Dataset Information

Early dynamics of circulating tumor DNA predict clinical response to immune checkpoint inhibitors in metastatic renal cell carcinoma.

ABSTRACT:

Objectives

Detection of genomic alterations in circulating tumor deoxyribonucleic acid of peripheral blood can guide the selection of systemic therapy in cancer patients. The predictive significance of circulating tumor deoxyribonucleic acid in metastatic renal cell carcinoma remains unclear, especially for patients treated with immune checkpoint inhibitors.

Methods

In this study, we collected plasma samples before and 1 month after commencing nivolumab monotherapy or nivolumab plus ipilimumab therapy from 14 metastatic renal cell carcinoma patients. We performed circulating tumor deoxyribonucleic acid genomic profiling in plasma cell-free deoxyribonucleic acid by next-generation sequencing using a commercially available pan-cancer panel (Guardant360 CDx). Additionally, we also performed whole exome sequencing of tumor tissues and compared the concordance of genomic profiles with circulating tumor deoxyribonucleic acid.

Results

Nine patients had circulating tumor deoxyribonucleic acid in pretreatment plasma samples with a total of 20 mutations (15 single nucleotide variants, three insertions/deletions, and two copy number amplification). VHL (30.0%) was the most frequently mutated gene, followed by TP53 (20.0%), and 45.0% of circulating tumor deoxyribonucleic acid mutations were concordant with somatic mutations in tumor tissues. Patients with decreasing circulating tumor deoxyribonucleic acid mutant allele frequency had better progression free survival when compared to those with increasing mutant allele frequency (P = 0.0441).

Conclusions

Our findings revealed that early circulating tumor deoxyribonucleic acid dynamics can serve as a predictive biomarker for response to immune checkpoint inhibitors in metastatic renal cell carcinoma patients.

SUBMITTER: Koh Y

PROVIDER: S-EPMC9306972 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria are the gold standard for risk-stratifying patients with metastatic renal cell cancer (mRCC). We developed a novel risk scoring system for patients with mRCC treated with immune checkpoint inhibitors (ICIs).MethodsWe performed a retrospective analysis of 100 ICI-treated patients with mRCC at Winship Cancer Institute from 2015 to 2018. Several baseline variables were collected, including markers of inflammation, body mass index (BMI), and sites of metastatic disease, and all were considered for inclusion in our risk scoring system. Upon variable selection in multivariable model, monocyte-to-lymphocyte ratio (MLR), BMI, and number and sites of metastases at baseline were used for risk score calculation. Patients were categorized using four-level risk groups as good (risk score = 0), intermediate (risk score = 1), poor (risk score = 2), or very poor (risk score = 3-4). Cox's proportional hazard model and the Kaplan-Meier method were implemented for survival outcomes.ResultsMost patients were male (66%) with clear cell renal cell carcinoma (72%). The majority (71%) received anti-programmed cell death protein-1 monotherapy. Our risk scoring criteria had higher Uno's concordance statistics than IMDC in predicting overall survival (OS; 0.71 vs. 0.57) and progression-free survival (0.61 vs. 0.58). Setting good risk (MLR <0.93, BMI ≥24, and D_Met = 0) as the reference, the OS hazard ratios were 29.5 (95% confidence interval [CI], 3.64-238.9), 6.58 (95% CI, 0.84-51.68), and 3.75 (95% CI, 0.49-28.57) for very poor, poor, and intermediate risk groups, respectively.ConclusionRisk scoring using MLR, BMI, and number and sites of metastases may be an effective way to predict survival in patients with mRCC receiving ICI. These results should be validated in a larger, prospective study.Implications for practiceA risk scoring system was created for patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors. The results of this study have significant implications for practicing oncologists in the community and academic setting. Importantly, these results identify readily available risk factors that can be used clinically to risk-stratify patients with metastatic renal cell carcinoma who are treated with immune checkpoint inhibitors.

Project description:BackgroundImmune checkpoint inhibitors (ICIs) are an important treatment for metastatic renal cell carcinoma (mRCC). These agents may cause immune-related adverse events (irAEs), and the relationship between irAEs and outcomes is poorly understood. We investigated the association between irAEs and clinical outcomes in patients with mRCC treated with ICIs.MethodsWe performed a retrospective study of 200 patients with mRCC treated with ICIs at Winship Cancer Institute from 2015 to 2020. Data on irAEs were collected from clinic notes and laboratory values and grades were determined using Common Terminology Criteria in Adverse Events version 5.0. The association with overall survival (OS) and progression-free survival (PFS) was modeled by Cox proportional hazards model. Logistic regression models were used to define odds ratios (ORs) for clinical benefit (CB). Landmark analysis and extended Cox models were used to mitigate lead-time bias by treating irAEs as a time-varying covariate.ResultsMost patients (71.0%) were male, and one-third of patients (33.0%) experienced at least one irAE, most commonly involving the endocrine glands (13.0%), gastrointestinal tract (10.5%), or skin (10.0%). Patients who experienced irAEs had significantly longer OS (hazard ratio [HR], 0.52; p = .013), higher chance of CB (OR, 2.10; p = .023) and showed a trend toward longer PFS (HR, 0.71; p = .065) in multivariate analysis. Patients who had endocrine irAEs, particularly thyroid irAEs, had significantly longer OS and PFS and higher chance of CB. In a 14-week landmark analysis, irAEs were significantly associated with prolonged OS (p = .045). Patients who experienced irAEs had significantly longer median OS (44.5 vs. 18.2 months, p = .005) and PFS (7.5 vs. 3.6 months, p = .003) without landmark compared with patients who did not.ConclusionWe found that patients with mRCC treated with ICIs who experienced irAEs, particularly thyroid irAEs, had significantly improved clinical outcomes compared with patients who did not have irAEs. This suggests that irAEs may be effective clinical biomarkers in patients with mRCC treated with ICIs. Future prospective studies are warranted to validate these findings.Implications for practiceThis study found that early onset immune-related adverse events (irAEs) are associated with significantly improved clinical outcomes in patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs). In this site-specific irAE analysis, endocrine irAEs, particularly thyroid irAEs, were significantly associated with improved clinical outcomes. These results have implications for practicing medical oncologists given the increasing use of ICIs for the treatment of mRCC. Importantly, these results suggest that early irAEs and thyroid irAEs at any time on treatment with ICIs may be clinical biomarkers of clinical outcomes in patients with mRCC treated with ICIs.

Project description:BackgroundImmune checkpoint inhibitors (ICI) have revolutionized the treatment of metastatic renal cell carcinoma (mRCC). Biomarkers for mRCC patients treated with ICI are limited, and body composition is underutilized in mRCC. We investigated the association between body composition and clinical outcomes in ICI-treated mRCC patients.MethodsWe performed a retrospective analysis of 79 ICI-treated mRCC patients at Winship Cancer Institute from 2015-2020. Baseline CT images were collected at mid-L3 and segmented using SliceOMatic v5.0 (TomoVision). Density of skeletal muscle (SM), subcutaneous fat, inter-muscular fat, and visceral fat were measured and converted to indices by dividing by height(m)2 (SMI, SFI, IFI, and VFI, respectively). Total fat index (TFI) was defined as the sum of SFI, IFI, and VFI. Patients were characterized as high versus low for each variable at gender-specific optimal cuts using overall survival (OS) as the primary outcome. A prognostic risk score was created based on the beta coefficient from the multivariable Cox model after best subset variable selection. Body composition risk score was calculated as IFI + 2*SM mean + SFI and patients were classified as poor (0-1), intermediate (2), or favorable risk (3-4). Kaplan-Meier method and Log-rank test were used to estimate OS and PFS and compare the risk groups. Concordance statistics (C-statistics) were used to measure the discriminatory magnitude of the model.ResultsMost patients were male (73%) and most received ICI as first (35%) or second-line (51%) therapy. The body composition poor-risk patients had significantly shorter OS (HR: 6.37, p<0.001), PFS (HR: 4.19, p<0.001), and lower chance of CB (OR: 0.23, p=0.044) compared to favorable risk patients in multivariable analysis. Patients with low TFI had significantly shorter OS (HR: 2.72, p=0.002), PFS (HR: 1.91, p=0.025), and lower chance of CB (OR: 0.25, p=0.008) compared to high TFI patients in multivariable analysis. The C-statistics were higher for body composition risk groups and TFI (all C-statistics ≥ 0.598) compared to IMDC and BMI.ConclusionsRisk stratification using the body composition variables IFI, SM mean, SFI, and TFI may be prognostic and predictive of clinical outcomes in mRCC patients treated with ICI. Larger, prospective studies are warranted to validate this hypothesis-generating data.