Tumour Suppressor Genes with Oncogenic Roles in Lung Cancer

Lung cancer is one of the most common cancers and the leading cause of cancer-related deaths worldwide. High-throughput sequencing efforts have uncovered the molecular heterogeneity of this disease, unveiling several genetic and epigenetic disruptions driving its development. Unlike oncogenes, tumour suppressor genes negatively regulate cell cycle control and exhibit loss-of-function alterations in cancer. Although tumour suppressor genes are more frequently disrupted, oncogenes are more likely to be drug-targeted. Many genes are described as presenting both tumour suppressive and oncogenic functions in different tumour types or even within the natural history of the disease in a single tumour. In this chapter, we describe current knowledge of tumour suppressor genes in lung tissues, focusing on tumour suppressor/oncogene duality

Small Noncoding RNA Expression in Cancer

Despite an inability to encode proteins, small noncoding RNAs (sncRNAs) have critical functions in the regulation of gene expression. They have demonstrated roles in cancer development and progression and are frequently dysregulated. Here we review the biogenesis and mechanism of action, expression patterns, and detection methods of two types of sncRNAs frequently described in cancer: miRNAs and piRNAs. Both miRNAs and piRNAs have been observed to play both oncogenic and tumor-suppressive roles, with miRNAs acting to directly regulate the mRNA of key cancer-associated genes, while piRNAs play crucial roles in maintaining the integrity of the epigenetic landscape. Elucidating these important functions of sncRNAs in normal and cancer biology relies on numerous in silico workflows and tools to profile sncRNA expression. Thus, we also discuss the key detection methods for cancer-relevant sncRNAs, including the discovery of genes that have yet to be described

Las frágiles y peligrosas medusas

International audienceIntroduction: Our aim was to explore the prognostic value of anthropometric parameters in patients treated with nivolumab for stage IV non-small cell lung cancer (NSCLC). Methods: We retrospectively included 55 patients with NSCLC treated by nivolumab with a pretreatment 18FDG positron emission tomography coupled with computed tomography (PET/CT). Anthropometric parameters were measured on the CT of PET/CT by in-house software (Anthropometer3D) allowing an automatic multi-slice measurement of Lean Body Mass (LBM), Fat Body Mass (FBM), Muscle Body Mass (MBM), Visceral Fat Mass (VFM) and Sub-cutaneous Fat Mass (SCFM). Clinical and tumor parameters were also retrieved. Receiver operator characteristics (ROC) analysis was performed and overall survival at 1 year was studied using Kaplan-Meier and Cox analysis. Results: FBM and SCFM were highly correlated (ρ = 0.99). In ROC analysis, only FBM, SCFM, VFM, body mass index (BMI) and metabolic tumor volume (MTV) had an area under the curve (AUC) significantly higher than 0.5. In Kaplan-Meier analysis using medians as cut-offs, prognosis was worse for patients with low SCFM (<5.69 kg/m2; p = 0.04, survivors 41% vs 75%). In Cox univariate analysis using continuous values, BMI (HR = 0.84, p= 0.007), SCFM (HR = 0.75, p = 0.003) and FBM (HR = 0.80, p= 0.004) were significant prognostic factors. In multivariate analysis using clinical parameters (age, gender, WHO performance status, number prior regimens) and SCFM, only SCFM was significantly associated with poor survival (HR = 0.75, p = 0.006). Conclusions: SCFM is a significant prognosis factor of stage IV NSCLC treated by nivolumab

Analysis of predictive biomarkers for immunotherapy in non-small cell lung cancer

L’immunothérapie par anti-PD1/PD L1 a bouleversé la prise en charge du cancer bronchique non à petites cellules (CBNPC) depuis 2015, offrant notamment la perspective d’un contrôle prolongé de la maladie métastatique. Néanmoins la majorité des patients ne tire pas de bénéfice de ces traitements. Il est donc indispensable d’identifier des biomarqueurs permettant de mieux Sélectionner les patients pour l’immunothérapie. A partir d’un modèle murin de CBNPC, nous avons établi le rôle du volume tumoral comme facteur prédictif de la réponse à un traitement par anti-PD1. La mesure du volume tumoral métabolique sur les données du PET scan préthérapeutique d’une cohorte de 48 patients porteurs d’un CBNPC métastatique et traités par Nivolumab a permis de confirmer ce rôle. Dans notre modèle murin, une chirurgie de cytoréduction permettait d’améliorer l’efficacité du traitement par anti-PD1. Dans une seconde étude, nous avons analysé l’efficacité des traitements par anti-PD1/PD-L1 dans le CBNPC avec mutation BRAF, MET ou HER2 ou translocation RET. Ces altérations oncogéniques sont autant de biomarqueurs permettant de proposer un traitement par thérapie ciblée, mais l’efficacité des anti-PD1/PD-L1 dans ces sous-groupes est mal connue. Des études antérieures suggèrent que cette efficacité est réduite. Nous avons mené une étude multicentrique nationale, réunissant 107 patients de 21 centres. : 26 BRAF-V600, 18 BRAF-nonV600, 30 MET, 23 HER2, 9 RET. Les taux de réponse aux anti-PD1/PD-L1 étaient de 26%, 33%, 27%, 38% et 38%, respectivement, soit des taux similaires à ceux de la population générale de CBNPC. Nos résultats incitent à poursuivre les études dans ces sous-groupes de patients puisque certains d’entre eux tirent un bénéfice prolongé des anti-PD1/PD-L1.Since 2015, anti-PD1/PD-L1 immunotherapy has emerged as a standard of care for non-small cell lung cancer (NSCLC), demonstrating a higher rate of long-term control of stage IV disease. Nonetheless, most patients do not derive benefit from these drugs. Reliable biomarkers are needed to better select patients for immunotherapy. Studying a mouse model of NSCLC, we identified tumor volume as a predictive marker of response to anti-PD1 therapy. We confirmed this role in a cohort of 48 NSCLC patients treated with Nivolumab, in whom metabolic tumor volume was assessed on pretherapeutic PET-scan. Moreover, in our mouse model, debulking surgery enhanced the efficacy of anti-PD1 treatment. In a second study, we analysed the efficacy of anti-PD1/PD-L1 treatment in NSCLC patients with BRAF, MET or HER2 mutations or RET translocation. These subgroups of patients were overlooked in clinical trials and previous studies suggest they are not good candidates for immunotherapy. We collected data from 107 patients in 21 centers : -26 BRAF-V600, 18 BRAF-nonV600, 30 MET, 23 HER2, 9 RET. Response rates to anti-PD1/PD-L1 treatment were 26%, 33%, 27%, 38% and 38%, respectively. These are close to the ones observed in unselected NSCLC patients. Our results emphasize the need for more studies in these patients, since some of them derive durable benefit from anti-PD1/PD-L1 treatment

ROS1-rearranged NSCLC With Secondary Resistance Mutation: Case Report and Current Perspectives

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ROS-1 Fusions in Non-Small-Cell Lung Cancer: Evidence to Date

The ROS-1 gene plays a major role in the oncogenesis of numerous tumors. ROS-1 rearrangement is found in 0.9&ndash;2.6% of non-small-cell lung cancers (NSCLCs), mostly lung adenocarcinomas, with a significantly higher rate of women, non-smokers, and a tendency to a younger age. It has been demonstrated that ROS-1 is a true oncogenic driver, and tyrosine kinase inhibitors (TKIs) targeting ROS-1 can block tumor growth and provide clinical benefit for the patient. Since 2016, crizotinib has been the first-line reference therapy, with two-thirds of the patients&rsquo; tumors responding and progression-free survival lasting ~20 months. More recently developed are ROS-1-targeting TKIs that are active against resistance mechanisms appearing under crizotinib and have better brain penetration. This review summarizes current knowledge on ROS-1 rearrangement in NSCLCs, including the mechanisms responsible for ROS-1 oncogenicity, epidemiology of ROS-1-positive tumors, methods for detecting rearrangement, phenotypic, histological, and molecular characteristics, and their therapeutic management. Much of this work is devoted to resistance mechanisms and the development of promising new molecules

Synthesis of multimodal tracers for apoptosis detection

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A rationale for surgical debulking to improve anti-PD1 therapy outcome in non small cell lung cancer

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The Role of Surgery in Lung Cancer Treatment: Present Indications and Future Perspectives—State of the Art

Non-small cell lung cancers (NSCLC) are different today, due to the increased use of screening programs and of innovative systemic therapies, leading to the diagnosis of earlier and pre-invasive tumors, and of more advanced and controlled metastatic tumors. Surgery for NSCLC remains the cornerstone treatment when it can be performed. The role of surgery and surgeons has also evolved because surgeons not only perform the initial curative lung cancer resection but they also accompany and follow-up patients from pre-operative rehabilitation, to treatment for recurrences. Surgery is personalized, according to cancer characteristics, including cancer extensions, from pre-invasive and local tumors to locally advanced, metastatic disease, or residual disease after medical treatment, anticipating recurrences, and patients’ characteristics. Surgical management is constantly evolving to offer the best oncologic resection adapted to each NSCLC stage. Today, NSCLC can be considered as a chronic disease and surgery is a valuable tool for the diagnosis and treatment of recurrences, and in palliative conditions to relieve dyspnea and improve patients’ comfort

Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab

Metabolic tumour volume (MTV) measured on fluorodeoxyglucose F18 (FDG) positron emission tomography coupled with computed tomography (PET/CT) is a prognostic factor of advanced non-small cell lung cancer (NSCLC) treated by first-line immunotherapy. However, these tumours are often necrotic and the necrosis, which is hypometabolic in PET FDG, is not included in the MTV. The aim of this study was to evaluate the prognostic value of total tumour volume (TTV), adding necrotic tumour volume (NTV) to metabolic tumour volume (MTV)