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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Precision medicine for patients with advanced biliary tract cancers: An effective strategy within the prospective MOSCATO-01 trial.

BACKGROUND: Recommended treatments of patients with advanced biliary tract cancer (aBTC) are limited to one chemotherapy doublet. Nevertheless, efficacy of treatment personalisation for aBTCs is supported by accumulating evidences but remains to be evaluated. PATIENTS AND METHODS: Patients with aBTCs included in the prospective clinical trial MOSCATO-01 were treated by at least one previous systemic treatment, had an ECOG performance status of 0-1, and at least one tumour site accessible to biopsy. Multiple high-throughput molecular analysis was performed on biopsies to drive the administration of molecular targeted agents (MTAs). RESULTS: From November 2011 to March 2016, 43 patients (4%) of the 1035 adult patients included in MOSCATO-01 had aBTCs with a majority of intrahepatic localisation (67%). Successful biopsy procedures and DNA extractions led to molecular portraits for 34 patients (79%). Orientation to an appropriate early clinical trial or accessible MTA(s) was possible for 23 of these patients (68%), and 18 (53%) have received matched MTA(s). Among them, the overall response rate was 33% and the disease control rate was 88%. A PFS ≥6 months was observed in 37% and the PFS ratio was >1.3 for 50% of the patients. These patients had a lower risk for death as compared to the 20 patients not orientated to a matched MTA (HR, 0.29; 95% CI, 0.11-0.76; p = 0.008). CONCLUSIONS: Within the MOSCATO-01 trial, patients with aBTCs had the highest rate of orientation to matched MTAs and derived a clear clinical benefit. A broader evaluation of these findings may improve future treatments strategies for aBTCs. TRIAL REGISTRATION: NCT01566019.

A phase IB dose-escalation study of the safety and pharmacokinetics of pictilisib in combination with either paclitaxel and carboplatin (with or without bevacizumab) or pemetrexed and cisplatin (with or without bevacizumab) in patients with advanced non-small cell lung cancer.

AIM: The phosphatidylinositol 3-kinase (PI3K) pathway is a potential therapeutic target in non-small cell lung cancer (NSCLC). This study aimed to evaluate the pan-PI3K inhibitor pictilisib in combination with first-line treatment regimens that were the standard of care at the time of study, in patients with NSCLC. PATIENTS AND METHODS: A 3 + 3 dose-escalation study was performed using a starting daily dose of 60 mg pictilisib on days 1-14 of a 21-day cycle. Depending on bevacizumab eligibility and NSCLC histology, patients also received either paclitaxel + carboplatin or pemetrexed + cisplatin, ± bevacizumab every 3 weeks. The primary objectives of the study were to assess safety and tolerability and to identify dose-limiting toxicities (DLTs), the maximum tolerated dose (MTD) and a recommended phase II dose (RP2D), for each combination. RESULTS: All 66 treated patients experienced at least one adverse event (AE). Grade ≥III AEs, serious AEs and deaths occurred in 57 (86.4%), 56 (84.8%) and 9 (13.6%) patients, respectively. Three patients reported DLTs across the four arms of the study. The MTD was not reached in any arm and the RP2D of pictilisib was determined to be 330 mg (capsules) or 340 mg (tablets) on a '14 days on, 7 days off' schedule. The best confirmed response was partial response in 29 (43.9%) patients and stable disease in 20 (30.9%) patients. CONCLUSION: Combining pictilisib with various standard-of-care first-line treatment regimens is feasible from a safety perspective in patients with NSCLC, and encouraging preliminary anti-tumour activity was observed.

Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence.

Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as entropy should be correlated between synchronous metastases. Therefore, a significant proportion of the variance of entropy should be attributed to the malignant process. We analyzed 112 patients with matched/paired synchronous metastases (SM#1 and SM#2) prospectively enrolled in the MOSCATO-01 clinical trial. Imaging features were extracted from Regions Of Interest (ROI) delineated on CT-scan using TexRAD software. We showed that synchronous metastasis entropy was correlated across 5 Spatial Scale Filters: Spearman's Rho ranged between 0.41 and 0.59 (P = 0.0001, Bonferroni correction). Multivariate linear analysis revealed that entropy in SM#1 is significantly associated with (i) primary tumor type; (ii) entropy in SM#2 (same malignant process); (iii) ROI area size; (iv) metastasis site; and (v) entropy in the psoas muscle (reference tissue). Entropy was a logarithmic function of ROI area in normal control tissues (aorta, psoas) and in mathematical models (P < 0.01). We concluded that entropy is a tumor-specific metric only if confounding factors are corrected.

Baseline lymphopenia should not be used as exclusion criteria in early clinical trials investigating immune checkpoint blockers (PD-1/PD-L1 inhibitors).

INTRODUCTION: A number of phase I immunotherapy trials for cancer patients incorporate the absolute lymphocyte count (ALC) as an inclusion criteria. This study aims to assess whether ALC is associated with a lack of response to anti-PD-1/PD-L1 in early clinical trials. METHODS: All consecutive patients treated with anti-PD-1/PD-L1 monotherapy in phase I trials in our institution between December 2011 and January 2014 were reviewed. Baseline ALC, neutrophil-to-lymphocyte ratio (NLR), Royal-Marsden Hospital (RMH) prognostic score, objective response rate (ORR) and disease control rate (DCR = SD + PR + CR, stable disease (SD), partial response (PR), complete response (CR)) defined by Response Evaluation Criteria In Solid Tumours (RECIST) version 1.1 were retrieved. RESULTS: Out of a total of 167 patients, 48 (28.7%) and 8 patients (4.8%) had baseline ALCs of <1 G/l and <0.5 G/l, respectively. The RECIST change (%) was not correlated with ALC (G/l) (Spearman's rho = -0.06, P = 0.43). We did not observe any difference in terms of ORR (8.3% versus 15.1%, P = 0.32) or of DCR (58.3% versus 61.3%, P = 0.73) between patients with ALC <1 G/l versus >1 G/l. When using 0.5 G/l as ALC threshold, we did not find any difference either in ORR or in DCR. In a multivariate Cox regression analysis, baseline ALC was not associated with overall survival, whereas the RMH and the number of previous lines of treatment remained independent prognostic factors. CONCLUSIONS: Baseline ALC was not associated with response to anti-PD-1/PD-L1 in cancer patients enrolled in phase I trials. Patients should not be excluded from early phase clinical trials testing immune checkpoints blockers because of ALC.

RECIST response and variation of circulating tumour cells in phase 1 trials: A prospective multicentric study.

BACKGROUND: Circulating tumour cell (CTC) counting could be a new biomarker for better evaluation of tumour response to molecules tested in phase I trials. PATIENTS AND METHODS: Consenting patients with advanced metastatic cancer referred to various phase I units were enrolled prospectively in this study. CTCs from 7.5 ml of whole blood drawn at baseline and after starting experimental therapy were counted using the CellSearch system, and tumour response was assessed using RECIST 1.1 criteria at baseline and 2 months after treatment initiation. RESULTS: Between March 2010 and May 2013, a total of 326 patients were enrolled, among whom 214 were evaluable (49% male, median age = 56; main cancer types: lung [28], colon [53], ovarian [18], breast [28]). At baseline, we detected ≥1 CTC/7.5 ml in 113/214 patients (53%), and at day 30, we observed ≥1 CTC/7.5 ml in 103/214 patients (48%). Two months after treatment initiation, 11 (5%) of the 214 patients were classified as having a partial response, with no CTCs in 9 of them or a decrease in the CTC count after therapy. In contrast, among the 104 patients (49%) classified as having progressive disease, 38 patients had a higher CTC count. The remaining 99 patients (49%), 33 of whom (33%) had a lower CTC count, were classified as having stable disease. The sensitivity and specificity of CTC variation for predicting progressive disease were 41% (32-51%) and 80% (73-88%) respectively. CONCLUSION: An early CTC change following therapy does not correlate with RECIST response in patients with advanced cancer enrolled in phase I trials.

Predictive and prognostic value of CT based radiomics signature in locally advanced head and neck cancers patients treated with concurrent chemoradiotherapy or bioradiotherapy and its added value to Human Papillomavirus status.

OBJECTIVES: To explore prognostic and predictive value of radiomics in patients with locally advanced head and neck squamous cell carcinomas (LAHNSCC) treated with concurrent chemoradiotherapy (CRT) or bioradiotherapy (BRT). MATERIALS AND METHODS: Data of 120 patients (CRT vs. BRT matched 2:1) were retrospectively analyzed. A total of 544 radiomics features of the primary tumor were extracted from radiotherapy planning computed tomography scans. Cox proportional hazards models were used to examine the association between survival and radiomics features with false discovery rate correction. The discriminatory performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Multivariate analysis showed a 24-feature based signature significantly predicted for OS (HR=0.3, P=0.02) and progression-free survival (PFS) (HR=0.3, P=0.01). Combining the radiomics signature with p16 status showed a significant improvement of prognostic performance compared with p16 (AUC=0.78vs. AUC=0.64 at 5years, P=0.01) or radiomics signature (AUC=0.78vs. AUC=0.67, P=0.01) alone. When patients were stratified according to this combination, OS and PFS were significantly different according to the 4 sub-types (p16+ with low/high signature score; p16- with low/high signature score) (P<0.001). Patients with high signature score significantly benefited from CRT (vs. BRT) in terms of OS (P=0.004), while no benefit from CRT in patients with low signature score. CONCLUSION: Our analysis suggests an added value of radiomics features as prognostic and predictive biomarker in HNSCC treated with CRT/BRT. Moreover, the radiomics signature provided additional information to HPV/p16 status to further stratify patients. External validation of such findings is mandatory given the risk of overfitting.