A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.

SUMMARY LKB1 regulates both cell growth and energy metabolism. It remains unclear how LKB1 inactivation coordinates tumor progression with metabolic adaptation in non-small cell lung cancer (NSCLC). Here in KrasG12D;Lkb1lox/lox (KL) mouse model, we reveal differential reactive oxygen species (ROS) levels in lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). ROS can modulate ADC-to-SCC transdifferentiation (AST). Further, pentose phosphate pathway deregulation and impaired fatty acid oxidation collectively contribute to the redox imbalance and functionally affect AST. Similar tumor and redox heterogeneity also exist in human NSCLC with LKB1 inactivation. In preclinical trials toward metabolic stress, certain KL ADC can develop drug resistance through squamous transdifferentiation. This study uncovers critical redox control of tumor plasticity that may affect therapeutic response in NSCLC.