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BMC Cancer

, 18:1202 | Cite as

Neutrophils to lymphocytes ratio as a useful prognosticator for stage II colorectal cancer patients

  • Nikoletta Dimitriou
  • Evangelos Felekouras
  • Ioannis Karavokyros
  • Andreas Alexandrou
  • Emmanuel Pikoulis
  • John Griniatsos
Open Access
Research article
Part of the following topical collections:
  1. Surgical oncology, cancer imaging, and interventional therapeutics

Abstract

Background

The incidence of colorectal cancer (CRC) is expected to increase by 80% in year 2035. Even though advantages in treatment of CRC have being made over the last decades, the outcome remains poor. Recently, several inflammatory markers including pretreatment neutrophil to lymphocyte ratio (NLR), have being used as prognostic factors, since host inflammatory response to cancer is believed to determine disease progression.

The aim of this study is to evaluate the prognostic significance of pretreatment NLR, in terms of overall survival (OS), 5-year survival, disease-free survival (DFS) and recurrence, in CRC patients who underwent curative resection.

Methods

We retrospectively reviewed 296 patients, who were submitted to elective surgery as first therapeutic option in curative intent, between January 2010 and December 2015. Pretreatment NLR, as well as demographics, clinical, histopathologic, and laboratory data were analyzed. Univariate and multivariate analyses were conducted to identify prognostic factors associated with OS, 5-year survival, DFS and recurrence.

Results

The cutoff point of NLR was calculated with Kaplan-Meier curves and log-rank test to 4.7. Univariate and multivariate analyses disclosed elevated NLR as a significant dismal prognostic factor for DFS (HR 1.88; 95% CI 1.01–3.52; p = 0.048), 5-year survival (HR 2.14; 95% CI 1.12–4.10; p = 0.021) and OS (HR 2.11; 95% CI 1.11–4.03; p = 0.023). In a subgroup analysis, in patients with stage II CRC, NLR > 4.7 was a stronger poor predictor for DFS (HR 2.76; 95% CI 1.07–7.13; p = 0.036), 5-year survival (HR 3.84; 95% CI 1.39–10.63; p = 0.01) and OS (HR 3.62; 95% CI 1.33–4.82; p = 0.012). After adjusting stage for gender, age, location of the primary tumor, differentiation, as well as the presence of perineural, vascular, and lymphovascular invasion, the significance of NLR > 4.7 became more prominent for DFS (HR 2.85; 95% CI 1.21–6.73; p = 0.0176), 5-year survival (HR 4.06; 95% CI 1.66–9.93; p = 0.002) and OS (HR 4.07; 95% CI 1.69–9.91; p = 0.002) in stage II patients.

Conclusion

Pretreatment NLR > 4.7 is a poor prognostic factor for DFS, 5-year survival and OS in CRC patients undergoing curative resection. The dismal prognostic effect of NRL is magnified in Stage II CRC patients.

Keywords

Colorectal cancer Prognosis Inflammatory markers Neutrophil to lymphocyte ratio Survival 

Abbreviations

AJCC

American Joint Committee on Cancer

CI

Confidence Interval

CRC

Colorectal Cancer

CRP

C-reactive protein

CT

Computer tomography

DFS

Disease Free Survival

ESMO

European Society for Medical Oncology

HR

Hazard Ratio

INF-γ

Interferon gamma

IR

Interquartile Range

MMR

Mismatch repair

MRI

Magnetic resonance imaging

MSI

Microsatellite instability

NCCN

National Comprehensive Cancer Network

NLR

Neutrophil to lymphocyte ratio

OS

Overall Survival

ROC

Receiver Operating Characteristic

TNM

TNM Classification of Malignant Tumors

Background

The “classical model” of colorectal carcinogenesis is from normal mucosa to adenoma, then to dyspasia and then to cancer, the so-called “adenoma-carcinoma sequence” [1]. The molecular sequence of the above events include early loss of regulation of the Wnt signaling pathway, accumulation of activating mutations in oncogenes such as KRAS and BRAF, mutations in TP53 and SMAD4 genes and chromosomal instability, finally leading to malignant transformation [2].

Inflammation is currently considered as a hallmark for cancer development [3]. Current evidence addresses that within a tumor tissue and beside cancer cells, host structures (e.g. extracellular matrix), non-immune cells (e.g. fibrous tissue cells) and immune cells namely eosinophils, basophils, mast cells, lymphocytes, natural killer cells and dendritic cells [4, 5, 6], interact and contribute to a highly immunosuppressive microenvironment [7]. Lymphocytes have a crucial role in this microenvironment, since progressive increase in tumor-infiltrating lymphocytes is directly correlated with antitumor activity [8]. Intratumoral inflammation is assessed in hematoxylin and eosin stained tissue sections of formalin-fixed paraffin-embedded tumor specimens, scoring the average of chronic inflammation cells density within neoplastic cells’ area.

On the other hand, tissue hypoxia and necrosis [9] can cause complex interactions between the tumor and the nonspecific host inflammatory response, finally favoring disease’s progression in cancer [10]. That systemic inflammatory response involves alterations in neuroendocrine and hematopoietic system, in protein and energy metabolism and in liver function. Hepatocytes synthesize and release into the systemic circulation acute-phase proteins which are associated with lymphocytopenia and impaired T lymphocytic response within the tumor, compromising cell-mediated immunity [11]. A dysregulated systemic inflammatory response promotes cancer progression [12], while the presence of a systemic inflammatory response is associated with reduced survival [11]. For systemic inflammatory response estimation, serum levels of white blood cells, neutrophils, lymphocytes, platelets, C-reactive protein (CRP) and albumin, either alone or in several combinations, have been used as prognostic factors in various malignant solid tumors.

Roxburgh et al [13] disclosed that intratumoral and systemic inflammation are linked through the cell-mediated immune system, further stating that the type, density and location of a variety of immune cells, and not an individual immune cell type, are the important independent determinants of cancer-specific survival in patients with colorectal cancer [14], while Turner et al [15] demonstrated that intratumoral and systemic inflammatory responses appeared to be largely independent of each other.

Comparative analyses of the two inflammatory responses disclosed that when a high-grade intratumoral immune response exists, the longer the survival [14], high tumor infiltration by chronic inflammatory cells combined with low systemic inflammation are correlated to a significantly better prognosis [15], while increased systemic inflammatory response is consistently associated with a poor outcome independently to the tumor stage [16, 17]. Hence, a decreased intratumoral inflammation response and an increased systemic one might indicate a decreased immunological local control of the tumor, producing a systemic pro-inflammatory environment which facilitates cancer progression [4, 18].

NLR has been proposed as reflecting the balance between pro-tumor inflammation and anti-tumor immune function [19] and its prognostic significance has been extensively studied in several solid tumors [20]. Pronounced intratumoral lymphocytic infiltration has been proposed as a novel independent prognostic factor for colorectal cancer patients, even superior to the Dukes’ staging system [21], while systemic inflammation response may serve as a supplemental index in TNM staging system [22, 23].

The aim of this study was to evaluate the prognostic significance of pretreatment NLR, in terms of overall survival (OS), 5-year survival, disease-free survival (DFS) and recurrence in CRC patients, who underwent curative resection, without neoadjuvant treatment.

Methods

Patients

From 2009 onwards, all patients who were referred to our Department for further investigation and treatment, having been diagnosed with colorectal tumors, were prospectively enrolled. Upon their admission, all patients were informed that their details such as demographics, clinical data, laboratory results, adjuvant or neo-adjuvant therapies, type of operation, postoperative complications, histological findings, follow-up, elapse time to either local or distant recurrence, short and long term outcome as well as survival, will be prospectively collected. All agreed to participate and all consented for free use of their details for scientific purposes (research, presentations, publications, etc) in the future.

Between January 2010 and December 2015, 360 patients suffering from colorectal cancer were submitted to surgery, as first therapeutic option in curative intent, in the 1st Department of Surgery of the University of Athens, in “Laiko” Hospital.

In accordance to the Declaration of Helsinki, the present study was approved by the Scientific Council of the “Laiko” Hospital.

All patients suffered from sporading colorectal cancer and all had undergone colonoscopy and biopsies for histological confirmation of the disease. For staging of the metastatic disease, they underwent at least computer tomography (CT) of thorax and abdomen. Patients with rectal cancer were further submitted to magnetic resonance imaging (MRI) of the pelvis for loco-regional disease staging [24].

Prior to any therapeutic option implementation, all cases were discussed in the Multi-Disciplinary Cancer meeting (which comprised Surgeons, Oncologists, Radiologists and Pathologists). The most suitable therapeutic strategy was planned and was adopted by all surgeons.

Excluding patients: (i) with uncompleted data (n = 5), (ii) who died within 90 days from the initial operation (n = 6), (iii) who were histologically classified as Tis (n = 35), (iv) who were diagnosed as stage IV, even though a curative resection was achieved (n = 8) and (vi) who suffered from multiple distant metastases (n = 10), a total of 296 adenocarcinoma patients were enrolled in the present study and retrospectively analyzed.

Hematological tests

All blood samples were taken within three days before surgery. In this way, any kind of infection and co-existing inflammatory disease could be reliably excluded [25]. NLR was defined as the absolute neutrophil count divided by the absolute lymphocyte count.

Optimal cut-off value for NLR

In literature, there is an increasing interest in finding the optimal threshold value above which NLR significantly increases the likelihood of death or recurrence [26, 27, 28, 29, 30].

This has been typically carried out using ROC curves, which visually represent the sensitivity (i.e. probability of correctly identifying an event e.g. a death) and the specificity (i.e. probability of correctly identifying a nonevent) of various cutoffs. However, main disadvantage of the method is that it cannot distinguish censored from fully observed survival times. Thus, patients who were lost during follow up, were remained throughout calculations, independently if their survival times were censored or not. Hence, failure to take into account the censored times can yield to misleading inferences. In the present study, we used a method [30] based on Kaplan-Meier curves and the logrank test, which do account for censoring. For a range of potential threshold values of NLR, we calculated the Kaplan-Meier curves and the logrank test, selecting the threshold giving the greatest separation of curves in terms of the lowest p-value.

Oncologic outcome

The pathological stage of the disease was based on the 7th TNM Classification [31]. The elapse period from the initial operation to the development of the recurrence, the site and the organ of recurrence, the therapeutic strategies and the final outcome were documented during the follow-up, for DFS and OS estimation.

Statistical analysis

Statistical analyses were performed using the STATA statistical package (Version 13.0, Stata Corp, College Station, Texas). Quantitative variables were summarized as median and Interquartile Range (IR) when deviation from normal distribution was observed. Histograms and distribution plots (Percentile-Percentile and Quantile-Quantile plots) were used to evaluate the normality of the quantitative variables. Categorical variables were summarized as absolute and percentage values. Such descriptive statistics were presented for the overall sample, as well as for the NLR category. For quantitative variables, p-values were based on the t-test or the Mann–Whitney U test, if non-normality was seen. Association between categorical variables was measured through Fisher’s exact test. The significance level was pre-determined at 5%.

We used standard Cox proportional hazards models, in order to study the effect of NLR on OS, 5-year survival, DFS and recurrence. Known significant demographic, clinical and tumor characteristics were taken into account to examine whether there is an independent association of NLR with the event of interest.

Results

There were 114 female patients with a median age of 71 years (IR 63–79) and 182 male patients with a median age of 72 years (IR 63–77). The clinicopathologic characteristics of the enrolled patients are presented in Table 1.
Table 1

Clinicopathological characteristics of the enrolled patients

Parameter

No of patients (n = 296)

%

Neutrophil / Lymphocyte Ratio

 NLR ≤ 4.7

260

87.8

 NLR > 4.7

36

12.2

Gender

 Female

114

38.5

 Male

182

61.5

Age (years)

 Median + IR

72 (63–77)

 

Age > 72

 Age ≤ 72

157

53

 Age > 72

139

47

Primary tumor

 Right colon

103

34.8

 Left colon

62

21

 Rectum

131

44.2

Differentiation

 Low

63

21.3

 Medium + High

233

78.7

Τ

 T1

18

6

 T2

57

19.2

 T3

195

65.9

 T4

26

8.8

Ν

 N0

187

63.2

 N1

77

26

 N2

32

10.8

No of lymph nodes harvested

 Median + IR

19 (14–27.5)

 

No of lymph nodes harvested

 Lymph nodes ≥12

261

88.2

 Lymph nodes < 12

35

11.8

Stage

 Stage I

61

20.6

 Stage II

126

42.6

 Stage III

109

36.8

Perineural invasion

 No

273

92.2

 Yes

23

7.8

Vascular invasion

 No

253

85.5

 Yes

43

14.5

Lymphatic invasion

 No

257

86.8

 Yes

39

13.2

Follow-up (months)

 Median + IR

45 (27–68.5)

 

Site of recurrence

 Distant

16

51.6

 Local

15

48.4

Follow up

 Alive with recurrence

8

2.7

 Deaths related to the recurrence

23

7.8

 Deaths unrelated to the disease

45

15.2

 Alive

220

74.3

Distribution of NLR values among several clinicopathological variables (Table 2)

The median value of NLR for the whole study population was 2.55 (IR: 1.93–3.41). Statistically significant increased median values of NLR was found among patients older than 72 years old compared to them younger than 72, and in primary tumors in which histology report disclosed perineural and vascular invasion. Moreover, there was a gradually increased median value of NLR from T1 to T4 tumors, (1.88, 2.49, 2.60 and 2.76, respectively) although a statistical significance was not reached under any possible combination. The lowest median NLR value was noticed in Stage I patients. However, a marginally statistically significant difference (p = 0.049) was noticed when stage I patients compared to the aggregated stage II and III patients. Although not statistically significant, we should mentioned that the highest median NLR values were detected among primary tumors positive for perineural invasion (3.45), among patients who developed distant metastases (3.05), among them who developed recurrence of the disease (2.79) and among N2 patients (2.78).
Table 2

NLR among several clinicopathological variables

Parameter

NLR (Median + IR)

p value

Gender

 Male

2.59 (2.05–3.32)

NS

 Female

2.51 (1.87–3.69)

Age

  ≥ 72 years

2.72 (2.14–3.76)

0.016

  < 72 years

2.41 (1.82–3.16)

Primary tumor

 Right colon

2.67 (2.13–3.76)

 

 Left colon

2.65 (1.89–3.42)

 Rectum

2.48 (1.81–3.08)

 Right VS Left colon

2.67 (2.13–3.76) VS 2.49 (1.85–3.24)

NS

 Colon VS Rectum

2.67 (2.10–3.68) VS 2.48 (1.81–3.08)

NS

Differentiation

 Low

2.7 (2.2–3.44)

NS

 Medium + High

2.51 (1.88–3.4)

T

 T1

1.88 (1.53–2.98)

NS

 T2

2.49 (1.85–3.14)

 T3

2.6 (2.0–3.43)

 T4

2.76 (2.27–5.22)

N

 N0

2.58 (1.92–3.37)

NS

 N1

2.34 (1.85–3.45)

 N2

2.78 (2.29–3.95)

No of lymph node harvested

  < 12

2.37 (2.09–3.28)

NS

  ≥ 12

2.58 (1.92–3.43)

No of infiltrated lymph nodes

 0 (n = 198)

2.58 (1.96–3.43)

NS

 1 (n = 21)

2.22 (1.73–3.82)

  ≥ 2 (n = 77)

2.55 (1.91–3.33)

Stage

 Stage I

2.26 (1.74–2.87)

0.049

 Stage II

2.67 (2.16–3.45)

 Stage III

2.55 (1.96–3.60)

 Stage I VS Stage II + III

2.26 (1.74–2.87) VS 2.62 (2.07–3.48)

Perineural invasion

 No

2.53 (1.91–3.30)

< 0.001

 Yes

3.45 (2.24–6.00)

Vascular invasion

 No

2.54 (1.91–3.36)

0.034

 Yes

2.68 (2.17–4.18)

Lymphatic invasion

 No

2.53 (1.91–3.40)

NS

 Yes

2.63 (2.12–3.69)

Recurrence

 No

2.54 (1.96–3.37)

NS

 Yes

2.79 (1.83–4.03)

Site of recurrence

 Local (n = 15)

2.11 (1.56–4.03)

NS

 Distant (n = 16)

3.05 (2.07–3.89)

Correlation between NLR and several clinicopathological variables

Setting the NLR cut-off value at 4.7, patients were divided in two groups (NLR ≤ 4.7, n = 260 and NLR > 4.7, n = 36). Univariate analysis among several clinicopathological variables between the two groups (Table 3), revealed that patients with NLR > 4.7 were most likely of advanced age (p = 0.004), elderly than 72 years old (p = 0.033), with nearly doubled probability for disease-related death (p = 0.012) and worse overall survival (p = 0.036), compared to the patients with NLR ≤ 4.7.
Table 3

Univariate analysis between the two groups of patients, after setting the NLR cutoff value at 4.7

Parameter

NLR ≤ 4.7 (n = 260)

NLR > 4.7 (n = 36)

p-value

Gender

 Female

96

18

NS

 Male

164

18

Age (years)

 Median + IR

71 (63–77)

75.5 (70.5–81)

0.004

Age > 72

 Age  72

144

13

0.033

 Age > 72

116

23

Primary tumor

 Right colon

88

15

NS

 Left colon

54

8

 Rectum

118

13

Differentiation

 Low

56

7

NS

 Medium + High

204

29

Τ

 T1

17

1

NS

 T2

49

8

 T3

175

20

 T4

19

7

Ν

 N0

165

22

NS

 N1

68

9

 N2

27

5

No of lymph nodes harvested

 Median + IR

19 (14–27)

17 (15–28)

NS

No of lymph nodes harvested

 Lymph nodes ≥12

230

31

NS

 Lymph nodes < 12

30

5

Stage

 Stage I

55

6

NS

 Stage II

110

16

 Stage III

95

14

Perineural invasion

 No

246

27

< 0.001

 Yes

14

9

Vascular invasion

 No

226

27

NS

 Yes

34

9

Lymphatic invasion

 No

227

30

NS

 Yes

33

6

Site of recurrence

 Distant

12

4

NS

 Local

14

1

Follow up

 Alive with recurrence

8

0

0.036

 Deaths related to the recurrence

18

5

 Deaths unrelated to the disease

35

10

 Alive

199

21

Probability for overall survival

 Alive

204

21

0.012

 Dead

56

15

Probability for recurrence

 No recurrence

234

31

NS

 Recurrence

26

5

Oncologic outcome

Recurrence, DFS, 5-year survival and OS were set as the end points for the oncologic outcome of the patients.

Within a median follow up of 45 months (IR 27–68.5), 31 patients developed recurrence of the disease. Fifteen patients developed local recurrence, while the remaining 16 developed distant metastases namely: liver (n = 7), lung (n = 3), simultaneous lung and liver (n = 3) and disseminated peritoneal carcinomatosis (n = 3). Eleven patients who developed local recurrence and 12 patients who developed distant metastases, died from the disease.

Multivariate analyses among factors which might influence recurrence (Table 4) disclosed that stages II and III, as well as vascular invasion were independently related to a worse prognosis. However, NLR was unrelated to the recurrence.
Table 4

Univariate and Multivariate analysis among factors which might affect the recurrence and the disease free survival (DFS)

 

Recurrence

DFS

Univariate Analysis

Multivariate Analysis

Univariate Analysis

Multivariate Analysis

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

NLR

  ≤ 4.7

1

  

1

  

1

  

1

  

  > 4.7

1.67

0.64–4.36

0.293

1.1

0.38–3.21

0.862

2.03

1.16–3.57

0.014

1.88

1.01–3.52

0.048

Gender

 Female

1

  

1

  

1

  

1

  

 Male

1.81

0.81–4.04

0.15

1.73

0.76–3.93

0.189

1.36

0.84–2.18

0.207

1.41

0.87–2.30

0.163

Age

  ≤ 72

1

  

1

  

1

  

1

  

  > 72

0.9

0.44–1.83

0.763

1.02

0.48–2.17

0.949

1.70

1.08–2.65

0.021

1.83

1.15–2.91

0.011

Primary tumor

 Right colon

1

  

1

  

1

  

1

  

 Left colon

0.84

0.29–2.46

0.753

0.7

0.23–2.14

0.535

0.81

0.41–1.61

0.543

0.71

0.35–1.46

0.354

 Rectum

1.34

0.61–2.96

0.463

1.53

0.66–3.55

0.316

1.39

0.85–2.28

0.196

1.46

0.85–2.51

0.175

Grade

 Low

1

  

1

  

1

  

1

  

 Medium + High

1.43

0.55–3.73

0.464

1.98

0.73–5.35

0.177

1.14

0.65–2.00

0.646

1.18

0.66–2.14

0.574

T

 T1

1

     

1

     

 T2

8.74E + 08

8.74e + 08–8.74e + 08

.

   

2.96

0.38–22.96

0.299

   

 T3

1.68e + 09

5.79e + 08–4.88e + 09

0

   

5.2

0.72–37.60

0.102

   

 T4

3.33e + 09

8.89e + 08–1.25e + 10

0

   

8.95

1.16–69.40

0.036

   

N

 N0

1

     

1

     

 N1

1.06

0.43–2.57

0.906

   

1.04

0.61–1.79

0.884

   

 N2

3.60

1.54–8.46

0.003

   

2.88

1.64–5.07

< 0.001

   

No lymph nodes yield

  ≥ 12

1

     

1

  

1

  

  < 12

0.55

0.13–2.29

0.408

0.55

0.13–2.44

0.433

1.56

0.86–2.83

0.145

1.7

0.89–3.24

0.106

Stage

 Stage I

1

     

1

  

1

  

 Stage II

3.86

0.88–16.99

0.074

5.14

1.14–23.30

0.034

2.35

1.09–5.07

0.029

2.80

1.28–6.10

0.01

 Stage III

4.81

1.10–21.05

0.037

5.22

1.13–24.13

0.035

2.80

1.30–6.03

0.008

3.06

1.38–6.78

0.006

Perineural invasion

 No

1

     

1

  

1

  

 Yes

2.03

0.71–5.84

0.189

0.89

0.26–3.05

0.848

1.37

0.63–2.99

0.428

0.54

0.22–1.32

0.176

Vascular invasion

 No

1

  

1

  

1

  

1

  

 Yes

4.05

1.93–8.49

0

4.23

1.78–10.03

0.001

2.36

1.39–4.02

0.001

2.38

1.26–4.49

0.007

Lymphatic invasion

 No

1

  

1

  

1

  

1

  

 Yes

2.42

1.04–5.64

0.04

1.16

0.43–3.11

0.769

2.07

1.20–3.59

0.009

1.48

0.77–2.83

0.237

On the other hand (Tables 4 and 5), NLR > 4.7, age above 72 years-old, stages II and III and vascular invasion had independent adverse effect on DFS (Fig. 1), 5-year survival (Fig. 2) and OS (Fig. 3).
Table 5

Univariate and Multivariate analysis among factors which might affect the 5-year survival and the overall survival (OS)

 

5-year survival

Overall survival

Univariate Analysis

Multivariate Analysis

Univariate Analysis

Multivariate Analysis

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

NLR

  ≤ 4.7

1

  

1

  

1

  

1

  

  > 4.7

2.58

1.45–4.59

0.001

2.14

1.12–4.10

0.021

2.48

1.40–4.40

0.002

2.11

1.11–4.03

0.023

Gender

 Female

1

  

1

  

1

  

1

  

 Male

1.11

0.67–1.83

0.681

1.22

0.72–2.04

0.459

1.18

0.72–1.93

0.517

1.29

0.78–2.16

0.324

Age

  ≤ 72

1

  

1

  

1

  

1

  

  > 72

2.05

1.25–3.35

0.004

2.30

1.37–3.87

0.002

2.13

1.32–3.46

0.002

2.41

1.45–4.01

0.001

Primary tumor

 Right colon

1

  

1

  

1

  

1

  

 Left colon

0.88

0.42–1.82

0.73

0.79

0.37–1.70

0.552

0.84

0.41–1.72

0.627

0.76

0.35–1.61

0.467

 Rectum

1.35

0.79–2.32

0.275

1.38

0.76–2.50

0.283

1.35

0.80–2.29

0.262

1.37

0.77–2.44

0.289

Grade

 Low

1

  

1

  

1

  

1

  

 Medium + High

1

0.55–1.80

0.995

0.99

0.53–1.85

0.98

1.04

0.58–1.87

0.891

1

0.54–1.86

0.989

T

 T1

1

           

 T2

2.08

0.26–16.63

0.491

         

 T3

4.25

0.59–30.76

0.152

         

 T4

8.08

1.03–63.13

0.046

         

N

 N0

1

           

 N1

1.2

0.67–2.15

0.546

         

 N2

3.68

2.04–6.63

0

         

No lymph nodes yield

  ≥ 12

1

  

1

  

1

  

1

  

  < 12

1.6

0.84–3.06

0.154

1.94

0.97–3.91

0.063

1.65

0.88–3.07

0.116

1.95

0.99–3.84

0.052

Stage

 Stage I

1

  

1

  

1

  

1

  

 Stage II

2.35

0.97–5.70

0.058

2.70

1.10–6.62

0.03

2.09

0.91–4.80

0.08

2.41

1.04–5.59

0.041

 Stage III

3.4

1.43–8.13

0.006

3.66

1.48–9.05

0.005

3.02

1.34–6.80

0.008

3.27

1.40–7.64

0.006

Perineural invasion

 No

1

  

1

  

1

  

1

  

 Yes

1.71

0.78–3.77

0.18

0.61

0.24–1.54

0.297

1.66

0.76–3.65

0.204

0.59

0.24–1.49

0.266

Vascular invasion

 No

1

  

1

  

1

  

1

  

 Yes

2.51

1.42–4.43

0.001

2.36

1.17–4.73

0.016

2.45

1.39–4.31

0.002

2.29

1.15–4.57

0.019

Lymphatic invasion

 No

1

  

1

  

1

  

1

  

 Yes

2.15

1.19–3.89

0.011

1.41

0.69–2.89

0.344

2.23

1.26–3.96

0.006

1.54

0.77–3.08

0.217

Fig. 1

Kaplan-Meier plots quantifying the effects of NLR status on the DFS

Fig. 2

Kaplan-Meier plots quantifying the effects of NLR status on the 5-year survival

Fig. 3

Kaplan-Meier plots quantifying the effects of NLR status on the overall survival

Oncologic outcome for stage II patients

Noteworthy, stage II was found as independently related to the DFS (p = 0.029) but it did not reach statistically significance regarding recurrence, 5-year survival and OS. Hence, a multivariate analysis among factors which could affect outcome in the 126 stage II patients was conducted (Table 6), disclosing NLR > 4.7 as an independent dismal factor for DFS, 5-year survival and OS, but not for the recurrence itself. After adjusting stage for gender, age, location of the primary tumor, differentiation, as well as the presence of perineural, vascular, and lymphovascular invasion, the significance of NLR > 4.7 became more prominent for DFS, 5-year survival and OS in stage II patients (Table 7).
Table 6

Multivariate Cox models among factors which might affect the recurrence, the disease free survival (DFS), the 5-year survival and the overall survival (OS) in stage II patients

 

Recurrence

DFS

5-year survival

Overall Survival

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

HR

95% CI

p value

NLR

  ≤ 4.7

1

  

1

  

1

  

1

  

  > 4.7

1.68

0.37–7.71

0.506

2.76

1.07–7.13

0.036

3.84

1.39–10.63

0.01

3.62

1.33–9.82

0.012

Gender

 Female

1

  

1

  

1

  

1

  

 Male

1.44

0.44–4.71

0.546

1.32

0.63–2.77

0.464

1.02

0.44–2.37

0.961

1.09

0.48–2.50

0.838

Age

  ≤ 72

1

  

1

  

1

  

1

  

  > 72

0.88

0.30–2.57

0.811

1.64

0.79–3.41

0.183

2.33

0.94–5.75

0.066

2.56

1.05–6.26

0.039

Primary tumor

 Right colon

1

  

1

  

1

  

1

  

 Left colon

0.96

0.21–4.40

0.958

0.88

0.33–2.35

0.794

0.95

0.31–2.94

0.935

0.96

0.31–2.95

0.947

 Rectum

1.98

0.53–7.41

0.312

1.75

0.70–4.39

0.233

1.59

0.53–4.76

0.41

1.74

0.59–5.11

0.317

Grade

 Low

1

  

1

  

1

  

1

  

 Medium + High

1.67

0.37–7.58

0.506

1.34

0.53–3.40

0.541

1.31

0.45–3.80

0.625

1.36

0.47–3.93

0.569

No lymph nodes yield

  ≥ 12

   

1

  

1

  

1

  

  < 12

   

1.82

0.66–5.07

0.249

2.76

0.90–8.45

0.075

2.4

0.80–7.19

0.117

Perineural invasion

 No

   

1

  

1

     

 Yes

   

0.49

0.08–2.85

0.426

0.57

0.09–3.78

0.562

0.63

0.10–4.04

0.624

Vascular invasion

 No

1

  

1

  

1

  

1

  

 Yes

2.65

0.53–13.18

0.234

2.09

0.71–6.13

0.182

2.28

0.66–7.89

0.192

2.22

0.65–7.58

0.205

Lymphatic invasion

 No

1

  

1

  

1

  

1

  

 Yes

0.93

0.10–8.70

0.953

2.3

0.75–7.02

0.145

2.06

0.55–7.69

0.284

2.12

0.58–7.80

0.257

Table 7

Correlation between NLR and DFS, 5-year survival and OS by stage, after adjusting it by gender, age, location of the primary tumor, differentiation as well as presence of perineural, vascular, and lymphovascular invasion

 

DFS

5-year survival

Overall Survival

HR

95% Confidence Interval

p value

HR

95% Confidence Interval

p value

HR

95% Confidence Interval

p value

Stage I

 NLR > 4.7

1.60

0.19–13.41

0.663

2.06

0.23–18.18

0.514

1.85

0.22–15.88

0.572

Stage II

 NLR > 4.7

2.85

1.21–6.73

0.017

4.06

1.66–9.93

0.002

4.07

1.67–9.91

0.002

Stage III

 NLR > 4.7

1.33

0.54–3.28

0.537

1.28

0.50–3.22

0.605

1.27

0.50–3.18

0.612

Discussion

Systematic review [32] and meta-analyses [33, 34, 35, 36, 37] agreed that elevated pre-treatment NLR predicts poor prognosis in CRC patients, both in those with localized disease as well as in those with liver metastases.

The exact NLR cut-off value varies among the studies. Among the 19 studies included in a systematic review, in one the cut-off value was set at 4.98 and in eight at 5 [32]. In eight out of 13 (61.5%) studies included in a meta-analysis, the cut-off value had been set at 5 [33], in 11 out of 16 (69%) studies included in another meta-analysis, the cut-off value had also been set at 5 [35], a third meta-analysis which included 15 studies, disclosed that patients with pretreatment NLR < 5 were significantly more likely to have 5-year overall survival and 5-year disease-free survival [36], while in the most recent meta-analysis, in 13 out of 16 (81%) included studies, the cut-off value had been set at 5 [37]. These findings suggest that a value close to 5 seems to provide the most statistically significant results.

In agreement to previous reports, the present study concluded that in patients with localized CRC, an NLR above 4.7 was a dismal prognostic factor for DFS, 5-year survival and overall survival.

However, the exact mechanism explaining the adverse association between NLR and survival outcome in CRC patients, remains unknown. Neutrophilia is a common finding in cancer patients. Colorectal cancer cells secrete granulocyte colony stimulating factor which recruits neutrophils into the tumor site [38]; several among the micro-environment cells produce mediators capable of recruiting different leukocytes populations from circulation into the tumor site [4]; while others are capable of secreting neutrophil chemotactic substances [5]. Neutrophils are the primary source of vascular endothelial growth factor [39], while neutrophils-derived proteinases degrade cytokines and chemokines [40, 41] and remodel the extracellular matrix [42], favoring tumor proliferation, local invasion, angiogenesis and tumor vascularization, promoting metastatic potential [39, 40, 41, 42, 43]. Moreover, neutrophil elastase, upon gaining entry to the tumor cells, leads to hyperactivity of the PI3K pathway, accelerating the uncontrolled tumor cell proliferation further [5, 44]. Finally, neutrophils are also capable to degrade basement membrane, mediating local tumor invasion and distant metastases formation [45]. Therefore, increased neutrophils may promote tumor growth and metastasis.

The adaptive immune system is mainly represented by tumor infiltrating lymphocytes comprising CD8+ cytotoxic T-lymphocytes and CD4+ T-helper lymphocytes [46]. Gene profiling analyses of tumor microenvironment in a variety of solid tumors revealed that the majority of them showed a T cell–infiltrated phenotype [47]. During the tumor specific adaptive response, cytotoxic T lymphocytes play a crucial role, inducing production of cytokines [48]. Especially cytokine IFN-γ has a pivotal antitumor role inducing cell cycle arrest and proliferation [34], autophagy-associated apoptosis [49] and antitumor macrophage activity [50]. Noteworthy, neutrophils isolated from early-stage, small-sized tumors are able to stimulate T-cell responses and are cytotoxic to cancer cells [51]. Thus, an increased intratumoral lymphocyte concentration may amplify host systemic inflammatory response to a tumor, fact probably associated with a positive clinical outcome [52, 53]. Pre-treatment lymphocytopenia has been proposed as a surrogate marker of cancer-induced immunosuppression. Various immunosuppressive molecules triggered by activated signaling pathways (STAT, MARK, NF-kB, Wnt/β-catenin) as a result of gene alterations [54] or an inherited T cell triggered adaptive resistance [55], impair activation of helper lymphocytes, promote recruitment of suppressive regulatory T cells and activate the extrinsic pathway of apoptosis, finally impairing lymphocytes homeostasis [56].

An elevated NLR can be the result of either an increase in nominator (neutrophils) or a decrease in denominator (lymphocytes) or both. In tumor microenvironment, an increased neutrophils concentration promotes tumor growth, while a decreased lymphocytes concentration indicates ineffective local tumor control. Thus, an increased microenvironmental NLR may indicate tumor progression, representing a marker of dismal prognosis. Since, all published so far reports, unanimously agree that a high serum NLR is an indicator of unfavorable prognosis, we can postulate that the serum NLR reflects indirectly but accurately the intratumoral inflammation process. Since calculation of intratumoral NLR is neither available in all institutes nor cost-effective, while serum NLR is an easily measured, reproducible and cost-effective marker, serum NLR may hold a great clinical impact in the future.

The present study disclosed that the lowest median NLR value was noticed in T1 tumors (1.88) and was gradually increased up to 2.76 in T4 tumors. Even higher median NLR values were noticed among patients who recurred (2.79), particularly among them who developed distant metastases (3.05). Previous reports [57, 58, 59] addressed that the lowest median NLR value had been noticed in normal mucosa, increasing gradually in the pathway extending from adenoma to cancer. Therefore, we can propose that host immune system responses with its maximum force at the earliest stage of carcinogenesis, even at the level of precancerous condition, in an attempt to confine tumor locally, subsequently eliminating as cancer cells progressively escape from host immunological surveillance.

In our study, the highest median NLR value was noticed among tumors positive for perineural invasion (3.45), although neural invasion was not disclosed as independent prognostic marker in our multivariate analysis. Perineural invasion is introduced in the seventh edition of TNM [31], as an accessory factor, for poor prognosis. It is believed that perineural invasion is an alternative route of metastatic spread, and it has been associated with poor differentiation, T stage, incidence of metastasis at time of diagnosis, lymphatic, venous invasion and local recurrence. Perineural invasion was also reported to be an independent prognostic factor for 5-year survival and 5-year DFS [60, 61]. We believed that NLR was higher in tumors with perineural invasion as both factors are markers of aggressive phenotype of CRC.

The finding that NLR > 4.7 was directly related to the advanced age of the patients (particularly those over 72 years old) is in agreement to published reports that aging cells create a inflammatory micro-environment more permissive to tumor growth [62].

NLR > 4.7 was found unrelated to the local or distant recurrence, although we tried different cut off values searching for any statistical significance. Cancer cells actively develop different mechanisms to escape tumor immunity. Cancer cells utilize chemokines, which are up-regulated as cancer becomes more malignant, and are key players in cancer cell proliferation and invasiveness, promoting cancer cell metastasis [63]. In response to specific chemokines, different immune cell subsets migrate into the tumor microenvironment and regulate tumor immune responses. Direct and indirect interactions on chemokine pathways may reshape the immune and biological phenotypes of a tumor, making its biological behavior unpredictable and altering its metastatic potential [64].

Even thought NLR > 4.7 was not associated with recurrence, as already stated, high NLR was associated with DFS, this inconsistency in our results, can be explain from the fact that DFS is actually a composite event consisting of either survival or recurrence and the number of recurrent events is low compared to the number of deaths.

The most interesting finding of the present study was that NLR > 4.7 disclosed as an independent dismal prognostic factor for DFS, 5-year survival and overall survival in stage II CRC patients. After adjusting stage for gender, age, location of the primary tumor, differentiation, and presence of perineural, vascular and lymphovascular invasion, NLR > 4.7 was isolated as dismal prognostic factor only for stage II patients.

According to the American Joint Committee on Cancer (AJCC), stage II CRC includes three subcategories: stage IIA (T3 N0), stage IIB (T4aN0) and stage IIC (T4bN0). Seventy five percent of stage II CRC patients can be cured with surgery alone, not experiencing any further recurrence, while the remaining 25% will develop recurrence in the future [65]. The definition of whom among the CRC stage II patients constitute a ‘high-risk’ subpopulation, which will be favored by adjuvant chemotherapy is not clearly defined in the TNM staging system and there is no clear consensus in the literature [66].

European Society for Medical Oncology (ESMO) recommends adjuvant chemotherapy for those individuals who fulfill at least one of the following criteria: T4 tumors, poorly differentiated tumors, tumors with vascular, lymphatic or perineural invasion, inadequate sample of lymph nodes (< 12) and bowel perforation or bowel obstruction at presentation [67].

The National Comprehensive Cancer Network (NCCN) furthermore recommends adjuvant chemotherapy for patients with inadequate or positive resection margins, with tumors characterized as MSI-L or MSS, with no significant comorbidities and anticipated life expectancy [66]. Stage II MSI-H CRC tumors do not benefit from adjuvant therapy [68].

The prognostic significance of NLR has also been examined in the subgroup of stage II CRC patients. Ding et al [69] disclosed that an elevated NLR was related to a worse 5-year survival. Hung et al [70] addressed that an elevated NLR was an independent predictor for OS but not for DFS because the patients of his study with an elevated NLR tended to have an increased risk of death from other causes and an elevated NLR was linked with some stronger risk factors such as T4b cancers, tumor obstruction or tumor perforation. Two reports from the same Institute [71, 72], concluded that an elevated NLR was related to a decreased OS and a decreased time-to-relapse, particularly in the group of patients who underwent curative surgery alone compared to them who underwent adjuvant chemotherapy. The authors concluded that an elevated NLR may be a negative prognostic marker, and that such high-risk patients may benefit from adjuvant chemotherapy. The most recent report is coming from Turner et al [15] who found that the combination of low intratumoral chronic inflammatory cells density with high serum NLR level, served a poor outcome in terms of recurrence-free survival and OS for stage II CRC patients, finally suggesting that in this particular subgroup of patients, adjuvant chemotherapy might be considered.

After adjusting stage by gender, age, location of the primary tumor, differentiation, the presence of perineural, vascular and lymphovascular invasion, the present study isolated NLR > 4.7 as an independent dismal prognostic factor only for stage II CRC patients. We hypothesize that in stage III patients, the well-known prognostication of the metastatically infiltrated lymph nodes [73, 74] represents the strongest factor finally defining the poorer outcome. The new finding that in stage II CRC patients an elevated NLR may be by itself an independent dismal prognostic factor should be evaluated further in order to be determined its prognostic significance (if any) and its possible clinical implications.

Conclusion

The present study concluded that in patients with localized CRC, a pretreatment NLR above 4.7 is a dismal prognostic factor for disease free survival (DFS), 5-year survival and overall survival (OS). The dismal prognostic effect of NRL is magnified in Stage II CRC patients.

Notes

Acknowledgments

No acknowledgments.

Funding

No funding.

Availability of data and materials

The dataset used and analysed during the present study is available from the corresponding author upon reasonable request.

Authors’ contributions

EF, IK, AA, EP and JG enrolled patients; ND, IK and JG designed the study; ND, AA and EP analyzed the data; EF made useful comments and corrections; ND and JG wrote the article; JG made the final approval. All authors have read and approved the final version for publication.

Ethics approval and consent to participate

The study was approved by the ethics committee of the LAIKO Hospital. All participants signed informed consent forms.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.
    Pino MS, Chung DC. The chromosomal instability pathway in colon cancer. Gastroenterology. 2010;138:2059–72.CrossRefPubMedCentralGoogle Scholar
  2. 2.
    Marks KM, West NP, Morris E, Quirke P. Clinicopathological, genomic and immunological factors in colorectal cancer prognosis. Br J Surg. 2018;105:e99–e109.CrossRefGoogle Scholar
  3. 3.
    Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–74.CrossRefPubMedCentralGoogle Scholar
  4. 4.
    Pedrazzani C, Mantovani G, Fernandes E, Bagante F, Luca Salvagno G, Surci N, et al. Assessment of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and platelet count as predictors of long-term outcome after R0 resection for colorectal cancer. Sci Rep. 2017;7:1494.CrossRefPubMedCentralGoogle Scholar
  5. 5.
    Gregory AD, Houghton AM. Tumor-associated neutrophils: new targets for cancer therapy. Cancer Res. 2011;71:2411–6.CrossRefPubMedCentralGoogle Scholar
  6. 6.
    Albini A, Sporn MB. The tumour microenvironment as a target for chemoprevention. Nat Rev Cancer. 2007;7:139–47.CrossRefPubMedCentralGoogle Scholar
  7. 7.
    Yin J, Markert JM, Leavenworth JW. Modulation of the Intratumoral immune landscape by oncolytic herpes simplex virus Virotherapy. Front Oncol. 2017;7:136.CrossRefPubMedCentralGoogle Scholar
  8. 8.
    Lee WS, Park S, Lee WY, Yun SH, Chun HK. Clinical impact of tumor-infiltrating lymphocytes for survival in stage II colon cancer. Cancer. 2010;116:5188–99.CrossRefPubMedCentralGoogle Scholar
  9. 9.
    Vakkila J, Lotze MT. Inflammation and necrosis promote tumour growth. Nat Rev Immunol. 2004;4:641–8.CrossRefPubMedCentralGoogle Scholar
  10. 10.
    DeNardo DG, Johansson M, Coussens LM. Immune cells as mediators of solid tumor metastasis. Cancer Metastasis Rev. 2008;27:11–8.CrossRefPubMedCentralGoogle Scholar
  11. 11.
    Roxbourgh CSD, McMillan DC. Role of systemic inflammatory response in predicting survival in patients with primary operable cancer. Future Oncol. 2010;6:149–63.CrossRefGoogle Scholar
  12. 12.
    McAllister SS, Weinberg RA. The tumour-induced systemic environment as a critical regulator of cancer progression and metastasis. Nat Cell Biol. 2014;16:717–27.CrossRefPubMedCentralGoogle Scholar
  13. 13.
    Roxburgh CS, Salmond JM, Horgan PG, Oien KA, McMillan DC. Comparison of the prognostic value of inflammation-based pathologic and biochemical criteria in patients undergoing potentially curative resection for colorectal cancer. Ann Surg. 2009;249:788–93.CrossRefPubMedCentralGoogle Scholar
  14. 14.
    Roxburgh CSD, Salmond JM, Horgan PG, Oien KA, McMillan DC. Tumour inflammatory infiltrate predicts survival following curative resection for node-negative colorectal cancer. Eur J Cancer. 2009;45:2138–45.CrossRefPubMedCentralGoogle Scholar
  15. 15.
    Turner N, Wong HL, Templeton A, Tripathy S, Whiti Rogers T, Croxford M, et al. Analysis of local chronic inflammatory cell infiltrate combined with systemic inflammation improves prognostication in stage II colon cancer independent of standard clinicopathologic criteria. Int J Cancer. 2016;138:671–8.CrossRefPubMedCentralGoogle Scholar
  16. 16.
    Roxburgh CS, McMillan DC. Cancer and systemic inflammation: treat the tumour and treat the host. Br J Cancer. 2014;110:1409–12.CrossRefPubMedCentralGoogle Scholar
  17. 17.
    McMillan DC. The systemic inflammation-based Glasgow prognostic score: a decade of experience in patients with cancer. Cancer Treat Rev. 2013;39:534–40.CrossRefPubMedCentralGoogle Scholar
  18. 18.
    Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD. Cancer immunoediting: from immunosurveillance to tumor escape. Nat Immunol. 2002;3:991–8.CrossRefPubMedCentralGoogle Scholar
  19. 19.
    Maeda K, Shibutani M, Otani H, Nagahara H, Ikeya T, Iseki Y, et al. Inflammation-based factors and prognosis in patients with colorectal cancer. World J Gastrointest Oncol. 2015;7:111–7.CrossRefPubMedCentralGoogle Scholar
  20. 20.
    Templeton AJ, McNamara MG, Seruga B, Vera-Badillo FE, Aneja P, Ocana A, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106.  https://doi.org/10.1093/jnci/dju12.
  21. 21.
    Jass JR. Lymphocytic infiltration and survival in rectal cancer. J Clin Pathol. 1986;39:585–9.CrossRefPubMedCentralGoogle Scholar
  22. 22.
    Chen JH, Zhai ET, Yuan YJ, Wu KM, Xu JB, Peng JJ, et al. Systemic immune-inflammation index for predicting prognosis of colorectal cancer. World J Gastroenterol. 2017;23:6261–72.CrossRefPubMedCentralGoogle Scholar
  23. 23.
    Song Y, Yang Y, Gao P, Chen X, Yu D, Xu Y, et al. The preoperative neutrophil to lymphocyte ratio is a superior indicator of prognosis compared with other inflammatory biomarkers in resectable colorectal cancer. BMC Cancer. 2017;17:744.CrossRefPubMedCentralGoogle Scholar
  24. 24.
    Balyasnikova S, Brown G. Optimal imaging strategies for rectal cancer staging and ongoing management. Curr Treat Options in Oncol. 2016;17:32.CrossRefGoogle Scholar
  25. 25.
    Szkandera J, Pichler M, Stotz M, Gerger A. Reply: comment on ‘A derived neutrophil to lymphocyte ratio predicts clinical outcome in stage II and III colon cancer patients’. Br J Cancer. 2013;109:3126–7.CrossRefPubMedCentralGoogle Scholar
  26. 26.
    Malietzis G, Giacometti M, Askari A, Nachiappan S, Kennedy RH, Faiz OD, et al. A preoperative neutrophil to lymphocyte ratio of 3 predicts disease-free survival after curative elective colorectal cancer surgery. Ann Surg. 2014;260:287–92.CrossRefPubMedCentralGoogle Scholar
  27. 27.
    Chiang SF, Hung HY, Tang R, Changchien CR, Chen JS, You YT, et al. Can neutrophil-to-lymphocyte ratio predict the survival of colorectal cancer patients who have received curative surgery electively? Int J Color Dis. 2012;27:1347–57.CrossRefGoogle Scholar
  28. 28.
    Ozdemir Y, Akin ML, Sucullu I, Balta AZ, Yucel E. Pretreatment neutrophil/lymphocyte ratio as a prognostic aid in colorectal cancer. Asian Pac J Cancer Prev. 2014;15:2647–50.CrossRefPubMedCentralGoogle Scholar
  29. 29.
    Shin JS, Suh KW, Oh SY. Preoperative neutrophil to lymphocyte ratio predicts survival in patients with T1-2N0 colorectal cancer. J Surg Oncol. 2015;112:654–7.CrossRefPubMedCentralGoogle Scholar
  30. 30.
    Jankova L, Dent OF, Chan C, Chapuis P, Clarke SJ. Preoperative neutrophil/lymphocyte ratio predicts overall survival but does not predict recurrence or cancer-specific survival after curative resection of node-positive colorectal cancer. BMC Cancer. 2013;13:442.CrossRefPubMedCentralGoogle Scholar
  31. 31.
    Sobin LH, Gospodarowicz MK, Wittekind C. TNM classification of malignant tumours, 7th edition. Oxford: Wiley-Blackwell; 2011.Google Scholar
  32. 32.
    Haram A, Boland MR, Kelly ME, Bolger JC, Waldron RM, Kerin MJ. The prognostic value of neutrophil-to-lymphocyte ratio in colorectal cancer: a systematic review. J Surg Oncol. 2017;115:470–9.CrossRefGoogle Scholar
  33. 33.
    Malietzis G, Giacometti M, Kennedy RH, Athanasiou T, Aziz O, Jenkins JT. The emerging role of neutrophil to lymphocyte ratio in determining colorectal cancer treatment outcomes: a systematic review and meta-analysis. Ann Surg Oncol. 2014;21:3938–46.CrossRefGoogle Scholar
  34. 34.
    Mei Z, Liu Y, Liu C, Cui A, Liang Z, Wang G, et al. Tumour-infiltrating inflammation and prognosis in colorectal cancer: systematic review and meta-analysis. Br J Cancer. 2014;110:1595–605.CrossRefPubMedCentralGoogle Scholar
  35. 35.
    Li MX, Liu XM, Zhang XF, Zhang JF, Wang WL, Zhu Y, et al. Prognostic role of neutrophil-to-lymphocyte ratio in colorectal cancer: a systematic review and meta-analysis. Int J Cancer. 2014;134:2403–13.CrossRefPubMedCentralGoogle Scholar
  36. 36.
    Tsai PL, Su WJ, Leung WH, Lai CT, Liu CK. Neutrophil-lymphocyte ratio and CEA level as prognostic and predictive factors in colorectal cancer: a systematic review and meta-analysis. J Cancer Res Ther. 2016;12:582–9.CrossRefPubMedCentralGoogle Scholar
  37. 37.
    Zhang J, Zhang HY, Li J, Shao XY, Zhang CX. The elevated NLR, PLR and PLT may predict the prognosis of patients with colorectal cancer: a systematic review and meta-analysis. Oncotarget. 2017;8:68837–46.PubMedPubMedCentralGoogle Scholar
  38. 38.
    Liu Q, Qiao L, Hu P, Deng G, Zhang J, Liang N, Xie J. The effect of granulocyte and granulocyte-macrophage colony stimulating factors on tumor promotion. J BUON. 2017;22:21–8.PubMedPubMedCentralGoogle Scholar
  39. 39.
    McCourt M, Wang JH, Sookhai S, Redmond HP. Proinflammatory mediators stimulate neutrophil-directed angiogenesis. Arch Surg. 1999;134:1325–31.CrossRefPubMedCentralGoogle Scholar
  40. 40.
    Pham CT. Neutrophil serine proteases: specific regulators of inflammation. Nat Rev Immunol. 2006;6:541–50.CrossRefPubMedCentralGoogle Scholar
  41. 41.
    Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010;140:883–99.CrossRefPubMedCentralGoogle Scholar
  42. 42.
    Shamamian P, Schwartz JD, Pocock BJ, Monea S, Whiting D, Marcus SG, et al. Activation of progelatinase a (MMP-2) by neutrophil elastase, cathepsin G, and proteinase-3: a role for inflammatory cells in tumor invasion and angiogenesis. J Cell Physiol. 2001;189:197–206.CrossRefPubMedCentralGoogle Scholar
  43. 43.
    Tazzyman S, Lewis CE, Murdoch C. Neutrophils: key mediators of tumour angiogenesis. Int J Exp Pathol. 2009;90:222–31.CrossRefPubMedCentralGoogle Scholar
  44. 44.
    Houghton AM, Rzymkiewicz DM, Ji H, Gregory AD, Egea EE, Metz HE, et al. Neutrophil elastase-mediated degradation of IRS-1 accelerates lung tumor growth. Nat Med. 2010;16:219–23.CrossRefPubMedCentralGoogle Scholar
  45. 45.
    Huh SJ, Liang S, Sharma A, Dong C, Robertson GP. Transiently entrapped circulating tumor cells interact with neutrophils to facilitate lung metastasis development. Cancer Res. 2010;70:6071–82.CrossRefPubMedCentralGoogle Scholar
  46. 46.
    Grizzi F, Basso G, Borroni EM, Cavalleri T, Bianchi P, Stifter S, et al. Evolving notions on immune response in colorectal cancer and their implications for biomarker development. Inflamm Res. 2018;67:375–89.CrossRefPubMedCentralGoogle Scholar
  47. 47.
    Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14:1014–22.CrossRefPubMedCentralGoogle Scholar
  48. 48.
    Huber C, Bobek N, Kuball J, Thaler S, Hoffarth S, Theobald M, Schuler M. Inhibitors of apoptosis confer resistance to tumour suppression by adoptively transplanted cytotoxic T-lymphocytes in vitro and in vivo. Cell Death Differ. 2005;12:317–25.CrossRefPubMedCentralGoogle Scholar
  49. 49.
    Wang QS, Shen SQ, Sun HW, Xing ZX, Yang HL. Interferon-gamma induces autophagy-associated apoptosis through induction of cPLA2-dependent mitochondrial ROS generation in colorectal cancer cells. Biochem Biophys Res Commun. 2018;498:1058–65.CrossRefPubMedCentralGoogle Scholar
  50. 50.
    Dunn GP, Old LJ, Schreiber RD. The three Es of cancer immunoediting. Annu Rev Immunol. 2004;22:329–60.CrossRefPubMedCentralGoogle Scholar
  51. 51.
    Kiss M, Van Gassen S, Movahedi K, Saeys Y, Laoui D. Myeloid cell heterogeneity in cancer: not a single cell alike. Cell Immunol. 2018.  https://doi.org/10.1016/j.cellimm.2018.02.008.CrossRefPubMedCentralGoogle Scholar
  52. 52.
    Kennelly RP, Murphy B, Larkin JO, Mehigan BJ, McCormick PH. Activated systemic inflammatory response at diagnosis reduces lymph node count in colonic carcinoma. World J Gastrointest Oncol. 2016;8:623–8.CrossRefPubMedCentralGoogle Scholar
  53. 53.
    Shibutani M, Maeda K, Nagahara H, Noda E, Ohtani H, Nishiguchi Y, Hirakawa K. A high preoperative neutrophil-to-lymphocyte ratio is associated with poor survival in patients with colorectal cancer. Anticancer Res. 2013;33:3291–4.PubMedPubMedCentralGoogle Scholar
  54. 54.
    Yaguchi T, Sumimoto H, Kudo-Saito C, Tsukamoto N, Ueda R, Iwata-Kajihara T, et al. The mechanisms of cancer immunoescape and development of overcoming strategies. Int J Hematol. 2011;93:294–300.CrossRefPubMedCentralGoogle Scholar
  55. 55.
    Yaguchi T, Kawakami Y. Cancer-induced heterogeneous immunosuppressive tumor microenvironments and their personalized modulation. Int Immunol. 2016;28:393–9.CrossRefPubMedCentralGoogle Scholar
  56. 56.
    Joseph N, Dovedi SJ, Thompson C, Lyons J, Kennedy J, Elliott T, et al. A. Pre-treatment lymphocytopaenia is an adverse prognostic biomarker in muscle-invasive and advanced bladder cancer. Ann Oncol. 2016;27:294–9.CrossRefPubMedCentralGoogle Scholar
  57. 57.
    Zhou WW, Chu YP, An GY. Significant difference of neutrophil-lymphocyte ratio between colorectal cancer, adenomatous polyp and healthy people. Eur Rev Med Pharmacol Sci. 2017;21:5386–91.PubMedPubMedCentralGoogle Scholar
  58. 58.
    Emir S, Aydin M, Can G, Bali I, Yildirim O, Oznur M, et al. Comparison of colorectal neoplastic polyps and adenocarcinoma with regard to NLR and PLR. Eur Rev Med Pharmacol Sci. 2015;19:3613–8.PubMedPubMedCentralGoogle Scholar
  59. 59.
    Ucmak F, Tuncel ET. Relationship between lesions in adenomatous polyp-dysplasia-colorectal cancer sequence and neutrophil-to-lymphocyte ratio. Med Sci Monit. 2016;22:4536–41.CrossRefPubMedCentralGoogle Scholar
  60. 60.
    van Wyk HC, Going J, Horgan P, McMillan DC. The role of perineural invasion in predicting survival in patients with primary operable colorectal cancer: a systematic review. Crit Rev Oncol Hematol. 2017;112:11–20.CrossRefPubMedCentralGoogle Scholar
  61. 61.
    Knijn N, Mogk SC, Teerenstra S, Simmer F, Nagtegaal ID. Perineural invasion is a strong prognostic factor in colorectal cancer: a systematic review. Am J Surg Pathol. 2016;40:103–12.CrossRefPubMedCentralGoogle Scholar
  62. 62.
    Owyong M, Efe G, Abbasi AJ, Sitarama V, Plaks V. Overcoming barriers of age to enhance efficacy of cancer immunotherapy: the clout of the extracellular matrix. Front Cell Dev Biol. 2018;6:19.CrossRefPubMedCentralGoogle Scholar
  63. 63.
    Itatani Y, Kawada K, Inamoto S, Yamamoto T, Ogawa R, Taketo MM, Sakai Y. The role of chemokines in promoting colorectal cancer invasion/metastasis. Int J Mol Sci. 2016;17.  https://doi.org/10.3390/ijms17050643.CrossRefGoogle Scholar
  64. 64.
    Nagarsheth N, Wicha MS, Zou W. Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat Rev Immunol. 2017;17:559–72.CrossRefPubMedCentralGoogle Scholar
  65. 65.
    Lavery IC, De Campos-Lobato LF. How to evaluate risk and identify stage II patients requiring referral to a medical oncologist: a surgeon's perspective. Oncology (Williston Park). 2010;24:14–6.Google Scholar
  66. 66.
    Meyers BM, Cosby R, Quereshy F, Jonker D. Adjuvant chemotherapy for stage II and III colon cancer following complete resection: a Cancer Care Ontario systematic review. Clin Oncol (R Coll Radiol). 2017;29:459–65.CrossRefGoogle Scholar
  67. 67.
    Labianca R, Nordlinger B, Beretta GD, Mosconi S, Mandala M, Cervantes A, Arnold D. Early colon cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2013;24(Suppl 6):vi64–72.CrossRefPubMedCentralGoogle Scholar
  68. 68.
    NCCN. Guidelines Clinical Practice Guidelines in Oncology (NCCN Guidelines) Version 2 2018. https://www.nccn.org/professionals/physician_gls/pdf/colon.pdf. Accessed 2 June 2018.
  69. 69.
    Ding PR, An X, Zhang RX, Fang YJ, Li LR, Chen G, et al. Elevated preoperative neutrophil to lymphocyte ratio predicts risk of recurrence following curative resection for stage IIA colon cancer. Int J Color Dis. 2010;25:1427–33.CrossRefGoogle Scholar
  70. 70.
    Hung HY, Chen JS, Yeh CY, Changchien CR, Tang R, Hsieh PS, et al. Effect of preoperative neutrophil-lymphocyte ratio on the surgical outcomes of stage II colon cancer patients who do not receive adjuvant chemotherapy. Int J Color Dis. 2011;26:1059–65.CrossRefGoogle Scholar
  71. 71.
    Absenger G, Szkandera J, Pichler M, Stotz M, Arminger F, Weissmueller M, et al. A derived neutrophil to lymphocyte ratio predicts clinical outcome in stage II and III colon cancer patients. Br J Cancer. 2013;109:395–400.CrossRefPubMedCentralGoogle Scholar
  72. 72.
    Absenger G, Szkandera J, Stotz M, Postlmayr U, Pichler M, Ress AL, et al. Preoperative neutrophil-to-lymphocyte ratio predicts clinical outcome in patients with stage II and III colon cancer. Anticancer Res. 2013;33:4591–4.PubMedGoogle Scholar
  73. 73.
    Bockelman C, Engelmann BE, Kaprio T, Hansen TF, Glimelius B. Risk of recurrence in patients with colon cancer stage II and III: a systematic review and meta-analysis of recent literature. Acta Oncol. 2015;54:5–16.CrossRefGoogle Scholar
  74. 74.
    Ong ML, Schofield JB. Assessment of lymph node involvement in colorectal cancer. World J Gastrointest Surg. 2016;8:179–92.CrossRefPubMedCentralGoogle Scholar

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© The Author(s). 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Nikoletta Dimitriou
    • 1
  • Evangelos Felekouras
    • 1
  • Ioannis Karavokyros
    • 1
  • Andreas Alexandrou
    • 1
  • Emmanuel Pikoulis
    • 1
  • John Griniatsos
    • 1
  1. 1.Department of SurgeryNational and Kapodistrian University of Athens, Medical School, Laiko HospitalAthensGreece

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