Impact of immunotherapy time-of-day infusion on survival and immunologic correlates in patients with metastatic renal cell carcinoma: a multicenter cohort analysis

Abstract

Background

Recent studies have demonstrated that earlier time-of-day infusion of immune checkpoint inhibitors (ICIs) is associated with longer progression-free survival (PFS) and overall survival (OS) among patients with metastatic melanoma and non-small cell lung cancer. These data are in line with growing preclinical evidence that the adaptive immune response may be more effectively stimulated earlier in the day. We sought to determine the impact of time-of-day ICI infusions on outcomes among patients with metastatic renal cell carcinoma (mRCC).

Methods

The treatment records of all patients with stage IV RCC who began ICI therapy within a multicenter academic hospital system between 2015 and 2020 were reviewed. The associations between the proportion of ICI infusions administered prior to noon (denoting morning infusions) and PFS and OS were evaluated using univariate and multivariable Cox proportional hazards regression.

Results

In this study, 201 patients with mRCC (28% women) received ICIs and were followed over a median of 18 months (IQR 5–30). The median age at the time of ICI initiation was 63 years (IQR 56–70). 101 patients (50%) received ≥20% of their ICI infusions prior to noon (Group A) and 100 patients (50%) received <20% of infusions prior to noon (Group B). Across the two comparison groups, initial ICI agents consisted of nivolumab (58%), nivolumab plus ipilimumab (34%), and pembrolizumab (8%). On univariate analysis, patients in Group A had longer PFS and OS compared with those in Group B (PFS HR 0.67, 95% CI 0.48 to 0.94, P_univar=0.020; OS HR 0.57, 95% CI 0.34 to 0.95, P_univar=0.033). These significant findings persisted following multivariable adjustment for age, sex, performance status, International Metastatic RCC Database Consortium risk score, pretreatment lactate dehydrogenase, histology, and presence of bone, brain, and liver metastases (PFS HR 0.70, 95% CI 0.50 to 0.98, P_multivar=0.040; OS HR 0.57, 95% CI 0.33 to 0.98, P_multivar=0.043).

Conclusions

Patients with mRCC may benefit from earlier time-of-day receipt of ICIs. Our findings are consistent with established mechanisms of chrono-immunology, as well as with preceding analogous studies in melanoma and lung cancer. Additional prospective randomized trials are warranted.

ZSB and DCQ are joint senior authors.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Prior studies have shown that circadian rhythm may impact the efficacy of immunotherapy in treating cancers.

WHAT THIS STUDY ADDS

• In this study we show that the timing of immunotherapy infusions is significantly associated with progression-free survival and overall survival in patients with metastatic renal cell carcinoma.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• The implications of this study merit larger-scale prospective randomized trials for additional validation.

Introduction

Cancer of the kidney and renal pelvis accounts for approximately 4.2% of all cancer incidence and 2.4% of all cancer deaths within the USA.¹ Renal cell carcinoma (RCC), the most common cancer of the kidney, is generally managed surgically for early-stage disease and metastatic cases where resection is possible. While systemic therapies are a key component of managing advanced-stage disease, there are wide variabilities in treatment response.² Innovative strategies are needed for improvement.

Circadian control of the immune system was established several decades ago with pioneering work showing that circulating lymphocyte counts fluctuate throughout the day in healthy adults.³ Subsequent studies have elegantly revealed that the secretion profile of multiple proinflammatory cytokines displays a circadian rhythm and this rhythmicity in cytokine production can have a profound effect on cancer pathogenesis and response to treatment.^4–10 Similarly, many studies have evaluated the impact of circadian physiology on chemotherapy toxicity. Phase 1 studies as early as 1990 have shown that for patients with breast cancer, hepatocellular carcinoma, and cholangiocarcinoma, synchronizing oxaliplatin with the host circadian rhythm leads to a decreased incidence of neutropenia and peripheral paresthesia while elevating mean and maximum tolerated dose.¹¹ This seminal work then motivated prospective randomized assessment of chronotherapy for colorectal cancer.^{12 13} Analogously, the effect of the circadian rhythm on therapeutic cytokine infusions has also been examined.^14–16

Immunotherapy has emerged as the first-line standard of care for numerous oncologic settings.^{17 18} We previously demonstrated that earlier time-of-day administration of immune checkpoint inhibitors (ICIs) is significantly associated with longer progression-free survival (PFS) and overall survival (OS) among patients with metastatic melanoma.¹⁹ ICIs have also become a cornerstone of metastatic RCC (mRCC) management, though the association between time-of-day of ICI infusions and outcomes in mRCC remains unclear and warrants further investigation.

Methods

Patient population

In this multicenter cohort study, we analyzed the de-identified individual-level clinicopathologic and treatment data of all adults (age ≥18 years) diagnosed with mRCC who received ICI infusions (pembrolizumab, nivolumab, or dual checkpoint blockade with ipilimumab and nivolumab) across the academic medical centers comprising Winship Cancer Institute of Emory University (Atlanta, Georgia, USA) between 2015 and 2020. Information on vital status was available for patients who died before or on December 31, 2021. Patients who received any ICI infusions outside of Winship Cancer Institute were excluded from the analysis (figure 1).

Figure 1. Study schema. ICI, immune checkpoint inhibitor; mRCC, metastatic renal cell carcinoma.

Primary independent variable

From our institution’s infusion clinic central records, we downloaded the timestamps of ICI infusions administered to patients for the treatment of primary renal malignancies. Exclusion of patients with histologies other than RCC or non-metastatic disease was performed by manual inspection of the electronic medical records for corresponding patients. Timestamps were automatically generated when infusion clinic staff had fulfilled a physician order and initiated ICI infusion. Timestamps were recorded in Eastern Standard Time. For combination ICI treatments (ie, dual checkpoint blockade with ipilimumab and nivolumab), the infusion start time of the first administered agent was established as the timestamp of record.

Patients in this study were partitioned into those who received at least 20% of their ICI infusions prior to noon (Group A) and those who received less than 20% of their ICI infusions prior to noon (Group B). Noon was chosen as the time-of-day threshold of interest as it is the nearest hour to the median infusion time among all patients and aligns with precedence set by previous circadian rhythm studies of ICIs for melanoma and lung cancer, as well as vaccination for infectious disease.^20–23 The proportion threshold of 20% was set to optimize the balance between comparison group sample sizes (table 1).

Table 1

Patient characteristics

	≥20% ICI infusions prior to noon N=101 (%)	<20% ICI infusions prior to noon N=100 (%)	P value
Sex			0.10
Female	22 (22)	33 (33)
Male	79 (78)	67 (67)
Age at ICI initiation			0.08
≤50	16 (16)	17 (17)
51–60	17 (17)	32 (32)
61–70	42 (41)	28 (28)
71–80	22 (22)	17 (17)
≥81	4 (4)	6 (6)
ECOG			0.86
0	45 (44)	41 (41)
1	39 (39)	40 (40)
≥2	17 (17)	19 (19)
Statin use	34 (34)	38 (38)	0.62
IMDC risk score			0.37
0 (favorable)	10 (10)	7 (7)
1–2 (intermediate)	55 (54)	48 (48)
≥3 (poor)	36 (36)	45 (45)
RCC histology			0.74
Clear cell	74 (73)	68 (68)
Papillary	5 (5)	6 (6)
Chromophobe	2 (2)	1 (1)
Collecting duct	3 (3)	1 (1)
Sarcomatoid	1 (1)	2 (2)
Mixed histologies of the above	7 (7)	12 (12)
With sarcomatoid features	1 (1)	3 (3)
With chromophobe features	0 (0)	0 (0)
Other (eg, eosinophilic, Xp11 translocation, poorly differentiated)	9 (9)	10 (10)
Pretreatment LDH			0.51
Normal	52 (51)	54 (54)
Elevated	12 (12)	16 (16)
Unknown	37 (37)	30 (30)
Bone metastasis	34 (34)	28 (28)	0.48
Brain metastasis	9 (9)	18 (18)	0.09
Liver metastasis	28 (28)	25 (25)	0.78
First-line therapy included ICI	44 (44)	32 (32)	0.12
Initial ICI regimen			0.57
Nivolumab	43 (43)	53 (53)
Nivolumab+TKI	11 (11)	10 (10)
Pembrolizumab	3 (3)	3 (3)
Pembrolizumab+TKI	4 (4)	5 (5)
Dual nivolumab/ipilimumab	40 (40)	29 (29)
ICI ever received*
Nivolumab	54 (53)	63 (63)	0.22
Pembrolizumab	14 (14)	8 (8)	0.27
Dual nivolumab/ipilimumab	40 (40)	30 (40)	0.20
Non-ICI systemic therapies ever received*
Cabozantinib	47 (46)	39 (39)	0.35
Pazopanib	29 (29)	31 (31)	0.84
Sunitinib	12 (12)	22 (22)	0.08
Everolimus	19 (19)	13 (13)	0.35
Lenvatinib	16 (16)	6 (6)	0.05
Axitinib	9 (9)	7 (7)	0.81

*Percentages do not add up to 100 because some patients received multiple ICI and non-ICI systemic therapy regimens.

ECOG, Eastern Cooperative Oncology Group performance status; ICI, immune checkpoint inhibitor; IMDC, International Metastatic RCC Database Consortium; LDH, lactate dehyrogenase; RCC, renal cell carcinoma; TKI, tyrosine kinase inhibitor.

Clinical and translational outcomes

The primary endpoints of this study are PFS and OS. PFS was defined as time to progression per the immune-modified Response Evaluation Criteria in Solid Tumors (RECIST) criteria (imRECIST).²⁴ OS was defined as time to death from any cause. Both PFS and OS were indexed from the date of the first ICI infusion. Patients lost to follow-up were censored at the time of last known contact. A subset of patients in the present study had also enrolled in our previously reported study of ICI treatment response biomarkers in RCC; a burst of HLA-DR+CD38+CD8+ T cells in the peripheral blood following two cycles of immunotherapy was found to be associated with objective response.^{19 25 26} For further immunologic corroboration of the present study, we stratified fold change (FC) of HLA-DR+CD38+CD8+ T cells by time-of-day ICI infusion group status for these overlapping patients.

Covariates

We also ascertained clinicopathologic characteristics for every patient, reflecting pre-immunotherapy baseline and factors with potential influence on infusion time-of-day scheduling or the outcomes of interest. These characteristics include sex, age, ECOG (Eastern Cooperative Oncology Group) performance status, statin use, RCC histology, pretreatment lactate dehydrogenase (LDH), International Metastatic RCC Database Consortium (IMDC) risk score (composite score derived from baseline hemoglobin, corrected calcium, circulating neutrophils, circulating platelets, Karnofsky performance status), presence of bone, brain, and liver metastases, history of ICIs received, and history of non-ICI systemic therapies received.^27–30 History of corticosteroid use and tumor Programmed Death-Ligand 1 (PD-L1) status were not considered; they have not consistently demonstrated influence on outcomes in mRCC, in contrast to metastatic melanoma and non-small cell lung cancer (NSCLC).^31–35

Statistical analysis

Patient clinicopathologic characteristics in Group A and Group B were compared using the χ² test for categorical variables and the Kruskal-Wallis test for continuous variables involving medians (table 1). The objective response rate was computed as the fraction of patients in each group who achieved a complete response (CR) or partial response (PR) per imRECIST, and compared using the χ² test.²⁴ PFS and OS were estimated using the Kaplan-Meier method. The associations between clinicopathologic characteristics and PFS and OS were computed using univariate Cox proportional hazards regression.

PFS and OS of patients in Group A were compared with those in Group B using Cox proportional hazards regression without and with multivariable adjustment for age, sex, and other clinically relevant and statistically significant covariates from univariate analyses of PFS and OS (table 2). Pretreatment LDH was the only variable with missing values (table 1); for regressions, this continuous variable was converted into a binary indicator coded as either elevated, or normal or unknown.

Table 2

Cox proportional hazards regression results

	Univariate				Multivariable
	PFS		OS		PFS		OS
	HR (95% CI)	P value	HR (95% CI)	P value	HR (95% CI)	P value	HR (95% CI)	P value
≥20% ICI infusions prior to noon	0.67 (0.48 to 0.94)	0.020	0.57 (0.34 to 0.95)	0.033	0.70 (0.50 to 0.98)	0.040	0.57 (0.33 to 0.98)	0.043
Age (per year)	1.00 (0.99 to 1.02)	0.543	1.00 (0.98 to 1.02)	0.910	1.01 (0.99 to 1.02)	0.339	1.01 (0.98 to 1.03)	0.651
Male (vs female)	0.82 (0.57 to 1.19)	0.300	0.97 (0.55 to 1.72)	0.928	0.85 (0.58 to 1.26)	0.421	1.00 (0.55 to 1.83)	0.990
ECOG≥2 (vs <2)	1.98 (1.30 to 3.03)	0.002	2.91 (1.54 to 5.50)	0.001	1.43 (0.88 to 2.34)	0.153	1.93 (0.92 to 4.02)	0.081
Statin use	0.88 (0.62 to 1.25)	0.475	0.91 (0.53 to 1.56)	0.721
Elevated LDH	1.89 (1.17 to 3.05)	0.009	3.82 (2.03 to 7.22)	<0.001	1.31 (0.77 to 2.22)	0.327	2.28 (1.10 to 4.69)	0.026
IMDC score (per unit increase)	1.33 (1.16 to 1.51)	<0.001	1.51 (1.22 to 1.86)	<0.001	1.26 (1.09 to 1.47)	0.002	1.33 (1.06 to 1.67)	0.016
Histology
Clear cell	0.76 (0.53 to 1.10)	0.141	0.50 (0.29 to 0.86)	0.012	1.03 (0.69 to 1.54)	0.876	0.67 (0.37 to 1.21)	0.182
Any chromophobe features	0.73 (0.18 to 2.94)	0.654	1.08 (0.15 to 7.82)	0.939
Any sarcomatoid features	1.04 (0.42 to 2.54)	0.938	1.70 (0.52 to 5.48)	0.378
Bone metastasis	1.17 (0.82 to 1.68)	0.384	1.31 (0.76 to 2.23)	0.329	1.01 (0.69 to 1.48)	0.953	1.13 (0.63 to 2.06)	0.677
Brain metastasis	1.13 (0.67 to 1.91)	0.647	0.68 (0.27 to 1.70)	0.408	0.97 (0.56 to 1.68)	0.908	0.60 (0.23 to 1.55)	0.290
Liver metastasis	1.42 (0.98 to 2.06)	0.064	2.19 (1.28 to 3.75)	0.004	1.41 (0.96 to 2.08)	0.078	1.92 (1.08 to 3.41)	0.027
First-line therapy included ICI	0.82 (0.57 to 1.17)	0.279	0.64 (0.35 to 1.15)	0.136
Initial ICI regimen
Dual ipi/nivo	(Reference)
Nivolumab	1.01 (0.70 to 1.47)	0.954	1.30 (0.71 to 2.38)	0.397
Nivolumab+TKI	0.68 (0.34 to 1.34)	0.262	1.21 (0.45 to 3.29)	0.706
Pembrolizumab	0.76 (0.27 to 2.12)	0.603	0.73 (0.10 to 5.47)	0.757
Pembrolizumab+TKI	1.01 (0.43 to 2.36)	0.986	2.29 (0.67 to 7.84)	0.188
Ever received
Nivolumab	0.97 (0.69 to 1.37)	0.856	1.20 (0.70 to 2.09)	0.506
Pembrolizumab	0.78 (0.46 to 1.34)	0.377	0.84 (0.36 to 1.97)	0.693
Dual ipi/nivo	1.07 (0.75 to 1.52)	0.724	0.74 (0.42 to 1.32)	0.314
Cabozantinib	1.31 (0.93 to 1.84)	0.119	1.37 (0.81 to 2.32)	0.241
Pazopanib	1.15 (0.81 to 1.65)	0.435	0.94 (0.54 to 1.64)	0.827
Sunitinib	0.93 (0.59 to 1.47)	0.752	1.16 (0.61 to 2.23)	0.647
Everolimus	1.32 (0.87 to 2.00)	0.191	1.43 (0.79 to 2.59)	0.232
Lenvatinib	1.25 (0.77 to 2.03)	0.368	0.89 (0.42 to 1.88)	0.758
Axitinib	1.56 (0.89 to 2.72)	0.118	0.67 (0.21 to 2.14)	0.495

ECOG, Eastern Cooperative Oncology Group performance status; ICI, immune checkpoint inhibitor; IMDC, International Metastatic renal cell carcinoma Database Consortium; ipi, ipilimumab; LDH, lactate dehydrogenase; nivo, nivolumab; OS, overall survival; PFS, progression-free survival; TKI, tyrosine kinase inhibitor.

For the patients in this study who had consented to provide peripheral blood before and after two cycles of immunotherapy, the FCs in HLA-DR+CD38+CD8+ T cells were computed as previously reported.²⁵ Here, we assessed the distribution of patients who experienced >1.5 FC of HLA-DR+CD38+CD8+ T cells across Groups A and B as well as across objective response categories of CR, PR, stable disease, and progression of disease per imRECIST.^36–38 The log₂(FC) of HLA-DR+CD38+CD8+ T cells was also compared between patients who initiated ICIs in the first line versus subsequent lines of systemic therapy using t-test.

Results

From initial Food and Drug Administration approval of immunotherapy for mRCC on November 23, 2015, to December 31, 2020, we identified 201 patients with confirmed mRCC, 55 (27%) were women and 146 (73%) were men with the median age at the time of ICI initiation of 63 years (IQR 56–70 years). The majority of patients had clear cell histology (142 patients, 71%), intermediate risk IMDC score (103 patients, 51%), and ECOG<2 (165 patients, 82%). In total, these patients received 2163 infusions of ipilimumab, nivolumab, and pembrolizumab, and were followed for a median of 18 months (IQR 5–30).

101 patients (50%) received ≥20% of their infusions prior to noon (Group A) and 100 patients (50%) received <20% of their infusions prior to noon (Group B). The percentage of patients who received at least one of their initial two infusions prior to noon was 64% in Group A and 7% in Group B (p<0.0001). Across the two comparison groups, initial ICI agents consisted of nivolumab (58%), dual ipilimumab/nivolumab (34%), and pembrolizumab (8%). Other non-ICI systemic therapies are outlined in table 1. Importantly, Group A and Group B were well-balanced for all reported patient characteristics (table 1).

Patients in Group A achieved a higher objective response rate than those in Group B (34% (34 of 101) vs 21% (21 of 100), p=0.044). Poor performance status (ECOG≥2), higher IMDC score, and elevated LDH were associated with worse PFS and worse OS. Administration of ICI in the first-line setting and choice of initial ICI did not impact outcomes (table 2). On univariate analysis, patients in Group A had longer PFS and OS compared with those in Group B (figure 2; PFS HR 0.67, 95% CI 0.48 to 0.94, P_univar=0.020; OS HR 0.57, 95% CI 0.34 to 0.95, P_univar=0.033). These significant findings persisted following multivariable adjustment for age, sex, ECOG, IMDC risk score, pretreatment LDH, RCC histology, and presence of bone, brain, and liver metastases (table 2; PFS HR 0.70, 95% CI 0.50 to 0.98, P_multivar=0.040; OS HR 0.57, 95% CI 0.33 to 0.98, P_multivar=0.043). In a multivariable sensitivity analysis of varying thresholds for time-of-day ICI infusion in the vicinity of noon and fraction of ICI infusions in the vicinity of 20%, OS HRs remained stable (online supplemental table 1).

Figure 2. Kaplan-Meier plots of progression-free survival (A) and overall survival (B) for Group A patients (>=20% infusions before noon) and Group B patients (<20% infusions before noon).

There were also no anomalous subgroup deviations in OS association. The effect size and direction of associations between time-of-day ICI infusions and OS stood congruent across clinicopathologic subgroups (figure 3). Of note, patients who were older in age, better in performance status, more favorable in IMDC risk, and with liver metastasis exhibited more pronounced associations between time-of-day ICI infusions and OS.

Figure 3. Forest plot of overall survival HRs across clinicopathological subgroups. For the few patients who received lenvatinib, one comparison group had zero events and the HR could not be confidently estimated using Cox proportional hazards regression. ECOG, Eastern Cooperative Oncology Group performance status; ICI, immune checkpoint inhibitor; IMDC, International Metastatic RCC Database Consortium; LDH, lactate dehydrogenase; RCC, renal cell carcinoma.

In our previous study, we showed that for patients with mRCC receiving ICIs, the FC in peripheral blood HLA-DR+CD38+CD8+ T cells correlates with clinical response.^{25 39} 16 patients from this prior translational immunologic analysis had relevant time-of-day metrics recorded. Of these, 6 patients belonged to Group A and 10 patients belonged to Group B. All patients from Group A (100%) demonstrated >1.5 FC in HLA-DR+CD38+CD8+ T cells in the peripheral blood compared with only 60% from Group B with a trend towards significance (p=0.074, figure 4A). For patients who had >1.5 FC in HLA-DR+CD38+ CD8+ T cells in the peripheral blood, only 33% had progressive disease while 50% of those with ≤1.5 FC had progressive disease (figure 4B). The log₂(FC) of HLA-DR+CD38+CD8+ T cells were similar between patients who did (n=4) and did not (n=12) initiate ICIs in the first-line setting (mean of 1.36 vs 1.30, p=0.962). Collectively, these data support the hypothesis that earlier time-of-day ICI infusions may induce a more robust systemic immune response that confers improved patient outcomes.

Figure 4. (A) Fold change in HLA-DR+CD38+CD8+ T cells following two cycles of immunotherapy across Group A patients (>=20% infusions before noon) and Group B patients (<20% infusions before noon). (B) Clinical response per immune-modified Response Evaluation Criteria in Solid Tumors. CR, complete response; PD, progression of disease; PR, partial response; SD, stable disease.

Discussion

Among patients with mRCC in this multicenter cohort study, receiving at least 20% of ICI infusions prior to noon was associated with longer PFS and OS in both univariate and multivariable analysis. Comparison groups were balanced in size and clinicopathologic characteristics.

Our findings suggest that preferential earlier infusions of ICIs may improve both treatment efficacy and survival through complex time-of-day dependent interactions between checkpoint inhibition and the rhythmic adaptive immune system.⁴⁰ These results are consistent with our previous studies of ICI administration timing for metastatic melanoma and NSCLC.^{19 21} It is also important to highlight that 64% of patients in Group A received at least one of their initial two ICI infusions prior to noon, compared with only 7% of Group B. Time-of-day administration of the initial two infusions may be exceptionally important for antitumor immunologic stimulation, as corroborated by a recent prospective clinical trial which demonstrated that for patients with advanced melanoma receiving nivolumab plus ipilimumab, treatment efficacy and toxicity were primarily driven by the initial two infusions.^{26 41}

Additionally, we investigated T-cell response in the peripheral blood for both Group A and Group B patients. A greater rise in HLA-DR+CD38+CD8+ T cells following the initial two cycles of immunotherapy correlated with achievement of objective response.²⁵ While only 16 patients with mRCC of that previous study overlap with the present study, 100% of Group A patients had >1.5 FC in peripheral HLA-DR+CD38+CD8+ T cells following two ICI cycles while 60% of Group B did. A greater than 1.5-fold increase in this proliferating CD8+ T cell population has been identified as a threshold for CD8+ T cell response following anti-Programmed Cell Death Protein 1 (PD-1) therapy.³⁷ This threshold was selected based on our institution’s prior study on patients with NSCLC treated with ICI in whom the median CD8+ T cell response was >1.5-fold.³⁷

Our clinical data are supported by accumulating translational evidence from murine models. Both B and T-cell subsets have been shown to oscillate in the blood, lymph, and lymph nodes in a circadian-dependent manner.^{42 43} This oscillation depends on the cyclical expression of pro-migratory chemokines and receptors, and these factors are expressed in a molecular clock-controlled, cell-autonomous manner.⁴⁴ Multiple groups have demonstrated more robust induction of autoimmune disease and greater antigen-specific T-cell responses when vaccines are administered during peak time-of-day nodal lymphocyte cellularity.^{22 42 43} This suggests that the anatomic localization of CD8+ T cells at the time of stimulation may influence their magnitude of response. In the context of tumor biology, it has now been shown that the time-of-day tumors are inoculated into mice influences the magnitude of the immune-mediated antitumor response.²³ Another study showed that rhythmic changes in PD-1 expression by tumor-infiltrating macrophages modulate response to PD-1 inhibition.⁴⁵ As ongoing preclinical studies investigate underlying mechanisms in more detail, the present clinical study adds to a growing body of literature that suggests a circadian dependence of the global and tumor-specific immune response.

There are several limitations to this study. First, it is retrospective and carries the potential for confounding. However, we performed a comprehensive multivariable analysis with adjustment for age, sex, ECOG, IMDC risk score, pretreatment LDH, RCC histology, and presence of bone, brain, and liver metastases, through which PFS and OS maintained statistical significance.³⁰ Second, infusion times varied widely across patients and for each patient, due to the flexibility given to patients to arrange their own infusion schedules. This flexibility invoked timing stratification to rely on proportions rather than fixed time intervals for infusion. A prospective randomized trial that directly assigns patients to specific time blocks for every infusion would help better determine the true effect of time-of-day ICI treatment on efficacy. Serial blood draws over the course of ICI treatment would also be valuable to correlate immunologic response with clinical outcomes.

Immunotherapy is the standard of care for many malignancies including mRCC. While the interplay between circadian rhythm and immunotherapy remains an area of active investigation, the findings presented herein justify further development of randomized studies that more concretely establish time-of-day optimization strategies for ICI management of patients with mRCC.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

Not applicable.

Footnote

Twitter @careyjans, @bilenma, @MohammadKhanMD, @haydnkissick, @zach_buchwald, @dave_qian

Contributors Conceptualization: DCQ and ZSB. Clinical data extraction and analysis: JSP, YW, LD, AD, DCQ. Writing—original draft preparation: JSP, ZSB, DCQ. Writing—review and editing: JSP, DCQ, ZSB, CSJ, JWC, PFI, FAL, VAM, MAB, MKK, MCL, and HK. All authors have read and agreed to the published version of the manuscript. Guarantors: JSP, ZSB, DCQ.

Funding JSP is supported by the T32 Training Program in Cancer Biology (National Institutes of Health grant T32CA275777). DCQ is supported by the Conquer Cancer Young Investigator Award (American Society of Clinical Oncology grant) and the Nell W. & William S. Elkin Fellowship (Winship Cancer Institute grant).

Disclaimer Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Emory University (RAD2620-13).

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

References

¹ Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin 2020; 70: 7–30. doi:10.3322/caac.21590

² Tran J, Ornstein MC. Clinical review on the management of metastatic renal cell carcinoma. JCO Oncol Pract 2022; 18: 187–96. doi:10.1200/OP.21.00419

³ Elmadjian F, Pincus G. A study of the diurnal variations in circulating lymphocytes in normal and psychotic subjects. J Clin Endocrinol Metab 1946; 6: 287–94. doi:10.1210/jcem-6-4-287

⁴ Gibbs J, Ince L, Matthews L, et al. An epithelial circadian clock controls pulmonary inflammation and glucocorticoid action. Nat Med 2014; 20: 919–26. doi:10.1038/nm.3599

⁵ Gibbs JE, Blaikley J, Beesley S, et al. The nuclear receptor REV-Erbalpha mediates circadian regulation of innate immunity through selective regulation of inflammatory Cytokines. Proc Natl Acad Sci U S A 2012; 109: 582–7. doi:10.1073/pnas.1106750109

⁶ Haspel JA, Anafi R, Brown MK, et al. Perfect timing: circadian rhythms, sleep, and immunity - an NIH workshop summary. JCI Insight 2020; 5: e131487. doi:10.1172/jci.insight.131487

⁷ Keller M, Mazuch J, Abraham U, et al. A circadian clock in macrophages controls inflammatory immune responses. Proc Natl Acad Sci U S A 2009; 106: 21407–12. doi:10.1073/pnas.0906361106

⁸ Nakao A. Temporal regulation of cytokines by the circadian clock. J Immunol Res 2014; 2014: 614529. doi:10.1155/2014/614529

⁹ Scheiermann C, Gibbs J, Ince L, et al. Clocking in to immunity. Nat Rev Immunol 2018; 18: 423–37. doi:10.1038/s41577-018-0008-4

¹⁰ Cash E, Sephton S, Woolley C, et al. The role of the circadian clock in cancer hallmark acquisition and immune-based cancer therapeutics. J Exp Clin Cancer Res 2021; 40: 119. doi:10.1186/s13046-021-01919-5

¹¹ Caussanel JP, Lévi F, Brienza S, et al. Phase I trial of 5-day continuous venous infusion of oxaliplatin at circadian rhythm-modulated rate compared with constant rate. J Natl Cancer Inst 1990; 82: 1046–50. doi:10.1093/jnci/82.12.1046

¹² Lévi F, Misset JL, Brienza S, et al. A Chronopharmacologic phase II clinical trial with 5-fluorouracil, folinic acid, and oxaliplatin using an ambulatory multichannel programmable pump. high antitumor effectiveness against metastatic colorectal cancer. Cancer 1992; 69: 893–900. doi:10.1002/1097-0142(19920215)69:4<893::aid-cncr2820690410>3.0.co;2-x

¹³ Lévi F, Zidani R, Misset JL. Randomised multicentre trial of chronotherapy with oxaliplatin, fluorouracil, and folinic acid in metastatic colorectal cancer. Lancet 1997; 350: 681–6. doi:10.1016/s0140-6736(97)03358-8

¹⁴ Deprés-Brummer P, Levi F, Di Palma M, et al. A phase I trial of 21-day continuous venous infusion of alpha-interferon at circadian rhythm modulated rate in cancer patients. J Immunother 1991; 10: 440–7. doi:10.1097/00002371-199112000-00008

¹⁵ Koren S, Whorton EB, Fleischmann WR. Circadian dependence of interferon antitumor activity in mice. J Natl Cancer Inst 1993; 85: 1927–32. doi:10.1093/jnci/85.23.1927

¹⁶ Ohdo S, Koyanagi S, Suyama H, et al. Changing the dosing schedule minimizes the disruptive effects of interferon on clock function. Nat Med 2001; 7: 356–60. doi:10.1038/85507

¹⁷ Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus Ipilimumab versus sunitinib in advanced renal-cell carcinoma. N Engl J Med 2018; 378: 1277–90. doi:10.1056/NEJMoa1712126

¹⁸ Rini BI, Plimack ER, Stus V, et al. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med 2019; 380: 1116–27. doi:10.1056/NEJMoa1816714

¹⁹ Qian DC, Kleber T, Brammer B, et al. Effect of immunotherapy time-of-day infusion on overall survival among patients with advanced melanoma in the USA (MEMOIR): a propensity score-matched analysis of a single-centre, longitudinal study. Lancet Oncol 2021; 22: 1777–86. doi:10.1016/S1470-2045(21)00546-5

²⁰ Landré T, Karaboué A, Buchwald ZS, et al. Effect of immunotherapy-infusion time of day on survival of patients with advanced cancers: a study-level meta-analysis. ESMO Open 2024; 9: 102220. doi:10.1016/j.esmoop.2023.102220

²¹ Karaboué A, Collon T, Pavese I, et al. Time-dependent efficacy of checkpoint inhibitor nivolumab: results from a pilot study in patients with metastatic non-small-cell lung cancer. Cancers 2022; 14: 896. doi:10.3390/cancers14040896

²² Long JE, Drayson MT, Taylor AE, et al. Morning vaccination enhances antibody response over afternoon vaccination: a cluster-randomised trial. Vaccine 2016; 34: 2679–85. doi:10.1016/j.vaccine.2016.04.032

²³ Wang C, Barnoud C, Cenerenti M, et al. Dendritic cells direct circadian anti-tumour immune responses. Nature 2023; 614: 136–43. doi:10.1038/s41586-022-05605-0

²⁴ Hodi FS, Ballinger M, Lyons B, et al. Immune-modified response evaluation criteria in solid tumors (imRECIST): refining guidelines to assess the clinical benefit of cancer immunotherapy. J Clin Oncol 2018; 36: 850–8. doi:10.1200/JCO.2017.75.1644

²⁵ Carlisle JW, Jansen CS, Cardenas MA, et al. Clinical outcome following checkpoint therapy in renal cell carcinoma is associated with a burst of activated CD8 T cells in blood. J Immunother Cancer 2022; 10: e004803. doi:10.1136/jitc-2022-004803

²⁶ Postow MA, Goldman DA, Shoushtari AN, et al. Adaptive dosing of nivolumab + ipilimumab Immunotherapy based upon early, interim radiographic assessment in advanced melanoma (the ADAPT-IT study). J Clin Oncol 2022; 40: 1059–67. doi:10.1200/JCO.21.01570

²⁷ Cortellini A, Tucci M, Adamo V, et al. Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice. J Immunother Cancer 2020; 8: e001361. doi:10.1136/jitc-2020-001361

²⁸ Kansal V, Burnham AJ, Kinney BLC, et al. Statin drugs enhance responses to immune checkpoint blockade in head and neck cancer models. J Immunother Cancer 2023; 11: e005940. doi:10.1136/jitc-2022-005940

²⁹ Zhang N, Zhang H, Zhu D, et al. Prognostic role of pretreatment lactate dehydrogenase in patients with metastatic renal cell carcinoma: a systematic review and meta-analysis. Int J Surg 2020; 79: 66–73. doi:10.1016/j.ijsu.2020.05.019

³⁰ McKay RR, Kroeger N, Xie W, et al. Impact of bone and liver metastases on patients with renal cell carcinoma treated with targeted therapy. Eur Urol 2014; 65: 577–84. doi:10.1016/j.eururo.2013.08.012

³¹ Choueiri TK, Motzer RJ, Rini BI, et al. Updated efficacy results from the JAVELIN renal 101 trial: first-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma. Ann Oncol 2020; 31: 1030–9. doi:10.1016/j.annonc.2020.04.010

³² Choueiri TK, Powles T, Burotto M, et al. Nivolumab plus cabozantinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med 2021; 384: 829–41. doi:10.1056/NEJMoa2026982

³³ Lefort F, Dalban C, Gross-Goupil M, et al. Association of corticosteroids with survival outcomes in patients with metastatic renal cell carcinoma treated with Nivolumab. JAMA Oncol 2023; 9: 1295–8. doi:10.1001/jamaoncol.2023.2296

³⁴ Motzer R, Alekseev B, Rha S-Y, et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N Engl J Med 2021; 384: 1289–300. doi:10.1056/NEJMoa2035716

³⁵ Powles T, Plimack ER, Soulières D, et al. Pembrolizumab plus axitinib versus sunitinib monotherapy as first-line treatment of advanced renal cell carcinoma (KEYNOTE-426): extended follow-up from a randomised, open-label, phase 3 trial. Lancet Oncol 2020; 21: 1563–73. doi:10.1016/S1470-2045(20)30436-8

³⁶ Ghatalia P, Gordetsky J, Kuo F, et al. Prognostic impact of immune gene expression signature and tumor infiltrating immune cells in localized clear cell renal cell carcinoma. J Immunother Cancer 2019; 7: 139. doi:10.1186/s40425-019-0621-1

³⁷ Kamphorst AO, Pillai RN, Yang S, et al. Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1-targeted therapy in lung cancer patients. Proc Natl Acad Sci U S A 2017; 114: 4993–8. doi:10.1073/pnas.1705327114

³⁸ Liikanen I, Lauhan C, Quon S, et al. Hypoxia-inducible factor activity promotes antitumor effector function and tissue residency by CD8+ T cells. J Clin Invest 2021; 131: e143729. doi:10.1172/JCI143729

³⁹ Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009; 45: 228–47. doi:10.1016/j.ejca.2008.10.026

⁴⁰ Patel J, Draper A, Woo Y, et al. Impact of Immunotherapy time-of-day infusion on overall survival in patients with metastatic renal cell carcinoma. J Immunother Cancer 2022; 10: 848. doi:10.1136/jitc-2022-SITC2022.0848

⁴¹ Nomura M, Hosokai T, Tamaoki M, et al. Timing of the infusion of nivolumab for patients with recurrent or metastatic squamous cell carcinoma of the esophagus influences its efficacy. Esophagus 2023; 20: 722–31. doi:10.1007/s10388-023-01006-y

⁴² de Bree LCJ, Mourits VP, Koeken VA, et al. Circadian rhythm influences induction of trained immunity by BCG vaccination. J Clin Invest 2020; 130: 5603–17. doi:10.1172/JCI133934

⁴³ Phillips AC, Gallagher S, Carroll D, et al. Preliminary evidence that morning vaccination is associated with an enhanced antibody response in men. Psychophysiology 2008; 45: 663–6. doi:10.1111/j.1469-8986.2008.00662.x

⁴⁴ Druzd D, Matveeva O, Ince L, et al. Lymphocyte circadian clocks control lymph node trafficking and adaptive immune responses. Immunity 2017; 46: 120–32. doi:10.1016/j.immuni.2016.12.011

⁴⁵ Tsuruta A, Shiiba Y, Matsunaga N, et al. Diurnal expression of PD-1 on tumor-associated macrophages underlies the dosing time-dependent antitumor effects of the PD-1/PD-L1 inhibitor BMS-1 in B16/Bl6 melanoma-bearing mice. Mol Cancer Res 2022; 20: 972–82. doi:10.1158/1541-7786.MCR-21-0786