Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of 'big data' in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment. <<<

The paradigm of surface-expressed programmed death ligand 1 (PDL1) signalling to immune cell programmed death 1 (PD1) to inhibit antitumour immunity has helped to develop effective and revolutionary immunotherapies using antibodies blocking these cell-extrinsic interactions. The recent discovery of cancer cell-intrinsic PDL1 signals has broadened understanding of pathologic tumour PDL1 signal consequences that now includes control of tumour growth and survival pathways, stemness, immune effects, DNA damage responses and gene expression regulation. Many such effects are PD1-independent. These insights demonstrate that the prevailing cell-extrinsic PDL1 signalling paradigm is useful, but incomplete in important respects. This Perspective discusses historical and recent advances in understanding cancer cell-intrinsic PDL1 signals, mechanisms for signal controls and important immunopathologic consequences including resistance to cytotoxic agents, targeted small molecules and immunotherapies. Cancer cell-intrinsic PDL1 signals present novel drug discovery targets and also have potential as reliable treatment response biomarkers. Cancer cell-intrinsic PD1 signals and cell-intrinsic PDL1 signals in non-cancer cells are discussed briefly, as are PDL1 signals from soluble and vesicle-bound PDL1 and PDL1 isoforms. We conclude with suggestions for addressing the most pressing challenges and opportunities in this rapidly developing field. <<<