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Supplementary Data from PD-1T TILs as a Predictive Biomarker for Clinical Benefit to PD-1 Blockade in Patients with Advanced NSCLC

Purpose:Durable clinical benefit to PD-1 blockade in non–small cell lung cancer (NSCLC) is currently limited to a small fraction of patients, underlining the need for predictive biomarkers. We recently identified a tumor-reactive tumor-infiltrating T lymphocyte (TIL) pool, termed PD-1T TILs, with predictive potential in NSCLC. Here, we examined PD-1T TILs as biomarker in NSCLC.Experimental Design:PD-1T TILs were digitally quantified in 120 baseline samples from advanced NSCLC patients treated with PD-1 blockade. Primary outcome was disease control (DC) at 6 months. Secondary outcomes were DC at 12 months and survival. Exploratory analyses addressed the impact of lesion-specific responses, tissue sample properties, and combination with other biomarkers on the predictive value of PD-1T TILs.Results:PD-1T TILs as a biomarker reached 77% sensitivity and 67% specificity at 6 months, and 93% and 65% at 12 months, respectively. Particularly, a patient group without clinical benefit was reliably identified, indicated by a high negative predictive value (NPV) (88% at 6 months, 98% at 12 months). High PD-1T TILs related to significantly longer progression-free (HR 0.39, 95% CI, 0.24–0.63, P < 0.0001) and overall survival (HR 0.46, 95% CI, 0.28–0.76, P < 0.01). Predictive performance was increased when lesion-specific responses and samples obtained immediately before treatment were assessed. Notably, the predictive performance of PD-1T TILs was superior to PD-L1 and tertiary lymphoid structures in the same cohort.Conclusions:This study established PD-1T TILs as predictive biomarker for clinical benefit to PD-1 blockade in patients with advanced NSCLC. Most importantly, the high NPV demonstrates an accurate identification of a patient group without benefit.See related commentary by Anagnostou and Luke, p. 4835

Supplementary Figure from PD-1T TILs as a Predictive Biomarker for Clinical Benefit to PD-1 Blockade in Patients with Advanced NSCLC

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 = 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 with progression-free survival (PFS) and overall survival (OS) across two validation cohorts (N = 98 and N = 75). In pooled analysis, significantly better OS was demonstrated for “sensitive” relative to “not sensitive” patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38–0–87; P = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort (n = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades.Conclusions:This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study.

Objectives Exhaled breath analysis by electronic nose (eNose) has shown to be a potential predictive biomarker before start of anti-PD-1 therapy in patients with non-small cell lung carcinoma (NSCLC). We hypothesized that the eNose could also be used as an early monitoring tool to identify responders more accurately at early stage of treatment when compared to baseline. In this proof-of-concept study we aimed to definitely discriminate responders from non-responders after six weeks of treatment. Materials and Methods This was a prospective observational study in patients with advanced NSCLC eligible for anti-PD-1 treatment. The efficacy of treatment was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 at 3-month follow-up. We analyzed SpiroNose exhaled breath data of 94 patients (training cohort n = 62, validation cohort n = 32). Data analysis involved signal processing and statistics based on Independent Samples T-tests and Linear Discriminant Analysis (LDA) followed by Receiver Operating Characteristic (ROC) analysis. Results In the training cohort, a specificity of 73% was obtained at a 100% sensitivity level to identify objective responders. The Area Under the Curve (AUC) was 0.95 (CI: 0.89–1.00). In the validation cohort, these results were confirmed with an AUC of 0.97 (CI: 0.91–1.00). Conclusion Exhaled breath analysis by eNose early during treatment allows for a highly accurate, non-invasive and low-cost identification of advanced NSCLC patients who benefit from anti-PD-1 therapy.

Purpose: Durable clinical benefit to PD-1 blockade in non–small cell lung cancer (NSCLC) is currently limited to a small fraction of patients, underlining the need for predictive biomarkers. We recently identified a tumor-reactive tumor-infiltrating T lymphocyte (TIL) pool, termed PD-1T TILs, with predictive potential in NSCLC. Here, we examined PD-1T TILs as biomarker in NSCLC. Experimental Design: PD-1T TILs were digitally quantified in 120 baseline samples from advanced NSCLC patients treated with PD-1 blockade. Primary outcome was disease control (DC) at 6 months. Secondary outcomes were DC at 12 months and survival. Exploratory analyses addressed the impact of lesion-specific responses, tissue sample properties, and combination with other biomarkers on the predictive value of PD-1T TILs. Results: PD-1T TILs as a biomarker reached 77% sensitivity and 67% specificity at 6 months, and 93% and 65% at 12 months, respectively. Particularly, a patient group without clinical benefit was reliably identified, indicated by a high negative predictive value (NPV) (88% at 6 months, 98% at 12 months). High PD-1T TILs related to significantly longer progression-free (HR 0.39, 95% CI, 0.24–0.63, P < 0.0001) and overall survival (HR 0.46, 95% CI, 0.28–0.76, P < 0.01). Predictive performance was increased when lesion-specific responses and samples obtained immediately before treatment were assessed. Notably, the predictive performance of PD-1T TILs was superior to PD-L1 and tertiary lymphoid structures in the same cohort. Conclusions: This study established PD-1T TILs as predictive biomarker for clinical benefit to PD-1 blockade in patients with advanced NSCLC. Most importantly, the high NPV demonstrates an accurate identification of a patient group without benefit. See related commentary by Anagnostou and Luke, p. 4835

Contains fulltext : 242612.pdf (Publisher’s version ) (Closed access) PURPOSE: We studied EGFR mutations in circulating tumor DNA (ctDNA) and explored their role in predicting the progression-free survival (PFS) of non-small cell lung cancer (NSCLC) patients treated with erlotinib or gefitinib. METHODS: The L858R, T790M mutations and exon 19 deletions were quantified in plasma using digital droplet polymerase chain reaction (ddPCR). The dynamics of ctDNA mutations over time and relationships with PFS were explored. RESULTS: In total, 249 plasma samples (1-13 per patient) were available from 68 NSCLC patients. The T790M and L858R or exon 19 deletion were found in the ctDNA of 49 and 56% patients, respectively. The median (range) concentration in these samples were 7.3 (5.1-3688.7), 11.7 (5.1-12,393.3) and 27.9 (5.9-2896.7) copies/mL, respectively. Using local polynomial regression, the number of copies of EGFR mutations per mL increased several months prior to progression on standard response evaluation. CONCLUSION: This change was more pronounced for the driver mutations than for the resistance mutations. In conclusion, quantification of EGFR mutations in plasma ctDNA was predictive of treatment outcomes in NSCLC patients. In particular, an increase in driver mutation copy number could predict disease progression.

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 = 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 with progression-free survival (PFS) and overall survival (OS) across two validation cohorts (N = 98 and N = 75). In pooled analysis, significantly better OS was demonstrated for “sensitive” relative to “not sensitive” patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38–0–87; P = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort (n = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades. Conclusions: This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study.

Background The major complication of COVID-19 is hypoxaemic respiratory failure from capillary leak and alveolar oedema. Experimental and early clinical data suggest that the tyrosine-kinase inhibitor imatinib reverses pulmonary capillary leak. Methods This randomised, double-blind, placebo-controlled, clinical trial was done at 13 academic and non-academic teaching hospitals in the Netherlands. Hospitalised patients (aged ≥18 years) with COVID-19, as confirmed by an RT-PCR test for SARS-CoV-2, requiring supplemental oxygen to maintain a peripheral oxygen saturation of greater than 94% were eligible. Patients were excluded if they had severe pre-existing pulmonary disease, had pre-existing heart failure, had undergone active treatment of a haematological or non-haematological malignancy in the previous 12 months, had cytopenia, or were receiving concomitant treatment with medication known to strongly interact with imatinib. Patients were randomly assigned (1:1) to receive either oral imatinib, given as a loading dose of 800 mg on day 0 followed by 400 mg daily on days 1–9, or placebo. Randomisation was done with a computer-based clinical data management platform with variable block sizes (containing two, four, or six patients), stratified by study site. The primary outcome was time to discontinuation of mechanical ventilation and supplemental oxygen for more than 48 consecutive hours, while being alive during a 28-day period. Secondary outcomes included safety, mortality at 28 days, and the need for invasive mechanical ventilation. All efficacy and safety analyses were done in all randomised patients who had received at least one dose of study medication (modified intention-to-treat population). This study is registered with the EU Clinical Trials Register (EudraCT 2020–001236–10). Findings Between March 31, 2020, and Jan 4, 2021, 805 patients were screened, of whom 400 were eligible and randomly assigned to the imatinib group (n=204) or the placebo group (n=196). A total of 385 (96%) patients (median age 64 years [IQR 56–73]) received at least one dose of study medication and were included in the modified intention-to-treat population. Time to discontinuation of ventilation and supplemental oxygen for more than 48 h was not significantly different between the two groups (unadjusted hazard ratio [HR] 0·95 [95% CI 0·76–1·20]). At day 28, 15 (8%) of 197 patients had died in the imatinib group compared with 27 (14%) of 188 patients in the placebo group (unadjusted HR 0·51 [0·27–0·95]). After adjusting for baseline imbalances between the two groups (sex, obesity, diabetes, and cardiovascular disease) the HR for mortality was 0·52 (95% CI 0·26–1·05). The HR for mechanical ventilation in the imatinib group compared with the placebo group was 1·07 (0·63–1·80; p=0·81). The median duration of invasive mechanical ventilation was 7 days (IQR 3–13) in the imatinib group compared with 12 days (6–20) in the placebo group (p=0·0080). 91 (46%) of 197 patients in the imatinib group and 82 (44%) of 188 patients in the placebo group had at least one grade 3 or higher adverse event. The safety evaluation revealed no imatinib-associated adverse events. Interpretation The study failed to meet its primary outcome, as imatinib did not reduce the time to discontinuation of ventilation and supplemental oxygen for more than 48 consecutive hours in patients with COVID-19 requiring supplemental oxygen. The observed effects on survival (although attenuated after adjustment for baseline imbalances) and duration of mechanical ventilation suggest that imatinib might confer clinical benefit in hospitalised patients with COVID-19, but further studies are required to validate these findings.&nbsp

Objectives Molecular profiling of tumours has become the mainstay of diagnostics for metastasised solid malignancies and guides personalised treatment, especially in nonsmall cell lung cancer (NSCLC). In current practice, it is often challenging to obtain sufficient tumour material for reliable molecular analysis. Cell-free DNA (cfDNA) in blood or other bio-sources could present an alternative approach to obtain genetic information from the tumour. In a retrospective cohort we analysed the added value of cfDNA analysis in pleural effusions for molecular profiling. Methods We retrospectively analysed both the supernatant and the cell pellet of 44 pleural effusions sampled from 39 stage IV patients with KRAS (n=23) or EGFR (n=16) mutated tumours to detect the original driver mutation as well as for EGFR T790M resistance mutations. Patients were diagnosed with either NSCLC (n=32), colon carcinoma (n=4), appendiceal carcinoma (n=2) or adenocarcinoma of unknown primary (n=1). Samples collected in the context of routine clinical care were stored at the Netherlands Cancer Institute biobank. We used droplet digital PCR for analysis. Results The driver mutation could be detected in 36 of the 44 pleural effusions by analysis of both the supernatant (35 out of 44 positive) and the cell pellet (31 out of 44 positive). In seven out of 20 pleural effusions from patients with EGFR mutation-positive tumours, a T790M mutation was detected. All seven supernatants and cell pellets were positive. Conclusions cfDNA in pleural effusion can be used to detect driver mutations as well as resistance mechanisms like EGFR T790M in pleural effusion with high accuracy and is therefore a valuable bio-source., Cell-free DNA in the supernatant of pleural effusion is a valuable bio-source and can be used to detect driver mutations as well as resistance mechanisms like EGFR T790M in pleural effusion http://ow.ly/Z16830nxxti

Contains fulltext : 215691.pdf (Publisher’s version ) (Closed access) BACKGROUND: Immune checkpoint inhibitors have improved survival outcome of advanced non-small-cell lung cancer (NSCLC). However, most patients do not benefit. Therefore, biomarkers are needed that accurately predict response. We hypothesized that molecular profiling of exhaled air may capture the inflammatory milieu related to the individual responsiveness to anti-programmed death ligand 1 (PD-1) therapy. This study aimed to determine the accuracy of exhaled breath analysis at baseline for assessing nonresponders versus responders to anti-PD-1 therapy in NSCLC patients. METHODS: This was a prospective observational study in patients receiving checkpoint inhibitor therapy using both a training and validation set of NSCLC patients. At baseline, breath profiles were collected in duplicate by a metal oxide semiconductor electronic nose (eNose) positioned at the rear end of a pneumotachograph. Patients received nivolumab or pembrolizumab of which the efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 at 3-month follow-up. Data analysis involved advanced signal-processing and statistics based on independent t-tests followed by linear discriminant and receiver operating characteristic (ROC) analysis. RESULTS: Exhaled breath data of 143 NSCLC patients (training: 92, validation: 51) were available at baseline. ENose sensors contributed significantly (P < 0.05) at baseline in differentiating between patients with different responses at 3 months of anti-PD-1 treatment. The eNose sensors were combined into a single biomarker with an ROC-area under the curve (AUC) of 0.89 [confidence interval (CI) 0.82-0.96]. This AUC was confirmed in the validation set: 0.85 (CI 0.75-0.96). CONCLUSION: ENose assessment was effective in the noninvasive prediction of individual patient responses to immunotherapy. The predictive accuracy and efficacy of the eNose for discrimination of immunotherapy responder types were replicated in an independent validation set op patients. This finding can potentially avoid application of ineffective treatment in identified probable nonresponders.

Contains fulltext : 242641.pdf (Publisher’s version ) (Open Access) 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.

Background For advanced non-small cell lung cancer anti-PD-1 treatment has become standard care in first and second line treatment in recent years. Because many of the clinical trials with anti-PD-1 drugs have only recently been completed, long term follow up data of patients treated with these agents is scarce, even more so of patients treated in real life clinical care. We present long term follow up of patients treated with nivolumab. Methods Two hundred forty-eight patients with pre-treated, advanced NSCLC who received nivolumab between August 2015 and December 2018 were included in this retrospective cohort study. Overall survival and progression free survival rates were calculated for the total cohort and for subgroups defined by clinical characteristics, responses to treatment, and other parameters. Data on further lines of treatment and characteristics of long term survivors were also collected. Results Median overall survival in the total cohort was 8.1 months, median progression free survival was 2.8 months. Overall survival after two and three years was 23.8% and 17.1%, respectively. Good ECOG performance scores, absence of liver metastases, experiencing treatment-related toxicity, and response to nivolumab were significantly associated with longer overall survival and progression free survival. Three-year survival rate among patients with an objective response was 55.3%. Survival for more than two years without subsequent therapy after nivolumab was observed in 13.3% of patients. Conclusions The results from our study confirm that long term survival rates of patients treated with nivolumab for advanced NSCLC in a real world clinical setting are comparable to survival rates shown in clinical trials.

Non-small-cell lung cancer (NSCLC) is often diagnosed at an advanced stage of disease, where it is no longer amenable to curative treatment. During the last decades, the survival has only improved significantly for lung cancer patients who have tumors harboring a driver mutation. Therefore, there is a clear unmet need for effective therapies for patients with no mutation. Immunotherapy has emerged as an effective treatment for different cancer types. Nivolumab, a monoclonal inhibitory antibody against PD-1 receptor, can prolong survival of NSCLC patients, with a manageable toxicity profile. In two Phase III trials, nivolumab was compared to docetaxel in patients with, respectively, squamous (CheckMate 017) and non-squamous NSCLC (CheckMate 057). In both trials, nivolumab significantly reduced the risk of death compared to docetaxel (41% and 27% lower risk of death for squamous and non-squamous NSCLC, respectively). Therefore, nivolumab has been approved in the US and in Europe as second-line treatment for advanced NSCLC. Unfortunately, accurate predictive factors for patient selection are lacking, making it difficult to decide who will benefit and who will not. Currently, there are many ongoing trials that evaluate the efficacy of nivolumab in different settings and in combination with other agents. This paper reviews the present literature about the role of nivolumab in the treatment of NSCLC. Particular attention has been given to efficacy studies, toxicity profile, and current and emerging predictive factors.

Introduction: Molecular profiling of tumors has become the mainstay of diagnostics for metastasized solid malignancies and guides personalized treatment, especially in non-small cell lung cancer (NSCLC). In current practice it is often challenging to obtain sufficient tumor material for reliable molecular analysis. Cell free (cf) DNA in blood or other bio-sources could present an alternative approach to obtain genetic information from the tumor. In a retrospective cohort we analyzed the added value of cfDNA analysis in pleural effusions for molecular profiling. Methods: We retrospectively analyzed both the supernatant and the cell pellet of 44 pleural effusions sampled from 39 patients with KRAS (23) or EGFR (16) positive tumors for the original driver gene mutation as well as for EGFR T790M resistance mutations. Patients were diagnosed with either NSCLC (32), colon carcinoma (4), appendiceal carcinoma (2) or adenocarcinoma of unknown primary (1). Samples collected in the context of routine clinical care were stored in the NKI-AVL biobank. We used Bio-Rad QX200 droplet digital PCR for analysis. Results: The original driver gene mutation could be detected in 37 of the 44 pleural effusions by analysis of both supernatant (35/44 positive) and cell pellet (29/44 positive). In 7 out of 20 pleural effusions from patients with EGFR mutation positive tumors, a T790M mutation was detected. All 7 supernatants were positive as were 5 of the 7 cell pellets. The EGFR T790M mutation was confirmed in all supernatants (4/4) and in 3 of the 4 cell pellets sampled from patients with T790M positive tumors (4). Conclusions: Cell free DNA in pleural effusion proved to be a valuable bio-source and can be used to detect driver gene mutations as well as resistance mechanisms like EGFR T790M in pleural effusion. Citation Format: Karlijn Hummelink, Mirte Muller, Dorothe Linders, Vincent van der Noort, Petra Nederlof, Sjaak Burgers, Gerrit Meijer, Michel van den Heuvel, Daan van den Broek, Kim Monkhorst. Cell free DNA in the supernatant of pleural effusion can detect driver and resistance mutations and can guide TKI treatment decisions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 641.

Chemotherapy-induced peripheral neuropathy (CIPN) is a common phenomenon, often resulting in serious limitations in daily functioning and compromised quality of life. Currently available toxicity grading systems typically use a combination of clinical and paraclinical parameters and relies on the judgment of clinicians and/or nurses. However, because many of the symptoms of CIPN are subjective in nature, it is only logical that an assessment of CIPN be based, at least in part, on patient self-report data. We report on the development of a patient self-report questionnaire, the CIPN20, intended to supplement the core quality of life questionnaire of the European Organization for Research and Treatment of Cancer (EORTC). Following EORTC guidelines, relevant CIPN-related issues were identified from a literature survey and interviews with health professionals (n=15) and patients (n=112). The resulting 20-item questionnaire was pre-tested in three languages and four countries and is currently being examined in a large, international clinical trial. The EORTC CIPN20 should provide valuable information on CIPN-related symptoms and functional limitations of patients exposed to potentially neurotoxic chemotherapeutic and/or neuroprotective agents.

Summary Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92–0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83–0.95; p, Graphical Abstract, Highlights • Tumor-educated platelet (TEP) RNA profiles allow for blood-based cancer diagnostics • Inflammatory conditions only minimally confound TEP-based cancer detection • Swarm intelligence algorithms enable efficient selection of biomarker gene panels • TEP gene panels enable support vector machine-based classification of lung cancer, Best et al. use particle-swarm optimization algorithms and RNA-seq of tumor-educated platelets from patients to generate RNA sets capable of identifying patients with non-small-cell lung cancer, including those having early stage, from individuals without cancer, including those having inflammatory conditions.

I: Studies have shown the activity of anti-PD(L)-1 therapies in patients with advanced non-small-cell lung cancer (NSCLC), however response rates are rather low (~20%). Therefore, there is an urgent need to identify biomarkers that predict patient outcome to immunotherapy (IT). Previously we have shown that RNA signatures of tumor-educated platelets (TEPs) may have predictive value for tumor type-specific diagnostics. Platelets are intimately involved in immune responses. We hypothesized that TEP RNA profiles have predictive value for IT response. M: We collected baseline platelet pellets, isolated from whole blood by differential centrifugation, from 389 stage IV NSCLC patients treated with Nivolumab (table 1). Tumor response was evaluated at 3 and 6 months and reported according to RECIST 1.1. Platelet pellets were subjected to total RNA isolation, SMARTer cDNA amplification, and libraries were sequenced on the HiSeq platform. Raw data (~20 M reads per sample) was mapped to the human genome, intron-spanning spliced RNA reads were selected for analysis. Gene panels were calculated by ANOVA statistics. R: Until now 64 samples were sequenced, 30 of patients with clinical benefit (PR or SD at six months; CB) and 34 of patients with no clinical benefit (PD; no CB). 40 randomly selected samples (20 CB, 20 no CB) were used for training of the support vector machine (SVM)-based therapy response classification algorithm. 24 samples were used for independent evaluation of the classifier. Hierarchical clustering of genes with p Table 1.Patient CharacteristicsTotal CohortNumber of patients389Start of treatmentAugust 2015-november 2016Date lock1th of November, 2016Gender (Male)56%Age (med, range)64.5 years (29-83)Treatment lines1st line1%2nd line72%>2nd line27%DiagnosisNon-Squamous68%Squamous26%Other6%ResponseClinical benefit27%Progressive54%Unknown19%PD-L1 expressionResults expected in april Citation Format: Mirte Muller, Myron Best, Nik Sol, Anna-Larissa N. Niemeijer, Adrienne Vancura, Robert D. Schouten, Jeroen J.N. Hiltermann, Sjors G.J.G. In 't Veld, Daan van den Broek, Vincent van der Noort, Adrianus J. de Langen, Ed M.D. Schuuring, Thomas Wurdinger, Michel M. van den Heuvel. RNA-sequencing of tumor-educated platelets enables nivolumab immunotherapy response prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-248. doi:10.1158/1538-7445.AM2017-LB-248

Summary Background Reliable reporting of chemotherapy-induced neurotoxicity is important. The objectives of the current study were to evaluate the differences in the peripheral neurotoxicity sections of several widely used chemotherapy-related toxicity grading systems, and the differences in the way in which observers interpret these scales. Patients and methods Two neurologists independently rated the severity of chemotherapy-induced peripheral neuropathy, according to WHO, ECOG, Ajani, and NCIC-CTC criteria in 37 patients. Results The highest percentage grade 1, grade 2 and grade 3 peripheral neurotoxicity was noted when employing the WHO, Ajani and NCIC-CTC scales, respectively. Percentage interobserver agreement across all grades of severity ranged from 45.9 (NCIC-CTC) to 83.8 (WHO). The degree of agreement varied from ‘poor to fair’ to ‘substantial’. Percentage interobserver agreement for the dichotomy grade ≤ 2 and grade 3 ranged from 81.1 (NCIC-CTC) to 94.6 (Ajani and WHO), however, exact agreement on grade 3 peripheral neurotoxicity ranged from 0 (Ajani and WHO) to 42% (NCIC-CTC). Percentage interscale agreement for the dichotomy grade ≤ 2 and grade 3 varied from 67.6 (WHO and NCIC-CTC) to 100 (WHO and ECOG). Interobserver disagreement of severity grading was partly due to different interpretation of scale parameters. Conclusions Our results suggest that caution should be used in interpreting results across studies using different scales for neurotoxicity grading in chemotherapy-related peripheral neuropathy. When (multicentre) trials are to be undertaken with potential neurotoxic or neuroprotective agents, consensus should be sought regarding the toxicity rating scale used, and its interpretation by participating physicians.