Literature DB >> 30237743

Checkpoint molecule PD-1-assisted CD8+ T lymphocyte count in tumor microenvironment predicts overall survival of patients with metastatic renal cell carcinoma treated with tyrosine kinase inhibitors.

Jiaxi Yao1, Wei Xi1, Yanjun Zhu1, Hang Wang1, Xiaoyi Hu1, Jianming Guo1.   

Abstract

PURPOSE: The aim of this study was to determine whether CD8+ T lymphocyte and its checkpoint-associated module programmed cell death protein 1 (PD-1)/main ligand of PD-1 (PD-L1) pathway impact overall survival (OS) in patients with metastatic renal cell carcinoma (mRCC) treated with tyrosine kinase inhibitors (TKIs).
MATERIALS AND METHODS: A total of 231 mRCC patients, from 2007 to 2017, treated with sunitinib or sorafenib in Zhongshan Hospital, Fudan University were included in the study analyses. CD8, PD-1, and PD-L1 was assessed by immunohistochemistry on continuous paraffin-embedded slides. Kaplan-Meier method and COX regression model were applied in the survival analyses.
RESULTS: Baseline characteristics were comparable between the training (n=118) and validation (n=113) sets. Patients with high CD8+ T lymphocytes infiltration and low PD-1 expression had longer survival in both sets (P=0.0106 and P=0.0047 in training set, P=0.0291 and P=0.0011 in validation set, respectively). However, survival stratified by PD-L1 was only insignificant or marginally significant. Multivariable analyses verified that CD8+ T lymphocytes, together with PD-1, but not tumor infiltrating mononuclear cells or tumor cells PD-L1, were independent prognostic factors (training set [HR 3.202, 95% CI 1.433-7.153, P=0.011] and validation set [HR 4.012, 95% CI 2.354-6.838, P<0.001]). Subsequent analysis revealed that the PD-1 high/CD8 low group had shorter survival (16 months) than PD-1 low/CD8 high group (51 months, P<0.0001). Combining the International Metastatic Renal Cancer Database Consortium system with the PD-1/CD8 model exhibited much better accuracy for the prediction of OS.
CONCLUSION: Our findings suggest that abundant CD8+ T cells are significantly associated with longer OS in mRCC patients treated with TKIs. The most influential checkpoint-associated molecule, PD-1, assisted CD8+ T cell-stratified patients and could be used as a better predictive and prognostic factor for the mRCC patients.

Entities:  

Keywords:  immune checkpoint; metastatic renal cell carcinoma; prognostic factor; tyrosine kinase inhibitors

Year:  2018        PMID: 30237743      PMCID: PMC6138960          DOI: 10.2147/CMAR.S172039

Source DB:  PubMed          Journal:  Cancer Manag Res        ISSN: 1179-1322            Impact factor:   3.989


Introduction

Renal cell carcinoma (RCC) is the second most common malignancy in the urinary system. The incidence and mortality of RCC seem to be rising, resulting in >14,970 deaths every year because of metastatic disease. The morbidity of RCC is twice in men compared with women.1 About 30% of the patients have metastatic disease at the time of diagnosis of RCC which results in poorer overall survival (OS) of the patients.2 The diagnosis of RCC is usually performed by ultrasonography, computed tomography (CT) scan, and MRI.3 Despite recent major progress in therapeutic strategies, including surgery, and targeted molecular therapies, the long-term survival remains poor due to distant metastases. Tyrosine kinase inhibitors (TKIs), targeting vascular endothelial growth factor (VEGF) signaling, are recommended as first-line systemic treatment for metastatic renal cell carcinoma (mRCC) patients, which has shown remarkably prolonged patient survival.4 Few models were developed to assess the prognostic factors for OS in patients with mRCC treated with TKIs.5 Tumor infiltrating lymphocytes (TILs), CD8+ T cells play a major role in tumor immune responses and are considered to have anticancer activity. Furthermore, it has been shown to be the most important prognostic factor in different solid tumors.6,7 A study by Weiss et al reported that CD8+ T cells infiltration was associated with long-term survival in patients with RCC.8 Although Nakano et al for the first time demonstrated a negative impact of CD8+ T cells, they found that Ki67+/CD8+ T cell, representing the proliferative CD8+ T cell, had protective effects.9 Programmed cell death protein 1 (PD-1) is a cell surface receptor molecule on the activated TILs, which interact with tumor cells (TC) and are involved in tumor-specific immune responses.10 PD-L1, the main ligand of PD-1, is expressed in peripheral tissues, including the tumor. In proinflammatory conditions, the molecular interaction between PD-1 and PD-L1 induces a co-inhibitory signal and decreases the level of cytokines, which subsequently results in the apoptosis of the effector T lymphocytes. This function can be translated into resistance to immunotherapy or TKIs.11 Therefore, T cell exhaustion/inhibition greatly impairs antitumor immunity and plays an important role in cancer progression. In the regulation of antitumor cytotoxicity of T cells, checkpoint-associated molecules PD-1 and its ligand (PD-1/PD-L1) pathway was best elaborated. Meanwhile, this pathway also showed significant value in TKI resistance.12,13 Therefore, our study determines whether CD8+ T lymphocyte and its checkpoint-associated module PD-1/PD-L1 pathway impact OS in patients with mRCC treated with TKIs.

Materials and methods

Patient selection

A total of 250 mRCC patients treated with sunitinib or sorafenib at Zhongshan Hospital, Fudan University between 2007 and 2017 were retrospectively reviewed. Of these, 19 patients were excluded for inadequate clinicopathological or follow-up data. The study was officially approved by the Ethics Committee of Zhongshan Hospital and written informed consent was obtained from each patient. The baseline characteristics were acquired from the medical records.

Evaluation

Initial disease stage was ascertained following the eighth Union for International Cancer Control TNM edition classification criteria.14 According to the International Society of Urological Pathology grading system (2016), the archived H&E stained slides were reviewed.15 Furthermore, metastases were determined by CT or MRI. The International Metastatic Renal Cancer Database Consortium (IMDC) model was used to stratify risk after metastasis. The responses to TKI treatment were evaluated according to the Revised Response Evaluation Criteria in Solid Tumors guidelines (version 1.1).16 Expression level of each staining was independently assessed by two senior pathologists, without knowing any clinical or survival information.

Immunohistochemistry for immune checkpoint-associated molecules and TILs

Continuous slides of formalin-fixed, paraffin-embedded tissues were used for immunohistochemical staining. The slides were heated at 60°C for 2 hours, dewaxed in xylene, and dehydrated by a gradient concentration of alcohol. After retrieving and blocking the endogenous peroxidase and nonspecific staining with 3% (v/v) hydrogen peroxide and normal goat serum, the sections were incubated with anti-primary antibody overnight at 4°C. The slides were then incubated with horseradish peroxidase-conjugated goat anti-mouse IgG secondary antibody for 30 minutes at 37°C. Finally, they were visualized by DAB solution (Dako Denmark A/S, Glostrup, Denmark) and counterstained with hematoxylin. The quantity of positively stained cells was measured independently by two pathologists, who were blind to outcomes of the patient. Mouse anti-human CD8 (ab17147; Abcam, Cambridge, UK), mouse anti-human PD-1 (ab52587, Abcam), and rabbit anti-human PD-L1 (ab205921, Abcam) were some of the primary antibodies used for immunohistochemistry. Each full-face tumor section was assessed for TILs within the TC using microscopic examination. Five independent areas, excluding those with necrosis and inflammation, were selected and photographed using a virtual digital slide scanner (Leica Microsystems, Wetzlar, Germany). The PD-L1 expression was measured on both lymphocytes and TC. The percentages of TC that were stained positive for PD-L1 were assessed according to the extent and intensity of membranous staining on the TC. The staining was scored as 0, no expression or expression in TC <5%; 1, weak expression in TC >5%; 2, moderate expression in TC >5%; and 3, strong expression in TC >5%. The TC samples were subsequently subdivided into TC positive (those with scores of 2–3) and TC negative (those with scores of 0–1). An adjusted score representing lymphocyte PD-L1 expression was calculated as absent (0), focal (1), mild (2), moderate (3), and severe (4). The lymphocytes with scores of 2–4 were considered as lymphocyte PD-L1-positive and lymphocytes with score 0 or 1 were considered as lymphocyte PD-L1-negative. OS was defined as the time interval between TKI treatment initiation and death or censoring at last followup. Progression-free survival was defined as the time interval between TKI treatment initiation and disease progression.

Statistical analysis

Chi-squared tests were used to compare categorical variables. Survival curves were generated using the Kaplan–Meier method and a log-rank test was used to test for differences between survival curves. The multivariate Cox proportional hazard regression model was used for survival analyses. Receiver operating characteristic (ROC) analysis was used to assess model accuracy. All analyses were conducted in SPSS (version 21.0; IBM Corporation, Armonk, NY, USA). All P-values were two-sided and those <0.05 were considered statistically significant.

Results

A total of 231 patients were included for analyses, of which 118 patients were from the training set and 113 patients were from the validation set. The two sets were comparable for clinical and pathological parameters (Table S1). Only 14 were identified as M1 stage at the first diagnosis. The median follow-up was 17.5 months (range: 3–111 months) across all patients, and more than half the metastases originated from initial localized disease (54.5%). The TIL and immune checkpoint expression in mRCC tissues are represented in Figure S1. Furthermore, PD-L1 was expressed not only on tumor infiltrating mononuclear cells (TIMC PD-L1) of inflammatory areas, but also on TC (TC PD-L1) (Figure S1). The CD8 and PD-1 staining in mRCC tissues were exclusively located in inflammatory areas (Figure S2). Across all the patients, distribution of PD-L1 was higher in Fuhrman grade 3 and 4 when compared to Fuhrman grade 2 (Figure S3). Patients with high initial stage or pathological grade had more TC PD-L1 density (45.71% in TNM III+IV vs 36.51% in TNM I+II, P=0.156; 47.90% in grade 3+4 vs 21.43% in grade 2, P<0.001) as well as TIMC PD-L1 (34.29% in TNM III+IV vs 26.19% in TNM I+II, P=0.181; 34.45% in grade 3+4 vs 21.43% in grade 2, P=0.022). In addition, three checkpoint-associated molecules were remarkably detected in patients with poorer physical status (Figure S3, Table 1).
Table 1

Clinical and pathologic characteristics of patients according to immune checkpoint expression

CharacteristicsPatients
PD-L1 in TC
PD-L1 in TIMC
PD-1
n%LowHighP-valueLowHighP-valueLowHighP-value
No of patients231100150811666519041
Gender0.8180.0050.436
Male16973.2109601135613732
Female6226.84121539539
Age0.0090.5490.123
≤57 years11047.6624877338624
>57 years12152.48833893210417
Histologic type<0.0010.0340.510
Clear cell type19986.1138611485116534
Non-clear cell type3213.912201814257
Tumor nucleus grade<0.0010.0220.082
211248.5882488249715
3+411951.5625778419326
Initial TNM stage0.1560.1810.758
Stage I+II12654.5804693338442
Stage III+IV10545.5574869367233
Pulmonary metastasis0.3720.7090.826
Present14361.996471043911726
Absent8838.1543462267315
Hepatic metastasis0.5840.3380.755
Present2510.81510205205
Absent20689.2135711466017036
Osseous metastasis0.3800.6120.758
Present5523.833224114469
Absent17676.2117591255114432
Metastatic organ number0.8500.9870.162
115366.2100531104312231
≥27833.8502856226810
Tumor hemorrhage/necrosis0.0070.7120.676
Present7432393552226212
Absent15768111461144312829
KPS0.038<0.0010.001
>8020086.6135651524817129
≤803113.4151614171912
IMDC0.2210.6510.435
Favorable3816.52711299299
Intermediate15366.289641054810053
Poor4017.3211928122713
Tumor size0.7200.9430.728
≤4 cm4117.729122813329
>4 and ≤7 cm9541.1633269268114
>7 and ≤10 cm6026.0372343174812
>10 cm3515.22114269296
Systemic therapy0.7130.5000.072
Sunitinib13658.987491003611719
Sorafenib9541.1633266297322
CD80.0580.0300.687
Low10864.9773185239018
High12335.17350814210023
PD-10.001<0.001
Low19082.31335714644
High4117.717242021
PD-L1 TIMC<0.001<0.001
Low16671.91313514620
High6528.119464421
PD-L1 TC<0.0010.001
Low15064.91311913317
High8135.135465724

Note: Data in bold indicates P<0.05.

Abbreviations: IMDC, International Metastatic Renal Cancer Database Consortium; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells; PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; KPS, Karnofsky Performance Status.

In the training and validation sets, abundant CD8 staining was remarkably associated with better OS. Median OS was 21 and 15 months longer in patients with abundant CD8 infiltration in the training and validation sets, respectively (Figure 1). On the contrary, checkpoint-related molecules generally were associated with poor survival, with PD-1 owing the best separation capability, and PD-L1 being marginally significant in the validation set (Figure 1). After adjusting to other parameters, abundant molecular CD8 density decreased 44% and 58% of the risk of death in the corresponding training and validation sets (training: HR =0.561, 95% CI 0.324–0.972, P=0.039; validation: HR =0.425, 95% CI 0.238–0.758, P=0.004). Checkpoint-related PD-L1 did not show any independent association with survival, but PD-1 density significantly affected OS both in the training and validation set (HR =2.189, 95% CI 1.097–4.370, P=0.026; validation: HR =2.178, 95% CI 1.070–4.433, P=0.032). It demonstrated an outstanding influential ability of PD-1 compared with other checkpoint molecules. In PD-1-assisted CD8-stratified populations, patients with PD-1 high/CD8 low staining had the worst OS, three times increased risk of death compared with PD-1 low/CD8 high subgroup, when adjusted to other parameters (Table 2).
Figure 1

Kaplan–Meier curves according to CD8 and PD-1/PD-L1 level in the training and validation sets.

Notes: Kaplan–Meier analysis of OS according to CD8 in patients with training set (A) and validation set (E), PD-1 in patients with training set (B) and validation set (F), TC PD-L1 in patients with training set (C) and validation set (G), TIMC PD-L1 in patients with training set (D) and validation set (H). P-value was calculated by log-rank test.

Abbreviations: PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; OS, overall survival; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells.

Table 2

Multivariate Cox regression analyses for OS of training and validation patients

VariablesTraining patients (n=118) Multivariate
Validation patients (n=113) Multivariate
HR (95% CI)P-valueHR (95% CI)P-value
PD-L1 TC
 High vs low0.944 (0.462–1.931)0.8741.002 (0.488–2.059)0.995
PD-L1 TIMC
 High vs low1.433 (0.736–2.791)0.2901.341 (0.631–2.852)0.446
CD8
 High vs low0.561 (0.324–0.972)0.0390.425 (0.238–0.758)0.004
PD-1
 High vs low2.189 (1.097–4.370)0.0262.178 (1.070–4.433)0.032
Tumor nucleus grade
 3+4 vs 21.129 (0.633–2.012)0.6821.042 (0.568–1.913)0.893
Initial TNM stage
 III+IV vs I+II1.227 (0.684–2.202)0.4921.321 (0.738–2.365)0.349
Pulmonary metastasis
 Present vs absent2.034 (1.104–3.747)0.0231.372 (0.780–2.415)0.272
IMDC0.002<0.001
 Favorable1.0001.000
 Intermediate1.448 (0.725–2.892)1.112 (0.509–2.431)
 Poor3.262 (1.680–6.335)4.094 (2.181–7.686)
PD-1/CD80.011<0.001
 Low/high1.0001.000
 Low/low–high/high1.319 (0.525–3.311)1.035 (0.568–1.881)
 High/low3.202 (1.433–7.153)4.012 (2.354–6.838)

Note: Data in bold indicates P<0.05.

Abbreviations: IMDC, International Metastatic Renal Cancer Database Consortium; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells; PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; OS, overall survival.

We performed ROC analysis at the time of 12-month and 36-month follow-ups, and the combination of PD-1 and CD8 expression level to the IMDC showed better prognostic value than using IMDC alone (Figure 2). The IMDC plus PD-1/CD8 expression (area under the curve [AUC] =0.812, 95% CI 0.752–0.862) performed better than the IMDC (AUC =0.755, 95% CI 0.691–0.812) (P=0.0035) at the 12-month follow-up, while at the 36-month follow-up the IMDC together with PD-1/CD8 expression (AUC =0.853, 95% CI 0.789–0.904) also revealed better prognostic value compared with the IMDC (AUC =0.763, 95% CI 0.689–0.826) (P<0.0001) (Figure 2A, B), indicating the advantage of using molecular biomarkers in mRCC assessment.
Figure 2

ROC analysis for predictive accuracy of IMDC combined with PD-1/CD8 model for OS and IMDC alone.

Note: All subtypes at 12 months (A) and 36 months (B).

Abbreviations: PD-1, programmed cell death protein 1; IMDC, International Metastatic Renal Cancer Database Consortium; OS, overall survival; ROC, receiver operating characteristic; AUC, area under the curve.

Furthermore, the impact of CD8 and PD-1, as well as PD-1-assisted CD8, on patient survival in different subgroups receiving TKI agents was assessed. Interestingly, CD8- positive density-stratified patients had better OS in the sunitinib group but not in the sorafenib group (Figure S4). Using PD-1-assisted CD8, we could obtain a more efficient and balanced prediction among mRCC patients for OS (Figure 3).
Figure 3

Kaplan–Meier curves according to PD-1-assisted CD8 level.

Abbreviation: PD-1, programmed cell death protein 1.

Discussion

In this study, we found that CD8+ T cell is an independent indicator for longer survival of mRCC patients treated with TKIs. Our results are concordant with previous studies in which higher CD8 expression was associated with prolonged survival and better outcomes in patients with mRCC and other solid tumors.9,17 Weiss et al demonstrated that a significant increase in the number of CD8+ T cells was observed in tumors from long-term surviving (>8 years) patients than short-term surviving (<4 years) patients.8 Also, George et al found that greater CD8+ T lymphocytes density in tumor tissue was associated with longer disease-free survival with adjuvant sunitinib in high-risk locoregional RCC. However, the prognostic value of PD-L1 expression in high-risk locoregional RCC had no significance.18 A meta-analysis indicates that a higher level of PD-L1 expression is a negative prognostic factor in RCC.19 In our present study, we focused on mRCC patients, PD-L1 and PD-1 affected patient outcomes in different levels. PD-L1 expressed on TC is not associated with survival, and PD-L1 expressed on TIMC only had a marginal influence in one set. They were not independent factors for OS when adjusted by other parameters. PD-1 was the only significant checkpoint-associated molecule in the multivariable analyses. High PD-1 level in inflammatory zone had 1.5-fold increased risk of death, indicating a powerful prognostic value. Meanwhile, PD-1 was different with PD-L1 in their association with other parameters. Patients with TC PD-L1-positive expression tend to have tumor necrosis. Moreover, the regulative role of PD-1 in anticancer immunity, and assisted CD8+ T lymphocytes were reported to predict OS of mRCC patients treated with TKIs. Granier et al found that overexpression of PD-1 and Tim-3 had a higher risk of relapse and a poorer OS.20 Our data showed that PD-1 high/CD8 low patients had the shortest OS; median OS was 16 in this subgroup, while median OS was 50 in the PD-1 low/CD8 high subgroup. A study by Giraldo et al reported that high expression of immune checkpoints was associated with increased risk of disease progression whereas low expression of immune checkpoints was associated with good prognosis.13 Interestingly, predictive difference was found between sunitinib and sorafenib patients. The stratification capabil ity of CD8 count was significant only in sunitinib patients, but not in sorafenib patients. This phenomenon implied a potential means of prediction in patients receiving sunitinib treatment. Why this happens and the final conclusion still need large-scale research for confirmation. It may be related to their different drug effects mechanisms on immune cells in the mRCC response to VEGF receptor-TKIs.21 The major limitations of this study are its retrospective design and relatively small number of patients. Meanwhile, recommendations on sorafenib in China were different from National Comprehensive Cancer Network and European Association of Urology guidelines. These reasons contribute to the higher percentage of sorafenib application. Future research should be performed in patients receiving other TKIs treatments. In conclusion, our findings suggest that abundant CD8+ T lymphocytes were significantly associated with longer OS in mRCC patients treated with TKIs. Moreover, PD-1 was the most influential checkpoint-associated molecule. PD-1-assisted CD8+ T cell better stratified patients and could cooperate with the present IMDC model to obtain better prediction. TIL and immune checkpoint expression in mRCC tissues. Notes: CD8 low (A), CD8 high (B), PD-1 low (C), PD-1 high (D), TC PD-L1 negative (E), TC PD-L1 positive (F), TIMC PD-L1 negative (G), TIMC PD-L1 positive (H) in mRCC tissues. Original magnification: ×100. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; mRCC, metastatic renal cell carcinoma; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells; TIL, tumor infiltrating lymphocyte. PD-1/CD8 expression in mRCC tissues. Notes: Hematoxylin-eosin staining (A), CD8 low (B), PD-1 high (C), hematoxylin-eosin staining (D), CD8 high (E), PD-1 low (F), hematoxylin-eosin staining (G), CD8 low (H), PD-1 low (I), hematoxylin-eosin staining (J), CD8 high (K), PD-1 high (L) in mRCC tissues. Original magnification: ×100. Abbreviations: PD-1, programmed cell death protein 1; mRCC, metastatic renal cell carcinoma. Association of CD8 and checkpoint-associated molecules with initial TNM stage and Fuhrman grade. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells. Kaplan-Meier curves according to CD8 and PD-1/PD-L1 level in mRCC patients treated with sunitinib or sorafenib. Notes: Kaplan–Meier analysis of OS according to CD8 in patients with sunitinib (A) and sorafenib (E), PD-1 in patients with sunitinib (B) and sorafenib (F), TC PD-L1 in patients with sunitinib (C) and sorafenib (G), TIMC PD-L1 in patients with sunitinib (D) and sorafenib (H). P-value was calculated by log-rank test. Abbreviations: PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; mRCC, metastatic renal cell carcinoma; OS, overall survival; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells. Clinical and pathologic characteristics of patients according to training and validation sets Abbreviations: IMDC, International Metastatic Renal Cancer Database Consortium; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells; PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; KPS, Karnofsky Performance Status.
Table S1

Clinical and pathologic characteristics of patients according to training and validation sets

CharacteristicsTotalTraining set%Validation set%P-value
No of patients23111851.111348.9
Gender0.428
 Male1698975.48070.8
 Female622924.63329.2
Age0.960
 ≤57 years1105647.55447.8
 >57 years1216252.55952.2
Histologic type0.529
 Clear cell type19910084.79987.6
 Non-clear cell type321815.31412.4
System therapy0.499
 Sorafenib9546394943.4
 Sunitinib13672616456.6
Tumor nucleus grade0.877
 21125849.25447.8
 3874538.14237.2
 4321512.71715
Initial TNM stage0.890
 Stage I914538.14640.7
 Stage II352016.91513.3
 Stage III914639.14539.8
 Stage IV1475.976.2
Pulmonary metastasis0.796
 Present1437462.76961.1
 Absent884437.34438.9
Hepatic metastasis0.923
 Present2513111810.6
 Absent2061058913289.4
Osseous metastasis0.369
 Present553126.32421.2
 Absent1768773.78978.8
Metastatic organ number0.720
 11537966.97465.5
 ≥2783933.13934.5
Tumor hemorrhage/necrosis0.080
 Present744437.33026.5
 Absent1577462.78373.5
KPS0.747
 >8020010387.39785.8
 ≤80311512.71614.2
Tumor size median0.900
 ≤4 cm412823.71311.5
 >4 and ≤7 cm954134.75447.8
 >7 and ≤10 cm603126.32925.7
 >10 cm351815.31715
PD-L1 TIMC0.725
 Negative1668665.38064.6
 Positive653234.73335.4
PD-L1 TC0.917
 Negative1507769.17362.7
 Positive814130.94037.3
PD-10.716
 Low1909681.49483.2
 High412218.61916.8
CD80.629
 Low1085748.35145.1
 High1236151.76254.9
PD-1/CD80.837
 PD-1 high/CD8 low20108.5108.8
 PD-1 low/CD8 high1004840.75246
 PD-1 low/CD8 low884739.84136.3
 PD-1 high/CD8 high231311108.8
IMDC0.796
 Favorable381815.32017.7
 Intermediate1537866.17566.4
 Poor402218.61815.9

Abbreviations: IMDC, International Metastatic Renal Cancer Database Consortium; TC, tumor cells; TIMC, tumor infiltrating mononuclear cells; PD-1, programmed cell death protein 1; PD-L1, ligand of PD-1; KPS, Karnofsky Performance Status.

  21 in total

1.  Cancer statistics, 2018.

Authors:  Rebecca L Siegel; Kimberly D Miller; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2018-01-04       Impact factor: 508.702

2.  Proliferative activity of intratumoral CD8(+) T-lymphocytes as a prognostic factor in human renal cell carcinoma: clinicopathologic demonstration of antitumor immunity.

Authors:  O Nakano; M Sato; Y Naito; K Suzuki; S Orikasa; M Aizawa; Y Suzuki; I Shintaku; H Nagura; H Ohtani
Journal:  Cancer Res       Date:  2001-07-01       Impact factor: 12.701

Review 3.  Immune checkpoint blockade: a common denominator approach to cancer therapy.

Authors:  Suzanne L Topalian; Charles G Drake; Drew M Pardoll
Journal:  Cancer Cell       Date:  2015-04-06       Impact factor: 31.743

4.  Tim-3 Expression on Tumor-Infiltrating PD-1+CD8+ T Cells Correlates with Poor Clinical Outcome in Renal Cell Carcinoma.

Authors:  Clémence Granier; Charles Dariane; Pierre Combe; Virginie Verkarre; Saïk Urien; Cécile Badoual; Hélène Roussel; Marion Mandavit; Patrice Ravel; Mathilde Sibony; Lucie Biard; Camélia Radulescu; Emeline Vinatier; Nadine Benhamouda; Michael Peyromaure; Stéphane Oudard; Arnaud Méjean; Marc-Olivier Timsit; Alain Gey; Eric Tartour
Journal:  Cancer Res       Date:  2016-11-21       Impact factor: 12.701

Review 5.  Prognostic Role of PD-L1 Expression in Renal Cell Carcinoma. A Systematic Review and Meta-Analysis.

Authors:  Roberto Iacovelli; Franco Nolè; Elena Verri; Giuseppe Renne; Chiara Paglino; Matteo Santoni; Maria Cossu Rocca; Palma Giglione; Gaetano Aurilio; Daniela Cullurà; Stefano Cascinu; Camillo Porta
Journal:  Target Oncol       Date:  2016-04       Impact factor: 4.493

6.  CD40 expression in renal cell carcinoma is associated with tumor apoptosis, CD8(+) T cell frequency and patient survival.

Authors:  Jonathan M Weiss; W Gregory Alvord; Octavio A Quiñones; Jimmy K Stauffer; Robert H Wiltrout
Journal:  Hum Immunol       Date:  2014-05-04       Impact factor: 2.850

7.  Immune Biomarkers Predictive for Disease-Free Survival with Adjuvant Sunitinib in High-Risk Locoregional Renal Cell Carcinoma: From Randomized Phase III S-TRAC Study.

Authors:  Daniel J George; Jean-François Martini; Michael Staehler; Robert J Motzer; Ahmed Magheli; Bernard Escudier; Paola Gerletti; Sherry Li; Michelle Casey; Brigitte Laguerre; Hardev S Pandha; Allan J Pantuck; Anup Patel; Maria J Lechuga; Alain Ravaud
Journal:  Clin Cancer Res       Date:  2018-01-26       Impact factor: 12.531

Review 8.  Advances in targeting cell surface signalling molecules for immune modulation.

Authors:  Sheng Yao; Yuwen Zhu; Lieping Chen
Journal:  Nat Rev Drug Discov       Date:  2013-02       Impact factor: 84.694

9.  Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study.

Authors:  Daniel Y C Heng; Wanling Xie; Meredith M Regan; Mark A Warren; Ali Reza Golshayan; Chakshu Sahi; Bernhard J Eigl; J Dean Ruether; Tina Cheng; Scott North; Peter Venner; Jennifer J Knox; Kim N Chi; Christian Kollmannsberger; David F McDermott; William K Oh; Michael B Atkins; Ronald M Bukowski; Brian I Rini; Toni K Choueiri
Journal:  J Clin Oncol       Date:  2009-10-13       Impact factor: 44.544

10.  First-line Systemic Therapy for Metastatic Renal Cell Carcinoma: A Systematic Review and Network Meta-analysis.

Authors:  Christopher J D Wallis; Zachary Klaassen; Bimal Bhindi; Xiang Y Ye; Thenappan Chandrasekar; Ann M Farrell; Hanan Goldberg; Stephen A Boorjian; Bradley Leibovich; Girish S Kulkarni; Prakesh S Shah; Georg A Bjarnason; Daniel Y C Heng; Raj Satkunasivam; Antonio Finelli
Journal:  Eur Urol       Date:  2018-04-13       Impact factor: 20.096

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  25 in total

Review 1.  Biomarkers of immune checkpoint inhibitor efficacy in cancer.

Authors:  D E Meyers; S Banerji
Journal:  Curr Oncol       Date:  2020-04-01       Impact factor: 3.677

2.  Immune Checkpoint Profiles in Luminal B Breast Cancer (Alliance).

Authors:  Meenakshi Anurag; Mayanne Zhu; Chen Huang; Suhas Vasaikar; Junkai Wang; Jeremy Hoog; Samantha Burugu; Dongxia Gao; Vera Suman; Xiang H Zhang; Bing Zhang; Torsten Nielsen; Matthew J Ellis
Journal:  J Natl Cancer Inst       Date:  2020-07-01       Impact factor: 13.506

3.  Exploration of the relationships between tumor mutation burden with immune infiltrates in clear cell renal cell carcinoma.

Authors:  Chuanjie Zhang; Zongtai Li; Feng Qi; Xin Hu; Jun Luo
Journal:  Ann Transl Med       Date:  2019-11

Review 4.  Immune checkpoint blockade in renal cell carcinoma.

Authors:  Phillip M Rappold; Andrew W Silagy; Ritesh R Kotecha; Ari A Hakimi
Journal:  J Surg Oncol       Date:  2021-03       Impact factor: 3.454

5.  Noninvasive evaluation of tumor immune microenvironment in patients with clear cell renal cell carcinoma using metabolic parameter from preoperative 2-[18F]FDG PET/CT.

Authors:  Caixia Wu; Yonggang Cui; Jumei Liu; Linlin Ma; Yan Xiong; Yanqing Gong; Yanyan Zhao; Xi Zhang; Silu Chen; Qun He; Jianhua Zhang; Meng Liu; Yan Fan
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-05-12       Impact factor: 9.236

Review 6.  Metastatic Renal Cell Carcinoma Management: From Molecular Mechanism to Clinical Practice.

Authors:  Michela Roberto; Andrea Botticelli; Martina Panebianco; Anna Maria Aschelter; Alain Gelibter; Chiara Ciccarese; Mauro Minelli; Marianna Nuti; Daniele Santini; Andrea Laghi; Silverio Tomao; Paolo Marchetti
Journal:  Front Oncol       Date:  2021-04-22       Impact factor: 6.244

7.  Immune infiltration in renal cell carcinoma.

Authors:  Shichao Zhang; Erdong Zhang; Jinhua Long; Zuquan Hu; Jian Peng; Lina Liu; Fuzhou Tang; Long Li; Yan Ouyang; Zhu Zeng
Journal:  Cancer Sci       Date:  2019-04-07       Impact factor: 6.716

8.  Profiles of tumor-infiltrating immune cells in renal cell carcinoma and their clinical implications.

Authors:  Gongmin Zhu; Lijiao Pei; Hubin Yin; Fan Lin; Xinyuan Li; Xin Zhu; Weiyang He; Xin Gou
Journal:  Oncol Lett       Date:  2019-09-20       Impact factor: 2.967

9.  Immune Cell Infiltration and Identifying Genes of Prognostic Value in the Papillary Renal Cell Carcinoma Microenvironment by Bioinformatics Analysis.

Authors:  Ting Liu; Man Zhang; Deming Sun
Journal:  Biomed Res Int       Date:  2020-07-25       Impact factor: 3.411

10.  Data Mining of Prognostic Microenvironment-Related Genes in Clear Cell Renal Cell Carcinoma: A Study with TCGA Database.

Authors:  Bin Chen; Wei Chen; Jing Jin; Xueping Wang; Yifang Cao; Yi He
Journal:  Dis Markers       Date:  2019-10-30       Impact factor: 3.434

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