Literature DB >> 18941457

Prognostic implications of type and density of tumour-infiltrating lymphocytes in gastric cancer.

H E Lee1, S W Chae, Y J Lee, M A Kim, H S Lee, B L Lee, W H Kim.   

Abstract

The study aims to determine whether type and density of tumour-infiltrating lymphocytes (TILs) can predict the clinical course in gastric cancer. Gastric carcinomas (n=220) were immunostained for CD3, CD8, CD20, and CD45RO and evaluated for clinicopathologic characteristics. Number of TILs that immunostained positively for each marker were counted using NIH ImageJ software. Tumours were grouped into low- and high-density groups for each marker (CD3, CD8, CD45RO). The densities of CD3(+), CD8(+), and CD45RO(+) TILs were found to be independent predictors of lymph node metastasis by multivariate analysis with odds ratios (95% CI) of 0.425 (0.204-0.885), 0.325 (0.150-0.707), and 0.402 (0.190-0.850), respectively. Kaplan-Meier survival analysis revealed that patients in the high-density groups for CD3, CD8, and C45RO had a significantly longer survival time than the patients in the corresponding low-density groups, respectively. In multivariate survival analysis, the densities of CD3(+), CD8(+), and CD45RO(+) TILs remained independent prognostic factors with hazard ratios (95% CI) of 0.549 (0.317-0.951), 0.574 (0.347-0.949), and 0.507 (0.298-0.862), respectively. In conclusion, density of TILs was found to be independently predictive of regional lymph node metastasis and patient survival in gastric cancer.

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Year:  2008        PMID: 18941457      PMCID: PMC2584941          DOI: 10.1038/sj.bjc.6604738

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


Despite a decreasing trend in its incidence, gastric cancer remains one of the most frequent causes of cancer-related death worldwide; more than 930 000 new cases are diagnosed and 700 000 deaths occur each year (Parkin ). At present, surgical resection is considered the most reasonable procedure (Engstrom ; Coombes ), and tumour-node-metastasis (TNM) stage (by UICC/AJCC) assessed after resection is viewed as the prognostic factor that is most strongly associated with patient survival. However, it is not rare that gastric cancer patients with the same TNM stage pursue different clinical courses. Histopathologic classifications including WHO classification (Fenoglio-Preiser ), Lauren's classification (Lauren, 1965), Ming's classification (Ming, 1977), and Goseki classification (Goseki ) and molecular classifications (Hippo ; Chen ) have also been applied for the prediction of patient survival, but their prognostic accuracies are controversial (Lewin and Appleman, 1996; Fenoglio-Preiser ). In addition, many attempts have been made to link molecular events in cancer cells with patient outcome, but none of these have been accepted to be clinically meaningful. In consequence, new prognostic determinants in conjunction with the TNM stage are required to predict patients' clinical course more reliably and precisely. As the cancer immunosurveillance hypothesis was first proposed, the concept that the immune system can recognise and eliminate tumour cells has been energetically debated. Many experimental rodent studies on transgenic and knockout mice, and on monoclonal antibodies specific for distinct immunologic components have provided substantial evidence for the existence of cancer immunosurveillance, and in particular, have shown that the immune system indeed functions to protect murine hosts against development of both chemically induced and spontaneous tumours (Dunn ). Moreover, in humans, epidemiologic data indicate that immunocompromised patients have a higher probability of developing cancers of both viral and non-viral origin, which supports the cancer immunosurveillance concept (Dunn ). In addition, an accumulating evidence shows a positive correlation between the presence of lymphocytes in tumour tissue and increased patient survival. Recent studies have shown that several types of tumour-infiltrating lymphocytes (TIL) are associated with better disease outcome for various human cancers, including melanoma (Clemente ; Taylor ) and colorectal (Pages ; Galon ), ovarian (Zhang ), cervical (Piersma ), hepatocellular (Gao ), and urothelial (Sharma ) carcinoma. These reports demonstrate that high numbers of CD3+, CD8+, or CD45RO+ T cells in tumour tissue are significantly correlated with lower frequencies of lymph node metastasis or disease recurrence, or longer patient survival. Moreover, Galon advocated that the type, density, and location of immune cells in colorectal cancer have prognostic values that are superior to and independent of those of the TNM classification . However, the effect of TILs on the clinical course of gastric cancer patients is largely unknown. The aim of this study was to assess the prognostic role of TILs in gastric cancer. Here, we determined whether type and density of TILs can predict the regional lymph node metastasis and patient survival in gastric cancer.

Materials and methods

Patients and specimens

The files of 274 surgically resected consecutive gastric carcinoma cases examined at the Department of Pathology, Seoul National University Hospital between January and June 1995 were obtained to quantify TILs by immunohistochemistry using a tissue array method. Cases with cancer confined to mucosa were excluded because they have an excellent prognosis regardless of TIL status. Finally 220 tumour tissue samples were included in the analysis. Age, sex, histologic type (according to Lauren and WHO classifications), lymphatic invasion, and pTNM (pathologic TNM) stage were evaluated by reviewing medical records or the glass slides. Patient clinical outcomes were followed from the date of surgery until either the date of death or 31 December 2003, which resulted in a follow-up period that ranged from 1 to 108 months (mean, 64.4 months). The data of patients lost to follow-up and of those who died from a cause other than gastric cancer were regarded as censored during the survival analysis. No patient had received preoperative chemotherapy, and patients with stage II, III, and IV had received postoperative chemotherapy using fluorouracil (5-FU) -based regimen (5-FU alone, 5-FU plus mitomycin C, or 5-FU plus cisplatin). No patient had received pre or postoperative radiotherapy. This study was approved by the Institutional Review Board for Human Subject Research at Seoul National University Hospital.

Tissue array method

Core tissue biopsies (2 mm in diameter) were taken from individual paraffin-embedded gastric carcinomas (donor blocks) and re-arranged in a new recipient paraffin block (tissue array block) using a trephine apparatus (Superbiochips Laboratories, Seoul, Korea). Six array blocks containing a total of 274 cases were prepared. As it has been shown that excellent staining result agreements are obtained for different intratumoral areas of gastric carcinomas (Lee ), a core was sampled from each of the cases. Each paraffin block contained internal controls consisting of non-neoplastic gastric mucosa from the body, antrum, and intestinal metaplasia. Sections (4 μm) were taken from each tissue array block, deparaffinised, and dehydrated.

Immunohistochemistry

Formalin-fixed and paraffin-embedded sections were dewaxed in xylene, rehydrated through graded alcohol, and placed in an endogenous peroxide block for 15 min. Antigen retrieval was done using a microwave in 10 mM citrate buffer or using an autoclave in Borg solution (Biocare Medical, Walnut Creek, CA, USA). Non-specific staining was blocked by treating sections with 1% horse serum in Tris-buffered saline (pH 6.0) for 3 min. Anti-CD3 (total T-cell marker; microwave; 1 : 100; rabbit polyclonal; DAKO, Glostrup, Denmark), -CD8 (cytotoxic T-cell marker; autoclave in Borg solution; 1 : 100; Rabbit monoclonal, SP16; Neomarkers, Fremont, CA, USA), -CD20 (total B cell marker; microwave; 1 : 300; Mouse monoclonal, L26; DAKO), and -CD45RO (memory T-cell marker; microwave; 1 : 100; Mouse monoclonal, OPD4; Neomarkers) antibodies were then applied, and antibody binding was detected using an avidin–biotin–peroxidase complex (Universal Elite ABC Kit; Vectastain, Burlingame, CA, USA) for 10 min. Diaminobenzidine tetrahydrochloride solution (Kit HK153-5K; Biogenex, San Ramon, CA, USA) was then used as a chromogen.

Quantitative analysis of TILs

Immunostained slides were scanned with a digital virtual microscope (dotSlide, Olympus, Hamburg, Germany), and a portion (area of 0.44 mm2 of tumour centre) of the virtual images was captured using an image viewer programme (OlyVIA, downloaded from http://www.olysia.co.kr/olyvia2992.zip) per case. The captured images were 1263 × 932 pixel in size and had a resolution of 1.633 pixel μm−1 at a magnification of × 100. Numbers of positively immunostained cells per in the 0.44 mm2 target areas were counted using NIH imageJ software with a Java-based colour deconvolution plugin (http://rsb.info.nih.gov/ij).

Statistical analysis

Comparisons between groups were performed using the Pearson's χ2 test or Fisher's exact (2-sided) test. Multivariate logistic regression was used to identify clinical and pathologic features predictive of regional lymph node metastases. Survival curves were estimated using the Kaplan–Meier product-limit method, and the significances of differences between survival curves were determined using the log-rank test. Multivariate comparisons of survival distributions were made using Cox proportional hazards models. All statistical analyses were conducted using SPSS 15.0 (SPSS, Chicago, IL, USA), and P-values of ⩽0.05 were considered statistically significant.

Two-fold cross-validation approach

To dichotomise prognostic variables, CD3, CD8, and CD45RO, a two-fold cross-validation methodology and a minimum P-value approach (Mazumdar ) were used. The dataset was randomly divided into two subsets. The inner 70% of the distribution from a marker was chosen as a selection interval of an optimal cutoff value. Stratified univariate and multivariate tests (logistic regression and Cox proportional hazards model) were performed for significance of prognostic variables.

Results

Density of TILs

Tumour-infiltrating lymphocytes were detected within cancer epithelium or in stroma except for CD20+ TILs, which were mostly present in stroma (Figure 1). Mean numbers of CD3+, CD8+, CD45RO+, and CD20+ TILs per area of 0.44 mm2 were 353.87±381.55, 191.72±265.69, 76.13±138.30, and 89.42±152.45, respectively. Numbers of CD3+, CD8+, and CD45RO+ TILs were correlated with each other (range of correlation coefficients, 0.739–0.868; P<0.001), and numbers of CD20+ TIL were positively correlated with those of other TIL subtypes, but correlation coefficients were relatively low (range, 0.527–0.641; P<0.001). First, using mean number, all cases were classified into low- and high-density groups for each marker, that is, CD3L, CD8L, and CD45ROL (low-density groups) and CD3H, CD8H, and CD45ROH (high-density groups) (Table 1). Also, each 75th percentile in the distributions of the TIL numbers in ascending order were determined as cutoffs (75th percentile cutoffs) for dichotomisation of the variables, that is, 75th percentile or a percentile less than 75 were considered as low-density groups and a percentile greater than 75 as high-density groups for each marker. Each 75th percentile was 452, 191, and 92 per area of 0.44 mm2, for CD3+, CD8+, and CD45RO+ TILs, respectively. We also grouped cases using combined variables, that is, as high or low for CD3+CD8, CD3+CD45RO, CD8+CD45RO, and CD3+CD8+CD45RO (refer to Table 1 for a complete list). We then compared groups dichotomised about means and about 75th percentile cutoffs. Because comparisons of the high- and low-density groups of CD20+, TIL using various cutoffs failed to show any significant difference in terms of clinicopathologic characteristics or survival, no detailed data on CD20+ TIL is presented.
Figure 1

Types of tumour-infiltrating lymphocytes. CD3 (A), CD8 (B), CD45RO (C), and CD20 (D) expressing cells were detected immunohistochemically. They are tumour-infiltrating total T cells, cytotoxic T cells, memory T cells, and B cells, respectively (original magnification, × 100).

Table 1

Classification of the gastric cancers according to TIL density

Variables Mean value cutoff (cases, N) 75th percentile cutoff (cases, N)
CD3L/CD3H142/78165/55
CD8L/CD8H164/56164/56
CD45ROL/CD45ROH155/65165/55
   
Combination of variables
 CD3LCD8 L/CD3CD8Het/CD3HCD8H135/36/49150/29/41
 CD3LCD45ROL/CD3CD45ROHet/CD3HCD45ROH131/35/54148/34/38
 CD8LCD45ROL/CD8CD45ROHet/CD8HCD45ROH140/39/41146/37/37
 CD3LCD8LCD45ROL/ CD3CD8CD45ROHet/CD3HCD8HCD45ROH125/55/40138/50/32

H=high density group; Het=mixture of low and high density group for different markers; L=low density group.

Correlation between TIL density and clinicopathologic characteristics

In a total of 220 gastric cancer patients, median age was 57 years (range, 18–80 years), and 70.9%. were male. The clinical and pathological characteristics of the cases grouped by TIL density with mean value cutoffs are summarised in Table 2. TIL density showed no correlation with either tumour invasion depth or the presence of lymphatic invasion, but it was found to be significantly associated with the presence of regional lymph node metastasis; CD3H, CD8H, and CD45ROH groups showed a lower frequency of lymph node metastasis than the corresponding low-density groups. Considering this observation, we assumed that TIL density would predict lymph node metastasis in gastric cancer.
Table 2

Correlation between TIL density and clinicopathologic characteristics in the 220 gastric cancers

  CD3+ TIL
CD8+ TIL
CD45RO+ TIL
Characteristics Low High P-value* Low High P-value* Low High P-value*
Age (years)   0.026  0.250  0.167
 <6610869 12948 12156 
 ⩾66349 358 349 
          
Gender   0.023  0.109  0.315
 Male10848 12135 11343 
 Female3430 4321 4222 
          
WHO classification   0.148  0.008  0.118
 WD93 111 93 
 MD5023 5815 5320 
 PD5844 6537 6537 
 Mucinous91 91 100 
 SRC167 212 185 
          
Lymphatic invasion   0.143  0.590  0.446
 Absent8856 10935 9945 
 Present5422 5521 5620 
          
Tumour stage   0.095  0.924  0.366
 T1/29862 11941 11050 
 T3/44416 4515 4515 
          
LN metastasis   <0.001  0.012  <0.001
 Absent2431 3421 2827 
 Present11847 13035 12738 
          
TNM stage   0.001  0.250  0.018
 I3235 4423 3829 
 II3221 4112 3815 
 III4411 4411 4510 
 IV3411 3510 3411 

LN=lymph node; MD=moderately differentiated tubular adenocarcinoma; Mucinous=mucinous adenocarcinoma; PD=poorly differentiated tubular adenocarcinoma; SRC=signet-ring cell carcinoma; WD=well differentiated tubular adenocarcinoma.

The results were according to the density groups of TIL with mean value cutoffs.

*χ2 test was used as a statistical method.

TIL as a predictor of regional lymph node metastasis

According to univariate logistic regression model, an advanced T stage, the presence of lymphatic invasion, and low densities of CD3+, CD8+, or CD45RO+ TILs were significantly associated with presence of regional lymph node metastasis regardless of the grouping method (mean value cutoff or 75th percentile cutoff). Low-density groups by combination of variables also showed significant relationships with the presence of lymph node metastasis. Multivariate logistic regression analysis, after adjusting for tumour invasion (T stage) and lymphatic invasion, demonstrated that densities of CD3+, CD8+, and CD45RO+ TILs were independent predictors of lymph node metastasis. As expected, combined analysis of variables showed similar results (Tables 3 and 4).
Table 3

Univariate and multivariate logistic regression models for predictors of regional lymph node metastasis (results from mean value cutoffs)

  Univariate analysis
Multivariate analysis a
Variables OR 95% CI P-value OR 95% CI P-value
CD3b0.3080.164–0.580<0.0010.3500.175–0.7010.003
CD8b0.4360.225–0.8430.0140.3250.150–0.7070.005
CD45ROb0.3100.163–0.589<0.0010.3020.147–0.6220.001
CD3CD8c0.3070.148–0.6400.0020.2770.122–0.6320.002
CD3CD45ROc0.2340.116–0.473<0.0010.2360.107–0.523<0.001
CD8CD45ROc0.2920.136–0.6250.0020.2600.111–0.6080.002
CD3CD8CD45ROd0.2580.117–0.5670.0010.2570.108–0.6140.028

CI=confidence interval; OR=odds ratio.

The results were according to the density groups of TIL with mean value cutoffs.

Univariate and multivariate logistic regression models were used as statistical methods.

Tumour invasion (T stage) and presence of lymphatic invasion were adopted as covariates in each multivariate analysis.

high vs low.

high/high vs low/low.

high/high/high vs low/low/low.

Table 4

Univariate and multivariate logistic regression models for predictors of regional lymph node metastasis (results from 75th percentile cutoffs)

  Univariate analysis
Multivariate analysis a
Variables OR 95% CI P-value OR 95% CI P-value
CD3b0.3750.194–0.7260.0040.4250.204–0.8850.022
CD8b0.4360.225–0.8430.0140.3250.150–0.7070.005
CD45ROb0.4200.217–0.8150.0100.4020.190–0.8500.017
CD3CD8c0.3380.161–0.7100.0040.3180.138–0.7340.007
CD3CD45ROc0.3210.149–0.6890.0040.3370.143–0.7930.013
CD8CD45ROc0.4000.180–0.8880.0240.3540.146–0.8600.022
CD3CD8CD45ROd0.3690.160–0.8510.0190.3970.160–0.9880.047

CI=confidence interval; OR=odds ratio.

The results were according to the density groups of TIL with 75th percentile cutoffs.

Univariate and multivariate logistic regression models were used as statistical methods.

Tumour invasion (T stage) and presence of lymphatic invasion were adopted as covariates in each multivariate analysis.

High vs low.

High/high vs low/low.

High/high/high vs low/low/low.

TIL as a predictor of patient survival

Significant advantages for overall survival were found for the CD3H, CD8H, and CD45ROH groups and for the high-density groups of combined TIL variables (refer to Table 1) according to 75th percentile cutoffs by Kaplan–Meier survival analysis (Figure 2). The analysis with variables according to mean value cutoffs showed similar results (data not shown). CD3H, CD8H, and CD45ROH groups had mean survival times of 85.1±5.2, 81.0±5.3, and 83.1±5.3 months, respectively, as compared with only 63.0±3.5, 64.3±3.5, and 63.7±3.5 months in the corresponding low-density groups. Thus, the density of various TILs seems to be useful for defining a subgroup with unfavourable prognosis in gastric cancer.
Figure 2

Kaplan–Meier survival plots for the 220 gastric cancer patients as a function of TIL density. (A) Significant differences in overall survival were found between the low- and high-density groups of CD3, CD8, and CD45RO, by the log-rank tests. (B, C) Survival differences were consistently found when analysing with diverse combined TIL variables (refer to Table 1).

Univariate Cox regression analysis for the prediction of overall survival also confirmed that the CD3H, CD8H, and CD45ROH groups and the high-density groups of combined TIL variables had better survival than the corresponding low-density groups regardless of the grouping method (mean value cutoff or 75th percentile cutoff). In addition, densities of CD3+, CD8+ and CD45RO+ TILs and the combined TIL densities remained significant predictors of overall survival by multivariate Cox proportional hazard analysis, even after controlling for T stage, histologic classification (WHO), presence of lymph node metastasis, and presence of lymphatic invasion, which were all found to be of prognostic significance by univariate analysis (Tables 5 and 6).
Table 5

Univariate and multivariate cox proportional hazards models for the predictors of overall survival (results from mean value cutoffs)

  Univariate analysis
Multivariate analysis a
Variables HR 95% CI P-value HR 95% CI P-value
CD3b0.6270.410–0.6270.0310.8130.523–1.2640.358
CD8b0.5830.358–0.9500.0300.5740.347–0.9490.031
CD45ROb0.5300.331–0.8500.0080.6120.377–0.9950.048
CD3CD8c0.5220.303–0.9000.0190.5720.325–1.0100.054
CD3CD45ROc0.4410.252–0.7720.0040.5650.317–1.0090.054
CD8CD45ROc0.4160.221–0.7850.0070.4360.227–0.8380.013
CD3CD8CD45ROd0.3930.202–0.7660.0060.4710.236–0.9370.032

CI=confidence interval; HR=hazard ratio.

The results were according to the density groups of TIL with mean value cutoffs.

Univariate and multivariate Cox proportional hazards models were used as statistical methods.

Tumour stage (T stage), histologic classification (WHO), presence of lymph node metastasis, and presence of lymphatic invasion which were proved to have a prognostic significance in univariate analysis were adopted as covariates in each multivariate analysis.

High vs low.

High/high vs low/low.

High/high/high vs low/low/low.

Table 6

Univariate and multivariate cox proportional hazard models for the predictors of overall survival (results from 75th percentile cutoffs)

  Univariate analysis
Multivariate analysis a
Variables HR 95% CI P-value HR 95% CI P-value
CD3b0.4460.261–0.7600.0030.5490.317–0.9510.032
CD8b0.5830.358–0.9500.0300.5740.347–0.9490.031
CD45ROb0.4830.287–0.8130.0060.5070.298–0.8620.012
CD3CD8c0.3730.193–0.7210.0030.4030.205–0.7950.009
CD3CD45ROc0.3050.147–0.6320.0010.3370.161–0.7080.004
CD8CD45ROc0.4180.216–0.8090.0100.4130.211–0.8120.010
CD3CD8CD45ROd0.2710.118–0.6240.0020.2820.121–0.6580.003

CI=confidence interval; HR=hazard ratio.

The results were according to the density groups of TIL with 75th percentile cutoffs.

Univariate and multivariate Cox proportional hazards models were used as statistical methods.

Tumour stage (T stage), histologic classification (WHO), presence of lymph node metastasis, and presence of lymphatic invasion which were proved to have prognostic significance in univariate analysis were adopted as covariates in each multivariate analysis.

High vs low.

High/high vs low/low.

High/high/high vs low/low/low.

For further validation of our results, we performed a two-fold cross-validation approach. In analyses using this approach, univariate and multivariate logistic regression analyses confirmed that densities of CD3+, CD8+, and CD45RO+ TILs were independent predictors of regional lymph node metastasis (Table 7). In univariate Cox regression analysis, CD3H, CD8H, and CD45ROH groups were proved to have longer survival time than the corresponding low-density groups (Table 8). In multivariate Cox regression analysis, CD45RO+ TIL density remained a statistically significant predictor of overall survival, and CD8+ TIL density was associated with overall survival marginally, but CD3+ TlL density did not remain a significant predictor (Table 8).
Table 7

Univariate and multivariate logistic regression models for predictors of regional lymph node metastasis (results from two-fold cross-validation approach)

  Univariate analysis
Multivariate analysis a
Variables OR 95% CI P-value OR 95% CI P-value
CD3b0.420.211–0.8180.0110.450.213–0.9350.033
CD8b0.320.158–0.6300.0010.340.162–0.7230.005
CD45ROb0.290.153–0.554<0.0010.270.128–0.554<0.001
CD3CD8c0.280.124–0.6140.0010.310.128–0.7290.003
CD3CD45ROc0.260.123–0.527<0.0010.250.108–0.563<0.001
CD8CD45ROc0.210.097–0.4590.0010.200.085–0.4790.001
CD3CD8CD45ROd0.200.083–0.463<0.0010.200.077–0.518<0.001

CI=confidence interval; OR=odds ratio.

Univariate and multivariate logistic regression models were used as statistical methods.

Tumour invasion (T stage) and presence of lymphatic invasion were adopted as covariates in each multivariate analysis.

high vs low.

high/high vs low/low.

high/high/high vs low/low/low.

Table 8

Univariate and multivariate cox proportional hazards models for the predictors of overall survival (results from two-fold cross-validation approach)

  Univariate analysis
Multivariate analysis a
Variables HR 95% CI P-value HR 95% CI P-value
CD3b0.570.343–0.9350.0260.670.404–1.1230.130
CD8b0.590.374–0.9380.0260.640.408–1.0030.052
CD45ROb0.300.151–0.5940.0010.420.209–0.8430.015
CD3CD8c0.490.288–0.8370.0090.560.324–0.9640.037
CD3CD45ROc0.340.162–0.6910.0030.440.211–0.9230.030
CD8CD45ROc0.280.134–0.5920.0010.360.170–0.7680.008
CD3CD8CD45ROd0.310.148–0.6560.0020.390.185–0.8360.015

CI=confidence interval; HR=hazard ratio.

Univariate and multivariate Cox proportional hazard models were used as statistical methods.

Tumour stage (T stage), histologic classification (WHO), presence of lymph node metastasis, and presence of lymphatic invasion which were proved to have prognostic significance in univariate analysis were adopted as covariates in each multivariate analysis.

high vs low.

high/high vs low/low.

high/high/high vs low/low/low.

Discussion

The present study demonstrates that the type and density of TILs correlate with the clinical outcome after gastrectomy in gastric cancer. TIL was found to be an independent predictor of lymph node metastasis and an independent prognostic factor of patients' overall survival by multivariate analyses. In addition, we evaluated an effect of TIL density on survival at each stage of TNM classification. Overall survival of patients with a high TIL density tended to be longer than that of patients with a low TIL density within the same TNM stage, although differences were not statistically significant due to small numbers of cases enrolled in each stage (Figure 3). This finding suggests that the diversity of clinical outcomes shown by gastric cancer patients with the same TNM stage is due in part to differences in TIL density, which underlines the importance of TIL as a predictor of clinical outcome.
Figure 3

Kaplan–Meier survival analysis of TIL densities at different stages of the TNM classification (log-rank tests). High TIL density tended to be associated with longer overall survival within a given TNM stage. The results were from 75th percentile cutoffs.

In this study, cases were classified into low or high TIL density groups using mean number or 75th percentile cutoffs, and the results were consistent regardless of the grouping method used. In addition, analyses using two-fold cross-validation approach strengthened our results, although it failed to show that CD3+ TIL density was an independent predictor of overall survival. Nevertheless, the counting method using image analysis software and the classification system used in this study would be difficult to use clinically. Thus, we suggest that a standard method be devised to measure TIL densities for clinical applications. Recent studies on colorectal cancer have demonstrated that a high density of CD45RO+ TIL is correlated with the absence of lymphovascular invasion and with increased survival (Pages ), and further that the densities of CD3+, CD8+, and CD45RO+ TILs are independent prognostic factors (Galon ). In a study on ovarian cancer, it was found that the presence of intratumoral T cells was associated with improved clinical outcome (Zhang ). Previous reports also show that hepatocellular and urothelial carcinoma patients with high numbers of CD8+ TIL within tumour tissues have better survival (Gao ; Sharma ). In terms of lymph node metastasis, Taylor reported that brisk TIL infiltration in tumour predicts sentinel lymph node metastasis in melanoma patients, and Piersma demonstrated that a high number of intraepithelial CD8+ TIL is associated with the absence of lymph node metastasis in uterine cervical cancer. However, the prognostic role of tumour-infiltrating immune cells in patients of gastric cancer is largely unknown. Only a few reports have been issued on the association between tumour-infiltrating immune cells and the clinical outcome in gastric cancer; Ishigami reported that patients showing a high level of natural killer cell infiltration in tumour tissues have a better prognosis, and Maehara showed that a high density of dendritic cell infiltration is associated with the absence of lymph node metastasis. Ichihara reported that the population of regulatory T cells among the TILs of patients with advanced disease (n=8) is significantly higher than that among the TILs of patients with early disease (n=7). On the other hand, Fukuda found no significant difference in survival between patients with marked or slight TIL infiltration, which does not agree with our findings. However, they detected TILs by UCLH-1 immunostaining in 129 gastric cancer patients, classified cases into groups with marked or slight TIL infiltration, and did not determine TIL numbers. In this study of a large series of gastric cancers, we counted the number of tumour-infiltrating total T cells, cytotoxic T cells, memory T cells, and B cells using an image analyser, and for the first time demonstrated the prognostic importance of TIL in gastric cancer. T-cell mediated adaptive immunity is considered to play a major role in anti-tumour immunity. In mouse models, it has been demonstrated that adaptive immunity prevents the development of tumours and inhibit tumour progression (Dunn ). Consistent with these results, our findings show that high densities of immune cells related to adaptive immunity, that is, total T cells, cytotoxic T cells, and memory T cells, are associated with favourable survival, and indicate that adaptive immunity plays a role in the prevention of tumour progression. On the other hand, tumour-infiltrating B cells are found not to have impact on patient survival in this study. Previous reports have concluded that B lymphocytes and humoral immunity are associated with tumour progression (de Visser ; Sabbatini and Odunsi, 2007), which is not contradicted by our findings. According to our results, TIL density is correlated with the presence of lymph node metastasis but not with depth of tumour invasion. On the basis of this finding, we suspect that the prognostic role of TIL is mainly contributed to decreased metastatic potential. We suggest the following possible mechanisms how TIL act to reduce metastatic potential. First, clones with metastatic potential usually contain larger amounts of aberrantly expressed proteins, including proteins that contribute to metastasis, which may act as tumour-associated antigens. As a result, these clones are more likely to be destroyed by in situ immune reactions. Second, a high density of TIL means a healthy immune system, and therefore, immune reaction occurring in lymph node may also exert a proper function against tumour cells that have drained into lymph nodes in patients with high TIL densities. Third, tumour burden of metastatic foci in lymph node is less bulky than those of primary foci, and thus, metastatic foci are more likely to be susceptible to complete destruction by immune reaction. In this study, we evaluated TIL distributions immunohistochemically, and although the majority of previous reports have also used this method, it has some limitations. First, the results obtained are dependent on the antibodies used. Second, various components of immune system such as interferon-γ (IFN-γ), IFN-γ receptor, transcription factor signal transducers and activators of transcription 1 (STAT1), perforin, and interleukins which can affect in situ immune reaction against tumour, and therefore, impact on patients' survival were not considered. Thus, additional studies are required to elucidate the expressional status of immune-related genes in tumour tissues. Significant advances have been made in the field of cancer immunotherapy over the last decade, and many nonrandomised, phase II, immune-targeted trials have shown that immunotherapy can confer survival benefits, although these benefits were not confirmed in phase III trials (Rosenberg ; Sabbatini and Odunsi, 2007). In gastric cancer, immunotherapy has not been shown to confer a survival benefit, although a clinical trial on postoperative adjuvant immunochemotherapy is currently in progress in Japan (Ueda ). It is hoped that the observations made during this study will provide crucial information concerning the design of effective immunotherapies, and aid the identification of patients suitable for immunotherapy. In conclusion, we elucidated the prognostic implications of the density of various types of TIL in gastric cancer. Moreover, our results suggest that adaptive immunity does act to prevent tumour progression. We believe that our findings can help predict clinical outcome and define patient subgroups with an unfavourable prognosis in gastric cancer. Furthermore, our observation will be useful for selecting patients that are more likely to benefit from the promising adjuvant immunotherapy.
  27 in total

1.  Global gene expression analysis of gastric cancer by oligonucleotide microarrays.

Authors:  Yoshitaka Hippo; Hirokazu Taniguchi; Shuichi Tsutsumi; Naoko Machida; Ja-Mun Chong; Masashi Fukayama; Tatsuhiko Kodama; Hiroyuki Aburatani
Journal:  Cancer Res       Date:  2002-01-01       Impact factor: 12.701

2.  Methods for categorizing a prognostic variable in a multivariable setting.

Authors:  Madhu Mazumdar; Alex Smith; Jennifer Bacik
Journal:  Stat Med       Date:  2003-02-28       Impact factor: 2.373

3.  Gastric carcinoma. A pathobiological classification.

Authors:  S C Ming
Journal:  Cancer       Date:  1977-06       Impact factor: 6.860

4.  Prognostic value of intratumoral natural killer cells in gastric carcinoma.

Authors:  S Ishigami; S Natsugoe; K Tokuda; A Nakajo; X Che; H Iwashige; K Aridome; S Hokita; T Aikou
Journal:  Cancer       Date:  2000-02-01       Impact factor: 6.860

5.  Increased populations of regulatory T cells in peripheral blood and tumor-infiltrating lymphocytes in patients with gastric and esophageal cancers.

Authors:  Fumiko Ichihara; Koji Kono; Akihiro Takahashi; Hiromichi Kawaida; Hidemitsu Sugai; Hideki Fujii
Journal:  Clin Cancer Res       Date:  2003-10-01       Impact factor: 12.531

6.  Cancer immunotherapy: moving beyond current vaccines.

Authors:  Steven A Rosenberg; James C Yang; Nicholas P Restifo
Journal:  Nat Med       Date:  2004-09       Impact factor: 53.440

7.  The expression of RCAS1 and tumor infiltrating lymphocytes in patients with T3 gastric carcinoma.

Authors:  Kenji Fukuda; Shunichi Tsujitani; Yoshihiko Maeta; Kenichi Yamaguchi; Masahide Ikeguchi; Nobuaki Kaibara
Journal:  Gastric Cancer       Date:  2002       Impact factor: 7.370

Review 8.  Immunologic approaches to ovarian cancer treatment.

Authors:  Paul Sabbatini; Kunle Odunsi
Journal:  J Clin Oncol       Date:  2007-07-10       Impact factor: 44.544

9.  Intratumoral T cells, recurrence, and survival in epithelial ovarian cancer.

Authors:  Lin Zhang; Jose R Conejo-Garcia; Dionyssios Katsaros; Phyllis A Gimotty; Marco Massobrio; Giorgia Regnani; Antonis Makrigiannakis; Heidi Gray; Katia Schlienger; Michael N Liebman; Stephen C Rubin; George Coukos
Journal:  N Engl J Med       Date:  2003-01-16       Impact factor: 91.245

Review 10.  The three Es of cancer immunoediting.

Authors:  Gavin P Dunn; Lloyd J Old; Robert D Schreiber
Journal:  Annu Rev Immunol       Date:  2004       Impact factor: 28.527

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  137 in total

Review 1.  Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors.

Authors:  Shona Hendry; Roberto Salgado; Thomas Gevaert; Prudence A Russell; Tom John; Bibhusal Thapa; Michael Christie; Koen van de Vijver; M V Estrada; Paula I Gonzalez-Ericsson; Melinda Sanders; Benjamin Solomon; Cinzia Solinas; Gert G G M Van den Eynden; Yves Allory; Matthias Preusser; Johannes Hainfellner; Giancarlo Pruneri; Andrea Vingiani; Sandra Demaria; Fraser Symmans; Paolo Nuciforo; Laura Comerma; E A Thompson; Sunil Lakhani; Seong-Rim Kim; Stuart Schnitt; Cecile Colpaert; Christos Sotiriou; Stefan J Scherer; Michail Ignatiadis; Sunil Badve; Robert H Pierce; Giuseppe Viale; Nicolas Sirtaine; Frederique Penault-Llorca; Tomohagu Sugie; Susan Fineberg; Soonmyung Paik; Ashok Srinivasan; Andrea Richardson; Yihong Wang; Ewa Chmielik; Jane Brock; Douglas B Johnson; Justin Balko; Stephan Wienert; Veerle Bossuyt; Stefan Michiels; Nils Ternes; Nicole Burchardi; Stephen J Luen; Peter Savas; Frederick Klauschen; Peter H Watson; Brad H Nelson; Carmen Criscitiello; Sandra O'Toole; Denis Larsimont; Roland de Wind; Giuseppe Curigliano; Fabrice André; Magali Lacroix-Triki; Mark van de Vijver; Federico Rojo; Giuseppe Floris; Shahinaz Bedri; Joseph Sparano; David Rimm; Torsten Nielsen; Zuzana Kos; Stephen Hewitt; Baljit Singh; Gelareh Farshid; Sibylle Loibl; Kimberly H Allison; Nadine Tung; Sylvia Adams; Karen Willard-Gallo; Hugo M Horlings; Leena Gandhi; Andre Moreira; Fred Hirsch; Maria V Dieci; Maria Urbanowicz; Iva Brcic; Konstanty Korski; Fabien Gaire; Hartmut Koeppen; Amy Lo; Jennifer Giltnane; Marlon C Rebelatto; Keith E Steele; Jiping Zha; Kenneth Emancipator; Jonathan W Juco; Carsten Denkert; Jorge Reis-Filho; Sherene Loi; Stephen B Fox
Journal:  Adv Anat Pathol       Date:  2017-11       Impact factor: 3.875

Review 2.  Role of prostanoids in gastrointestinal cancer.

Authors:  Dingzhi Wang; Raymond N DuBois
Journal:  J Clin Invest       Date:  2018-05-07       Impact factor: 14.808

3.  Adiponectin receptors are downregulated in human gastric cancer.

Authors:  Kensuke Otani; Joji Kitayama; Takao Kamei; Daisuke Soma; Hideyo Miyato; Toshimasa Yamauchi; Takashi Kadowaki; Hirokazu Nagawa
Journal:  J Gastroenterol       Date:  2010-03-25       Impact factor: 7.527

4.  Clinicopathologic features of early gastric carcinoma with lymphoid stroma and feasibility of endoscopic submucosal dissection.

Authors:  Dong Hun Shin; Gwang Ha Kim; Bong Eun Lee; Jong Wook Lee; Dong Woo Ha; Hye Kyung Jeon; Dong Hoon Baek; Geun Am Song; Sang Jeong Ahn; Do Youn Park
Journal:  Surg Endosc       Date:  2017-04-13       Impact factor: 4.584

5.  Infiltrating and peripheral immune cell analysis in advanced gastric cancer according to the Lauren classification and its prognostic significance.

Authors:  Simon Pernot; Magali Terme; Nina Radosevic-Robin; Florence Castan; Cécile Badoual; Elie Marcheteau; Fréderique Penault-Llorca; Olivier Bouche; Jaafar Bennouna; Eric Francois; Francois Ghiringhelli; Christelle De La Fouchardiere; Emmanuelle Samalin; Jean Baptiste Bachet; Christophe Borg; Valérie Boige; Thibault Voron; Trevor Stanbury; Eric Tartour; Sophie Gourgou; David Malka; Julien Taieb
Journal:  Gastric Cancer       Date:  2019-07-02       Impact factor: 7.370

6.  Tumor-infiltrating memory T-lymphocytes for prognostic prediction in cancer patients: a meta-analysis.

Authors:  Qingzhu Jia; Yi Yang; Ying Wan
Journal:  Int J Clin Exp Med       Date:  2015-02-15

7.  Level of circulating PD-L1 expression in patients with advanced gastric cancer and its clinical implications.

Authors:  Zhixue Zheng; Zhaode Bu; Xijuan Liu; Lianhai Zhang; Ziyu Li; Aiwen Wu; Xiaojiang Wu; Xiaojing Cheng; Xiaofang Xing; Hong Du; Xiaohong Wang; Ying Hu; Jiafu Ji
Journal:  Chin J Cancer Res       Date:  2014-02       Impact factor: 5.087

8.  Tumor infiltration by Tbet+ effector T cells and CD20+ B cells is associated with survival in gastric cancer patients.

Authors:  Audrey Hennequin; Valentin Derangère; Romain Boidot; Lionel Apetoh; Julie Vincent; David Orry; Jean Fraisse; Sylvain Causeret; François Martin; Laurent Arnould; Françoise Beltjens; François Ghiringhelli; Sylvain Ladoire
Journal:  Oncoimmunology       Date:  2015-06-03       Impact factor: 8.110

9.  Analysis of PD1, PDL1, PDL2 expression and T cells infiltration in 1014 gastric cancer patients.

Authors:  Xiaofang Xing; Jianping Guo; Guangyu Ding; Bo Li; Bin Dong; Qin Feng; Shen Li; Jian Zhang; Xiaomin Ying; Xiaojing Cheng; Ting Guo; Hong Du; Ying Hu; Tao Zhou; Xiaohong Wang; Lin Li; Qingda Li; Meng Xie; Liting Li; Xiangyu Gao; Fei Shan; Ziyu Li; Xianzi Wen; Jiping Wang; Jiafu Ji
Journal:  Oncoimmunology       Date:  2017-12-21       Impact factor: 8.110

10.  Clinicopathological features of programmed death ligand 1 expression with tumor-infiltrating lymphocyte, mismatch repair, and Epstein-Barr virus status in a large cohort of gastric cancer patients.

Authors:  Akihito Kawazoe; Takeshi Kuwata; Yasutoshi Kuboki; Kohei Shitara; Akiko Kawano Nagatsuma; Masaaki Aizawa; Takayuki Yoshino; Toshihiko Doi; Atsushi Ohtsu; Atsushi Ochiai
Journal:  Gastric Cancer       Date:  2016-09-14       Impact factor: 7.370

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