No abstract

Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor survival1–3. We sequenced 29 SCLC exomes, two genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4±1 protein-changing mutations per million basepairs. Therefore, we conducted integrated analyses of the various data sets to identify pathogenetically relevant mutated genes. In all cases we found evidence for inactivation of TP53 and RB1 and identified recurrent mutations in histone-modifying genes, CREBBP, EP300, and MLL. Furthermore, we observed mutations in PTEN, in SLIT2, and EPHA7, as well as focal amplifications of the FGFR1 tyrosine kinase gene. Finally, we detected many of the alterations found in humans in SCLC tumors from p53/Rb1-deficient mice4. Our study implicates histone modification as a major feature of SCLC, reveals potentially therapeutically tractable genome alterations, and provides a generalizable framework for identification of biologically relevant genes in the context of high mutational background.

The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine. Significance The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy.

Our study suggests that HPD is more common with PD-1/PD-L1 inhibitors compared with chemotherapy in pretreated patients with NSCLC and is also associated with high metastatic burden and poor prognosis in patients treated with PD-1/PD-L1 inhibitors. Additional studies are needed to determine the molecular mechanisms involved in HPD.

Pretreatment LIPI, combining dNLR greater than 3 and LDH greater than ULN, was correlated with worse outcomes for ICI, but not for chemotherapy, suggesting that LIPI can serve as a potentially useful tool when selecting ICI treatment, raising the hypothesis that the LIPI might be useful for identifying patients unlikely to benefit from treatment with an ICI.