NF1 mutations as biomarker of response to immune checkpoint blockades for lung adenocarcinoma patients.

Little is known about immune checkpoint inhibitors (ICI) response of NF1-mutated lung adenocarcinomas. 341/4,181 (8.2%) TCGA lung adenocarcinomas samples have a somatic NF1 mutation. NF1-mutated tumors have higher TMB (p < 0.0001), higher expression of immune genes ("hot phenotype") and higher CD8 + T cell (p = 0.03) and macrophage (p = 0.02) infiltrations compared to NF1 wild-type tumors. NF1 mutation status appears as a candidate predictive biomarker for ICI response in lung adenocarcinoma patients.

Sarcoma_CellminerCDB: A tool to interrogate the genomic and functional characteristics of a comprehensive collection of sarcoma cell lines.

Sarcomas are a diverse group of rare malignancies composed of multiple different clinical and molecular subtypes. Due to their rarity and heterogeneity, basic, translational, and clinical research in sarcoma has trailed behind that of other cancers. Outcomes for patients remain generally poor due to an incomplete understanding of disease biology and a lack of novel therapies. To address some of the limitations impeding preclinical sarcoma research, we have developed Sarcoma_CellMinerCDB, a publicly available interactive tool that merges publicly available sarcoma cell line data and newly generated omics data to create a comprehensive database of genomic, transcriptomic, methylomic, proteomic, metabolic, and pharmacologic data on 133 annotated sarcoma cell lines. The reproducibility, functionality, biological relevance, and therapeutic applications of Sarcoma_CellMinerCDB described herein are powerful tools to address and generate biological questions and test hypotheses for translational research. Sarcoma_CellMinerCDB (https://discover.nci.nih.gov/SarcomaCellMinerCDB) aims to contribute to advancing the preclinical study of sarcoma.

[The French National College of Oncology Teachers (CNEC): Missions, organization, and projects]. / Le Collège national des enseignants de cancérologie (CNEC) : missions, organisation et projets.

The National College of Cancerology Teachers (CNEC) was created in September 1986. Its missions are to develop the teaching of oncology, to promote educational actions in the discipline, to participate in the development of teaching content and the definition of curricula and the control of knowledge for the training of medical students and specialists, to develop and validate educational documents relating to the above teaching, to ensure the representation of oncology teaching to of the National University Council (CNU) and administrative authorities, to ensure and coordinate relations with other university disciplines, scientific societies, national, European, and international professional groups, and to contribute to the development of research in the discipline. The current office was elected in September 2022 for three years.

Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients.

OBJECTIVES: To evaluate the performance of artificial intelligence (AI) in the preoperative detection of lung metastases on CT. MATERIALS AND METHODS: Patients who underwent lung metastasectomy in our institution between 2016 and 2020 were enrolled, their preoperative CT reports having been performed before an AI solution (Veye Lung Nodules, version 3.9.2, Aidence) became available as a second reader in our department. All CT scans were retrospectively processed by AI. The sensitivities of unassisted radiologists (original CT radiology reports), AI reports alone and both combined were compared. Ground truth was established by a consensus reading of two radiologists, who analyzed whether the nodules mentioned in the pathology report were retrospectively visible on CT. Multivariate analysis was performed to identify nodule characteristics associated with detectability. RESULTS: A total of 167 patients (men: 62.9 %; median age, 59 years [47-68]) with 475 resected nodules were included. AI detected an average of 4 nodules (0-17) per CT, of which 97 % were true nodules. The combination of radiologist plus AI (92.4 %) had significantly higher sensitivity than unassisted radiologists (80.4 %) (p < 0.001). In 27/57 (47.4 %) patients who had multiple preoperative CT scans, AI detected lung nodules earlier than the radiologist. Vascular contact was associated with non-detection by radiologists (OR:0.32[0.19, 0.54], p < 0.001), whilst the presence of cavitation (OR:0.26[0.13, 0.54], p < 0.001) or pleural contact (OR:0.10[0.04, 0.22], p < 0.001) was associated with non-detection by AI. CONCLUSION: AI significantly increases the sensitivity of preoperative detection of lung metastases and enables earlier detection, with a significant potential benefit for patient management.

Efficacy and Safety of Immune Checkpoint Blockade in Patients With Li-Fraumeni Syndrome.

A case series evaluating efficacy and safety of immune checkpoint blockade in Li-Fraumeni syndrome.

A de novo germline pathogenic BRCA1 variant identified following an osteosarcoma pangenomic molecular analysis.

De novo germline pathogenic variants (gPV) of the BReast CAncer 1 (BRCA1) gene are very rare. Only a few have been described up to date, usually in patients with a history of ovarian or breast cancer. Here, we report the first case of an incidental de novo BRCA1 germline pathogenic variant which was identified within the framework of the Plan France Médecine Génomique (PFMG) 2025 French national tumor sequencing program. The proband was a 29-year-old man diagnosed with metastatic osteosarcoma. Tumor whole exome sequencing identified a BRCA1 c.3756_3759del p.(Ser1253Argfs*10) pathogenic variant without loss-of-heterozygosity. A low genomic instability score and the absence of single base substitution signatures of homologous recombination deficiency suggested that the BRCA1 variant was not driver in the osteosarcoma tumorigenesis. Germline whole genome sequencing asserted the germline nature of this variant, with a 36% allele frequency, suggesting a mosaicism caused by a post-zygotic mutational event. The proband's family (parents and siblings) were not carriers of this variant confirming the de novo occurrence. Tumor sequencing programs like the French PFMG 2025 have been implemented worldwide and may help identify new gPV, including de novo variants.