A phase 2 trial combining afatinib with cetuximab in patients with EGFR exon 20 insertion-positive non-small cell lung cancer.

BACKGROUND: Epidermal growth factor receptor (EGFR) exon 20 insertion (ex20ins) mutations are the third most common EGFR mutations in patients with non-small cell lung cancer (NSCLC) and are associated with primary resistance to EGFR tyrosine kinase inhibitors (TKIs). There is evidence of activity of combining EGFR TKIs with monoclonal antibodies. This study reports on the efficacy and safety of afatinib in combination with cetuximab. METHODS: In this single-arm phase 2 trial, patients with advanced NSCLC harboring an EGFR ex20ins mutation were treated with afatinib 40 mg once daily in combination with cetuximab 500 mg/m2 every 2 weeks. The primary end point was disease control rate (DCR) at 18 weeks of treatment. RESULTS: Thirty-seven patients started treatment, with a median age of 65 years (range, 40-80 years), 78% female, and 95% White. The study achieved its primary end point with a DCR of 54% at 18 weeks, an overall response rate (ORR) of 43%, and a 32% confirmed ORR. Best responses were partial (n = 16), stable (n = 16), progressive disease (n = 2), or not evaluable (n = 3). Median progression-free survival was 5.5 months (95% CI, 3.7-8.3 months) and median overall survival was 16.8 months (95% CI, 10.7-25.8 months). The most common treatment-related adverse events (TRAEs) were diarrhea (70%), rash (65%), dry skin (59%), paronychia (54%), and erythema (43%). Grade 3 TRAEs were reported in 54% of all patients. CONCLUSIONS: Combination treatment with afatinib and cetuximab demonstrated antitumor activity with a DCR of 54% at 18 weeks and a 32% confirmed ORR. Toxicity was significant, although manageable, after dose reduction.

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium.

BACKGROUND: Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands). METHODS: Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance. RESULTS: A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately. CONCLUSIONS: Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine.

Blood platelet RNA profiles do not enable for nivolumab response prediction at baseline in patients with non-small cell lung cancer.

BACKGROUND: Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content. OBJECTIVE: We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses. METHODS: We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm. RESULTS: We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63-0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51-0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45-0.70, n = 107 samples)), employing a five-RNAs biomarker panel. CONCLUSIONS: We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass.

OBJECTIVE: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). METHODS: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. RESULTS: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. CONCLUSION: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

Tumour-educated platelets for breast cancer detection: biological and technical insights.

BACKGROUND: Studies have shown that blood platelets contain tumour-specific mRNA profiles tumour-educated platelets (TEPs). Here, we aim to train a TEP-based breast cancer detection classifier. METHODS: Platelet mRNA was sequenced from 266 women with stage I-IV breast cancer and 212 female controls from 6 hospitals. A particle swarm optimised support vector machine (PSO-SVM) and an elastic net-based classifier (EN) were trained on 71% of the study population. Classifier performance was evaluated in the remainder (29%) of the population, followed by validation in an independent set (37 cases and 36 controls). Potential confounding was assessed in post hoc analyses. RESULTS: Both classifiers reached an area under the curve (AUC) of 0.85 upon internal validation. Reproducibility in the independent validation set was poor with an AUC of 0.55 and 0.54 for the PSO-SVM and EN classifier, respectively. Post hoc analyses indicated that 19% of the variance in gene expression was associated with hospital. Genes related to platelet activity were differentially expressed between hospitals. CONCLUSIONS: We could not validate two TEP-based breast cancer classifiers in an independent validation cohort. The TEP protocol is sensitive to within-protocol variation and revision might be necessary before TEPs can be reconsidered for breast cancer detection.

A review on genetic alterations in CNS metastases related to breast cancer treatment. Is there a role for liquid biopsies in CSF?

Acquired mutations or altered gene expression patterns in brain metastases (BM) and/or leptomeningeal metastases (LM) of breast cancer may play a role in therapy-resistance and offer new molecular targets and treatment options. Despite expanding knowledge of genetic alterations in breast cancer and their metastases, clinical applications for patients with central nervous system (CNS) metastases are currently limited. An emerging tool are DNA-techniques that may detect genetic alterations of the CNS metastases in the cerebrospinal fluid (CSF). In this review we discuss genetic studies in breast cancer and CNS metastases and the role of liquid biopsies in CSF.

Dutch National Round Robin Trial on Plasma-Derived Circulating Cell-Free DNA Extraction Methods Routinely Used in Clinical Pathology for Molecular Tumor Profiling.

BACKGROUND: Efficient recovery of circulating tumor DNA (ctDNA) depends on the quantity and quality of circulating cell-free DNA (ccfDNA). Here, we evaluated whether various ccfDNA extraction methods routinely applied in Dutch laboratories affect ccfDNA yield, ccfDNA integrity, and mutant ctDNA detection, using identical lung cancer patient-derived plasma samples. METHODS: Aliquots of 4 high-volume diagnostic leukapheresis plasma samples and one artificial reference plasma sample with predetermined tumor-derived mutations were distributed among 14 Dutch laboratories. Extractions of ccfDNA were performed according to local routine standard operating procedures and were analyzed at a central reference laboratory for mutant detection and assessment of ccfDNA quantity and integrity. RESULTS: Mutant molecule levels in extracted ccfDNA samples varied considerably between laboratories, but there was no indication of consistent above or below average performance. Compared to silica membrane-based methods, samples extracted with magnetic beads-based kits revealed an overall lower total ccfDNA yield (-29%; P < 0.0001) and recovered fewer mutant molecules (-41%; P < 0.01). The variant allelic frequency and sample integrity were similar. In samples with a higher-than-average total ccfDNA yield, an augmented recovery of mutant molecules was observed. CONCLUSIONS: In the Netherlands, we encountered diversity in preanalytical workflows with potential consequences on mutant ctDNA detection in clinical practice. Silica membrane-based methodologies resulted in the highest total ccfDNA yield and are therefore preferred to detect low copy numbers of relevant mutations. Harmonization of the extraction workflow for accurate quantification and sensitive detection is required to prevent introduction of technical divergence in the preanalytical phase and reduce interlaboratory discrepancies.

An Automated Correction Algorithm (ALPACA) for ddPCR Data Using Adaptive Limit of Blank and Correction of False Positive Events Improves Specificity of Mutation Detection.

BACKGROUND: Bio-Rad droplet-digital PCR is a highly sensitive method that can be used to detect tumor mutations in circulating cell-free DNA (cfDNA) of patients with cancer. Correct interpretation of ddPCR results is important for optimal sensitivity and specificity. Despite its widespread use, no standardized method to interpret ddPCR data is available, nor have technical artifacts affecting ddPCR results been widely studied. METHODS: False positive rates were determined for 6 ddPCR assays at variable amounts of input DNA, revealing polymerase induced false positive events (PIFs) and other false positives. An in silico correction algorithm, known as the adaptive LoB and PIFs: an automated correction algorithm (ALPACA), was developed to remove PIFs and apply an adaptive limit of blank (LoB) to individual samples. Performance of ALPACA was compared to a standard strategy (no PIF correction and static LoB = 3) using data from commercial reference DNA, healthy volunteer cfDNA, and cfDNA from a real-life cohort of 209 patients with stage IV nonsmall cell lung cancer (NSCLC) whose tumor and cfDNA had been molecularly profiled. RESULTS: Applying ALPACA reduced false positive results in healthy cfDNA compared to the standard strategy (specificity 98 vs 88%, P = 10-5) and stage IV NSCLC patient cfDNA (99 vs 93%, P = 10-11), while not affecting sensitivity in commercial reference DNA (70 vs 68% P = 0.77) or patient cfDNA (82 vs 88%, P = 0.13). Overall accuracy in patient samples was improved (98 vs 92%, P = 10-7). CONCLUSIONS: Correction of PIFs and application of an adaptive LoB increases specificity without a loss of sensitivity in ddPCR, leading to a higher accuracy in a real-life cohort of patients with stage IV NSCLC.

Validation of a clinical blood-based decision aid to guide immunotherapy treatment in patients with non-small cell lung cancer.

BACKGROUND: The widespread introduction of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has led to durable responses but still many patients fail and are treated beyond progression. OBJECTIVE: This study investigated whether readily available blood-based tumor biomarkers allow accurate detection of early non-responsiveness, allowing a timely switch of therapy and cost reduction. METHODS: In a prospective, observational study in patients with NSCLC treated with nivolumab or pembrolizumab, five serum tumor markers were measured at baseline and every other week. Six months disease control as determined by RECIST was used as a measure of clinical response. Patients with a disease control <  6 months were deemed non-responsive. For every separate tumor marker a criterion for predicting of non-response was developed. Each marker test was defined as positive (predictive of non-response) if the value of that tumor marker increased at least 50% from the value at baseline and above a marker dependent minimum value to be determined. Also, tests based on combination of multiple markers were designed. Specificity and sensitivity for predicting non-response was calculated and results were validated in an independent cohort. The target specificity of the test for detecting non-response was set at >  95%, in order to allow its safe use for treatment decisions. RESULTS: A total of 376 patients (training cohort: 180, validation cohort: 196) were included in our analysis. Results for the specificity of the single marker tests in the validation set were CEA: 98·3% (95% CI: 90·9-100%), NSE: 96·5% (95% CI: 87·9-99·6%), SCC: 96·5% (95% CI: 88·1-99·6%), Cyfra21·1 : 91.8% (95% CI: 81·9-97·3%), and CA125 : 86·0% (95% CI: 74·2-93·7%). A test based on the combination of Cyfra21.1, CEA and NSE accurately predicted non-response in 32.3% (95% CI 22.6-43.1%) of patients 6 weeks after start of immunotherapy. Survival analysis showed a significant difference between predicted responders (Median PFS: 237 days (95% CI 184-289 days)) and non-responders (Median PFS: 58 days (95% CI 46-70 days)) (p <  0.001). CONCLUSIONS: Serum tumor marker based tests can be used for accurate detection of non-response in NSCLC, thereby allowing early and safe discontinuation of immunotherapy in a significant subset of patients.

The diagnostic accuracy of human epididymis protein 4 (HE4) for discriminating between benign and malignant pelvic masses: a systematic review and meta-analysis.

INTRODUCTION: Many women with benign pelvic masses, suspected of ovarian cancer, are unnecessarily referred for treatment at specialized centers. There is an unmet clinical need to improve diagnostic assessment in these patients. Our objective was to obtain summary estimates of the accuracy of human epididymis protein (HE4) for diagnosing ovarian cancer and to compare the performance of HE4 with that of cancer antigen 125 (CA125). MATERIAL AND METHODS: We searched PubMed, Ovid and Scopus using search terms for "pelvic masses" and "HE4", to identify studies that evaluated HE4 for diagnosing malignant ovarian masses, in adult women presenting with a pelvic mass, suspected of ovarian cancer, and with diagnosis confirmed by histopathology. Screening, data extraction and Risk of Bias assessment with the QUADAS-2 tool were done independently by two authors. We performed a meta-analysis of the accuracy of HE4 and CA125 using a random-effects bivariate logit-normal model. A study protocol was registered at PROSPERO (CRD42020158073). RESULTS: In the 17 eligible studies, which included 3404 patients, ovarian cancer prevalence ranged from 15% to 71%. Overall, the studies were heterogeneous. All studies seemed to have recruited patients in specialized settings. A meta-analysis of seven HE4 studies resulted in a mean sensitivity of 79.4% (95% confidence interval [CI] 74.1%-83.8%) and a mean specificity of 84.1% (95% CI 79.6%-87.8%), for cut-off values of 67-72 pmol/L. Based on eight studies, the mean sensitivity of CA125 was 81.4% (95% CI 74.6%-86.2%) and the mean specificity was 56.8% (95% CI 47.9%-65.4%), at a cut-off of 35 U/ml. Given a 40% ovarian cancer prevalence, the positive predictive value (PPV) for HE4 would be 76.9% (71.9%-81.2%) vs 55.6% (50.2%-60.9%) for CA125. The negative predictive value (NPV) would be 85.9 (82.8%-88.6%) and 81.9% (76.2%-86.4%), respectively. At a 15% prevalence, the NPV would be 95.8% (95% CI 94.4%-96.7%) for HE4 and 94.4% (95% CI 92.3%-96.0%) for CA125. The PPV would be 46.9% (40.4%-53.4%) and 24.9% (21.1%-29.2%), respectively. CONCLUSIONS: HE4 had higher specificity and similar sensitivity compared with CA125. At high prevalence, PPV was also higher for HE4, but at low prevalence, it had a similar NPV to CA125. The field would benefit from studies conducted in general settings.