Cumulative incidence rates for CNS and non-CNS progression in two phase II studies of alectinib in ALK-positive NSCLC

Background: We evaluated the cumulative incidence rate (CIR) of central nervous system (CNS) and non-CNS progression in alectinib-treated patients with anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC) to determine the extent to which alectinib may treat or control CNS disease. Methods: Patients with crizotinib-pretreated locally advanced or metastatic disease received alectinib 600 mg orally twice daily in two phase II trials. All patients underwent baseline imaging and regular centrally reviewed scans. Results: At 24 months, the CIR for CNS progression was lower in patients without vs with baseline CNS metastases (8.0 vs 43.9%). Patients with baseline CNS disease and prior radiotherapy had a higher CIR of CNS progression than radiotherapy-naive patients (50.5 vs 27.4%) and a lower CIR of non-CNS progression (25.8 vs 42.5%). Adverse events leading to withdrawal occurred in 5.9% and 6.7% of patients with and without baseline CNS metastases, respectively. Conclusions: This analysis indicates a potential role for alectinib in controlling and preventing CNS metastases.

Challenges in identifying cancer genes by analysis of exome sequencing data

Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13–60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed