The French multicentric molecular analysis platforms and personalized medicine trials MOST, MOST Plus and MEGAMOST.

BACKGROUND AND PURPOSE: In this manuscript we describe the academic French multicentric molecular analysis platforms including PROFILER, promoted by Centre Léon Berard, and the multicentric personalized medicine trials MOST, MOST Plus and MEGAMOST. PATIENTS/MATERIAL AND METHODS: MOST, MOST Plus and MEGAMOST comprise 14 cohorts with different targeted agents and immunotherapies. RESULTS AND INTERPRETATION: PROFILER has recruited 5,991 patients in 10 years, MOST and MOST Plus 875 patients since 2014 and MEGAMOST 172 patients since 2020, and are still ongoing. We provide a description of the local, national and international implications of these initiatives, and we review the results of the sorafenib and olaparib cohorts.

PCM4EU and PRIME-ROSE: Collaboration for implementation of precision cancer medicine in Europe.

BACKGROUND: In the two European Union (EU)-funded projects, PCM4EU (Personalized Cancer Medicine for all EU citizens) and PRIME-ROSE (Precision Cancer Medicine Repurposing System Using Pragmatic Clinical Trials), we aim to facilitate implementation of precision cancer medicine (PCM) in Europe by leveraging the experience from ongoing national initiatives that have already been particularly successful. PATIENTS AND METHODS: PCM4EU and PRIME-ROSE gather 17 and 24 partners, respectively, from 19 European countries. The projects are based on a network of Drug Rediscovery Protocol (DRUP)-like clinical trials that are currently ongoing or soon to start in 11 different countries, and with more trials expected to be established soon. The main aims of both the projects are to improve implementation pathways from molecular diagnostics to treatment, and reimbursement of diagnostics and tumour-tailored therapies to provide examples of best practices for PCM in Europe. RESULTS: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu.eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024. CONCLUSION: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu.eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024. CONCLUSION: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients.

Qualitative evaluation of motives for acceptance or refusal of early palliative care in patients included in early-phase clinical trials in a French comprehensive cancer center: the PALPHA study.

PURPOSE: The integration of palliative care (PC) into oncological management is recommended well before the end of life. It improves quality of life and symptom control and reduces the aggressiveness of end-of-life care. However, its appropriate timing is still debated. Entry into an early-phase clinical trial (ECT) represents hopes for the patient when standard treatments have failed. It is an opportune moment to integrate PC to preserve the patient's general health status. The objective of this study was to evaluate the motives for acceptance or refusal of early PC management in patients included in an ECT. METHODS: Patients eligible to enter an ECT were identified and concomitant PC was proposed. All patients received exploratory interviews conducted by a researcher. Their contents were analyzed in a double-blind thematic analysis with a self-determination model. RESULTS: Motives for acceptance (PC acceptors: n = 27) were both intrinsic (e.g., pain relief, psychological support, anticipation of the future) and extrinsic (e.g., trust in the medical profession, for a relative, to support the advance of research). Motives for refusal (PC refusers: n = 3) were solely intrinsic (e.g., PC associated with death, negative representation of psychological support, no need for additional care, claim of independence). CONCLUSIONS: The motives of acceptors and refusers are not internalized in the same way and call for different autonomy needs. Acceptors and refusers are influenced by opposite representations of PC and a different perception of mixed management.

An international phase II trial and immune profiling of SBRT and atezolizumab in advanced pretreated colorectal cancer.

BACKGROUND: Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the colorectal (CRC) cohort analysis from the SABR-PDL1 trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in advanced cancer patients. METHODS: Eligible patients received atezolizumab 1200 mg every 3 weeks until progression or unmanageable toxicity, together with ablative SBRT delivered concurrently with the 2nd cycle (recommended dose of 45 Gy in 3 fractions, adapted upon normal tissue tolerance constraint). SBRT was delivered to at least one tumor site, with at least one additional measurable lesion being kept from the radiation field. The primary efficacy endpoint was one-year progression-free survival (PFS) rate from the start of atezolizumab. Sequential tumor biopsies were collected for deep multi-feature immune profiling. RESULTS: Sixty pretreated (median of 2 prior lines) advanced CRC patients (38 men [63%]; median age, 59 years [range, 20-81 years]; 77% with liver metastases) were enrolled in five centers (France: n = 4, Spain: n = 1) from 11/2016 to 04/2019. All but one (98%) received atezolizumab and 54/60 (90%) received SBRT. The most frequently irradiated site was lung (n = 30/54; 56.3%). Treatment-related G3 (no G4-5) toxicity was observed in 3 (5%) patients. Median OS and PFS were respectively 8.4 [95%CI:5.9-11.6] and 1.4 months [95%CI:1.2-2.6], including five (9%) patients with PFS > 1 year (median time to progression: 19.2 months, including 2/5 MMR-proficient). Best overall responses consisted of stable disease (n = 38; 64%), partial (n = 3; 5%) and complete response (n = 1; 2%). Immune-centric multiplex IHC and RNAseq showed that SBRT redirected immune cells towards tumor lesions, even in the case of radio-induced lymphopenia. Baseline tumor PD-L1 and IRF1 nuclear expression (both in CD3 + T cells and in CD68 + cells) were higher in responding patients. Upregulation of genes that encode for proteins known to increase T and B cell trafficking to tumors (CCL19, CXCL9), migration (MACF1) and tumor cell killing (GZMB) correlated with responses. CONCLUSIONS: This study provides new data on the feasibility, efficacy, and immune context of tumors that may help identifying advanced CRC patients most likely to respond to immuno-radiotherapy. TRIAL REGISTRATION: EudraCT N°: 2015-005464-42; Clinicaltrial.gov number: NCT02992912.

Biliary tract cancers: French national clinical practice guidelines for diagnosis, treatments and follow-up (TNCD, SNFGE, FFCD, UNICANCER, GERCOR, SFCD, SFED, AFEF, SFRO, SFP, SFR, ACABi, ACHBPT).

INTRODUCTION: This document is a summary of the French intergroup guidelines of the management of biliary tract cancers (BTC) (intrahepatic, perihilar and distal cholangiocarcinomas, and gallbladder carcinomas) published in September 2023, available on the website of the French Society of Gastroenterology (SNFGE) (www.tncd.org). METHODS: This collaborative work was conducted under the auspices of French medical and surgical societies involved in the management of BTC. Recommendations were graded in three categories (A, B and C) according to the level of scientific evidence until August 2023. RESULTS: BTC diagnosis and staging is mainly based on enhanced computed tomography, magnetic resonance imaging and (endoscopic) ultrasound-guided biopsy. Treatment strategy depends on BTC subtype and disease stage. Surgery followed by adjuvant capecitabine is recommended for localised disease. No neoadjuvant treatment is validated to date. Cisplatin-gemcitabine chemotherapy combined to the anti-PD-L1 inhibitor durvalumab is the first-line standard of care for advanced disease. Early systematic tumour molecular profiling is recommended to screen for actionable alterations (IDH1 mutations, FGFR2 rearrangements, HER2 amplification, BRAFV600E mutation, MSI/dMMR status, etc.) and guide subsequent lines of treatment. In the absence of actionable alterations, FOLFOX chemotherapy is the only second-line standard-of-care. No third-line chemotherapy standard is validated to date. CONCLUSION: These guidelines are intended to provide a personalised therapeutic strategy for daily clinical practice. Each individual BTC case should be discussed by a multidisciplinary team.

Bexmarilimab-induced macrophage activation leads to treatment benefit in solid tumors: The phase I/II first-in-human MATINS trial.

Macrophage Clever-1 contributes to impaired antigen presentation and suppression of anti-tumor immunity. This first-in-human trial investigates the safety and tolerability of Clever-1 blockade with bexmarilimab in patients with treatment-refractory solid tumors and assesses preliminary anti-tumor efficacy, pharmacodynamics, and immunologic correlates. Bexmarilimab shows no dose-limiting toxicities in part I (n = 30) and no additional safety signals in part II (n = 108). Disease control (DC) rates of 25%-40% are observed in cutaneous melanoma, gastric, hepatocellular, estrogen receptor-positive breast, and biliary tract cancers. DC associates with improved survival in a landmark analysis and correlates with high pre-treatment intratumoral Clever-1 positivity and increasing on-treatment serum interferon γ (IFNγ) levels. Spatial transcriptomics profiling of DC and non-DC tumors demonstrates bexmarilimab-induced macrophage activation and stimulation of IFNγ and T cell receptor signaling selectively in DC patients. These data suggest that bexmarilimab therapy is well tolerated and show that macrophage targeting can promote immune activation and tumor control in late-stage cancer.

Integrative Pan-Cancer Genomic and Transcriptomic Analyses of Refractory Metastatic Cancer.

Metastatic relapse after treatment is the leading cause of cancer mortality, and known resistance mechanisms are missing for most treatments administered to patients. To bridge this gap, we analyze a pan-cancer cohort (META-PRISM) of 1,031 refractory metastatic tumors profiled via whole-exome and transcriptome sequencing. META-PRISM tumors, particularly prostate, bladder, and pancreatic types, displayed the most transformed genomes compared with primary untreated tumors. Standard-of-care resistance biomarkers were identified only in lung and colon cancers-9.6% of META-PRISM tumors, indicating that too few resistance mechanisms have received clinical validation. In contrast, we verified the enrichment of multiple investigational and hypothetical resistance mechanisms in treated compared with nontreated patients, thereby confirming their putative role in treatment resistance. Additionally, we demonstrated that molecular markers improve 6-month survival prediction, particularly in patients with advanced breast cancer. Our analysis establishes the utility of the META-PRISM cohort for investigating resistance mechanisms and performing predictive analyses in cancer. SIGNIFICANCE: This study highlights the paucity of standard-of-care markers that explain treatment resistance and the promise of investigational and hypothetical markers awaiting further validation. It also demonstrates the utility of molecular profiling in advanced-stage cancers, particularly breast cancer, to improve the survival prediction and assess eligibility to phase I clinical trials. This article is highlighted in the In This Issue feature, p. 1027.

Molecular analysis for refractory rare cancers: Sequencing battle continues - learnings for the MOSCATO-01 study.

BACKGROUND: For patients with metastatic rare cancers, treatments are limited. How systematic tumor sequencing can improve therapeutic possibilities in this population? PATIENTS AND METHODS: Patients with rare cancer were identified in the MOSCATO-01 trial. Patients' outcome was measured by progression-free survival (PFS) and overall survival (OS). RESULTS: The most frequently identified histologic subypes were ovarian adenocarcinoma (N = 13), carcinoma of unknown primary (N = 11), and leiomyosarcoma (N = 10). Ninety-nine (39%) of them had at least one targetable cancer molecular alteration Forty-nine patients (50%) received the therapy proposed by the molecular tumor board, and 13 patients (26%, 95%CI 15-41%) achieved a PFS2/PFS1 > 1.3. The median PFS2 on matched treatment subgroup was 2.3 months (95% CI 1.8-3.6) and the median OS was 11.4 months (95% CI 9-15.5). CONCLUSIONS: The molecular screening of patients with refractory, metastatic rare cancers might increase the therapeutic options. Facilitating access strategy to molecular-driven clinical trials or agnostic-approved treatment is crucial.

Implementing the European Society for Medical Oncology Scale for Clinical Actionability of Molecular Targets in a Comprehensive Profiling Program: Impact on Precision Medicine Oncology.

PURPOSE: To facilitate implementation of precision medicine in clinical management of cancer, the European Society of Medical Oncology proposed in 2018 a new scale to harmonize and standardize the reporting and interpretation of clinically relevant genomics data (ESMO Scale of Actionability of molecular Targets [ESCAT]). This study aims to characterize the clinical impact of matching targetable genomic alterations (GAs) in patients with advanced cancer according to ESCAT. MATERIAL AND METHODS: Analysis of next-generation sequencing results from 552 patients is included in two prospective precision medicine studies at Gustave Roussy. End points included objective response rates, progression-free survival, and overall survival according to ESCAT. RESULTS: Molecular data from 516 patients were available and discussed within a Molecular Tumor Board. The most common tumor types were GI (n = 164; 30%), lung (n = 137; 25%), and urologic tumors (n = 68; 13%). Overall, 379 GAs were considered as actionable targets according to ESCAT in 348 (67%) patients. In 31 (6%) patients, two concomitant actionable targets were identified. On the basis of ESCAT, GAs were considered to be classified as tier I in 120 patients (29%), II in 25 patients (5%), III in 80 patients (16%), and IV in 153 patients (30%). A total of 136 patients (27%) received a matched therapy. ESCAT was significantly associated with objective response rates and clinical benefit rates. The median progression-free survival was 6.5 months (95% CI, 4.2 to 8.9), 3 months (95% CI, 1 to not available), 3 months (95% CI, 2.2 to 3.8), and 4 months (95% CI, 2.8 to 6.3) for ESCAT I, II, III, and IV, respectively (P = .0125). CONCLUSION: Implementation of ESCAT classification for clinical decision making by Molecular Tumor Board is feasible and useful to better tailor therapies in patients with cancer.

PALLIA 10 score in phase I cancer studies.

OBJECTIVE: Phase I clinical trials usually include patients with advanced disease who have failed standard therapies and should benefit from early palliative care. We try to assess whether PALLIA 10, a score developed in France to help identify patients who might benefit from a palliative care referral, could be used in a phase I department trial. METHODS: We assessed PALLIA 10 score and other prognostic factors in patients enrolled in phase I trials at Gustave Roussy Cancer Center prospectively during two periods of time (cohort 1 (C1) and 2 (C2)). A double-blind assessment of the PALLIA 10 score was done in C2 by a palliative care specialist and a nurse. RESULTS: From 1 July 2018 to 1 November 2018 (C1) and from 1 December 2020 to 16 April 2021 (C2), 86 patients were assessed in C1 and 302 in C2. Median PALLIA 10 was very low in both cohorts (median 1, range 1-5 in C1 and 1-8 in C2). On C1 and C2, 12% and 5% of patients had a dedicated palliative consultation. In C2, assessment of PALLIA 10 score was significantly different between palliative care physician (median 5, range 3-8), phase I physician (median 1, range 1-6) and phase I nurse (median 3, range 1-8) (p<0.001). CONCLUSION: Median PALLIA 10 score was low when assessed by the phase I physician, which suggests the need for a better tool and appropriate clinician's education to implement early palliative care in clinical practice and trials.

Prognostic value of tumor immune biomarkers in biopsies from patients with refractory solid cancers.

PD-L1 and tumor-infiltrating lymphocytes play a key role in the immune escape of cancer, although their prognostic value remains unknown in patients with refractory solid cancer compared to other known prognostic estimation methods. In this ancillary study, we assessed the prognostic value of previously-defined prognostic scores (such as the Royal Marsden Hospital (RMH) score) and of PD-L1, CD3, CD8 and FOXP3 expressions based on immunohistochemistry (IHC) and RNA sequencing (RNAseq) of tumor samples from patients included in the personalized-medicine MOSCATO-02 trial. We collected biopsies with successful IHC analysis from 266 patients treated between April 2016 and September 2017, among whom 170 (63.9%) also had a matched RNAseq. We used a Random Forest model to identify the best prognostic factor, and a Lasso-penalized Cox model to validate the findings. We found that the RMH score was the strongest prognostic factor, with high scores associated with a higher risk of death (Hazard Ratio (HR)=1.29; CI95%[1.19-1.21]). The PD-L1 expression score obtained from IHC analyses was the second-best performing predictor, with the 1+ score (low expression) linked to a lower risk of death (HR=0.564; CI95%[0.539-0.580]). Other tested variables, including primary tumor type and subsequent treatments received following biopsy, were not found significantly linked to prognosis. We found modest correlation between IHC and RNAseq expressions of immune genes, but RNAseq related better to prognosis. Overall, our study supports the use of the RMH score and the assessment of PD-L1 expression in IHC to estimate prognosis in patients with advanced cancer.

Epigenetic gene alterations in metastatic solid tumours: results from the prospective precision medicine MOSCATO and MATCH-R trials.

INTRODUCTION: Although the role of epigenetic alterations in oncogenesis has been well studied, their prevalence in metastatic solid tumours is still poorly described. We therefore aimed at: (i) describing the presence of epigenetic gene alterations (EGA) - defined by an alteration in a gene encoding an epigenetic regulator; and (ii) evaluating their relationship with clinical characteristics and outcome in patients (pts) included in prospective molecular profiling trials. MATERIALS AND METHODS: On-purpose tumour biopsies from pts with metastatic solid tumours enrolled in the Gustave Roussy-sponsored MOSCATO (NCT01566019) and MATCHR (NCT02517892) trials were molecularly profiled using whole exome sequencing (WES). Alterations in 176 epigenetic genes were assessed and classified as pathogenic variants (PV) or non-pathogenic variants by a molecular tumour board. Clinical characteristics and outcome were collected. RESULTS: Between Dec 2011 and Oct 2016, WES was successfully performed in 292 pts presenting various solid tumours. We found 496 epigenetic gene alterations in 134 patients (49%), including 237 pathogenic variants in 86 patients; 63 tumour samples (47%) presented ≥3 EGAs. The median number of previous treatment lines was 3 (1-10). The most frequently altered genes were KMT2D and KMT2C (16% each), ARID1A and SETD2 (10% each) and KMT2A (8%).; 31% of EGA co-occurred with a driver gene alteration (p &lt; 0.001). Outcome was not correlated with the presence of EGA. CONCLUSIONS: Epigenetic alterations occur frequently in metastatic solid tumours. With the current development of epigenetic modifiers, they increasingly represent actionable targets. Such genes should now be systematically analysed in molecular profiling studies.

Radiological patterns of tumour progression in patients treated with a combination of immune checkpoint blockers and antiangiogenic drugs.

BACKGROUND: Immune checkpoint blockers (ICBs) in combination with antiangiogenic drugs showed synergistic efficacy in several tumour types. New patterns of progression have recently been defined upon treatment with ICB alone including atypical responses such as pseudoprogression (PsPD), dissociated response and hyperprogressive disease (HPD). This study aimed to describe the patterns of response observed in patients treated with combination ICB with antiangiogenic drugs. METHODS: We conducted a monocentric retrospective analysis of patients (pts) enrolled in phase I trials at Gustave Roussy assessing the combination of ICB and antiangiogenic drugs. Radiological CT scans were centrally reviewed by a senior radiologist according to iRECIST criteria including progressive disease (PD), partial response (PR) and stable disease (SD). HPD was defined as a progression at the first evaluation with a delta tumour growth rate exceeding 50%. PsPD was defined as initial progression followed by stabilisation or decrease of tumour size, DisR as a concomitant size decrease in some tumour lesions and size increase in others. Both PsPD and DisR are defined as atypical responses. Overall response rate included PR and complete response (CR) and disease control rate included PR, CR and SD. RESULTS: Between December 2016 and June 2020, 111 pts were included. The median follow up was 12.8 months (11.3-15.1). The most common tumour types were lung and pleura (20%), kidney (18%) and bladder (17%). The overall response rate and disease control rate were 21.6% (n = 24) and 59% (n = 65), respectively. Twenty-one patients (19%) experienced PD as the best response. PsPD, DisR and HPD were observed in 4 (3.6%), 11 (9.9%) and 7 (6.3%) pts, respectively. DisR and PsPD were associated with longer iProgression Free Survival (median: 6.9 and 18.9 months, respectively) and iOverall Survival (median: 28.4 and 31.1 months, respectively) than a median of SD in immune progression-free survival (median: 4.2 months) and immune overall survival (median: 12.7 months). CONCLUSION: Patients treated with ICBs and antiangiogenic agents display atypical responses. Survival might be longer in patients with DisR responses and PsPD disease than patients with HPD, PD and SD.

Natural Language Processing for Patient Selection in Phase I or II Oncology Clinical Trials.

PURPOSE: Early discontinuation affects more than one third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We aimed at predicting the successful screening and dose-limiting toxicity period completion (SSD) from automatic analysis of consultation reports. MATERIALS AND METHODS: We retrieved the consultation reports of patients included in phase I and/or phase II oncology trials for any tumor type at Gustave Roussy, France. We designed a preprocessing pipeline that transformed free text into numerical vectors and gathered them into semantic clusters. These document-based semantic vectors were then fed into a machine learning model that we trained to output a binary prediction of SSD status. RESULTS: Between September 2012 and July 2020, 56,924 consultation reports were used to build the dictionary and 1,858 phase I or II inclusion reports were used to train (72%), validate (14%), and test (14%) a random forest model. Preprocessing could efficiently cluster words with semantic proximity. On the unseen test cohort of 264 consultation reports, the performances of the model reached: F1 score 0.80, recall 0.81, and area under the curve 0.88. Using this model, we could have reduced the screen fail rate (including dose-limiting toxicity period) from 39.8% to 12.8% (relative risk, 0.322; 95% CI, 0.209 to 0.498; P < .0001) within the test cohort. Most important semantic clusters for predictions comprised words related to hematologic malignancies, anatomopathologic features, and laboratory and imaging interpretation. CONCLUSION: Machine learning with semantic conservation is a promising tool to assist physicians in selecting patients prone to achieve SSD in early-phase oncology clinical trials.

Applications of single-cell and bulk RNA sequencing in onco-immunology.

The rising interest for precise characterization of the tumour immune contexture has recently brought forward the high potential of RNA sequencing (RNA-seq) in identifying molecular mechanisms engaged in the response to immunotherapy. In this review, we provide an overview of the major principles of single-cell and conventional (bulk) RNA-seq applied to onco-immunology. We describe standard preprocessing and statistical analyses of data obtained from such techniques and highlight some computational challenges relative to the sequencing of individual cells. We notably provide examples of gene expression analyses such as differential expression analysis, dimensionality reduction, clustering and enrichment analysis. Additionally, we used public data sets to exemplify how deconvolution algorithms can identify and quantify multiple immune subpopulations from either bulk or single-cell RNA-seq. We give examples of machine and deep learning models used to predict patient outcomes and treatment effect from high-dimensional data. Finally, we balance the strengths and weaknesses of single-cell and bulk RNA-seq regarding their applications in the clinic.

Rare cancer, rare alteration: the case of NTRK fusions in biliary tract cancers.

Introduction: For patients with advanced/unresectable biliary tract cancers, cisplatin-gemcitabine combination is the standard first-line treatment. Beyond the first line, the therapeutic arsenal is limited with minimal benefit. Biliary tract cancers exhibit one of the highest frequencies of targetable molecular alterations across cancer types, and several targeted therapies are emerging as treatment options.Areas covered:We discuss neurotrophic tyrosine kinase receptor gene (NTRK) fusions in biliary tract cancers and the use of NTRK inhibitors (now approved in a 'cancer-agnostic' way), mechanisms of resistance, and emerging second-generation NTRK inhibitors.Expert opinion: Despite their rarity in biliary tract cancers, NTRK fusions are promising molecular targets because i) NTRK inhibitors have proven highly effective in NTRK-rearranged cancers and are now approved in a 'cancer-agnostic' way; ii) emerging second-generation NTRK inhibitors may overcome secondary resistance; iii) NTRK rearrangements will be readily detectable with the generalization of next-generation-sequencing in biliary tract cancers, including the detection of other frequent gene rearrangements, such as those involving the fibroblast growth factor receptor 2 gene (FGFR2). However, more data are necessary regarding the prevalence and characteristics of NTRK fusions in biliary tract cancers and the efficacy of NTRK inhibitors in these patients.

Prediction of Drug Approval After Phase I Clinical Trials in Oncology: RESOLVED2.

PURPOSE: Drug development in oncology currently is facing a conjunction of an increasing number of antineoplastic agents (ANAs) candidate for phase I clinical trials (P1CTs) and an important attrition rate for final approval. We aimed to develop a machine learning algorithm (RESOLVED2) to predict drug development outcome, which could support early go/no-go decisions after P1CTs by better selection of drugs suitable for further development. METHODS: PubMed abstracts of P1CTs reporting on ANAs were used together with pharmacologic data from the DrugBank5.0 database to model time to US Food and Drug Administration (FDA) approval (FDA approval-free survival) since the first P1CT publication. The RESOLVED2 model was trained with machine learning methods. Its performance was evaluated on an independent test set with weighted concordance index (IPCW). RESULTS: We identified 462 ANAs from PubMed that matched with DrugBank5.0 (P1CT publication dates 1972 to 2017). Among 1,411 variables, 28 were used by RESOLVED2 to model the FDA approval-free survival, with an IPCW of 0.89 on the independent test set. RESOLVED2 outperformed a model that was based on efficacy/toxicity (IPCW, 0.69). In the test set at 6 years of follow-up, 73% (95% CI, 49% to 86%) of drugs predicted to be approved were approved, whereas 92% (95% CI, 87% to 98%) of drugs predicted to be nonapproved were still not approved (log-rank P < .001). A predicted approved drug was 16 times more likely to be approved than a predicted nonapproved drug (hazard ratio, 16.4; 95% CI, 8.40 to 32.2). CONCLUSION: As soon as P1CT completion, RESOLVED2 can predict accurately the time to FDA approval. We provide the proof of concept that drug development outcome can be predicted by machine learning strategies.

Sustained Type I interferon signaling as a mechanism of resistance to PD-1 blockade.

PD-1 blockade represents a major therapeutic avenue in anticancer immunotherapy. Delineating mechanisms of secondary resistance to this strategy is increasingly important. Here, we identified the deleterious role of signaling via the type I interferon (IFN) receptor in tumor and antigen presenting cells, that induced the expression of nitric oxide synthase 2 (NOS2), associated with intratumor accumulation of regulatory T cells (Treg) and myeloid cells and acquired resistance to anti-PD-1 monoclonal antibody (mAb). Sustained IFNß transcription was observed in resistant tumors, in turn inducing PD-L1 and NOS2 expression in both tumor and dendritic cells (DC). Whereas PD-L1 was not involved in secondary resistance to anti-PD-1 mAb, pharmacological or genetic inhibition of NOS2 maintained long-term control of tumors by PD-1 blockade, through reduction of Treg and DC activation. Resistance to immunotherapies, including anti-PD-1 mAb in melanoma patients, was also correlated with the induction of a type I IFN signature. Hence, the role of type I IFN in response to PD-1 blockade should be revisited as sustained type I IFN signaling may contribute to resistance to therapy.

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.