Literature DB >> 23868006

Tumour-infiltrating CD68+ and CD57+ cells predict patient outcome in stage II-III colorectal cancer.

N Chaput1, M Svrcek, A Aupérin, C Locher, F Drusch, D Malka, J Taïeb, D Goéré, M Ducreux, V Boige.   

Abstract

BACKGROUND: The aim of our study was to evaluate the prognostic role of immunological microenvironnement in stage II-III CRC patients.
METHODS: We constructed a tissue microarray from 196 consecutive patients with stage II-III CRC and compared CD3, CD4, CD8, CD57, CD68, CXCL9/MIG, CXCL13, and PPARγ immunoreactivity in tumour samples and their matched non-tumour tissue. We assessed their association with relapse-free survival (RFS; primary endpoint) and overall survival (OS) in multivariate Cox models.
RESULTS: Low densities of CD57+ and CD68+ tumour-infiltrating cells (TIC) independently predicted worse outcomes. A prognostic score combining CD57 (+, > vs -, ≤2 cells per spot) and CD68 (+, >0 vs -, =0 cells per spot) TIC density discriminated CRC patients at low (CD68+/CD57+), intermediate (CD68+/CD57-), or high (CD68-/CD57-) risk, with hazard ratios for the intermediate-risk and high-risk groups of 2.7 (95% confidence interval (CI): 1.3-5.8) and 9.0 (3.2-25.4) for RFS, and 2.5 (1.2-5.1) and 10.6 (3.8-29.2) for OS, respectively, as compared with the low-risk group. Corresponding 5-year survival rates (95% CI) in the low-, moderate- and high-risk groups were 84% (71-91), 65% (54-74), and 12% (2-47), respectively, for RFS, and 91% (80-96), 76% (66-84), and 25% (7-59), respectively, for OS.
CONCLUSION: Tumour CD57+ and CD68+ TIC density assessment independently predicts survival in patients with stage II-III CRC. If validated, our score based on a quick, inexpensive, and well-established method such as point counting on diagnostic tissue sections could be used routinely as a prognostic tool in CRC patients.

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Year:  2013        PMID: 23868006      PMCID: PMC3749560          DOI: 10.1038/bjc.2013.362

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Despite advances in screening, diagnosis, and treatment, colorectal cancer (CRC) is the third leading cause of cancer-related mortality (Greenlee ). Pathological staging is currently the most accurate predictor of CRC prognosis and is used in clinical practice to select patients for adjuvant chemotherapy—more specifically, those with stage II (node-negative) CRC and stage III (node-positive) CRC, patients with stage I disease not deriving benefit from adjuvant chemotherapy due to an excellent prognosis, and those with stage IV disease being already metastatic (AJCC, 2010). However, 10–40% of patients with stage II (node-negative) CRC and 20–80% of those with stage III (node-positive) CRC develop recurrence after curative-intent (R0) surgical resection (AJCC, 2010). Several molecular markers have been shown to predict the likelihood of recurrence in stage II and III CRC, including microsatellite instability (deficient mismatch repair (dMMR)) and allelic imbalances (for example, loss of 8p and 18q chromosomal arms) (Halling ; Gryfe ; Zhou ). However, only the dMMR tumour phenotype remained a significant prognostic factor in early CRC both in a meta-analysis and prospective trials (Popat ; Hutchins ). Recently, Pages showed that the absence of an immune response within primary colonic cancer (CC) (stage I–IV disease) was associated with early metastatic invasion and worse survival, and that the density of CD3+ CD45RO+ tumour-infiltrating lymphocytes (TIL) was a better predictor of outcome than pathological staging according to the Union Internationale Contre le Cancer (UICC) tumour–node–metastasis (TNM) system (Galon ). By contrast, Laghi showed that CD3+ TIL density was prognostic in stage II, but not in stage III CRC. Furthermore, apart from T-cell markers, other tumour immune markers related to macrophages, NK cells, or chemokines have also been found to predict outcome in CRC. However, these putative immune prognostic markers have not been assessed simultaneously in the same patient cohort (Coca ; Pages ; Galon ; Forssell ; Hojo ; Laghi ; Ogino ; Ferdinande ; Mlecnik ). In the present study, we aimed to evaluate the prognostic value of immune tumour-infiltrating cells (TIC) and chemokines in stage II and III CRC patients. To assess simultaneously on the same patients the prognostic value of multiple immune parameters, we used a tissue microarray (TMA) analysis.

Materials and Methods

Patients

Patients with CRC who underwent primary surgery at our institution between 1990 and 2000 were selected according to the following criteria: curative-intent resection (negative (R0) surgical margin status) for pathologically confirmed colorectal adenocarcinoma, UICC TNM stage II or III tumour (AJCC, 2010), no preoperative chemotherapy, no family history of Lynch syndrome or adenomatous polyposis, and postoperative follow-up of at least 2 years. As increased numbers of TIL represent one of the particular pathological features of CRC with dMMR phenotype (Jass ; Laghi ), patients with dMMR CRC as defined by molecular analysis or immunohistochemistry (IHC) (Suraweera ; Hampel ) were excluded. Tumour stage (TNM) and differentiation, vascular emboli, lymphatic invasion, and perineural invasion (VELIPI) (Pages ) were determined from the histopathological reports obtained at the time of the resection.

Construction of TMAs

Paired, paraffin-embedded tumour (TT) and normal (NT) tissues from the whole patient population were used for the construction of TMA (product MTA1; Beecher Instruments, Sun Prairie, WI, USA). Three core biopsy samples measuring 0.6 mm in diameter (0.3 mm2 per spot) from paraffin-embedded TT (centre of the tumour) and the NT counterpart blocks were arrayed into a recipient paraffin block (35 × 22 × 5 mm3). Tissue microarray containing the tissue cores was then cut into 4-μm sections for hematoxylin and IHC staining.

Immunohistochemistry

The sections were affixed to Superfrost Plus slides (CML, Nemours, France), deparaffinised, and rehydrated. Antigen retrieval, consisting of microwave processing at 750 W and 150 W for 15 minutes each and pressure cooking in 0.01 M citrate buffer (pH 7.3), was applied. Dako Cytomation peroxidase blocking reagent (Dako, Les Ulis, France) was used to suppress non-specific staining due to endogenous peroxidase activity. On the basis of previous published data on tumour immunity, immune cell recruitment and/or inflammation status of tumour environment, and the prognostic role of immune response in CRC, the following markers were selected for IHC analysis on TMA: CD3 (Pages ; Galon ; Laghi ; Pages ; Mlecnik ), CD68 (Ohtani ; Funada ; Forssell ; Algars ; Zhou ), CD57 (Coca ; Jonges ; Menon ), CD8 (Pages , 2009), CD4 (Diederichsen ; Hojo ) in order to quantify macrophage and lymphocyte cell infiltration as effectors of IFN-γ production. In addition, the following chemokines known to be regulated by IFN-γ pathway were analysed: CXCL9/MIG (Mlecnik ), CXCL10/IP-10 (Mlecnik ), CXCL13/BCA1 (Lin ; Agesen ), Conversely, PPARγ (Ogino ) and IDO (Brandacher ; Ferdinande ) previously identified as potential prognostic markers in CC and involved in inhibition of Th1 (IFN-γ producer T cells) and Tc1 (cytotoxic T cells) were also selected. The following monoclonal antibodies were used: anti-CXCL9 (clone 49106.11, R&D systems, Lille, France) at 1 : 100 dilution, anti-CXCL13 (clone 53610, R&D systems) at 1 : 20 dilution, anti-PPARγ (clone E-8, Santa Cruz Biotechnology, Heidelberg, Germany) at 1 : 10 dilution, anti-CD4 (clone 4B12, Novocastra, Nanterre, France) at 1 : 20 dilution, anti-CD8 (clone 4B11, Dako) at 1 : 25 dilution, anti-CD57 (clone NK1, Dako) at 1 : 100 dilution, anti-CD68 (clone PGM1, Dako) at 1 : 100 dilution, and polyclonal antibody anti-CD3 (Dako) at 1 : 100 dilution. All incubations were performed at room temperature. Immunoperoxidase staining, using 3,3′-diaminobenzidine as a chromogen, was performed. Nuclei were counterstained with hematoxylin. The number of CD3-, CD4-, CD8- and CD57-positive (intra-epithelial and stromal) cells per spot was quantified by a single pathologist unaware of clinical data. Positivity for CD68 was scored quantitatively according to the number of positive stromal cells per spot: 0, no staining; 1, less or equal to 10-positive cells; 2, more than 10-positive cells. IHC staining of CXCL9, CXCL13/BCA1, and PPARγ was evaluated by semi-quantitative scores. For CXCL9, intact nuclear staining of the colonic crypts of the normal mucosa, lymphocytes, and endothelial cells was used as an internal positive control and was required for adequate evaluation. Normal immunoreactivity of the CXCL9 protein was defined as the presence of nuclear staining. The intensity of nuclear immunostaining was evaluated by the following scoring system: 0, no staining; 1, weak staining; 2, moderate staining; and 3, strong staining. Nuclear immunoreactivity for CXCL13/BCA1 was scored semi-quantitatively according to staining of stromal lymphocytes: 0, no staining; 1, few lymphocytes stained; and 2, numerous lymphocytes stained. Nuclear immunoreactivity for PPARγ was based on staining intensity and graded as 0, no staining; 1, mild-to-moderate staining; and 2, strong staining. The rounded average expression of the three core biopsy samples was used for each patient. No reliable IHC data could be obtained for CXCL10/IP-10 and IDO.

Statistical analyses

The primary endpoint of the prognostic analysis was relapse-free survival (RFS), defined as the time from CRC diagnosis to locoregional relapse, distant relapse, or death related to CRC. Patients without any of these three events were censored at the time of last follow-up or at the death time in case of death from other cause. The secondary endpoint of the prognostic analysis was overall survival (OS), defined as the time from CRC diagnosis to death whatever the cause. Patients alive at the time of last follow-up were censored at that date. RFS and OS probabilities were estimating according to the Kaplan–Meier method. Follow-up duration was estimated by the reverse Kaplan–Meier method. The prognostic impact of each clinicopathological factor was studied in univariate analysis using logrank test. Clinicopathological factors associated with RFS or OS with a P-value lower than 0.20 were tested in multivariate analysis using Cox model. The prognostic impact of immune markers measured within the tumour was studied. CD3-, CD4-, and CD8-positive cells were dichotomised at their median value. Despite a median value of one per spot for CD57, we chose a threshold value of >2 per spot that seemed to the pathologist more reliable for the quantification. The number of CD68-positive cells per spot was studied in three categories: no staining; less or equal to 10-positive cells; and more than 10-positive cells. CXCL9/MIG was studied in three categories: no staining; weak staining; moderate to strong staining. PPARγ and CXCL13/BCA1 were studied in three categories as they were graded, that is, for PPARγ, no staining; mild-to-moderate staining; strong staining and for CXCL13/BCA1 no staining, few lymphocytes stained, numerous lymphocytes stained. The prognostic impact of each immune marker was studied using Cox model with adjustment for clinicopathological prognostic factors previously identified. All markers with a P-value lower then 0.20 in the Cox model were analysed all together to determine their independent prognostic value. Immune markers staining were compared between TT and NT using paired t-test for quantitative variables and Bowker's test of symmetry for qualitative staining variables. Comparisons of markers staining between patients who received preoperative radiotherapy (preop-RT) and other patients and associations between all markers staining in TT and in NT were analysed using χ2-test or Fisher's exact test. As the number of tests realised for the latter analysis was high, Bonferroni correction was used (P⩽0.0018 as the threshold of significance instead of 0.05). All statistical tests were two-sided. Statistical analyses were performed with the SAS System, version 9.1 (SAS, Grégy-sur-Yerres, France).

Results

Patient characteristics

Characteristics of the 196 eligible patients are shown in Table 1. Adjuvant chemotherapy consisted of intravenous 5-fluorouracil and leucovorin in all the 115 (59%) patients who received adjuvant chemotherapy. The median duration of follow-up was 10 years (Interquartile range 6.8–13.3). Only 11 patients were followed less than 4 years. During follow-up, 73 recurrences and 72 deaths (cancer-related, 54) occurred. Five-year RFS and OS rates were 64% (s.e., 3.5) and 75% (s.e. 3.2), respectively. Prognostic analysis of clinicopathological factors (Cox model) identified tumour location (rectal vs colonic tumour), TNM stage (II vs III), and adjuvant chemotherapy (yes vs no) as independent predictors of RFS, and the same factors plus tumour grade for OS (Table 2).
Table 1

Patient characteristics

 n (%)
Age
Mean±s.d.61.5±11
Range
27–86
Sex
Male108 (55)
Female
88 (45)
Tumour site
Colon, right-sided51 (26)
Colon, left-sided98 (50)
Rectum
47 (24)
Nodal status
N099 (50)
N154 (28)
N231 (16)
N positive (not specified)
12 (6)
Tumour grade
Well to moderately differentiated167 (85)
Poorly differentiated20 (10)
Missing
9 (5)
VELIPI
067 (34)
1122 (62)
Missing
7 (4)
Tumour stage
II99 (51)
III
97 (49)
Adjuvant chemotherapy
5-Fluorouracil and folinic acid115 (59)
No
81 (41)
Preoperative radiation therapy
Yes38 (19)
No158 (81)

Abbreviation: VELIPI=vascular emboli, lymphatic invasion and perineural invasion.

Table 2

Five-year relapse-free and overall survival according to clinicopathological factors

 
Univariate analysis
Multivariate analysis
Relapse-free survivaln5-Year rateP-valueaHR (95% CI)P-valueb
Sex
Male10862   
Female
88
66
0.97
 
 
Tumour site
Colon14971 1.0 
Rectum
47
40
<0.0001
2.4 (1.5–3.9)
0.0004
Tumour grade
Well-to-moderate differentiation16767   
Poor differentiation
20
42
0.012
 
 
Tumour stage
Stage II9973 1.0 
Stage III
97
54
0.0005
3.5 (2.0–6.1)
<0.0001
VELIPIc
VELIPI no6770   
VELIPI yes
122
61
0.11
 
 
Adjuvant chemotherapy
Yes11568 1.0 
No
81
59
0.37
0.5 (0.3–0.9)
0.013
Preoperative radiation therapy
Yes3842   
No
158
69
0.0008
 
 
Overall survival
Sex
Male10874   
Female
88
76
0.88
 
 
Tumour site
Colon14980 1.0 
Rectum
47
58
0.0014
2.0 (1.2–3.3)
0.009
Tumour grade
Well-to-moderate differentiation16781 1.0 
Poor differentiation20340.00012.3 (1.2–4.6) 
Unknown
9
 
 
1.5 (0.5–4.1)
0.045
Tumour stage
Stage II9982 1.0 
Stage III
97
68
0.016
2.8 (1.6–5.0)
0.0004
VELIPIc
VELIPI no6786   
VELIPI yes
122
69
0.30
 
 
Adjuvant chemotherapy
Yes11580 1.0 
No
81
68
0.068
0.5 (0.3–0.9)
0.02
Preoperative radiation therapy
Yes3859   
No158790.0047  

Abbreviations: CI=confidence interval; HR=hazard ratio; VELIPI=vascular emboli, lymphatic invasion and perineural invasion.

log-rank P-value.

Cox-Wald χ2-test P-value.

Vascular/lymphatic/perineural invasion.

Tissue microarray analysis

CD3, CD4, CD8, CD57, and CD68 cell density as for PPARγ, CXCL13/BCA1, and CXCL9/MIG staining intensity were significantly decreased in TT as compared with NT (each univariate, P<0.0001, except for CD8, P=0.007) (Figure 1).
Figure 1

Immune environment differ between tumour tissue and matched normal tissue. (A) Enumeration of positive cells per spot in normal (NT) and tumour tissues (TT) was assessed for CD3, CD4, CD8, and CD57. (B) As in A but CD68-positive cells were studied in three semi-quantitative categories: no staining (white bars); 1 to 10 cells per spot (light grey bars); more than 10 cells per spot (dark grey bars) as for CXCL9/MIG, PPARγ but using three qualitative categories: no staining (white bars); weak to moderate staining (light grey bars); moderate to strong staining (dark grey bars) as indicated in the figure, and for CXCL13/BCA1 no staining (white bars); few cells stained (light grey bars); numerous cells stained (dark grey bars). Paired t-test for quantitative variables and Bowker's test of symmetry for qualitative staining variables, P<0.05 was considered as significant.

Preop-RT impacted on all immune markers but PPARγ expression (Supplementary Table 1). The expression levels of CD57 and CD68 were significant higher in irradiated tumours (n=38) than in non-irradiated tumours (n=158) (P=0.002 and P<0.0001, respectively). The expression levels of CD57, CD68, and CXCL13/BCA1 were significant higher in normal tissue in patients who received preop-RT compared with non- irradiated patients (P=0.009, P=0.004, and P=0.010, respectively), whereas those of CD3, CD4, CD8, and CXCL9/MIG were significant lower (P=0.018, P=0.004, P<0.0001, and P=0.0017 respectively). Therefore, we concluded that preop-RT significantly modified the tumour immune microenvironment, and decided to base further analyses on patient population who did not receive preop-RT. Among the 158 remaining patients, positive associations were found for TT expression between CD57 and CD68 (P=0.0006), CXCL9/MIG and PPARγ (P=0.0015), and CD8 and CXCL13/BCA1 (P<0.0001), and a negative association for TT expression between CD8 and CXCL9/MIG (P<0.0001). Positive associations were also found for NT expression between CXCL9/MIG and both CD4 (P<0.0001) and PPARγ (P=0.0001), and CD8 and CXCL13/BCA1 (P<0.0001), and a negative association between CD57 and CD4 (P=0.0005) (Supplementary Table 2A and 2B).

Prognostic analyses

Five-year RFS and OS rates in the subset of patients who did not receive preop-RT (n=158) were 69% (s.e.=3.7) and 79% (s.e.=3.4), respectively. The same prognostic clinicopathological factors as in the whole patient cohort were found in this patient subgroup (data not shown). After adjustment for these factors (tumour location, stage, grade, and adjuvant chemotherapy), lower CD3+, CD57+, and CD68+ TIC densities were significantly associated with worse RFS and OS, and lower tumour expression of CXCL9/MIG with worse RFS (Table 3A, Figure 2). In multivariate analysis, only CD57+ and CD68+ TIC densities remained independently associated with RFS and OS (Table 3B). The hazard ratio (HR) for the risk of relapse was 2.7 (95% confidence interval (CI): 1.2–5.7) in patients with ⩽2 CD57+ TIC per spot as compared with those with >2 CD57+ TIC per spot, and 3.5 (1.4–9.1) in patients with no CD68+ TIC as compared with those with >10 CD68+ TIC per spot. However, the risk of relapse was not significantly increased in patients with 1–10 CD68+ TIC per spot as compared with those with >10 CD68+ TIC per spot (HR: 1.2; 95% CI: 0.6–2.3). Similar results were observed regarding OS (Table 3B). Of note, the prognostic effect of CD57+ and CD68+ TIC densities on RFS and OS did not significantly differ according to the disease stage (that is, stage II vs stage III) (Supplementary Table 3).
Table 3A

Prognostic value of CD3, CD8, CD4, CD57, CD68, CXCL9/MIG, PPARγ, and CXCL13/BCA1 in tumour tissue from patients without preop-RT after adjustment for anatomoclinical factors (tumour location, stage, grade, and adjuvant chemotherapy)

 
 
Relapse-free survival
Overall survival
 nHR95% CIPHR95% CIP
CD3
CD3 ⩽80 cells per spot762.11.1–4.0 2.01.1–3.8 
CD3 >80 cells per spot731 0.021 0.025
Missing
9
 
 
 
 
 
 
CD4
CD4 ⩽2 cells per spot880.90.5–1.6 1.30.7–2.4 
CD4 >2 cells per spot661 0.721 0.41
Missing
4
 
 
 
 
 
 
CD8
CD8 ⩽8 cells per spot801.40.8–2.6 1.50.8–2.7 
CD8 >8 cells per spot741 0.251 0.22
Missing
4
 
 
 
 
 
 
CD57
CD57 ⩽2 cells per spot1003.21.5–6.6 2.91.4–5.9 
CD57 >2 cells per spot561 0.0021 0.003
Missing
2
 
 
 
 
 
 
CD68
CD68=0 cells per spot85.42.1–13.4 7.63.0–18.8 
1⩽ CD68 ⩽10 cells per spot551.40.8–2.7 1.91.0–3.5 
CD68 >10 cells per spot941 0.00161 <0.0001
Missing
1
 
 
 
 
 
 
CXCL9/MIG
No staining363.31.3–8.4 3.21.2–8.4 
Weak staining802.31.0–5.3 2.61.0–6.3 
Moderate to strong421 0.0411 0.063
Missing
0
 
 
 
 
 
 
PPARγ
No staining731.30.7–2.5 0.70.4–1.4 
Mild-to-moderate330.70.3–1.8 0.70.3–1.7 
Strong staining511 0.381 0.57
Missing
1
 
 
 
 
 
 
CXCL13/BCA1
No staining851.00.3–3.3 3.00.4–22.2 
Few lymphocytes stained571.00.3–3.3 3.30.4–24.5 
Numerous lymphocytes stained121 0.981 0.51
Missing4      

Abbreviations: CI=confidence interval; HR=hazard ratio.

Figure 2

Relapse-free survival according to CD57 (    

Table 3B

Multivariate analysis adjusted for anatomoclinical parameters (tumour location, stage, grade, and adjuvant chemotherapy) for patients without preop-RT (model based on 156 patients because of missing value for two patients)

 
 
Relapse-free survival
Overall survival
 nHR95% CIPHR95% CIP
CD57
CD57 ⩽2 cells per spot1002.71.3–5.7 2.31.1–4.8 
CD57 >2 cells per spot
56
1
 
0.011
1
 
0.026
CD68
CD68=0 cells per spot83.61.4–9.1 5.32.1–13.6 
1⩽ CD68 ⩽10 cells per spot551.20.6–2.3 1.60.9–3.0 
CD68 >10 cells per spot931 0.031 0.002

Abbreviations: CI=confidence interval; HR=hazard ratio.

Finally, we generated a prognostic score based on the combination of CD57+ (+, > vs −, ⩽2 cells per spot) and CD68+ (+, >0 vs −, =0 cells per spot) TIC densities. This three-category prognostic score discriminated CRC patients at low (CD68+, CD57+), intermediate (CD68+, CD57−), or high (CD68−, CD57−) risk, with HRs for the intermediate-risk and high-risk groups of 2.7 (95% CI: 1.3–5.8) and 9.0 (3.2–25.4) for RFS, and 2.5 (1.2–5.1) and 10.6 (3.8–29.2) for OS, respectively, as compared with the low-risk group. Corresponding 5-year survival rates in the low-, moderate-, and high-risk groups were 84% (71–91), 65% (54–74), and 12% (2–47), respectively, for RFS, and 91% (80–96), 76% (66–84), and 25% (7–59), respectively, for OS (Figure 3).
Figure 3

Relapse-free survival (    

Discussion

In the present study, we showed that tumour infiltration by CD57+ and CD68+ cells is an independent prognostic factor for RFS and OS in patients with pMMR CRC, regardless of disease stage (that is, stage II or III, Supplementary Table 3). Although CD3+ TIC density was also prognostic for RFS and OS in univariate analysis in accordance with other reports (Pages ), it was correlated with CD57+ TIC density and did not remain an independent prognostic factor after taking into account CD57+ TIC density in multivariate analysis. Unlike in previous studies (Pages ; Galon ), we used stringent patient eligibility criteria and methods for this study. First, only patients with stage II or III disease were included. In fact, additional prognostic biomarkers are mainly needed for such patients, as the vast majority of stage I CRC patients will never relapse after curative surgery while most stage IV CRC patients will die from their disease. Second, we excluded patients with dMMR CRC, as an increased number of TIL is a well-known pattern in dMMR CRC (Jass ; Laghi ). Third, we excluded patients who received preop-RT. As previously suggested by others, we showed here that preop-RT strongly influenced immune microenvironment. Indeed, radiation therapy may enhance tumour-associated antigen and major histocompatibility complex-I expressions, increase CD8+ and CD4+ tumour cell infiltration, and favour the antigen-capture by dendritic cells that may promote immunological recognition of tumour cells (Lugade ; Teitz-Tennenbaum ; Sharma ). Recent works have highlighted the immunological pathways involved in immunogenic cell death after irradiation of tumour in mice models. Irradiation may lead to calreticulin exposure at the cell surface of tumour cells, secretion of HMGB1 and ATP from tumour cells and IL-1β from antigen-presenting cells (APC) resulting in a better uptake of apoptotic bodies by APC and their maturation leading to an induction/amplification of specific tumour antigen IFNγ +CD8+ T cells at the tumour site (Apetoh ; Obeid ; Ghiringhelli ). Therefore, we excluded patients who received preop-RT from the analysis. Fourth, we showed that the stainings of all the immune markers we studied were significantly decreased in the centre of the tumour. This suggests that tumour microenvironment hampers immune cells to infiltrate deeply within the tumour. Furthermore, we only focused the analysis of the immune infiltrate in the centre of the tumour as our TMA did not target the invasive margin of the tumour samples. Therefore, we did not assess the peritumoural nor the crohn-like lymphocytic reactions, which have been shown to be associated with longer survival in CRC (Ogino , 2010). However, the cell counting may be more reproducible in the centre of the tumour, the invasive/peritumoural margin being potentially difficult to delineate reliably and thus difficult to incorporate in the daily practice. In addition, Galon and others (Sinicrope ; Ogino ) showed that CD3+ TIL density within the tumour was also prognostic of disease-free survival (DFS), although less significantly than in the combined region analysis (centre of the tumour and invasive margin) or than a score based on the overall lymphocytic reaction calculated as the sum of scores of Crohn's like lymphoid reaction, peritumoural lymphocytic reaction, and tumour-infiltrating lymphocytes (Ogino ). In the study by Laghi in which patient selection was closer to ours (i.e., Stage II and III without preop-RT), CD3+ TIL density was found to be prognostic only in stage II, but not in stage III CRC. In this study CD3 expression was analysed as a continuous variable at the tumour invasive margin on whole slides and CD57+ tumour cell infiltrate was not studied (Laghi ). Finally, Galon explored mainly CD3, CD8, and CD45RO and did not assessed CD57+ and CD68+ tumour cell infiltrate. We found that the complete absence of CD68+ TIC is characteristic of a small subset of patients with a very poor prognosis. Several reports showed an association between lower CD68+ TIC densities and worse outcome in patients with CRC (Forssell ; Algars ; Zhou ; Zlobec ). However, whether CD68 staining corresponds to activated type 1 macrophages or regulatory/suppressive type 2 macrophages, and what are the exact roles of these distinct cell populations in the tumour microenvironment (e.g., induction of regulatory T cells by type 2 macrophages) remain to be elucidated. We found that CD57 TIC density tended to be associated with that of CD3 (P=0.003, Table 2). Thus, these cells may represent a subpopulation of CD3+ T cells. However, the lack of correlation with CD4+ TIC density and the weak association with CD8+ TIC density (P=0.02, Table 2) suggest that these cells may not belong to the conventional T-cell family. Okada found abundant CD57+ TIC in CRC patients, the majority of which being CD4−, half CD8 +, and one third γδTCR+. Other investigators have reported that CD57+ cells were one of the major TIL, especially in patients with gastric carcinoma (Karimine ; Arinaga ). However, they did not examine whether or not such CD57+ cells express CD3 (or TCR). In other words, they considered these cells as NK cells rather than CD3+ T cells (Karimine ; Arinaga ). More recently, CD8+ and CD57+ T cells with cytotoxic functions were found in patients with multiple myeloma (Sze ). Higher numbers of CD57+ cells (mostly CD8+ T cells and NK cells) were associated with longer progression-free survival in patients with multiple myeloma treated with thalidomide (Mileshkin ). These CD57+ T cells are often associated with chronic antigenic stimulation and denominated as ‘highly antigen experienced CD8+ T cells' in patients with cancer, chronic stimulation by tumour antigens may be responsible for the differentiation of these T cells within the tumour (Strioga ). Of note, marked infiltration by CD57+ TIC at the advancing tumour margin was independently associated with longer DFS in one previous series of 93 CRC patients (Menon ). We found a strong association between CD57+ and CD68+ TIC densities. We built a strongly prognostic score based on these two immune markers, which allowed us to discriminate three groups of patients with stage II–III CRC harbouring very different risks of relapse and death. This suggests that CD57+ and CD68+ TIC may interact for their recruitment, reciprocal activation, and survival at the tumour site, favouring tumour clearance. However, our hypothesis warrants further investigations. Our study has several limitations: its retrospective design, the relative small numbers of CRC patients included before the use of modern chemotherapy, that is, FOLFOX regimen that became the standard of care for patients with stage III colon cancer (Andre ) as well as the unavailability of some established prognostic parameters in CRC patients (e.g., the refined TN substage and the number of examined nodes (AJCC, 2010)) that could not be included in our analyse. Considering the adjuvant treatment, we cannot exclude a potential interaction with such treatment and the immune system. However, there is no preclinical/clinical data supporting an immunogenic cell death induced by 5-FU. Conversely, oxaliplatin may influence anti-tumour immune responses as we showed previously (Tesniere ). Therefore, such interactions warrant further investigation in future prospective trials. Furthermore, and as discussed earlier, TMA is by itself less indicative than whole slides and can not account for potential heterogeneity in TIC density within the tumour. In conclusion, CD68+ and CD57+ TIC densities are independent prognostic biomarkers in stage II and III CRC, adding to the growing body of evidence for the influence of the host immune response on CRC outcome. If confirmed in other studies, our results may support the routine use of IHC assessment of both CD68+ and CD57+ TIC densities as a prognostic tool in patients with stage II–III CRC. Whether these markers may also predict the benefit of adjuvant treatment after primary surgery deserves to be assessed. Finally, our results argue for the potential therapeutic interest of immune modulators in CRC patients.
  47 in total

1.  Caspase-3 activity as a prognostic factor in colorectal carcinoma.

Authors:  L E Jonges; J F Nagelkerke; N G Ensink; E A van der Velde; R A Tollenaar; G J Fleuren; C J van de Velde; H Morreau; P J Kuppen
Journal:  Lab Invest       Date:  2001-05       Impact factor: 5.662

2.  Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer.

Authors:  R Gryfe; H Kim; E T Hsieh; M D Aronson; E J Holowaty; S B Bull; M Redston; S Gallinger
Journal:  N Engl J Med       Date:  2000-01-13       Impact factor: 91.245

3.  Counting alleles to predict recurrence of early-stage colorectal cancers.

Authors:  Wei Zhou; Steven N Goodman; Gennaro Galizia; Eva Lieto; Francesca Ferraraccio; Carlo Pignatelli; Colin A Purdie; Juan Piris; Robert Morris; David J Harrison; Philip B Paty; Al Culliford; Katharine E Romans; Elizabeth A Montgomery; Michael A Choti; Kenneth W Kinzler; Bert Vogelstein
Journal:  Lancet       Date:  2002-01-19       Impact factor: 79.321

4.  ColoGuideEx: a robust gene classifier specific for stage II colorectal cancer prognosis.

Authors:  Trude H Agesen; Anita Sveen; Marianne A Merok; Guro E Lind; Arild Nesbakken; Rolf I Skotheim; Ragnhild A Lothe
Journal:  Gut       Date:  2012-01-02       Impact factor: 23.059

5.  Cancer statistics, 2000.

Authors:  R T Greenlee; T Murray; S Bolden; P A Wingo
Journal:  CA Cancer J Clin       Date:  2000 Jan-Feb       Impact factor: 508.702

6.  Clonal cytotoxic T cells are expanded in myeloma and reside in the CD8(+)CD57(+)CD28(-) compartment.

Authors:  D M Sze; G Giesajtis; R D Brown; M Raitakari; J Gibson; J Ho; A G Baxter; B Fazekas de St Groth; A Basten; D E Joshua
Journal:  Blood       Date:  2001-11-01       Impact factor: 22.113

7.  Prognostic significance of CD8+ T cell and macrophage peritumoral infiltration in colorectal cancer.

Authors:  Yukihiro Funada; Tsuyoshi Noguchi; Ryuichi Kikuchi; Shinsuke Takeno; Yuzo Uchida; Helmut E Gabbert
Journal:  Oncol Rep       Date:  2003 Mar-Apr       Impact factor: 3.906

8.  Lymphokine-activated killer cell activity of peripheral blood, spleen, regional lymph node, and tumor infiltrating lymphocytes in gastric cancer patients.

Authors:  N Karimine; S Nanbara; S Arinaga; T Asoh; H Ueo; T Akiyoshi
Journal:  J Surg Oncol       Date:  1994-03       Impact factor: 3.454

9.  Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer.

Authors:  Thierry André; Corrado Boni; Lamia Mounedji-Boudiaf; Matilde Navarro; Josep Tabernero; Tamas Hickish; Clare Topham; Marta Zaninelli; Philip Clingan; John Bridgewater; Isabelle Tabah-Fisch; Aimery de Gramont
Journal:  N Engl J Med       Date:  2004-06-03       Impact factor: 91.245

10.  Immune system and prognosis in colorectal cancer: a detailed immunohistochemical analysis.

Authors:  Anand G Menon; Connie M Janssen-van Rhijn; Hans Morreau; Hein Putter; Rob A E M Tollenaar; Cornelis J H van de Velde; Gert Jan Fleuren; Peter J K Kuppen
Journal:  Lab Invest       Date:  2004-04       Impact factor: 5.662

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  23 in total

1.  High macrophage PD-L1 expression not responsible for T cell suppression.

Authors:  Naomi Goldman; Yelizavet D Lomakova; Jennifer Londregan; Amanda Bucknum; Kelley DePierri; John Somerville; James E Riggs
Journal:  Cell Immunol       Date:  2017-12-30       Impact factor: 4.868

2.  Cytotoxic T Cells and Granzyme B Associated with Improved Colorectal Cancer Survival in a Prospective Cohort of Older Women.

Authors:  Anna E Prizment; Robert A Vierkant; Thomas C Smyrk; Lori S Tillmans; Heather H Nelson; Charles F Lynch; Thomas Pengo; Stephen N Thibodeau; Timothy R Church; James R Cerhan; Kristin E Anderson; Paul J Limburg
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-12-15       Impact factor: 4.254

3.  Malignant peripheral nerve sheath tumor (MPNST) in the spine: a retrospective analysis of clinical and molecular prognostic factors.

Authors:  Ting Wang; Huabin Yin; Shuai Han; Xinhai Yang; Jing Wang; Quan Huang; Wangjun Yan; Wang Zhou; Jianru Xiao
Journal:  J Neurooncol       Date:  2015-01-20       Impact factor: 4.130

4.  Macrophage regulation of B cell proliferation.

Authors:  Naomi Goldman; Kornelija Valiuskyte; Jennifer Londregan; Adam Swider; John Somerville; James E Riggs
Journal:  Cell Immunol       Date:  2017-02-21       Impact factor: 4.868

5.  Identification of a Novel Immune Landscape Signature for Predicting Prognosis and Response of Colon Cancer to Immunotherapy.

Authors:  Zheng Wang; Jingru Song; Nisma Lena Bahaji Azami; Mingyu Sun
Journal:  Front Immunol       Date:  2022-04-28       Impact factor: 8.786

6.  Clinical and prognostic value of MET gene copy number gain and chromosome 7 polysomy in primary colorectal cancer patients.

Authors:  An Na Seo; Kyoung Un Park; Gheeyoung Choe; Woo Ho Kim; Duck-Woo Kim; Sung-Bum Kang; Hye Seung Lee
Journal:  Tumour Biol       Date:  2015-07-10

7.  Interactions between colon cancer cells and tumor-infiltrated macrophages depending on cancer cell-derived colony stimulating factor 1.

Authors:  Huayang Wang; Qianqian Shao; Jintang Sun; Chao Ma; Wenjuan Gao; Qingjie Wang; Lei Zhao; Xun Qu
Journal:  Oncoimmunology       Date:  2016-01-04       Impact factor: 8.110

Review 8.  Prognostic value and clinicopathological roles of phenotypes of tumour-associated macrophages in colorectal cancer.

Authors:  Yamei Zhao; Xiaoxu Ge; Xiaoming Xu; Shaojun Yu; Jian Wang; Lifeng Sun
Journal:  J Cancer Res Clin Oncol       Date:  2019-10-24       Impact factor: 4.553

9.  Itaconate and leptin affecting PPARγ in M2 macrophages: A potential link to early-onset colorectal cancer.

Authors:  Katharina M Scheurlen; Dylan L Snook; Mary N Walter; Cheyenne N Cook; Casey R Fiechter; Jianmin Pan; Robert J Beal; Susan Galandiuk
Journal:  Surgery       Date:  2021-12-06       Impact factor: 3.982

10.  The Prognostic Role of Macrophage Polarization in the Colorectal Cancer Microenvironment.

Authors:  Juha P Väyrynen; Koichiro Haruki; Mai Chan Lau; Sara A Väyrynen; Jeffrey A Meyerhardt; Marios Giannakis; Shuji Ogino; Jonathan A Nowak; Rong Zhong; Andressa Dias Costa; Jennifer Borowsky; Melissa Zhao; Kenji Fujiyoshi; Kota Arima; Tyler S Twombly; Junko Kishikawa; Simeng Gu; Saina Aminmozaffari; Shanshan Shi; Yoshifumi Baba; Naohiko Akimoto; Tomotaka Ugai; Annacarolina Da Silva; Jennifer L Guerriero; Mingyang Song; Kana Wu; Andrew T Chan; Reiko Nishihara; Charles S Fuchs
Journal:  Cancer Immunol Res       Date:  2020-10-06       Impact factor: 12.020

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