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Войти в исследования Genomic landscape and molecularly informed therapy in thymic carcinoma and other advanced thymic epithelial tumors.
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Möhrmann Lino, Rostock Lysann, Werner Maximilian, Oleś Małgorzata, Arnold Jonas S, Paramasivam Nagarajan, Jöhrens Korinna, Rupp Luise, Schmitz Marc, Richter Daniela, Uhrig Sebastian, Fröhlich Martina, Hutter Barbara, Hüllein Jennifer, Jahn Arne, Arlt Marie, Möhrmann Elena E, Hanf Dorothea, Gieldon Laura, Kreutzfeldt Simon, Heilig Christoph E, Teleanu Maria-Veronica, Lipka Daniel B, Beck Katja, Baude-Müller Annika, Mock Andreas, Jelas Ivan, Rieke Damian T, Wiesweg Marcel, Brandts Christian, Boerries Melanie, Illert Anna L, Desuki Alexander, Kindler Thomas, Krackhardt Angela M, Westphalen C Benedikt, Christopoulos Petros, Apostolidis Leonidas, Stenzinger Albrecht, Allgäuer Michael, Neumann Olaf, Kerle Irina A, Horak Peter, Heining Christoph, Grosch Heidrun, Schröck Evelin, Hübschmann Daniel, Fröhling Stefan, Glimm Hanno
Аннотация
METHODS: We examined the genomic landscape and therapeutic outcomes in 81 patients with advanced TETs, including thymic carcinomas (TCs), thymomas, and thymic neuroendocrine neoplasms (TNENs), who were enrolled in the MASTER trial, a prospective observational precision oncology trial.
FINDINGS: Using whole-genome-sequencing and whole-exome-sequencing analysis, transcriptome analysis, and methylome analysis, we identified distinct molecular features across TET subtypes, including a higher tumor mutational burden in TC and pathogenic germline variants in 18% of cases. We performed transcriptome- and methylome-based unsupervised clustering and were able to divide TCs into immunologically hot and cold subsets, with hot TCs exhibiting higher T cell infiltration and significantly longer overall survival. In 65 out of 76 (86%) patients, we recommended molecularly informed therapies, which were applied in 29 out of 65 (45%) cases, leading to a disease control rate of 62% and an objective response rate of 23% (both n = 26). The progression-free survival ratio (PFSr) was > 1.3 in 8 out of 24 (33%) patients, 7 of them having TC. Among TCs, patients achieved a mean PFSr of 1.4, indicating potential therapeutic advantages in this subgroup. The PFSr between the PFS of immune checkpoint inhibition and preceding therapies was significantly higher in the hot cluster compared to the cold cluster (median 1.7 vs. 0.3; p = 0.01945).
CONCLUSIONS: Our findings expand the understanding of TET biology and emphasize the role of precision oncology in informing treatment decisions and improving outcomes for patients with advanced TETs, particularly in TCs.