Journal Article

Geospatial immune variability illuminates differential evolution of lung adenocarcinoma

Zapata, Luis, McGranahan, Nicholas, Marafioti, Teresa, Rosenthal, Rachel, Yuan, Yinyin, Hackshaw, Allan, Le Quesne, John, Veeriah, Selvaraju, Swanton, Charles, Salgado, Roberto, Al Bakir, Maise, Officer, Leah, Akarca, Ayse, Loi, Sherene, Quezada, Sergio A., AbdulJabbar, Khalid, Smith, Claire Rachel, Sereno, Marco, Lund, Tom, Moore, David A., Hiley, Crispin T., Raza, Shan E. Ahmed, Jamal-Hanjani, Mariam

2020

Overview

Remarkable progress in molecular analyses has improved our understanding of the evolution of cancer cells toward immune escape 1 – 5 . However, the spatial configurations of immune and stromal cells, which may shed light on the evolution of immune escape across tumor geographical locations, remain unaddressed. We integrated multiregion exome and RNA-sequencing (RNA-seq) data with spatial histology mapped by deep learning in 100 patients with non-small cell lung cancer from the TRACERx cohort 6 . Cancer subclones derived from immune cold regions were more closely related in mutation space, diversifying more recently than subclones from immune hot regions. In TRACERx and in an independent multisample cohort of 970 patients with lung adenocarcinoma, tumors with more than one immune cold region had a higher risk of relapse, independently of tumor size, stage and number of samples per patient. In lung adenocarcinoma, but not lung squamous cell carcinoma, geometrical irregularity and complexity of the cancer–stromal cell interface significantly increased in tumor regions without disruption of antigen presentation. Decreased lymphocyte accumulation in adjacent stroma was observed in tumors with low clonal neoantigen burden. Collectively, immune geospatial variability elucidates tumor ecological constraints that may shape the emergence of immune-evading subclones and aggressive clinical phenotypes. Multiregion spatial histology, exome and transcriptome data from patients with non-small cell lung cancer suggest that cancer subclones from immune cold regions diversify later than subclones from immune hot regions

• Publisher: Nature Publishing Group US,Nature Publishing Group
• Subject: 631/250/2161 / 631/67/2329 / 631/67/580 / 692/699/67/1612/1350 / Adenocarcinoma / Adenocarcinoma of Lung - genetics / Adenocarcinoma of Lung - immunology / Adenocarcinoma of Lung - pathology / Antigen presentation / Antigens / Antigens, Neoplasm - genetics / Antigens, Neoplasm - immunology / Biomarkers, Tumor - genetics / Biomedical and Life Sciences / Biomedicine / Cancer Research / Carcinoma, Non-Small-Cell Lung - genetics / Carcinoma, Non-Small-Cell Lung - immunology / Carcinoma, Non-Small-Cell Lung - pathology / Cold regions / Deep Learning / Development and progression / Evolution / Evolutionary computation / Exome - genetics / Exome Sequencing / Female / Gene expression / Gene sequencing / Genetic aspects / Geographical locations / Health aspects / Histology / Humans / Immune system / Infectious Diseases / Letter / Lung cancer / Lung cancer, Non-small cell / Lung carcinoma / Lymphocytes / Machine learning / Male / Metabolic Diseases / Middle Aged / Molecular Medicine / Mutation / Mutation - genetics / Neoantigens / Neoplasm Recurrence, Local - genetics / Neoplasm Recurrence, Local - immunology / Neoplasm Recurrence, Local - pathology / Neoplasm Staging / Neurosciences / Non-small cell lung carcinoma / Phenotypes / Recurrence / Ribonucleic acid / RNA / RNA-Seq / Small cell lung carcinoma / Spatial data / Squamous cell carcinoma / Stromal cells / Tumor Microenvironment - genetics / Tumor Microenvironment - immunology / Tumors