The transition from primary colorectal cancer to isolated peritoneal malignancy is associated with an increased tumour mutational burden

Abstract

Colorectal Peritoneal metastases (CPM) develop in 15% of colorectal cancers. Cytoreductive surgery and heated intraperitoneal chemotherapy (CRS & HIPEC) is the current standard of care in selected patients with limited resectable CPM. Despite selection using known prognostic factors survival is varied and morbidity and mortality are relatively high. There is a need to improve patient selection and a paucity of research concerning the biology of isolated CPM. We aimed to determine the biology associated with transition from primary CRC to CPM and of patients with CPM not responding to treatment with CRS & HIPEC, to identify those suitable for treatment with CRS & HIPEC and to identify targets for existing repurposed or novel treatment strategies. A cohort of patients with CPM treated with CRS & HIPEC was recruited and divided according to prognosis. Molecular profiling of the transcriptome (n = 25), epigenome (n = 24) and genome (n = 21) of CPM and matched primary CRC was performed. CPM were characterised by frequent Wnt/ β catenin negative regulator mutations, TET2 mutations, mismatch repair mutations and high tumour mutational burden. Here we show the molecular features associated with CPM development and associated with not responding to CRS & HIPEC. Potential applications include improving patient selection for treatment with CRS & HIPEC and in future research into novel and personalised treatments targeting the molecular features identified here.

Full text

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
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The transition from primary
colorectal cancer to isolated
peritoneal malignancy is associated
with an increased tumour
mutational burden
Sally Hallam, Joanne Stockton, Claire Bryer, Celina Whalley, Valerie Pestinger,
Haney Youssef & Andrew D. Beggs*
Colorectal Peritoneal metastases (CPM) develop in 15% of colorectal cancers. Cytoreductive surgery
and heated intraperitoneal chemotherapy (CRS & HIPEC) is the current standard of care in selected
patients with limited resectable CPM. Despite selection using known prognostic factors survival is
varied and morbidity and mortality are relatively high. There is a need to improve patient selection
and a paucity of research concerning the biology of isolated CPM. We aimed to determine the biology
associated with transition from primary CRC to CPM and of patients with CPM not responding to
treatment with CRS & HIPEC, to identify those suitable for treatment with CRS & HIPEC and to
identify targets for existing repurposed or novel treatment strategies. A cohort of patients with CPM
treated with CRS & HIPEC was recruited and divided according to prognosis. Molecular proling of
the transcriptome (n = 25), epigenome (n = 24) and genome (n = 21) of CPM and matched primary CRC
was performed. CPM were characterised by frequent Wnt/ β catenin negative regulator mutations,
TET2 mutations, mismatch repair mutations and high tumour mutational burden. Here we show the
molecular features associated with CPM development and associated with not responding to CRS &
HIPEC. Potential applications include improving patient selection for treatment with CRS & HIPEC and
in future research into novel and personalised treatments targeting the molecular features identied
here.
Abbreviations
CRC Colorectal cancer
CPM Colorectal peritoneal metastasis
CRS & HIPEC Cytoreductive surgery and heated intraperitoneal chemotherapy
DFS Disease free survival
DMR Dierentially methylated regions
OS Overall survival
FFPE Formalin xed paran embedded
Background
Little is known about the biology of isolated colorectal peritoneal metastasis (CPM), which although a relatively
rare phenomenon is one with a high mortality rate1. Understanding tumour biology may identify which patients
with primary colorectal cancer (CRC) are at risk of developing CPM, and which are suitable for treatment with
cytoreductive surgery and heated intra-peritoneal chemotherapy (CRS & HIPEC). CRS & HIPEC (usually using
an agent such as mitomycin C or more recently, oxaliplatin) aims to achieve macroscopic tumour resection with
multiple visceral and peritoneal resections and ablation of microscopic disease. Five-year survival however varies
OPEN

*email: a.beggs@bham.ac.uk
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widely, and morbidity and mortality are relatively high2. ere is a need therefore to improve patient selection,
allowing alternative existing or novel treatment strategies to be used for patients unlikely to respond.
Primary CRC research has identied markers of response to specic treatments, for example KRAS mutation
in selection for anti-EGFR mAb therapy3. Gene expression signatures have been developed and are in clinical
use for prognostication and therapeutic stratication in breast cancer4–7. Gene expression proling in primary
CRC has identied signatures associated with the development of metastasis6. One small study combining a small
number of CPM with a larger cohort of appendix adenocarcinoma identied a signature predictive of reduced
overall survival (OS) following CRS & HIPEC; these are however two biologically distinct tumours, appendix
having signicantly improved prognosis7.
e dysregulation of methylation is a key step in tumorigenesis CpG island promoter methylation (CIMP)
appears to be stable between matched primary CRC and hepatic metastasis suggesting an epigenetic methylation
programme is established prior to the development of metastasis8–10. Hypermethylation of KRAS, Wnt modula-
tors, tumour suppressor genes, CIMP and hypomethylation of oncogenes are associated with an unfavourable
response to chemotherapy and anti-EGFR antibodies as well as tumour recurrence and reduced OS in primary
and metastatic CRC
11–16. Chromosomal instability is ubiquitous in cancer, increased copy number alteration,
indicative of chromosomal instability is found in metastatic CRC
17,18. Lopez-Garcia etal.19 demonstrated that
the evolution of chromosomal instability is depending on cellular tolerance, either via dysregulation of TP53 or
via alternate escape mechanisms such as dysfunction of BCL9L regulated caspase signalling.
CRC metastatic drivers are less clearly dened, apart from TP53 which is well characterised as being present
in metastatic cancer20. Some studies have found mutations exclusive to metastatic sites21,22, whereas others found
similar patterns of mutation between primary and metastasis23. Studies have examined the somatic mutations
in CPM and their prognostic implications. ese studies are limited to individual or small panels of mutations
routinely tested for in clinical practice with limited evidence to suggest which genes should be included in panel
sequencing in CPM. Schneider etal. examined the KRAS and BRAF mutation status of patients with CPM who
underwent CRS & HIPEC24. ey found mutations of RAS/RAF were associated with reduced OS independent
of the use of targeted anti-EGFR treatment24. Sasaki etal. examined the KRAS, BRAF and PIK3CA mutation
status of patients with metastatic CRC, with or without CPM25. ey found the incidence of BRAF mutation was
signicantly associated with the presence of CPM but not with prognosis25.
e landscape of metastatic colorectal cancer was studied by the MSK-IMPACT
20 group which undertook
panel based sequencing of 1134 metastatic colorectal cancers. Of these 39 patients were dened as “peritoneal”
malignancy, it is unclear whether these were isolated peritoneal metastasis. Only 14 of these patients had meta-
sectomy. 7 of these had peritonectomy suggesting isolated disease suitable for resection. ese tumours were
also not studied with matched primary tumour of origin.
ere is a need to improve the outcomes for patients with CPM and signicant variation in survival despite
patient selection for treatment using known prognostic factors. ere is a paucity of knowledge concerning CPM
tumour biology. Understanding tumour biology will identify patients with primary CRC at risk of developing
CPM, those suitable for treatment with CRS & HIPEC or alternative existing and novel treatment strategies. is
study aims to determine the landscape of gene expression, methylation, and somatic mutation prole associ-
ated with the transition from primary CRC to isolated CPM and determine the association between these and
prognosis following CRS & HIPEC in order to identify therapeutic targets.
Methods
Patient cohorts. is study obtained ethical approval from the North West Haydock Research Ethics Com-
mittee, (15/NW/0079), project ID (17/283). Participants gave informed consent. All experiments were per-
formed in accordance with relevant guidelines and regulations Consecutive retrospective patients were recruited
from an internally held database of all patients undergoing CRS & HIPEC at Good Hope hospital from 2011
to 2017. Patients with CPM (adenocarcinoma), no extra-abdominal metastasis, a complete resection (CC0)
and a peritoneal carcinomatosis index (PCI) of < 12 were eligible for inclusion. e completeness of cytoreduc-
tion score describes the degree of macroscopic tumour remaining aer CRS and the likelihood of benet from
intraperitoneal chemotherapy26. Patients with no residual tumour score CC0, residual tumour < 0.25cm, CC1,
residual tumour 0.25–2.5cm CC2. e extent of peritoneal metastasis is described by the PCI score. A PCI
of ≥ 12 is poor prognostic factor for patients undergoing CRS & HIPEC27. Patients were divided into two groups.
CRS & HIPEC is a long operation associated with a protracted inpatient and high dependency (HDU) or inten-
sive care (ITU) stay an associated mortality of 1–12% and morbidity of 7–63% and a prolonged post-operative
recovery28–37.With palliative chemotherapy DFS is 11–13months and therefore patients post-treatment (CRS &
HIPEC) with disease free survival (DFS) < 12months were dened as “non-responders”38. Patients undergoing
therapy with DFS > 12months were dened as “responders”. Patients were imaged with CT which was reported
by an experienced CPM radiologist, diagnostic laparoscopy was not used, not all patients with recurrence are
suitable for iterative CRS & HIPEC and so this is not a standard procedure in their follow up. Adhesions follow-
ing primary excision and CRS & HIPEC may also preclude accurate assessment of peritoneal recurrence in all
areas with laparoscopy. Disease recurrence was determined when conrmed by CT and MDT review.
Demographic, tumour and treatment details were compared between the prognostic cohorts. For continuous
variables, the students T-test was applied to normally distributed data and Mann Whitney-U to non-normally
distributed data. Categorical variables were compared with the Chi-squared test or Fishers exact test. A p value
of < 0.05 was considered statistically signicant. DFS survival between the responders and non-responders was
compared using the Kaplan Meier method. Statistical analysis was performed in IBM SPSS Statistics for Win-
dows, Version 24.039.
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Nucleic acid extraction. DNA and RNA were extracted from histologically conrmed Formalin xed,
paran embedded (FFPE) scrolls using the Covaris E220 evolution focused-ultrasonicator and the truTRAC
FFPE total NA Kit. All peritoneal metastases samples were taken at the commencement of surgery. Nucleic acid
concentration was quantied using the Qubit 3.0 Fluorometer and Qubit RNA / DNA HS (high sensitivity)
assay kit. Nucleic acid quality was measured by electrophoresis using the Agilent 2200 TapeStation Nucleic Acid
System, Agilent 2200 TapeStation Soware A.01.05 and the Aligent High Sensitivity RNA / DNA ScreenTape
and reagents.
RNA library preparation, sequencing and bioinformatics. RNA library preparation was performed
using the Lexogen Quant Seq 3′ mRNA-Seq Library Prep kit. RNA libraries were denatured, diluted, loaded onto
a 75-cycle High output ow cell and sequenced using the NextSeq500 at 2.5–5 million reads40.
Quality control, trimming and alignment to the reference genome, (NCBI build 37, hg19) was performed
with the Partek Flow genomics suite soware package (Partek, St Louis, MI, USA). e gene expression proles
of primary and CPM and responders and non-responders were compared using gene Specic Analysis (GSA)
Modelling using Partek ow with a false discovery rate (FDR) of < 0.1. Gene specic enrichment analysis (GSEA)
and gene expression pathway analysis was performed using Partek ow, a p value of ≤ 0.05 was considered sta-
tistically signicant.
CMS and CRIS classifications were performed using ‘CMScaller’ (v0.99.1) in the R package, version
2.10.238,41,42. Fishers exact test was used to compare contingency between primary and CPM and responders and
non-responders in IBM SPSS Statistics for Windows, Version 24.039. A p value of < 0.05 was considered signicant.
Methylation array and bioinformatics. DNA was treated with sodium bisulphite using the Zymo EZ-
DNA methylation kit, according to manufacturer’s instructions. Degraded FFPE DNA was restored prior to
methylation array with the Innium HD FFPE restore kit, according to manufacturer’s instructions. Methylation
array was performed according to the Innium MethylationEPIC BeadChip Kit manufacturer’s instructions.
BeadChips were imaged using the Illumina iScan system. Initial data quality was checked using GenomeStudio
Methylation Module Soware.
Raw data was loaded into the RStudio version 3.5.0 soware using the mini package. Bioinformatics analysis
was performed using the Chip Analysis Methylation Pipeline (ChAMP) R package, version 2.10.243,44. Probes
with signals from less than three functional beads, low condence with a detection p value > 0.01, covering
SNPs, non-CpG and those located on the X and Y chromosome where ltered. Beta-mixture quantile normali-
zation (BMIQ) was applied and a singular value decomposition (SVD) performed to identify batch eects. e
association between methylation and prognosis was determined using the Bioconductor R package limma and
bumphunter functions. Copy number alteration calling was performed using the CHAMP CNA function with
a signicance threshold of, p value < p < × 10–10.
Exome capture, high‑throughput sequencing and bioinformatics. DNA was sheared using the
Covaris E220 evolution focused-ultrasonicator to produce a uniform 150bp fragment size. Libraries were pre-
pared using the TruSeq Exome Kit then denatured, diluted, loaded onto a 150-cycle High output ow cell and
sequenced using the NextSeq500.
Sequencing reads were assessed using FastQC. Sequences with a Phred score of < 30 were removed giving
a base call accuracy of 99.9%. Sequence reads were aligned to the human reference genome, (hg19) using the
Burrows–Wheeler Aligner (BWA) package45. SAMTools was used to generate chromosomal coordinate-sorted
BAM les and Picard was used to remove PCR duplicates46. Somatic variants were called from matched tumour-
normal samples using Strelka2 in tumour/normal mode47. Somatic variants were viewed, ltered and annotated
in genomics workbench48. Mutations with a MAF of > 1% in known variant databases, (dbSNP and 100,000
genomes) were ltered. Mutations were annotated with information from known variant databases, (dbSNP and
100,000 genomes), PhastCons score and functional consequences. e prognostic groups were compared using
Fischer exact test to identify potential candidate driver mutations for non-responders. Somatic mutations were
entered into the IntOGen platform for further analysis49. e IntOGen-mutation platform incorporates a number
of pipelines to identify cancer driver mutations and activated pathways49. e OncodriveFM pipeline identies
mutations with a high functional impact using three scoring methods (Sorting Intolerant From Tolerant, (SIFT)50,
PolyPhen251, and Mutation Assessor scores)49,52, and assesses the likelihood that such mutations are cancer driv-
ers. e OncodriveCLUST pipeline assesses the clustering of mutations to identify relevant activated pathways49.
MSI assessment was carried out using MSI_classier_v3 (https ://rpubs .com/sigve n/msi_class ica tion_v3).
Ethics approval and consent to participate. North West Haydock Research Ethics Committee, (15/
NW/0079), project ID (17/283).
Results
Patient cohort. From 2011 to 2017 a total of n = 161 patients underwent CRS & HIPEC at University Hos-
pitals Birmingham, n = 88 patients for metachronous CPM.
Patients were excluded for the following reasons: other primary tumour (appendix, pseudomyxoma peritonei,
ovarian) n = 49, synchronous colorectal cancer n = 26, no primary tumour available n = 53 CC2 resection n = 826,
PCI of ≥ 12 n = 20, follow up period of ≤ 12months n = 27, leaving n = 28 patients. Complete information regard-
ing the primary CRC pathology and treatment was available for n = 26 patients who form the basis of this study.
Each patient had matched normal, primary CRC and CPM samples.
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irteen patients had a DFS of 24months (15–72 range) following CRS & HIPEC and formed the ‘responders
cohort, thirteen patients had a DFS of 6months (2–11 range) and formed the ‘non-responders’. ere were no
signicant dierences between cohorts in demographics, primary CRC or CPM tumour, treatment or follow up
(Table1). No patients had neoadjuvant therapy for their primary tumour. ree patients (all in the responders
group) had poorly dierentiated, mucinous adenocarcinoma, one had signet ring adenocarcinoma (in the non-
responders group) and all the others had moderately dierentiated adenocarcinoma.
Following nucleic acid extraction all patients had adequate CPM RNA for RNAseq (n = 13 responders,
n = 13 non-responders), n = 25 had matched primary CRC samples. For methylation array n = 24 patients
(n = 12 responders, n = 12 non-responders) had adequate DNA. As the Innium methylation array comprises
a 32-prep kit, n = 4 responders and n = 4 non-responders primary tumours were matched to these. For exome
sequencing n = 24 patients (n = 12 responders, n = 12 non-responders) had adequate DNA from both the primary
and CPM samples, extraction of DNA from normal tissue resulted in n = 21 samples (n = 9 responders, n = 12
non-responders).
Exome sequencing. Across all six sequencing runs, we obtained a median of 60X coverage (42–166) with
a median uniformity of 88% (71–89).
Somatic mutations identied in the primary and matched CPM cohort. In the matched CPM
cohort, a total of n = 244,531 somatic SNV’s were identied (CPM-primary subtraction) signicantly more than
found in the matched primary cohort (n = 112,420).
Nine CPM samples, 9/24 (56%) had a high tumour mutational burden TMB ≥ 10 mut/Mb53 compared with
7/24 (30%) samples in the matched primary cohort. Mutations were identied in n = 69 of n = 95 known CRC
driver genes, n = 51 were shared between the primary and CPM, n = 13 were novel (supplementary tableS1)54.
Of the somatic variants identied in CPM, n = 58,958 (29%) were present in the primary CRC, n = 205,552 vari-
ants occurred exclusively in the CPM suggesting a signicant accumulation of mutations in the transition to
CPM (Fig.1). OncodriveFM identied n = 265 potential driver genes with high levels of functional mutation
(Q-value < 0.05) in the CPM cohort: FLNB, SPTB, PPL, TP53, PDE4DIP, RIOK2, CDC16, NUP98, CDC16 and
SVEP1 (supplementary tableS2), however these results must be treated with caution due to the bias of the hyper-
mutator phenotype. KEGG pathway analysis of mutations demonstrated enrichment in pathways concerning
the immune system, signalling, metabolism and cancer (supplementary tableS1). In the CPM group KRAS or
BRAF status was not signicantly associated with prognosis (chi2 p = 1.00).
Clonality analysis with SuperFreq showed signicant (Wilcoxon rank p = 0.007) dierences between the
responders and non-responders groups, with a median of 2 clones in the responders group of primary tumours
(range 1–4) and 3 clones in the non-responders group (range 2–7). In the peritoneal metastases there were a
Table 1. Comparison of responders and non-responders to CRS & HIPEC. N number value in parenthesis,
percentage, DFI disease free interval, time from primary CRC to metachronous CPM, PCI peritoneal
carcinomatosis index, CC score completeness of cytoreduction, DFS disease free survival, OS overall survival.
Log rank p < 0.0001.
Responders Non-responders p Val ue
Age, mean + /−SD 58 ± 13 58 ± 9 0.97
Gender, male n = 7 (54) n = 7 (54) 0.68
Tumour location
Right n = 9 (69) n = 6 (46)
Transverse n = 1 (8) n = 0 (0)
Le n = 3 (23) n = 7 (54) 0.33
T stage primary
3n = 3 (23) n = 3 (23)
4a n = 5 (38.5) n = 7 (54
4b n = 5 (38.5) n = 3 (23) 0.66
N stage primary
0n = 4 (31) n = 1 (8)
1n = 7 (54) n = 5 (38)
2n = 2 (15) n = 7 (54) 0.86
DFI months 25 ± 9 24 ± 12 0.83
PCI score, median (range) 5 (3–12) 8 (2–12) 0.019
CC score
CC0 n = 13 (100) n = 13 (100) 1
CC1 n = 0 (0) n = 0 (0)
CC2 n = 0 (0) n = 0 (0)
Follow up, months, median (range) 29 (19–72) 16 (5–55) 0.11
Adjuvant tre atment Yes n = 11 (85) n = 12 (92) 0.38
No n = 2 (15) n = 1 (8)
DFS, median (range) 24 (15–72) 6 (2–11) < 0.0001
OS, median (range) 29 (19–72) 16 (5–55) 0.12
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median of 3 clones in both the responders (range 1–4) and non-responders (range 2–5) groups. Of note, in the
non-responders group during clonal expansion, the dominant clone in the peritoneal metastasis group arose
de-novo rather than being a prior clone that existed in the primary tumour (Supplementary Fig.1, S1e primary
tumours, 9/21 were MSI (47.4%) and 10/21 were MSS (52.6%) whereas in the isolated peritoneal metastasis
group, 4/21 (19.0%) were MSS and 17/21 MSI (81.0%) Demonstrating that there was a signicantly higher rate
of MSI in the isolated peritoneal metastasis group (p < 0.05, Chi2).
Non-responders had a higher frequency of somatic mutations: 60% of all mutations in CPM cohort vs. 40%.
Non-responders more commonly had a high tumour mutational burden, TMB ≥ 10 mut/Mb53, 56% vs. 44%. Of
the somatic mutations identied in non-responders, n = 35,461 (30%) were present in responders, n = 145,089
variants occurred exclusively in non-responders, suggesting a high tumour mutational burden was associated
with non-response to CRS & HIPEC (Fig.1). Mutational signature analysis of the MSI tumours demonstrated a
predominance of signature 5 (associated with mutational “clock” eects), signature 26 (associated with defective
mismatch repair) and signature 20 (associated with defective mismatch repair).
Comparison of somatic mutations in responders and non-responders identied two potential candidate genes
to identify non-responders, FAM13A and PIEZO2 (Fishers exact p < 0.05, FDR = 0.53) (Table2).
Dierentialene expression. Dierential gene expression between primary CRC and matched CPM. Pri-
mary CRC and matched CPM showed dierential expression of n = 65 genes with an FDR < 0.1. (Fig.2) Sixteen
genes showed signicantly decreased expression in CPM compared with primary CRC (Table3). Forty-nine
genes showed signicantly increased expression in CPM compared with primary CRC (Table3). A KEGG path-
way analysis was performed to identify the enriched biological functions among the dierentially expressed
genes (Supplementary Table1). e expression of FABP6, an intercellular bile acid transporter, was decreased
34.30-fold in CPM. OLFM4 is a target of the Wnt/β-catenin pathway, its expression was reduced 3.77-fold in
CPM. DCN and PTEN are able to initiate a number of signalling pathways including ERK and EGFR leading
to growth suppression, their expression was increased 3.3-fold and 3.25 fold in CPM, this was unexpected and
in contrast to the literature55. NF-κBIA expression was increased 3.24-fold in CPM, its upregulation may reect
increased NF-κB activity in the development of CPM56.
Gene specic enrichment analysis (GSEA) results are presented in supplementary table5 We identied 848
upregulated gene ontology categories in CPM and 14 upregulated gene pathways. which may contribute to the
pathogenesis of CPM: the mTOR pathway as well as immune pathways including the intestinal immune network
for IgA production, Leukocyte transendothelial migration and the actin cytoskeleton pathway.
Dierential gene expression between non-responders and responders to CRS & HIPEC. One hundred and forty-
nine genes showed increased expression in non-responders (Fig.3). Five genes showed decreased expression in
non-responders, however none had a fold change ≥ 1.5 suggesting minimal dierence in expression between the
responders and non-responders (Supplementary Table2). KEGG pathway analysis demonstrated enrichment in
endocytosis, metabolism, phagocytosis, cell movement and architecture, bacterial and viral cell infection, tran-
Figure1. Venn diagrams depicting the frequency of mutations exclusive to and shared between primary CRC
and matched CPM and responders and non-responders.
Table 2. Potential candidate variants, non-responders to CRS & HIPEC. CPM identied through Fisher exact
test, genomics workbench (Chr, chromosome, FDR, false discovery rate).
Chr Position Reference Allele p Va lu e FDR Sample frequency (case) Sample frequency (control) Gene ID
4 93,084,410 C G 0.007 0.53 62.5 0 FAM13A
18 11,552,313 G C 0.023 0.53 50 0 PIEZO2
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BCYRN1
H19
MT2A
HBB
HBA2
MGP
TAGLN
HLA-DRB1
HLA-DRA
CD74
CTSB
TIMP1
FTL
COL1A1
COL1A2
SPARC
COL3A1
FN1
PSAP
COL6A1
ACTG1
RPS23P8
PPIA
FTH1
TPT1
EEF1A1
TMSB4X
TMSB10
B2M
S100A6
AC132217.4
RP11-543P15.1
ACTB
NEAT1
RNA5-8SP6
RP11-742N3.1
TFF3
CKB
PIGR
MTND1P23
PRSS3
GP2
CTRB1
CELA3B
AMY2A
PLA2G1B
CPB1
CTRB2
CLPS
PNLIP
PRSS1
CPA1
REG1A
SP100
IGHG4
IGHA1
IGJ
IGHG3
IGLC3
IGKC
IGLC2
IGLC1
MYL9
MALAT1
CRS
P
Z-score
Figure2.
Heatmap of dierential gene expression in 100 highest genes ranked by variance between primary CRC (P, red) and colorectal peritoneal metastasis (CRS, blue). Sample type is
indicated at the X axis of the heatmap with individual genes on the Y-axis. Individual IDs of each patient are below the indicators of primary or CRS sample. Gene expression as indicated by the
Z-score is displayed as colour ranging from green to black to red as shown in the legend. Created in Partek Flow.
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scription and the expression of genes controlling apoptosis, cell cycle, oxidative stress resistance and longevity
(Table3). e expression of CEACAM1, a member of the carcinoembryonic antigen (CEA) immunoglobulin
family, was increased 8.27-fold in non-responders57.
AXIN1 encodes a cytoplasmic protein which forms the ß-Catenin destruction complex, a negative regulator
of the WNT signalling pathway58. AXIN1 expression was increased 5.42-fold in non-responders59.
Gene specic enrichment analysis (GSEA) results are presented in supplementary table6. We identied 591
upregulated gene ontology categories in CPM and 15 upregulated gene pathways. which may contribute to the
pathogenesis of CPM: Endocytosis, the adherens junction pathway and immune pathways such as those regulat-
ing the bacterial invasion of epithelial cells.
Amongst the n = 51 primary CRC and CPM samples n = 29 were representative of each CMS subtype, the
remaining n = 22 samples did not have a consistent pattern (Fig.4). Comparison of the CMS subtypes in primary
and CPM and prognostic groups revealed an apparent transition from primary CRC to CPM. No primary CRC
samples were classied as CMS4 (mesenchymal subtype characterized by prominent transforming growth factor
activation, stromal invasion and angiogenesis) compared to 31% of CPM (p = 0.085). Secondly, non-responders
were more commonly CMS4, 46% vs. 15% (p = 0.005, Table4).
Methylation. Dierential methylation between primary CRC and matched CPM. irty-two samples in
total were hybridised successfully to the Illumina HumanMethylation EPIC microarrays. DMPs were called
between the primary CRC and CPM. e top ranked dierentially methylated probe was cg04146982, BF 34.5,
adjusted p value 5.67 × 10–16 (chr8:144,943,810–144,943,810, hg19 coordinates), which tags a CpG dinucleotide
3651bp upstream of the transcription start site of gene Epiplakin 1,(EPPK1)60. EPPK1 is part of the Plakin fam-
ily an important component of the cell cytoskeleton61. e other DMP was cg12209861, BF 7.1, adjusted p value
0.059 (chr4:37,459,078–37,459,078, hg19 coordinates), 3526bp upstream of the transcription start site of gene
Chromosome 4 Open Reading Frame 19, (C4orf19). DMRs were called between primary CRC and CPM via the
dmrLasso function of the CHAMP pipeline (Supplementary Table3). e top 10 most DMRs were in the region
of IGF2, ZNF461, RASGFR1, CELF4, ZSCAN18, EDNRB, ZBED9, VTRNA2-1, ZNF256 and EGFLAM. KEGG
pathway analysis did not reveal any signicantly enriched pathways.
Comparison of CNA between primary and CPM via methylation arrays did not identify and signicant dif-
ferences in CNA between primary and CPM at a stringent p value of < × 10–10 however a number of CNA were
identied at a lower signicance threshold, p = 2.78 × 10–07 (Supplementary Table4).Genes showing CNA gains
of known signicance in patients with CPM included; TRIM3, 5, 6, 21 and 22, MT1A, 2A, 3, 4 encode proteins
of the metallothionein family.
Table 3. e top 10 genes with signicantly altered expression (FDR < 0.1) in CPM samples compared with
primary CRC samples.
Rank Gene name Function Fold change FDR p value
Reduced expression CPM samples vs. primary CRC
1 FABP6 Intracellular bile acid transporter − 34.30 1.74 × 10–06
2 DEFA6 Cytotoxic peptide involved in host intestine defence − 8.15 8.55 × 10–06
3 DMBT1 Tumour suppressor − 6.06 2.43 × 10–04
4 TTC38 Protein coding gene − 4.56 5.80 × 10–05
5 OLFM4 Wnt/β-catenin pathway target − 3.77 1.01 × 10–04
6 IGHA1 Immune receptor − 3.66 4.23 × 10–05
7 CES2 Intestinal enzyme controlling drug clearance − 3.20 6.84 × 10–05
8 NDUFS6 Enzyme in electron transport chain of mitochondria − 2.70 7.74 × 10–05
9 P2RY11 G-protein coupled receptor − 2.53 6.37 × 10–04
10 MUC2 Encodes a mucinous intestinal coating − 2.34 7.22 × 10–04
Increased expression CPM samples vs. primary CRC
1 CD53 Tetraspanin 7.29 5.87 × 10–05
2 CYR61 Extracellular signalling protein 4.24 3.12 × 10–04
3 CXCL12 G-protein coupled receptor 3.64 9.25 × 10–04
4 NR2F1 Nuclear hormone receptor and transcriptional regulator 3.53 7.09 × 10–04
5 CTGF C onnective tissue growth factor 3.49 1.55 × 10–04
6 CSTB Cystatin 3.41 6.13 × 10–04
7 TSC22D3 Anti-inammatory protein glucocorticoid (GC)-induced leucine zipper 3.36 3.94 × 10–04
8 DCN Tumour suppressor gene 3.30 6.19 × 10–05
9 PTEN Tumour suppressor gene 3.25 9.28 × 10–04
10 NF-κBIA Inhibits the NF-κB transcription factor 3.24 1.06 × 10–04
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www.nature.com/scientificreports/
NEAT1
RP11-742N3.1
RNA5-8SP6
MALAT1
MYL9
SP100
IGHG4
IGHA1
IGJ
IGKC
IGLC3
IGLC2
IGLC1
IGHG3
REG1A
GP2
CTRB1
PLA2G1B
CTRB2
CPB1
CPA1
PRSS1
PNLIP
CLPS
AMY2A
CELA3B
PRSS3
CKB
TFF3
PIGR
MTND1P23
BCYRN1
H19
MT2A
HBA2
HBB
MGP
TAGLN
HLA-DRB1
HLA-DRA
CD74
CTSB
AC132217.4
S100A6
PPIA
TPT1
FTH1
TMSB4X
EEF1A1
TMSB10
B2M
RPS23P8
ACTG1
COL6A1
TIMP1
FTL
FN1
COL1A2
SPARC
COL3A1
COL1A1
PSAP
RP11-543P15.1
ACTB
Resp
Non-r
Z-score
Figure3.
Heatmap dierential gene expression of top 100 genes as ranked by variance between responders (blue) and non-responders (red)Sample type is indicated at the transverse border
of the heatmap with individual genes on the longitudinal border. Gene expression as indicated by the Z-score is displayed as colour ranging from green to black to red as shown in the legend.
Created in Partek Flow.
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Figure4. Sankey diagram depicting the transition in consensus molecular subtypes (CMS) from primary to
CPM. CMS classications were performed using ‘CMScaller’ (v0.99.1) in the R /Bioconductor statistics package.
Classications include CMS1 to CMS4, non-consensus samples do not have a consistent pattern of subtype label
association. Primary CRC samples, classication and number are shown to the le of the diagram with CPM
samples, classication and number to the right of the diagram. Fishers exact p value 0.085, values in parenthesis
percentages.
Table 4. CMS classication responders vs. non-responders to CRS & HIPEC. CMS Fishers exact p value
0.005, CRIS Fischer’s exact p value 0.148, values in parenthesis percentages.
Non-consensus CMS1 CMS2 CMS3 CMS4 Tot a l
Responders 10 (77) 0 (0) 0 (0) 1 (8) 2 (15) 13
Non-responders 2 (15) 1 (8) 3 (23) 1 (8) 6 (46) 13
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Dierential methylation between non-responders and responders to CRS & HIPEC. e top ranked dierentially
methylated probe was cg07951355, BF = 6, (chr1:40,123,717) which tags an intergenic region 1076bp before
gene NT5C1A. Cg25909064, BF 4 adjusted p value 0.47 (chr11:120,081,487–120,082,345) which tags an intron
of gene OAF and cg12977942, BF 4 adjusted p value 0.47 (chr5:92,839,309–92,839,309) which tags an intron of
gene NR2F1-AS160. Six signicant DMRs (Supplementary Table3) were identied in the regions of NKX6-2,
CHFR, GATA3, IRX5, HCK and BC019904. KEGG pathway analysis did not reveal any signicantly enriched
pathways.
Comparison of CNA between the CPM prognostic groups identied recurrent gene losses at chromosomes 3,
4, 14, 15, 17 and 19 (Supplementary Table4). CNA losses clustered in the RAS-MAPK-ERK signalling pathway
suggesting dysregulation in non-responders.
Comparison of CNA between the CPM prognostic groups identied n = 19 gene gains at chromosomes 9,
10 and 11. Genes showing CNA gains in non-responders included: SIT1, RNF38, MELK, PAX5, SHB, ZEB1,
DEAF1, ANTXR, EPS8L2 and PIDD1.
Discussion
is study determined the gene expression, CNA, methylation and somatic mutation prole of primary CRC and
matched isolated CPM to determine whether there were changes associated with the development of CPM or
predicting prognosis for patients with CPM. To our knowledge, this is the rst such analysis in a cohort of patients
with isolated CPM suitable for treatment with CRS & HIPEC. e MSKCC cohort of metastatic cancer20 had a
diverse range of metastatic cancer, none of whom overlapped with the type we have studied, which is isolated
colorectal peritoneal metastasis, with matched primary samples, suitable for cytoreduction.
Within this study responders and non-responders to CRS & HIPEC were well matched by demographics,
tumour stage, treatment and follow up. PCI varied between groups with responders having a median PCI of 5
(3–12) and non-responders a median PCI of 8 (2–12). A PCI of greater than 12 is associated with reduced survival
following CRS & HIPEC, no signicant dierence is consistently found at PCI levels below this27.
Comparison of patients with primary CRC and metachronous CPM identied biological changes associated
with the transition from primary CRC to CPM. Hypermethylation, CNA and hypermutation resulted in the
inactivation of tumour suppressors and oncogene activation in CPM, (TP53, VTRA2-1, TRIM proteins). ese
changes suggest a rapid rate of tumour growth unchecked by tumour suppressor or apoptotic mechanisms.
Increased MAPK and Wnt/β-catenin pathway activation was noted in CPM. Gene expression of negative
regulators of the Wnt pathway was reduced, (OLFM4, DEAFA6), negative Wnt regulators contained somatic
mutations, (APC, RNF43, FAM123B and TSC1), and the MAPK marker, RASFGFR1 was hypermethylated
suggesting persistent activation of MAPK and Wnt pathways. Multiple mutations of negative Wnt signalling
regulators make this an attractive therapeutic target. Porcupine inhibitors mediate the palmitoylation of Wnt
ligands, blocking Wnt signalling. e porcupine inhibitor LGK974 inhibits the upstream negative Wnt regulator
mutant RNF43 and is a potential therapeutic target in CPM62.
CPM contained a high proportion of MSH6 somatic mutations suggesting deciency in the mismatch repair
pathway and MSI. MSH6 mutations are commonly found in isolated peritoneal metastasis59. As expected for
tumours with mismatch repair deciency both the primary CRC and CPM cohort had a high tumour mutational
burden, crucially this suggests they may have a good response to treatment with immune checkpoint inhibitors
such as pembrolizumab63, a new therapeutic avenue for these dicult to treat patients. e frequency of hyper-
mutation seen in our study (48%) was considerably higher than that observed for both the MSKCC metastatic
disease cohort (5%) and the TCGA Colorectal64 cohort (10%). e expression of genes regulating innate immu-
nity however was downregulated, (DEFA6, DMBT1, MUC2) or altered via somatic mutations, (HLA-A antigen)
suggesting immune evasion in the transition to CPM which may reduce the likelihood of successful PD-1 therapy.
e expression of genes supressing invasion, migration and EMT was downregulated or hypermethylated,
(MUC2, MMP26, ILK, FLNB, SPTB, PPL, and SVEP1) and those triggering these processes upregulated, (CYR61,
CXCL12, CTGF, and CSTB). ese changes suggest a mechanism by which CPM cells metastasise from the
primary CRC. In keeping with changes in EMT regulators there appeared to be a transition in CMS subtypes
towards CMS4 from primary CRC to CPM. e CMS4 subtype is an interesting therapeutic target, TGFβ sig-
nalling inhibitors and targeted immunotherapies have been trialled with success in pre-clinical models to block
cross talk between the tumour microenvironment and halt disease progression of stromal rich CMS4 CRC
65,66.
Methylation appeared to be dysregulated in CPM with a bias towards a hypermethylator phenotype caused by
somatic mutation of the TET2 tumour suppressor and CDH7 chromatin regulator. Active DNA demethylation
by TET enzymes is an important tumour suppressor mechanism in a variety of cancers67–69. Downregulation of
CES2, a gene known to activate the prodrug irinotecan, a chemotherapy used as part of the FOLFIRI regimen in
the UK in the adjuvant treatment of primary CRC and CPM was seen in this cohort. Resistance to the treatment
of primary CRC may in part explain the development of CPM.
CEACAM1 expression correlates with metastasis and reduced survival in CRC and was upregulated in this
cohort of patients70. Novel therapies in the form or CEA TCB IgG-based T-cell bispecic antibodies (Cibisa-
tamab) may therefore be of benet71. Additionally there was a downregulation of gene expression of negative
regulators of the Wnt pathway, (AXIN1) and somatic mutations of key Wnt regulators, (FAM13A) and hyper-
methylation of MAPK and TGF-β pathway markers, (RAB8A, RAB34, FGF5 and BMP3) suggesting persistent
activation of MAPK, TGF-β and Wnt in non-responders to CRS & HIPEC.
A recent randomised controlled trial has called into question the use of HIPEC in CPM, PRODIGE-7 treated
patients with CPM with CRS & HIPEC or CRS alone in addition to systemic chemotherapy. PRODIGE-7 suggests
no added benet from HIPEC however this study was not powered to stratify the impact of HIPEC according to
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PCI score, on subgroup analysis patients with a PCI of 11–15 had signicantly improved median survival with
the addition of HIPEC 41.6months vs. 32.7months p value 0.020972.
A relative weakness of this study is the small cohort of patients, the biological changes identied here form a
starting point in identifying the tumour biology associated with the development of CPM and predicting non-
responders to CRS & HIPEC. However, we have identied multiple potential targets for therapy, along with the
important nding that CPM appears to be a hypermutated, hypermethylated, immune evasive cancer which
allows it to be potentially targeted by emerging novel therapeutics. Our study ndings have implications for the
recent addition of oxaliplatin to HIPEC, as the FOXTROT study of neoadjuvant therapy in colorectal cancer
showed that oxaliplatin has no eect in dMMR tumours.
Conclusions
Patients with colorectal peritoneal metastasis (CPM) secondary to colorectal cancer have limited survival with the
best available treatments. Despite selection for treatment using known prognostic factors survival varies widely
and can be dicult to predict. ere is a paucity of knowledge concerning the biology of CPM, it is likely that
there are additional biological markers of response to currently available as well as novel or re-purposed alterna-
tive treatments. Here we have comprehensively proled a cohort of patients with isolated CPM and identied a
number of therapeutically targetable alterations including mutations in Wnt/β catenin regulators (via Porcupine
inhibitors), the mismatch repair pathway (via PD-1/CTLA-4 immunotherapy) and methylation regulators. We
suggest that these are urgently investigated in a larger cohort with the development of pre-clinical models as, in
particular, the nding that these patients may be sensitive to immunotherapy may radically change the therapy
options available for this dicult to treat group of patients.
Data availability
e data that support the ndings of this study are available from the corresponding author upon reasonable
request.
Received: 20 May 2020; Accepted: 13 October 2020
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Author contributions
Study design: A.D.B., S.H., H.Y. Patient recruitment: S.H., H.Y. Molecular analysis: S.H., J.S., C.W., C.B., V.P.
Funding
e study was funded by a grant from the Good Hope Hospital Charity. ADB is funded by a Cancer Research
UK Advanced Clinician Scientist Award (C31641/A23923).
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https ://doi.org/10.1038/s4159 8-020-75844 -6.
Correspondence and requests for materials should be addressed to A.D.B.
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