A study reported in Cell has shown through single-cell analysis that targeted lung cancer therapies result in transcriptional changes that researchers could exploit to improve patient outcomes.
Lung cancer is the leading cause of cancer mortality. It exhibits a vast amount of heterogeneity that allows the cancer to adapt and resist targeted therapies. In addition to intrinsic heterogeneity, the tumour microenvironment (TME) further contributes to tumour heterogeneity in cancer. Researchers have characterised the heterogeneity of the TME and tumours in many cancer subtypes. However, our understanding of how these properties evolve and interact in response to treatment remains unclear.
In this study, researchers from the University of California, San Francisco, performed single-cell RNA sequencing (scRNA-seq) analysis on advanced non-small cell lung cancer (NSCLC) samples to dissect heterogeneity. These samples were obtained from patients before starting targeted therapy, at residual disease state and at progressive disease stage where tumours showed apparent drug resistance.
The researchers used scRNA-seq to profile 49 samples from 30 patients. These samples included 45 lung adenocarcinomas, 1 squamous cell carcinoma and 3 tumour adjacent tissues. They generated transcriptomic profiles for over 20,000 cancer and TME cells.
The analysis found potentially targetable oncogenes that were different to those detected clinically. This suggests that current bulk testing might be underestimating the true heterogeneity of the tumour. The team also compared transcriptomic profiles of patient cells at residual disease state and before treatment. They found that residual disease cells expressed lower levels of proliferative marker genes. In addition, residual disease cells also expressed an alveolar-regenerative cell signature. This signature associates with improved patient outcomes and also suggests that treatment induces a transition to a primitive state.
By investigating gene expression changes between residual disease state to progressive disease state, researchers identified over 2,000 genes that had different gene expression between the two states. In the residual disease state, genes associated with the alveolar cell signature, cell growth, differentiation, cell motility and tumour suppression were overexpressed. Whereas, in progressive disease, cells overexpressed genes involved in invasion, cell-to-cell communication, differentiation and immune modulation. Researchers noted that the TME reflected a more proinflammatory state during residual disease compared to before and upon disease progression.
This study emphasises the intra-tumoral heterogeneity in cancers. It uncovered transcriptional signatures specific to different treatment time points and clinical states. Researchers could use these signatures to improve targeted therapeutic responses. Therefore, the team believe that targeting cancers at specific time points in their evolution will help improve patient survival and prevent drug resistance.