Association of Lymphocyte Subsets Percentage with Prognosis for Recurrent or Metastatic Nasopharyngeal Carcinoma Patients Receiving PD-L1 Inhibitors

doi:10.21203/rs.3.rs-4957934/v1

Background: Immune checkpoint inhibitors (ICIs), particularly PD-1/PD-L1 inhibitors, have demonstrated significant survival benefits in treating recurrent or metastatic nasopharyngeal carcinoma (R/M-NPC). While baseline peripheral blood lymphocyte subsets have been identified as prognostic biomarkers in various cancers treated with ICIs, their relevance in R/M-NPC has not been extensively studied.

Methods: This post-hoc analysis used data from 153 R/M-NPC patients treated with PD-L1 inhibitor monotherapy in the phase 2 trial KL167-2-05-CTP. The lymphocyte subsets, including total T cells, CD4/CD8 ratio, helper T cells, suppressor cytotoxic T cells, NK cells, and B cells, were tested by flow cytometry. These subsets were grouped using optimal cutoff values identified by the Maximally Selected Log-rank Statistic. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier and Cox regression analysis, and logistic regression analysis evaluated the associations with objective response rate (ORR) and disease control rate (DCR).

Results: Patients with lower NK cell percentages showed significantly longer OS (26.3 vs. 12.1 months, p<0.001) and PFS (5.5 vs. 3.7 months, p<0.001) compared to those with higher NK cell percentages. No significant differences in OS or PFS were observed for other lymphocyte subsets. High NK cell percentages were identified as risk factors for shorter OS (HR, 2.49) and PFS (HR, 1.62). There were no significant differences in ORR and DCR between high and low lymphocyte subsets.

Conclusion: Lower baseline NK cell percentages are associated with improved OS and PFS in R/M-NPC patients undergoing PD-L1 inhibitor therapy.

Lymphocyte subsets

Immune checkpoint inhibitors

PD-L1 inhibitor

Nasopharyngeal carcinoma

Prognosis

Nasopharyngeal carcinoma (NPC) shows geographical difference in its incidence and mortality worldwide, with Asia accounting for 83.3% of global NPC cases and 83.6% of mortality. [1,2] Early-stage NPC patients (stages I and II, AJCC staging system) have a 5-year overall survival rate of 94.0%, which drops to 89.2% for stage III and 73.7% for stage IV. [3] Given the shorter survival time of R/M-NPC patients, several clinical trials were conducted and demonstrated that chemotherapy combining ICIs can significantly prolong PFS. Compared to placebo group, Camrelizumab (median PFS: 9.7 months vs 6.9 months; HR, 0·54[95%CI, 0·39 − 0·76]; p = 0.0002) and Tislelizumab (median PFS: 9.2 months vs 7.4 months; HR, 0.52[95%CI, 0.38–0.73]; p < 0.0001) both achieved longer PFS.[4,5] In the phase 2 clinical trial KL167-2-05-CTP, patients with R/M-NPC received KL-A167 (PD-L1 inhibitor) monotherapy and achieved 2.8 months for median PFS.[6] PD-L1 inhibitors have demonstrated both effective outcomes and acceptable safety profiles. A network Meta-analysis for recurrent/metastatic head and neck carcinoma (R/M HNSCC) indicates no statistically significant difference in clinical efficacy between PD-1 inhibitor and PD-L1 inhibitor (PD-1 vs PD-L1: HR, 0.90[95%CI, 0.78–1.04]; p = 0.96).[7] Additionally, PD-1 inhibitors are associated with a higher incidence of grade 3 or higher adverse reactions (AEs) compared to PD-L1 inhibitors (OR, 1.58 [95% CI, 1.00-2.54]).[8] The lower incidence of AEs with PD-L1 inhibitors could be due to their selective blocking of PD-L1 only, whereas PD-1 inhibitors block signals from both PD-L1 and PD-L2, increasing the risk of the potential autoimmune reactions. [9,10]

In the previous study (KL167-2-05-CTP) of PD-L1 inhibitors treating R/M-NPC, for full analysis set (FAS) population, ORR was 26.5% (95%CI, 19.2–34.9%) and DCR was 56.8% (95%CI, 47.9–65.4%).[6] Given the significant heterogeneity in patient prognosis, identifying novel biomarkers to predict the efficacy of PD-L1 inhibitor therapy is crucial. PD-L1 inhibitors can reactivated TILs and remodel lymphocyte differentiation in tumor microenvironment (TME). [11,12] Lymphocytes in peripheral blood can eventually infiltrate the TME, providing insights into the efficacy of PD-L1 inhibitor therapy.[13] Therefore, peripheral blood lymphocyte subsets may have potential value in predicting outcomes of PD-L1 inhibitors therapy. Similarly, some studies have demonstrated that peripheral blood lymphocyte subsets can predict the prognosis of patients receiving immunotherapy with other cancers, including NSCLC,[14] metastatic genitourinary cancer[15] and melanoma.[16] However, its prognostic value of peripheral blood lymphocyte subsets remains unreported in NPC. To investigate the predictive value of peripheral blood lymphocyte subsets as biomarkers, we conducted this study using the largest cohort of R/M-NPC patients treated with PD-L1 inhibitors to date.

The design and results of the KL167-2-05-CTP study have been published previously. This phase 2, open-label, multicenter, single-arm trial evaluating KL-A167 in patients with R/M-NPC across 42 hospitals in China. Our retrospective prognostic study protocol received approval from the independent ethics committees of each participating center and was conducted following the Declaration of Helsinki. [17] Study participants obtained the written informed consent.

Patients

Between February 26th, 2019, and January 13th, 2021, a total of 231 patients with R/M-NPC were evaluated for eligibility across 42 hospitals in China. 153 of them were enrolled. Patients with histologically confirmed non-keratinizing R/M-NPC were eligible. All participants had stage IVb R/M-NPC, as classified by the eighth edition of the American Joint Committee on Cancer/International Union Against Cancer staging system. They all have experienced treatment failure with at least two lines of chemotherapy, with platinum-based regimens being included in the first-line chemotherapy. Additional eligibility criteria included being 18 years or older, having at least one measurable lesion per RECIST v1.1, and an ECOG performance status of 0 or 1. Key exclusion criteria included prior immune checkpoints inhibitors (ICIs) usage, antitumor antibody therapy within 12weeks before treatment initiation, receiving any antitumor therapy within 4 weeks prior to the first dose of KL-A167, using immunosuppressive medications within 14 days before treatment initiation, and active central nervous system metastases.

Procedures

OS was defined as the duration from the first dose until death. Secondary endpoints included PFS, ORR and DCR. PFS was defined as the period from the first dose to the first occurrence of disease progression or death. ORR, determined according to RECIST v1.1, defined as the percentage of patients with confirmed complete response (CR) and partial response (PR). DCR was defined as the percentage of patients achieving CR, PR and stable disease (SD). Patients received KL-A167 at 900 mg via intravenous infusion every 2 weeks until confirmed disease progression. Progressive disease (PD) was be determined by assessment at least 4 weeks or longer when it reached the criteria for response for the first time, as determined by the investigators. Response assessments took place every 6 weeks during the initial 24 months, then every 12 weeks until disease progression or therapy discontinuation. The baseline peripheral blood lymphocyte subsets percentage were determined in the laboratory at each research center at the time of response assessment. Measured lymphocyte subsets include Total T cells percentage, CD4/CD8 T cells percentage, Helper T cells percentage, Suppressor Cytotoxic T cells percentage, NK cells percentage and B cells percentage. Some centers did not detect the lymphocyte subsets percentage in full, leading to missing data that we excluded from our analysis. We analyzed these six biomarkers to investigate their prognostic value. The grouping in the study was not randomized. Data of each biomarker were divided into two groups according to the calculated cutoff value and the best cutoff value was calculated using Maximally Selected Log-rank Statistic method. Then, we conducted Kaplan-Meier survival curve and Cox regression analysis to evaluate OS and PFS. COX regression analysis on continuous lymphocyte subsets percentage was also conducted. The odds rates (OR) and 95%CIs for ORR and DCR were computed using logistic regression analysis. Finally, we explored the correlation of lymphocyte subsets with each other by generating heat maps.

Statistical Analysis

We aimed to explore the association of lymphocyte subsets and the prognosis of PD-L1 inhibitor therapy. A two-tailed p < 0.05 was considered to statistical significance. Pearson's chi-squared test was used for analyzing categorical variables. Continuous variables conforming to a normal distribution were subjected to t-tests, while variables which do not follow a normal distribution were subjected to the Mann-Whitney test. The cutoff value was determined by using Maximally Selected Log-rank Statistic method. Survival curves were generated using the Kaplan-Meier method, with comparisons made using the log-rank test. Cox regression analysis was used to calculate hazard rate (HR) and 95%CIs. The odds rates (OR) and 95%CIs for ORR and DCR were computed using logistic regression analysis. R, version 4.3.2 was used for our analyses.

Patient cohort

Overall, 153 patients (125 men [81.7%]; average age, 47.6 years [SD, 9.8 years]) participated in the phase 2 clinical trial of KL-A167 (anti-PD-L1 monotherapy) for R/M-NPC (Table 1). The median OS is 456 days. Table 2 showed patients’ baseline peripheral blood lymphocyte subsets.

Table 1. Characteristics of Patients

Characteristic	Patients, No. (%) (N=153)
Age (mean (SD))	47.6 (9.8)
Gender
male	125 (81.7)
female	28 (18.3)
ECOG PS
0	59 (38.6)
1	94 (61.4)
T Stage
T0-2	103 (67.3)
T3-4	50 (32.7)
N Stage
N0-2	127 (83.0)
N3	26 (17.0)
Liver Metastasis
Yes	59 (38.6)
No	94 (61.4)
Smoke
Yes	98 (64.1)
No	55 (35.9)
Alcohol
Yes	111 (72.5)
No	42 (27.5)
Lactate Dehydrogenase U/L (median [IQR])	232.0 [176.0, 403.0]
EBV DNA Copies/mL (median [IQR])	1865.0 [421.5, 12275.0]
Body Mass Index (median [IQR])	21.6 [19.1, 23.5]

Abbreviations: ECOG PS, Eastern Cooperative

Oncology Group Performance Status.

Table 2. Baseline Lymphocyte Subsets Percentage of Patients

Baseline Lymphocyte Subsets Percentage	Patients, No. (%) (N=153)
NK cells (mean (SD))	28.4 (12.1)
NK cells group
≤25.57%	42 (47.7)
>25.57%	46 (52.3)
CD4/CD8 ratio (mean (SD))	3.0 (10.9)
CD4/CD8 ratio group
≤0.43%	16 (17.6)
>0.43%	75 (82.4)
Total T cells (mean (SD))	58.0 (13.3)
Total T cells group
≤65.08%	68 (68.0)
>65.08%	32 (32.0)
Helper T cells (mean (SD))	23.6 (7.8)
Helper T cells group
≤22.1%	49 (51.6)
>22.1%	46 (48.4)
Suppressor cytotoxic T cells (mean (SD))	30.7 (11.7)
Suppressor cytotoxic T cells group
≤38.47%	69 (72.6)
>38.47%	26 (27.4)
B cells (mean (SD))	9.4 (5.5)
B cells group
≤15.1%	76 (88.4)
>15.1%	10 (11.6)

Cutoff value of baseline lymphocyte subsets percentage is calculated by the Maximally Selected Log-rank Statistic method.

Association Between Lymphocyte Subsets Percentage and OS, PFS

We conducted the analysis of the association continuous lymphocyte subsets percentage and groups of high and low lymphocyte subsets percentage and OS and PFS. We found that OS and PFS were not significantly different in the two groups of CD4/CD8 ratio in both univariate analysis and multivariate analysis (Table 3). The differences in OS and PFS between two groups of Total T cells were not significant in univariate and multivariate analysis (Table 3). In multivariate analysis of Helper T cells, patients in low Helper T cells percentage group had longer OS than those in high Helper T cells percentage group [HR, 2.08(95%CI, 1.11-3.89); p=0.022] (Table 3). In multivariate analysis of Suppressor Cytotoxic T cells, patients in high Suppressor Cytotoxic T cells percentage group had longer OS than those in low Suppressor Cytotoxic T cells percentage group [HR, 0.51(95%CI, 0.28-0.93); p=0.029] (Table 3). Patients in the high baseline NK cells percentage group had significantly shorter median OS than those in the low baseline NK cells percentage group (12.1 months vs 26.3 months, p<0.001) (Figure 1). In the analysis of NK cells, patients in high NK cells percentage group had an increased risk of death compared with patients in low NK cells percentage group [HR, 2.49(95%CI, 1.39-4.47); p=0.002] (Table 3). The results were consistent in the multivariate analysis of OS [HR, 3.14(95%CI, 1.47-6.75); p=0.003] (Table 3). Patients in low NK cells percentage group also had longer PFS than those in high NK cells percentage group (5.5 months vs 3.7 months, p<0.001) (Figure 1). Patients in low NK cells percentage group had lower risk of progression than those in high NK cells percentage group in univariate [HR, 1.62(95%CI, 1.02-2.57); p=0.041] (Table 3) and multivariate [HR, 2.04(95%CI, 1.16-3.59); p=0.013] (Table 3) analysis of PFS. It was found that higher continuous NK cells percentage is significantly associated with higher risk of death [HR, 1.04(95%CI, 1.01-1.08); p=0.019] and progression [HR, 1.03(95%CI, 1.01-1.05); p=0.010] (Table 3). Higher continuous B cells was associated longer OS [HR, 0.93(95%CI, 0.86-0.99); p=0.032] (Table 3). However, in

Table 3 Cox Analysis for Association Between Lymphocyte Subsets Percentage and Survival Outcomes for Patients with R/M-NPC Receiving Anti-PD-L1 Monotherapy

		OS				PFS
		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
CD4/CD8 ratio	continuous	0.99(0.96-1.03)	0.742	0.99(0.96-1.02)	0.616	1.02(1.00-1.04)	0.035	1.02(1.00-1.04)	0.047
CD4/CD8 ratio	low vs high	2.50(0.92-4.53)	0.078	1.48(0.63-3.51)	0.368	1.17(0.65-2.08)	0.605	1.07(0.65-2.00)	0.832
Total T Cells	continuous	1.00(0.98-1.02)	0.823	0.99(0.97-1.02)	0.648	1.00(0.66-1.01)	0.662	0.99(0.97-1.01)	0.305
Total T Cells	low vs high	0.69(0.38-1.20)	0.187	0.86(0.44-1.65)	0.644	0.76(0.48-1.21)	0.246	0.71(0.43-1.20)	0.200
Helper T Cells	continuous	1.01(0.97-1.04)	0.645	1.02(0.97-1.06)	0.448	1.00(0.97-1.03)	0.816	1.02(0.98-1.04)	0.519
Helper T Cells	low vs high	1.62(0.96-2.73)	0.072	2.08(1.11-3.89)	0.022	1.24(0.80-1.92)	0.329	1.51(0.92-2.48)	0.099
Suppressor Cytotoxic T Cells	continuous	1.00(0.98-1.02)	0.782	1.00(0.98-1.02)	0.912	0.97(0.94-1.00)	0.008	0.98(0.96-1.00)	0.103
Suppressor Cytotoxic T Cells	low vs high	0.67(0.37-1.23)	0.198	1.33(0.84-2.10)	0.222	0.41(0.18-0.93)	0.032	0.51(0.28-0.93)	0.029
NK Cells	continuous	1.01(0.98-1.03)	0.518	1.04(1.01-1.08)	0.019	1.01(0.99-1.03)	0.241	1.03(1.01-1.05)	0.010
NK Cells	low vs high	2.49(1.39-4.47)	0.002	3.14(1.47-6.75)	0.003	1.62(1.02-2.57)	0.041	2.04(1.16-3.59)	0.013
B Cells	continuous	0.97(0.92-1.02)	0.249	0.93(0.86-0.99)	0.032	0.98(0.94-1.03)	0.419	1.00(0.94-1.05)	0.875
B Cells	low vs high	0.37(0.11-1.19)	0.096	0.45(0.12-1.62)	0.220	0.85(0.41-1.77)	0.659	1.03(0.44-2.42)	0.944

In multivariate analysis, we adjusted for age, gender, ECOG PS, T stage, N stage, liver metastasis, serum LDH multivariate analysis, no significant differences in OS and PFS were demonstrated between high and low B cells groups.

Association Between Lymphocyte Percentage and ORR, DCR

We performed logistics regression analysis to explore the relationship between lymphocyte subsets and ORR, DCR. However, we found no significant difference in other analysis of lymphocyte percentage and ORR, DCR between low and high two groups (eFigure 1). The results were consistent in the analysis of continuous lymphocyte subsets percentage (eFigure 1).

Characteristics of Patients grouped by NK cells and Correlation of NK cells and other lymphocyte

Given the good prognostic predictive ability of NK cells percentage, we additionally analyzed the characteristics of patients in high and low NK cell percentage groups (Table 4). We also explored the correlation of NK cells percentage and other lymphocyte subsets percentage. There is a negative linear correlation between NK cells percentage and B cells percentage (r=-0.179; p<0.001) (eFigure 1). NK cells percentage also had a negative linear correlation with Total T cells percentage (r=-0.795; p<0.001) (eFigure 1), Helper T cells percentage (r=-0.397; p<0.001) (), Suppressor Cytotoxic T cells percentage (r=-0.555; p<0.001) (eFigure 1). However, we did not see a linear correlation between NK cells and CD4/CD8 percentage (r=0.258; p>0.05) (eFigure 1).

Table 4. Characteristics of Patients grouped by NK cells

	NK cells≤25.57%，No. (%) (N=42)	NK cells>25.57%， No. (%) (N=46)	p-value
Age (mean (SD))	47.1 (9.7)	48.9 (9.4)	0.383
Gender			0.167
male	33 (78.6)	42 (91.3)
female	9 (21.4)	4 (8.7)
ECOG PS			0.012
0	24 (57.1)	13 (28.3)
1	25 (46.3)	69 (69.7)
T Stage			0.610
T0-2	28 (66.7)	34 (73.9)
T3-4	14 (33.3)	12 (26.1)
N Stage			1.000
N0-2	36 (85.7)	39 (84.8)
N3	6 (14.3)	7 (15.2)
Liver Metastasis			0.012
Yes	24 (57.1)	13 (28.3)
No	18 (42.9)	33 (71.7)
Smoke			0.929
Yes	26 (61.9)	27 (58.7)
No	16 (38.1)	19 (41.3)
Alcohol			0.622
Yes	30 (71.4)	36 (78.3)
No	12 (28.6)	10 (21.7)
LDH U/L (median [IQR])	205.2 [166.5, 341.2]	232.5 [181.5, 403.0]	0.3759
EBV DNA Copies/mL (median [IQR])	882.0 [400.0, 5980.0]	3035.0 [431.8, 14725.0]	0.255
BMI (median [IQR])	22.8 [20.0, 24.2]	21.2 [19.3, 22.8]	0.088

Abbreviations: ECOG, Eastern Cooperative Oncology Group.

With the increasing application of ICIs in various tumors, the era of immunotherapy for RM-NPC has arrived. Previous studies on ICIs for other cancers have demonstrated the value of peripheral blood lymphocyte subsets in predicting prognosis.[13] For example, in NSCLC patients receiving PD-1 blockade treatment, researchers found that higher T-cell factor 1 (TCF1) frequency in effector-memory (CCR7–) CD8+ T cells correlated with longer PFS (17 months vs 3 months; HR, 0.39; p = 0.019).[18] Similarly, in metastatic pancreatic cancer, higher baseline circulating CD4+ T central memory cells were associated with longer survival following treatment with nivolumab combined with chemotherapy (20 months vs 10 months; p=0.037).[19] In melanoma patients receiving PD-1 inhibitors, peripheral blood B cells were found to correlate with prognosis.[20] However, up to now, the data on the association between the lymphocyte subsets percentage and the prognosis of RM-NPC patients receiving PD-1 inhibitors are limited.

In our study, we thoroughly explored the predictive value of baseline lymphocyte subset percentages in peripheral blood for OS and PFS by analyzing data from a clinical trial with the largest cohort of R/M-NPC patients treated with PD-L1 inhibitor monotherapy.[6] These patients had received two lines of chemotherapy, which can suppress immune function and reduce lymphocyte counts, creating an immune desert status. Despite the compromised immune status following extensive chemoradiotherapy, it was found that patients with higher baseline NK cells percentage had a significantly shorter median OS (12.1 months vs 26.3 months) and shorter median PFS (3.7 months vs 5.5 months) after analyzing six lymphocyte subsets percentage. This result suggests that the percentage of NK cells in peripheral blood may serve as a valuable biomarker for predicting outcomes in patients with R/M-NPC receiving anti-PD-L1 therapy. It was observed that CD4/CD8 ratio, Total T cells, Helper T cells and Suppressor Cytotoxic T cells were not significantly associated with prognosis of R/M-NPC patients who received PD-1 inhibitors treatment.

The role of NK cells percentage as a biomarker for predicting the prognosis of patients receiving immunotherapy remains uncertain due to limited data. There are currently studies investigating the relationship between baseline lymphocyte subsets percentages in peripheral blood and prognosis in other types of cancer. For instance, in NSCLC patients receiving nivolumab, lower baseline NK cell levels were associated with longer OS.[14] This aligns with our findings that high levels of circulating NK cells predict a worse outcome. Moreover, there have been no similar studies in the field of NPC to date.

NK cells can induce target cell death by releasing cytotoxic granules containing perforin and granzymes, as well as by activating death receptor-mediated pathways.[21] NK cells have multiple anti-tumor function. Many cancer cells can evade detection by cytotoxic CD8 T cells by downregulating the expression of MHC I molecules. However, NK cells can identify the cells of low expression of MHC I molecules and cause the lysis of the cancer cells.[22] ADCC is also a key function of NK cells to kill cancer cells. Given its anti-tumor function, NK cells also play an important role in cancer immunotherapy. In cancer mouse models, it is found activated NK cells can express PD-1 and PD-1 engagement by PD-L1 on tumor cells can suppress anti-tumor mediated by NK cells.[23] In a study of human body specimens, Wang et al had reported that a high density of NK cells within the tumor or stroma indicates longer OS and PFS.[24] Chen et al also reported that patients with high NK cells had a longer PFS in a single-cell transcriptomics study.[25] Tumor-infiltrating NK cells was proven to serve as prognostic factors for patients with nasopharyngeal carcinoma receiving immunotherapy, but measuring NK cells in specimens is not easily achievable. In addition, the change of Tumor-infiltrating NK cells may also affect NK cells in peripheral blood. Hence, studying the relationship between NK cells in peripheral blood and prognosis of patients with cancer receiving immunotherapy is significantly important.

There are some limitations in this study. There might be selection bias present because the study used data from a clinical trial, potentially limiting the generalizability of the findings to the broader population. Some research centers did not test all types of lymphocytes resulting in incomplete data for some types of lymphocytes, which resulted in a smaller amount of data being available for analysis. Our study focused on baseline peripheral blood lymphocyte subsets percentage, and the relationship between changes in peripheral blood lymphocyte subsets percentage during treatment and OS may require further investigation in future studies.

This study suggests that baseline low peripheral blood NK cells percentage is associated with better OS and PFS of R/M-NPC patients who will have prolonged survival with PD-L1 inhibitor therapy.

Acknowledgments: N/A

Disclosure:

Funding Information

The work was supported by the National Key Research and Development Program of China(2021YFE0206600), National Natural Science Foundation of China (82172842 and 81672386) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflict of Interest

Junyou Ge, Yan Qing and Youneng Wei are employees of Sichuan Kelun-Biotech Biopharmaceutical Co., Ltd (Chengdu, China). All other authors declare no potential conflicts of interest

Data Availability

The data generated and analyzed during this study can be obtained from the corresponding author upon reasonable request.

Ethics Statement

Approval of the research protocol by an Institutional Reviewer Board: Ethical approval for the collection of human data was obtained from the Institutional Review Board (HX-IRB-AF-12-V4.0) of West China Hospital.

Informed Consent: Prior to enrollment, all participants provided written informed consent

Registry and the Registration No. of the study/trial: KL-A167 clinical trial (NCT03848286)

Animal Studies: N/A

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No competing interests reported.

Association of Lymphocyte Subsets Percentage with Prognosis for Recurrent or Metastatic Nasopharyngeal Carcinoma Patients Receiving PD-L1 Inhibitors

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Abstract

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Introduction

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Statistical Analysis

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