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Research Papers:

The prevalence and clinicopathological features of programmed death-ligand 1 (PD-L1) expression: a pooled analysis of literatures

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Oncotarget. 2016; 7:15033-15046. https://doi.org/10.18632/oncotarget.7590

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Ziying Lin, Yutong Xu, Yaxiong Zhang, Qihua He, Jianrong Zhang, Jianxing He and Wenhua Liang _

Abstract

Ziying Lin1,2,3,*, Yutong Xu1,2,3,*, Yaxiong Zhang1,2,3,4,*, Qihua He1,2, Jianrong Zhang1,2, Jianxing He1,2, Wenhua Liang1,2

1Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China

2Guangzhou Institute of Respiratory Disease & China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China

3Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China

4Department of Medical Oncology of Sun Yat-sen University Cancer Center, Guangzhou, China

*These authors have contributed equally to this work

Correspondence to:

Wenhua Liang, e-mail: [email protected]

Jianxing He, e-mail: [email protected]

Keywords: programmed death-ligand 1, clinicopathological features, cancer, meta-analysis

Received: September 15, 2015    Accepted: January 20, 2016    Published: February 22, 2016

ABSTRACT

Background & Aims: Programmed death-ligand 1 (PD-L1) has been recognized as a critical and promising target in therapies that direct immune escape of cancers. However, its association with aggressive clinicopathological features in solid tumors remains unclear. We investigated this question by synthesizing published articles.

Methods: Electronic databases were searched for relevant studies. Outcomes of interest included age, gender, tumor size, tumor size, lymph node metastasis and tumor cell differentiation.

Results: A total of 61 studies involving 17 types of malignancies were included. The overall expression rate of PD-L1 was 44.5% (95% CI, 37.5% to 51.6 %). Patients with regional lymph node metastases (OR 1.38; P < 0.01), large size tumor (OR 1.89; P < 0.01) or poor differentiated tumors (OR 1.71; P < 0.01) were associated with higher PD-L1 expression rate. However, no significant association was observed between young and elder patients (OR 1.04; P = 0.58), or male and female patients (OR 1.13; P = 0.06). A numerically higher PD-L1 expression rate was detected in polyclonal antibodies (57.2%) than monoclonal antibodies (39.6%). In addition, the PD-L1 expression rate reported by studies from Asian areas (52.3%) was numerically higher than those from non-Asian areas, namely Caucasians (32.7%).

Conclusions: This meta-analysis indicated that patients with larger tumors, regional lymph node metastases, or poor-differentiated tumors were associated with a higher PD-L1 expression rate; in addition the expression rate of PD-L1 in Asians might be higher than that of Caucasians. This information might be useful in screening candidates for relevant tests and treatments.


INTRODUCTION

Programmed cell death ligand 1 (PD-L1), also known as B7 homolog 1 (B7H1), plays a critical role in T cells co-inhibition and exhaustion via the binding with programmed death 1 (PD-1) receptor expressed on activated T cells[1, 2]. Recently, it’s reported that PD-L1 expressed on tumor cells can promote anergy or apoptosis of tumor antigen-specific T-cells, resulting in enhanced tumor cell growth and tumor immune evasion [2, 3].

PD-L1 expression has been observed in various solid tumors, including carcinomas of the esophagus, gastrointestinal tract, pancreas, breast, lung, and kidney [48]. Inhibition of the PD-1/PD-L1 axis may become a promising approach to restore host immunity against these tumors [9, 10].

Recent clinical trials show that blockage of PD-1/PD-L1 pathway with anti-PD-1 or anti-PD-L1 antibodies can produce durable remission in several different malignancies including, but not limited to, melanoma, lung, renal and bladder cancer[1114]. Although the response is remarkable, the response rate is quite low, which means only a small subset of patients benefit from PD-1/PD-L1-directed immunotherapy [15, 16]. Further research has demonstrated that clinical response was closely associated with PD-L1 expression[17]. However, screening the target population is difficult due to a lack of uniform standard in PD-L1 detection [18]. Therefore, determining the subset of patients with positively expressed PD-L1 in tumor cells is of great clinical significance, particularly in light of the autoimmune toxicity of immunotherapy.

A number of recent studies have reported on the clinicopathologic features of PD-L1 positive cancer. However the results of these studies were not consistent and sample sizes were relatively modest. Since PD-L1/PD-1 is a common pathway that functions in a wide spectrum of cancers, we performed a meta-analysis by incorporating all the available evidence to evaluate the association between clincopathological features and PD-L1 expression, aiming to identify those with high PD-L1 expression that may benefit from anti-PD-L1 therapy.

RESULTS

Search results

Our initial search yielded 1158 potential literature citations. Of these, 863 were excluded after scanning titles and abstracts, leaving 295 citations for full-text assessment. Of the 295, 61 studies met the inclusion criteria and were used for this meta-analysis. The remaining studies were excluded largely because of the following reasons: (I) reported data regarding clinicopathological features was not stratified by PD-L1 status, (II) the data was reported in an unsuitable format and therefore unable to be compared to the others studies, or (III) they included data that overlapped with other studies. (Figure 1)

Flow chart of study selection.

Figure 1: Flow chart of study selection.

Characteristics of the studies

Baseline characteristics of the studies included are shown in Table 1. The 61 included studies covered 17 types of epithelial-originated malignancies, including adrenocortical carcinoma (AC) breast cancer (BC), cervical carcinoma (CC), clear cell renal cell carcinoma (CRCC), non-clear cell renal cell carcinoma (NCRCC), colorectal cancer (CRC), esophageal cancer (EC), gastric carcinoma (GC), hepatocellular carcinoma (HCC), head and neck cancer (HNC), non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), pancreatic cancer (PC), plural mesothelium, skin cancer (SK), thymic carcinoma (TC) and urothelial cell carcinoma (UCC). The total number of patients of epithelial-originated cancer was 9212, including 4068 cases of Asian origin. The overall expression rate of PD-L1 was 44.5% (95% CI, 37.5% to 51.6 %). Mouse-originated monoclonal antibody accounted for the vast majority in terms of primary anti-PD-L1/PD-1 antibody. In the subgroup analysis of PD-L1 expression rate (more details are in Table 2), we found a numerically higher PD-L1 expression rate when using polyclonal antibodies 57.2% (95% CI 49.8% to 64.6%) than monoclonal antibodies 39.6% (95% CI 32.8% to 46.3%). In addition, the PD-L1 expression rate reported by studies from Asian areas was numerically higher than those from non-Asian areas, namely Caucasians 52.3% (95% CI 46.9% to 57.6%) and 32.7% (95% CI 24.3% to 41.1%) respectively. Not all studies reported on all variables examined in the meta-analysis; therefore, only studies that reported the variable of interest were analyzed for PD-L1 association with that variable. Funnel plots with the Begg’s tests of different clinicopathological parameters were shown as Supplementary Figure S1.

Table 1: Characteristics of included studies for meta-analysis

Lead author (y)

Tumor type

Patients’ origin

IHC evaluationa

Cut-off value for PD-L1 positive

Antibody

PD-L1 positive/total

PD-L1 positive (%)

Company

Source

Type

Catalog

Fay(2015)

AC

Non-Asia

Percentage

≥5%

NA

NA

MAB

NA

3/28

10.71

GhebehH(2006)

BC

Asia

Percentage

≥5%

eBioscience,USA

Mouse

MAB

clone MIH1

13/44

29.55

Ghebeh H(2008)

BC

Asia

Percentage

≥5%

eBioscience,USA

Mouse

MAB

clone MIH1

19/62

30.65

Mittendorf EA(2014)

BC

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

20/105

19.04

Muenst S(2014)

BC

Non-Asia

H-score

≥100

Abcam, UK

Rabbit

PAB

NA

152/650

23.38

Karim R(2009)

CC

Non-Asia

Percentage

>0

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

22/115

19.13

Droeser RA(2013)

CRC

Non-Asia

H-score

≥200

MBL, USA

Mouse

MAB

clone 27A2

669/1420

47.11

Hua D(2012)

CRC

Asia

H-score

≥200

NA

NA

NA

NA

15/33

45.45

Liang M(2014)

CRC

Asia

H-score

≥20

Santa Cruz Biotechnology, USA

Rabbit

PAB

NA

102/185

55.14

Shi SJ(2013)

CRC

Asia

H-score

≥200

Abcam, UK

Rabbit

PAB

ab58810

64/143

44.76

Zhang MY(2012)

CRC

Asia

Percentage

≥10%

NA

NA

NA

NA

26/57

45.61

Zhao LW(2014)

CRC

Asia

H-score

≥20

eBioscience,USA

Mouse

MAB

clone MIH1

27/56

48.21

Krambeck AE(2007)

CRCC

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

70/298

23.49

Thompson RH(2005)

CRCC

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

103/196

52.55

Thompson RH(2006)

CRCC

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

73/306

23.86

Thompson RH(2007)

CRCC

Non-Asia

Percentage

≥10%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

142/267

53.18

Loos M(2011)

EC

Non-Asia

H-score

≥66

Abcam, UK

Rabbit

PAB

NA

37/101

36.63

Ohigashi Y(2005)

EC

Asia

Percentage

≥10%

eBioscience,USA

Mouse

MAB

clone MIH1

18/41

43.9

Shohei Eto(2015)

GC

Asia

H-score

≥51

Abcam, Cambridge, UK

Rabbit

MAB

ab174838

28/105

26.7

Geng Y(2014)

GC

Asia

H-score

≥22

Novus, USA

Mouse

MAB

clone 2H11

65/100

65

Hou J(2014)

GC

Asia

Percentage

≥10%

Abcam, UK

Rabbit

PAB

NA

70/111

63.06

Wu C(2006)

GC

Asia

NA

NA

Novus, USA

Mouse

MAB

clone 2H11

43/102

42.16

Gao Q(2009)

HCC

Asia

H-score

≥75th percentile

eBioscience,USA

Mouse

MAB

clone MIH1

60/240

25

Wang BJ(2011)

HCC

Asia

H-score

≥10

eBioscience,USA

Mouse

MAB

clone MIH1

24/26

92.31

Cho YA(2011)

HNC

Asia

H-score

≥Median

Abcam, UK

Rabbit

PAB

ab82059

26/45

57.78

Oliveira-Costa JP(2015)

HNC

Non-Asia

NA

NA

NA

NA

NA

NA

47/96

48.96

Ukpo OC(2013)

HNC

Asia

Percentage

≥5%

NA

NA

MAB

clone A3

84/181

46.41

Zhang F(2008)

HNC

Asia

Percentage

≥10%

Boster, China

Rabbit

PAB

BA2495

40/59

67.8

Choueiri(2014)

NCRCC

Non-Asia

Percentage

≥5%

Dana-Farber Cancer Institute, Boston, MA

mouse

MAB

405.9A11

11/101

10.89

Azuma K(2014)

NSCLC

Asia

H-score

>30

Lifespan Biosciences, WA

Rabbit

PAB

NA

82/164

50

Boland JM(2013)

NSCLC

Non-Asia

Percentage

≥5%

Laboratory developed

NA

NA

clone 5H1

42/214

19.63

Chen YB(2012)

NSCLC

Asia

H-score

≥3

Abcam, HK

Rabbit

PAB

clone 236A/E7

69/120

57.5

Chen YY(2013)

NSCLC

Asia

H-score

>9

Abcam, HK

Rabbit

PAB

NA

136/208

65.38

Cooper, W. A(2015)

NSCLC

Non-Asia

percentage

≥50%

Merck

Mouse

MAB

clone22C3

628/678

92.6

D’Incecco(2015)

NSCLC

Non-Asia

H-score

≥10

Abcam, UK

Rabbit

PAB

ab58810

68/123

55.3

Jiang(2015)

NSCLC

Asia

Percentage

≥5%

Abcam, UK

Rabbit

PAB

NA

50/79

63.29

Kim(2015)

NSCLC

Asia

H-score

≥30

Cell Signaling Technology, Danvers, MA, USA

NA

MAB

E1L3N

89/331

26.89

Mu CY(2011)

NSCLC

Asia

H-score

≥Median value

NA

NA

MAB

NA

58/109

53.21

Velcheti V(2014)

NSCLC (Yale U. cohort)

Non-Asia

DIA

NA

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

56/155

36.13

Velcheti V(2014)a

NSCLC(Greek cohort)

Non-Asia

DIA

NA

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

75/303

24.75

Yang CY(2014)

NSCLC

Asia

Percentage

≥5%

Proteintech Group Inc.,USA

Rabbit

PAB

17952-1-AP

65/163

39.88

Yih-Leong Chang(2015)

NSCLC

Asia

NA

NA

Proteintech Group Inc

Rabbit

PAB

NA

50/66

75.76

Zhang Y(2014)

NSCLC

Asia

H-score

≥60

Sigma-Aldrich, USA

Rabbit

PAB

SAB2900365

70/143

48.95

Ishii(2015)

SCLC

Asia

Percentage

≥5%

Abcam, UK

Rabbit

PAB

NA

73/102

71.56

Chen XL(2009)

PC

Asia

Percentage

≥10%

Novus, USA

Mouse

MAB

clone 2H11

18/40

45

Geng L(2008)

PC

Asia

Percentage

≥10%

R&D systems

Mouse

MAB

Clone130002

23/40

57.5

Nomi T(2007)

PC

Asia

Percentage

≥10%

eBioscience,USA

Mouse

MAB

clone MIH1

20/51

39.22

Wang L(2010)

PC

Asia

Percentage

≥5%

eBioscience,USA

Mouse

MAB

clone MIH1

40/81

49.38

SusanaCedrés(2015)

Plural mesothelium

Non-Asia

Percentage

≥1%

Cell Signaling Technology, Danvers, MA, USA

Rabbit

MAB

cloneE1L3N

16/77

20.78

Gadiot J(2011)

SC (Melanoma)

Non-Asia

Percentage

≥1%

R&D Systems,USA

Mouse

MAB

156-B7-100

16/63

25.4

Hino R(2010)

SC (Melanoma)

Asia

DIA

RDb≥90

MBL, Japan

Mouse

MAB

clone 27A2

34/59

57.63

Oba J(2014)

SC (Melanoma)

Asia

Percentage

≥5%

eBioscience,USA

Mouse

MAB

clone MIH1

36/77

46.75

Taube JM(2012)

SC (Melanoma)

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

57/150

38

Lipson EJ(2013)

SC (Merkel cell carcinoma)

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

24/49

48.98

Katsuya (2015)

TC

Asia

H-score

3

Cell Signaling Technology, Danvers, MA, USA

Rabbit

MAB

NA

48/139

34.53

Boorjian SA(2008)

UCC

Non-Asia

Percentage

≥5%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

39/314

12.42

Faraj (2015)

UCC

Non-Asia

Percentage

≥5%

NA

Mouse

MAB

clone 5H1

10/56

17.86

Inman BA(2007)

UCC

Non-Asia

Percentage

≥1%

Lieping Chen, Yale University

Mouse

MAB

clone 5H1

77/280

27.5

Nakanishi J(2006)

UCC

Asia

Percentage

≥2.1%

eBioscience,USA

Mouse

MAB

clone MIH1

46/65

70.77

Wang Y(2009)

UCC

Asia

Percentage

>10%

Santa Cruz Biotechnology, USA

Rabbit

PAB

NA

36/50

72

Wang YH(2014)

UCC

Asia

Percentage

≥10%

Boster, China

Rabbit

PAB

BA2495

43/60

71.67

a H-score = SI (staining intensity) × PP (percentage of positive cells). SI was determined as: 0, negative; 1, weak; 2, moderate; and 3, strong. PP was defined as: 0, negative; 1-100, 1-100% positive cells

b Digitized specimens were exported to JPG files by using NDP View software (Hamamatsu Photonics). Three different areas from the tumor cell cytoplasm were selected and expressed as Red channel histograms. Histograms revealed 255 different shades from pitch black (0) to pure white (255), and a number represented the level of brightness of each color. RD (red density) values represent the mean of each color

Abbreviations: AC = adrenocortical carcinoma; BC = breast cancer; CC = cervical carcinoma; CRCC = clear cell renal cell carcinoma; NCRCC = non-CRCC; CRC = colorectal cancer; EC = esophageal cancer; GC = gastric carcinoma; HCC = hepatocellular carcinoma; HNC =head and neck cancer; SCLC = small cell lung cancer; NSCLC = non-SCLC; PC = pancreatic cancer; SC=skin cancer; TC = thymic carcinoma; UCC = urothelial cell carcinoma; DIA = digital image analysis; IHC = immunohistochemistry; MAB = monoclonal antibody; NA = not available; PAB= polyclonal antibody; PD-L1 = Programmed cell death ligand 1.

Table 2: Summary of PD-L1 expression rate in subgroup analysis

Subgroup

No. of studies

PD-L1 expresson rate (95% CI) / %

Subgroup

No. of studies

PD-L1 expression rate (95% CI) / %

Tumor type

Patients’ origin

adrenocortical carcinoma

1

10.7 (-0. 7-22.1)

Asian

37

52.3 (46.9-57.6)

Breast cancer

4

23.7 (19.9-27.4)

Non-Asian

24

32.7 (24.3- 41.1)

Cervical carcinoma

1

19.1 (11.9-26.3)

Antibody-Type

Clear cell renal cell carcinoma

4

38.1 (22.0-54.2)

Monoclonal antibody

39

39.6 (32.8-46.3)

Non-clear cell renal cell carcinoma

1

10.9 (4.8-17.0)

Polyclonal antibody

18

57.2 (49.8-64.6)

Colorectal cancer

6

47.7 (45.4-49.9)

IHC evaluation

Esophageal cancer

2

38.6 (30.7-46.6)

Percentage

35

42.8 (31.5-54.2)

Gastric carcinoma

4

49.2 (30.8-67.6)

H-score

20

47.7 (40.5-54.9)

Hepatocellular carcinoma

2

58.5 (-7.5-124.5)

DIA

3

24.9 (20.4-29.3)

Small cell lung cancer

1

71.6 (62.8-80.3)

NA

3

55.6 (35.7-75.4)

Non-small cell lung cancer

13

51.7 (33.1-70.3)

IHC evaluation-Percentage

Pancreatic cancer

4

47.6 (40.5-54.6)

Cut-off = 5%

19

34.3 (26.5-42.1)

plural mesothelium

1

20.8 (11.7-29.8)

Cut-off = 10%

10

56.5 (49.5-63.6)

Head and neck cancer

4

54.4 (44.8-60.0)

Others

6

42.9 (7.3-78.5)

Skin cancer

5

42.8 (32.5-53.1)

IHC evaluation-H-score

Thymic carcinoma

1

34.5 (26.6-42.4)

Cut-off ≤ 50

10

54.8 (43.1-66.5)

Urothelial carcinoma

6

44.9 (24.4-65.4)

Cut-off > 50

8

37.1 (27.8-46.5)

Abbreviations: CI = confidence interval; IHC = immunohistochemistry; DIA = digital image analysis; NA = not available; PD-L1 = programmed cell death 1ligand 1.

Correlation of PD-L1 expression and clinicopathological features

Age

Twenty-nine studies, including 3845 patients, were analyzed for the association between PD-L1 expression and age. Of 1909 elder patients, 821 (43.0%) were PD-L1 expression positive, and 821 (42.4%) of 1936 younger patients were PD-L1 expression positive. No significant association was found between PD-L1 expression and age (OR 1.04, 95% CI 0.90 to 1.20; P = 0.58) (Figure 2A).

Forest plot for the association between PD-L1 expression and clinicopathological features.

Figure 2: Forest plot for the association between PD-L1 expression and clinicopathological features. A. age, B. gender. Events refer to cases with PD-L1 positive expression. ORs with corresponding 95 % CIs of individual studies and overall are shown in the forest plot. Abbreviations: OR = odds ratio; CI = confidence interval; LNM= lymph node metastasis; PD-L1= Programmed cell death ligand 1. C. tumor size, D. lymph node metastasis. Events refer to cases with PD-L1 positive expression. ORs with corresponding 95 % CIs of individual studies and overall are shown in the forest plot. Abbreviations: OR = odds ratio; CI = confidence interval; LNM= lymph node metastasis; PD-L1= Programmed cell death ligand 1. E. tumor cell differentiation. Events refer to cases with PD-L1 positive expression. ORs with corresponding 95 % CIs of individual studies and overall are shown in the forest plot. Abbreviations: OR = odds ratio; CI = confidence interval; LNM= lymph node metastasis; PD-L1= Programmed cell death ligand 1.

Gender

Thirty-eight studies, including 6675 patients, were analyzed for the association between PD-L1 expression and gender. Of 4309 male patients, 2298 (53.3%) were PD-L1 expression positive, and 1404 (59.3%) of 2366 female patients were PD-L1 expression positive. No significant association was found between PD-L1 expression and gender (OR 1.13, 95% CI 0.99 to 1.29; P = 0.06) (Figure 2B).

Tumor size

The association between PD-L1 expression and size of tumor was analyzed in Thirty-eight studies, including a total of 6273 patients. Of 3417 tumors of large size, 1953 (57.6%) were PD-L1 expression positive, and 1070 (37.5%) of 2856 small size tumors were PD-L1 expression positive. There was a significant association betweenPD-L1 expression and tumors of large size (OR 1.89, 95% CI 1.66 to 2.16; P < 0.01) (Figure 2C).

Lymph node metastasis

Thirty-four studies, including 6300 patients, were analyzed for the association between PD-L1 expression and lymph node metastasis. Of 2530 lymph node-positive patients, 1354 (53.5%) tested positive for PD-L1 expression, and 1443 (38.3%) of 3770 lymph node-negative patients tested positive for PD-L1 expression. A significant association was found between PD-L1 expression and the presence of lymph node metastases (OR 1.38, 95% CI 1.20 to 1.58; P < 0.01) (Figure 2D).

Differentiation

Twenty-three studies, including 4735 patients, were analyzed for the association of PD-L1 expression and differentiation of tumor cells. Of 1791 patients with poor tumor differentiation (grade III), 668 (37.3%) were PD-L1 expression positive, and 880 (29.9%) of 2944 patients with well differentiation (grade I/II) were PD-L1 expression positive. A significant association exists between PD-L1 expression and tumor cell differentiation (OR 1.71, 95% CI 1.48 to 1.98; P < 0.01) (Figure 2E).

Subgroup analysis

Further subgroup analysis was performed by stratifying the studies according to the patients’ origins (Asian & Non-Asian), primary anti-PD-L1 antibodies (monoclonal antibody & polyclonal antibody), IHC evaluation for PD-L1 (percentage & H-score), cut-off values for percentage (5% & 10%) and H-score (≤ 50 & > 50). The conclusions drawn from the subgroup analyses are similar to that of the overall analysis (more details are listed in Table 3).

Table 3: Summary of subgroup analyses results in studies reported PD-L1 status stratified by clinicopathlogical features

Subgroup

No. of studies; OR [95% CI]

Age

Gender

Tumor size

Differentiation

LNM

Patients’ origin

Asian

24; 1.03 [0.87, 1.22]

26; 1.19 [1.01, 1.41]

27; 1.75 [1.48, 2.08]

14; 1.58 [1.24, 2.02]

20; 1.53 [1.26, 1.87]

Non-Asian

5; 1.07 [0.82, 1.41]

12; 1.05 [0.85, 1.29]

11; 2.13 [1.73, 2.62]

9; 1.78 [1.49, 2.14]

14; 1.24 [1.02, 1.50]

Primary anti-PD-L1 antibodies

Monoclonal antibody

15; 1.04 [0.86, 1.26]

21; 1.11 [0.94, 1.32]

24; 1.85 [1.57, 2.19]

13; 1.62 [1.34, 1.96]

23; 1.16 [0.96, 1.41]

Polyclonal antibody

13; 1.08 [0.86, 1.34]

16; 1.18 [0.96, 1.45]

13; 2.00 [1.61, 2.48]

9; 1.73 [1.37, 2.18]

11; 1.68 [1.37, 2.06]

IHC evaluation

Percentage

12; 0.98 [0.76, 1.26]

18; 1.16 [0.95, 1.41]

22; 2.16 [1.79, 2.61]

12; 2.61 [2.07, 3.31]

16; 1.61 [1.23, 2.10]

H-score

11; 1.09 [0.88, 1.34]

14; 1.14 [0.93, 1.39]

14; 1.58 [1.30, 1.91]

10; 1.32 [1.09, 1.61]

12; 1.37 [1.13, 1.65]

IHC evaluation-Percentage

Cut-off = 5%

7; 0.97 [0.70, 1.34]

10; 1.17 [0.92, 1.48]

13; 2.15 [1.71, 2.71]

5; 3.50 [2.45, 4.98]

11; 1.82 [1.31, 2.53]

Cut-off = 10%

5; 0.99 [0.67, 1.46]

6; 1.12 [0.71, 1.77]

10; 2.31 [1.66, 3.20]

6; 1.84 [1.28, 2.64]

4; 1.66 [1.00, 2.78]

IHC evaluation-H-score

Cut-off ≤ 50

7; 1.20 [0.92, 1.57]

8; 1.17 [0.90, 1.52]

6; 1.30 [0.96, 1.76]

3; 1.82 [1.16, 2.87]

4; 1.20 [0.86, 1.69]

Cut-off > 50

2; 0.94 [0.59, 1.49]

5; 1.12 [0.81, 1.54]

7; 1.81 [1.41, 2.33]

5; 1.14 [0.91, 1.43]

6; 1.50 [1.17, 1.91]

Abbreviations: CI = confidence interval; OR = Odds ratio; IHC = immunohistochemistry; LNM = lymph node metastasis; PD-L1 = programmed cell death 1ligand 1.

DISCUSSION

For patients with epithelial-originated malignancies, the association between clinicopathological features and PD-L1 expression remains unclear. A meta-analysis incorporating all available data from correlative studies is a reasonable method to clarify this issue. Through the completion of this meta-analysis we found that epithelial-originated cancer with regional lymph node metastasis, large size tumors, or well differentiated tumors were associated with higher PD-L1 expression rate. We also found that polyclonal antibodies detected a numerically higher PD-L1 expression rate than monoclonal antibodies. Additionally, PD-L1 expression rates reported in studies from Asian areas were numerically higher than those from non-Asian areas namely Caucasians.

We might infer the following as the basis for the positive correlation of PD-L1 expression with large tumor size and lymph node metastasis: under normal conditions, the genetic and epigenetic alterations can distinguish the cancer cells from the normal counterparts, allowing tumors to be recognized and repelled as foreign by the immune system [19]. When PD-L1 is highly expressed on tumor cells, its engagement with PD-1, an important co-inhibitor on the T cell, can block the T cell cytotoxicity and lead to T-cell exhaustion[9]. Binding of PD-L1 to PD-1 on naive tumor-infiltrating lymphocytes (TILs) can arrest the process of antigen presenting at the effector phase and suppress T-cell activation, migration, proliferation and secretion of cytotoxic mediators. Interaction of PD-L1 with PD-1 can also increase apoptosis of tumor specific CD8+ cells [20]. What’s more, PD-L1 acts not only as a ligand of PD-1, but can also serve as a receptor transmitting reverse signals that protect cancers cells from apoptosis mediated by FAS-FASL pathway [21]. These actions of PD-L1 expressed on the tumor can thereby dampen the antitumor immunity and contribute the over growth and metastasis of the tumor cells.

The positive correlation between PD-L1 expression and poor differentiation of tumors found in this meta-analysis is consistent with the majority of other studies, though the underlying mechanism remains unclear. Poor differentiation may be associated with over proliferating effect of the PD-L1 positive tumor cells. Quite a lot published evidences have shown that PD-L1 expression promote tumor cell proliferation indirectly through both exogenous and intrinsic pathway. On one hand, exogenous stimulus delivered by the pro-inflammatory cytokines in the inflammatory microenvironment can trigger the receptor mediated signaling molecules within the tumor cells (including NF-κB, MAPK, PI3K, mTOR, and JAK/STAT) that promote cell proliferation, and induce PD-L1 expression as well [22]. On the other hand, some intrinsic oncogenic pathway (like anaplastic lymphoma kinase in lung cancer [23], loss of tumor suppressor phosphate and tension homolog in pancreatic cancer [24] etc.) have been reported to drive PD-L1 expression and, in the meanwhile, are involved in key cellular functions such as proliferation, growth, and survival [2527]. Over proliferation of the tumor cells is usually accompanied with cellular de-differentiation, which explains the positive correlation between poor differentiation and PD-L1 over expression of the tumor cells.

With regard to the immune evasion of solid tumor mediated by PD-1/PD-L1 immune-checkpoint pathway, a series of specific inhibitors are currently under investigation and in clinical development such as nivolumab, a fully human IgG4 PD-1 immune checkpoint inhibitor antibody, pembrolizumab (formerly known as MK-3475 or lambrolizumab), a high affinity humanized IgG4 monoclonal antibody targeting PD-1, and MPDL3280A, an engineered IgG anti-PD-L1 antibody [11, 12, 15, 28]. Among these, pembrolimumab and nivolumab [29, 30] have been approved by the US Food and Drug administration (FDA) in the treatment of advanced melanoma and non-small cell lung cancer for their remarkably durable clinical response. Along with that, two different immunohistochemical (IHC) assays that linked to the use of pembrolizumab and nivolumab will come into the market for PD-L1 expression detection[31]. Although the therapeutic effect of anti-PD-1/PD-L1 treatment is unprecedented, the response rate in the context of unselected population affected by advanced solid tumors was barely satisfactory, ranging from 10% to 45% [3234]. In light of the expense and adverse effects of anti-PD-1/PD-L1 therapy, further exploration is warranted to identify the proportion of patients most likely to benefit from the immunotherapy and thus optimize their therapeutic index. More and more evidences indicated that PD-L1 expression level in tumor cells is positively correlated with the response rate [17, 35]. It’s well known that epidermal growth factor receptor gene (EGFR) mutation status has a similar predictive role in the efficacy of EGFR-targeting therapy for patients with non-small cell lung cancer (NSCLC) [34]. But what differs PD-L1 from the EGFR protein is the lack of a clear-cut gene-mediated pathway that exclusively contributes to the over expression of PD-L1. That means we can’t precisely identify PD-L1 status at the gene level as multiple (intrinsic and extrinsic) signaling pathways are involved in the induction of PD-L1 expression [37]. As for the quantitative or semi-quantitative detection of PD-L1 by immunohistochemistry (IHC), its reliance and reproducibility is still disputed due to the lack of uniform antibody and cut-off values, which consequently restricts its application in screening candidate patients for the immunotherapy. What’s more, PD-L1 expression may change dynamically during the process of tumor progression. It’s unreliable to decide PD-L1 status by IHC detection at a single time point. Considering the dilemma of PD-L1 detection in clinical practice, a more practical way of patients’ stratification is warranted. The elucidation of the relationship between PD-L1 expression and clinicopathological parameters in this meta-analysis provides a convenient way to identify patients that are most likely to have a high level of PD-L1 expression on the tumor cells and thus provides rationale for patients’ stratification in clinical practice. According to our pooled analysis, patients with larger tumor size, lymph node metastasis, or poorly differentiated tumors tend to have higher level of PD-L1 expression; these patients may benefit more from treatment targeting PD-1/PD-L1 pathway. What’s more, as these clinicopathological parameters are also associated with advanced stage and poor prognosis, our results rationalize the application of anti-PD-1/PD-L1 immunotherapy in patients with advanced tumors that currently lack effective treatment options. It also indirectly proves that PD-L1 over expression is associated with poor prognosis of solid tumors as demonstrated by previous studies [38].

The higher expression rate of PD-L1 among patients of Asian origin, as shown in our results, may be associated with higher frequencies of virus-associated malignancies in Asian areas. PD-L1 over expression has been reported to be associated with viral infection and chronic inflammation [39]. Intratumoral expression of PD-L1 and/or PD-1 has been shown in polyomavirus-associated Merkel cell carcinoma [40], hepatitis B virus(HBV)-related hepatocellular carcinoma [41], human papillomavirus(HPV)-associated head and neck cancer [42], Epstein Barr Virus(EBV)-associated nasopharyngeal cancer [43] and so on. Our result implies that the immune associated PD-1/PD-L1 may play a significant role in the development and progression of virus associated cancer.

To the best of our knowledge, this is the first study to comprehensively demonstrate the relationship between PD-L1 status and clinicopathological parameters of solid tumors. However, several limitations existed: (I) Different tumors may have different biologic behaviors, but we failed to conduct this particular subgroup analysis as data for some tumor types was insufficient; (II) Cut-off values distinguishing high or low levels of PD-L1 expression determined by IHC evaluation and the primary antibodies varied in different types of tumors, which might cause heterogeneity of the overall results; (III) Different studies adopt different thresholds for the size of large tumors, as well as the age for elder patients, which can also lead to the heterogeneity of the pooled result. (IV) As a result of the lack of sufficient data, we were unable to evaluate the relationship between clinicopathological parameters and PD-1/PD-L1 status on the tumor infiltrating lymphocytes (TILs) which is also associated with immune evasion of tumor and responsiveness of immunotherapy.

Regardless of the above limitations, this comprehensive analysis demonstrates the relationship between PD-L1 expression and clinicopathological features of solid tumors. The results may lead to improvement in the outcome of anti-PD-1/PD-L1 therapy by guiding patients’ stratification in a convenient way. Further large-scale clinical studies should be performed to demonstrate the association between PD-L1 expression and clinicopathological characteristics in the subgroups of different tumor types. Further effort is also warranted to investigate the relationship between PD-1/PD-L1 status on TILs.

In summary, meta-analysis of the literature shows that PD-L1 over expression on the tumor cells correlates with poor prognostic features including large tumor size, lymph node metastasis and poor differentiation of solid tumors. The PD-L1 expression rate in Asians might be higher than that in Caucasians. This information might prove to be helpful in screening candidates for relevant treatments.

MATRIALS AND METHODS

Search strategy

We conducted a systematic search of PubMed, Embase, and Cochrane databases for articles published from inception to July 2015. The following keywords were used: “PD-L1” or “B7-H1” or “CD274” or “PD-1” or “CD279” or “programmed cell death 1” combined with “cancer” or “tumor” or “carcinoma” with limits “human”. An additional search through Google Scholar and a manual search through reference lists of relevant reviews were additionally performed. Three authors (ZY, KS and SJ) independently carried out the search. As Chinese investigators, we restricted our searches to studies published in either English or Chinese.

Inclusion and exclusion criteria

Eligible studies fulfilled the following inclusion criteria: (i) original articles; (ii) the expression level of PD-L1 is tested by immunohistochemistry (IHC) staining on tumor cell specimens; (iii) data of the binary clinicopathological factors stratified by PD-L1 status were available. Studies that failed to meet the inclusion criteria were excluded.

Data extraction

The data collection and assessment of methodological quality followed the QUORUM and the Cochrane Collaboration guidelines (http://www.cochrane.de). The data on lead author, publication year, tumor type, patients’ characteristics, patient origin, primary antibody, and PD-L1 status, clinicopathological features stratified by PD-L1 status were extracted by two investigators (LZY and XYT) independently. For uniformed data analysis, T1 was considered as small size, and T2, T3, and T4 as large size for CRC, EC and UC. For the histological grade, grades I and II (well/moderate differentiation) were grouped together vs grade III (poor differentiation). We defined large tumors in other tumor types and elder patients according to the criteria of each individual study. Reviewers (LZY and XYT) used the Newcastle-Ottawa scale specific to cohort study to assess all included studies. Discrepancies were discussed by all investigators to reach consensus. All eligible studies were of high quality.

Statistical analysis

Analysis was performed using Stata 12.0 (Stata Corporation, Texas, US) and Review Manager 5.2 (Cochrane Collaboration, Oxford, UK). The relationship between PD-L1 expression rate and antibody types, patients’ origin, and IHC evaluation methods were investigated using independent statistical t-test respectively. Comparisons of dichotomous measures were performed by pooled estimates of odds ratios (ORs), as well as their 95% CI. Subgroup analysis was conducted according to patients’ origin, primary antibody (monoclonal antibody & polyclonal antibody) and IHC evaluation method (even in different cut-off values for PD-L1 positive) respectively. All CIs had two-sided probability coverage of 95%. A statistical test with P-value less than 0.05 was considered significant.

Publication bias

An extensive search strategy was made to minimize the potential publication bias. Graphical funnel plots were generated to visually assess publication bias. The statistical method to detect funnel plot asymmetry was the Begg’s test.

FUNDING

  1. Guangdong Doctoral Launching Program, Grant No. 2014A030310460;

  2. Doctoral Launching Program of Guangzhou Medical University, Grant No. 2014C27;

  3. Guangzhou Health and Medical Collaborative Innovative Major Special Projects, Grant No. 201400000001-2;

  4. Study of Genome-test guided comprehensive individualized diagnose and treatment of lung cancer. Grant No. B1504001.

CONFLICTS OF INTEREST

There are no conflicts of interests to declare.

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