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esmo.org
INDICATIONS FOR GERMLINE TESTING FROM TUMOUR-ONLY SEQUENCING
Consensus Recommendations from ESMO Working Group
ACGS Birmingham 10th
June 2019
Clare Turnbull Professor in Genomic Medicine, Queen Mary University of London and Institute of Cancer Research
Clinical Lead for Cancer Genomics, 100,000 Genomes Project, Genomics England
Consultant in Cancer Genetics (Honorary), Guys and St Thomas and Barts NHS Trusts
Consultant in Public Health Medicine (Honorary), Public Health England
Clare Turnbull, Institute of Cancer Research, Queen Mary University London (Chair),
Diana Mandelker, Memorial Sloan Kettering
Angela George, Institute of Cancer Research/Royal Marsden
Funda Meric-Bersntam, MD Anderson
Emmanuele Rial-Sebbag, University of Tolouse
Susan Wallace, University of Leicester
Meetings: 6
Data analyses: Mandelker+team, Turnbull
WORKING GROUP
Early tumour testing:
Single mutation/hot-spots testing (genotyping)
Oncogenes
NGSrecent expansion in tumour testing:
Larger panels: more genes
More patients (umbrella/drug-matching trials)
Sequencing entire gene
Tumour suppressor genes (overlap with cancer susceptibility genes)
Approach
Tumour-normal paired sequencing (WGS, research)
Tumour-only (majority including commercial providers)
WHEN SHOULD A FINDING IN THE TUMOUR-ONLY SEQUENCNG
TRIGGER A GERMLINE TEST?
BACKGROUND Somatic==acquired==tumour only
Germline==constitutional
Association with tumour
On-tumour association: “pertinent” but mainly for aetiological reasons -utility==future risk
Off-tumour association: non-“pertinent” (‘secondary’ finding) -utility==future risk
Clinical ‘actionability’ of genes (==utility of a true germline finding)
Penetrance
Gene-level: High eg BRCA1/BRCA2, Intermediate eg CHEK2 1100delC
Variant –level (ATM V2424G)
Variant Pathogenicity: confidence
?Pathogenic (Class 5), ?Likely pathogenic (Class 4) ?VUS ?hot3-VUS
CONSIDERATIONS: SCIENTIFIC/CLINICAL
Workflow, Skillset of molecular pathology lab, turnaround time
Manpower, cost,
Germline interpretation-?individualised ‘ACMG’ scoring approach
?Delay tumour reporting ?Dual reporting
Timing:
Patient information-giving
Consent
Obtaining blood sample
?Upfront in all
?Two stage approach
?Tumour-type specific approach
CONSIDERATIONS: LOGISTIC
Clare Turnbull, Institute of Cancer Research, Queen Mary University London (Chair),
Diana Mandelker, Memorial Sloan Kettering
Angela George, Institute of Cancer Research/Royal Marsden
Funda Meric-Bersntam, MD Anderson
Emmanuele Rial-Sebbag, University of Tolouse
Susan Wallace, University of Leicester
Meetings: 6
Data analyses: Mandelker+team, Turnbull
WORKING GROUP
1. 17,622 cases, paired tumour and blood sequencing using MSK-IMPACT panel
358 cases excluded: MSI-high, hyper-mutated, TMZ treated
METHODS I
TUMOUR TYPES ANALYSED Non-Small Cell Lung Cancer 2810 Germ Cell Tumor 390 Non-Hodgkin Lymphoma 72 Penile Cancer 9
Breast Cancer 2644 Thyroid Cancer 314 Small Bowel Cancer 63 Vaginal Cancer 8
Colorectal Cancer 1564 Head and Neck Cancer 295 Anal Cancer 49 Gestational Trophoblastic
Disease 6
Prostate Cancer 1207 Gastrointestinal Stromal
Tumor 233 Ampullary Carcinoma 48 Pheochromocytoma 5
Pancreatic Cancer 994 Bone Cancer 216 Thymic Tumor 45 Pineal Tumor 4
Glioma 941 Skin Cancer, Non-
Melanoma 203 Adrenocortical Carcinoma 44 Histiocytosis 3
Soft Tissue Sarcoma 680 Mesothelioma 180 Nerve Sheath Tumor 34 Hodgkin Lymphoma 3
Melanoma 665 Salivary Gland Cancer 168 Sex Cord Stromal Tumor 29 Leukemia 2
Bladder Cancer 587 Small Cell Lung Cancer 136 Sellar Tumor 25 Adenocarcinoma In Situ 1
Endometrial Cancer 569 Embryonal Tumor 130 Breast Sarcoma 24 Choroid Plexus Tumor 1
Hepatobiliary Cancer 551 Appendiceal Cancer 129 Miscellaneous Brain Tumor 15
Renal Cell Carcinoma 525 Uterine Sarcoma 129 Miscellaneous
Neuroepithelial Tumor 13
Esophagogastric Cancer 461 Gastrointestinal
Neuroendocrine Tumor 90 Retinoblastoma 12
Cancer of Unknown Primary 428 Cervical Cancer 87 Wilms Tumor 11
Ovarian Cancer 398 CNS Cancer 75 Mastocytosis 11
1. 17,622 cases, paired tumour and blood sequencing using MSK-IMPACT panel
358 cases excluded: MSI-high, hyper-mutated, TMZ treated
2. Cancer Susceptibility genes extracted from dual dataset
64 AD genes implicated in cancer susceptibility present on MSK IMPACT germline panel +1 AR
gene (MuTYH, as ACMG)
1,959,587 vars (somatic+germline)
3. Automated ‘pathogenicity pipeline’
Rare variants (MAF <0.01) 79,342 vars (somatic+germline)
Truncating if LOF gene and/or Pathogenic/LP on ClinVar 17,075 vars (somatic+germline)
Removal of low penetrance mutations in high penetrance genes (previously ‘pathogenic’
in ClinVar):
– APC (NM_000038.5) c.3920T>A (p.Ile1307Lys)
– VHL (NM_000551.3) c.598C>T (p.Arg200Trp)
– FH (NM_000143.3) c.1431_1433dupAAA (p.Lys477dup)
METHODS I
All tumours
Associated
tumours
Non-
associated
tumours
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
(A) Application of serial filters to
MSK data on 65 genes for
16,322 tumours: number of
variants
1,997,499 1,959,587
Retained: MAF≤0.01 79,342 53,388 Retained: LP/P (ClinVar) or truncating 17,075 1,494 Retained: VAF ≥ 0.3
(SNV) or ≥ 0.2 (insdel)
All 9,222 1,442 2,904 454 6,305 983 HA-CSGs (AD) 6,141 677 2,259 326 3,882 351 SA-CSGs (AD)
2,372 213 539 37 1,820 176 Other (ie recessive or NA-
CSGs) 709 547 106 91 603 456 (B) Application of ESMO-PWG
recommendations for
gene/context/age criteria based
on 10% germline conversion:
number of variants
HA-CSGs (AD) all ages (18 genes) 851 615 410 300 441 315
age <30 (APC, RB1) 63 10 37 4 26 6 age <30, on-tumour only
(TP53) 59 7 59 7 n/a n/a
Total 973 632 506 311 467 321 SA-CSGs (AD) all ages, on tumour only
(BAP1, FH, FLN, POLE), 60 17 60 17 n/a n/a age <30, on tumour only
(NF1) 9 4 9 4 n/a n/a Total 69 21 69 21 n/a n/a
Grand Total 1,042 653 575 332 467 321
1. Retain only variants where VAF in tumour is
>20% (insertion/deletion)
>30% (SNV)
METHODS II
All tumours
Associated
tumours
Non-
associated
tumours
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
(A) Application of serial filters to
MSK data on 65 genes for
16,322 tumours: number of
variants
1,997,499 1,959,587
Retained: MAF≤0.01 79,342 53,388 Retained: LP/P (ClinVar) or truncating 17,075 1,494 Retained: VAF ≥ 0.3
(SNV) or ≥ 0.2 (insdel)
All 9,222 1,442 2,904 454 6,305 983 HA-CSGs (AD) 6,141 677 2,259 326 3,882 351 SA-CSGs (AD)
2,372 213 539 37 1,820 176 Other (ie recessive or NA-
CSGs) 709 547 106 91 603 456 (B) Application of ESMO-PWG
recommendations for
gene/context/age criteria based
on 10% germline conversion:
number of variants
HA-CSGs (AD) all ages (18 genes) 851 615 410 300 441 315
age <30 (APC, RB1) 63 10 37 4 26 6 age <30, on-tumour only
(TP53) 59 7 59 7 n/a n/a
Total 973 632 506 311 467 321 SA-CSGs (AD) all ages, on tumour only
(BAP1, FH, FLN, POLE), 60 17 60 17 n/a n/a age <30, on tumour only
(NF1) 9 4 9 4 n/a n/a Total 69 21 69 21 n/a n/a
Grand Total 1,042 653 575 332 467 321
PREMLINARY ANALYSIS
Variants in 65 CSGs (64 AD, 1 AR)
MAF <0.01
Path/LP (ClinVar)/truncating
VAF>0.3 (SNPs) VAF>0.2 insdels
9,222 variants (1,442 genuine germline)
METHODS III Assignation of tumour-gene combination as ‘associated’, ‘non-associated’ (germline)
Independently reviewed by 4 cancer clinical geneticists (≥2 support ‘associated’)
Assignation of genes by actionability
High Actionability: ACMG 25 CGSs (24 AD, 1 AR)+ (PALB2, RAD51C, RAD51D, BRIP1,
SDHA):
Standard Actionability : other dominant high penetrance CSGs in clinical usage
Questionable Actionability :
– intermediate penetrance,
– uncertainty of association of monoallelic variants with disease
(BARD1)
Threshold for triggering germline test
UK: 10% rate for detection of pathogenic mutation (NICE 2013;Familial Breast Cancer).
Only single fragment test…but also ‘additional aspects on process’
– ?just molecular test (ie ‘consent’+blood draw upfront)
– ?full genetics consultation+blood draw+molecular test
ALK
APC
ATM
BAP1
BARD1
BMPR1A
BRCA1
BRCA2
BRIP1
CDH1
CDK4
CDKN2A
CHEK2
DICER1
EPCAM
ERCC3
FH FLCN
HOXB13
HRAS
KIT
KRAS
MEN
1
MET
MITF
MLH1
MSH
2
MSH
6
MUTYH
NBN
NF1
NF2
NRAS
PALB2
PDGFRA
PMS2
POLE
PTCH1
PTEN
RAD50
RAD51B
RAD51C
RAD51D
RB1
RET
RUNX1
SDHA
SDHAF2
SDHB
SDHC
SDHD
SMAD3
SMAD4
SMARCA4
SMARCB1
STK11
SUFU
TERT
TGFBR1
TGFBR2
TMEM
127
TP53
TSC1
TSC2
VHL
HA-CSG N Y N N N Y Y Y Y N N N N N N N N N N N N N Y N N Y Y Y Y N N Y N Y N Y N N Y N N Y Y Y Y N Y Y Y Y Y N Y N N Y N N N N N Y Y Y Y
Penetrance H H I H H H H H H H H H I H H H H H I H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H
Robust for clinical implementation Y Y Y Y N Y Y Y Y Y Y Y Y Y N Y Y Y Y Y Y Y Y Y N Y Y Y Y N Y Y Y Y Y Y Y Y Y N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
Adenocarcinoma In Situ
Adrenocortical Carcinoma
Ampullary Carcinoma
Anal Cancer
Appendiceal Cancer
Bladder Cancer
Bone Cancer
Breast Cancer
Breast Sarcoma
CNS Cancer
Cancer of Unknown Primary
Cervical Cancer
Colorectal Cancer
Embryonal Tumour
Endometrial Cancer
Oesophagogastric Cancer
GIST
Gastrointestinal NET
Germ Cell Tumour
Glioma
Head and Neck Cancer
Hepatobiliary Cancer
Histiocytosis
Melanoma
Mesothelioma
Miscellaneous Brain Tumour
NHL
NSCLC
Nerve Sheath Tumour
Ovarian Cancer
Pancreatic Cancer
Penile Cancer
Phaeochromocytoma
Pineal Tumour
Prostate Cancer
Renal Cell Carcinoma
Retinoblastoma
Salivary Gland Cancer
Sellar Tumour
Sex Cord Stromal Tumour
Skin Cancer
Small Bowel Cancer
Small Cell Lung Cancer
Soft Tissue Sarcoma
Thymic Tumour
Thyroid Cancer
Uterine Sarcoma
Vaginal Cancer
Wilms Tumour
neuro misc
Trophoblast
METHODS III Assignation of tumour-gene combination as ‘associated’, ‘non-associated’ (germline)
Independently reviewed by 4 cancer clinical geneticists (≥2 support ‘associated’)
Assignation of genes by actionability
High Actionability: ACMG 25 CGSs (24 AD, 1 AR)+ (PALB2, RAD51C, RAD51D, BRIP1,
SDHA):
Standard Actionability : other dominant high penetrance CSGs in clinical usage
Questionable Actionability :
– intermediate penetrance,
– uncertainty of association of monoallelic variants with disease
(BARD1)
Threshold for triggering germline test
UK: 10% rate for detection of pathogenic mutation (NICE 2013;Familial Breast Cancer).
Only single fragment test…but also ‘additional aspects on process’
– ?just molecular test (ie ‘consent’+blood draw upfront)
– ?full genetics consultation+blood draw+molecular test
HA-GENES (“ACMG+” LIST OF 30 GENES)
OFF TUMOUR:
→ 20 GENES
(19 AD+MUTYH)
HA-GENES (“ACMG+” LIST OF 30 GENES)
ON TUMOUR:
HA-GENES (“ACMG+” LIST OF 30 GENES)
OFF TUMOUR:
HA-GENES (“ACMG+” LIST OF 30 GENES)
ON TUMOUR:
HA-GENES (“ACMG+” LIST OF 30 GENES)
OFF TUMOUR:
HA-GENES (“ACMG+” LIST OF 30 GENES)
ON TUMOUR:
VHL: ALL TUMOURS
HA-GENES (“ACMG+” LIST OF 30 GENES)
OFF TUMOUR:
→ 20 GENES
(19 AD+MUTYH)
HA-GENES (“ACMG+” LIST OF 30 GENES)
ON TUMOUR:
APC: ALL TUMOURS
METHODS III Assignation of tumour-gene combination as ‘associated’, ‘non-associated’ (germline)
Independently reviewed by 4 cancer clinical geneticists (≥2 support ‘associated’)
Assignation of genes by actionability
High Actionability: ACMG 25 CGSs (24 AD, 1 AR)+ (PALB2, RAD51C, RAD51D, BRIP1,
SDHA):
Standard Actionability : other dominant high penetrance CSGs in clinical usage
Questionable Actionability :
– intermediate penetrance,
– uncertainty of association of monoallelic variants with disease
(BARD1)
Threshold for triggering germline test
UK: 10% rate for detection of pathogenic mutation (NICE 2013;Familial Breast Cancer).
Only single fragment test…but also ‘additional aspects on process’
– ?just molecular test (ie ‘consent’+blood draw upfront)
– ?full genetics consultation+blood draw+molecular test
OTHER CANCER SUSCPTIBILITY GENES: ON TUMOUR
METHODS V: ARE WE MISSING ANY GROUPS
Any idiosyncratic combinations of tumour and gene for which germline attribution is
high?
Examined all combinations
Are there subgroups of patients defined by age of cancer onset for which germline
attribution is high?
Are there genes for which there are a set of particular mutations for which germline
attribution is high?
TUMOUR-GENE
COMBINATIONS
METHODS V: ARE WE MISSING ANY GROUPS
Any idiosyncratic combinations of tumour and gene for which germline attribution is
high?
Examined all combinations
Are there subgroups of patients defined by age of cancer onset for which germline
attribution is high?
Are there genes for which there are a set of particular mutations for which germline
attribution is high?
PREMLINARY ANALYSIS:
TUMOURS ARISING AGE <30
Variants in 65 CSGs (64 AD, 1 AR)
MAF <0.01
Path/LP (ClinVar)/truncating
VAF>0.3 (SNPs) VAF>0.2 insdels
All (on tumour AND off tumour)
Examining HA genes
HA-GENES (“ACMG+” LIST OF 30 GENES)
ON TUMOUR:
AGE<30: ALL GENES; ON TUMOUR
Examining SA
genes
And ?HA too
METHODS IV: ARE WE MISSING ANY GROUPS
Any idiosyncratic combinations of tumour and gene for which germline attribution is
high?
Examined all combinations
Are there subgroups of patients defined by age of cancer onset for which germline
attribution is high?
Are there genes for which there are a set of particular mutations for which germline
attribution is high?
Variant Total tumour-observed variants Germline origin Somatic origin
c.527G>T p.C176F 17 1 16
c.665delC p.P222Rfs*25 2 1 1
c.713G>C p.C238S 2 1 1
c.422G>A p.C141Y 6 1 5
c.818G>C p.R273P 4 1 3
c.916C>T p.R306* 32 2 30
c.273G>A p.W91* 10 2 8
c.743G>A p.R248Q 103 2 101
c.742C>T p.R248W 89 2 87
c.586C>T p.R196* 51 1 50
c.1009C>T p.R337C 17 1 16
c.638G>A p.R213Q 8 1 7
c.818G>A p.R273H 104 1 103
c.536A>G p.H179R 17 1 16
c.919+1G>C
p.X307_splice 2 1 1
c.524G>A p.R175H 157 1 156
c.733G>A p.G245S 52 2 50
c.542G>A p.R181H 3 2 1
c.403T>C p.C135R 5 1 4
c.844C>G p.R282G 7 1 6
TP53: ANALYSIS
BY MUTATION
1) Germline-focused analysis should be performed routinely on tumour-only sequencing (where
there is full sequencing of genes which are involved in cancer susceptibility)
2) Germline follow-up should be undertaken when ≥10% likelihood of variant in HA/SA gene
being germline in origin
3) Analyse only for Class 4/5 germline variants is reccommended
4) Analyse only genes with strong evidence for AD cancer susceptibility (not BARD1, NBN)
5) Intermediate penetrance genes (CHEK2, ATM) do not need to be included.
6) An automated LOF+ClinVar pipeline can be applied
SUMMARY: RECOMMENDATIONS (GENERAL)
1) HA-CSGs (on and off tumour): 19 +1 genesBMPR1A, BRCA1, BRCA2, BRIP1, MLH1,
MSH2, MSH6, MUTYH*, PALB2, PMS2, RAD51C, RAD51D, RET, SDHA, SDHAF2, SDHB,
SDHC, SDHD, TSC2, VHL**,
2) SA-CSGs (on tumour only): FH, FLCN, BAP1, POLE
3) Analysis if tumour arose <30
1) On and off tumour: RB1, APC
2) On tumour: NF1, TP53***
1. Ahead of confirmatory analysis in germline sample, patients should be provided with
information and offered option to opt-in or opt-out of analysis of germline sample
SUMMARY: RECOMMENDATIONS (SPECIFIC)
MuTYH only taken forwards if biallelic mutations present *VHL analysis not recommended in renal cancers, *** TP53 analysis not recommended in brain cancers
SUMMARY: RECOMMENDATIONS (CONSENT)
All tumours
Associated
tumours
Non-
associated
tumours
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
Tu
mour
dete
cte
d
Tru
e
germ
line
(A) Application of serial filters to
MSK data on 65 genes for
16,322 tumours: number of
variants
1,997,499 1,959,587
Retained: MAF≤0.01 79,342 53,388 Retained: LP/P (ClinVar) or truncating 17,075 1,494 Retained: VAF ≥ 0.3
(SNV) or ≥ 0.2 (insdel)
All 9,222 1,442 2,904 454 6,305 983 HA-CSGs (AD) 6,141 677 2,259 326 3,882 351 SA-CSGs (AD)
2,372 213 539 37 1,820 176 Other (ie recessive or NA-
CSGs) 709 547 106 91 603 456 (B) Application of ESMO-PWG
recommendations for
gene/context/age criteria based
on 10% germline conversion:
number of variants
HA-CSGs (AD) all ages (18 genes) 851 615 410 300 441 315
age <30 (APC, RB1) 63 10 37 4 26 6 age <30, on-tumour only
(TP53) 59 7 59 7 n/a n/a
Total 973 632 506 311 467 321 SA-CSGs (AD) all ages, on tumour only
(BAP1, FH, FLN, POLE), 60 17 60 17 n/a n/a age <30, on tumour only
(NF1) 9 4 9 4 n/a n/a Total 69 21 69 21 n/a n/a
Grand Total 1,042 653 575 332 467 321
In 17,622 large tumour panels:
ON-TUMOUR: 575 germline tests 332 true germline (57%)
OFF TUMOUR: 487 germline tests 321 true germline (66%)
COMBINED: 1042 germline tests (6.7%) 653 true germline (63%)
IMPACT
Working Group:
Clare Turnbull, Institute of Cancer Research, Queen Mary University London (Chair),
Diana Mandelker, Memorial Sloan Kettering
Angela George, Institute of Cancer Research/Royal Marsden
Funda Meric-Bersntam, MD Anderson
Emmanuele Rial-Sebbag, University of Tolouse
Susan Wallace, University of Leicester
ESMO: Svetlana Jezdic, Fabrice Andre, Jean-Yves Douillard
Expert Genetics Panel: Drs Helen Hanson, Katie Snape, Anjana Kulkani
Painless access to MSK data: Prof Marc Ladyani
ACKNOWLEDGEMENTS