The Glasgow Microenvironment Score and risk and site of recurrence in TNM I–III colorectal cancer

Abstract

Background
Glasgow Microenvironment Score (GMS) stratifies long-term survival into three groups based on tumour phenotype: peritumoural inflammation (Klintrup–Mäkinen (KM)) and tumour stroma percentage (TSP). However, it is not known if the location of disease recurrence is influenced by the GMS category.

Methods
Seven hundred and eighty-three TNM I–III colorectal cancers (CRC) were included. GMS (GMS0—high KM; GMS1—low KM, low TSP; GMS2—low KM, high TSP) and cancer-specific survival (CSS), overall survival (OS) and disease recurrence were assessed using Cox regression analysis.

Results
Of the 783 patients, 221 developed CRC recurrence; 65 developed local recurrence + systemic disease. GMS was independent for CSS (HR 1.50, 95% CI 1.17–1.92, p < 0.001) and OS (HR 1.23, 1.05–1.44, p = 0.01). Higher GMS category was associated with T-stage, N-stage, emergency presentation and venous invasion. GMS was independent for local+systemic recurrence (HR 11.53, 95% CI 1.45–91.85, p = 0.04) and distant-only recurrence (HR 3.01, 95% CI 1.59–5.71, p = 0.002). GMS 2 disease did not appear to have statistically better outcomes with adjuvant chemotherapy in high-risk disease.

Conclusion
Although confounded by a higher rate of T4 and node-positive disease, GMS 1 and 2 are associated with an increased risk of local and distant recurrence. GMS is an independent poor prognostic indicator for recurrent colorectal cancer. Higher GMS patients may benefit from enhanced postoperative surveillance.

Full text

ARTICLE OPEN
Clinical Studies
The Glasgow Microenvironment Score and risk and site of
recurrence in TNM I–III colorectal cancer
P. G. Alexander
1
✉, H. C. van Wyk
1
, K. A. F. Pennel
2
, J. Hay
3
, D. C. McMillan
1
, P. G. Horgan
1
, C. S. D. Roxburgh
1,2
, J. Edwards
2
and
J. H. Park
1
© The Author(s) 2022
BACKGROUND: Glasgow Microenvironment Score (GMS) stratifies long-term survival into three groups based on tumour
phenotype: peritumoural inflammation (Klintrup–Mäkinen (KM)) and tumour stroma percentage (TSP). However, it is not known if
the location of disease recurrence is influenced by the GMS category.
METHODS: Seven hundred and eighty-three TNM I–III colorectal cancers (CRC) were included. GMS (GMS0—high KM; GMS1—low
KM, low TSP; GMS2—low KM, high TSP) and cancer-specific survival (CSS), overall survival (OS) and disease recurrence were
assessed using Cox regression analysis.
RESULTS: Of the 783 patients, 221 developed CRC recurrence; 65 developed local recurrence +systemic disease. GMS was
independent for CSS (HR 1.50, 95% CI 1.17–1.92, p< 0.001) and OS (HR 1.23, 1.05–1.44, p=0.01). Higher GMS category was
associated with T-stage, N-stage, emergency presentation and venous invasion. GMS was independent for local+systemic
recurrence (HR 11.53, 95% CI 1.45–91.85, p=0.04) and distant-only recurrence (HR 3.01, 95% CI 1.59–5.71, p=0.002). GMS 2 disease
did not appear to have statistically better outcomes with adjuvant chemotherapy in high-risk disease.
CONCLUSION: Although confounded by a higher rate of T4 and node-positive disease, GMS 1 and 2 are associated with an
increased risk of local and distant recurrence. GMS is an independent poor prognostic indicator for recurrent colorectal cancer.
Higher GMS patients may benefit from enhanced postoperative surveillance.
British Journal of Cancer; https://doi.org/10.1038/s41416-022-02069-x
INTRODUCTION
The disease burden posed by colorectal cancer (CRC) on healthcare
worldwide is significant, with 1.8 million deaths attributed to the
disease in 2018 [1]. The primary tool for guiding both prognosis and the
multidisciplinary management of CRC is the TNM staging system, but
this has its limitations and cannot account for wide variations in
outcomeswithineachstage.Even with the addition of other
commonly used clinicopathological features, such as venous invasion
and common genetic markers, the prognostic ability remains poor [2].
In view of this need for further prognostic markers, the Glasgow
Microenvironment Score (GMS) was developed, combining the
beneficial prognostic marker of high peritumoural inflammation
and the poor prognostic marker of high tumour stroma [3]. In
terms of the consensus molecular subtypes (CMS) [4], high
peritumoural inflammation is one of the defining features of the
CMS1 (immune) subtype, whereas high tumour stroma represents
the CMS4 (mesenchymal) subtype [5]. The poor prognosis of the
CMS4 subgroup is due largely to its associated pro-angiogenic and
immunosuppressive properties [6].
Recently, GMS has been validated in a large independent cohort
and was found to be a prognostic indicator independent of TNM
stage, venous invasion and measures of the systemic inflammatory
response, with GMS 2 tumours shown to represent an additional
high-risk feature in otherwise low-risk disease [7]. In addition,
within a post hoc analysis of the SCOT Trial adjuvant chemother-
apy study, the GMS aided in the selection of patients for adjuvant
therapy; patients with GMS 0 appeared to derive greater benefit
from FOLFOX compared to CAPOX, whereas patients with GMS 2
did not appear to obtain any benefit from either regimen [7].
Finally, a modified version of the GMS in colorectal cancer biopsy
specimens has been shown to reflect that of the full resected
specimen, indicating that it may be useful in aiding in the selection
of patients for neoadjuvant therapy [8].
However, it is not yet known whether the GMS has the
propensity to identify the likelihood of future recurrence or
indicate potential sites of recurrence. There are data that suggest
high stromal tumours, represented by GMS 2, have a higher rate of
local recurrence [9,10]. Given that prognosis is good in those with
high peritumoural inflammation, represented by GMS 0, it is
hypothesised that patients in this group would have a low
recurrence rate in general. GMS 1 represents a heterogenous
group with neither high peritumoural inflammation nor high TSP
with an anticipated intermediate recurrence rate. Therefore, GMS
may select patients who are more at risk of disease recurrence and
Received: 13 June 2022 Revised: 10 November 2022 Accepted: 14 November 2022
1
School of Medicine, University of Glasgow, Glasgow, UK.
2
Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.
3
Glasgow Tissue Research Facility, University of
Glasgow, Queen Elizabeth University Hospital, Glasgow, UK. ✉email: p.alexander.1@research.gla.ac.uk
www.nature.com/bjc
British Journal of Cancer
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who, as a result, may benefit from more intense postoperative
surveillance.
Therefore, the aim of the present study was to examine the
relationship between the GMS and patterns of recurrence in patients
who have undergone resection of stage I–III colorectal cancer.
METHODS
The patients in this study were derived from a previously published cohort
of 1000 patients who have undergone resection of colorectal adenocarci-
noma between January 1997 and May 2013 in Glasgow Royal Infirmary
[11]. The following exclusions were applied: mortality within 30 days, TNM
4 disease, and palliative or R1 resection (positive resection margins). Of the
remaining 906 patients, pathology samples for GMS scoring were available
for 783 tumours. The West of Scotland Research Ethics Committee
provided ethical approval for the research.
Study endpoints
The primary study endpoints were cancer-specific survival (CSS; measured
from the date of surgery to date of death from cancer-specific cause or
censor date), overall survival (OS; measured from the date of surgery to
date of death from any cause or censor date) and colorectal cancer
recurrence (recurrences were considered present on either radiological or
pathological diagnosis, time from date of surgery to date of recurrence was
calculated). Survival data were confirmed by review of electronic case
notes and complete until 1 July 2020, which acted as the censor date. Data
on the location of recurrence were collected from paper and electronic
patient notes. Widespread recurrence was defined as more than one site of
disease recurrence. As a secondary endpoint, the disease response of
different GMS categories to adjuvant chemotherapy was compared with
those not receiving chemotherapy.
Clinicopathological data
Clinical characteristics and recurrence data were recorded from patient case
notes, both paper and electronic, and the site of recurrence from imaging.
Pathological data, including TNM stage and venous invasion (using elastic
haematoxylin–eosin (H&E) staining, for which both intramural and extramural
venous invasion were considered as present) were collected from pathology
reports. As previously described [11], the modified Glasgow Prognostic Score was
calculated using CRP (C-reactive Protein) and Albumin levels in whole venous
blood obtained within the 30 days preceding surgery. Data were available
regarding which patients received adjuvant chemotherapy, but not the regimen
or duration of chemotherapy. The Petersen index was used to indicate low- and
high-risk TNM stage II disease [12]: tumours with venous invasion or peritoneal
involvement were assigned a score of 1, whereas tumour perforation was
assigned a score of 2. Any individual with TNM III disease or TNM II with a
Petersen index ≥2 was considered high-risk. The definition of emergency surgery
was unplanned surgery on index hospital admission within 5 days.
Scoring the GMS
Whole H&E-stained sections taken from the point of deepest invasion were
scored manually for GMS using NDP view (Hamamatsu) after scanning
slides onto a server using the Hamamatsu NanoZoomer at ×20
magnification (Welwyn Garden City, UK). GMS score was calculated
according to Klintrup–Mäkinen grade (KM) and tumour stroma percentage
(TSP), as described [13]. Briefly, KM was scored (by single investigator PGA,
blinded to clinical data) semi-quantitatively at the tumour’s invasive
margin as weak (no inflammatory cells present or mild increase only) or
strong (presence of a band or cup-like infiltrate of inflammatory cells with
evidence of tumour nest destruction). TSP was calculated by assigning the
percentage area occupied, to the nearest 10%, by stroma vs tumour in the
centre of the tumour at ×100 magnification, excluding areas of necrosis
and mucin. This value was subsequently dichotomised into low stroma
(≤50%) vs high stroma (>50%). The scores for KM and TSP were combined
as follows: strong KM irrespective of TSP scored GMS 0; weak KM and low
TSP scored GMS 1; weak KM and high TSP scored GMS 2.
Fifty cases were co-scored by a second investigator (HCvW), and for all
scores, intra-class correlation co-efficient was >0.8.
Mismatch repair (MMR) protein analysis
MMR status was assessed by immunohistochemistry according to UK
NEQAS guidelines. Briefly, a tissue microarray comprised of four tumour-
rich cores per patient was utilised, with immunohistochemical staining
performed for MLH1, MSH2, MSH6 and PMS2 as previously described [14].
Intraepithelial immune cell staining was used as a positive control.
Tumours were considered MMR proficient if there was strong nuclear
staining with positive immune cells and were considered MMR deficient if
there was loss of tumour nuclear staining while immune cells remained
positive.
Statistical analysis
All data were analysed using SPSS version 27.0 (IBM SPSS). Survival analysis was
performed using Kaplan–Meier curves and log-rank analysis with adjustment for
T-stage, N-stage and other clinicopathological features, where appropriate.
Results are presented with hazard ratios (HRs) and 95% confidence intervals (CIs)
calculated with univariate Cox regression analysis. Multivariate survival analysis
was performed using a backward conditional stepwise model. A statistical
significance threshold of p< 0.1 was used to identify variables for inclusion in the
multivariate model. In-text results are given as HR, 95% CI for GMS 0 vs GMS 2, p
value of log-rank analysis for the overall trend. Chi-squared analysis was
performed to test associations between categorical variables and GMS. The study
conformed to the REMARK guidelines [15] and the statistical significance value
was set at p< 0.05.
RESULTS
Slides were available for scanning and subsequent GMS scoring for 783
tumours, out of a possible 906, with TNM I–III CRC. Compared with the
missing slides, those with H&E slides available were more likely to have
higher T-stage, more venous invasion and be colonic rather than rectal
location (Supplementary Table S1). Of the available samples, 554 were
colon cancers and 229 were rectal cancers. Clinicopathological
characteristics for included patients are given in Table 1.Sixty-seven
percentofpatientswereyoungerthan75yearsatthetimeofsurgery;
55% were male; 8% presented as an emergency and 61% were node
negative. One hundred and thirty-two patients (17%) were GMS 0; 501
(64%) were GMS 1 and 149 (19%) wereGMS2.Therewere477deaths,
of which 201 were related to CRC, and 221 developed recurrence. Of
the recurrences, 66 patients developed local recurrence with or without
systemic recurrence. An increasing GMS was associated with
emergency presentation (p=0.04), higher T- and N-stage (both
p< 0.001), greater MMR deficiency (p=0.02) and venous invasion
(p< 0.001), (Table 1).
Associations between GMS and CSS were assessed (Table 1and
Fig. 1a). GMS was able to stratify CSS in the whole cohort with 5-year
CSS of 89% for GMS 0, 78% for GMS 1 and 61% for GMS 2 (GMS 0 vs
GMS 2: HR 3.72 95% CI 2.22–6.24, p< 0.001). On multivariate analysis,
GMS remained independent (p=0.001) of age (p< 0.001), T-stage
(p=0.03), N-stage (p< 0.001) and mGPS (p=0.06). Subgroup analysis
was performed according to TNM stage, MMR status and primary
tumour location (Table 2). GMS was able to stratify survival in early TNM
I-II disease with 5-year CSS for GMS 0, 1 and 2 of 89%, 87% and 75%,
respectively (GMS 0 vs GMS 2: HR 2.89 95% CI 1.42–5.85, p=0.003,
Fig. 1B); and TNM III disease with 5-year CSS for GMS 0, 1 and 2 of 90%,
63% and 50%, respectively (GMS 0 vs GMS 2: HR 3.36 95% CI 1.42–7.91,
p=0.006, Fig. 1C). GMS was also able to stratify MMR proficient and
MMR deficient disease with 5-year CSS of 93%, 80% and 65%, and 95%,
75% and 59%, respectively (MMR proficient: GMS 0 vs GMS 2: HR 3.21
95% CI 1.76–5.84, p< 0.001; MMR deficient: GMS 0 vs GMS 2: HR 6.72
95% CI 1.53–29.58, p=0.02). In addition, GMS was able to stratify CSS
regardless of the use of adjuvant chemotherapy (No adjuvant therapy:
GMS 0 vs GMS 2: HR 3.33 95% CI 1.91–5.82, p< 0.001; Adjuvant therapy:
GMS 0 vs GMS 2: HR 11.54 95% CI 1.54–86.27, p=0.02). It has been
suggested that high stromal tumours respond poorly to standard
chemotherapy, and it may be seen that the GMS 2 patients in the
adjuvant chemotherapy group did not have a good outcome (Table 2).
To further explore this, analysis was performed for high-risk patients for
each GMS category according to whether the patients received
adjuvant chemotherapy or not (Supplementary Table 2). The only
group with a significant benefit from chemotherapy was GMS 1. Those
with GMS 0 had a good outcome regardless of chemotherapy and
P.G. Alexander et al.
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British Journal of Cancer

Table 1. Cancer-specific and overall survival in stage I–III colorectal cancer and associations of clinicopathological features with GMS (N=783).
Clinicopathological
characteristics
Cancer-specific survival Overall survival GMS category
N(%)
a
Univariate HR
(95% CI)
pMultivariate HR
(95% CI)
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
p0(n=132)
N(%)
a
1(n=501)
N(%)
2(n=150)
N(%)
Pearson X
2
Age
≤64 257 (33) 50 (38) 162 (32) 45 (30) 0.72
65–74 265 (34) 34 (26) 174 (35) 57 (38)
≥75 261 (33) 1.39 (1.17–1.66) <0.001 1.38 (1.14–1.67) <0.001 1.85 (1.64–2.08) <0.001 1.84 (1.62–2.09) <0.001 48 (36) 165 (33) 48 (32)
Gender
Female 354 (45) 61 (46) 231 (46) 62 (41) 0.39
Male 429 (55) 1.16 (0.88–1.54) 0.29 ––1.12 (0.93–1.34) 0.23 ––71 (54) 270 (54) 88 (59)
Presentation
Elective 719 (92) 125 (95) 462 (92) 132 (88) 0.04
Emergency 64 (8) 2.11 (1.41–3.14) <0.001 –0.07 1.46 (1.09–1.96) 0.012 –0.67 7 (5) 39 (8) 18 (12)
TNM
I 112 (14) 41 (31) 65 (13) 6 (4) <0.001
II 368 (47) 62 (47) 249 (50) 57 (38)
III 303 (39) 2.32 (1.83–2.93) <0.001
b
––1.39 (1.21–1.59) <0.001
b
––29 (22) 187 (37) 87 (58)
T-stage
T1 43 (6) 17 (13) 25 (5) 1 (1) <0.001
T2 92 (12) 33 (25) 53 (11) 6 (4)
T3 451 (58) 68 (52) 300 (60) 83 (55)
T4 197 (25) 1.78 (1.44–2.19) <0.001 1.31 (1.02–1.67) 0.03 1.33 (1.17–1.50) <0.001 –0.13 14 (11) 123 (25) 60 (40)
N-stage
N0 480 (61) 103 (78) 314 (63) 63 (42) <0.001
N1 225 (29) 25 (19) 139 (28) 61 (41)
N2 78 (10) 1.93 (1.61–2.31) <0.001 1.89 (1.54–2.32) <0.001 1.29 (1.13–1.46) <0.001 1.37 (1.18–2.09) <0.001 4 (3) 48 (10) 26 (17)
Site
Colon 554 (71) 93 (71) 359 (72) 102 (68) 0.63
Rectum 229 (29) 1.08 (0.80–1.45) 0.63 ––0.99 (0.81–1.20) 0.90 ––39 (30) 142 (28) 48 (32)
Neoadjuvant therapy
No 725 (93) 127 (96) 464 (93) 134 (91) 0.06
Yes 54 (7) 0.99 (0.59–1.68) 0.98 ––0.68 (0.45–1.03) 0.07 –0.71 5 (4) 35 (7) 14 (10)
Differentiation
Well/mod 705 (91) 128 (97) 442 (89) 135 (90) 0.06
Poor 74 (9) 1.10 (0.68–1.79) 0.70 ––1.23 (0.91–1.66) 0.18 ––4 (3) 55 (11) 15 (10)
MMR deficient
No 550 (82) 92 (83) 363 (84) 95 (74) 0.02
Yes 121 (18) 1.41 (0.99–2.00) 0.05 –0.08 1.35 (1.07–1.71) 0.01 1.30 (1.03–1.64) 0.03 19 (17) 68 (16) 34 (26)
Venous invasion
Absent 374 (48) 74 (56) 247 (49) 53 (35) <0.001
Present 409 (52) 1.48 (1.12–1.97) 0.006 –0.26 1.20 (1.00–1.44) 0.047 –0.23 58 (44) 254 (51) 97 (65)
mGPS
0 500 (64) 88 (67) 323 (65) 89 (59) 0.19
1 160 (20) 22 (17) 108 (22) 30 (20)
2 123 (16) 1.39 (1.17–1.66) <0.001 1.22 (0.99–1.50) 0.06 1.44 (1.28–1.61) <0.001 1.27 (1.12–1.44) <0.001 22 (17) 70 (14) 31 (21)
P.G. Alexander et al.
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British Journal of Cancer

those with GMS 2 did not have an improved outcome despite
chemotherapy. Finally, GMS was able to stratify OS regardless of the
site of the primary tumour (Colon cancer: GMS 0 vs GMS 2: HR 3.54
95% CI 1.92–6.51, p< 0.001; Rectal cancer: GMS 0 vs GMS 2: HR 4.17
95% CI 1.56–11.13, p=0.004).
Next, associations between GMS and OS were assessed (Table 1).
GMS was able to stratify OS in the whole cohort with 5-year OS of
75% for GMS 0, 63% for GMS 1 and 48% for GMS 2 (GMS 0 vs GMS 2:
HR 1.97 95% CI 1.44–2.69, p< 0.001). On multivariate analysis, GMS
was independent (p=0.006) of age (p< 0.001), N-stage (p< 0.001),
MMR deficiency (p=0.03) and mGPS (p< 0.001). Subgroup analysis
was performed according to TNM stage, MMR status, adjuvant
therapy and primary tumour location (Table 2). GMS was able to
stratify survival in TNM I–II disease with 5-year OS for GMS 0, 1 and 2
of 74, 69 and 58%, respectively (GMS 0 vs GMS 2: HR 1.59 95% CI
1.04–2.42, p=0.03); and TNM III disease with 5-year OS for GMS 0, 1
and 2 of 79, 54 and 41%, respectively (GMS 0 vs GMS 2: HR 2.32 95%
CI 1.33–4.03, p=0.003). GMS was also able to stratify MMR-
proficient and MMR-deficient disease with 5-year OS of 75, 63 and
49%, and 68, 60 and 38%, respectively (MMR proficient: GMS 0 vs
GMS 2: HR 1.84 95% CI 1.26–2.70, p=0.007; MMR deficient: GMS 0
vs GMS 2: HR 2.23 95% CI 1.13–4.41, p=0.02). GMS was able to
stratify OS regardless of the use of adjuvant chemotherapy (No
adjuvant therapy: GMS 0 vs GMS 2: HR 1.88 95% CI 1.34–2.64,
p< 0.001; Adjuvant therapy: GMS 0 vs GMS 2: HR 5.30 95% CI
1.84–15.26, p=0.002) or the site of primary tumour (Colon cancer:
GMS 0 vs GMS 2: HR 1.95 95% CI 1.34–2.83, p< 0.001; Rectal cancer:
GMS 0 vs GMS 2: HR 2.02 95% CI 1.15–3.54, p=0.015).
The relationship between pattern of recurrence and GMS was
subsequently examined (Table 3). Overall, the recurrence rate for
GMS 0 was 15% during the course of follow-up, compared with
27% in GMS 1 and 38% in GMS 2. The rates of local recurrence
only GMS 0, 1 and 2 were 4, 5 and 7%, respectively, while for
recurrence of local+systemic recurrences these were 1, 5 and 7%,
respectively. Similarly, the rates for distant recurrence only were
10, 18 and 25%, respectively, for GMS 0, 1 and 2 (p< 0.001). In
terms of specific recurrence location, GMS 0 had the highest
recurrence-free rate of 85%, vs 73% for GMS 1 and 62% for GMS
2. The numbers were small for most individual locations, but the
pattern was similar for liver, lung and widespread recurrences
with the highest rates in GMS 2 and lowest in GMS 0.
Cox regression analysis for recurrence risk was subsequently
performed according to the location of recurrence inthe full cohort
(Table 4). On univariate analysis for local recurrence only, three
variables were significant for recurrence risk and all remained
independent on multivariate analysis: age (p=0.01), T-stage
(p=0.02), and N-stage (p=0.008). GMS was not significant for
local recurrence only (Fig. 2a). GMS was, however, significant for
local+systemic recurrence risk on multivariate analysis (p<0.05,
Fig. 2b), independent of T-stage (p=0.009) and mGPS (p=0.04).
GMS was also significant in multivariate analysis for distant-only
recurrence risk (p=0.02, Fig. 2c), independent of N-stage
(p< 0.001), venous invasion (p=0.002) and mGPS (p=0.02).
Differences in recurrence patterns between colon and rectal
cancers were subsequently assessed (Table 3and Fig. 2).
Comparing colon and rectal cancer recurrences, there was a
higher number of liver metastases in rectal cancer than colon
cancer (10 vs 7%, respectively), although this was not significant
(p=0.10). Furthermore, local recurrence rates, although small,
were a similar number in both rectal and colon cancer (4 and 6%,
respectively, p=0.30) and when considering local with or
without systemic recurrence, the rates were 9 and 9%,
respectively. In colon cancers, the recurrence rate for GMS 0
was 18%, compared with 26% in GMS 1 and 36% in GMS 2. The
rates of local recurrence only for GMS 0, 1 and 2 were 3, 6 and
7%, while those for local+systemic recurrence were 1, 4 and 5%,
respectively. Similarly, the rates for distant recurrence only were
14, 17 and 24%, respectively, for GMS 0, 1 and 2 (p=0.04). In
Table 1. continued
Clinicopathological
characteristics
Cancer-specific survival Overall survival GMS category
N(%)
a
Univariate HR
(95% CI)
pMultivariate HR
(95% CI)
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
p0(n=132)
N(%)
a
1(n=501)
N(%)
2(n=150)
N(%)
Pearson X
2
GMS
0 132 (17) ––––
1 501 (64) 1.95 (1.54–2.46) –––
2 150 (19) <0.001 1.54 (1.19–2.00) 0.001 1.41 (1.21–1.65) <0.001 1.22 (1.07–1.49) 0.006 –––
a
Percentages rounded to nearest whole number and may not total 100%.
b
Not included in multivariate model as T-stage and N-stage are included separately.
Statistically significant p< 0.05 values are in bold.
P.G. Alexander et al.
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British Journal of Cancer

terms of specific recurrence location, GMS 0 had the highest
recurrence-free rate of 82%, vs 74% for GMS 1 and 64% for GMS 2.
The numbers were small for most individual locations, but the
pattern was similar for liver, lung and widespread recurrences with
highest rates in GMS 2 and lowest in GMS 0. On univariate
analysis, GMS was not significant for local recurrence only
(p=0.11, Fig. 2d and Table 5), nor for local+systemic recurrence
(p=0.07, Fig. 2e and Table 5). However, this was likely due to
small numbers, since on analysis local recurrence with or without
systemic recurrence, GMS was able to stratify recurrence risk,
although the trend did not reach significance (HR 3.66 95% CI
1.18–11.36, p=0.07, Supplementary Fig. 1). GMS was significant
on univariate analysis for Distant recurrence only (p=0.02, Fig. 2f
and Table 5), although this was not independent of N-stage
(p=0.02), venous invasion (p=0.03) or mGPS (p=0.04).
In rectal cancers, the recurrence rate for GMS 0 was 8% during
the course of follow-up, compared with 29% in GMS 1 and 39% in
GMS 2. The rates of local recurrence only for GMS 0, 1 and 2 were
6, 3 and 5%, while those for local+systemic recurrence were 0, 7
and 9%, respectively. Similarly, the rates for distant recurrence
only were 3, 21 and 26%, respectively, for GMS 0, 1 and 2
(p< 0.001). In terms of specific recurrence location, GMS 0 had the
highest recurrence-free rate of 92%, vs 71% for GMS 1 and 61% for
GMS 2. The numbers were small for most individual locations, but
the pattern was similar for liver, lung and widespread recurrences
with higher rates in GMS 2 and the lowest in GMS 0. On univariate
analysis, GMS was not significant for local recurrence only
(p=0.92, Fig. 2g and Table 6). However, GMS was significant for
local+systemic recurrence (p=0.02, Fig. 2h and Table 6) and was
the only variable to be significant for recurrence risk in this group
other than mGPS. It was not possible to perform multivariate
analysis for this group due to low event numbers (N=11). For
local recurrence with or without systemic recurrence, GMS
trended towards significance, but was unable to stratify recur-
rence risk (HR 3.92 95% CI 0.78–19.77, p=0.10, Supplementary
Fig. 1). GMS was significant on multivariate analysis for distant
recurrence only (HR 2.10, 1.23–3.56, p=0.006, Fig. 2i and Table 6),
independent of gender (p=0.04) and N-stage (p< 0.001).
DISCUSSION
In this large, single-centre study, the GMS was observed to be an
independent prognostic marker for TNM I-III CRC. An increasing
GMS was associated with increased risk of recurrence overall. GMS
was also able to identify those at risk of local recurrences with
systemic involvement in the full cohort and in rectal cancers. The
main advantage of GMS over other proposed scores is its ability to
be performed on routine H&E-stained whole slides with no need
for immunohistochemistry. Klintrup-Mäkinen grade has also been
shown to strongly correlate with immunohistochemistry for other
peritumoural immune cells (CD3 and CD8) [7,16].
GMS 0, characterised by higher peritumoural inflammatory
response, has been established as a prognostic marker conferring
a survival benefit[17]. The same effect was observed in the
current study with the lowest recurrence rate in this group. It must
be noted, however, that the recurrence rate is not zero and whilst
higher peritumoural inflammatory response is considered protec-
tive, there are clearly other factors at play in this group. Of note,
the type of immune cells is not accounted for by this specific
scoring system. Others have shown that polarisation of
a
bc
Number of
patients at risk
GMS 0 132 (0) 121 (6)
100
80
60
% survival
40
20
0
100
02448
CSS (months)
CSS (months)
72 96 120 02448
CSS (months)
72 96 120
80
60
% survival
40
20
0
100
80
60
% survival
40
20
0
0 24487296120
112 (8) 98 (13) 85 (16) 57 (18)
GMS 1 500 (0) 440 (36) 367 (75) 314 (102) 242 (115) 154 (118)
GMS 2 150 (0) 121 (18) 90 (41) 71 (53) 52 (59) 28 (59)
Full Cohort
GMS 0
GMS 1 HR 1.88 95% CI 1.16–3.06
GMS 2 HR 3.72 95% CI 2.22–6.24, p < 0.001
Number of
patients at risk
GMS 0 103 (0) 94 (4) 86 (5) 75 (10) 65 (12) 44 (12)
GMS 1 313 (0) 284 (12) 243 (28) 215 (38) 159 (45) 103 (46)
GMS 2 63 (0) 57 (3) 47 (8) 36 (14) 25 (18) 13 (18)
TNM I-II
GMS 0
GMS 1 HR 1.35 95% CI 0.73–2.48
GMS 2 HR 2.89 95% CI 1.42–5.85, p = 0.003
Number of
patients at risk
GMS 0 29 (0) 27 (2) 26 (3) 23 (3) 20 (4) 13 (6)
GMS 1 187 (0) 156 (24) 124 (47) 99 (64) 83 (70) 51 (72)
GMS 2 87 (0) 64 (15) 43 (33) 35 (39) 27 (41) 15 (41)
TNM III
GMS 0
GMS 1 HR 2.24 95% CI 0.97–5.14
GMS 2 HR 3.36 95% CI 1.42–7.91, p = 0.007
Fig. 1 Cancer-specific survival according to GMS category. a Full cohort (N=782); bTNM I-II (N=479); cTNM III (n=303).
P.G. Alexander et al.
5
British Journal of Cancer

Table 2. Univariate survival for GMS according to TNM, MMR status, adjuvant chemotherapy and location of primary cancer (N=783).
Group GMS category NCancer-specific survival Overall survival
5-year CSS (%; SE) Events (N=201) HR (95% CI) p5-year OS (%; SE) Events (N=477) HR (95% CI) p
Full cohort Trend <0.001 Trend <0.001
0 132 89 (3) 19 1.0 (reference) 75 (4) 67 1.0 (reference)
1 501 78 (2) 122 1.88 (1.16–3.06) 0.01 63 (2) 310 1.40 (1.08-1.82) 0.01
2 149 61 (4) 60 3.72 (2.22–6.24) <0.001 48 (4) 100 1.97 (1.44–2.69) <0.001
TNM I–II Trend 0.003 Trend 0.09
0 103 89 (3) 13 1.0 (reference) 74 (4) 51 1.0 (reference)
1 314 87 (2) 50 1.35 (0.73–2.48) 0.34 69 (3) 183 1.26 (0.92–1.72) 0.15
2 63 75 (6) 19 2.89 (1.42–5.85) 0.003 58 (6) 38 1.59 (1.04–2.42) 0.03
TNM III Trend 0.007 Trend 0.006
0 29 90 (6) 6 1.0 (reference) 79 (8) 16 1.0 (reference)
1 187 63 (4) 72 2.24 (0.97–5.14) 0.06 54 (4) 127 1.67 (0.99–2.81) 0.05
2 86 50 (6) 41 3.36 (1.42–7.91) 0.006 41 (5) 62 2.32 (1.33–4.03) 0.003
MMR proficient Trend <0.001 Trend 0.007
0 92 93 (3) 15 1.0 (reference) 75 (5) 47 1.0 (reference)
1 362 80 (2) 86 1.62 (0.94–2.81) 0.08 63 (3) 223 1.38 (1.01–1.89) 0.045
2 95 65 (5) 38 3.21 (1.76–5.84) <0.001 49 (5) 62 1.84 (1.26–2.70) 0.002
MMR deficient Trend 0.024 Trend 0.02
0 19 95 (5) 1 1.0 (reference) 68 (11) 12 1.0 (reference)
1 68 75 (5) 34 3.81 (0.90–16.11) 0.07 60 (6) 50 1.21 (0.65–2.29) 0.55
2 34 59 (9) 19 6.72 (1.53–29.58) 0.01 38 (8) 28 2.23 (1.13–4.41) 0.02
No adjuvant chemo Trend <0.001 Trend 0.001
0 111 87 (3) 18 1.0 (reference) 70 (4) 63 1.0 (reference)
1 375 78 (2) 88 1.59 (0.96–2.65) 0.07 61 (3) 252 1.33 (1.01–1.75) 0.046
2 99 63 (5) 40 3.33 (1.91–5.82) <0.001 47 (5) 72 1.88 (1.34–2.64) <0.001
Adjuvant chemo Trend 0.007 Trend 0.002
0 21 100 (0) 1 1.0 (reference) 100 (0) 4 1.0 (reference)
1 126 76 (4) 34 6.82 (0.93–49.86) 0.06 71 (4) 58 3.33 (1.21–9.20) 0.02
2 49 58 (7) 19 11.54 (1.54–86.27) 0.02 51 (7) 27 5.30 (1.84–15.26) 0.002
Colon cancer Trend <0.001 Trend 0.002
0 93 90 (3) 14 1.0 (reference) 77 (4) 47 1.0 (reference)
1 359 79 (2) 85 1.78 (1.01–3.13) 0.046 64 (3) 225 1.40 (1.03–1.92) 0.04
2 102 61 (5) 40 3.54 (1.92–6.51) <0.001 47 (5) 68 1.95 (1.34–2.83) <0.001
Rectal cancer Trend 0.004 Trend 0.04
0 39 89 (5) 5 1.0 (reference) 69 (7) 20 1.0 (reference)
1 142 75 (4) 37 2.16 (0.85–5.50) 0.11 63 (4) 85 1.38 (0.84–2.24) 0.20
2 47 61 (8) 20 4.17 (1.56–11.13) 0.004 51 (7) 32 2.02 (1.15–3.54) 0.015
Statistically significant p< 0.05 values are in bold.
P.G. Alexander et al.
6
British Journal of Cancer

macrophages to M2 macrophages may be a poor prognostic sign
[18]. Furthermore, these individuals that developed recurrence in
spite of the beneficial phenotype of high KM may have had a
more aggressive tumour biology. These, therefore, represent
areas requiring further investigation and the combination of
genetic profile and GMS is one of the planned future directions
of study.
In the present study, patients with GMS 2 had the highest rates
both of local and distant disease recurrence. Previous work suggests
that this pathological phenotype, characterised by high TSP and
accompanied by a poor immune response, denotes a mesenchymal
subtype with poor prognosis and higher recurrence risk [5,7,9,10,19].
There are several confounding factors in this group with associations
demonstrated between higher GMS and higher T-stage, N-stage and
Table 3. GMS and recurrence location (n=737).
Group GMS category GMS
Colon +Rectal cancer N (%) 0(n=125) N(%)
a
1(n=474) N(%) 2 (n=138)
N(%)
Pearson X
2
Recurrence
None 540 106 (85) 348 (73) 86 (62)
Local only 37 5 (4) 23 (5) 9 (7)
Local +systemic 29 1 (1) 19 (4) 9 (7)
Distant only 162 13 (10) 84 (18) 34 (25) <0.001
Recurrence location
None 540 106 (85) 348 (73) 86 (62) –
b
Local only 37 5 (4) 23 (5) 9 (7)
Nodal 3 1 (1) 2 (1) 0 (0)
Liver 57 3 (2) 39 (8) 15 (11)
Lung 22 3 (2) 12 (3) 7 (5)
Brain 6 1 (1) 5 (1) 0 (0)
Widespread 74 6 (5) 46 (10) 22 (16)
Colon cancer only (n =544) N 0(n=89) N(%)
a
1(n=338) N(%) 2 (n=95) N(%)
Recurrence
None 384 (74) 73 (82) 251 (74) 60 (64)
Local only 29 3 (3) 19 (6) 7 (7)
Local +systemic 18 1 (1) 12 (4) 5 (5)
Distant only 91 (17) 12 (14) 56 (17) 23 (24) 0.04
Recurrence location
None 384 (74) 73 (86) 251 (82) 60 (72) –
b
Local only 29 (5) 3 (3) 18 (5) 7 (7)
Nodal 3 1 (1) 2 (1) 0 (0)
Liver 35 (6) 3 (3) 21 (6) 11 (12)
Lung 12 (2) 2 (2) 7 (2) 3 (3)
Brain 4 1 (1) 3 (1) 0 (0)
Widespread 56 6 (7) 36 (11) 15 (15)
Rectal cancer only (n =229) N0(n=36) N(%)
a
1(n=136) N(%) 2 (n=43) N(%)
Recurrence
None 156 (73) 33 (92) 97 (71) 26 (61)
Local only 8 2 (6) 4 (3) 2 (5)
Local +systemic 11 0 (0) 7 (5) 4 (9)
Distant only 40 (19) 1 (3) 28 (21) 11 (26) <0.001
Recurrence location
None 156 (68) 33 (92) 97 (71) 26 (61) –
b
Local only 7 (3) 2 (6) 4 (3) 1 (2)
Nodal 0 –––– ––
Liver 22 (10) 0 (0) 18 (13) 4 (9)
Lung 10 (4) 1 (3) 5 (4) 4 (9)
Brain 2 0 –2 (2) 0 –
Widespread 18 0 (0) 10 (7) 8 (19)
a
Total percentage may not equal 100 as it is rounded to the nearest whole number.
b
No statistical analysis as cells with n<6.
P.G. Alexander et al.
7
British Journal of Cancer

Table 4. Univariate and multivariate recurrence risk analysis in stage I–III colorectal cancer (full cohort).
Clinicopathological
characteristics
Local recurrences only Local +systemic Distant only
Univariate HR
(95% CI)
pMultivariate HR
(95% CI)
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
p
Age
≤64
65–74
≥75 1.65 (1.09–2.50) 0.02 1.73 (1.14–2.64) 0.01 0.87 (0.55–1.38) 0.55 ––1.10 (0.88–1.36) 0.39 ––
Gender
Female
Male 1.08 (0.56–2.07) 0.82 ––1.00 (0.48–2.09) 0.99 ––1.36 (0.95–1.94) 0.09 –0.06
Presentation
Elective
Emergency 1.26 (0.39–4.11) 0.70 ––3.83 (1.55–9.46) 0.004 –0.17 1.89 (1.12–3.19) 0.02 –0.29
TNM
I
II (low risk)
III (high risk) 2.20 (1.29–3.75) 0.004
a
––1.99 (1.10–3.60) 0.02
a
––2.01 (1.52–2.65) <0.001
a
––
T-stage
T1
T2
T3
T4 2.10 (1.27–3.46) 0.004 1.82 (1.09–3.06) 0.02 3.10 (1.66–5.77) <0.001 2.39 (1.25–4.59) 0.009 1.50 (1.17–1.93) 0.001 –0.39
N-stage
N0
N1
N2 1.97 (1.29–2.99) 0.02 1.84 (1.18–2.89) 0.008 1.82 (1.13–2.94) 0.01 –0.14 1.79 (1.43–2.25) <0.001 1.58 (1.25–2.00) <0.001
Differentiation
Well/mod
Poor 2.04 (0.85–4.90) 0.11 ––0.77 (0.18–3.23) 0.72 ––1.07 (0.59–1.93) 0.83 ––
MMR status
Proficient
Deficient 1.71 (0.77–3.83) 0.19 ––0.93 (0.32–2.72) 0.90 ––1.19 (0.76–1.88) 0.45 ––
Venous invasion
Absent
Present 0.81 (0.43–1.55) 0.53 ––2.14 (0.97–4.71) 0.06 –0.35 2.07 (1.43–3.00) <0.001 1.81 (1.23–2.65) 0.002
mGPS
0
1
2 1.21 (0.79–1.85) 0.39 ––1.88 (1.22–2.90) 0.004 1.60 (1.01–2.52) 0.04 1.22 (0.98–1.53) 0.08 1.31 (1.04–1.64) 0.02
GMS
0
1
2 1.49 (0.86–2.58) 0.15 ––2.52 (1.34–4.73) 0.004 1.90 (1.00–3.61) <0.05 1.70 (1.27–2.28) <0.001 1.41 (1.05–1.89) 0.02
a
Not included in multivariate model as T-stage and N-stage are included separately.
Statistically significant p< 0.05 values are in bold.
P.G. Alexander et al.
8
British Journal of Cancer

venous invasion, a finding also demonstrated in other studies [19].
GMS was not able to stratify risk of local only recurrence. However,
GMS was an independent marker when comparing recurrence risk for
both local+systemic recurrence and distant only recurrence. Further-
more, Kaplan–Meier curves for both CSS and OS display an early and
sustained fall in survival in the GMS 2 group.
Given the high-risk nature of the GMS 2 phenotype, these tumours
may warrant more aggressive follow-up with an enhanced surveillance
programme, in order to detect recurrent disease at an earlier stage.
It was observed that 54 of the patients with rectal cancer also
received neoadjuvant chemoradiotherapy and this may have had
an impact on these recurrence figures [20]. Given the anatomy of
colon and rectal cancers and the blood supply/venous drainage, it
was hypothesised that local recurrences may be higher in the
rectal cancer group whereas liver metastases may be higher in the
colon cancer group [21]. Liver metastases were in fact proportio-
nately higher in the rectal cancer group than the colon cancer
group, although this was not significant. In addition, local
recurrences were at a similar level in both groups.
Whilst not the primary aim of this study, the response of different
GMS categories to chemotherapy was of interest, particularly in light
of the findings in the SCOT trial [7]. In this cohort, the specific
chemotherapy regimen was not known and the analysis therefore
focused on chemotherapy vs no chemotherapy in high-risk
colorectal cancer. GMS 1 was the only group found to benefitfrom
chemotherapy. The numbers were relatively small in the GMS
0 subgroup. However, these patients were in a GMS category that
have a naturally good prognosis according to phenotypic tumour
assessment. The finding that the GMS 2 subgroup did not have a
statistically better outcome following chemotherapy may indicate,
as has been previously stated, that this group of tumours do not
respond well to standard chemotherapy regimens and would
benefit from novel strategies to combat high tumour stroma and
the chemoresistance that this may offer [22].
In terms of limitations, this study was not performed in the
context of the rigorous follow-up of a clinical trial and therefore,
although data was taken from a prospectively maintained data set, it
is possible that patients were lost to follow-up. Furthermore, a small
number of patients received neoadjuvant therapy for rectal cancer
(n=54) and this is known to alter the appearance of the tumour
microenvironment with the addition of fibrosis making assessment
of TSP difficult [23]. However, only 14 of these were deemed to have
high TSP. Additionally, GMS was independent of neoadjuvant
therapy on multivariate analysis for survival. Finally, the chemother-
apeutic regimen that patients received was not known, which
limited further analysis of the adjuvant chemotherapy subgroup.
CONCLUSION
GMS has been observed to associate with both local and systemic
CRC recurrence. GMS was an independent prognostic indicator for
disease recurrence at any location. The numbers for local disease
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
100
Recurrence free %
80
60
40
20
0
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 12002448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
02448
Time from surgery (months)
72 96 120
Number of
patients at risk
GMS 0 124 (0) 111 (5) 100 (9) 90 (9) 79 (11) 53 (13)
GMS 1 473 (0) 392 (42) 323 (69) 286 (78) 226 (80) 145 (82)
GMS 2 137 (0) 92 (23) 75 (30) 63 (32) 50 (33) 26 (33)
Local recurrence only in Full cohort
GMS 0
GMS 1
GMS 2 HR 2.16 95% CI 0.72–6.44, p = 0.33
Local + systemic recurrence in Full cohort
GMS 0
GMS 1
GMS 2 HR 11.53 95% CI 1.45–91.85, p = 0.04
Distant recurrence only in Full cohort
GMS 0
GMS 1
GMS 2 HR 3.01 95% CI 1.59–5.71, p = 0.002
Number of
patients at risk
GMS 0 124 (0) 111 (0) 100 (1) 90 (1) 79 (1) 53 (1)
GMS 1 473 (0) 392 (9) 323 (14) 286 (15) 226 (18) 145 (18)
GMS 2 137 (0) 92 (7) 75 (9) 63 (9) 50 (9) 26 (9)
de
Number of
patients at risk
GMS 0 89 (0) 81 (2) 71 (2) 65 (3) 55 (3) 37 (3)
GMS 1 339 (0) 279 (6) 235 (12) 209 (17) 161 (19) 105 (19)
GMS 2 95 (0) 65 (3) 54 (4) 44 (7) 35 (7) 18 (7)
Local recurrence only in Colon cancers
GMS 0
GMS 1
GMS 2 HR 2.89 95% CI 0.75–11.20, p = 0.29
Local + systemic recurrence in Colon cancers
GMS 0
GMS 1
GMS 2 HR 5.94 95% CI 0.69–50.91, p = 0.24
abc
Number of
patients at risk
GMS 0 124 (0) 111 (4) 100 (4) 90 (5) 79 (5) 53 (5)
GMS 1 473 (0) 392 (7) 323 (15) 286 (21) 226 (23) 145 (23)
GMS 2 137 (0) 92 (5) 75 (6) 63 (9) 50 (9) 26 (9)
Number of
patients at risk
GMS 0 89 (0) 81 (5) 71 (9) 65 (9) 55 (11) 37 (12)
GMS 1 339 (0) 279 (29) 235 (45) 209 (51) 161 (53) 105 (54)
GMS 2 95 (0) 65 (14) 54 (20) 44 (22) 35 (22) 18 (22)
Distant recurrence only in Colon cancers
GMS 0
GMS 1
GMS 2 HR 2.28 95% CI 1.13–4.58, p = 0.02
f
Number of
patients at risk
GMS 0 89 (0) 81 (0) 71 (1) 65 (1) 55 (1) 37 (1)
GMS 1 339 (0) 279 (7) 235 (8) 209 (9) 161 (12) 105 (12)
GMS 2 95 (0) 65 (5) 54 (5) 44 (5) 35 (5) 18 (5)
gh
Number of
patients at risk
GMS 0 35 (0) 30 (2) 29 (2) 25 (2) 24 (2) 16 (2)
GMS 1 135 (0) 114 (1) 89 (3) 78 (4) 66 (4) 41 (4)
GMS 2 43 (0) 28 (2) 22 (2) 20 (2) 16 (2) 9 (2)
Local recurrence only in Rectal cancers
GMS 0
GMS 1
GMS 2 HR 1.12 95% CI 0.16–7.99, p = 0.67
Local + systemic recurrence in Rectal cancers
GMS 0
GMS 1
GMS 2 HR NA*
Number of
patients at risk
GMS 0 35 (0) 30 (0) 29 (0) 25 (0) 24 (0) 16 (1)
GMS 1 135 (0) 114 (13) 89 (24) 78 (27) 66 (27) 41 (28)
GMS 2 43 (0) 28 (9) 22 (10) 20 (10) 16 (11) 9 (11)
Distant recurrence only in Rectal cancers
GMS 0
GMS 1
GMS 2 HR 11.51 95% CI 1.49–89.22, p = 0.06
i
Number of
patients at risk
GMS 0 35 (0) 30 (0) 29 (0) 25 (0) 24 (0) 16 (0)
GMS 1 135 (0) 114 (2) 89 (6) 78 (6) 66 (6) 41 (6)
GMS 2 43 (0) 28 (2) 22 (4) 20 (4) 16 (4) 9 (4)
* No events in GMS 0, unable to calculate
Fig. 2 Recurrence risk in full cohort, colon cancers and rectal cancers, stratified by GMS. a Local recurrence only in full cohort; blocal
+systemic recurrence in full cohort; cdistant recurrence only in full cohort; dlocal recurrence only in colon cancers; elocal+systemic
recurrence in colon cancers; fdistant recurrence only in colon cancers; glocal recurrence only in rectal cancers; hlocal+systemic recurrence in
rectal cancers; idistant recurrence only in rectal cancers.
P.G. Alexander et al.
9
British Journal of Cancer

Table 5. Univariate and multivariate recurrence risk analysis in stage I–III colon cancers (N=554).
Clinicopathological
characteristics
Local recurrences only Local +systemic Distant only
Univariate HR
(95% CI)
pMultivariate HR
(95% CI)
pUnivariate HR
(95% CI)
pMultivariate HR (95%
CI)
a
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
p
Age
≤64
65–74
≥75 1.42 (0.89–2.25) 0.14 ––1.00 (0.57–1.78) 0.99 ––1.16 (0.90–1.50) 0.26 ––
Gender
Female
Male 0.81 (0.39–1.67) 0.56 ––0.68 (0.27–1.73) 0.42 ––1.10 (0.72–1.66) 0.67 ––
Presentation
Elective
Emergency 1.20 (0.36–3.95) 0.77 ––2.93 (0.96–8.91) 0.06 ––2.10 (1.22–3.61) 0.007 –0.19
TNM
I
II (low risk)
III (high risk) 2.14 (1.16–3.92) 0.01
b
––3.11 (1.33–7.24) 0.009
b
––1.90 (1.35–2.66) <0.001
b
––
T-stage
T1
T2
T3
T4 1.86 (1.06–3.26) 0.03 –0.10 5.95 (2.24–15.82) <0.001 ––1.71 (1.25–2.34) <0.001 –0.08
N-stage
N0
N1
N2 1.92 (1.20–3.09) 0.007 1.71 (1.04–2.79) 0.03 2.28 (1.39–4.42) 0.002 ––1.61 (1.22–2.13) <0.001 1.40 (1.05–1.89) 0.02
Differentiation
Well/mod
Poor 1.93 (0.73–5.05) 0.18 ––1.15 (0.27–5.01) 0.85 ––1.14 (0.59–2.19) 0.70 ––
MMR status
Proficient
Deficient 1.54 (0.61–3.89) 0.36 ––0.92 (0.27–3.17) 0.89 ––1.07 (0.62–1.85) 0.80 ––
Venous invasion
Absent
Present 0.82 (0.40–1.71) 0.61 ––3.48 (1.15–10.58) 0.03 ––2.04 (1.32–3.16) 0.001 1.65 (1.04–2.60) 0.03
mGPS
0
1
2 1.17 (0.73–1.89) 0.52 ––1.81 (1.05–3.15) 0.03 ––1.39 (1.08–1.80) 0.01 1.32 (1.01–1.72) 0.04
GMS
0
1––
2 1.66 (0.89–3.08) 0.11 ––2.08 (0.94–4.57) 0.07 1.55 (1.09–2.19) 0.02 –0.25
a
Multivariate analysis not supported as only 18 events for Local +systemic.
b
Not included in multivariate model as T-stage and N-stage are included separately.
Statistically significant p< 0.05 values are in bold.
P.G. Alexander et al.
10
British Journal of Cancer

Table 6. Univariate and multivariate recurrence risk analysis in stage I–III rectal cancers (N=229).
Clinicopathological
characteristics
Local recurrences only Local +systemic Distant only
Univariate HR
(95% CI)
pMultivariate HR (95%
CI)
b
pUnivariate HR
(95% CI)
pMultivariate HR (95%
CI)
b
pUnivariate HR
(95% CI)
pMultivariate HR
(95% CI)
p
Age
≤64
65–74
≥75 2.76 (1.05–7.26) 0.04 ––0.68 (0.28–1.62) 0.38 ––0.99 (0.66–1.49) 0.97 ––
Gender
Female
Male 5.00 (0.61–40.67) 0.13 ––2.13 (0.56–8.17) 0.27 ––2.44 (1.16–5.13) 0.02 2.21 (1.05–3.21) 0.04
Presentation
Elective
Emergency –
a
–– ––
c
–– ––
c
–– –
TNM
I
II (low risk)
III (high risk) 2.59 (0.79–8.46) 0.12 ––1.16 (0.51–2.63) 0.73 ––2.23 (1.35–3.68) 0.002
d
––
T-stage
T1
T2
T3
T4 3.13 (0.96–10.13) 0.06 ––1.72 (0.68–4.38) 0.25 ––1.23 (0.80–1.91) 0.35 ––
N-stage
N0
N1
N2 2.24 (0.90–5.59) 0.09 ––0.92 (0.37–2.27) 0.92 ––2.25 (1.50–3.37) <0.001 2.10 (1.39–3.18) <0.001
Differentiation
Well/mod
Poor 2.42 (0.30–19.69) 0.41 –––
a
–– –0.87 (0.21–3.61) 0.85 ––
MMR status
Proficient
Deficient 2.23 (0.43–11.50) 0.34 ––0.96 (0.12–7.94) 0.97 ––1.57 (0.68–3.63) 0.29 ––
Venous invasion
Absent
Present 0.81 (0.20–3.25) 0.81 ––0.94 (0.29–3.10) 0.92 ––2.12 (1.06–4.24) 0.03 –0.13
mGPS
0
1
2 1.24 (0.45–3.37) 0.68 ––2.19 (1.09–4.39) 0.03 ––0.81 (0.46–1.43) 0.47 ––
GMS
0
1
2 1.06 (0.33–3.44) 0.92 ––3.50 (1.20–10.24) 0.02 ––2.10 (1.23–3.56) 0.006 1.99 (1.14–3.48) 0.02
a
No events in GMS 0, not possible to perform Cox regression.
b
Multivariate analysis not supported as only 8 events for Local only and 11 events for Local +systemic.
c
Only three cases in the emergency group.
d
Not included in multivariate model as T-stage and N-stage are included separately.
Statistically significant p< 0.05 values are in bold.
P.G. Alexander et al.
11
British Journal of Cancer

recurrence were low. However, GMS was found to be an independent
indicator of recurrence risk for both local+systemic recurrence and
distant recurrence. Since GMS is a marker for recurrent colorectal
cancer, patients with GMS 2 tumours may benefitfromenhanced
postoperative surveillance to aid the earlier detection of recurrent
disease. Furthermore, patients with GMS 2 have not been found to
respond well to standard chemotherapy; however, novel agents that
may be of benefit remain to be investigated.
DATA AVAILABILITY
The datasets that formed the basis of this article are contained in the University of
Glasgow’s MVLS Institute and are continually being updated with ongoing research.
They contain patient-sensitive information and therefore cannot be made available
on a public repository.
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ACKNOWLEDGEMENTS
The authors would like to thank Maria Thomson and Kirsten Wallace at the Glasgow Tissue
Research Facility for their hard work in identifying the samplesf orthe patients in this data set.
AUTHOR CONTRIBUTIONS
Conceptualisation and design (PGA, DCM, PGH, CSDR, JE, JHP), methodology (PGA,
HCvW, KAFP, DCM, CSDR, JE, JHP), investigation (PGA, KAFP, JH, JE, JHP) data curation
(PGA, KAFP, HCvW, CSDR, JHP), validation (PGA, HCvW, JE, JHP), formal analysis (PGA),
resources (JH), supervision (DCM, PGH, JE, JHP), writing: original draft (PGA), review
and editing (PGA, KAFP, HCvW, DCM, PGH, JH, CSDR, JE, JHP).
FUNDING
The authors declare no funding particular to this study.
COMPETING INTERESTS
The authors declare no competing interests.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
All patients provided written informed consent. The study complied with the
Declaration of Helsinki and was approved by the West Glasgow Research Ethics
Committee.
CONSENT FOR PUBLICATION
All authors consent to publication of this research/data.
ADDITIONAL INFORMATION
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1038/s41416-022-02069-x.
Correspondence and requests for materials should be addressed to P. G. Alexander.
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P.G. Alexander et al.
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British Journal of Cancer