Donor-derived cell-free DNA detects kidney transplant rejection during nivolumab treatment

Background: In solid organ transplant (SOT) recipients, transplant rejection during immune checkpoint inhibitor (ICI) treatment for cancer is a clinical problem. Donor-derived cell-free DNA (dd-cfDNA) can be detected in blood and is a sensitive biomarker for diagnosis of acute rejection in SOT recipients. To our best knowledge, this is the first case report of a kidney transplant recipient with advanced cancer treated with ICI who was monitored with dd-cfDNA. Case presentation: A 72-year old female with a long-standing renal transplant was diagnosed with advanced melanoma in 2018 and was treated with the anti-PD1 antibody nivolumab. Within 12 days after the first administration of nivolumab, dd-cfDNA ratio increased to 23%, suggesting allograft rejection. Her kidney transplant function deteriorated and acute rejection was confirmed by renal transplant biopsy. As the rejection could not be controlled despite immunosuppressive treatment, a transplant nephrectomy was necessary and haemodialysis was started. Immunological analysis of the renal explant showed infiltration of alloreactive, nivolumab-saturated, PD1+ cytotoxic T cells. After transplant nephrectomy, she experienced nivolumab-related toxicity and rapid disease progression. Conclusion: Clinicians prescribing ICIs should be aware that SOT recipients are a

Blood-based kinase activity profiling: A potential predictor of response to immune checkpoint inhibition in metastatic cancer

Background Many cancer patients do not obtain clinical benefit from immune checkpoint inhibition. Checkpoint blockade targets T cells, suggesting that tyrosine kinase activity profiling of baseline peripheral blood mononuclear cells may predict clinical outcome. Methods Here a total of 160 patients with advanced melanoma or non-small-cell lung cancer (NSCLC), treated with anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) or anti-programmed cell death 1 (anti-PD-1), were divided into five discovery and cross-validation cohorts. The kinase activity profile was generated by analyzing phosphorylation of peripheral blood mononuclear cell lysates in a microarray comprising of 144 peptides derived from sites that are substrates for protein tyrosine kinases. Binary grouping into patients with or without clinical benefit was based on Response Evaluation Criteria in Solid Tumors V.1.1. Predictive models were trained using partial least square discriminant analysis (PLS-DA), performance of the models was evaluated by estimating the correct classification rate (CCR) using cross-validation. Results The kinase phosphorylation signatures segregated responders from non-responders by differences in canonical pathways governing T-cell migration, infiltration and co-stimulation. PLS-DA resulted in a CCR of 100% and 93% in the anti-CTLA-4 and anti-PD1 melanoma discovery cohorts, respectively. Cross-validation cohorts to estimate the accuracy of the predictive models showed CCRs of 83% for anti-CTLA-

A Serum Protein Classifier Identifying Patients with Advanced Non–Small Cell Lung Cancer Who Derive Clinical Benefit from Treatment with Immune Checkpoint Inhibitors

Purpose: Pretreatment selection of patients with non–small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings. Experimental Design: In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care (n ¼ 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good (“sensitive”), intermediate, and poor (“resistant”) outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA). Results: A signature consisting of 274 MS features derived from a development set of 116 patients was associated wit

The prognostic value of weight and body composition changes in patients with non-small-cell lung cancer treated with nivolumab

BACKGROUND: It is not well known to what extent effectiveness of treatment with immune checkpoint inhibitors in stage IV non‐small‐cell lung cancer (NSCLC) is influenced by weight loss and changes in body composition. Therefore, the goal of this study was to evaluate body composition changes in relation to early weight change and overall survival (OS) in stage IV NSCLC patients treated with second‐line nivolumab. METHODS: All patients with stage IV NSCLC, who were treated with second‐line nivolumab between June 2015 and December 2018 at Maastricht University Medical Center, were evaluated. Skeletal muscle mass (SMM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were assessed at the first lumbar level on computed tomography images obtained before initiation of nivolumab and at week 6 of treatment. The contribution of changes in body weight (defined as >2% loss), SMM, VAT, and SAT to OS was analysed by Kaplan–Meier method and adjusted for clinical confounders in a Cox regression analysis. The results from the study cohort were validated in another Dutch cohort from Erasmus Medical Center, Rotterdam. RESULTS: One hundred and six patients were included in the study cohort. Loss of body weight of >2% at week 6 was an independent predictor for poor OS (hazard ratio 2.39, 95% confidence interval 1.51–3.79, P 1 organ with metastasis, pretreatment hypoalbumenaemia, and pretreatment elevated C‐reactive protein. The result was confirmed in the validation cohort (N = 62). Loss of SMM as a feature of cancer cachexia did not significantly predict OS in both cohorts. Significant (>2%) weight loss during treatment was reflected by a significant loss of VAT and SAT, while loss of SMM was comparable between weight‐stable and weight‐losing patients. CONCLUSIONS: Weight loss, characterized by loss of subcutaneous and visceral adipose tissues, at week 6 of treatment with nivolumab, is a significant poor prognostic factor for survival in patients with Stage IV NSCLC

Tumor mutational load, CD8+ T cells, expression of PD-L1 and HLA class I to guide immunotherapy decisions in NSCLC patients

Objectives: A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitors. A rational combination of biomarkers is needed. The objective was to determine the predictive value of tumor mutational load (TML), CD8+ T cell infiltration, HLA class-I and PD-L1 expression in the tumor. Materials and methods: Metastatic NSCLC patients were prospectively included in an immune-monitoring trial (NTR7015) between April 2016-August 2017, retrospectively analyzed in FFPE tissue for TML (NGS: 409 cancer-related-genes) and by IHC staining to score PD-L1, CD8+ T cell infiltration, HLA class-I. PFS (RECISTv1.1) and OS were analyzed by Kaplan–Meier methodology. Results: 30 patients with adenocarcinoma (67%) or squamous cell carcinoma (33%) were included. High TML was associated with better PFS (p = 0.004) and OS (p = 0.025). Interaction analyses revealed that patients with both high TML and high total CD8+ T cell infiltrate (p = 0.023) or no loss of HLA class-I (p = 0.026), patients with high total CD8+ T cell infiltrate and no loss of HLA class-I (p = 0.041) or patients with both high PD-L1 and high TML (p = 0.003) or no loss of HLA class-I (p = 0.032) were significantly associated with better PFS. Unsupervised cluster analysis based on these markers revealed three sub-clusters, of which cluster-1A was overrepresented by patients with progressive disease (15 out of 16), with significant effect on PFS (p = 0.007). Conclusion: This proof-of-concept study suggests that a combination of PD-L1 expression, TML, CD8+ T cell infiltration and HLA class-I functions as a better predictive biomarker for response to anti-PD-1 immunotherapy. Consequently, refinement of this set of biomarkers and validation in a larger set of patients is warranted

Influence of esomeprazole on the bioavailability of afatinib: A pharmacokinetic cross-over study in patients with non-small cell lung cancer

Afatinib is an oral small-molecule kinase inhibitor (SMKI) approved for treatment of metastatic non-small cell lung cancer (NSCLC) with an epidermal growth factor receptor (EGFR) driver mutation. Although oral administration is convenient, most SMKIs experience pH-dependent solubility. A drug-drug interaction between afatinib and proton-pump inhibitors (PPIs) has, however, never been studied in humans. Hence, we performed a randomized, three-period cross-over study. Afatinib (30 mg or 40 mg) was administered without PPI (period A), concomitantly with esomeprazole (period B) and three hours after esomeprazole intake (period C). Primary objective was the area under the curve (AUC0–24 h) comparing period A to period B and period A to period C. Secondary objectives were other pharmacokinetic parameters and toxicity. Linear mixed effect modelling was performed for differences in AUC0–24 h and Cmax between periods A and B and periods A and C. In 18 evaluable NSCLC patients, concomitant use of 40 mg esomeprazole decreased the steady-state afatinib AUC0–24 h with 10.2% (95% CI −29.2 to +14.0%; p = 0.564) compared to afatinib administration without PPI. Esomeprazole intake three hours prior to afatinib did not significantly influence afatinib AUC0–24 h (−0.6%; 95% CI −14.9 to +16.1%; p = 1.0). No differences in toxicity were observed. To conclude, esomeprazole did not change the exposure to afatinib in patients with NSCLC. Since there is no clinically relevant drug-drug interaction, esomeprazole can safely be co-administered with afatinib. This is important for clinical practice, because other EGFR-SMKIs (e.g. erlotinib and gefitinib) do experience clinically relevant drug-drug interactions with acid-suppressive agents

Germline variation in pdcd1 is associated with overall survival in patients with metastatic melanoma treated with anti‐pd‐1 monotherapy

A substantial number of melanoma patients do not benefit from therapy with anti‐PD‐1. Therefore, we investigated the predictive value of single nucleotide polymorphisms (SNPs) in genes related to the PD‐1 axis in patients with metastatic melanoma. From 119 consecutive melanoma patients who were treated with pembrolizumab or nivolumab monotherapy, blood samples were genotyped for 11 SNPs in nine genes. Associations between SNPs and OS were tested using Cox regression analysis and internally validated by bootstrapping. For SNPs with a statistical significance, an expression quantitative trait loci (eQTL) analysis was performed. In a subset of patients, immunophenotyping was performed. Patients with a SNP in PDCD1 (804C > T; rs2227981) had a significantly poorer OS with a 3‐year OS rate of 51.8%, as compared to 71% in wild type patients (hazard ratio [HR] 2.37; 95% CI: 1.11–5.04; p = 0.026). eQTL analysis showed that this SNP was associated with decreased gene expression. In addition, PDCD1 804C > T carriers had a reduced fraction of peripheral PD‐1+CD4+ T cells. No other associations between SNPs and OS were found. PDCD1 804C > T is associated with poorer OS after anti‐PD‐1 monotherapy in patients with metastatic melanoma. This SNP may affect clinical benefit from ICIs by decreasing transcription initiation and expression of PD‐1 in T cells

Associations between patient and disease characteristics and severe adverse events during immune checkpoint inhibitor treatment: An observational study

Aim: With increasing use of immune checkpoint inhibitors (ICIs) more patients will develop severe and potentially life-threatening immune-related adverse events (irAEs). So far, predictive models for the occurrence of grade ≥3 irAEs are lacking. Therefore, we analysed associations between patient and disease characteristics, and the occurrence of grade ≥3 irAEs. Methods: Patients with cancer who were treated with anti-PD-1 (+/−anti-CTLA-4) between July 2015 and February 2020, and who were prospectively included in the MULTOMAB-trial, were eligible for this cohort study. Time to and occurrence of grade ≥3 irAEs according to CTCAE v5.0 were retrospectively registered. The associations between patient and disease characteristics and irAE occurrence were analysed using the competing risk cox-regression model of Fine and Gray. Analyses were performed separately in patients treated with monotherapy (anti-PD-1) and combination therapy (anti-PD-1 + anti-CTLA-4). Subgroup analyses were performed in tumour types with the highest number of patients; melanoma and NSCLC. Results: Out of 641 patients, 106 patients (17%) experienced grade ≥3 irAEs. None of the analysed factors were associated with grade ≥3 irAE occurrence in the monotherapy (n = 550) or the combination therapy (n = 91) groups, nor in the subgroup analyses. Of interest, none of the patients with NSCLC with a WHO performance status of 0 (n = 34) experienced grade ≥3 irAEs. Most common NSCLC histology types were adenocarcinoma (n = 99/55%) and squamous cell carcinoma (n = 39/22%). Concluding statement: This study shows that patient and disease characteristics are not able to predict the occurrence of serious AEs in patients treated with ICIs

A prospective cohort study on the pharmacokinetics of nivolumab in metastatic non-small cell lung cancer, melanoma, and renal cell cancer patients

textabstractBackground: Nivolumab is administered in a weight-based or fixed-flat dosing regimen. For patients with non-small cell lung cancer (NSCLC), a potential exposure-response relationship has recently been reported and may argue against the current dosing strategies. The primary objectives were to determine nivolumab pharmacokinetics (PK) and to assess the relationship between drug clearance and clinical outcome in NSCLC, melanoma, and renal cell cancer (RCC). Methods: In this prospective observational cohort study, individual estimates of nivolumab clearance and the impact of baseline covariates were determined using a population-PK model. Clearance was related to best overall response (RECISTv1.1), and stratified by tumor type. Results: Two-hundred-twenty-one patients with metastatic cancer receiving nivolumab-monotherapy were included of whom 1,715 plasma samples were analyzed. Three baseline parameters had a significant effect on drug clearance and were internally validated in the population-PK model: gender, BSA, and serum albumin. Women had 22% lower clearance compared to men, while the threshold of BSA and albumin that led to > 20% increase of clearance was > 2.2m2 and < 37.5 g/L, respectively. For NSCLC, drug clearance was 42% higher in patients with progressive disease (mean: 0.24; 95% CI: 0.22-0.27 L/day) compared to patients with partial/complete response (mean: 0.17; 95% CI: 0.15-0.19 L/day). A similar trend was observed in RCC, however, no clearance-response relationship was observed in melanoma. Conclusions: Based on the first real-world population-PK model of nivolumab, covariate analysis revealed a significant effect of gender, BSA, and albumin on nivolumab clearance. A clearance-response relationship was observed in NSCLC, with a non-significant trend in RCC, but not in melanoma. Individual pharmacology of nivolumab in NSCLC appears important and should be prospectively studied