Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology

Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments

Novel lymphocyte-independent antitumor activity by PD-1 blocking antibody against PD-1+ chemoresistant lung cancer cells

Purpose: Antibodies against the lymphocyte PD-1 (aPD-1) receptor are cornerstone agents for advanced non-small cell lung cancer (NSCLC), based on their ability to restore the exhausted antitumor immune response. Our study reports a novel, lymphocyte-independent, therapeutic activity of aPD-1 against NSCLC, blocking the tumor-intrinsic PD-1 receptors on chemoresistant cells. Experimental design: PD-1 in NSCLC cells was explored in vitro at baseline, including stem-like pneumospheres, and following treatment with cisplatin both at transcriptional and protein levels. PD-1 signaling and RNA sequencing were assessed. The lymphocyte-independent antitumor activity of aPD-1 was explored in vitro, by PD-1 blockade and stimulation with soluble ligand (PD-L1s), and in vivo within NSCLC xenograft models. Results: We showed the existence of PD-1+ NSCLC cell subsets in cell lines and large in silico datasets (Cancer Cell Line Encyclopedia and The Cancer Genome Atlas). Cisplatin significantly increased PD-1 expression on chemo-surviving NSCLC cells (2.5-fold P = 0.0014), while the sequential treatment with anti-PD-1 Ab impaired their recovery after chemotherapy. PD-1 was found to be associated with tumor stemness features. PD-1 expression was enhanced in NSCLC stem-like pneumospheres (P < 0.0001), significantly promoted by stimulation with soluble PD-L1 (+27% ± 4, P < 0.0001) and inhibited by PD-1 blockade (-30% ± 3, P < 0.0001). The intravenous monotherapy with anti-PD-1 significantly inhibited tumor growth of NSCLC xenografts in immunodeficient mice, without the contribution of the immune system, and delayed the occurrence of chemoresistance when combined with cisplatin. Conclusions: We report first evidence of a novel lymphocyte-independent activity of anti-PD-1 antibodies in NSCLC, capable of inhibiting chemo-surviving NSCLC cells and exploitable to contrast disease relapses following chemotherapy. See related commentary by Augustin et al., p. 505