s called om WGS and WES we e
compa ed o he se en cance ypes (STAR Me hods). O e all,
94.6% o a ian s o e lapping be ween WES and WGS had he
same geno ypes in he same samples (Figu e S1E; Table S1D).
WGS da a was also used o con i m gene ic ances y p edic-
ions ob ained om WES. Ances y was i s p edic ed om
WES using a andom o es classi ie o all indi iduals (STAR
Me hods), while WGS was used o e ine ances y o 9 indi id-
uals o Sla ic o igin in he glioblas oma (GBM), head and neck
squamous cell ca cinoma (HNSCC), lung squamous cell ca ci-
noma (LSCC), panc ea ic duc al adenoca cinoma (PDAC), and
A
BC
Figu e 1. CPTAC da ase o e iew and p ecision pep idomics wo k low
(A) The CPTAC coho o 1,064 indi iduals o di e en gene ic ances ies ac oss 10 cance ypes and a ailable da a ypes. Colo s in op dis ibu ion ep esen
gene ic ances y: A ican (AFR); admixed Ame ican (AMR); Eas Asian (EAS); Eu opean (EUR); Sou h Asian (SAS).
(B) Ou p ecision pep idomics wo k low, ep esen ing he implemen a ion o he Spec um Mill wo k low on he LC-MS/MS da ase s o yield pep ide spec um
ma ches (PSMs) ha de ec ed 18,599 ge mline a ian s in he p o eome, phosphop o eome, and ace ylome da ase s.
(C) O e iew o phospho yla ion (uppe ) and ace yla ion (lowe ) si es a ec ed by ge mline a ian s ac oss cance ypes based on he p ecision pep ide da a.
Va ian s occu nea by o di ec ly a he si e, wi h 78% o phosphosi es and 84% o ace ylsi es ha ing ge mline a ian s loca ed a 10 o ewe amino acids om he
PTM si e.
See also Figu e S1.
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2314 Cell 188, 2312–2335, May 1, 2025
A icle
A
C
EF
D
B
Figu e 2. Impac o a e pa hogenic and common ge mline a ian s on gene and p o ein exp ession
(A) Schema ic o il e ing and classi ica ion o ge mline a ian s. Pu ple boxes desc ibe he p io i iza ion p ocedu e o a e a ian s; yellow boxes show p o-
cessing o common a ian s.
(B) (Le ) Dis ibu ion o a e pa hogenic/likely pa hogenic (P/LP) a ian s ac oss 10 cance ypes. (Righ ) Dis ibu ion o a ian s p e iously epo ed in any o he
TCGA, gnomAD, and UKBB da ase s (ligh blue) o no el o his s udy (da k blue).
(C) Gene exp ession (x axis) and p o ein abundance (y axis) quan iles o p o eins om P/LP a ian ca ie s. Yellow and pink shading indica es a ian s wi h impac
on p o ein le els and gene exp ession, espec i ely; g ay deno es a ian s wi h e ec in bo h.
(legend con inued on nex page)
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Cell 188, 2312–2335, May 1, 2025 2315
A icle

u e ine co pus endome ial ca cinoma (UCEC) coho s
which we e misclassi ied in he WES-based p edic ions, bu
co ec ly classi ied as EUR using WGS (Figu e S1F; STAR
Me hods).
Nex , we combined p o eomics and genomics da ase s o
c ea e p o ein sequence da abases o each indi idual using
he p o eogenomic in eg a ion ool Quan i a i e In eg a ed Li-
b a y o T ansla ed SNPs/Splicing (QUILTS)
29
(STAR Me hods).
F om he o al o 185,724,997 ge mline a ian s om WES, we
inco po a ed 337,469 unique pa ien -speci ic coding a ian s
ha mapped o Gencode 34 e e ence p o ein sequences (Fig-
u e 1B). Using hese da abases o each cance coho , he p o-
eomics liquid ch oma og aphy- andem mass spec ome y
(LC-MS/MS) da ase s we e sea ched wi h he Spec um Mill
wo k low (STAR Me hods) o yield pep ide spec um ma ches
(PSMs) ha ma ched pep ides om he e e ence p o eome,
ge mline a ian s, o soma ic mu a ions. We de ec ed pep ides
o 18,599 unique coding ge mline a ian s in he p o eome,
phosphop o eome, and ace ylome, wi h he majo i y ha ing
low equencies a he coho le el. Among he a ian s de ec ed,
1,828 we e in mo e han one da ase , while he majo i y we e in
only one: 12,330 in he p o eome, 4,081 in he phosphop o-
eome, and 360 in he ace ylome (Figu e 1B). Sc u iny o he
loca ion o hese a ian s e ealed 8,046 PTM si es (7,353 phos-
phosi es and 693 ace yla ion si es) a ec ed by ge mline a ian s,
150 o which we e de ec ed ac oss all cance s and 5,459 de-
ec ed in a single cance (Figu e 1C). The pa e n o high can-
ce - ype speci ici y o PTM si es is consis en wi h ou p e ious
s udy
30
and sugges s a ole o PTMs in issue/cell-speci ic egu-
la ion and signaling.
Looking a he pep ide-leng h dis ibu ion o e e ence and
al e na i e alleles (Figu e S1G), he e is a endency o pep ides
ca ying he al e na i e allele o be longe han all e e ence p o-
eome-de i ed pep ides, ega dless o he speci ic p o eomics
da ase (p o ein, phospho yla ion, o ace yla ion). While he
highe minimum-sco e h esholds employed in he subse spe-
ci ic alse disco e y a e (ssFDR) il e ing o he p o eome da a-
se o main ain sui able alse disco e y a e (FDR) le els will
bias agains sho e pep ides, a andom a ian in a p o ein is
mo e likely o occu in a pep ide ha spans a longe p opo ion
o ha p o ein.
P o eogenomic modeling o a e pa hogenic and
common ge mline a ian s
Ge mline a ian s associa ed wi h cance likely ha e di e en P
mechanisms depending on allele equency (AF): a e P a ian s
a e o en imes mo e damaging o p o ein unc ion han common
a ian s.
31,32
He e, we in es iga ed he landscape o a e P and
common ge mline a ian s in he CPTAC coho , le e aging
mul i-omics in o ma ion om umo and ma ching NAT samples.
F om 27,104,152 o al exonic ge mline a ian s, a mino i y o
hem we e a e (1,528,083 a ian s; gnomAD AF %0.05%), ol-
lowed by low equency (993,176; 0.05% < gnomAD AF < 1%),
and common a ian s (24,582,893, gnomAD AF R1%; Fig-
u e 2A). These p opo ions a e simila o o he la ge-scale da a-
bases o popula ion genomics, such as UK Biobank (UKBB).
Conside ing ha a e P ge mline a ian s play impo an oles
in cance suscep ibili y,
16,18
we aimed o iden i y such e en s us-
ing Cha Ge
33
(STAR Me hods;Figu es 2A and S2). We iden i ied
119 P and likely pa hogenic (LP) a ian s ac oss CPGs (Table S1)
a ec ing 115 indi iduals (10.8% o he coho ; Figu e 2B). The
majo i y o P/LP a ian s likely ep esen loss-o - unc ion e en s
(i.e., nonsense, ameshi , s a -loss, and splice-si e a ian s;
75%, n= 89), wi h he emaining being missense a ian s p e-
dic ed o be dele e ious (n= 30; Table S2). These a ian s we e
also obse ed in o he coho s (The Cance Genome A las
[TCGA],
16
gnomAD, and UKBB) a ex emely low equencies
(mean gnomAD AF = 0.0001, and mean UKBB AF = 0.0002).
Fu he mo e, 34 a ian s (29%) we e p i a e o he CPTAC
coho (Figu e 2B). We also obse ed ha ca ie s we e younge
a diagnosis compa ed wi h non-ca ie s o he b eas cance
(BRCA), colo ec al adenoca cinoma (COAD), and clea cell enal
cell ca cinoma (ccRCC) coho s (Figu e S2A).
To e alua e he impac o ge mline a ian s in a soma ic
con ex , we in es iga ed LOH e en s using allele ac ions om
umo -no mal da a o iden i y a ian s posi i ely selec ed in he
umo based on he wo-hi hypo hesis
17,34,35
(STAR Me hods).
F om 119 P/LP a ian s, we obse ed 21 (17.6%) and 11
(9.2%) a ian s unde going signi ican (FDR %0.05) and sugges-
i e (0.05 < FDR %0.15) LOH in he umo , espec i ely
(Figu e S2C). Fo 15 o 21 (71%) signi ican LOH, we obse ed
dele ion o he espec i e gene de ec ed by he ool Genomic
Iden i ica ion o Signi ican Ta ge s in Cance , e sion 2
(GISTIC2).
36
Also, 6 (5%) o 119 P/LP a ian s co-occu ed
wi h non-silen soma ic mu a ions in he same gene.
Nex , we explo ed he molecula consequences o hese 119
P/LP a ian s using p o ein and RNA exp ession da a, ocusing
on 65 P/LP a ian s o which bo h RNA and p o ein le els
we e a ailable. Consis en wi h a loss-o - unc ion pheno ype,
P/LP a ian ca ie s displayed lowe RNA exp ession and p o-
ein le els (wi hin-cance - ype quan ile means o 0.36 and
0.29, espec i ely, compa ed wi h 0.5 o he en i e coho ;
Figu es 2C and S2D). This was obse ed o a ian s a ec ing
membe s o he misma ch epai (MMR) pa hway (PMS2,
MSH2, and MSH6) associa ed wi h low RNA exp ession and p o-
ein le els (exp ession quan iles < 0.25). We obse ed ha 4 o 5
ca ie s o P/LP a ian s in hose genes (MSH2 L277*, MSH6
E744 s, MSH2 Q518*, and PMS2 I611 s) we e also iden i ied as
mic osa elli e ins abili y (MSI)-high samples (Table S1 om Li
e al.
37
), consis en wi h he ac ha ca ie s o P/LP a ian s
(D) E ec s o common ge mline a ian s in cance genes in hei p o ein abundance (y axis) and RNA exp ession (x axis). E ec is calcula ed as he slope in he
eg ession model. Do size e lec s he log
10
o he FDR adjus ed p alues om he eg ession model.
(E) P o ein le els (y axis) in NAT o umo samples o ATM, SDHA, and ERCC2 acco ding o geno ype (x axis). p alues om pai wise Wilcoxon es s be ween
geno ype g oups a e p o ided, and da a a e ep esen ed as median and in e qua ile ange.
(F) Mapping o he ERCC2 K751 posi ion on he PDB: 6RO4. Blue ep esen s he esidue, g ay deno es ERCC2, pink ep esen s ERCC3, o ange highligh s he
DNA molecule.
See also Figu e S2.
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2316 Cell 188, 2312–2335, May 1, 2025
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A
B
EF
D
C
Figu e 3. Impac o missense ge mline a ian s on PTM si es based on linea dis ances
(A) Depic ion o how missense a ian s may impac PTM si es based on linea dis ances: di ec hi (colocalizes wi h PTM si e); p oximal (wi hin 5 amino acids); o
dis al (loca ed beyond 5 amino acids). C ea ed in Bio ende .
(B) Di ec hi s a e classi ied based on hei consequence: loss, change, and gain. C ea ed in Bio ende .
(C) Dis ibu ion o di ec , p oximal, and dis al e en s de ec ed in CPTAC, beside a ba plo summa izing he dis ibu ion o di ec hi s ac oss he op 30 cance -
ela ed genes.
(D) Signi icance (y axis) and e ec (x axis) o di ec -hi e en s on global p o ein le els in NATs (le ) and umo samples ( igh ) om linea model esul s. Poin s a e
colo ed by a ian consequence and shaped acco ding o PTM ype. E ec (x axis) is calcula ed as he slope in he eg ession model, and y axis e lec s he
log
10
o he FDR adjus ed p alues om model.
(E) Signi icance (y axis) and e ec (x axis) o p oximal o dis al a ian s in cance - ela ed genes on phospho yla ion and ace yla ion le els o hei co esponding
PTM si es in NATs (le ) and umo s ( igh ). (Top and bo om) Resul s om a e/low equency (gnomAD AF < 1%) and common a ian s (gnomAD AF R1%),
espec i ely. Colo s ep esen a ian dis ance o he PTM si es; shapes ep esen PTM ype; and sizes ep esen he equency o he e en in he CPTAC coho
(pan-cance le el). Only e en s o which p o ein abundance di e ences we e no obse ed a e labeled. E en s in HLA-A and HLA-B we e emo ed om common
(legend con inued on nex page)
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Cell 188, 2312–2335, May 1, 2025 2317
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in co e MMR pa hway genes end o de elop an MSI cance
pheno ype.
38
Mos a ian s had compa able quan iles o bo h
gene and p o ein exp ession ( ho = 0.49, p= 3.08 310
5
;Fig-
u e 2C). In e es ingly, we also obse ed ou lie s, including
TP53 M1I, ERCC2 A717G, and ATM L1283 s, which we e asso-
cia ed wi h high RNA exp ession bu low p o ein abundance o
he espec i e genes, highligh ing he impo ance o p o eomics
o assess he unc ional impac o a ian s.
Nex , we explo ed he po en ial e ec s o common ge mline
a ian s (gnomAD AF R1%) in ou lis o 160 CPGs and 299 can-
ce d i e genes
37,39
(Figu e 2D). We obse ed a ian s in ATM,
SDHA, and ERCC2 wi h no de ec able e ec on RNA exp ession,
bu lowe p o ein le els in ca ie s o he DER alleles in umo and
ma ched NAT samples (Figu e 2E). ERCC2 K751Q has been
associa ed wi h lowe DNA- epai ac i i y in i o and be e ou -
comes in pa ien s ea ed wi h chemo he apy,
40,41
consis en
wi h he DER allele lowe ing DNA- epai e iciency. A s uc u al
alignmen o he AlphaFold2 model o ERCC2 (P o ein Da a
Bank [PDB]: 6RO4) sugges s ha K751 could si a he binding
in e ace be ween ERCC2 and ERCC3 (Figu e 2F). This, oge he
wi h p e ious in i o and clinical da a, and lowe p o ein le els,
sugges s ha he DER allele may damage he s abili y o he
complex. Fu he expe imen s a e needed o alida e his hy-
po hesis. In conclusion, he o e all lowe p o ein le els o co e
p o eins o he DNA- epai machine y sugges ha , e en i hese
a e common a ian s and wi h no de ec able e ec s a he RNA
le el, hey could po en ially ha e impo an clinical impac s.
Di ec , p oximal, and dis al e ec s o ge mline a ian s
on PTM si es
Ge mline a ian s may media e cance isk h ough dys egula-
ion o signaling pa hways.
42,43
Fo example, a ian s migh
change a PTM si e o ab oga e i s abili y o become phospho y-
la ed o ace yla ed
44–48
o al e he mo i s ha make i ecogniz-
able by enzymes, making i mo e o less likely o become modi-
ied. We explo ed he impac o a e/low equency (gnomAD
AF < 1%) and common (gnomAD AF R1%) missense a ian s
co-localizing, p oximal (wi hin 5 amino acids), o dis al (beyond
5 amino acids) o PTM si es a he linea dis ance (Figu e 3A).
Fo ge mline a ian s di ec ly o e lapping a PTM si e, h ee sce-
na ios we e assessed: (1) loss o a PTM si e; (2) c ea ion o a new
si e; o , in he case o phospho yla ions, (3) change o he sub-
s a e, e.g., se ine o h eonine (Figu e 3B). To ocus on p o-
ein-coding a ian s, we e alua ed missense ge mline a ian s
om WES o iden i y e e ence pep ides in he (phopsho/
ace yl)p o eomics da ase s wi h he ma ching amino acids o
bo h alleles ac oss he en i e coho (STAR Me hods). We
obse ed 532,142 p oximal, dis al, and di ec -hi e en s
in ol ing single phospho yla ion si es and 42,014 e en s
in ol ing ace yla ion si es. O hese, 1,706 a ian s di ec ly o e -
lapped a si e, 4,660 we e p oximal, and 567,790 we e dis al o a
si e on he same p o ein (Figu e 3C; Table S3). Mos PTM- ela ed
gene ic a ian s (92.6%) we e associa ed wi h phospho yla ion
a he han ace yla ion si es, e lec ing he highe abundance o
phospho yla ion PTMs in ou da ase (Figu es 1A and 3C).
Rega ding a ian s o e lapping a PTM si e, PTM losses we e
he mos equen e en s: 1,578 losses de ec ed ac oss all p o-
eins, compa ed o 120 gain and 8 changes (Figu e 3C). O hese,
we obse e 115 loss and 5 gain e en s ac oss he lis s o 160
CPGs (Table S1), 299 cance d i e genes,
37,39
and 624
o he cance genes
17
including ATRX,BRCA1,TP53BP1, and
PARP4 (Figu e 3C; Table S3). Samples wi h a ian s a ec ing
PTMs in hese p o eins displayed di e ences in p o ein abun-
dance compa ed wi h hose wi h e e ence alleles (STAR
Me hods). Speci ically, 16 p o eins wi h a ian s loca ed a a
PTM si e exhibi ed signi ican dys egula ion in NATs, o which
14 we e also obse ed in umo s (gene alized linea model
[GLM] FDR %0.05; Figu e 3D; Table S3). Fo example, we no ed
a small bu s a is ically signi ican inc ease in he le el o DEP
con aining MTOR in e ac ing p o ein (DEPTOR) in he p esence
o he S389N phosphosi e loss allele. DEPTOR is associa ed
wi h supp ession o he mechanis ic a ge o apamycyin kinase
(mTOR) complexes 1/2 (mTORC1/2),
49
and he S389N a ian
( s4871827, gnomAD AF = 0.33) is a he in e ace be ween
DEPTOR and mTOR.
50
To unde s and whe he his a ian has
b oade mTOR pa hway e ec s, we es ed o changes in p o-
eins o phosphop o eins in pa hway membe s be ween a ian
ca ie s and non-ca ie s (STAR Me hods), as e en modes
changes in p o ein abundance may elici downs eam e ec s
(Table S3). We ound a sligh dec ease in MAP2K2 T25 phos-
pho yla ion le els in HNSCC (GLM FDR = 0.0163; Wilcoxon
FDR = 0.00097 be ween non-ca ie s and he e ozygous (HET) in-
di iduals; Figu e S3A). In PDAC, EIF4EBP1 showed dec eased
phospho yla ion a S83/S101 and T36/T37 (GLM FDR = 0.02
and 0.027, espec i ely). Mo eo e , pa ien s homozygous o
he DER allele o DEPTOR S389N showed he lowes phospho -
yla ion le els a bo h EIF4EBP1 si es (Wilcoxon FDR = 0.018 and
0.036, espec i ely; Figu es S3B and S3C; Table S3). The T37
si e in EIF4EBP1 is in ol ed in hype phospho yla ion-dependen
dis up ion o eIF4E binding.
51
Beyond DEPTOR, se e al o he
PTM-o e lapping a ian s showed associa ions wi h phospho -
yla ion le els o pa hway membe s, including ERBB2 P1170A
on PAK1 S220s/T225 phospho yla ion in he pan-cance coho
(GLM FDR = 0.043; Figu e S3D), HLA-B V69A on HSP90AA1
S763s phospho yla ion in BRCA (GLM FDR = 0.005; Figu e S3E),
and CASP8 D344H on SEPTIN4 S605s phospho yla ion in GBM
(GLM FDR = 0.048; Figu e S3F).
Nex , we quan i ied he associa ion o p oximal o dis al a i-
an s wi h phospho yla ion/ace yla ion abundance di e ences
on e e ence pep ides a he pan-cance le el (STAR Me hods).
Fo a e/low- equency a ian s, o inc ease s a is ical powe ,
we collapsed all indi iduals ha bo ing a p oximal o dis al a ian
in o a single a iable a he gene le el (STAR Me hods). We
iden i ied 46 a ian s associa ed wi h phospho yla ion and
a ian esul s (bo om) (see Table S3D o comple e lis o es ed e en s and Table S3E o p o ein abundance di e ences esul s). E ec (x axis) is calcula ed as
he slope in he eg ession model, and y axis e lec s he log
10
o he FDR adjus ed p alues om he model.
(F) PTM le els acco ding o pa ien geno ype s a us o a ian s p oximal ( op) and dis al (bo om) o he si es. FDR adjus ed p alues om pai wise Wilcoxon es s
be ween geno ype g oups a e p o ided, and da a a e ep esen ed as median and in e qua ile ange.
See also Figu e S3.
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2318 Cell 188, 2312–2335, May 1, 2025
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A
C
E
D
B
Figu e 4. Spa ially in e ac ing missense ge mline a ian s, soma ic mu a ions, and PTM si es
(A) Depic ion o how missense ge mline a ian s and soma ic mu a ions may in e ac wi h PTM si es based on spa ial dis ances, showing an o e iew o Ho Pho
analyses, which map inpu mu a ions and PTM si es on o p o ein s uc u es. C ea ed in Bio ende .
(B) Ho Pho pipeline. C ea ed in Bio ende .
(C) (Le ) Numbe o in amolecula hyb id clus e s in cance - ela ed p o eins de ec ed in AFDB and PDB (inne ). (Righ ) Numbe o ge mline a ian s and soma ic
mu a ions in each hyb id clus e ha a e di ec ly o e lapping a PTM si e in he same clus e a a linea dis ance (di ec ), wi hin 5 amino acids (p oximal), o beyond
5 amino acids (dis al).
(D) P o ein le el di e ences in samples in ol ed in hyb id clus e s de ec ed in AlphaFoldDB s uc u es s. no . Do s ep esen a clus e , whe e colo depic s i s
ype based on in ol ed e en s. AFDB clus e ID is shown beside p o ein names. E ec (x axis) is calcula ed as he slope in he eg ession model, and y axis
e lec s he log
10
o he FDR adjus ed p alues om he model.
(legend con inued on nex page)
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Cell 188, 2312–2335, May 1, 2025 2319
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OAS1, CARD8, CASP7, and ITIH1 (Figu e S6). We highligh a
no el associa ion be ween a common a ian in he 30UTR and
p o ein exp ession o he glial ib illa y acid p o ein (GFAP) in
GBM umo s (Figu e 6E, op x axis). No associa ion is de ec able
be ween indel ca ie s and non-ca ie s a RNA exp ession le el,
bu he e is a d as ic shi in p o ein abundance (Figu e 6E, igh y
axis, Welch’s es p alue = 1.323 310
8
). This associa ion
ound in he UTR o GFAP has no been p e iously epo ed,
p obably because o i s lack o in luence on RNA le els and
sca ce p o eomics da a in his disease. GFAP is a c i ical GBM
bioma ke ,
145
and a ‘‘p omising he apeu ic a ge ’’
146
. A b eak-
down o ca ie s and non-ca ie s a he pep ide le el indica ed
an inc ease in he abundance and s abili y o he en i e p o ein
(Figu e 6F). Fu he mo e, miRWalk,
147
an miRNA binding p edic-
ion ool, sugges s s ong binding o miR-137 a his indel si e.
Collec i ely, hese analyses unde sco e he u ili y o mul i-omic
in eg a ion in linking genomic, exp ession, and p o eomic
changes o cance mechanisms.
Omics-wide associa ion o common ge mline a ian s
and ANC a ian s wi h p o eomics impac s
Mos ge mline a ia ions occu in non-coding egions o he
genome, which egula e cellula p ocesses. To cha ac e ize hei
egula o y impac on gene exp ession and p o ein abundance,
we pe o med QTL analyses. Ge mline a ian calling was pe -
o med on blood-de i ed WGS samples ollowed by impu a ion
using he NYGC 1,000 Genomes P ojec genome.
28
QTLs
a ec ing ansc ip (eQTL) and p o ein (pQTL) abundance we e
mapped in NAT and umo s ac oss ccRCC, HNSCC, LSCC,
LUAD, and PDAC (Figu es 7A and 7B; Table S7A). We obse ed
ha he exp ession le els o 5% and 10% o he o al es ed
genes (eGenes) and he abundance le els o 4% and 5% o-
al es ed p o eins (pP o eins) we e associa ed wi h WGS ge m-
line a ian s in umo and NAT, espec i ely (Table S7). Fu he -
mo e, 12% and 15% o pQTLs we e also eQTLs in umo and
NAT, espec i ely.
Pan-cance analysis iden i ied 237 eGenes and 47 pP o eins
ha we e sha ed ac oss all NATs and cance s we s udied, sug-
ges ing c oss- issue QTLs (Figu e 7C). In e es ingly, ERAP2,
HLA-DQB1, and PPIL3 we e unde ge mline gene ic con ol
ac oss all NATs and cance s a bo h gene exp ession and p o ein
le els. To de e mine whe he he causal gene ic a ian was he
same o ansc ip exp ession and p o ein abundance o each
o hese h ee genes, we conduc ed a Bayesian es o colocal-
iza ion o all eQTL-pQTL cis-pai s. We disco e ed ha o
ERAP2 (Figu e 7D), he same a ian d i es bo h eQTLs and
pQTLs (Figu e 7E). We also show he e ec o he lowes p alue
cis-SNP ( s2927608) on ERAP2 in Figu e 7D. Simila ly, in HLA-
DQB1 and PPIL3, we obse ed ha eQTLs and pQTLs sha ed
he same causal a ian s in mos o he NAT and umo issues
(Table S7F). As a posi i e con ol, we compa ed he cis-eQTLs
o NAT and umo issues o LSCC and LUAD wi h no mal lung
eQTL da a om he Geno ype-Tissue Exp ession (GTEx) Con-
so ium (Figu e 7F; Table S7G), showing ha 60% o eQTLs
(65% eGenes) and 50% o eQTLs (60% eGenes) in NAT
and umo s, espec i ely, we e also iden i ied in GTEx a 1%
FDR. Fu he mo e, >95% o common cis-eQTLs had he same
allelic e ec s (be a di ec ion) in bo h lung GTEx and ou
lung NAT.
Gi en hei p e alence ac oss issues and -omics da ase s,
and hei ole in disease isk in o he immune ela ed diseases,
we es ed whe he he exp essions o ERAP2,HLA-DQB1, and
PPIL3 co ela ed wi h pa ien su i al. Indeed, he exp ession
o ERAP2 and HLA-DQB1 was posi i ely associa ed wi h o e all
su i al in HNSCC. No e ha 109 o 110 HNSCC indi iduals we e
HPV-nega i e. Fu he mo e, we obse ed he same end in he
TCGA HNSCC coho (Figu e S7A).
We calcula ed PRSs using a ian s disco e ed h ough p io
GWAS o e alua e he global impac o pe sonal isk in CPTAC
pa icipan s (Table S7H). Fo GBM, LSCC, and PDAC, PRSs
we e associa ed wi h cance diagnosis as compa ed wi h o he
cance ypes in CPTAC and heal hy con ols om UKBB
(Figu es 7G and S7B). PRSs also s a i ied pa ien s by disease
agg essi eness, as indica ed by disease ecu ence and o e all
su i al a es in PDAC (Figu e 7H; same pa e ns obse ed o
LSCC). Conside ing he po en ial o PRSs, and ha mos isk a -
ian s om GWAS a e non-coding, we cha ac e ized hei egula-
o y impac on he umo p o eome. We modeled he e ec o
PRSs on p o ein abundance while con olling o clinical, demo-
g aphic, and molecula co a ia es. We obse ed ew p o eins
Figu e 7. eQTL, pQTL, and polygenic isk assessmen o samples wi h umo and no mal WGS
(A) Sha ed numbe o eGenes (genes wi h signi ican eQTLs).
(B) pP o eins (p o eins wi h signi ican pQTLs) ac oss NAT and umo issues o di e en cance ypes indica ed by an UpSe R plo
148
( op 40). As e isks indica e
ha eQTL analysis was no pe o med o no mals due o he limi ed numbe o samples.
(C) In e sec ion o eGenes and pP o eins om a Pan-CPTAC (CCRCC, HNSCC, LSCC, and LUAD) compa ison ac oss NAT and umo s.
(D) All p alues o cis-eQTLs and -pQTLs associa ed wi h ERAP2 in LUAD umo samples. Plo inse s highligh he e ec o s2927608 alleles on ERAP2 RNA
exp ession ( op) and p o ein abundance (bo om).
(E) Colocaliza ion esul s o eQTLs and pQTLs in ERAP2 ac oss NAT and umo s o di e en cance ypes (PP: pos e io p obabili ies suppo ing each hypo hesis;
H0: no causal a ian ; H1: causal a ian o RNA exp ession only; H2: causal a ian o p o ein abundance only; H3: dis inc causal a ian s; H4: common causal
a ian s o eQTL and pQTL).
(F) Compa ison o be a coe icien s o common cis-eQTLs a 1% FDR be ween GTEx lung and CPTAC LSCC NAT ( op) and LUAD NAT (bo om).
(G) Li e a u e-based polygenic isk sco es (PRSs) calcula ed on CPTAC PDAC samples and compa ed wi h o hogonal da ase s. Da a a e ep esen ed as median
and in e qua ile ange. p alues o s a is ical signi icance o he compa ison agains ‘‘Cance CPTAC’’ and ‘‘Con ols UK Biobank’’ a e p o ided ( es ).
(H) Kaplan-Mye plo s es ima ing ecu ence ee su i al ( op) and o e all su i al (bo om) o samples wi h high and low PRSs.
(I) P o ein abundance changes ha co ela e wi h PRS, highligh ing ha p oximal genes (magen a) change less han dis al genes.
(J) GSEA shows ha high PRS samples a e en iched o genes in he adap i e immune sys em and he RAF/MAPK cascades.
(K) The gnomAD ANC allele equency (AF) o ou op indings, sepa a ed by he sec ion in which hey a e desc ibed. Top anno a ions show o e all gnomAD AF
sepa a ed by a e and common ge mline a ian s (le : gnomAD AF %0.05%, igh : gnomAD AF > 0.05%). y axis displays he ANC popula ion.
See also Figu e S7.
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2326 Cell 188, 2312–2335, May 1, 2025
A icle

associa ed wi h PRS (Figu e 7I), implying limi ed impac a he
single-p o ein le el in CPTAC. Howe e , a pa hway-based
app oxima ion o hese esul s wi h gene-se en ichmen ana-
lyses (GSEAs) showed signi ican o e ep esen a ion o se e al
biological p ocesses (Figu e 7J; Table S7I), sugges ing ha ge-
ne ic isk has a cumula i e impac ha con e ges in ce ain bio-
logical p ocesses a he han la ge al e a ions in speci ic p o-
eins. An igen p esen a ion was among he op pa hways
associa ed wi h common isk o PDAC, consis en wi h i s
high he i abili y es ima ed by pan-cance immuni y s udies,
20
in
addi ion o pla ele unc ion
149
and L1 cell adhesion molecule
(L1CAM) ela ed neu al mic oen i onmen emodeling.
150
Com-
mon a ian s also impac ed p o ein le els o he RAS/MAPK
pa hway, which is mu a ed in 96% o panc ea ic duc al
umo s.
151
We also examined whe he a ian s in his s udy a y in p e -
alence ac oss gene ic ances ies. While ou analyses accoun ed
o ances y as a co a ia e (STAR Me hods), we ecognize ha
some a ian s may di e in equency among indi iduals om
di e en gene ic backg ounds. To explo e his, we selec ed
150 s a is ically signi ican a ian s om ou analyses and
compa ed hei ances y-speci ic AF using gnomAD o he
g oups ele an o CPTAC: admixed-Ame ican (AMR), Eas
Asian (EAS), non-Finnish Eu opean (NFE), and Sou h Asian
(SAS). We obse ed some a ian s wi h a ying AFs among he
i e ances y g oups, while o he s showed consis en AF ac oss
all g oups (Figu e 7K). Fo ins ance, he unca ing SIRPA indel is
mo e common in EAS indi iduals, while he CHD4 E139D a ian
exhibi ing s ong ASE is mo e equen in AFR indi iduals. In
con as , a ian s like he op SNP om QTL analysis o HLA-
DQB1 ( s9273472) and CASP8 D344H, which in luenced a dis al
phospho yla ion si e, showed simila AFs ac oss all ances ies in
gnomAD.
DISCUSSION
While mos cance genomics s udies ha e ocused on he ole o
soma ic mu a ions, he numbe o ge mline a ian s g ea ly
exceed ha o soma ic mu a ions in a cance cell. The composi-
ion o hese a ian s is unique, and hei e ec s in oncogenic
p ocesses and cance e olu ion emain poo ly unde s ood. We
ha e le e aged he CPTAC coho wi h mul iple cance ypes
o explo e he impac o ge mline a ia ions on cance - ele an
genes h ough mul iple-omics laye s: om DNA o RNA, p o ein
abundance, and PTM.
To assess he e ec s o coding a ian s and hei associa ion
wi h cogna e p o eins (and PTMs), we used p ecision pep ido-
mics, i.e., he quan i ica ion o pep ides ca ying gene ic a ian s
om indi idual pa ien s. In eg a ing bulk p o eomic and an-
sc ip omic da a wi h ge mline a ian s, we de i ed mechanis ic
in e ences on he e ec s o coding a ian s. Poin mu a ions a
o nea phosphosi es al e ing downs eam biological p ocesses
we e no ed in bo h umo and NAT samples. Simila egula o y
mechanisms a e seen o mu a ions a om phosphosi es in
linea dis ance. We ha e highligh ed examples whe e a dis al
linea e ec is likely caused by he gene ic a ian s and he
PTM si es being close in 3D, bene i ing om p edic ed 3D
models by AlphaFold2. We a e mind ul ha hose models a e
impe ec , pa icula ly ega ding he ela i e spa ial a angemen
o di e en domains wi hin he same p o ein.
152
Finally, we also
show ha ge mline indels can shape pep ide and p o ein abun-
dance h ough e ec s ha canno be disce ned a he RNA le el.
We explo ed he impac o non-coding a ian s on bo h gene
exp ession and p o ein abundance (QTL analyses), epo ing
genes and p o eins unde ge mline gene ic con ol ac oss
di e en NATs and umo s (h ps://immune egula ion.mssm.
edu). Compa ison o ou lung NAT eQTLs wi h lung eQTLs
om GTEx showed an ex ensi e o e lap, alida ing ou
app oach. Beyond highligh ed genes om colocaliza ion and
su i al analyses, he e a e addi ional issue-speci ic o mul i-
cance eGenes and pP o eins ha me i u he in es iga ion.
In ecen yea s, la ge conso ia like GTEx ha e gene a ed
genome-wide ca alogs o egula o y e ec s ha we e c i ical in
unde s anding he molecula consequences o ge mline loci
iden i ied by GWAS.
153
He e, we p o ide a pan- issue ca alog
o ma ched gene exp ession and p o ein abundance in umo s
and NATs ha expands such e o s. We also obse ed ha
he collec i e e ec o known GWAS isk a ian s in PDAC,
measu ed as PRS, co ela ed be e wi h p o ein le els wi hin
oncogenic pa hways ha a e dis al o he loci ha a e pa o
he PRS. These esul s sugges ha , on op o hei local impac
in cis, GWAS loci can collec i ely al e global p o eomic egula-
ion in ans. Despi e he case-con ol design o he cance dis-
co e y GWASs pe o med o da e, ou esul s con i m ha a
PRS can s a i y pa ien s acco ding o disease agg essi eness
and o e all su i al a es.
10
These indings unde sco e he alue
o p o eogenomics in in e p e ing ge mline a ian e ec s on
cance pheno ypes and clinical ou comes.
Finally, gene ic ances y migh in luence he e ec s o ge mline
a ian s.
154,155
While di e se, spanning i e key gene ic ances-
ies—EUR (n=786),AFR(n=40),EAS(n=194),SAS(n=5),
and AMR (n= 39)— he CPTAC coho emains unde powe ed
o disco e y o no el con ibu o s o cance pheno ypes o spe-
ci ic gene ic ances ies o he han EUR. Also, ou coho is ela-
i ely small compa ed wi h la ge genomic s udies.
39,156–158
Despi e his limi a ion, we unco e ed ances y-independen asso-
cia ions o p o eomic, phospho-p o eomic, and ansc ip omic
a ia ions by accoun ing o gene ic ances y in ou analyses.
In conclusion, he ge mline genome is he undamen al a ena
whe e he d ama o cance un olds and is depic ed. Amid mu a-
ional chaos, he ge mline plays a c i ical ole ha can enable o
cons ain he e olu ion o cance , dic a ing he odds o many clin-
ically ele an phenomena: om cance d i e mu a ions
11,159
o
immune esponses agains cance cells.
20
A deepe unde s and-
ing, a o ded by p o eomics, illumina es his complexi y, un eiling
al e ed p o ein unc ion as pi o al in ca cinogenesis.
Limi a ions o he s udy
While ou da ase is one o he la ges mul i-omic esou ces
a ailable, we emain unde powe ed due o sample size. Ou
coho included pa ien s p edominan ly o EUR gene ic ances y,
wi h smalle subse s o o he ances ies. Fu u e p o eogenomic
s udies need o include mo e di e se popula ions. All -omics da-
ase s we e om bulk analy es, limi ing ou abili y o esol e im-
pac s o ge mline a ian s on speci ic cell ypes. We only used
he common a ian s impu ed om he 1,000 Genomes
ll
OPEN ACCESS
Cell 188, 2312–2335, May 1, 2025 2327
A icle
P ojec ,
28
as we did no ha e high-co e age WGS da a. Cu en
p o eomic pipelines ely on gene ic pep ide e e ences o quan-
i y pep ide abundance. We add essed his limi a ion by iden i-
ying pe sonalized pep ides, bu single pep ides e lec di e se
allele equencies om popula ions and ou cance -speci ic
coho . While p o ein and gene-le el quan i ica ion a e mi iga ed
by agg ega ing many pep ides, we emain conse a i e when
add essing he impac o single pep ides. AlphaFoldDB
expanded ou s uc u al analysis o all human p o eins, bu i s
models a e no expe imen ally alida ed. Finally, alida ion o
ou indings is challenging due o he limi ed a ailabili y o com-
pa able comp ehensi e da ase s, so some o ou esul s will
likely e ol e as mo e samples a e analyzed.
RESOURCE AVAILABILITY
Lead con ac
Fu he in o ma ion and eques s o esou ces and eagen s should be
di ec ed o and will be ul illed by D . Li Ding ([email p o ec ed]).
Ma e ials a ailabili y
This s udy did no gene a e new unique eagen s.
Da a and code a ailabili y
Raw and p ocessed p o eomics as well as open-access genomic da a, can be
ob ained ia P o eomic Da a Commons (PDC) a h ps://pdc.cance .go /pdc/
cp ac-pancance . Raw genomic and ansc ip omic da a iles can be ac-
cessed ia he Genomic Da a Commons (GDC) Da a Po al a h ps://po al.
gdc.cance .go wi h dbGaP S udy Accession: phs001287. 17.p6. Comple e
CPTAC Pan-Cance con olled and p ocessed da a, including he p ecision
p o eogenomics da a gene a ed in his manusc ip , can be accessed ia he
Cance Da a Se ice (CDS). The CPTAC Pan-Cance da a hos ed in CDS is
con olled da a and can be accessed h ough he NCI DAC app o ed, dbGaP
compiled whi elis s. Use s can access he da a o analysis h ough he
Se en B idges Cance Genomics Cloud (SB-CGC) which is one o he NCI-
unded Cloud Resou ce/pla o m o compu e in ensi e analysis. Ins uc ions
o access da a a e as ollows: (1) c ea e an accoun on CGC, Se en B idges
(h ps://cgc-accoun s.sbgenomics.com/au h/ egis e ; (2) ge app o al om
dbGaP o access he con olled s udy (h ps://www.ncbi.nlm.nih.go /p ojec s/
gap/cgi-bin/s udy.cgi?s udy_id=phs001287. 17.p6); (3) log in o CGC o access
Cance Da a Se ice (CDS) File Explo e; (4) copy da a in o you own space and
s a analysis and explo a ion; (5) isi he CDS page o see wha s udies a e
a ailable and ins uc ions and guides o use he esou ces (h ps://
da ase ice.da acommons.cance .go /#/da a).
Da a used in his publica ion we e gene a ed by CPTAC, accessible
h ough dbGaP accession numbe s phs000892. 6.p1 (‘‘CPTAC P o eoge-
nomic Con i ma o y S udy’’) and phs001287. 17.p6 (‘‘CPTAC P o eogenomic
S udy’’).
We ocused on he CPTAC samples wi h bo h genomic and p o eomic da a
a ailable o in es iga e he Pan-Cance p o eogenomic impac s o oncogenic
d i e s. DOIs a e lis ed in he key esou ces able. Any addi ional in o ma ion
and code equi ed o eanalyze he da a epo ed in his pape is a ailable
om he lead con ac upon eques .
CONSORTIA
The membe s o he Na ional Cance Ins i u e Clinical P o eomic Tumo Anal-
ysis Conso ium a e Eunkyung An, Meenakshi Anu ag, Jasmin Ba a a, Che
Bi ge , Michael J. Bi e , Anna P. Calinawan, Michele Cecca elli, Daniel W.
Chan, A ul M. Chinnaiyan, Hanbyul Cho, Sh aban i Chowdhu y, Ma cin P. Cie-
slik, Daniel Cui Zhou, Co bin Day, Ma cin J. Domagalski, Yongchao Dou, B ian
J. D uke , Na han Edwa ds, Ma hew J. Ellis, S e en M. Fol z, Alicia F ancis,
Tania J. Gonzalez Robles, Sa a J.C. Gosline, Runyu Hong, Galen Hos e e ,
Yingwei Hu, Ta a Hil ke, Chen Huang, Emily Hun sman, E ic J. Jaehnig, Sco
D. Jewell, Jiayi Ji, Wen Jiang, Lizabe h Ka snelson, Ka en A. Ke chum, Iga
Kolodziejczak, Jona han T. Lei, Yuxing Liao, Caleb M. Lindg en, Tao Liu, Weip-
ing Ma, Wilson McKe ow, Chelsea J. New on, Robe Old oyd, Gilbe S.
Omenn, Amanda G. Paulo ich, F ancesca Pe alia, Bo is Re a, Ka in D. Rod-
land, Hen y Rod iguez, Kelly V. Ruggles, Dmi y Rykuno , Sa a R. Sa age, E ic
E. Schad , Michael Schnaubel , Tobias Sch aink, Zhiao Shi, Richa d D. Smi h,
Xiaoyu Song, Yizhe Song, Jimin Tan, Ra na R. Thangudu, Nicole Tigno ,
Joshua M. Wang, Pei Wang, Ying Wang, Bo Wen, Maciej Wizne owicz, Xinpei
Yi, Bing Zhang, Hui Zhang, Xu Zhang, Zhen Zhang, Da id I. Heiman, Ja ed L.
Johnson, Liang-Bo Wang, Lijun Yao, Ma hangi Thiaga ajan, Mehdi Mes i,
O
¨zgu
¨n Babu , Pie o Pugliese, Qing Zhang, Samuel H. Payne, Sa a ana M.
Dhanaseka an, Shanka a Anand, Shankha Sa pa hy, S ephan Schu
¨ e , Vasi-
leios S a hias, Wen-Wei Liang, Wenke Liu, and Yige Wu.
ACKNOWLEDGMENTS
We would like o hank he pa icipan s and in es iga o s om he Na ional
Cance Ins i u e (NCI) Clinical P o eomic Tumo Analysis Conso ium
(CPTAC). This wo k was suppo ed by NCI-CPTAC unde awa d numbe s
U24CA210955, U24CA210985, U24CA210986, U24CA210954, U24CA2
10967, U24CA210972, U24CA210979, U24CA210993, U01CA214114,
U01CA214116, and U01CA214125 as well as U24CA210972 (D.F., and
L.D.), U24CA210979 (G.G.), U24CA270823 (M.A.G.), and con ac numbe
GR0012005 (L.D.). This wo k was also suppo ed by NCI U24CA211006 and
R01HG009711 o L.D. The Spanish Minis y o Science suppo s E.P.-P. and
K.J.I. (RYC2019-026415-I and PID2019-107043RA-I00) and U.M.M.
(RYC2020-030632-I and PID2019-108244RA-I00). I.M. is suppo ed by
Fundacio
´n C is Con a el Ca
´nce (PR_TPD_2020-19). This esea ch was con-
duc ed using he UK Biobank Resou ce unde applica ion numbe s 54343 and
74382 ( o E.P.-P. and U.M.M., espec i ely).
This p ojec is unded in pa wi h ede al unds om he NCI, Na ional Ins i-
u es o Heal h, unde con ac no. HHSN261201500003I, Task O de no.
HHSN26100064. The con en o his publica ion does no necessa ily e lec
he iews o policies o he Depa men o Heal h and Human Se ices, no
does men ion o ade names, comme cial p oduc s, o o ganiza ions imply
endo semen by he US Go e nmen .
AUTHOR CONTRIBUTIONS
S udy concep ion and design, Z.H.G., E.P.-P., L.D., M.H.B., and G.G.; pe -
o med expe imen s o da a collec ion, F.M.R., N.V.T., Y.L., Y.A., A.I.R.,
Y.G., F.d.V.L., and A.I.N.; mul i-omic & s a is ical analyses, F.M.R., N.V.T.,
K.J.I., K.R.C., M.M., K.K., M.E.S., I.M., Y.G., Y.A., T.M.Y., S.C., E.P.S., Y.L.,
O.S.G., A.G., E.A.K., U.M.M., Z.H.G., M.H.B., E.P.-P., B.T., and R.J.K.; da a
in e p e a ion & biological analysis, F.M.R., N.V.T., K.R.C., A.C., K.-l.H.,
C.K.-S., F.A., A.J.L., L.C.C., U.M.M., Z.H.G., M.H.B., G.G., E.P.-P., and L.D.;
w i ing, F.M.R., N.V.T., K.J.I., K.R.C., M.E.S., I.M., Y.G., Y.A., C.K.-S., A.J.L.,
U.M.M., Z.H.G., D.F., M.A.W., M.H.B, G.G., E.P.-P., and L.D.; supe ision,
D.R.M., M.A.G., D.F., S.A.C., Z.H.G., M.H.B., G.G., E.P.-P., and L.D.; admin-
is a ion, G.G., A.I.R., and L.D.
DECLARATION OF INTERESTS
The au ho s decla e no compe ing in e es s.
STAR+METHODS
De ailed me hods a e p o ided in he online e sion o his pape and include
he ollowing:
dKEY RESOURCES TABLE
dEXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS
BHuman subjec s
BClinical da a anno a ion
dMETHOD DETAILS
BHa monized genome alignmen
BGe mline a ian calling and il e ing om WES
BSoma ic mu a ion and copy numbe a ian calling om WES
BGe mline a ian calling and il e ing om WGS
ll
OPEN ACCESS
2328 Cell 188, 2312–2335, May 1, 2025
A icle
BCompa ison o WES and WGS a ian calls
BAnces y p edic ion
BGene lis cu a ion o pa hogenic a ian classi ica ion
BIn e ence o he ances al s a e o ge mline a ian s
dQUANTIFICATION AND STATISTICAL ANALYSIS
BPa hogenici y assessmen o a e ge mline a ian s
BBu den es ing analyses o a e P/LP ge mline a ian s
BLOH analysis o a e P/LP ge mline a ian s
BP o eomics LC-MS/MS da a in e p e a ion
BGe mline Va ian s Co-localizing wi h o A ound PTM si es
BAnalyses o Di ec , P oximal, and Dis al Impac o Ge mline Va ian s
on P o ein and PTM Le els
BHo Spo 3D / Ho Pho analyses
BAllele speci ic exp ession analysis using RNA-seq da a
BIndel a ian analysis
BIden i ica ion o exp ession and p o ein quan i a i e ai loci (eQTLs
and pQTLs)
BPolygenic Risk Sco es and associa ions wi h p o ein abundance
dADDITIONAL RESOURCES
SUPPLEMENTAL INFORMATION
Supplemen al in o ma ion can be ound online a h ps://doi.o g/10.1016/j.cell.
2025.03.026.
Recei ed: Oc obe 9, 2023
Re ised: Ap il 29, 2024
Accep ed: Ma ch 13, 2025
Published: Ap il 14, 2025
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Pep ide spec um ma ch (PSM) il e ing and alse disco e y a es (FDR)
Using he SM Au o alida ion module pep ide spec um ma ches (PSMs) o indi idual spec a we e con iden ly assigned by applying
a ge -decoy based FDR es ima ion o achie e <1.0% FDR a he PSM, pep ide, VM si e and p o ein le els. Fo he whole p o eome
da ase h esholding was done in 3 s eps: a he PSM le el, he p o ein le el o each TMT-plex, and he p o ein le el o he coho o 2
TMT-plexes. Fo he PTM omes (phosphop o eome and ace ylome da ase s), h esholding was done in wo s eps: a he PSM le el
o each TMT-plex and a he VM si e le el o he coho o 2 TMT-plexes. In s ep 1 o all da ase s, PSM le el au o alida ion was done
i s and sepa a ely o each TMT-plex expe imen using an au o- h esholds s a egy wi h a minimum sequence leng h o 7; au oma ic
a iable ange p ecu so mass il e ing; wi h sco e and del a Rank1 - Rank2 sco e h esholds op imized o yield a PSM le el FDR
es ima e o p ecu so cha ges 2 h ough 4 o < 0.8% o each p ecu so cha ge s a e in each LC-MS/MS un. To achie e easonable
s a is ics o p ecu so cha ges 5-6, h esholds we e op imized o yield a PSM-le el FDR es ima e o < 0.4% ac oss all uns pe TMT-
plex expe imen (ins ead o pe each un), since many ewe spec a a e gene a ed o he highe cha ge s a es.
In s ep 2 o he PTM omes: phosphop o eome and ace ylome da ase s VM si e polishing au o alida ion was applied ac oss bo h
TMT plexes o e ain all VM si e iden i ica ions wi h ei he a minimum id sco e o 8.0 o obse a ion in n TMT plexes (n=4, 3, o 2 i > 20,
7, o 1 plexes/coho , espec i ely). The in en ion o he VM si e polishing s ep is o con ol FDR by elimina ing un eliable VM si e le el
iden i ica ions, pa icula ly low sco ing VM-si es ha a e only de ec ed as low sco ing pep ides ha a e also in equen ly de ec ed
ac oss TMT plexes in he s udy. Using he SM P o ein/Pep ide Summa y module o make VM-si e epo s he ubiqui ylome and ace-
ylome da ase s a e u he il e ed o emo e pep ides ending wi h he egula exp ession [^K][^K]k since ypsin and Lys-C canno
clea e a a ace yla ed lysine. The [^K] means e ain i unmodi ied Lys p esen in one o he las wo posi ions o allow o a missed
clea age wi h ambiguous PTM-si e localiza ion. C- e minally ace yla ed lysines a e p esen in he ace ylome da ase , bu ha e
been shown o a ise om a i ac ual modi ica ion du ing TMT-labeling a e ypsin diges ion.
In s ep 2 o he whole p o eome da ase , p o ein polishing au o alida ion was applied sepa a ely o each TMT-plex expe imen o
u he il e he PSMs using a a ge p o ein le el FDR h eshold o ze o. The p ima y goal o his s ep was o elimina e pep ides iden-
i ied wi h low sco ing PSMs ha ep esen p o eins iden i ied by a single pep ide, so-called ‘‘one-hi wonde s.’’ A e assembling
p o ein g oups om he au o alida ed PSMs, p o ein polishing de e mined he maximum p o ein le el sco e o a p o ein g oup
ha consis ed en i ely o dis inc pep ides es ima ed o be alse-posi i e iden i ica ions (PSMs wi h nega i e del a o wa d- e e se
sco es). PSMs we e emo ed om he se ob ained in he ini ial pep ide le el au o alida ion s ep i hey con ibu ed o p o ein g oups
ha had p o ein sco es below he maximum alse-posi i e p o ein sco e. S ep 3 was hen applied, consis ing o p o ein polishing
au o alida ion ac oss all TMT plexes in a coho oge he using he p o ein g ouping me hod ‘‘expand subg oups, op uses sha ed’’
o e ain p o ein subg oups wi h ei he a minimum p o ein sco e o 25 o obse a ion in TMT plexes (n=4, 3, o 2 i > 20, 7, o 1 plexes/
coho , espec i ely). The p ima y goal o his s ep was o elimina e low sco ing p o eins ha we e in equen ly de ec ed in a coho .
As a consequence o hese wo p o ein- polishing s eps, each iden i ied p o ein epo ed in he s udy comp ised mul iple pep ides,
unless a single excellen sco ing pep ide was he sole ma ch and ha pep ide was obse ed in mul iple TMT-plexes.
Subse -speci ic FDR il e ing o ge mline a ian con aining pep ides in he p o eome
While pep ides in he p o eome da ase ma ched o e e ence p o eome sequences a e subjec o mul i-s ep, p o ein-le el and
coho le el FDR il e ing as desc ibed abo e, FDR o subse s o a ely obse ed (<5% o o al) classes o pep ides equi ed
mo e s ingen sco e h esholding o each a sui able subse -speci ic FDR < 1.0%. To his end, we de ised and applied subse -spe-
ci ic il e ing app oaches.
The subse o pep ides con aining single amino acid a ian s (SAAVs) and indels obse ed in he p o eome was ex ac ed a e s ep
1 o PSM il e ing desc ibed abo e using he SM P o ein/Pep ide Summa y module o c ea e a p o eogenomics (PG) si e epo , wi h
quan i a ion no malized o nulli y he e ec o di e en ial p o ein loading using he agg ega e p o ein-le el no maliza ion ac o s om
he ully il e ed p o eome da ase . Ge mline a ian s con aining pep ides we e spli up in o 4 subse s (SAAVs and indels, wi h each
u he spli by mul iple o single ep esen a ion in a coho ) and each subse was il e ed o <1% FDR.
Subse s we e h esholded independen ly in each subse using a 2-s ep app oach. Fi s , PSM sco ing me ic h esholds we e igh -
ened in a ixed manne so ha dis ibu ions o each me ic imp o ed o mee o exceed he agg ega e dis ibu ions. The ixed h esh-
olds we e: minimum sco e: 7; minimum pe cen sco ed peak in ensi y: 50%; no malized p ecu so mass e o : +/-5 ppm. Second,
indi idual subse s wi h FDR es ima es emaining abo e 1% we e u he subjec o a g id sea ch o de e mine he lowes alues o
backbone clea age sco e (sequence co e age me ic) and sco e ( agmen ion assignmen me ic) ha imp o ed FDR o < 1% o
each subse .
Quan i a ion using TMT a ios
Using he SM P o ein/Pep ide Summa y module, a p o ein compa ison epo was gene a ed o he p o eome da ase using he p o-
ein g ouping me hod ‘‘expand subg oups, op uses sha ed’’ (SGT). Fo he PTM omes (phosphop o eome and ace ylome da ase s)
Va iable Modi ica ion si e compa ison epo s limi ed o ei he phospho, o ace yl si es, espec i ely, was gene a ed using he p o ein
g ouping me hod ‘‘unexpand subg oups.’’ Rela i e abundances o p o eins and VM-si es we e de e mined in SM using TMT epo e
ion log
2
in ensi y a ios om each PSM. TMT epo e ion in ensi ies we e co ec ed o iso opic impu i ies in he SM P o ein/Pep ide
Summa y module using he a RICA co ec ion me hod, which implemen s de e minan calcula ions acco ding o C ame ’s Rule and
co ec ion ac o s ob ained om he eagen manu ac u e ’s ce i ica e o analysis o each coho . Each p o ein-le el o PTM si e-
le el TMT a io was calcula ed as he median o all PSM-le el a ios con ibu ing o a p o ein subg oup o PTM si e. PSMs we e
excluded om he calcula ion i hey lacked a TMT label, had a p ecu so ion pu i y < 50% (MS/MS has signi ican p ecu so isola ion
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con amina ion om co-elu ing pep ides), o had a nega i e del a o wa d- e e se iden i ica ion sco e (hal o all alse-posi i e iden-
i ica ions). Using he SM P ocess Repo module non-quan i iable p o eins and PTM si es (ex: unlabeled pep ides con aining an
ace yla ed p o ein N- e minus and ending in a ginine a he han lysine) we e emo ed, and median/MAD no maliza ion was pe -
o med on each TMT channel in each ome o cen e and scale he agg ega e dis ibu ion o p o ein-le el o PTM si e-le el log- a ios
a ound ze o in o de o nulli y he e ec o di e en ial p o ein loading and/o sys ema ic MS a ia ion. When subse s o an ome
(nuORF o SAAVs, e c) he TMT a ios we e no malized using he no maliza ion ac o s o he agg ega e dis ibu ion o he co e-
sponding ome.
I is wo h no ing ha cu en p ecision da abase me hods sepa a ely quan i y di e en o ms o a pep ide ( e e ence sequence,
a ian –con aining, phospho yla ed, unphospho yla ed, e c.) ha ing dis inc pep ide masses and e en ion imes in TMT labeled a-
io-based LC-MS/MS expe imen s. A TMT labeled expe imen is pu pose-buil o measu e a ios o an indi idual pep ide o m ac oss
samples, which a e combined so ha each sample in a TMT-plex p oduces a epo e ion o dis inc m/z in each MS/MS spec um.
The TMT epo e ion in ensi ies o he e e ence sequence and a ian -con aining o ms o a pep ide canno be di ec ly combined o
o m a single alue ep esen ing he o e all pep ide abundance since he MS/MS spec a will ha e been b ie ly sampled a di e en
poin s in hei co esponding ch oma og aphic peaks.
187
P o ein- o gene-le el quan i ica ion will mi iga e his e ec by elying on
mul iple o he wild- ype (WT)-only pep ides. In con as , PTM measu emen s may be mo e a ec ed since hey a e usually measu ed
as single pep ides.
Ge mline Va ian s Co-localizing wi h o A ound PTM si es
Inpu da a
F om a o al o 27,104,152 ge mline a ian s called om WES da a, we selec ed 11,962,341 missense ge mline a ian s ac oss ou
1,064 samples o e 10 cance ypes o ind ge mline a ian s di ec ly co-localizing o nea by a PTM si e.
As pe PTM da a, we ob ained a o al o 141,330 unique phospho yla ion si es de ec ed in a leas one o he samples in ou CPTAC
coho (134,244 on e e ence pep ides and 7,086 on a ian pep ides a ec ed by ge mline SAAVs) and 23,756 unique ace yla ion
si es (23,190 on e e ence pep ides and 566 on a ian pep ides a ec ed by ge mline SAAVs). Si es de ec ed on he same pep ide
sequence we e conside ed as sepa a e indi idual si es yielding a o al o 168,423 and 9,018 phospho yla ion si es on e e ence and
a ian pep ides, espec i ely, and 24,109 and 639 ace yla ion si es on e e ence and a ian pep ides, espec i ely.
Calcula ion o linea dis ances
Missense a ian s co-localizing wi h PTM si es in ol ing se ine (S), h eonine (T), y osine (Y), o lysine (K) codons we e c oss- e e -
enced in he PTM da a o cogna e posi ions. PTM associa ed ge mline a ian s we e g ouped acco ding o he h ee ypes o con-
sequences a he PTM le el: (1) an amino acid change caused loss o he PTM si e; (2) a a ian caused gain o a PTM si e no encoded
by he e e ence allele; o , (3) one phospho yla ed esidue changed o ano he (such as om a se ine o a y osine, wi h phospho -
yla ion de ec ed in bo h). The ances al and de i ed alleles we e compiled o all he co-localizing a ian s. In h ee speci ic cases:
AHNAK S4516N, FAM83B S729T, and FLG S3174C he e e ence-associa ed phospho yla ed se ine de ec ed in he PTM da a
was de i ed om he ances al anno a ion (T4516N, P729T, and G3174C, espec i ely). The e o e, hese a ian s we e excluded
om he analysis.
We also de ec ed a ian s a ound a PTM si e by calcula ing he linea dis ance o missense ge mline a ian s ela i e o PTM si es
based on amino acid posi ion as ex ac ed om e e ence pep ides, classi ying e en s using 2 ca ego ies: missense a ian s
a ec ing an amino acid wi hin 5 amino acids o he PTM si e we e ca ego ized as p oximal e en s; a ian s a ec ing amino acids
beyond 5 amino acids o he PTM si e we e ca ego ized as dis al. We u he con i med i he amino acid changes p edic ed om
ge mline a ian in o ma ion ma ched wha was de ec ed in he a ian pep ide in o ma ion, when exis en . In e ms o a ian s p ox-
imal o dis al o a si e, because mos a ian s dis al o a PTM si e and a po ion o p oximal a ian s ell ou side he pep ide cap u e o
he PTM si e in ques ion, we would no expec o de ec a a ian -de i ed pep ide o such cases. These di ec , p oximal, and dis al
e en s we e used o downs eam analyses.
Analyses o Di ec , P oximal, and Dis al Impac o Ge mline Va ian s on P o ein and PTM Le els
We assessed he po en ial in luence o a ge mline a ian di ec , p oximal, o dis al o a PTM si e on he o e all p o ein abundance
le els using a gene al linea model app oach. We also es ed he e ec s o ge mline a ian s on phospho yla ion and ace yla ion
le els o e e ence pep ides using he same app oach, bu only hose a ian s o which he posi ion ell ou side he pep ide cap u e
o he PTM si e in ques ion in o de o limi he possibili y o bias in he mass spec measu es (See limi a ions o he s udy and quan-
i a ion using TMT a ios STAR Me hods sec ion). The e o e, o a ian s di ec ly o e lapping a PTM si e, we only es ed hei impac
on he o e all p o ein abundance, no on PTM le els. Common ge mline a ian s (gnomAD AF R1%) we e es ed indi idually. In
he case o low equency and a e ge mline a ian s (gnomAD AF <1%), o inc ease s a is ical powe , we collapsed all
indi iduals ha bo ing a low equency/ a e a ian p oximal (wi hin 5 amino acids), o all indi iduals wi h a low equency/ a e a ian
dis al (> 5 amino acids) o a PTM si e in o a single a iable, a he gene le el. In o de o es he pan-cance di e ences in p o ein,
phospho yla ion, o ace yla ion le els be ween ca ie s and non-ca ie s o a ce ain ge mline a ian , we an he ollowing model o
lea n he bcoe icien s:
Y=b0+b1M +b2P1+b3P2+b4P3+b5C+e
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whe e Y is a (n x 1) ec o ep esen ing he p o ein, phospho yla ion, o ace yla ion abundance o he p o ein o in e es o he si e o
in e es ; M is a bina y ec o indica ing he ge mline a ian s a us o he si e o in e es ( ) o each sample; P
1-3
deno e he i s h ee
PCs o pa ien gene ic ances y de e mina ion (WES-based); and C is he one-ho encoded cance ype o he samples. The e o (e)
is assumed o be no mally dis ibu ed wi h a cons an a iance. Tumo samples and ma ching NAT samples we e es ed sepa a ely.
Cance - ype speci ic analyses we e also pe o med. All esul ing p- alues we e adjus ed o FDR using he s anda d Benjamini-
Hochbe g p ocedu e. The esul s om hese es s a e p o ided in Table S3.
Using he same app oach as abo e, we also es ed o he e ec s o highligh ed a ian s om he di ec /p oximal/dis al analyses
on hei Kyo o Encyclopedia o Genes and Genomes (KEGG) pa hway pa ne s’ p o ein and phosphop o ein abundances. Tha is, we
e alua ed ‘‘mTOR signaling’’ o DEPTOR S389N (hsa04150), ‘‘E bB signaling’’ o ERBB2 P1170A (hsa04012), ‘‘MAPK signaling’’ o
MAP2K2 P298L (hsa04010), ‘‘An igen p ocessing and p esen a ion’’ o HLA-B V69A (hsa04612), ‘‘Apop osis’’ o CASP8 D344H
(hsa04210), and ‘‘Cell cycle’’ o ATRX E929Q (hsa04110). Because MGMT is no a membe o any KEGG pa hways, i was no es ed.
We simila ly did no es SBDS, which is only in he gene al "Ribosome biogenesis in euka yo es" pa hway. The analyses we e done a
bo h pan-cance and cance -speci ic le els, in which we equi ed a leas 5 obse a ions each in a ian ca ie s and non-ca ie s o
es . Resul ing p- alues we e FDR adjus ed using he s anda d Benjamini-Hochbe g p ocedu e, and all hi s om he gene al linea
model wi h FDR %0.05 we e p io i ized o plo ing by ca ie s a us. Pai wise Wilcoxon es s be ween ca ie g oups we e pe o med
o plo ing, and FDR adjus ed p- alues a e p o ided wi hin he boxplo s.
To de e mine whe he he genes ha bo ing PTM-a ec ing ge mline a ian s exhibi ed any biological bias, we conduc ed an o e -
ep esen a ion analysis o cu a ed pa hways om he MiSigDB Hallma k
188,189
se and Wiki Pa hways.
190
Fo genes wi h a ian s
di ec ly o e lapping PTM si es imposing phospho yla ion loss and gain, he backg ound gene se was de ined as all genes de ec ed
in he phosphop o eome da a. All ace yla ed p o eins de ec ed in he PTM da a we e simila ly used o backg ound adjus men o
genes ha expe ience ace yla ion si e loss o gain. The R package clus e P o ile 4.4.2 was used o conduc hese analyses o each
PTM ype and consequence g oup sepa a ely. Resul s we e cons ic ed o a cu o o 0.05 FDR adjus ed p- alue and a q- alue cu o
o 0.1. A simila analysis was pe o med o p oximal and dis al e en s. In his case, genes ha bo ing a ian s p oximal o dis al o a
PTM si e we e used as he es gene se , es ing each g oup sepa a ely. The backg ound gene se s and signi icance cu -o s we e
de ined as abo e.
Ho Spo 3D / Ho Pho analyses
Inpu PTM da a
He e, we collec ed in o ma ion o e e y PTM si e de ec ed on bo h e e ence and a ian pep ides in a leas one o he samples in ou
CPTAC coho ia ou analyses o p o eomics LC-MS/MS da a (See p o eomics LC-MS/MS da a in e p e a ion STAR Me hods sec-
ion o mo e de ails). In o al, 8,046 PTM si es (7,353 phosphosi es and 693 ace yla ion si es) we e de ec ed on a ian pep ides
a ec ed by ge mline SNVs o Indels in a leas one o ou samples. Fo he pu poses o Ho Spo 3D/Ho Pho analyses, howe e ,
we ha e excluded PTM si es on a ian pep ides a ec ed by ge mline Indels.
We ob ained 141,330 unique phospho yla ion si es de ec ed in a leas one o he samples in ou CPTAC coho , om which
134,244 a e on e e ence pep ides and 7,086 a e on a ian pep ides a ec ed by ge mline SAAVs. As pe ace yla ion si es, we ob-
ained 23,756 unique ace yla ion si es, om which 23,190 a e on e e ence pep ides and 566 a e on a ian pep ides a ec ed by
ge mline SAAVs. Fu he , si es de ec ed on he same pep ide sequence we e conside ed as sepa a e indi idual si es o he pu poses
o using i as an inpu o Ho Spo 3D
72
due o he o ma equi ed by he ool, yielding a o al o 168,423 and 9,018 phospho yla ion
si es on e e ence and a ian pep ides, espec i ely, and 24,109 and 639 ace yla ion si es on e e ence and a ian pep ides, espec-
i ely. O hese, 123,676 phospho yla ion si es and 23,646 ace yla ion si es a e unique and we e used as inpu s o Ho Spo 3D/
Ho Pho. To map amino acid esidues on di e en p o ein iso o ms be ween UniP o Knowledge Base (UniP o KB, e sion
2023_01)
79
and ou da ase , we used T ans a ,
175
which allowed us o map hem o hei unique genomic posi ions.
Inpu soma ic mu a ion and ge mline a ian da a
Soma ic mu a ions and ge mline a ian s de ec ed om WES, as desc ibed abo e, we e il e ed o missense single nucleo ide
e en s. The e o e, om a o al o 345,653 and 27,104,152 exonic soma ic mu a ions and ge mline a ian s called om WES da a,
espec i ely, we selec ed 183,503 missense soma ic mu a ions and 11,962,341 missense ge mline a ian s ac oss ou 1,064 sam-
ples o e 10 cance ypes as inpu s o Ho Spo 3D/Ho Pho.
PDB and AlphaFoldDB s uc u es
We used he GRCh38 assembly and Ensembl elease 100 (Gencode 34) in o de o p ep ocess esidue pai da a o all human p o-
eins a ailable in wo da abases: (1) he RCSB P o ein Da a Bank (RCSB PDB)
77,78
as o June 24
h
, 2021, which con ains PDB s uc-
u es o 7,780 p o eins; and (2) he AlphaFold P o ein S uc u e Da abase (AlphaFoldDB - AFDB)
75,76
4, as o Ma ch 16
h
, 2023,
which con ains p edic ed p o ein s uc u es om 19,966 p o eins p esen in Unip o . Fo PDB, we il e ed ou chains o s uc u es
due o a i ac s, as p e iously desc ibed.
73
Fo AFDB, Ho Spo 3D’s algo i hm pulls in o ma ion om he web page e sion o he
da abase, which p o ides in o ma ion o p o eins up o 2700 amino acids long. Fo hose p o eins which a e longe han 2700aa,
AFDB p o ides 1400aa long o e lapping agmen s, o which only he i s 1400aa a e a ailable in he webpage e sion used he e.
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Quali y con ol
As desc ibed be o e,
73
Ho Spo 3D/Ho Pho akes as inpu a ile con aining all PTM si es o in e es con aining he ollowing in o ma-
ion o each: he HUGO gene symbol, he co esponding Ensembl ansc ip ID, he p o ein esidue posi ion, and a summa ized
desc ip ion o he si e (e.g. Phosphose ine, Ace yllysine, e c). This in o ma ion is hen passed h ough he so wa e, oge he wi h
he inpu ge mline a ian and soma ic mu a ion in o ma ion, o ind pai wise ela ionships be ween mu a ions and si es. Fo he pu -
poses o hese analyses, we use he wo d ‘‘mu a ions’’ o desc ibe bo h soma ic and ge mline e en s. Fo PDB, because he s uc-
u es p o ided by uploade s in he da abase do no always di ec ly map o he associa ed Unip o en ies, Ho Spo 3D/Ho Pho cal-
cula es o se s in esidue numbe s in PDB s uc u es and ansc ip s. Fo AFDB, because we a e dealing wi h compu a ionally
p edic ed s uc u es, he esidues a he same posi ion be ween he da abase s uc u e and he Unip o en y may no always
pe ec ly ma ch. The e o e, we ha e il e ed ou any si es whe e he esidue p o ided in he PDB o AFDB s uc u e did no ma ch
he esidue in he inpu phospho yla ion o ace yla ion si e da a, esul ing in he ollowing esul s o each inpu da abase: (1) PDB:
41,748 mu a ion-mu a ion pai s, 13,072 mu a ion-si e pai s (4,625 excluded), and 11,328 si e-si e pai s (5,414 excluded); (2)
AFDB: 110,255 mu a ion-mu a ion pai s; 29,888 mu a ion-si e pai s (3,282 excluded), and 32,946 si e-si e pai s (4,972 excluded).
Clus e disco e y and il e ing
We ha e implemen ed Ho Spo 3D
72
and Ho Pho
73
o allow o he co-clus e ing o bo h missense ge mline a ian s and soma ic mu-
a ions wi h phospho yla ion and ace yla ion si es on he 3D p o ein s uc u es (Figu e 4A), as p e iously desc ibed.
73
B ie ly, we used
Ho Spo 3D o calcula e he 3D dis ances be ween mu a ions and PTM si es using s uc u es om PDB, as well as p edic ed s uc-
u es om AFDB. Du ing his p ocess, missense a ian s and PTM si es a e conside ed as nodes and he 3D dis ances be ween hem
as edges on an undi ec ed g aph. The clus e s a e hen calcula ed using he Floyd–Wa shall sho es -pa hs algo i hm and using
ecu ence as he e ex ype and clus e ing dis ance o 10A
˚, as implemen ed in Ho Spo 3D.
72
These analyses yielded a o al o
15,132 un il e ed clus e s ac oss 4,409 unique p o eins using PDB s uc u es (2,084 si e-only, 9,558 mu a ion-only, 3,490 hyb id),
and 96,719 un il e ed clus e s in 15,655 unique p o eins using AFDB s uc u es (14,788 si e-only, 62,437 mu a ion-only, 19,494
hyb id).
We u he il e ed clus e s based on he clus e closeness sco e (Cc), o which a high sco e indica es a clus e en iched in mu-
a ions and PTM si es on he 3D p o ein s uc u e. He e we use a h eshold o op 5% o selec high con idence in amolecula clus-
e s o downs eam analyses, as desc ibed in he p e ious Ho Spo 3D and Ho Pho s udies.
72,73
This gene a ed a inal se o 210
hyb id, 509 mu a ion-only, and 111 si e-only clus e s om PDB and 978 hyb id, 3126 mu a ion-only, 731 si e-only clus e s om
AFDB. These esul s a e p o ided in Table S4.
Impac on p o ein abundance analyses
We applied a linea model o e alua e he p o ein abundance le el di e ences be ween ca ie s and non-ca ie s o co-clus e ed mu-
a ions and/o PTM si es wi hin he same in amolecula clus e . We an he model o lea n he bcoe icien s as ollows:
Y=b0+b1M +b2P1+b3P2+b4P3+b5C+b5N+e
whe e Y is a (n x 1) ec o ep esen ing he p o ein abundance o he p o ein o in e es o he clus e o in e es ; M is a bina y ec o
indica ing he co-clus e ed s a us ( ) o each sample (i.e. i a sample had any e en co-clus e ed in a pa icula clus e , i was g ouped
he e); P
1-3
deno e he i s h ee PCs o pa ien gene ic ances y de e mina ion (WES-based); C is he one-ho encoded cance ype
o he samples, and N is he CNV alue o he gene being es ed, as de e mined by GISTIC2. The e o (e) is assumed o be no mally
dis ibu ed wi h a cons an a iance.
Cance - ype speci ic analyses we e also pe o med in he same way, whe e we e alua ed he e ec o ge mline and soma ic a -
ian s in ol ed in hyb id clus e s on p o ein abundance le els be ween ca ie s and non-ca ie s o ind gene ic changes po en ially
associa ed wi h a ce ain cance ype.
Analyses o phospho yla ion and ace yla ion le els we e no pe o med in his case due o he limi a ions add essed in his manu-
sc ip (See limi a ions o he s udy).
Allele speci ic exp ession analysis using RNA-seq da a
To iden i y allele speci ic exp ession (ASE) e en s based on RNA-seq, we used 1,057 umo and 340 NAT samples wi h
a ailable RNA-seq da a. Fo hese analyses, we used only SNVs in cance - ela ed genes (624 cance ela ed genes
17
). Fi s ,
ge mline a ian s we e il e ed o he ones ha we e de ec ed in ei he o he h ee da ase s: p o eome, phosphop o eome, o ace-
ylome. Nex , we calcula ed ead coun s o each a ian in each sample’s RNA-seq BAM iles using bam- eadcoun ( 0.7.4 wi h
pa ame e s -q 10, -b 15, and -i so ha eads o e lapping wi h an inse ion we e no included in he pe base coun s). We e ained
only a ian s wi h a leas 10 ead coun s co e ing e e ence and al e na i e alleles o his analysis. Then, o iden i y ASE e en s,
we pe o med a wo-sided binomial es wi h a null p obabili y o success 0.5 in a Be noulli expe imen . The esul ing p- alues
we e adjus ed using BH p ocedu e, and ASE e en s we e called signi ican i hey eached FDR<0.05.
Indel a ian analysis
Summa y s a is ics o indel coun s we e measu ed acco ding o he ge mline MAF iles (abo e Me hods) and es ic ed o a la ge se
o cance ela ed genes as p e iously desc ibed.
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Indel posi ioning was pe o med by mapping a ian s o he exons and labeling hem acco ding o posi ion (Fi s , Middle, o Las
exon). When only 1 o 2 exons made up he composi ion o a gene, hen hey we e assigned i s and las , and no did no ecei e a
middle label. Rela i e posi ion o he mu a ion wi hin he gene model was calcula ed o each gene based on he size o he exon as
ca aloged by Ensembl 100.
191
The Penul ima e egion nex o he las exon junc ion (<50bp om he las exon junc ions [EJC]) was
measu ed. This was pe o med o ameshi mu a ions and p edic ed in ame mu a ions as anno a ed in he ge mline MAF iles (see
abo e STAR Me hods -ge mline a ian calling and il e ing om WES). Again, using he Ensembl gene anno a ions, ela i e posi ions
o he las exon s a -posi ion was used o de e mine whe he a mu a ion was assigned o he penul ima e posi ion. Ke nel densi y
in o ma ion was es ima ed and plo ed o iden i y gene posi ion di e ences o in ame and ameshi mu a ions (Figu e 6B).
We also de eloped wo simple algo i hms o disco e he impac o hese ge mline a ian s on p o ein abundances. The i s
me hod seeks o de e mine he impac o indels by looking a he ups eam and downs eam pep ide-le el abundances. Simply
s a ed, we used a - es as he c ux o he i s analysis. Second, we sough o ind mu a ions ha had an e ec on p o ein abundance
wi h espec o he RNA exp ession. Below we ou line he implemen a ion o a mul i-omic LDA (moLDA) analysis o accomplish his
objec i e.
We used he ollowing c i e ia o disco e a ian s ha had a iable ups eam and downs eam consequences o indels. Fi s , we
es ic ed ou indel a ian s o hose ha had a p edic ed ameshi , splice- egion, p o ein-al e ing designa ion acco ding o VEP
anno a ions (see abo e STAR Me hods -ge mline a ian calling and il e ing om WES). Nex , we es ic ed ou sea ch o a ian s
ha we e obse ed in a leas 20 samples. We ensu ed only a ian s wi h a leas 6 measu ed pep ides, up- and down-s eam, we e
included. We hen spli he da a based on whe he he e was a signi ican di e ence be ween ups eam pep ide abundances o
downs eam pep ide abundances using a - es . P- alues and 95% con idence in e als o all indels and genes ha me hese
c i e ia a e p o ided in Table S6.
The second s a egy we implemen ed o iden i y he ole o indels on p o ein a iabili y was o le e age an assumed ela ionship
be ween RNA exp ession and p o ein abundance o ind examples whe e mu a ions clea ly associa ed wi h an expec ed ela ionship.
To achie e his objec i e we implemen ed a mul i-omic linea disc iminan analysis (LDA) o classi y indel s a us based on RNA and
p o ein abundance. B ie ly, LDA is a s a is ical me hod used o classi ying o p edic ing he g oup membe ship o obse a ions
based on a se o p edic o a iables. I aims o ind a linea combina ion o p edic o s ha maximally sepa a es wo di e en ia ing
g oups. He e he g oups a e de ined as indel ca ie s and non-ca ie s and he p edic o s a e p o ein abundance and RNA exp es-
sion. Fi s , we ensu ed ha mo e han 30 samples had bo h RNA and p o ein abundance measu emen s o a gi en gene (in cis). Nex ,
we excluded all mu a ions ha didn’ ha e a leas 6 samples wi h he mu a ions and a leas 6 samples wi hou he mu a ions.
Following a da a in eg a ion s ep o me ge RNA exp ession wi h p o ein abundance we used he ‘lda‘ unc ion as pa o he
MASS R lib a y o ind linea combina ions o p o ein and RNA ha seg ega ed based on mu a ion s a us (Figu e 6E). Genes and mu-
a ions we e p io i ized based on hei singula alue decomposi ion (SVD) sco es which p o ide highe sco es o imp o ed sepa-
a ion be ween p edic o s Table S6.
Iden i ica ion o exp ession and p o ein quan i a i e ai loci (eQTLs and pQTLs)
We pe o med quan i a i e ai loci (QTL) mapping o iden i y common ge mline gene ic a ian s ha a ec gene exp ession (eQTL)
and p o ein abundance (pQTL) in umo and no mal issues u ilizing he linea eg ession model in Ma ixeQTL.
192
Fo his pu pose,
we used WGS ge mline SNPs wi h MAF R5% and included gende and en p incipal componen s as co a ia es o adjus o pop-
ula ion s a i ica ion. We analyzed he da a on each cance and issue sepa a ely. Speci ically, we conduc ed he eQTL and pQTL
analyses o umo and no mal issues o ccRCC, HNSCC, LSCC LUAD and PDAC o which bo h gene exp ession and p o ein abun-
dance da a a e a ailable (excep o eQTL analysis on no mal issue o PDAC pa ien s due o he limi ed numbe o samples wi h
no mal da a). Fo he eQTL analysis, we u ilized he FPKM no malized gene exp ession gene a ed om he RNA-Seq da a as dis-
cussed in he Pan-Cance Da a and Resou ce and Pan-Cance D i e manusc ip s,
37,160
and u he pe o med TPM con e sion,
quan ile no maliza ion, and in e se no mal ans o ma ion o emo e echnical noises and allow c oss-sample compa isons. The
eQTL analysis included indi iduals o whom geno ype and gene exp ession da a we e a ailable and genes wi h TPM > 0.1 in a leas
20% o samples (Table S7A). To elimina e he hidden de e minan s in he exp ession da a, we addi ionally selec ed 15 PEER ac o s
as co a ia es using PEER so wa e.
193
The pQTL analysis included indi iduals o whom geno ype and p o ein abundance we e a ail-
able and p o eins wi h da a in a leas 20% o samples (Table S7A). We deemed QTLs a FDR %1% as signi ican and conside ed
a ian s wi hin 1 Mb o a genes’ ansc ip ion s a si e as cis-QTLs. The signi ican eQTLs can be iewed a h ps://immune egula ion.
mssm.edu/.
168
Fu he mo e, we pe o med o e all su i al analysis based on he exp ession o in e es ing genes (ERAP2,HLA-
DQB1 and PPIL3) in he ccRCC, HNSCC, LSCC, and LUAD CPTAC coho s using he bes cu o wi h Kaplan-Meie Plo e .
194
We also used Kaplan-Meie Plo e o assess he co ela ion be ween he exp ession and o e all su i al in he TCGA coho .
Colocaliza ion Analysis o eQTLs and pQTLs
We pe o med colocaliza ion analysis o de e mine whe he he leading a ian s among he cis- eQTLs and pQTLs a e he same in
ce ain genes o in e es using ‘coloc’ R package’s coloc.Ab unc ion.
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We applied he de aul alues o he p io p obabili ies o a
SNP being associa ed wi h gene exp ession only, p o ein abundance only and wi h bo h.
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Polygenic Risk Sco es and associa ions wi h p o ein abundance
Summa y s a is ics, including isk allele, p o ec i e allele, odds a io (OR) and anno a ed gene, we e ob ained o he la ges genome-
wide associa ion s udy a ailable o each cance ype. This included ccRCC, PDAC, UCEC, GBM, LUAD, and LSCC o a o al o 133
isk a ian s (Table S7H). The same GWAS s udy was used o LUAD and LSCC as his disco e y s udy comp ised a balanced mix u e
o cases o bo h lung cance sub ypes. Polygenic isk sco es (PRS) o each cance ype we e calcula ed using he sco e ou ine a ail-
able in PLINK 2.0, weigh ing he allele dosage a each a ian by he e ec size.
In a i s pass, we checked he disc imina o y powe o he PRS by in eg a ing CPTAC and UKBB da ase s. To con ol o popu-
la ion s uc u e, o hese speci ic analyses we selec ed indi iduals o Eu opean ances y in bo h da ase s. Fo each cance ype, we
compa ed he PRSs o he co esponding sub ype wi h: a) pa ien s o o he cance ypes in CPTAC; b) indi iduals wi h cance diag-
nosis in he UKBB; and c) indi iduals wi hou cance diagnosis in he UKBB. Th ee ou o i e es ed cance s, namely PDAC, GBM,
and LSCC, showed signi ican ly highe PRSs in he co esponding CPTAC pa ien s compa ed o con ols (Figu e S7B). We ocused
on hese h ee cance s in subsequen analyses.
We iden i ied umo p o eins ha showed signi ican associa ion wi h PRS using linea models. To a oid he e ec s o hidden a i-
ables inducing co a iance in he p o ein abundance ma ix, we i s ca ied ou a p incipal componen analysis. Conside ing he ela-
i ely la ge numbe o po en ial co a ia es o he sample size in ou s udy, we pe o med a supe ised selec ion o co a ia es o be
included in he linea models. We es ed he co ela ion be ween he PRS as well as he i s en p incipal componen s (PCs) o p o ein
abundance wi h ele an clinical, demog aphic and molecula a iables, including: gene ic ances y ( i s 10 PCs), age a diagnosis,
sex, umo pu i y, and smoking in he case o lung cance s. In he linea models we only included as co a ia es hose showing sig-
ni ican co ela ion wi h he co esponding PRS and/o p o eomic PCs. Gi en ou in e es in ge mline a ian s (which a e p esen in
he di e en umo compa men s), umo pu i y was no included in any o he models despi e signi ican co ela ion. We excluded
p o eins wi h mo e han 20% o missing da a ac oss indi iduals. The e ec o he PRS was es ima ed o each p o ein using lm() unc-
ion in R wi h he ollowing designs:
lmp o ein PRS GMB +Ances yPC1 +Ances yPC2 +Ances yPC3 +Ances yPC5 +Ances yPC7 +Ances yPC10
+Age +P o einPC1 +P o einPC2 +P o einPC3 +P o einPC4 +P o einPC8
lmp o ein PRS LSCC +Ances yPC6 +P o einPC1 +P o einPC3 +P o einPC7 +P o einPC9
lmp o ein PRS PDAC +Ances yPC1 +Ances yPC2 +Ances yPC4 +Ances yPC5 +Age +P o einPC2
+P o einPC3 +P o einPC4 +P o einPC5 +P o einPC6
False disco e y a es we e es ima ed om he p- alues using he d ool R package.
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STRINGdb
173
R package ( 11.5; h ps://
www.s ing-db.o g) was used o in e he p o ein-p o ein in e ac ion ne wo ks and compu e en ichmen s o he numbe o in e ac-
ions among he op p o eins associa ed wi h PRS. The da abase con ains in o ma ion o 19,566 p o eins and o e 2.9 million in e -
ac ions. O e 93% o que ied p o eins we e p esen in he STRING da ase . We pe o med Gene Se En ichmen Analyses (GSEA)
analyses o Reac ome pa hways using he R package Reac omePA
197
wi h 10,000 pe mu a ions and signi icance h eshold o 0.05
wi h BH FDR adjus men . Disease ee su i al and o e all su i al plo s we e gene a ed using su mine ( 0.4.9; h ps://gi hub.com/
kassamba a/su mine ) and su i al (h ps://gi hub.com/ he neau/su i al) R packages, s a i ying he pa ien s acco ding o he me-
dian o he PRS sco es.
ADDITIONAL RESOURCES
Comp ehensi e in o ma ion abou he CPTAC p og am, including p og am ini ia i es, in es iga o s, and da ase s, a e a ailable a he
CPTAC p og am websi e: h ps://p o eomics.cance .go /p og ams/cp ac.
Fo he Pan-Cance p o eogenomics collec ion pape s, along wi h links o he da a and supplemen a y ma e ials associa ed wi h
hese publica ions, please isi he P o eomic Da a Commons (PDC) a h ps://pdc.cance .go /pdc/cp ac-pancance and he Can-
ce Resea ch Da a Commons a h ps://da ase ice.da acommons.cance .go /#/da a.
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Figu e S1. Sample and a ian quali y con ol p ocedu es, ela ed o Figu e 1
(A) Co e age dis ibu ion o e WES a ge egions o he en i e CPTAC coho (n= 1,064). WES samples wi h co e age R203we e used o ge mline a ian
calling.
(B) A e age WES co e age o 160 CPGs o he en i e coho . Da a a e ep esen ed as a e age co e age ±1 s anda d de ia ion (mean ±SD).
(C) Numbe o exonic ge mline a ian s de ec ed in no mal samples om CPTAC WES da a. Indi iduals a e ep esen ed by do s, which a e colo ed acco ding o
hei gene ic ances y as p edic ed by ou pipelines. A e age numbe o a ian s pe cance ype ±one s anda d de ia ion is also shown (mean ±SD).
(D) Boxplo s ep esen ing he conco dance o whole-exome-based a ian calls wi h dbSnP ( elease 151), showing >99% conco dance. O e all conco dance o
he en i e coho was 97.43%, wi h a TiT a io o 2.74.
(E) O e lap a e be ween a ian s called om WES and WGS da ase s o se en cance ypes.
(F) P incipal-componen analysis (PCA) plo s showing WES and WGS-based gene ic ances y p edic ions o he CPTAC coho . Ances y p edic ions we e
ob ained om WES da a using a andom o es classi ie o all 1,064 indi iduals (STAR Me hods). The 9 indi iduals o Sla ic o igin in he GBM, HNSCC, LSCC,
PDAC, and UCEC coho s which we e misclassi ied as AMR in he WES-based p edic ions, bu co ec ly classi ied as EUR in he WGS-based p edic ions a e
labeled (see STAR Me hods).
(G) His og ams depic ing he pep ide-leng h dis ibu ion o bo h e e ence ( op) and al e na i e (bo om) pep ides de ec ed in he p o eome (le ), phospho-
p o eome (middle), and ace ylome ( igh ).
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Figu e S2. Impac o pa hogenic a e a ian s, ela ed o Figu e 2
(A) Violin plo s showing age a diagnosis dis ibu ions in ca ie s and non-ca ie s o a e pa hogenic (P) and likely pa hogenic (LP) ge mline a ian s ac oss 10
cance ypes.
(B) Hea map showing ac ion o samples ha a e ca ie s o P/LP a e a ian s ac oss 10 cance ypes in he combined sample se o CPTAC and TCGA coho s.
Cance gene pai s wi h signi ican (FDR %0.05) and sugges i e (FDR %0.15) en ichmen wi h P/LP a ian s a e indica ed wi h black and g ay ou line
espec i ely.
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(C) Plo showing compa ison o a ian allele equencies (VAFs) o P/LP in umo and no mal samples, highligh ing a ian s unde going LOH in he umo .
Each do co esponds o one a ian , wi h he diagonal line indica ing equal umo and no mal VAFs (i.e., neu al selec ion). G een indica es sugges i e LOH
(FDR %0.15); ed is signi ican LOH (FDR %0.05); and blue indica es e en s no s a is ically signi ican .
(D) Plo showing p o ein exp ession quan iles in NAT (x axis) and umo (y axis) o he p o eins om ge mline P/LP a ian ca ie s.
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Figu e S6. EJ models o indels and moLDA summa y, ela ed o Figu e 6
(A) Simila o he main Figu e 6, EJ models a e shown o each cance ype highligh ing he i s , middle, and las exons. Two penul ima e egions wi hin 50 bps o
he las exon and g ea e han 50 bps away om he las exon a e also displayed.
(B) Squa e- oo no malized dis ibu ion o moLDA SVD sco es o each cance ype. Ve ical h eshold is se a he PanCance op 2.5% o sco es.
(C) Genes ha exceed he SVD h eshold ha all in o mul iple cance ypes.
(D) moLDA esul o CPNE1 in LUAD. Log no malized RNA-seq gene exp ession on he x axis and p o ein abundance on he y axis. Each poin ep esen s a umo
om ha cance ype.
(E) Same as (D) bu o he OAS1 gene in LSCC.
(F) Same as (D) bu o ITIH1 gene in HNSCC.
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Figu e S7. Su i al plo s and PRS dis ibu ions, ela ed o Figu e 7
(A) Kaplan-Meie su i al plo s based on ERAP2 and HLA-DQB1 exp ession and o e all su i al in CPTAC and TCGA HNSCC coho s.
(B) Polygenic isk sco e (PRS) dis ibu ions. Fo 6 cance ypes, we calcula ed he PRS in he CPTAC indi iduals using common isk a ian s disco e ed by he
la ges GWAS a ailable in each speci ic cance ype. These alues we e compa ed wi h he dis ibu ions o PRSs in h ee o he g oups, namely (1) CPTAC
indi iduals o he emaining cance ypes (‘‘CPTAC’’), (2) UKBB indi iduals diagnosed wi h any cance ype (‘‘Ukbb_cance ’’, and (3) es o UKBB indi iduals
(‘‘Ukbb_con ols’’). The p alues o s a is ical signi icance o he compa isons agains CPTAC and Ukbb_con ols, espec i ely, a e p o ided o each cance
ype ( es ).
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