A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study.

BACKGROUND: Because responses of patients with cancer to immunotherapy can vary in success, innovative predictors of response to treatment are urgently needed to improve treatment outcomes. We aimed to develop and independently validate a radiomics-based biomarker of tumour-infiltrating CD8 cells in patients included in phase 1 trials of anti-programmed cell death protein (PD)-1 or anti-programmed cell death ligand 1 (PD-L1) monotherapy. We also aimed to evaluate the association between the biomarker, and tumour immune phenotype and clinical outcomes of these patients. METHODS: In this retrospective multicohort study, we used four independent cohorts of patients with advanced solid tumours to develop and validate a radiomic signature predictive of immunotherapy response by combining contrast-enhanced CT images and RNA-seq genomic data from tumour biopsies to assess CD8 cell tumour infiltration. To develop the radiomic signature of CD8 cells, we used the CT images and RNA sequencing data of 135 patients with advanced solid malignant tumours who had been enrolled into the MOSCATO trial between May 1, 2012, and March 31, 2016, in France (training set). The genomic data, which are based on the CD8B gene, were used to estimate the abundance of CD8 cells in the samples and data were then aligned with the images to generate the radiomic signatures. The concordance of the radiomic signature (primary endpoint) was validated in a Cancer Genome Atlas [TGCA] database dataset including 119 patients who had available baseline preoperative imaging data and corresponding transcriptomic data on June 30, 2017. From 84 input variables used for the machine-learning method (78 radiomic features, five location variables, and one technical variable), a radiomics-based predictor of the CD8 cell expression signature was built by use of machine learning (elastic-net regularised regression method). Two other independent cohorts of patients with advanced solid tumours were used to evaluate this predictor. The immune phenotype internal cohort (n=100), were randomly selected from the Gustave Roussy Cancer Campus database of patient medical records based on previously described, extreme tumour-immune phenotypes: immune-inflamed (with dense CD8 cell infiltration) or immune-desert (with low CD8 cell infiltration), irrespective of treatment delivered; these data were used to analyse the correlation of the immune phenotype with this biomarker. Finally, the immunotherapy-treated dataset (n=137) of patients recruited from Dec 1, 2011, to Jan 31, 2014, at the Gustave Roussy Cancer Campus, who had been treated with anti-PD-1 and anti-PD-L1 monotherapy in phase 1 trials, was used to assess the predictive value of this biomarker in terms of clinical outcome. FINDINGS: We developed a radiomic signature for CD8 cells that included eight variables, which was validated with the gene expression signature of CD8 cells in the TCGA dataset (area under the curve [AUC]=0·67; 95% CI 0·57-0·77; p=0·0019). In the cohort with assumed immune phenotypes, the signature was also able to discriminate inflamed tumours from immune-desert tumours (0·76; 0·66-0·86; p<0·0001). In patients treated with anti-PD-1 and PD-L1, a high baseline radiomic score (relative to the median) was associated with a higher proportion of patients who achieved an objective response at 3 months (vs those with progressive disease or stable disease; p=0·049) and a higher proportion of patients who had an objective response (vs those with progressive disease or stable disease; p=0·025) or stable disease (vs those with progressive disease; p=0·013) at 6 months. A high baseline radiomic score was also associated with improved overall survival in univariate (median overall survival 24·3 months in the high radiomic score group, 95% CI 18·63-42·1; vs 11·5 months in the low radiomic score group, 7·98-15·6; hazard ratio 0·58, 95% CI 0·39-0·87; p=0·0081) and multivariate analyses (0·52, 0·35-0·79; p=0·0022). INTERPRETATION: The radiomic signature of CD8 cells was validated in three independent cohorts. This imaging predictor provided a promising way to predict the immune phenotype of tumours and to infer clinical outcomes for patients with cancer who had been treated with anti-PD-1 and PD-L1. Our imaging biomarker could be useful in estimating CD8 cell count and predicting clinical outcomes of patients treated with immunotherapy, when validated by further prospective randomised trials. FUNDING: Fondation pour la Recherche Médicale, and SIRIC-SOCRATE 2.0, French Society of Radiation Oncology.

rCGH: a comprehensive array-based genomic profile platform for precision medicine.

UNLABELLED: We present rCGH, a comprehensive array-based comparative genomic hybridization analysis workflow, integrating computational improvements and functionalities specifically designed for precision medicine. rCGH supports the major microarray platforms, ensures a full traceability and facilitates profiles interpretation and decision-making through sharable interactive visualizations. AVAILABILITY AND IMPLEMENTATION: The rCGH R package is available on bioconductor (under Artistic-2.0). The aCGH-viewer is available at https://fredcommo.shinyapps.io/aCGH_viewer, and the application implementation is freely available for installation at https://github.com/fredcommo/aCGH_viewer CONTACT: frederic.commo@gustaveroussy.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Personalized radiation therapy and biomarker-driven treatment strategies: a systematic review.

Radiosensitivity varies to a great extent across tumor types and also between patients bearing the same type of tumor. Radiation oncology pioneered the field of biomarkers with attempts to correlate tumor response to clonogenic survival, tumor potential doubling time (Tpot), and PaO2. Biomarkers predicting the clinical outcome after radiotherapy are already available, but their levels of evidence are heterogeneous. In light of these molecular factors, the issue of personalized radiation therapy in combination or as a standalone modality is addressed. Known molecular prognostic and predictive biomarkers and their present or potential respective therapeutic implications are described for six tumor types where radiotherapy is considered to be part of the mainstay: chemoradiation (e.g., gliomas, head and neck, cervical cancer), radiotherapy with or without androgen deprivation (e.g., prostate), neo-adjuvant chemoradiation (e.g., rectum), or adjuvant radiotherapy (e.g., breast).

Primary Colorectal Tumor Displays Differential Genomic Expression Profiles Associated with Hepatic and Peritoneal Metastases.

BACKGROUND: Despite improvements in characterization of CRC heterogeneity, appropriate risk stratification tools are still lacking in clinical practice. This study aimed to elucidate the primary tumor transcriptomic signatures associated with distinct metastatic routes. METHODS: Primary tumor specimens obtained from CRC patients with either isolated LM (CRC-Liver) or PM (CRC-Peritoneum) were analyzed by transcriptomic mRNA sequencing, gene set enrichment analyses (GSEA) and immunohistochemistry. We further assessed the clinico-pathological associations and prognostic value of our signature in the COAD-TCGA independent cohort. RESULTS: We identified a significantly different distribution of Consensus Molecular Subtypes between CRC-Liver and CRC-peritoneum groups. A transcriptomic signature based on 61 genes discriminated between liver and peritoneal metastatic routes. GSEA showed a higher expression of immune response and epithelial invasion pathways in CRC-Peritoneum samples and activation of proliferation and metabolic pathways in CRC-Liver samples. The biological relevance of RNA-Seq results was validated by the immunohistochemical expression of three significantly differentially expressed genes (ACE2, CLDN18 and DUSP4) in our signature. In silico analysis of the COAD-TCGA showed that the CRC-Peritoneum signature was associated with negative prognostic factors and poor overall and disease-free survivals. CONCLUSIONS: CRC primary tumors spreading to the liver and peritoneum display significantly different transcriptomic profiles. The implementation of this signature in clinical practice could contribute to identify new therapeutic targets for stage IV CRC and to define individualized follow-up programs in stage II-III CRC.

Phase II trials in patients with carcinoma of unknown primary: a pooled data analysis.

BACKGROUND: The management of carcinoma of unknown primary site remains debatable. The literature data consists of about 29 phase-II studies investigating 38 regimens, providing a broad range of response rates (RR). METHODS: We performed a pooled published data analysis to identify the factors influencing RR in these 29 studies. RESULTS: In front-line treatment, the overall RR was 31% (430/1,380). At least nine factors significantly influenced the reported RR, excluding drugs under investigation, such as the impact factor of the journal, single-centre study, some eligibility criteria, central radiological review, sample size calculation based on statistical hypothesis and stratification. Two drugs seem to improve RR: cisplatin and doxorubicin. Two drugs seem to be associated with a worse RR: irinotecan and carboplatin. CONCLUSIONS: This pooled data analysis illustrates that in a phase II trial setting, it is impossible to attribute the variation in RR solely to the modification of drugs under investigation.

Reversible cardiogenic shock following 5-fluorouracil infusion.

5-Fluorouracil remains a major component of chemotherapy regimens for various tumors. We report the case of reversible cardiogenic shock following 5-FU administration and discuss the different pitfalls of such toxicity. Oncologist should be aware of that rare but potentially lethal adverse event.

Individual life expectancy estimation using validated prognostic scores for patients with cancer of unknown primary.

PURPOSE: To implement 3 published prognostic scores in an independent set of patients with cancer of unknown primary (CUP), and compare their performance on individual life expectancy prediction. PATIENTS AND METHOD: The survival of 430 consecutive patients with CUP was measured after they had allocated to their prognostic group (good prognosis vs. poor prognosis) according to each prognostic score. Using a 2 x 2 contingency table, we measured the sensitivity, specificity, positive predictive value (PPV) and accuracy of each score in predicting individual outcome (survival <90 days or >180 days). RESULTS: The median overall survival was 189 days (1-4,801 days). Survival was <90 days in 143/421 cases and >180 days in 208/413 cases. The three PPVs were within the same range for prediction of survival <90 days (from 43 to 49%) as well as for prediction of survival >180 days (from 70 to 80%), and underestimate individual life expectancy of 40-50% of the patients. None of the 3 scores appeared significantly better. CONCLUSION: The main finding of this retrospective analysis is that the published prognostic scores cannot be used for rational decision making.

Evidence of pseudoprogression in patients treated with PD1/PDL1 antibodies across tumor types.

BACKGROUND: PD(L)1 antibodies (anti-PD(L)-1) have been a major breakthrough in several types of cancer. Novel patterns of response and progression have been described with anti-PD(L)-1. We aimed at characterizing pseudoprogression (PSPD) among patients with various solid tumor types treated by anti-PD(L)-1. METHODS: All consecutive patients (pts) enrolled in phase 1 trials with advanced solid tumors and lymphomas treated in phase I clinical trials evaluating monotherapy by anti-PD(L)-1 at Gustave Roussy were analyzed. We aimed to assess prevalence and outcome of PSPD across tumor types. We also intended to describe potential clinical and pathological factors associated with PSPD. RESULTS: A total of 169 patients treated with anti-PD(L)-1 were included in the study. Most frequent tumor types included melanoma (n = 57) and non-small cell lung cancer (n = 19). At first tumor evaluation 77 patients (46%) presented with immune unconfirmed progressive disease. Six patients (8%) experienced PSPD: 2 patients with partial response; 4 patients with stable disease. Increase in target lesions in the first CT-scan was more frequently associated to PSPD (67% vs 33%; P = .04). Patients with a PSPD had a superior survival when compared to patients progressing (median OS: 10.7 months vs 8.7 months; P = .07). CONCLUSIONS: A small subset of PSPD patients may experience response after an initial progression. Assessment of the current strategy for immune-related response evaluations may require further attention.

Safety and clinical activity of intratumoral MEDI9197 alone and in combination with durvalumab and/or palliative radiation therapy in patients with advanced solid tumors.

BACKGROUND: MEDI9197 is an intratumorally administered toll-like receptor 7 and 8 agonist. In mice, MEDI9197 modulated antitumor immune responses, inhibited tumor growth and increased survival. This first-time-in-human, phase 1 study evaluated MEDI9197 with or without the programmed cell death ligand-1 (PD-L1) inhibitor durvalumab and/or palliative radiation therapy (RT) for advanced solid tumors. PATIENTS AND METHODS: Eligible patients had at least one cutaneous, subcutaneous, or deep-seated lesion suitable for intratumoral (IT) injection. Dose escalation used a standard 3+3 design. Patients received IT MEDI9197 0.005-0.055 mg with or without RT (part 1), or IT MEDI9197 0.005 or 0.012 mg plus durvalumab 1500 mg intravenous with or without RT (part 3), in 4-week cycles. Primary endpoints were safety and tolerability. Secondary endpoints included pharmacokinetics, pharmacodynamics, and objective response based on Response Evaluation Criteria for Solid Tumors version 1.1. Exploratory endpoints included tumor and peripheral biomarkers that correlate with biological activity or predict response. RESULTS: From November 2015 to March 2018, part 1 enrolled 35 patients and part 3 enrolled 17 patients; five in part 1 and 2 in part 3 received RT. The maximum tolerated dose of MEDI9197 monotherapy was 0.037 mg, with dose-limiting toxicity (DLT) of cytokine release syndrome in two patients (one grade 3, one grade 4) and 0.012 mg in combination with durvalumab 1500 mg with DLT of MEDI9197-related hemorrhagic shock in one patient (grade 5) following liver metastasis rupture after two cycles of MEDI9197. Across parts 1 and 3, the most frequent MEDI9197-related adverse events (AEs) of any grade were fever (56%), fatigue (31%), and nausea (21%). The most frequent MEDI9197-related grade ≥3 events were decreased lymphocytes (15%), neutrophils (10%), and white cell counts (10%). MEDI9197 increased tumoral CD8+ and PD-L1+ cells, inducing type 1 and 2 interferons and Th1 response. There were no objective clinical responses; 10 patients in part 1 and 3 patients in part 3 had stable disease ≥8 weeks. CONCLUSION: IT MEDI9197 was feasible for subcutaneous/cutaneous lesions but AEs precluded its use in deep-seated lesions. Although no patients responded, MEDI9197 induced systemic and intratumoral immune activation, indicating potential value in combination regimens in other patient populations. TRIAL REGISTRATION NUMBER: NCT02556463.

Comparison of Fast-Progression, Hyperprogressive Disease, and Early Deaths in Advanced Non-Small-Cell Lung Cancer Treated With PD-1/PD-L1 Inhibitors or Chemotherapy.

PURPOSE: Hyperprogressive disease (HPD), fast progression (FP), and early death (ED) have been described in 13.8%, 4.7%, and 5.6% and in 5.1%, 2.8%, and 6.8%, respectively, of patients with non-small-cell lung cancer (NSCLC) treated with single-agent programmed cell death ligand 1 inhibitors (ICI) or chemotherapy, respectively. Whether FP/ED and HPD represent overlapping patterns is unknown. PATIENTS AND METHODS: FP, ED, and HPD were retrospectively assessed in patients with NSCLC treated with single-agent ICI or chemotherapy. Eligibility required 2 computed tomography (CT) scans before and 1 CT scan during treatment. (1) HPD, (2) FP, (3) ED were defined as (1) RECIST version 1.1 progression at first CT scan and tumor growth rate variation per month > 50%, (2) ≥ 50% increase in the sum of the longest diameters of target lesions within 6 weeks from baseline, and (3) death as a result of radiologic progression within 12 weeks from baseline CT scan, respectively. RESULTS: Of 406 ICI-treated NSCLC, 56 patients (13.8%), 9 patients (2.2%), and 36 patients (8.8%) were HPD, FP, and ED, respectively. Eight (14.2%) and 20 (35.7%) of 56 patients with HPD were also FP and ED. ED significantly correlated with baseline Eastern Cooperative Oncology Group performance status ≥ 2 compared with HPD (33% v 13%, P = .02). Overall survival was significantly longer for HPD (3.4 months [95% CI, 2.7 to 4.0 months]) compared with FP (0.7 months [95% CI, 0.6 to 0.8 months]); HR, 0.18 [95% CI, 0.08 to 0.42]; P < .0001) and ED (1.4 months [95% CI, 1.3 to 1.6 months]); HR, 0.19 [95% CI, 0.11 to 0.34]); P < .0001), whereas it did not differ between FP and ED (HR, 1.3 [95% CI, 0.56 to 3.0]; P = .55). Of 59 patients with NSCLC treated with single-agent chemotherapy, the HPD, FP, and ED rates were 5.1%, 1.7%, and 6.7%, respectively. CONCLUSION: FP, ED, and HPD represent distinct progression patterns with limited overlap and different survival outcomes.

Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells.

BACKGROUND: Combining radiotherapy (RT) with immuno-oncology (IO) therapy (IORT) may enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to provide prognosis, predict tumor response in a non-invasive fashion and improve patient selection for IORT. A biologically inspired CD8 T-cells-associated radiomics signature has been developed on previous cohorts. We evaluated here whether this CD8 radiomic signature is associated with lesion response, whether it may help to assess disease spatial heterogeneity for predicting outcomes of patients treated with IORT. We also evaluated differences between irradiated and non-irradiated lesions. METHODS: Clinical data from patients with advanced solid tumors in six independent clinical studies of IORT were investigated. Immunotherapy consisted of 4 different drugs (antiprogrammed death-ligand 1 or anticytotoxic T-lymphocyte-associated protein 4 in monotherapy). Most patients received stereotactic RT to one lesion. Irradiated and non-irradiated lesions were delineated from baseline and the first evaluation CT scans. Radiomic features were extracted from contrast-enhanced CT images and the CD8 radiomics signature was applied. A responding lesion was defined by a decrease in lesion size of at least 30%. Dispersion metrices of the radiomics signature were estimated to evaluate the impact of tumor heterogeneity in patient's response. RESULTS: A total of 94 patients involving multiple lesions (100 irradiated and 189 non-irradiated lesions) were considered for a statistical interpretation. Lesions with high CD8 radiomics score at baseline were associated with significantly higher tumor response (area under the receiving operating characteristic curve (AUC)=0.63, p=0.0020). Entropy of the radiomics scores distribution on all lesions was shown to be associated with progression-free survival (HR=1.67, p=0.040), out-of-field abscopal response (AUC=0.70, p=0.014) and overall survival (HR=2.08, p=0.023), which remained significant in a multivariate analysis including clinical and biological variables. CONCLUSIONS: These results enhance the predictive value of the biologically inspired CD8 radiomics score and suggests that tumor heterogeneity should be systematically considered in patients treated with IORT. This CD8 radiomics signature may help select patients who are most likely to benefit from IORT.

"Classical 3 + 3 design" versus "accelerated titration designs": analysis of 270 phase 1 trials investigating anti-cancer agents.

The number of patients treated at each dose-level in dose seeking phase I trials is arbitrarily established. The most frequently used design is the "classical 3 + 3 design (3 + 3D)". Recently, Simon et al. had introduced several "accelerated titration designs (ATD)". In the present analysis, we compared the performance of these two types of designs in 270 recently (1997-2008) published phase I trials. ATD had been used in only 10% of the recent studies. ATD had permitted to explore significantly more dose levels (seven versus five, p = 0.0001) and reduced the rate of patients treated at doses below phase-2 recommended dose (46% versus 56%, p = 0.0001). Nevertheless, ATD did not allow a reduction in the number of enrolled patients, shorten the accrual time nor increase the efficacy of phase I trials. These data support that ATD as an effective clinical trial design over a standard 3 + 3 dose escalation design.

Wound healing delay after central venous access following DCF/VEGF-trap therapy.

Hypertension, proteinuria, thromboembolic or bleeding events are well-recognized complications occurring while targeting VEGF pathway. Wound healing dysfunctions have also been described in patients undergoing major surgery. For the first time, we report wound healing delay after central venous access following DCF-VEGF-Trap. VEGF-Trap may affect both angiogenesis and reepithelialization which are necessary to the normal repair process.

The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features.

Radiomics extracts high-throughput quantitative data from medical images to contribute to precision medicine. Radiomic shape features have been shown to correlate with patient outcomes. However, how radiomic shape features vary in function of tumor complexity and tumor volume, as well as with method used for meshing and voxel resampling, remains unknown. The aims of this study are to create tumor models with varying degrees of complexity, or spiculatedness, and evaluate their relationship with quantitatively extracted shape features. Twenty-eight tumor models were mathematically created using spherical harmonics with the spiculatedness degree d being increased by increments of 3 (d = 11 to d = 92). Models were 3D printed with identical bases of 5 cm, imaged with a CT scanner with two different slice thicknesses, and semi-automatically delineated. Resampling of the resulting masks on a 1 × 1 × 1 mm3 grid was performed, and the voxel size of each model was then calculated to eliminate volume differences. Four MATLAB-based algorithms (isosurface (M1), isosurface filter (M2), isosurface remeshing (M3), and boundary (M4)) were used to extract nine 3D features (Volume, Surface area, Surface-to-volume, Compactness1, Compactness2, Compactness3, Spherical Disproportion, Sphericity and Fractional Concavity). To quantify the impact of 3D printing, acquisition, segmentation and meshing, features were computed directly from the stereolithography (STL) file format that was used for 3D printing, and compared to those computed. Changes in feature values between 0.6 and 2 mm slice acquisitions were also compared. Spearman's rank-order correlation coefficients were computed to determine the relationship of each shape feature with spiculatedness for each of the four meshing algorithms. Percent changes were calculated between shape features extracted from the original and resampled contoured images to evaluate the influence of spatial resampling. Finally, the percent change in shape features when the volume was changed from 25% to 150% of their original volume was quantified for three distinct tumor models and compared to the percent change observed when modifying the spiculatedness of the model from d = 11 to d = 92. Values extracted using isosurface remeshing method are the closest to the STL reference ones, with mean differences less than 10.8% (Compactness2) for all features. Seven of the eight features had strong significant correlations with tumor model complexity irrespective of the meshing algorithm (r > 0.98, p < 10-4), with fractional concavity having the lowest correlation coefficient (r = 0.83, p < 10-4, M2). Comparisons of features extracted from the 0.6 and 2 mm slice thicknesses showed that mean differences were from 2.1% (Compactness3) to 12.7% (Compactness2) for the isosurface remeshing method. Resampling on a 1 × 1 × 1 mm3 grid resulted in between 1.3% (Compactness3) to 9.5% (Fractional Concavity) mean changes in feature values. Compactness2, Compactness3, Spherical Disproportion, Sphericity and Fractional Concavity were the features least affected by volume changes. Compactness1 had a 90.4% change with volume, which was greater than the change between the least and most spiculated models. This is the first methodological study that directly demonstrates the relationship of tumor spiculatedness with radiomic shape features, that also produced 3D tumor models, which may serve as reference phantoms for future radiomic studies. Surface Area, Surface-to-volume, and Spherical Disproportion had direct relationships with spiculatedness while the three formulas for Compactness, Sphericity and Fractional Concavity had inverse relationships. The features Compactness2, Compactness3, Spherical Disproportion, and Sphericity should be prioritized as these have minimal variations with volume changes, slice thickness and resampling.

Correction to: 33rd Annual Meeting & Pre-Conference Programs of the Society for Immunotherapy of Cancer (SITC 2018).

After publication of this supplement [1, 2], it was brought to our attention that due to an error authors were missing in the following abstracts. This has now been included in this correction.

Hyperprogressive disease: recognizing a novel pattern to improve patient management.

Anti-PD-1/PD-L1 monoclonal antibodies have substantially improved the overall survival of a subset of patients across multiple solid tumour types, but other patients can have a deterioration of their disease as a result of such therapies. This paradoxical phenomenon is defined as hyperprogression. In this Review, we present the available evidence of hyperprogressive disease following immune-checkpoint inhibition, the pathophysiological hypotheses that might explain hyperprogressive disease and the current challenges for patient management in routine clinical settings. Finally, we also discuss how the risk of hyperprogressive disease should be taken into account in clinical decisions involving immune-checkpoint inhibition.

A Model of Overall Survival Predicts Treatment Outcomes with Atezolizumab versus Chemotherapy in Non-Small Cell Lung Cancer Based on Early Tumor Kinetics.

Purpose: Standard endpoints often poorly predict overall survival (OS) with immunotherapies. We investigated the predictive performance of model-based tumor growth inhibition (TGI) metrics using data from atezolizumab clinical trials in patients with non-small cell lung cancer.Patients and Methods: OS benefit with atezolizumab versus docetaxel was observed in both POPLAR (phase II) and OAK (phase III), although progression-free survival was similar between arms. A multivariate model linking baseline patient characteristics and on-treatment tumor growth rate constant (KG), estimated using time profiles of sum of longest diameters (RECIST 1.1) to OS, was developed using POPLAR data. The model was evaluated to predict OAK outcome based on estimated KG at TGI data cutoffs ranging from 10 to 122 weeks.Results: In POPLAR, TGI profiles in both arms crossed at 25 weeks, with more shrinkage with docetaxel and slower KG with atezolizumab. A log-normal OS model, with albumin and number of metastatic sites as independent prognostic factors and estimated KG, predicted OS HR in subpopulations of patients with varying baseline PD-L1 expression in both POPLAR and OAK: model-predicted OAK HR (95% prediction interval), 0.73 (0.63-0.85), versus 0.73 observed. The POPLAR OS model predicted greater than 97% chance of success of OAK (significant OS HR, P < 0.05) from the 40-week data cutoff onward with 50% of the total number of tumor assessments when a successful study was predicted from 70 weeks onward based on observed OS.Conclusions: KG has potential as a model-based early endpoint to inform decisions in cancer immunotherapy studies. Clin Cancer Res; 24(14); 3292-8. ©2018 AACR.

Does smoking alter the mutation profile of human papillomavirus-driven head and neck cancers?

BACKGROUND: Human papillomavirus (HPV)-driven oropharyngeal cancer (OPC) patients are characterised by a better prognosis than their HPV-negative counterparts. However, this significant survival advantage is not homogeneous and among HPV-positive patients those with a smoking history have a significantly increased risk of oncologic failure. The reason why tobacco consumption impacts negatively the prognosis is still elusive. Tobacco might induce additional genetic alterations leading to a more aggressive phenotype. The purpose of this study was to characterise the mutational profile of HPV-positive OPCs by smoking status. We hypothesise a higher frequency of mutations affecting smokers. METHODS: Targeted next-generation sequencing of 39 genes that are recurrently mutated in head and neck cancers (HNCs) caused by tobacco/alcohol consumption was performed in 62 HPV-driven OPC cases including smokers and non-smokers. RESULTS: The study population included 37 (60%) non-smokers and 25 (40%) smokers. Twenty (32%) patients had no mutation, 14 (23%) had 1 mutation and 28 (45%) had 2 or more mutations. The most commonly mutated genes regardless of tobacco consumption were PIK3CA (19%), MLL2 (19%), TP53 (8%), FAT 1 (15%), FBXW7 (16%), NOTCH1 (10%) and FGFR3 (10%). Mutation rate was not significantly different in smokers compared with non-smokers even when analyses focused on heavy smokers (>20 pack-years vs. <20 pack-years). Similarly, there was no significant difference in mutations patterns according to tobacco consumption. CONCLUSION: In HPV-positive patients, smoking does not increase the mutation rate of genes that are recurrently mutated in traditional HNC. Additional studies are warranted to further describe the molecular landscape of HPV-driven OPC according to tobacco consumption.

High incidence of cetuximab-related infusion reactions in head and neck patients.

BACKGROUND: Cetuximab is crucial in the management of squamous cell carcinoma of the head and neck of patients. Grade 3-4 cetuximab-induced infusion reactions (CI-IRs) occur in 2% of patients with colorectal cancer. Despite the 2.7% CI-IR rate in the EXTREME trial, higher rates were reported in small series of patients with head and neck squamous cell carcinoma (HNSCC) (6%-18%). There is an urgent need to better appraise the natural history and the predictive factors for CI-IRs in patients with HNSCC exposed to cetuximab. METHODS: The medical records from patients with HNSCC (n=428) treated by cetuximab at Gustave Roussy from January 2013 to December 2015 were reviewed. The impact of potential risk factors was analysed. RESULTS: Out of 428 patients, 24 patients (5.4%) presented CI-IR, including grade 3-4 (95.7%); about 21% (5/24) requiring intensive care unit referral and quasi all occurred within the first cycle (21/24). In a multivariate analysis, the occurrence of grade 3-4 CI-IR was associated with tobacco and alcohol history (p=8.5e-3) and with prior allergy history (p=2.9e-3). CI-IRs tended to be associated with poor overall survival in patients with recurrent and metastatic HNSCC and with a higher number of further lines of chemotherapy. CONCLUSION: In real life, CI-IRs appear far more common in patients with HNSCC (5.4%) than reported in prospective trials. This is the largest series of patients ever focusing on the risk of CI-IR in patients with HNSCC. Prior allergy history and tobacco history are associated with CI-IR and could be used to better allocate treatment. Further prospective data are required to confirm these findings.

Hyperprogressive Disease in Patients With Advanced Non-Small Cell Lung Cancer Treated With PD-1/PD-L1 Inhibitors or With Single-Agent Chemotherapy.

Importance: Hyperprogressive disease (HPD) is a new pattern of progression recently described in patients with cancer treated with programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors. The rate and outcome of HPD in advanced non-small cell lung cancer (NSCLC) are unknown. Objectives: To investigate whether HPD is observed in patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors compared with single-agent chemotherapy and whether there is an association between treatment and HPD. Design, Setting, and Participants: In this multicenter retrospective study that included patients treated between August 4, 2011, and April 5, 2017, the setting was pretreated patients with advanced NSCLC who received PD-1/PD-L1 inhibitors (8 institutions) or single-agent chemotherapy (4 institutions) in France. Measurable disease defined by Response Evaluation Criteria in Solid Tumors (RECIST version 1.1) on at least 2 computed tomographic scans before treatment and 1 computed tomographic scan during treatment was required. Interventions: The tumor growth rate (TGR) before and during treatment and variation per month (ΔTGR) were calculated. Hyperprogressive disease was defined as disease progression at the first evaluation with ΔTGR exceeding 50%. Main Outcomes and Measures: The primary end point was assessment of the HPD rate in patients treated with IO or chemotherapy. Results: Among 406 eligible patients treated with PD-1/PD-L1 inhibitors (63.8% male), 46.3% (n = 188) were 65 years or older, 72.4% (n = 294) had nonsquamous histology, and 92.9% (n = 377) received a PD-1 inhibitor as monotherapy in second-line therapy or later. The median follow-up was 12.1 months (95% CI, 10.1-13.8 months), and the median overall survival (OS) was 13.4 months (95% CI, 10.2-17.0 months). Fifty-six patients (13.8%) were classified as having HPD. Pseudoprogression was observed in 4.7% (n = 19) of the population. Hyperprogressive disease was significantly associated with more than 2 metastatic sites before PD-1/PD-L1 inhibitors compared with non-HPD (62.5% [35 of 56] vs 42.6% [149 of 350]; P = .006). Patients experiencing HPD within the first 6 weeks of PD-1/PD-L1 inhibitor treatment had significantly lower OS compared with patients with progressive disease (median OS, 3.4 months [95% CI, 2.8-7.5 months] vs 6.2 months [95% CI, 5.3-7.9 months]; hazard ratio, 2.18 [95% CI, 1.29-3.69]; P = .003). Among 59 eligible patients treated with chemotherapy, 3 (5.1%) were classified as having HPD. Conclusions and Relevance: Our study suggests that HPD is more common with PD-1/PD-L1 inhibitors compared with chemotherapy in pretreated patients with NSCLC and is also associated with high metastatic burden and poor prognosis in patients treated with PD-1/PD-L1 inhibitors. Additional studies are needed to determine the molecular mechanisms involved in HPD.