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Background Among patients with non–small-cell lung cancer (NSCLC), data on intratumor heterogeneity and cancer genome evolution have been limited to small retrospective cohorts. We wanted to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to determine the clonal nature of driver events and evolutionary processes in early-stage NSCLC. Methods In this prospective cohort study, we performed multiregion whole-exome sequencing on 100 early-stage NSCLC tumors that had been resected before systemic therapy. We sequenced and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between intratumor heterogeneity and recurrence-free survival. Results We observed widespread intratumor heterogeneity for both somatic copy-number alterations and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always clonal. However, heterogeneous driver alterations that occurred later in evolution were found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes that are involved in chromatin modification and DNA damage response and repair. Genome doubling and ongoing dynamic chromosomal instability were associated with intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy-number heterogeneity was associated with an increased risk of recurrence or death (hazard ratio, 4.9; P=4.4×10⁻⁴), which remained significant in multivariate analysis. Conclusions Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor. (Funded by Cancer Research UK and others; TRACERx ClinicalTrials.gov number, NCT01888601.)
Content may be subject to copyright.
The new england
journal of medicine
n engl j med 376;22 nejm.org June 1, 2017
2109
established in 1812
June 1, 2017
vol. 376 no. 22
The authors’ full names, academic de-
grees, and af filiations are listed in the
Appendix. Address reprint requests to
Dr. Swanton at the Translational Cancer
Therapeutics Laboratory, Francis Crick
Institute, 3rd Fl. SW, 1 Midland Rd., Lon-
don NW1 1AT, United Kingdom, or at
charles . swanton@ crick . ac . uk.
* A complete list of investigators in the
Tracking Non–Small-Cell Lung Cancer
Evolution through Therapy (TRACERx)
Consortium is provided in Supplemen-
tary Appendix 1, available at NEJM.org.
Drs. Jamal-Hanjani, Wilson, McGranahan,
Birkbak, and Veeriah and Mr. Watkins con-
tributed equally to this ar ticle.
This arti cle was published on Apr il 26, 2017,
at NEJM.org.
N Engl J Me d 2017;376:2109-21.
DOI: 10.1056/NEJMoa1616288
Copyright © 2017 Massachusetts Medical Society.
BACKGROUND
Among patients with non–small-cell lung cancer (NSCLC), data on intratumor heterogeneity
and cancer genome evolution have been limited to small retrospective cohorts. We wanted
to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to
determine the clonal nature of driver events and evolutionary processes in early-stage NSCLC.
METHODS
In this prospective cohort study, we performed multiregion whole-exome sequencing on
100 early-stage NSCLC tumors that had been resected before systemic therapy. We sequenced
and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal
and subclonal events, and assess the relationship between intratumor heterogeneity and
recurrence-free survival.
RESULTS
We observed widespread intratumor heterogeneity for both somatic copy-number altera-
tions and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always
clonal. However, heterogeneous driver alterations that occurred later in evolution were
found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes
that are involved in chromatin modification and DNA damage response and repair.
Genome doubling and ongoing dynamic chromosomal instability were associated with
intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number
alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy-number
heterogeneity was associated with an increased risk of recurrence or death (hazard ratio,
4.9; P = 4.4×10
−4
), which remained significant in multivariate analysis.
CONCLUSIONS
Intratumor heterogeneity mediated through chromosome instability was associated with
an increased risk of recurrence or death, a f inding that supports the potential value of
chromosome instability as a prognostic predictor. (Funded by Cancer Research UK and
others; TRACERx ClinicalTrials.gov number, NCT01888601.)
abs tr act
Tracking the Evolution of Non–Small-Cell Lung Cancer
M. Jamal-Hanjani, G.A. Wilson, N. McGranahan, N.J. Birkbak, T.B.K. Watkins, S. Veeriah, S. Shafi, D.H. Johnson,
R. Mitter, R. Rosenthal, M. Salm, S. Horswell, M. Escudero, N. Matthews, A. Rowan, T. Chambers, D.A. Moore,
S. Turajlic, H. Xu, S.-M. Lee, M.D. Forster, T. Ahmad, C.T. Hiley, C. Abbosh, M. Falzon, E. Borg, T. Marafioti,
D. Lawrence, M. Hayward, S. Kolvekar, N. Panagiotopoulos, S.M. Janes, R. Thakrar, A. Ahmed, F. Blackhall,
Y. Summers, R. Shah, L. Joseph, A.M. Quinn, P.A. Crosbie, B. Naidu, G. Middleton, G. Langman, S. Trotter,
M. Nicolson, H. Remmen, K. Kerr, M. Chetty, L. Gomersall, D.A. Fennell, A. Nakas, S. Rathinam, G. Anand,
S. Khan, P. Russell, V. Ezhil, B. Ismail, M. Irvin-Sellers, V. Prakash, J.F. Lester, M. Kornaszewska, R. Attanoos,
H. Adams, H. Davies, S. Dentro, P. Taniere, B. O’Sullivan, H.L. Lowe, J.A. Hartley, N. Iles, H. Bell, Y. Ngai,
J.A. Shaw, J. Herrero, Z. Szallasi, R.F. Schwarz, A. Stewart, S.A. Quezada, J. Le Quesne, P. Van Loo, C. Dive,
A. Hackshaw, and C. Swanton, for the TRACERx Consortium*
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L
ung cancer is the leading cause of
cancer-related death worldwide,
1,2
with non–
small-cell lung cancer (NSCLC) being the
most common type. Large-scale sequencing stud-
ies have revealed the complex genomic landscape
of NSCLC
3-6
and genomic differences between lung
adenocarcinomas and lung squamous-cell carcino-
mas.
7
However, in-depth exploration of NSCLC
intratumor heterogeneity (which provides the fuel
for tumor evolution and drug resistance) and can-
cer genome evolution has been limited to small
retrospective cohorts.
8,9
Therefore, the clinical
signif icance of intratumor heterogeneity and the
potential for clonality of driver events to guide
therapeutic strategies have not yet been def ined.
Tracking Non–Small-Cell Lung Cancer Evolu-
tion through Therapy (TRACERx)
10
is a multi-
center, prospective cohort study, which began
recruitment in April 2014 with funding from
Cancer Research UK. The target enrollment is
842 patients from whom samples will be obtained
for high-depth, multiregion whole-exome se-
quencing of surgically resected NSCLC tumors in
stages IA through IIIA. One primary objective of
TRACERx is to investigate the hypothesis that in-
tratumor heterogeneit y — in terms of mutations
(single or dinucleotide base substitutions or small
insertions and deletions) or somatic copy-number
alterations (reflecting gains or losses of chromo-
some segments) — is associated with clinical
outcome. Here, we report on the f irst 100 patients
who were prospectively recruited in the study.
Methods
Patients and Tumor Sample s
We collected tumor samples from 100 patients
with NSCLC who had not received previous sys-
temic therapy (Fig. 1A; and Fig. S1 in Supplemen-
tar y Appendix 1, available with the full text of
this article at NEJM.org). Identifiers of patients
were reassigned to protect anonymity and were
ordered according to intratumor heterogeneity
and histologic subtype. Eligible patients were at
least 18 years of age and had received a diagno-
sis of NSCLC in stages IA through IIIA (except
Patient CRUK0035, whose tumor was classified
as stage IIIB on the basis of postoperative histo-
logic analysis). The cohort was representative of
a population of patients with NSCLC who were
eligible for curative resection. Histologic data
were confirmed on central review by a lung pa-
thologist. (Details regarding the study design are
provided in the protocol, available at NEJM.org.)
To assess intratumor heterogeneity, samples
of at least two tumor regions that were separated
by a margin of 0.3 cm to 1 cm (depending on the
size of the tumor) had to be available for study.
None of the tumors carried a translocation in
ALK, ROS1, or RET on the basis of sequencing.
This finding was confirmed for ALK and ROS1
with the use of immunohistochemical testing.
All the patients provided written informed con-
sent. The clinical characteristics of the patients
and the study criteria are provided in Tables S1
and S2 and in the Experimental Procedures sec-
tion in Supplementar y Appendix 1.
Multiregion Whole-Ex ome Sequencing
We used the Illumina HiSeq to perform whole-
exome sequencing on multiple regions collected
from each tumor. We sequenced 327 tumor re-
gions (323 primary tumor regions and 4 lymph-
node metastases) and 100 matched germline sam-
ples derived from whole blood (median number,
3 regions per tumor; range, 2 to 8), to a median
depth of 426× (Table S3 in Supplementary Ap-
pendix 1). Orthogonal validation was performed
(Table S4 and Fig. S2 in Supplementary Appen-
dix 1). All sequencing data have been deposited
in the European Genome–Phenome Archive under
accession number EGAS00001002247.
Results
Intratumor Heterogeneity in NSCLC
Genetic diversity within tumors can act as a
substrate for natural selection and tumor evolu-
Figure 1 (facing page). Overview of the Demographic
and Clinical Characteristics of the Patients
in the TRACERx Study.
Panel A shows the demographic and clinical character-
istics of the 100 patients in the study, including diag-
nosis, tumor stage, and smoking status. Panel B shows
how multiregion sequencing was performed on surgi-
cally resec ted tumors to analyze somatic mutations
and copy-number alterations, which facilitated the as-
sessment of intratumor heterogeneity and phylogenetic
reconstruction. Stars on the schematic chromosomes
indicate mutations, where yellow represents clonal pre-
genome doubling mutations, pink represents clonal
postgenome doubling mutations, and red represents
subclonal mutations. Panel C shows the key clinical
questions that were addressed in the study.
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2111
Tracking the Evolution of Non–Small-Cell Lung Cancer
ATRACERx 100 Cohort
BMultiregion Intratumor Heterogeneity Analysis
CClinical Questions
R2
R2
R2
R2
R1
R2
R3
R4
Multiregion Sampling
Multiregion Mutation and
Copy-Number Analysis Clonal Hierarchy and Phylogeny
Surgery with
Curative Intent
Intratumor Heterogeneity and Survival Causes of Intratumor Heterogeneity Census of Clonal and Subclonal Drivers
R1 R2 R3 R4
Genome
doubling
Subclonal
mutations
Late clonal
mutations
Early clonal
mutations
Genome doublingMutational heterogeneity and survival Clonal status of targetable alterations
Chromosomal instability
Mutational processes
GCGATCACGAC
CGCTAGTGCTG
GCGATTACGAC
CGCTAATGCTG
R1 R2
R3 R4
Copy-number heterogeneity and survival
Time
% Alive
Time
% Alive
Never smoked (N=12) Former smoker (N=48) Current or recent smoker (N=40) 62 Men, 38 Women
1B
3A
2B
Lung Adenocarcinoma (N=61)
Stage 1A (N=26) Stage 1B (N=36) Stage 2A (N=13) Stage 2B (N=11) Stage 3A (N=13) Stage 3B (N=1)
Other (N=7)
Lung Squamous-Cell Carcinoma (N=32)
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tion. We performed multiregion whole-exome
sequencing on 100 TRACERx tumors and classi-
fied somatic mutations, which were def ined as
coding and noncoding single-nucleotide variants,
and copy-number alterations, which were measured
as a percentage of the genome affected by such
alterations, as clonal (present in all cancer cells)
or subclonal (present in a subset of cancer
ce lls) (Fig. 1).
We observed extensive intratumor heteroge-
neity, with a median of 30% (range, 0.5 to 93) of
somatic mutations identified as subclonal and a
median of 48% (range, 0.3 to 88) of copy-number
alterations as subclonal (Fig. 2A, and Fig. S3 in
Supplementary Appendix 1). This finding sug-
gests that genomic-instability processes at the
mutational and chromosomal level are ongoing
during tumor development. Considerable varia-
tion in intratumor heterogeneity among tumors
was also observed, with the number of subclonal
mutations ranging from 2 to 2310 and the per-
centage of the genome affected by subclonal copy-
number alterations ranging from 0.06 to 81%
(Fig. 2A). Without multiregion whole-exome se-
quencing, 76% of subclonal mutations could have
appeared to be clonal, which suggests the selec-
tion of subclones within individual tumor regions
(Fig. S4 in Supplementary Appendix 1). Signif i-
cantly more mutations were identified with the
use of multiregion whole-exome sequencing than
with single-sample analysis (median number, 517
vs. 398; P = 0.009) or with the use of single NSCLC
samples obtained from the Cancer Genome Atlas
(median number, 207; P<0.001) (Fig. S5 in Supple-
mentary Appendix 1). The Cancer Genome Atlas
research network (http://cancergenome . nih . gov)
was retrieved through dbGaP authorization acces-
sion number phs000178.v9.p8.
Squamous-cell carcinomas carried significant-
ly more clonal mutations than did adenocarcino-
mas (P = 0.003) (Fig. S6 in Supplementary Ap-
pendix 1). This finding potentially ref lects
differences in smoking history, with a median of
32 pack-years for adenocarcinomas and 41 pack-
years for squamous-cell carcinomas (P = 0.047)
(Fig. S7 in Supplementary Appendix 1). There were
no significant differences between squamous-cell
carcinomas and adenocarcinomas in the number
or proportion of subclonal mutations (P = 0.72)
(Fig. S6 in Supplementar y Appendix 1) or within
specif ic adenocarcinoma histopathological sub-
types (Fig. S8 in Supplementary Appendix 1). In
squamous-cell carcinomas, no significant rela-
tionship was observed between intratumor hetero-
geneity and clinical variables (Table S5 in Sup-
plementary Appendix 1).
In adenocarcinomas, tumor stage positively
correlated with the proportion of subclonal copy-
number alterations, and Ki67 staining positively
correlated with the burden of both clonal and
subclonal mutations, as well as with the propor-
tion of subclonal copy-number alterations (Table
S5 in Supplementary Appendix 1). Furthermore,
in adenocarcinomas, a signif icantly higher clonal
and subclonal mutational burden was observed
in smokers than in patients who had never smoked
(Fig. S9 in Supplementar y Appendix 1).
There was no signif icant association between
the proportion of subclonal mutations (median in
the cohort, 30%) and relapse-free survival (Fig.
2B). However, in this preliminary analysis, patients
who had tumors with a high proportion of sub-
clonal copy-number alterations (≥48%, the co-
hort median) were at higher risk for recurrence
or death than those with a low proportion (haz-
ard ratio, 4.9; 95% confidence interval [CI], 1.8 to
13.1; P = 4.4×10
−4
) (Fig. 2C). The median time
until recurrence or death was 24.4 months in the
higher risk group of patients compared with a
median that was not reached in the lower risk
group. This finding remained significant in a
multivariate analysis after adjustment for age,
pack-years of smoking, histologic subtype, adju-
Figure 2 (facing page). Genomic Heterogeneity
of Tumors Obtained from Patients with Non–Small-
Cell Lung Cancer (NSCLC).
Panel A shows the number of coding and noncoding
mutations that were detec ted in each tumor region in
the study, according to tumor stage, smoking history,
outcome of recurrence or death, and number of regions
affected. The percentages of somatic mutations and
copy-number alterations that were found to be clonal
or subclonal in each tumor are shown below the num-
ber of mutations. The percentages of study patients
who were disease -free over a 30-month period are
shown according to whether the patients had a high
proportion (above the median) or a low proportion
(below the median) of subclonal mutations (Panel B)
or of subclonal copy-number alterations (Panel C).
There was no signif icant association between the pro-
portion of subclonal mutations and relapse-free sur-
vival (P = 0.70), but patients who had tumors with a
high proportion of subclonal copy-number alterations
were at significantly higher risk for recurrence or death
than those with a low proportion (P = 4.4×10
−4
).
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Tracking the Evolution of Non–Small-Cell Lung Cancer
vant therapy, and tumor stage (hazard ratio,
3.70; 95% CI, 1.29 to 10.65; P = 0.01) (Table S6
in Supplementary Appendix 1). A static measure
of chromosome disruption (describing the mean
proportion of the genome that was aberrant
across tumor regions) was not associated with
No. of Coding and Noncoding
Mutations per Tumor
4000
2000
3000
1000
0
Copy Number,
Percentage
Subclonal
Tumor Stage
Pack-Years
Recurrence or Death
No. of Regions
100
60
80
40
20
0
Mutation,
Percentage
Subclonal
100
60
80
40
20
0
AIntratumor Heterogeneity
Subclonal
Clonal
No Yes
Disease-free Survival (%)
100
60
80
40
20
0
05 10 15 20 25 30
Months to Death or Recurrence
BDisease-free Survival According to Percentage of Subclonal Mutations
Hazard ratio, 0.86 (95% CI, 0.40 –1.85)
P=0.70
No. at Risk
Low
High
49
51
40
49
36
43
31
35
21
21
7
4
0
0
Low
High
Low
High
Disease-free Survival (%)
100
60
80
40
20
0
05 10 15 20 25 30
Months to Death or Recurrence
CDisease-free Survival According to Percentage of Subclonal
Copy-Number Alterations
Hazard ratio, 4.9 (95% CI, 1.8 –13.1)
P=4.4×10 4
No. at Risk
Low
High
47
45
42
40
40
32
36
24
19
18
5
4
0
0
13001a 1b 2 3 4 5 6 7 8
Adenocarcinoma Squamous-Cell Carcinoma Other
Patients 1– 61 Patients 62– 93 Patients
94– 100
Tumor Stage Pack-Years Recurrence or Death No. of Regions
2a 2b 3a 3b
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survival, which suggests that the rate of ongoing
dynamic chromosomal instability, rather than the
state of the genome, is prognostic (Fig. S10 in
Supplementary Appendix 1).
Evolutionary Histories and Tumor Clonal
Architecture in NSCLC
The number or proportion of subclonal muta-
tions does not fully capture the extent of intra-
tumor heterogeneit y, since these measures do not
ref lect the number or prevalence of genetically
distinct subclones that evolve in space and time.
To elucidate subclones within regions and map
the evolutionary history of each tumor, we clus-
tered mutations according to their cellular prev-
alence. Each cluster represents a node on the
phylogenetic tree of the tumor and a subclone
that is present in the tumor population or has
existed during its evolutionary history (Table S7,
Figs. S11 and S12, and the Experimental Proce-
dures section in Supplementary Appendix 1).
We identified 525 mutation clusters, with a
median of 5 per tumor (range, 2 to 15). Most
tumor regions (86%) were found to carry sub-
clones from only a single branch of the phyloge-
netic tree, which emphasizes the limitations of
a single diagnostic biopsy sample in accurately
capturing the true extent of intratumor hetero-
geneity. Without the use of multiregion whole-
exome sequencing, 65% of branched subclone
clusters could have erroneously appeared to be
clonal.
Causes of Intratumor Heterogeneity in NSCLC
Mutational Processes
Understanding how mutational processes shape
tumor evolution may inform strategies to limit
tumor adaptation in the clinical setting.
11
Using
published mutational signatures,
12
we analyzed
clonal and subclonal mutations to determine
which mutational processes contributed to intra-
tumor heterogeneit y.
The number of early mutations (accumulated
before genome doubling or copy-number change)
signif icantly correlated with the burden of muta-
tions associated with smoking (mutational sig-
nature 4), with Spearman’s rank correlations of
0.90 (P<1.1×10
−16
) for adenocarcinomas and of
0.84 (P = 3.9×10
−9
) for squamous-cell carcinomas.
This finding was consistent with the identif ica-
tion of mutations induced by tobacco carcino-
gens as being a key influence on trunk length
(i.e., the number of mutations found in the most
recent common ancestor of all cancer cells) and
was ref lected in the significant correlation be-
tween pack-years and truncal signature 4 muta-
tions in adenocarcinomas (Spearman’s rank cor-
relation, 0.63; P = 5.3×10
−8
). In samples obtained
from 7 of 12 patients with adenocarcinomas who
were long-term former smokers (with >20 years
since last tobacco exposure), a smoking signa-
ture could be detected in late clonal mutations
(>30% with signature 4). This finding was sug-
gestive of a long period of tumor latency in the
evolution of lung adenocarcinomas before clini-
cal presentat ion.
In squamous-cell carcinomas, no signif icant
correlation was observed between pack-years and
smoking-related signature 4 (Spearman’s rank
correlation, 0.10; P = 0.57), and the timing of
genome doubling (ratio of the number of early
mutations to the number of late mutations) was
signif icantly later than in adenocarcinomas (Fig.
S13 in Supplementary Appendix 1). Intriguingly,
Patient CRUK0093, who had squamous-cell car-
cinoma, had a large burden of clonal signature
4 mutations (>1000) despite having been identi-
fied as a lifelong nonsmoker. This patient’s oc-
cupational history indicated exposure to chemicals
that included arsenic, benzene, bisphenol, and
polybrominated diphenyl ethers and coal tar,
which may mimic the mutagenic effects of to-
bacco exposure.
There were signif icant correlations between
the subclonal mutation burden and the number
of subclonal mutations that were classified as
clocklike signatures 1A (spontaneous deamina-
tion of methylated cytosines) and 5 (of unknown
cause).
13
The number of subclonal mutations was
also significantly correlated with signatures 2 and
13 (induced by APOBEC, a family of cytidine
deaminase enzymes involved in messenger RNA
editing) but not with signature 4 (smoking)
12
(Fig.
S14 in Supplementary Appendix 1). (APOBEC cy-
tidine deaminases, which are usually involved in
innate immunity and RNA editing, have been
found to be enriched in several tumor t ypes and
act as an important source of mutagenesis.
14
)
Tumors with the largest subclonal mutation bur-
den had extensive APOBEC-mediated mutagene-
sis (e.g., those obtained from Patients CRUK0001,
CRUK0006, CRUK0020, and CRUK0063), and
spatial heterogeneity in APOBEC mutations was
observed in 15 tumors (Figs. S11 and S14 in
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Tracking the Evolution of Non–Small-Cell Lung Cancer
Supplementary Appendix 1). Tumors obtained
from 19 patients had subclonal driver mutations
that could be attributed to APOBEC activity,
which illustrates how APOBEC mutagenesis may
frequently induce a subclonal driver event that
may contribute to subclonal expansions.
Chromosomal Instability and Genome Doubling
Given the association between intratumor hetero-
geneity characterized by copy-number alterations
and shorter relapse-free survival, we further ex-
plored the dynamics of chromosomal alterations
in different tumor regions and the extent to
which chromosomal instability may drive intra-
tumor heterogeneity. By leveraging germline
heterozygous single-nucleotide polymorphisms
in tumors by means of multiregion whole-exome
sequencing, it is possible to determine whether
the same or distinct parental alleles are gained or
lost in distinct subclones on different branches
of the phylogenetic tree of a tumor. Specifically,
if the maternal allele is gained or lost in a sub-
clone in one region, yet the paternal allele is
gained or lost in a different subclone in another
region, it will result in a mirrored subclonal al-
lelic imbalance profile (Fig. 3A and 3B). Such an
imbalance, which indicates additional ongoing
chromosomal instability, may also reflect parallel
Figure 3. Drivers of Intratumor Heterogeneity.
Panel A shows an example of mirrored subclonal allelic imbalance. This occurs when the maternal allele is gained or lost in a subclone in
one region and the paternal allele is gained or lost in a different subclone in another region. Such imbalance indicates additional ongoing
chromosomal instability and can be inferred through multiregion whole -exome sequencing by using the frequencies at which heterozy-
gous germline single-nucleotide polymorphisms (SNPs) (termed B-allele frequency [BAF]) are detected. The BAF of heterozygous SNPs
is plotted in the same color as their parental chromosome of origin. Panel B shows the BAF profile across the genome of a tumor sample
obtained from Patient CRUK0062. Areas of BAF in regions (including tumor regions R1 through R7 and a germline [GL] reference region)
that have mirrored subclonal allelic imbalance are highlighted in blue or orange. Events that showed mirrored subclonal allelic imbalance
were identified in more than 40% of the genome. Panel C shows phylogenetic trees that indicate parallel evolution of driver amplifica-
tions detec ted through the observation of mirrored subclonal allelic imbalance (arrows). Subclones that are colored blue carr y a cancer
driver event, and those that are colored gray carry no driver event; black outlining of the circles indicates that the subclone appears to be
clonal in at least one tumor region.
AMirrored Subclonal Allelic Imbalance BBAF Profile in a Single Tumor Sample
CPhylogenetic Trees Indicating Parallel Evolution of Driver Amplifications
12345678910 11 12 13 14 15161718
19 22
21
20
Chromosomes
R2
R3
R1
R4
R5
R6
R7 0.7
0.3
0.7
0.3
0.7
0.3
0.7
0.3
0.7
0.3
0.7
0.3
0.7
0.3
0.7
0.3
GL
0.7
0.3
R2
1 maternal
2 paternal
CRUK0062 Region BAF
Germline
BAF
Maternal chromosome
Paternal chromosome
1
1
0.7
0.3
0.7
R1
2 maternal
1 paternal
0.3
CRUK0012
MUC1
amp
MUC1
amp
CRUK0083
CCNB1IP1
CHD8
NKX2-1
FOXA1
amp
CCNB1IP1
CHD8
NKX2-1
FOXA1
amp
CRUK0072
BCL11A
REL
XPO1
amp
BCL11A
REL
XPO1
amp
CRUK0009
RHOH
PHOX2B
amp
RHOH
PHOX2B
amp
CRUK0001
CDK4
LRIG3
amp
CDK4
LRIG3
amp
CDK4
LRIG3
amp
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evolution involving multiple distinct events con-
verging on the same genes in different subclones
(Fig. S15 in Supplementary Appendix 1). This
phenomenon was obser ved in 62% of 92 tumors
with copy-number data on multiregion whole-
exome sequencing (found in 30 adenocarcino-
mas, 23 squamous-cell carcinomas, and 4 other
samples). In total, we detected 375 mirrored
subclonal allelic imbalance events that varied in
size from focal to whole chromosome and in-
volved 1 to 43% of affected tumor genomes (Fig.
S16 in Supplementary Appendix 1).
Chromosomal instabilit y may also directly con-
tribute to mutational heterogeneity through loss
of genomic segments carr ying clonal mutations.
Overall, a median of 13% of subclonal mutations
(range, 0 to 56) per sample are probably sub-
clonal as a result of loss events associated with
copy-number alterations, which suggests that
chromosomal instability may be an initiator of
both copy-number and mutational heterogeneity
(Fig. S17 in Supplementary Appendix 1).
Accumulating evidence suggests that genome-
doubling events are associated with the propaga-
tion of chromosomal instability by cancer cells
and may predict a poor prognosis.
15 -17
Genome-
doubling events were identified in 76% of tumors
and appeared to be clonal in all but three of
these t umors (from Patients CRUK0011, CRUK0062,
and CRUK0063), which suggests that whole-
genome duplication is an early event in NSCLC
evolution. In adenocarcinomas, we observed a
significant association bet ween genome doubling
and the frequency of both subclonal mutations
(P = 0.02) and subclonal copy-number alterations
(P = 0.003) (Fig. S18 in Supplementary Appendix 1).
Moreover, mirrored subclonal allelic imbalance
was signif icantly enriched in genome-doubled
tumors (P = 0.004 by Fisher’s exact test) (Fig. S16
in Supplementary Appendix 1).
Selection and Parallel Evolution
Deciphering evidence of ongoing selection in tu-
mors may shed light on evolutionary constraints,
which may identify therapeutic targets. Con-
straints and selection are exemplified by the oc-
currence of parallel evolution, in which somatic
events in distinct branches within a single tumor
converge on the same gene, protein complex, or
pathway.
No evidence of parallel evolution was found
at the mutational level. However, focal amplifi-
cations of different parental alleles in distinct
subclones occurred in 5 tumors and affected
known cancer genes, including MUC1, CDK4,
CHD8, and N K X2-1 (Fig. 3C, and Fig. S19 in Sup-
plementary Appendix 1). At the chromosome-arm
level, potential parallel evolution was observed in
13 tumors (5 adenocarcinomas, 6 squamous-cell
carcinomas, and 2 other tumors). Most parallel
evolution of chromosome-arm gains (in 10 of 11
samples) and losses (in 6 of 8 samples) have
been previously classified as significantly gained
or lost in NSCLC,
3,7
a finding that is consistent
with positive selection operating later in tumor
evolution (Fig. S20, S21, and S22 in Supplemen-
tar y Appendix 1).
To empirically estimate positive selection at
the mutational level, we used a ratio of substitu-
tion rates at nonsynonymous sites to those at
synonymous sites (dN/dS) that accounts for the
trinucleotide context of each mutation and de-
termines whether there is an enrichment of
protein-altering mutations as compared with the
background mutation rate.
18
Evidence for positive
selection (dN/dS, >1) was observed when all exonic
missense mutations were considered (Table S8
in Supplementary Appendix 1). This finding sug-
gests that mutations may be shaped by selection
in NSCLC. However, when mutations were tem-
porally dissected, signif icant positive selection
was observed for late, but not early, mutations.
Consistent with this f inding, nonsense mutations
were found to be depleted (dN/dS, <1) early but
not late in tumor development. These data fur-
ther suggest that selection is persistent in NSCLC
evolution and that constraints shape evolution-
ary trajectories. Depletion of early nonsense mu-
tations (dN/dS, <1) was greater in squamous-cell
carcinomas than in adenocarcinomas, and t he
rate of acquisition of clonal driver mutations (as
determined by the ratio of driver mutations to
passenger mutations) was significantly greater
in adenocarcinomas than in squamous-cell car-
cinomas (P = 0.001 by the Wilcoxon test).
Clonal and Subclonal Driver Alterations
and Timing of Genomic Events
Determining whether a cancer driver event oc-
curs early or late can indicate whether it is in-
volved in tumor initiation or maintenance, and
its clonality may inform potential therapeutic
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2117
Tracking the Evolution of Non–Small-Cell Lung Cancer
strategies, since subclonal alterations will be
present in only a proportion of cells and when
targeted may result in reduced treatment effi-
cac y.
19
We identified 795 driver events (range in
adenocarcinomas, 1 to 19; range in squamous-
cell carcinomas, 2 to 21). Of these events, 219 in
77 tumors were found to be subclonal (range in
adenocarcinomas, 0 to 10; range in squamous-
cell carcinomas, 0 to 12) and 576 to be clonal
(range in adenocarcinomas, 1 to 18; range in
squamous-cell carcinomas, 1 to 14) (Fig. S23 in
Supplementary Appendix 1 and Table S9 in Sup-
plementary Appendix 2). Significantly more driver
alterations were identif ied with the use of multi-
region whole-exome sequencing than with single-
sample analysis (P = 0.004 by the Wilcoxon test)
(Fig. S24 in Supplementary Appendix 1).
Alterations in cert ain cancer genes were not
only primarily clonal but almost always occurred
before genome duplication, which suggests in-
volvement in tumor initiation (Fig. 4). In adeno-
carcinomas, these alterations included targeta-
ble mutations or amplif icat ions in EGFR, MET, and
BRAF, as well as amplifications in TE R T, 8p loss,
and 5p gain. In squamous-cell carcinomas, muta-
tions in NOTCH1, amplifications in FGFR1 and in
the 3q region (which includes SOX2 and PIK3CA),
and loss of 3p, 4p, 5q, and 17p were early clonal
events. Mutations in T P53 were predominantly
clonal and early for both subtypes. Conversely,
other driver events, including mutations in K MT2C
and COL5A2 in adenocarcinomas and in PIK3CA
in squamous-cell carcinomas, while predomi-
nant ly clonal, often occurred after genome du-
plication, which suggests their involvement in
tumor maintenance or progression. Except for
alterations in T P53, ATM, CHEK2, and MDM2,
51% of 72 driver alterations affecting chromatin
remodeling, histone methylation, or DNA dam-
age response and repair were subclonal or late in
both histologic subtypes (23 of 41 events in ad-
enocarcinomas and 14 of 31 events in squamous-
cell carcinomas) (Fig. S25 in Supplementary
Appendix 1). UBR5, with a known role in dif-
ferentiation and DNA damage response, was one
of the most frequently altered genes later in evolu-
tion in both adenocarcinomas and squamous-cell
carcinomas. Other genes that were subject to
frequent subclonal or late alterations in adeno-
carcinomas included NF1 and NOTCH1, along
with 3p, 13q, and 21p loss and 7q and 8q gain,
whereas in squamous-cell carcinomas, alterations
in MLH1 and KRAS, along with 10q loss and 7p,
8q, and 20q gain, were late events.
Driver mutations that occurred early showed
a signif icantly greater tendency to occur in estab-
lished histologic-subtype–specific cancer genes
than did late or subclonal driver mutations,
which affected a broader selection of pan-cancer
genes
20
(Fig. S26 in Supplementary Appendix 1).
These data are consistent with the dN/dS muta-
tion-selection analysis and suggest that constraints
inherent in cancer evolution var y as tumors de-
velop, which potentially renders more evolution-
ary paths permissive for progression.
Overall, 86 of the 100 tumors in our study
had alterations that are being investigated in
NSCLC in genomically profiled drug studies, in-
cluding the National Lung Matrix Trial (NLMT)
21
and the Molecular Analysis for Therapy Choice
(MATCH) trial.
22
Of these 86 tumors, 17 (20%)
had subclonal targetable mutations and copy-
number alterations. In 12 of these 17 tumors
(71%), both a clonal and a subclonal targetable
alteration were present, which indicates how tar-
gets might be prioritized for therapeutic inter-
vention (Fig. S27 in Supplementary Appendix 1).
Discussion
Intratumor heterogeneit y provides the fuel for
tumor evolution and drug resistance.
23
Here, we
have provided an analysis of NSCLC evolution,
which has shown that intratumor heterogeneity
and branched evolution are almost universal
across the cohort. We also observed a common
pattern of early clonal genome doubling, followed
by extensive subclonal diversification.
These data may have important implications
for our understanding of tumor biolog y and
therapeutic control in NSCLC. Certain targetable
driver mutations, including those in EGFR, MET,
and BR AF, were almost exclusively clonal and
early, which explains the robust and uniform
responses that are often seen across multiple
sites of disease when these alterations are tar-
geted.
24 -26
However, more than 75% of the tumors
in our study carried a subclonal driver alteration,
including in genes such as PIK3C A, NF1, KRAS,
TP53, and NOTCH family members. Moreover, a
large fraction of subclonal driver mutations ap-
peared to be clonal in a single region but were
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Genome
doubling
Late
drivers
Mutations Copy-Number Events
Copy-Number Events
Copy-Number Events
Mutations
Mutations
Mutational Processes
Mutational Processes
Mutational Processes
7q
8q
3p
13q
21p
9p
15q
7p
17p
9q
1q
5p
8p
14/18
12/16
12/19
12/20
12/21
11/20
11/20
17/31
6/15
7/20
5/16
4/22
2/16
PPFIBP1 (12p)
EIF3E (8q)
KRAS (12p)
COX6C (8q)
RSPO2 (8q)
NKX2−1 (14q)
HEY1 (8q)
TERT (5p)
EGFR (7p)
FOXA1 (14q)
2/6
2/6
2/7
2/7
1/6
1/6
1/7
1/10
1/10
0/7
CS ES NS
CS ES NS
CS ES NS
CIC
EP300
FLT4
NOTCH1
PTPRC
SMAD4
DNM2
PASK
UBR5
KMT2C
BAP1
PLXNB2
ARID2
CTNNB1
NCOR1
NCOA6
COL2A1
COL5A2
U2AF1
KMT2D
PIK3CA
NF1
MGA
DOT1L
FUBP1
CREBBP
PRF1
RASA1
WRN
NOTCH2
NRAS
RNF43
SMARCA4
ARHGAP35
RAD21
SERPINB13
RB1
ATRX
KDM5C
WAS
FANCM
ARID1B
STK11
ATM
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
3/3
3/4
3/4
3/4
2/3
2/3
2/3
2/3
2/3
2/3
2/3
3/5
4/7
5/9
1/2
1/2
1/2
1/2
1/2
1/2
2/4
1/2
1/2
1/2
2/4
1/2
1/2
2/5
1/3
1/3
1/3
1/3
1/3
2/7
1/4
FAT1
EGFR
TP53
KRAS
KEAP1
BCOR
RBM10
APC
CHEK2
FBXW7
PHOX2B
TSC2
BRAF
CMTR2
MET
PRDM1
1/5
2/13
4/29
3/26
1/9
0/2
0/5
0/4
0/2
0/2
0/2
0/2
0/4
0/3
0/2
0/2
Pre-GD
initiating
drivers
Post-GD
clonal/
subclonal
Genome
doubling
Mutations Copy-Number Events
Mutational Processes
Mutational Processes
Mutational Processes
2p
7p
8q
15q
12p
20q
16q
7q
22q
1p
10q
9/9
10/10
12/13
7/8
6/7
9/11
8/10
5/7
7/10
6/10
8/14
5p
20p
4q
9p
10p
18p
13q
9q
11p
18q
21p
21q
5q
17p
3q
3p
10/20
6/12
5/10
7/14
8/16
5/10
7/15
5/11
3/7
3/7
6/15
4/10
4/17
3/13
2/9
4/18
4p 2/13
CDKN2A (9p)
BCL11A (2p)
FIP1L1 (4q)
IL7R (5p)
AKT2 (19q)
CD79A (19q)
FOXL2 (3q)
CCND1 (11q)
MYC (8q)
FGFR1 (8p)
PIK3CA (3q)
SOX2 (3q)
2/3
2/3
2/3
LSM14A (19q)
TERT (5p)
REL (2p)
IKBKB (8p)
CEBPA (19q)
LIFR (5p)
HOOK3 (8p)
2/5
2/5
1/3
1/4
1/4
1/5
1/5
1/6
1/6
0/3
0/3
0/4
0/4
0/8
0/13
0/14
CS ES
CS ES
CS ES
CYLD
KRAS
MLH1
UBR5
CBLB
PIK3CA
MGA
NCOA6
PLXNB2
ERCC5
CUL3
COL2A1
NOTCH2
COL5A2
FAT1
CDKN2A
BRIP1
DNM2
FANCM
WRN
CUX1
DICER1
NFE2L2
RASA1
NOTCH1
TP53
CREBBP
KEAP1
LATS1
SMAD4
KMT2D
FBXW7
PTEN
WT1
2/2
2/2
2/2
4/4
2/2
5/7
2/3
2/3
2/3
1/2
1/2
1/2
1/2
2/4
4/8
4/8
1/2
1/2
1/2
1/2
1/2
1/2
3/7
2/5
1/5
2/27
0/2
0/2
0/2
0/2
0/3
0/2
0/3
0/2
Late
drivers
Pre-GD
initiating
drivers
Post-GD
clonal/
subclonal
Pre-GD clonal
somatic event
Untimed clonal
somatic event
Post-GD clonal
somatic event
Subclonal
somatic event
Signature
Unclassified
Signature 1A
(mitotic clock)
Signature 2/13
(APOBEC)
Signature 4
(smoking)
Signature 5
(unknown)
AAdenocarcinoma BSquamous-Cell Carcinoma
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Tracking the Evolution of Non–Small-Cell Lung Cancer
absent or subclonal in other regions, which con-
firmed the limitations of sampling single tumor
regions and emphasized the ability of multi-
region whole-exome sequencing to def ine the
clonality of driver events for prioritization of
drug t argets.
Late mutations in tumor-suppressor genes that
occur after genome doubling often affected only
one allele, which potentially left the wild-type
alleles intact. Although this finding could indi-
cate that late tumor-suppressor mutations are
often passenger events that do not contribute to
tumor progression, it is also plausible that germ-
line defects, subclonal copy-number loss, haplo-
insuff iciency, or transcriptional regulation may
act to limit wild-type expression. In contrast to
early mutations, late driver mutations were not
specific to the NSCLC subtype and often occurred
in cancer genes that have been identif ied in
other tumor types; a high proportion occurred
in genes that are involved in the maintenance of
genome integrit y through DNA damage response
and repair, chromatin remodeling, and histone
methylation. Such mutations may remove tissue-
specif ic constraints on the cancer genome and
provide advantages to emerging subclones later
in evolution. However, the observation of paral-
lel evolution of driver copy-number alterations
that were identified through mirrored subclonal
allelic imbalance, including in CDK4, FOXA1, and
BCL11A, suggests that despite extensive diversity,
specific constraints, which could be therapeuti-
cally exploited, may operate later in tumor evo-
lution.
Tumors with the highest subclonal mutational
burden had extensive APOBEC-mediated muta-
genesis, and 19 tumors carried subclonal driver
mutations within an APOBEC context. This find-
ing suggests that targeting the enzymatic activ-
ity of APOBEC may provide a means of limiting
subclone diversif icat ion. The clonal mutation
burden was significantly enriched in patients
with a smoking history. Conceivably, this f ind-
ing could be exploited for therapeutic benef it
through the use of peptide vaccines or adoptive
cell therapy against clonal neoantigens that are
present in every tumor cell. However, the obser-
vation that clonal mutations can be lost owing to
later copy-number events could limit the eff icacy
of such strategies, especially in tumors with high
chromosome instability.
Finally, although a single sample can provide
a static measure of chromosomal complexity,
27
the use of multiregion whole-exome sequencing
enables the assessment of dynamic chromosome
instability, which may lead to differences in chro-
mosomal karyotypes between NSCLC subclones.
The onset of chromosome instability appears to
have a considerable effect on the evolution of
NSCLC; such instability appears to be the pre-
dominant driver of parallel evolution and can
lead to both mutational and copy-number diver-
sity among subclones. Elevated copy-number het-
erogeneity was associated with shorter relapse-
free survival, which suggests that patients who
have early-stage tumors with high levels of copy-
number heterogeneity may represent a high-risk
group who may benefit from close monitoring
and early therapeutic intervention during follow-
up. We are continuing to assess this association
in the next 742 patients enrolled in TRACERx.
Whether noninvasive prognostic approaches, such
as liquid biopsy, can be used to prospectively
assess the levels of chromosomal instability in
the clinical setting warrants further attention.
28
In addition to ongoing efforts to target single
genetic alterations, there is a need to develop a
greater understanding of chromosomal instabil-
ity, which can alter the copy number of a multi-
tude of genes simultaneously. Indeed, therapeu-
tic efforts that can attenuate this process may
limit the ensuing heterogeneit y and tumor evolu-
tion that drive poor rates of relapse-free survival.
In the analysis presented here, we provide a
Figure 4 (facing page). Timing of Somatic Events
in NSCLC Evolution.
A diagram of tumor evolution in adenocarcinoma
(Panel A) and squamous-cell carcinoma (Panel B)
shows the approximate timing of genomic aberrations
with respect to the cancer life history. The timing of
mutations and copy-number events is shown as bars
indicating whether the events are clonal or subclonal.
Clonal mutations and chromosome-arm events are fur-
ther timed as early or late with respect to genome dou-
bling (GD). The frequency of mutations and copy-num-
ber alterations (subclonal and total) is indicated on the
right side of the bars. Pie charts show the fraction of
estimated mutations for each signature, averaged
across current smokers or recent ex-smokers (CS),
long-term (>20 years) former smokers (ES), and life-
long never smokers (NS) at three different time points.
Only genes that were mutated in at least two patients
or that had copy-number alterations in at least 20% of
the patients in the cohort are shown.
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census of driver events in early-stage NSCLC in
relation to clonality and show that chromo-
somal instability is not only a significant driver of
parallel evolution but also a predictor of poor
outcome.
Supported by Cancer Research UK (CRUK), the CRUK Lung
Cancer Centre of Excellence, t he University Col lege London Hos-
pitals Biomedical Rese arch Centre, the CRUK University College
London Experimental Ca ncer Medicine Centre, the Rosetrees
Trust, t he Francis Crick Institute (which receives it s core fund-
ing from CRUK [FC001169 and FC001202]), the U.K. Medical
Research Counci l (FC001169 and FC001202), and the Wellcome
Trust (FC001169 and FC001202). Dr. Swanton is a Royal Society
Napier Chair in Oncolog y and is funded by CRUK (TRACERx
and CRUK Cancer Immunotherapy Catalyst Net work), the Na-
tiona l Inst itute for Healt h Research, Novo Nord isk Foundation
(ID16584), the European Research Council, and PloidyNet (a
Marie Cu rie Initia l Train ing Net work). Dr. Van Loo is a Winton
Group Leader in recog nition of the suppor t of the Wi nton
Charit able Foundation i n the est ablishment of the Francis Crick
Institute.
Disclosure forms provided by the authors are available with
the fu ll text of this article at NEJM.org.
We thank a ll the patients who participated in this study and
represent atives of Illumin a and Agi lent who prov ided sequenc-
ing inf rast ruct ure suppor t.
Appendix
The authors’ full names and academic degrees are as follows: Mariam Jamal-Hanjani, M.D., Ph.D., Gareth A. Wilson, Ph.D., Nicholas
McGranahan, Ph.D., Nicolai J. Birkbak, Ph.D., Thomas B.K. Watkins, M.C.I.T., Selvaraju Veeriah, Ph.D., Seema Shafi, Ph.D., Diana H.
Johnson, B.Sc., Richard Mitter, M.Sc., Rachel Rosenthal, M.Sc., Max Salm, Ph.D., Stuart Horswell, M.Math., Mickael Escudero, M.Sc.,
Nik Matthews, B.Sc., Andrew Rowan, B.Sc., Tim Chambers, M.Sc., David A. Moore, M.D., Samra Turajlic, M.D., Ph.D., Hang Xu, Ph.D.,
Siow-Ming Lee, M.D., Ph.D., Martin D. Forster, M.D., Ph.D., Tanya Ahmad, M.D., Crispin T. Hiley, M.D., Ph.D., Christopher Abbosh,
M.D., Mary Falzon, M.D., Elaine Borg, M.D., Teresa Marafioti, M.D., David Lawrence, M.D., Martin Hayward, M.D., Shyam Kolvekar,
M.D., Nikolaos Panagiotopoulos, M.D., Sam M. Janes, M.D., Ph.D., Ricky Thakrar, M.D., Asia Ahmed, M.D., Fiona Blackhall, M.D.,
Ph.D., Yvonne Summers, M.D., Ph.D., Rajesh Shah, M.D., Leena Joseph, M.D., Anne M. Quinn, M.D., Ph.D., Phil A. Crosbie, M.D.,
Ph.D., Babu Naidu, M.D., Gary Middleton, M.D., Gerald Langman, M.D., Simon Trotter, M.D., Marianne Nicolson, M.D., Hardy Rem-
men, M.D., Keith Kerr, M.D., Mahendran Chetty, M.D., Lesley Gomersall, M.D., Dean A. Fennell, M.D., Ph.D., Apostolos Nakas, M.D.,
Sridhar Rathinam, M.D., Girija Anand, M.D., Sajid Khan, M.D., Peter Russell, M.D., Ph.D., Veni Ezhil, M.D., Babikir Ismail, M.D.,
Melanie Irvin-Sellers, M.D., Vineet Prakash, M.D., Jason F. Lester, M.D., Malgorzata Kornaszewska, M.D., Ph.D., Richard Attanoos,
M.D., Haydn Adams, M.D., Helen Davies, M.D., Stefan Dentro, M.Sc., Philippe Taniere, M.D., Ph.D., Brendan O’Sullivan, B.Sc., Helen L.
Lowe, Ph.D., John A. Hartley, Ph.D., Natasha Iles, Ph.D., Harriet Bell, M.Sc., Yenting Ngai, B.Sc., Jacqui A. Shaw, Ph.D., Javier Herrero,
Ph.D., Zoltan Szallasi, M.D., Roland F. Schwarz, Ph.D., Aengus Stewart, M.Sc., Sergio A. Quezada, Ph.D., John Le Quesne, M.D., Ph.D.,
Peter Van Loo, Ph.D., Caroline Dive, Ph.D., Allan Hackshaw, M.Sc., and Charles Swanton, M.D., Ph.D.
The authors’ affiliations are as follows: the Cancer Research UK Lung Cancer Centre of Excellence (M.J.-H., G.A.W., N. McGranahan,
N.J.B., S.V., S.S., D.H.J., R.R., S.-M.L., M.D.F., C.A., S.M.J., C.D., C.S.), London and Manchester, Good Clinical Laboratory Practice
Facility, University College London (UCL) Experimental Cancer Medicine Centre (H.L.L., J.A.H.), Bill Lyons Informatics Centre (J.H.),
and Cancer Immunology Unit (S.A.Q.), UCL Cancer Institute, the Translational Cancer Therapeutics Laboratory (G.A.W., N. McGranahan,
N.J.B., T.B.K.W., A.R., T.C., S. Turajlic, H.X., C.T.H., C.S.), Department of Bioinformatics and Biostatistics (R.M., M.S., S.H., M.E.,
A.S.), Advanced Sequencing Facility (N. Matthews), and Cancer Genomics Laboratory (S.D., P.V.L.), Francis Crick Institute, the Renal
and Skin Units, Royal Marsden Hospital (S. Turajlic), the Departments of Medical Oncology (M.J.-H., S.-M.L., M.D.F., T.A., C.A., C.S.),
Pathology (M.F., E.B., T.M.), Cardiothoracic Surgery (D.L., M.H., S. Kolvekar, N.P.), Respiratory Medicine (S.M.J., R.T.), and Radiol-
ogy (A.A.), UCL Hospitals, Lungs for Living, UCL Respiratory, UCL (S.M.J.), the Department of Radiotherapy, North Middlesex Univer-
sity Hospital (G.A.), the Department of Respiratory Medicine, Royal Free Hospital (S. Khan), and UCL Cancer Research UK and Cancer
Trials Centre (N.I., H.B., Y.N., A.H.), London, Cancer Studies, University of Leicester (D.A.M., D.A.F., J.A.S., J.L.Q.), the Department
of Thoracic Surgery, Glenfield Hospital (A.N., S.R.), and the Medical Research Center Toxicology Unit (J.L.Q.), Leicester, the Institute
of Cancer Studies, University of Manchester (F.B.), the Christie Hospital (F.B., Y.S.), the Departments of Cardiothoracic Surgery (R.S.)
and Pathology (L.J., A.M.Q.) and the North West Lung Centre (P.A.C.), University Hospital of South Manchester, and Cancer Research
UK Manchester Institute (C.D.), Manchester, the Departments of Thoracic Surgery (B.N.) and Cellular Pathology (G.L., S. Trotter),
Birmingham Heartlands Hospital, Molecular Pathology Diagnostic Services, Queen Elizabeth Hospital (P.T., B.O.), and Institute of Im-
munology and Immunotherapy, University of Birmingham (G.M.), Birmingham, the Departments of Medical Oncology (M.N.), Cardio-
thoracic Surgery (H.R.), Pathology (K.K.), Respiratory Medicine (M.C.), and Radiology (L.G.), Aberdeen University Medical School and
Aberdeen Royal Infirmary, Aberdeen, the Department of Respiratory Medicine, Barnet and Chase Farm Hospitals, Barnet (S. Khan), the
Department of Respiratory Medicine, Princess Alexandra Hospital, Harlow (P.R.), the Department of Clinical Oncology, St. Luke’s
Cancer Centre, Guildford (V.E.), the Departments of Pathology (B.I.), Respiratory Medicine (M.I.-S.), and Radiology (V.P.), Ashford and
St. Peters’ Hospitals, Surrey, the Department of Clinical Oncology, Velindre Hospital (J.F.L.), the Departments of Radiology (H.A.) and
Respiratory Medicine (H.D.), University Hospital Llandough, the Departments of Pathology (R.A.) and Cardiothoracic Surgery (M.K.),
University Hospital of Wales, and Cardiff University (R.A.), Cardiff, and Wellcome Trust Sanger Institute, Hinxton, and Big Data Insti-
tute, University of Oxford, Oxford (S.D.) — all in the United Kingdom; the Center for Biological Sequence Analysis, Department of
Systems Biology, Technical University of Denmark, Lyngby (Z.S.); the Computational Health Informatics Program, Boston Children’s
Hospital and Harvard Medical School, Boston (Z.S.); MTA-SE-NAP, Brain Metastasis Research Group, 2nd Department of Pathology,
Semmelweis University, Budapest, Hungary (Z.S.); Berlin Institute for Medical Systems Biology, Max Delbrueck Center for Molecular
Medicine, Berlin (R.F.S.); and the Department of Human Genetics, University of Leuven, Leuven, Belgium (P.V.L.).
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... Shortly, existence of an abnormal TP53 may indicate an illness with clear symptoms and, thus, a possibly shorter lifespan. 81,82 Adjuvant treatment for Cancer and Leukemia Group B (CALGB) patients with tumors ≥4 cm significantly affected both overall survival (OS) and disease-free survival (DFS) in Phase III studies. OS and DFS were linked to the IHC staining for TP53, BCL-2, blood group antigen A, and mucin and mucin expression was 45% and TP53 was 47%, respectively. ...
... One of such investigation has demonstrated that TP53 mutations may develop at the metaplastic stage. 77,79,81,82 Figure 4 offers a model that demonstrates how TP53 alteration might arise as an initial or final incident in cancer development. In accordance with our premise that assortment pressure is the factor for the development of an alteration, we propose that the site of the variation depends on the biological mechanism of stimulating p53 protein activity. ...
... Though, these genetic modifications will cause oncogenic stress, which stimulates the p53-protein via the p14arf pathway. [75][76][77][78][79][80][81][82] Therefore, the existence of wild-type (WT) p53 is a restricting event for the evolution of such lesions, and only such cells that have missing TP53 activity will be capable to advance to invasive malignancy. The model in Figure 4 only displays two stages of collection for TP53 alterations, but it's evident that this approach may be extended to clarify the incidence of TP53 alterations at nearly every step of cancer progression. ...
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Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Mutations within the TP53 gene represent critical molecular events in NSCLC, contributing to the tumorigenesis in the pulmonary epithelial tissues. TP53 is a widely researched prognostic indicator in NSCLC, and pathological investigations have revealed a weak to mild negative predictive effect for TP53. Mutated p53 protein may have some pro-oncogenic impact, and the variations may change tumor inhibitors into oncogenes. The diverse mutational spectrum of TP53 in NSCLC with different mutations is linked to varied treatment responses. In contrast, first-line chemotherapeutics to this progress are limited, however, randomized trials with new chemotherapeutics have shown significant survival benefits. This review highlighted the critical influence of TP53 gene mutations on pathological-sensitivity and overall survival outcomes in NSCLC. Further research is needed to explore TP53 mutation-specific pathways and their effects on NSCLC progression and treatment effectiveness.
... Analysis of variant allele frequencies (VAF) and phylogenetic reconstruction were performed using established methods, TumE 65 and PyClone 66 . Briefly, mutations were classified as clonal/subclonal based on cancer cell fraction (CCF) 67 and further timed with respect to whole-genome doubling (WGD) following previous publications 33 . This section consists of two parts, VAF analysis and timing of mutations. ...
... Any clonal mutations that could not be timed as either early or late, were classified as "clonal untimed". The sequencing profile from TRACERx and our published study about solitary NSCLC were also include to further investigate the temporal difference in cancer evolution 26,33 . ...
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Next-generation sequencing (NGS) offers a promising approach for differentiating multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), though panel selection and clonal interpretation remain challenging. Whole-exome sequencing (WES) data from 80 lung cancer samples were utilized to simulate MPLC and IPM, with various sequenced panels constructed through gene subsampling. Two clonal interpretation approaches primarily applied in clinical practice, MoleA (based on shared mutation comparison) and MoleB (based on probability calculation), were subsequently evaluated. ROC analysis highlighted MoleB's superior performance, especially with the NCCNplus panel (AUC = 0.950 ± 0.002) and pancancer MoleA (AUC = 0.792 ± 0.004). In two independent cohorts (WES cohort, N = 42 and non-WES cohort, N = 94), NGS-based methodologies effectively stratified disease-free survival, with NCCNplus MoleB further predicting prognosis. Phylogenetic analysis further revealed evolutionary distinctions between MPLC and IPM, establishing an optimized NGS-based framework for differentiating multiple lung cancers.
... One of the key advantages of liquid biopsies (LBs) is their non-invasiveness, which enables longitudinal analyses with high temporal resolution, making dynamic response assessment during cancer treatment a highly attractive aspect of personalized cancer therapy 23,[31][32][33] . Furthermore, LBs can provide unique insights into tumor molecular heterogeneity and its evolution during cancer treatment, thereby minimizing the sampling bias of tissue biopsies 34 . Several interventional clinical trials are currently assessing the potential of serial LBs to guide cancer treatment, with focus on MRD detection and selection of adjuvant treatment based on cfDNA analysis 6, 35 . ...
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Background: KRAS exon 2 mutations are highly prevalent in human malignancies, making them attractive targets for detection and monitoring in cell-free DNA (cfDNA) of cancer patients. Drop-off assays designed for digital polymerase chain reaction (ddPCR drop-off) span entire mutational hotspots and detect any mutated allele within the covered region, overcoming a major limitation of mutation-specific ddPCR assays. We therefore set out to develop a novel KRAS codon 12/13 ddPCR drop-off assay for the robust, highly sensitive and specific detection of KRAS exon 2 hotspot mutations in cfDNA. Methods: We designed, optimized and extensively validated a KRAS codon 12/13 ddPCR drop-off ssay. We compared assay performance to a commercially available KRAS multiplex assay. For clinical validation, we analyzed plasma samples collected from patients with KRAS- mutated gastrointestinal malignancies. Results: Limit of detection of the newly established ddPCR drop-off assay was 0.57 copies/µL, limit of blank was 0.13 copies/µ. The inter-assay precision (r ² ) was 0.9096. Our newly developed KRAS ddPCR drop-off assay accurately identified single nucleotide variants in 35/36 (97.2%) of circulating tumor-positive samples from the patient validation cohort. Assay cross-validation showed that the newly established KRAS codon 12/13 ddPCR drop-off assay outperformed a commercially available KRAS multiplex ddPCR assay in terms of specificity . Moreover, the newly developed assay proved to be suitable for multiplexing with mutation-specific probes. Conclusion: We developed and clinically validated a highly accurate ddPCR drop-off assay for KRAS exon 2 hot-spot detection in cfDNA with broad applicability for clinic and research.
... These clones may be interesting to study further to identify features associated with treatment resistance, allowing to design new combination treatments that are specifically targeting the disrupted pathways. Recently, the TRACERx Consortium revealed that NSCLC intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, 58 raising the need to further study tumor clonal heterogeneity and subclonal selection in NSCLC. 59 Moreover, the monitoring of circulating tumor DNA to detect and profile residual tumor cells after therapy should provide insights into mechanisms of metastatic dissemination in patients with NSCLC. ...
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Background More efficient therapeutic options for non-small cell lung cancer (NSCLC) are needed as the survival at 5 years of metastatic disease is near zero. In this regard, we used a preclinical model of metastatic lung adenocarcinoma (SV2-OVA) to assess the safety and efficacy of novel radio-immunotherapy combining hypofractionated radiotherapy (HRT) with muPD1-IL2v immunocytokine and muFAP-CD40 bispecific antibody. Methods We evaluated the changes in the lung immune microenvironment at multiple timepoints following combination therapies and investigated their underlying antitumor mechanisms. Additionally, we analyzed the tumor clonal heterogeneity upon the combination treatments to explore potential mechanisms associated with the lack of complete response. Results The combination of HRT with muPD1-IL2v had a potent antitumor effect and increased survival in the SV2-OVA lung cancer model. Importantly, this combination therapy was devoid of measurable toxicity. It induced remodeling of the immune contexture through the increase of CD8 ⁺ T and natural killer (NK) cells. The addition of muFAP-CD40 to the combination treatment further increased infiltrating CD8 ⁺ T cells, expressing high levels of effector molecules, both in the periphery and core tumor regions. An accumulation of CD8 ⁺ PD-1 ⁺ TOX ⁺ (exhausted) T cells, already at the ‘early’ timepoint, is consistent with the limited clinical benefits provided by the various combination treatments in this model. The study of the clonal dynamics of tumor cells during disease progression and therapy highlighted a clonal selection upon HRT+muPD1-IL2v therapy. Conclusions We demonstrated that HRT+muPD1-IL2v combination is a potent therapeutic strategy to delay tumor growth and increase survival in a metastatic lung cancer model, but additional studies are required to completely understand the resistance mechanisms associated with the lack of complete response in this model.
... Cancer is an evolutionary process [1] in which genetic and epigenetic alterations accumulate over time, driving molecular divergence and widespread genetic intratumour heterogeneity [2]. As a result, multiple studies have sought to characterize the variation in the rate of evolution (the tempo) and the distribution of evolutionary rates through time (the mode) during primary tumour progression [3][4][5][6][7]. Yet, the primary cause of cancer-related mortality is owing to metastatic evolutions [8]-the spread of cancer to distal sites within the body. ...
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The evolution of metastasis, the spread of cancer to distal sites within the body, represents a lethal stage of cancer progression. Yet, the evolutionary dynamics that shape the emergence of metastatic disease remain unresolved. Here, using single-cell lineage tracing data in combination with phylogenetic statistical methods, we show that the evolutionary trajectory of metastatic disease is littered with bursts of rapid molecular change as new cellular subpopulations appear, a pattern known as punctuational evolution. Next, by measuring punctuational evolution across the metastatic cascade, we show that punctuational effects are concentrated within the formation of secondary tumours at distal metastatic sites, suggesting that qualitatively different modes of evolution may drive primary and metastatic tumour progression. Taken as a whole, our findings provide empirical evidence for distinct patterns of molecular evolution at early and late stages of metastatic disease and our approach provides a framework to study the evolution of metastasis at a more nuanced level than has been previously possible.
... Second, we only set two blood sampling points post-MWA, lacking longitudinal monitoring. Third, since we obtained biopsy samples simultaneously with ablation, the local sampling might not represent the entire tumor due to tumor heterogeneity, which could lead to inconsistencies [22]. Finally, ctDNA is considered to reflect systemic mutation characteristics. ...
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Purpose As microwave ablation continues to be used in patients with inoperable stage I non‐small cell lung cancer (NSCLC), it is particularly important to monitor efficacy. Whether plasma ctDNA detection can predict its efficacy should be illustrated. Methods We recruited 43 patients with inoperative stage I NSCLC, all of whom underwent biopsy‐synchronous microwave ablation (MWA). Peripheral blood samples were collected at baseline (n = 43), within 1 h post‐MWA (n = 28), and at the landmark time point (n = 26) for MRD detection. Clinical outcomes were analyzed using Kaplan–Meier survival analysis. Results Patients with undetectable ctDNA at baseline (p = 0.042) and within 1 h after MWA (p = 0.023) had better clinical outcomes. In particular, patients with undetectable ctDNA at the 1‐h post‐MWA time point did not experience recurrence. Detection of ctDNA at the landmark time point is considered an independent risk factor for prognosis and is strongly correlated with clinical outcomes (p = 0.001), the median time to recurrence indicated by ctDNA was 4.9 months earlier compared to imaging. The clinical outcomes of patients with ctDNA clearance were similar to those with no ctDNA (p = 0.570). Risk stratification indicated that patients with persistent ctDNA had worse clinical outcomes compared to those who never had detectable ctDNA (p = 0.004). Conclusion Our findings suggest that ctDNA monitoring can assist in predicting clinical outcomes in stage I NSCLC treated with microwave ablation. Patients with undetectable ctDNA within 1 h after MWA are determined to be clinically cured. Risk stratification based on ctDNA test results helps to differentiate high‐risk patients.
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Recent studies suggest that lung adenocarcinoma cells are closely associated with the tumorigenesis of large‐cell neuroendocrine carcinoma via cellular transformation. However, morphological evidence, along with genetic abnormalities before, during, and after transformation, is quite limited. We present here a case of combined large‐cell neuroendocrine carcinoma and adenocarcinoma exhibiting acinar and solid patterns. Adenocarcinoma cells with abundant mucin, exhibiting positivity for both napsin‐A and neuroendocrine markers, were partially found in the acinar adenocarcinoma component and extensively observed in the solid adenocarcinoma component. Next‐generation sequencing using extracted genomic DNA from the three components revealed homozygous TP53 (missense) and STK11 (nonsense) mutations in all three components, suggesting monoclonal origin. Furthermore, MYC gene amplification, recently presumed to be a pivotal driver in neuroendocrine transformation, was observed in both the solid adenocarcinoma and large‐cell neuroendocrine carcinoma components. These genetic findings corresponded to pre‐ and post‐transformation morphology, providing compelling evidence that some kinds of adenocarcinomas may serve as a precursor of large‐cell neuroendocrine carcinoma.
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APOBEC3 proteins (A3s) play an important role in host innate immunity against viruses and DNA mutations in cancer. A3s-induced mutations in both viral and human DNA genomes vary significantly from non-lethal mutations in viruses to localized hypermutations, such as kataegis in cancer. How A3s are regulated remains largely unknown. Since A3s exist in complexes and belong to the same family as APOBEC-1 (A1), which requires cofactors to be functional, we investigated the role of A1 cofactors and other A3 potentially associated hnRNPs on A3 mutational activity using hepatitis B virus (HBV) cellular replication as a model. We found that A1-associated cofactors and other hnRNPs were involved in A3 mutational activity regulation, and their regulatory effect was dependent on the strength of A3 association with hnRNPs with an order of A3C > 3G>3B and A1 cofactors > other hnRNPs. A1 cofactors had a strong protein interaction with A3 and significantly increased A3 mutational activity by co-expression. Endogenous gene expression knockdown by siRNA had the opposite decrease effect. Disruption of the protein interactions between A3 and hnRNPs through A3G and A3B mutagenesis decreased A3 mutational activity significantly, even to a level of near total loss, indicating that A1 cofactors and hnRNPs are required for A3 mutational activity. HBV genome-wide mutation analyses showed that A1 cofactors significantly increased A3C accessibility to HBV (−)DNA and A3C-induced mutational efficiency to generate kataegis-like hypermutation. These data demonstrate that A1 cofactors and hnRNPs are closely associated with A3s and may play an important regulatory role under physiological conditions. IMPORTANCE As human host restriction factors, A3s play an important role against viral infections. A3s are also major mutagenic drivers of cancer. However, why A3-induced mutations vary significantly from non-lethal mutations in virus to localized hypermutations in cancer remains unknown. We found that A1 cofactor and other hnRNPs are not only associated with A3 complexes but also play important regulatory roles in A3-induced mutation activities. A1 cofactors like GRY-RBP significantly increased A3 accessibility and mutational efficiency to its single-strand DNA substrate during HBV reverse transcription to generate hypermutations. Disruption of the A3 protein association with hnRNPs by A3 mutagenesis diminished A3 mutational activity. This finding not only reveals a regulatory mechanism for A3-induced mutation but also indicates that A3-associated cellular factors can be a potential target for regulating A3-induced mutation for cancer therapeutics.
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During the course of a lifetime, somatic cells acquire mutations. Different mutational processes may contribute to the mutations accumulated in a cell, with each imprinting a mutational signature on the cell's genome. Some processes generate mutations throughout life at a constant rate in all individuals, and the number of mutations in a cell attributable to these processes will be proportional to the chronological age of the person. Using mutations from 10,250 cancer genomes across 36 cancer types, we investigated clock-like mutational processes that have been operating in normal human cells. Two mutational signatures show clock-like properties. Both exhibit different mutation rates in different tissues. However, their mutation rates are not correlated, indicating that the underlying processes are subject to different biological influences. For one signature, the rate of cell division may influence its mutation rate. This study provides the first survey of clock-like mutational processes operating in human somatic cells.
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Targeting defects in the DNA repair machinery of neoplastic cells, for example, those due to inactivating BRCA1 and/or BRCA2 mutations, has been used for developing new therapies in certain types of breast, ovarian and pancreatic cancers. Recently, a mutational signature was associated with failure of double-strand DNA break repair by homologous recombination based on its high mutational burden in samples harbouring BRCA1 or BRCA2 mutations. In pancreatic cancer, all responders to platinum therapy exhibit this mutational signature including a sample that lacked any defects in BRCA1 or BRCA2. Here, we examine 10,250 cancer genomes across 36 types of cancer and demonstrate that, in addition to breast, ovarian and pancreatic cancers, gastric cancer is another cancer type that exhibits this mutational signature. Our results suggest that 7–12% of gastric cancers have defective double-strand DNA break repair by homologous recombination and may benefit from either platinum therapy or PARP inhibitors.
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Background The management of NSCLC has been transformed by stratified medicine. The National Lung Matrix Trial (NLMT) is a UK-wide study exploring the activity of rationally selected biomarker/targeted therapy combinations. Patients and methods The Cancer Research UK (CRUK) Stratified Medicine Programme 2 is undertaking the large volume national molecular pre-screening which integrates with the NLMT. At study initiation, there are eight drugs being used to target 18 molecular cohorts. The aim is to determine whether there is sufficient signal of activity in any drug–biomarker combination to warrant further investigation. A Bayesian adaptive design that gives a more realistic approach to decision making and flexibility to make conclusions without fixing the sample size was chosen. The screening platform is an adaptable 28-gene Nextera next-generation sequencing platform designed by Illumina, covering the range of molecular abnormalities being targeted. The adaptive design allows new biomarker–drug combination cohorts to be incorporated by substantial amendment. The pre-clinical justification for each biomarker–drug combination has been rigorously assessed creating molecular exclusion rules and a trumping strategy in patients harbouring concomitant actionable genetic abnormalities. Discrete routes of pathway activation or inactivation determined by cancer genome aberrations are treated as separate cohorts. Key translational analyses include the deep genomic analysis of pre- and post-treatment biopsies, the establishment of patient-derived xenograft models and longitudinal ctDNA collection, in order to define predictive biomarkers, mechanisms of resistance and early markers of response and relapse. Conclusion The SMP2 platform will provide large scale genetic screening to inform entry into the NLMT, a trial explicitly aimed at discovering novel actionable cohorts in NSCLC. Clinical Trial ISRCTN 38344105.
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Veliparib (ABT-888) is a potent, orally bioavailable, small-molecule inhibitor of the DNA-repair enzymes poly ADP-ribose polymerase-1 and -2.Veliparib enhances the efficacy of temozolomide (TMZ) and other cytotoxic agents in preclinical tumor models. In this multicenter, double-blind trial, adults with unresectable stage III or IV metastatic melanoma were randomized 1:1:1 to TMZ plus veliparib 20 mg or 40 mg, or placebo twice daily. Efficacy endpoints included progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). Patients (N=346) were randomized between February 2009 and January 2010. Median (95% CI) PFS was 3.7 (3.0-5.5), 3.6 (1.9-4.1), and 2 (1.9-3.7) months in the 20-mg, 40-mg, and placebo arms, respectively. Median (95% CI) OS was 10.8 (9.0-13.1), 13.6 (11.4-15.9), and 12.9 (9.8-14.3) months, respectively; ORR was 10.3%, 8.7%, and 7.0%. Exploratory analyses showed patients with low ERCC1 expression had longer PFS when TMZ was combined with veliparib. Toxicities were as expected for TMZ. The frequencies of thrombocytopenia, neutropenia, and leukopenia were significantly increased in the veliparib groups. Grade 3 or 4 adverse events, mainly hematologic toxicities, were seen in 55%, 63%, and 41% of patients in the 20-mg, 40-mg, and placebo arms, respectively. Median PFS with 20 mg and 40 mg veliparib almost doubled numerically compared with placebo, but the improvements did not reach statistical significance. OS was not increased with veliparib. Toxicities were similar to TMZ monotherapy, but with increased frequency. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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How somatic mutations accumulate in normal cells is central to understanding cancer development but is poorly understood. We performed ultradeep sequencing of 74 cancer genes in small (0.8 to 4.7 square millimeters) biopsies of normal skin. Across 234 biopsies of sun-exposed eyelid epidermis from four individuals, the burden of somatic mutations averaged two to six mutations per megabase per cell, similar to that seen in many cancers, and exhibited characteristic signatures of exposure to ultraviolet light. Remarkably, multiple cancer genes are under strong positive selection even in physiologically normal skin, including most of the key drivers of cutaneous squamous cell carcinomas. Positively selected mutations were found in 18 to 32% of normal skin cells at a density of ~140 driver mutations per square centimeter. We observed variability in the driver landscape among individuals and variability in the sizes of clonal expansions across genes. Thus, aged sun-exposed skin is a patchwork of thousands of evolving clones with over a quarter of cells carrying cancer-causing mutations while maintaining the physiological functions of epidermis. Copyright © 2015, American Association for the Advancement of Science.
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We report the efficacy and safety of crizotinib treatment among Chinese patients with advanced-stage NSCLC. We retrospectively analyzed patients with EML4-ALK positive advanced NSCLC who were treated with crizotinib from May 2012 to Aug 2013. Baseline clinical parameters, treatment protocol, response to therapy and survival were noted. The primary goal was to evaluate the efficacy of crizotinib in patients who were previously treated patients or who had poor ECOG performance status (PS). Forty patients were evaluable for safety and efficacy. Median age was 43 years, 100% had adenocarcinoma and stage IV disease, and 42.5% were female. Six patients received frontline treatment with crizotinib, 17 patients had 1 prior treatment, and 17 patients had more than 2 lines of prior treatment. Patients received a median of 5 cycles of treatment (range 1-15 cycles). After the first cycle, 92.5% (37/40) patients archived partial remission (PR). At the end of the follow-up period, the overall PR rate was 70% (28/40), and progression of disease (PD) occurred in 30% of patients (12/40). The median PFS was 28 weeks (95% CI 15.4 to 40.5 weeks), and median OS was 40 weeks (95% CI 38.6 to 49.3 weeks). The most frequent treatment-related AEs were vomiting (47.5%), vision disorder (27.5%) and increased ALT/AST (42%); most toxicities were Grade 1/2. Observed treatment-related Grade 3/4 AEs included increased ALT/AST (10%) and vomiting (5%). The EML4-ALK fusion rate and number of prior chemotherapy cycles did not appear to significantly affect the efficacy of crizotinib. However, PS 0-2 patients had improved PFS (50 weeks vs. 24 weeks, p = 0.015). Crizotinib was safe, well-tolerated, and effective in Chinese patients with pre-treated ALK-rearranged NSCLC. QOL was improved and PS appears to have an effect on the efficacy of crizotinib, but prior treatment and ALK fusion rate do not.
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Our understanding of cancer is being transformed by exploring clonal diversity, drug resistance, and causation within an evolutionary framework. The therapeutic resilience of advanced cancer is a consequence of its character as a complex, dynamic, and adaptive ecosystem engendering robustness, underpinned by genetic diversity and epigenetic plasticity. The risk of mutation-driven escape by self-renewing cells is intrinsic to multicellularity but is countered by multiple restraints, facilitating increasing complexity and longevity of species. But our own species has disrupted this historical narrative by rapidly escalating intrinsic risk. Evolutionary principles illuminate these challenges and provide new avenues to explore for more effective control. Lifetime risk of cancer now approximates to 50% in Western societies. And, despite many advances, the outcome for patients with disseminated disease remains poor, with drug resistance the norm. An evolutionary perspective may provide a clearer understanding of how cancer clones develop robustness and why, for us as a species, risk is now off the scale. And, perhaps, of what we might best do to achieve more effective control. Cancer Discov; 5(8); 1-15. ©2015 AACR. ©2015 American Association for Cancer Research.