Colorectal liver metastases are more often super wild type. toward treatment based on
metastatic site genotyping?
M. A. Allard1,2,3; R. Saffroy1,2; P. Bouvet de la Maisonneuve1,2; L. Ricca1,2,3,4; N. Bosselut1,2;
J. Hamelin1,2; E. Lecorche1,2, M.A. Bejarano1,2; P. Innominato2,5,7; M. Sebagh6; R. Adam3,7; J.
F. Morère2,5; A. Lemoine1,2,8*<c>00 33 1 45 59 36 93, antoinette.lemoine@pbr.aphp.fr
1
APHP, Biochemistry and Oncogenetic Department, Paul Brousse Hospital
Groupe Hospitalier de Hôpitaux Universitaires Paris-Sud
Villejuif, France
2
Inserm UMRS-1004, Université Paris-11
Villejuif, France
3
APHP, Centre Hépato-biliaire, Paul Brousse Hospital
Groupe Hospitalier de Hôpitaux Universitaires Paris-Sud
Villejuif, France
4
Dipartimento di Scienze Medico-Chirurgiche e Medicina Traslazionale
Sapienza Università di Roma
Sapienza, Italy
5
APHP , Department of Medical Oncology, Paul Brousse Hospital
Groupe Hospitalier de Hôpitaux Universitaires Paris-Sud
Villejuif, France
6
APHP Department of Pathology
Groupe Hospitalier de Hôpitaux Universitaires Paris-Sud
Villejuif, France
7
INSERM UMRS-776
Villejuif, France
1
8
Service de Biochimie
Hôpital Paul Brousse
12 av Paul Vaillant Couturier, 94804, Villejuif cedex, France
Abstract
Recent data showed that metastatic colorectal (mCRC) tumors exhibiting extended RASBRAF mutations were resistant to anti-EGFR monoclonal antibodies, making these drugs
suitable for the so-called “super” wild type (WT) patients only. This study aimed to compare
the extended RAS-BRAF mutation frequency and characteristics according to location of
tumor sampling. All consecutive mCRC specimens (N=1,659) referred to our institution from
January 2008 till June 2014 were included in the analysis. Tumor genotyping (first for KRAS
exon 2, then for BRAF exon 15 and later for KRAS exons 2,3,4 and NRAS exon 2,3,4) was
performed with high resolution melting analysis or allelic discrimination. The factors
predicting for the presence of mutation were explored using multivariate binary logistic
regression. Overall, the prevalence of KRAS exon 2 was 36.8%, and it was lower in liver
metastases (N=138/490; 28.2%) in comparison with primary tumors (N=442/1086; 40.7%),
lung metastases (16/32; 50%) or others metastatic sites (15/51; 29.4%; P<0.0001). Similarly,
in the 1,428 samples analyzed, BRAF mutations were less often found in liver metastases
(N=9/396; 2.3%) as compared to primary tumors (N=79/959; 8.2%), lung metastases (N=2/29;
6.9%) or others metastatic locations (N=2/44; 4.5%; P<0.0002). Overall occurrence of
extended RAS mutation was 51.7%. Of the 503 samples tested, the prevalence of extended
RAS-BRAF mutations twice as low in liver metastases (N=53/151; 34.2%) as compared to
primary tumors (N=191/322; 59.3%, P<0.0001). Univariate analysis identified age ≤ 65 years,
male gender and liver localization as predictors of “super” WT status. At multivariate
analysis, only liver metastases was retained (RR: 2.85 [95% CI: 1.91 – 4.30]). Colorectal liver
metastases are twice as likely to exhibit a “super” WT genotype as compared to other tumor
locations, independently from other factors. This molecular feature has the potential to
influence therapeutic strategy in mCRC patients.
Keywords
2
KRAS, NRAS, BRAF, “Super” wild type, Metastatic colorectal cancer
INTRODUCTION
Anti-Epidermal Growth Factor Receptor (EGFR) therapies have been shown to increase
tumor response rate and survival in metastatic colorectal cancer (mCRC) [1–4]. Several
studies have clearly demonstrated that activating mutations in KRAS (exon 2) and BRAF
(exon 15), both involved in signal transduction downstream of EGFR, confer resistance to
anti-EGFR therapies [2, 5–7]. Recent data [8–10] have shown that tumors carrying mutations
in KRAS exon 2,3,4 and in NRAS exon 2,3 and 4 predict for the lack of activity of anti-EFGR
therapies. This has led to the restriction to the use of anti EGFR therapies only in patients with
“super” wild type (WT) metastatic colorectal cancers.
In most cases in daily practice, tumor RAS mutational status is assessed in samples issued
from primary tumor at the time of diagnostic colonoscopy. The rationale for the use antiEGFR monoclonal antibodies in mCRC patients relies on the good concordance of mutational
status between primary tumor and metastatic sites, shown in several studies [11–13].
However, significant differences in the incidence of KRAS exon 2 mutations among tumor
locations have been reported [14].
The aim of the present study was to compare the prevalence of extended RAS-BRAF
mutation according to tumor location in a prospective cohort of consecutive mCRC samples
and to identify factors associated with “super” WT status.
MATERIALS AND METHODS
Study population
The department of molecular biology at the Paul Brousse Hospital is a platform, labellized by
the French Health Cancer Institute (INCa, Institut National du Cancer) to routinely perform
molecular diagnosis of mutations observed in solid malignancies that can be targeted by
tyrosine kinase inhibitors (TKIs). CRC genotyping is only indicated in metastatic patients.
Thus, mCRC samples are daily genotyped for a list of mutations, in accordance with French
guidelines [15]. Routine tumor genotyping for KRAS exon 2 started in January 2008; later,
3
BRAF exon 15 genotyping was added in June 2008. Finally, genotyping was extended to
KRAS exon 3, 4 and NRAS exon 2, 3 and 4 since September 2013. Thus, at July 2014, our
study population consists of 1659 tumors for KRAS exon 2, 1428 for BRAF exon 15, and 503
for extended RAS-BRAF genotyping.
All results and basic clinical data have been collected since January 2008 in a prospectively
maintained-database. RS, NB and JH are specifically responsible for entering data on a daily
basis. Clinical variables include age, sex, origin of sample organ, percentage of tumor cell,
date of analysis and mutational status.
DNA samples
Hematoxylin-eosin-stained slides from tumors are assessed for the ratio percentage of tumor
cells/sample area (non tumoral tissue, stroma of the tumor) by pathologists of our department.
Three sections of 10 µm thickness were obtained from the paraffin-embedded tissue
containing at least 10% of tumoral cells. DNA extraction was performed using the QIAmp
DNA Mini kit (Qiagen, Courtaboeuf, France) according to the manufacturer instructions.
Somatic gene mutations were detected both by the High Resolution Melting analysis, as
described [16–18]. and allelic discrimination with the LightCycler 480 system (Roche).
Statistical analysis
Chi square test or Fisher exact test were used to compare categorical data, as appropriate. Test
T was used to compare means. All variables associated with “super” WT status (P < 0.15)
were entered into a multiple regression logistic model. Multivariate analysis was performed
according to a backward stepwise procedure. The threshold for statistical significance was set
for P<0.05. Calculations were performed with R 3.0.0.
RESULTS
Study population and overall mutation frequency (Table 1)
Clinical and demographic features of the study population genotyped for KRAS exon 2
(N=1659) are detailed in Table 1, together with those of the more recent subgroup genotyped
for extended RAS-BRAF (N=503). The two groups were similar in terms of age, sex ratio,
locations of tumor sampling and KRAS exon 2 or BRAF exon 15 mutation frequencies.
4
Overall incidence of KRAS exon 2 mutation was 36.8% , and that of BRAF exon 15 mutation
was 6.4% Similar rates were observed in the subgroup with extended RAS-BRAF genotyping:
42.1% for KRAS exons 2,3,4 mutations and 6.2% for BRAF exon 15 mutations. NRAS exon
2,3, 4 mutations were found in 18 (3.6%) samples of the 503 analyzed. Codon 12 was more
frequently involved (76.8%) than codon 13 in KRAS exon 2 mutations.
KRAS exon 2 and BRAF mutations by origin of tumor sample (Table 2)
KRAS exon 2 mutations frequency was higher in samples originating from primary intestinal
lesions (40.7%) or lung localizations (50.0%) in comparison to liver (28.2%) or others
metastatic sites (29.4%; P < 0.0001). Similarly, BRAF exon 15 mutations were observed
more often in primary tumors or lung metastases (8.2% and 6.9%, respectively) as compared
to liver or others metastatic sites (2.3% and 4.5%, respectively; P=0.0002). In KRAS exon 2
mutations, no significant difference according to organ of origin was observed for the codon
involved (P=0.65).
Mutation frequency by origin of tumor sample in the group genotyped for extended RASBRAF (Table 3)
The prevalence of extended RAS-BRAF mutations was 59.3% in primary tumors, 55.6% in
lung lesions, 56.5% in other metastatic sites and 34.2% in liver metastases (P<0.0001). In this
subgroup, as for the whole study population, KRAS and BRAF mutations were both
significantly less frequent in liver metastases (28.9% and 2.8%) as compared with primary
tumors (47.5% and 8.1%; P=0.0002 and P= 0.04, respectively) The incidence of NRAS
mutations was similar according to sampled organ, but they were only found in 18 patients.
Factors associated with super WT status: univariate and multivariate analysis (Table 4)
Clinical variables tested as potential predictors of super WT status included age, gender, type
surgical specimen (biopsy vs surgery) and sample location organ. At univariate analysis,
super WT status was more frequently observed in males, ≤ 65 years and in liver metastases.
Multivariate analysis showed that liver localization (RR: 2.85 [1.91 – 4.30]) and male sex (RR
1.83 [1.26 – 2.67]) were independent predictors of a super WT status.
DISCUSSION
5
In this large monocentric cohort of consecutive samples from metastatic colorectal cancer, we
report that the prevalence of KRAS exon 2 and BRAF exon 15 mutations, as well extended
RAS/RAF mutation genotype, was significantly lower (about 2-fold) in liver metastases than
in primary tumors or other metastatic sites.
The overall frequency of KRAS exon 2 mutations observed in our cohort was in the range of
the frequency usually described, albeit their prevalence is subject to variations [19, 20].
Indeed, in three multicentric phase III trials, the prevalence of KRAS exon 2 mutation ranged
from 30 to 45% [2, 3, 6]. Although there is no clear explanation to account for these
differences, it is likely that variability in demographic features, techniques of mutation
detection used, and the tumor location analyzed may be involved.
Several studies have investigated mutational concordance for RAS between primary tumor
and metastatic sites [11, 12, 21–24]. Discordance rates range from 0% to 25%, depending on
the number of patients, the metastatic sites sampled and stage of the disease. Globally, it
appears that there is a good level of concordance between primary tumor and metastases [13].
A lower frequency of KRAS exon 2 mutations in liver lesions (32.3%) as compared to other
sites (lung: 62.0%; brain: 56.5%) has been reported by Tie et al [14]. Similarly, Vauthey et al
[25] observed a KRAS (codon 12 and 13) mutation frequency of 16.1%, even lower than the
present data. These and our data, clearly show significant differences in KRAS mutations
incidence according to the tumor location.
Mutations in BRAF exon 15 have been associated with microsatellite instability and
mismatch repair deficient status in non-metastatic patients [26] and have been shown to
predict poor survival outcome [4]. The mutational rate for BRAF in primary tumor in our
study population is similar to that observed in others large cohorts, in which the BRAF
mutation rate is about 8% [27]. In the present study, the rate of BRAF mutation in liver
metastases was 2.3%, significantly lower than that in primary tumor. This finding is in line
with previous studies that reported a rate of BRAF mutation ranging from 1% to 3.2% in liver
lesions [14, 25]. These results suggest that BRAF mutated primary tumor may have a lower
propensity to metastasize in the liver.
Alongside these confirmatory observations in a much larger sample size, our main finding is
that liver metastases are more often super WT as compared to others tumor locations and
particularly primary tumor. This difference was true when considering KRAS exon 2 only,
6
and become greater when considering the up to date genotyping recommendations (ie,
extended RAS-BRAF mutations). This result is strengthened by multivariate analysis that
enables to exclude potential confounding factors.
A few hypotheses may be postulated in order to explain these differences according to tumor
location. First, discordance alone is unlikely to account for the observed differences in
mutation frequencies. Studies dealing with the issue of genotype concordance, consider the
genotype of a tumor location at a given time of the history of the disease. Even if this cannot
be demonstrated here, it is likely that genotype may evolve during the evolution of the disease
over the time, because of treatment or intrinsic tumor evolution [28]. Another factor involved
could be the intratumoral heterogeneity. This feature has been previously described in CRC
[29–31]. Baldus et al. [31] compared tumor centers and invasion front of 100 primary CRC
tumors and found a rate of discrepancy of 8% for KRAS exon 2 and 1% for BRAF. Giaretti et
al[30] found a 33% of KRAS heterogeneity defined by the presence of mutated and WT clone
within the same tumor. Liver metastases are known to exhibit spontaneous fibrosis or necrosis
[32] and may be subject to o a higher heterogeneity, as compared to other locations.
The mechanisms underlying metastatic process are only very partially understood [33]. On
one hand, concordance between primary tumor and metastases for oncogene support the
concept that KRAS mutation is an event occurring early in the tumorigenesis and may confer
specific metastatic properties in accordance with the theory proposed by Bernards and
Weinberg [34]. On the other hand, discordance argues in favor of clonal selection process as
already advocated [35] and established in other malignancy [36]
Lung metastases exhibited the highest frequency of KRAS exon 2 and extended RAS-BRAF
mutations compared to liver metastases. Moreover, clinical data have clearly show that RAS
mutated patents have a high propensity to develop lung metastases [14, 25]. Our results are in
line with these observations which suggest the importance of the tumor-host tissue interaction
[37], a concept evocated a century ago as the “seed and soil” theory and highlight the
relevancy of lung surveillance in RAS mutated patients [14, 38].
The lower frequency of RAS mutation in liver metastases in comparison with primary tumors
suggests that liver metastases may arise from a WT clone in patients harboring a mutated
primary tumor. This uncommon situation may be advanced to explain unexpected disease
control with anti EGFR therapies in mutated patients (0 to 11% of patients according to these
recent clinical series) [39–41].
7
Another possible clinical explanation could involve a selection bias: samples from organs
other than primary lesion involved, most of the times, a surgical resection of the metastases.
Since very rarely surgery of metastatic lesions is indicated in case of disease progression, the
higher rate of super WT tumors in the liver could be partially due to the fact that this
molecular subgroup is more likely to respond to chemotherapy including anti-EGFR targeted
drugs. Hence, samples obtained from resected metastases could be the result of less extensive
disease dissemination related to intrinsic less aggressive biological features or higher
sensitivity to preoperative chemotherapy. However, lesions obtained from sites other than the
liver seem to display a similar incidence of RAS-BRAF mutations as compared to primary
tumor, suggesting that liver metastases could have a different molecular pattern.
The lower frequency of extended RAS-BRAF mutations in liver metastases compared to
primary tumor therefore supports the proposal of considering genotyping of liver metastases
in patients with mutated primary tumor. This attitude may identify about 10 to 15 % of the
mCRC patients with a mutated tumor but with WT liver metastases. The superiority of anti
EGFR therapy over the alternative treatment such as anti VEGF therapy in WT patients
remains a matter of debate [42, 43], which precludes any recommendations. However, if anti
EGFR therapy becomes the standard in the future, liver metastases genotyping in primary
tumor-mutated patients may be worth to consider.
Conflict of interest
The authors have no conflicts of interest.
References
1. Cunningham D, Humblet Y, Siena S, et al. (2004) Cetuximab monotherapy and cetuximab
plus irinotecan in irinotecan-refractory metastatic colorectal cancer. The New England
journal of medicine 351:337–45. doi: 10.1056/NEJMoa033025
2. Douillard J-Y, Siena S, Cassidy J, et al. (2010) Randomized, phase III trial of panitumumab
with infusional fluorouracil, leucovorin, and oxaliplatin (FOLFOX4) versus FOLFOX4
alone as first-line treatment in patients with previously untreated metastatic colorectal
cancer: the PRIME study. Journal of clinical oncology : official journal of the American
Society of Clinical Oncology 28:4697–705. doi: 10.1200/JCO.2009.27.4860
3. Van Cutsem E, Peeters M, Siena S, et al. (2007) Open-label phase III trial of panitumumab
plus best supportive care compared with best supportive care alone in patients with
chemotherapy-refractory metastatic colorectal cancer. Journal of clinical oncology :
8
official journal of the American Society of Clinical Oncology 25:1658–64. doi:
10.1200/JCO.2006.08.1620
4. Douillard J-Y, Oliner KS, Siena S, et al. (2013) Panitumumab-FOLFOX4 treatment and
RAS mutations in colorectal cancer. The New England journal of medicine 369:1023–
34. doi: 10.1056/NEJMoa1305275
5. Lièvre A, Bachet J-B, Le Corre D, et al. (2006) KRAS mutation status is predictive of
response to cetuximab therapy in colorectal cancer. Cancer research 66:3992–5. doi:
10.1158/0008-5472.CAN-06-0191
6. Peeters M, Price TJ, Cervantes A, et al. (2010) Randomized phase III study of
panitumumab with fluorouracil, leucovorin, and irinotecan (FOLFIRI) compared with
FOLFIRI alone as second-line treatment in patients with metastatic colorectal cancer.
Journal of clinical oncology : official journal of the American Society of Clinical
Oncology 28:4706–13. doi: 10.1200/JCO.2009.27.6055
7. Mao C, Liao R-Y, Qiu L-X, et al. (2011) BRAF V600E mutation and resistance to antiEGFR monoclonal antibodies in patients with metastatic colorectal cancer: a metaanalysis. Molecular biology reports 38:2219–23. doi: 10.1007/s11033-010-0351-4
8. Douillard J-Y, Oliner KS, Siena S, et al. (2013) Panitumumab-FOLFOX4 treatment and
RAS mutations in colorectal cancer. The New England journal of medicine 369:1023–
34. doi: 10.1056/NEJMoa1305275
9. De Roock W, Claes B, Bernasconi D, et al. (2010) Effects of KRAS, BRAF, NRAS, and
PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapyrefractory metastatic colorectal cancer: a retrospective consortium analysis. The lancet
oncology 11:753–62. doi: 10.1016/S1470-2045(10)70130-3
10. Sorich MJ, Wiese MD, Rowland A, et al. (2014) Annals of Oncology Advance Access
published August 12 , 2014. 1–27.
11. Santini D, Loupakis F, Vincenzi B, et al. (2008) High concordance of KRAS status
between primary colorectal tumors and related metastatic sites: implications for clinical
practice. The oncologist 13:1270–5. doi: 10.1634/theoncologist.2008-0181
12. Knijn N, Mekenkamp LJM, Klomp M, et al. (2011) KRAS mutation analysis: a
comparison between primary tumours and matched liver metastases in 305 colorectal
cancer patients. British journal of cancer 104:1020–6. doi: 10.1038/bjc.2011.26
13. Han C-B, Li F, Ma J-T, Zou H-W (2012) Concordant KRAS mutations in primary and
metastatic colorectal cancer tissue specimens: a meta-analysis and systematic review.
Cancer investigation 30:741–7. doi: 10.3109/07357907.2012.732159
14. Tie J, Lipton L, Desai J, et al. (2011) KRAS mutation is associated with lung metastasis in
patients with curatively resected colorectal cancer. Clinical cancer research : an official
journal of the American Association for Cancer Research 17:1122–30. doi:
10.1158/1078-0432.CCR-10-1720
9
15. Institut National du Cancer (2010) Bonnes pratiques pour la recherche à visée
théranostique demutations somatiques dans les tumeurs solides. wwwe-cancerfr
16. Mancini I, Pinzani P, Pupilli C, et al. (2012) A high-resolution melting protocol for rapid
and accurate differential diagnosis of thyroid nodules. The Journal of molecular
diagnostics : JMD 14:501–9. doi: 10.1016/j.jmoldx.2012.03.003
17. Simi L, Pratesi N, Vignoli M, et al. (2008) High-resolution melting analysis for rapid
detection of KRAS, BRAF, and PIK3CA gene mutations in colorectal cancer. American
journal of clinical pathology 130:247–53. doi: 10.1309/LWDY1AXHXUULNVHQ
18. Willmore-Payne C, Holden JA, Hirschowitz S, Layfield LJ (2006) BRAF and c-kit gene
copy number in mutation-positive malignant melanoma. Human pathology 37:520–7.
doi: 10.1016/j.humpath.2006.01.003
19. Brink M, de Goeij AFPM, Weijenberg MP, et al. (2003) K-ras oncogene mutations in
sporadic colorectal cancer in The Netherlands Cohort Study. Carcinogenesis 24:703–10.
20. Samowitz WS, Curtin K, Schaffer D, et al. (2000) Relationship of Ki- ras Mutations in
Colon Cancers to Tumor Location , Stage , and Survival : A Population-based Study
Relationship of Ki- ras Mutations in Colon Cancers to Tumor Location ,. 1193–1197.
21. Cejas P, López-Gómez M, Aguayo C, et al. (2009) KRAS mutations in primary colorectal
cancer tumors and related metastases: a potential role in prediction of lung metastasis.
PloS one 4:e8199. doi: 10.1371/journal.pone.0008199
22. Park JH, Han S-W, Oh D-Y, et al. (2011) Analysis of KRAS, BRAF, PTEN, IGF1R,
EGFR intron 1 CA status in both primary tumors and paired metastases in determining
benefit from cetuximab therapy in colon cancer. Cancer chemotherapy and
pharmacology 68:1045–55. doi: 10.1007/s00280-011-1586-z
23. Losi L, Benhattar J, Costa J (1992) Stability of K-ras mutations throughout the natural
history of human colorectal cancer. European journal of cancer (Oxford, England : 1990)
28A:1115–20.
24. Weber J-C, Meyer N, Pencreach E, et al. (2007) Allelotyping analyses of synchronous
primary and metastasis CIN colon cancers identified different subtypes. International
journal of cancer Journal international du cancer 120:524–32. doi: 10.1002/ijc.22343
25. Vauthey J-N, Zimmitti G, Kopetz SE, et al. (2013) RAS mutation status predicts survival
and patterns of recurrence in patients undergoing hepatectomy for colorectal liver
metastases. Annals of surgery 258:619–26; discussion 626–7. doi:
10.1097/SLA.0b013e3182a5025a
26. Gavin PG, Colangelo LH, Fumagalli D, et al. (2012) Mutation profiling and microsatellite
instability in stage II and III colon cancer: an assessment of their prognostic and
oxaliplatin predictive value. Clinical cancer research : an official journal of the American
Association for Cancer Research 18:6531–41. doi: 10.1158/1078-0432.CCR-12-0605
10
27. Venderbosch S, Nagtegaal ID, Maughan TS, et al. (2014) Mismatch repair status and
BRAF mutation status in metastatic colorectal cancer patients: a pooled analysis of the
CAIRO, CAIRO2, COIN and FOCUS studies. Clinical Cancer Research. doi:
10.1158/1078-0432.CCR-14-0332
28. Misale S, Yaeger R, Hobor S, et al. (2012) Emergence of KRAS mutations and acquired
resistance to anti-EGFR therapy in colorectal cancer. Nature 486:532–6. doi:
10.1038/nature11156
29. Losi L, Baisse B, Bouzourene H, Benhattar J (2005) Evolution of intratumoral genetic
heterogeneity during colorectal cancer progression. Carcinogenesis 26:916–22. doi:
10.1093/carcin/bgi044
30. Giaretti W, Monaco R, Pujic N, et al. (1996) Intratumor heterogeneity of K-ras2 mutations
in colorectal adenocarcinomas: association with degree of DNA aneuploidy. The
American journal of pathology 149:237–45.
31. Baldus SE, Schaefer K-L, Engers R, et al. (2010) Prevalence and heterogeneity of KRAS,
BRAF, and PIK3CA mutations in primary colorectal adenocarcinomas and their
corresponding metastases. Clinical cancer research : an official journal of the American
Association for Cancer Research 16:790–9. doi: 10.1158/1078-0432.CCR-09-2446
32. Poultsides G a, Bao F, Servais EL, et al. (2012) Pathologic response to preoperative
chemotherapy in colorectal liver metastases: fibrosis, not necrosis, predicts outcome.
Annals of surgical oncology 19:2797–804. doi: 10.1245/s10434-012-2335-1
33. Talmadge JE, Fidler IJ (2010) AACR centennial series: the biology of cancer metastasis:
historical perspective. Cancer research 70:5649–69. doi: 10.1158/0008-5472.CAN-101040
34. Bernards R, Weinberg R a (2002) A progression puzzle. Nature 418:823. doi:
10.1038/418823a
35. Fidler IJ, Kripke ML (1977) Metastasis results from preexisting variant cells within a
malignant tumor. Science (New York, NY) 197:893–5.
36. Wu X, Northcott P a, Dubuc A, et al. (2012) Clonal selection drives genetic divergence of
metastatic medulloblastoma. Nature 482:529–33. doi: 10.1038/nature10825
37. Langley RR, Fidler IJ (2007) Tumor cell-organ microenvironment interactions in the
pathogenesis of cancer metastasis. Endocrine reviews 28:297–321. doi: 10.1210/er.20060027
38. Kim M-J, Lee HS, Kim JH, et al. (2012) Different metastatic pattern according to the
KRAS mutational status and site-specific discordance of KRAS status in patients with
colorectal cancer. BMC cancer 12:347. doi: 10.1186/1471-2407-12-347
39. Lièvre A, Bachet J-B, Boige V, et al. (2008) KRAS mutations as an independent
prognostic factor in patients with advanced colorectal cancer treated with cetuximab.
11
Journal of clinical oncology : official journal of the American Society of Clinical
Oncology 26:374–9. doi: 10.1200/JCO.2007.12.5906
40. Di Fiore F, Blanchard F, Charbonnier F, et al. (2007) Clinical relevance of KRAS
mutation detection in metastatic colorectal cancer treated by Cetuximab plus
chemotherapy. British journal of cancer 96:1166–9. doi: 10.1038/sj.bjc.6603685
41. Khambata-Ford S, Garrett CR, Meropol NJ, et al. (2007) Expression of epiregulin and
amphiregulin and K-ras mutation status predict disease control in metastatic colorectal
cancer patients treated with cetuximab. Journal of clinical oncology : official journal of
the American Society of Clinical Oncology 25:3230–7. doi: 10.1200/JCO.2006.10.5437
42. Heinemann V, von Weikersthal LF, Decker T, et al. (2014) FOLFIRI plus cetuximab
versus FOLFIRI plus bevacizumab as first-line treatment for patients with metastatic
colorectal cancer (FIRE-3): a randomised, open-label, phase 3 trial. The lancet oncology
2045:1–11. doi: 10.1016/S1470-2045(14)70330-4
43. Sclafani F, Cunningham D (2014) Cetuximab or bevacizumab in metastatic colorectal
cancer? The lancet oncology 2045:2–3. doi: 10.1016/S1470-2045(14)70360-2
Table 1. Overview of the study population
Variables
Mean age, yrs (SD,range)
Gender M/F
Site of tumor sampling
Primary tumor
Liver
Lung
Others*/**
Origin of sampling
Surgical specimen
Biopsy
Mutations
KRAS exon 2
KRAS codon 12
KRAS codon 13
BRAF exon 15
extended RAS-RAF
mutated status
KRAS exon 3
KRAS exon 4
KRAS exon 2
only
N = 1,156
No. (%)
65.9 (13)
637 (55.1)/519
(44.9)
Extended RAS
N = 503
No. (%)
65.3 (14)
289 (57.5)/214
(42.5)
Total
P
0.41
0.99
N = 1,659
No. (%)
65.7 (13)
926 (55.8)/733
(44.2)
764 (66.1)
341 (29.5)
23 (2.0)
28 (2.4)
322 (64)
149 (29.6)
9 (1.8)
23* (4.6)
0.13
1086 (65.5)
490 (29.5)
32 (1.9)
51** (3.1)
860 (76.6)
263 (23.4)
408 (81.1)
95 (18.9)
0.05
1268 (76.4)
358 (21.6)
425 (36.7)
320 (27.7)
105 (9.0)
60 (6.4)
186 (37)
149 (29.6)
37 (7.6)
32 (6.2)
0.97
0.45
0.29
0.99
611 (36.8)
469 (28.3)
142 (8.6)
92/1428 (6.4)
12
260 (51.7)
_
6 (1.2)
20 (4)
_
_
NRAS
18 (3.6)
_
NRAS exon 2
6 (1.2)
_
NRAS exon 3
12 (2.4)
_
NRAS exon 4
0 (0)
_
* Peritoneum (N =15); Lymph node (N=6); Brain (N=1); Adrenal gland (N = 1)
**Others: Peritoneal metastases (N=24 ); Lymph node (N=14); skin metastases (N=2);
pancreatic metastasis (N=1); brain metastasis (N= 1); adrenal gland metastasis (N=1 ); bone
metastases (N=2 ); ovarian metastases (N=6)
Table 2. KRAS exon 2 and BRAF mutations by origin of tumor sampling
Origin of tumor sampling
P
Primary
Liver
Lung
Others*
No. (%)
No. (%)
No. (%)
No. (%)
KRAS exon 2 (N=1,659)
WT
644 (59.3)
352 (71.8)
16 (50)
36 (70.6)
<0.0001
Mutant
442 (40.7)
138 (28.2)
16 (50)
15 (29.4)
Codon 12
335 (30.8)
111 (22.7)
12 (37.5)
11 (21.6)
0.003
Codon 13
107 (9.9)
27 (5.5)
4 (12.5)
4 (7.8)
0.01
BRAF (N = 1,428)
WT
880 (91.8)
387 (97.7)
27 (93.1)
42 (95.5)
0.0002
Mutant
79 (8.2)
9 (2.3)
2 (6.9)
2 (4.5)
*Others: Peritoneal metastases (N=24 ); Lymph node (N=14); ovarian metastases (N=6); skin
metastases (N=2); pancreatic metastasis (N=1); brain metastasis (N= 1); adrenal gland
metastasis (N=1 ); bone metastases (N=2 )
Table 3. Mutations by origin of sampling in the cohort genotyped for extended RAS-BRAF
Origin of tumor sampling
Primary
Liver
Lung
No.
No. (%)
No. (%)
(%)
Extended RAS-BRAF
Super WT
Mutant
KRAS
WT
Mutant
KRAS exon 2
Codon 12
Others*
P
No. (%)
131 (40.7)
191 (59.3)
98 (65.8)
53 (34.2)
4 (44.4) 10 (43.5) <0.0001
5 (55.6) 13 (56.5)
169 (52.5)
153 (47.5)
138 (42.9)
112 (34.8)
106 (71.1)
43 (28.9)
35 (23.5)
29 (19.5)
5 (55.6)
4 (44.4)
4 (44.4)
2 (22.2)
13
11 (47.8) 0.0009
12 (52.2)
9 (39.1) 0.0004
6 (26.1) 0.005
Codon 13
KRAS exon 3
KRAS exon 4
BRAF
WT
Mutant
NRAS
WT
Mutant
NRAS exon 2
NRAS exon 3
NRAS exon 4
26 (8.1)
4 (1.2)
11 (3.4)
6 (4.0)
3 (2.0)
5 (3.4)
2 (22.2) 3 (13.0)
0 (0)
0 (0)
0 (0)
3 (13)
296 (91.9)
26 (8.1)
145 (97.2) 9 (100) 22 (95.7) 0.12
4 (2.8)
0 (0)
1 (4.3)
309 (96)
13 (4.0)
4 (1.2)
9 (2.8)
0 (0)
145 (97.3)
4 (2.7)
2 (1.3)
2 (1.3)
0 (0)
8 (88.9)
1 (11.1)
0 (0)
0 (0)
0 (0)
23 (100)
0 (0)
0 (0)
0 (0)
0 (0)
0.05
0.80
0.15
0.36
0.99
0.26
>0.99
Table 4. Factors associated with “super” WT status: univariate and multivariate analysis
Variables
≤ 65 yrs
Age
> 65 yrs
Female
Gender
Male
Surgical
spe.
Biopsy
Sampling
Liver location
No
Yes
Univariate analysis
Super
Mutant
WT
82 (33.7) 72 (27.7)
161
188
(66.3)
(72.3)
127
87 (35.8)
(48.8)
156
133
(64.2)
(51.2)
200
208 (80)
(82.3)
43 (17.7) 52 (20)
145
209
(59.7)
(80.4)
98 (40.3) 51 (19.6)
Multivariate analysis
P
RR 95%CI
P
0.14
0.71 0.48 - 1.06 0.09
0.003
1.83 1.26 - 2.67 0.001
0.51
<0.0001 2.85 1.91 - 4.31 <0.0001
Supplementary table: Factors associated with BRAF mutation: univariate and multivariate
analysis
Age
≤ 65 yrs
> 65 yrs
Female
Gender
Male
Univariate analysis for
BRAF mutation
WT
Mutant P
642 (48) 31 (33) 0.009
653 (52) 61 (67)
65
575 (43)
<0.0001
(70.7)
27
761 (57)
(29.3)
14
Multivariate analysis
RR 95%CI
1.84 1.15 - 3.00
P
0.01
0.29 0.17 - 0.46
<0.0001
Surgical spe.
Sampling
Biopsy
Tumor
location
Primary tumor & Other
loc.
Liver
987
(75.2)
326
(24.8)
69
(76.7)
21
(23.3)
949 (71)
83 (90)
387 (29)
9 (10)
15
0.75
<0.0001 0.32 0;15 - 0.62
0.001