Project description:<p>Blockade of T cell coinhibitory molecules such as CTLA-4 and PD-1, can activate T cell antitumor response. Although these immune checkpoint blockades (CTLA-4 blockade and PD-1 blockade) have shown durable response, response rate is modest. Therefore, there is a need to find stable biomarkers predictive of response to immune checkpoint blockades and to understand underlying resistance mechanisms. We collected longitudinal tumor biopsies from a cohort of metastatic melanoma patients treated with sequential immune checkpoint blockades and performed whole exome sequencing of this cohort. The comprehensive genomic characterization of tumors enabled identification of higher copy number loss burden as a resistance mechanism and clonal T cell repertoire as a predictive biomarker.</p>
Project description:Tumor cell-containing Regions of Interest from 17 patients with melanoma after progression to Immune Checkpoint Blockade were profiled at the transcriptomic level.
Project description:Immune checkpoint blockade (ICB) has demonstrated efficacy in patients with melanoma, but many exhibit poor responses. Using single cell RNA sequencing of melanoma patient-derived circulating tumor cells (CTCs) and functional characterization using mouse melanoma models, we show that the KEAP1/NRF2 pathway modulates sensitivity to ICB, independently of tumorigenesis. The NRF2 negative regulator, KEAP1, shows intrinsic variation in expression, leading to tumor heterogeneity and subclonal resistance.
Project description:Immune checkpoint blockade (ICB) has demonstrated efficacy in patients with melanoma, but many exhibit poor responses. Using single cell RNA sequencing of melanoma patient-derived circulating tumor cells (CTCs) and functional characterization using mouse melanoma models, we show that the KEAP1/NRF2 pathway modulates sensitivity to ICB, independently of tumorigenesis. The NRF2 negative regulator, KEAP1, shows intrinsic variation in expression, leading to tumor heterogeneity and subclonal resistance.
Project description:Mitochondrial DNA (mtDNA) encodes essential machinery for respiration and metabolic homeostasis but is paradoxically among the most common targets of somatic mutations in the cancer genome, with truncating mutations in complex I genes being over-represented1 . While mtDNA mutations have been associated with both improved and worsened prognoses in several cancer lineages1–3, whether these mutations are drivers, or exert any functional effect on tumour biology remains controversial. Here we discover that complex I-encoding mtDNA mutations are sufficient to remodel the tumour immune landscape and therapeutic resistance to immune checkpoint blockade. Using mtDNA base editing technology we engineered recurrent truncating mutations in the mtDNA-encoded complex I gene, Mt-Nd5, into murine models of melanoma. Mechanistically, these mutations promoted utilisation of pyruvate as a terminal electron acceptor and increased glycolytic flux driven by an over-reduced NAD pool and NADH shuttling between GAPDH and MDH1, mediating a Warburg-like metabolic shift. In turn, without modifying tumour growth, this altered cancer cell-intrinsic metabolism reshaped the tumour microenvironment of mouse and human cancer in a mutation load-dependent fashion, encouraging an anti-tumour immune response. This subsequently sensitises both mouse and human cancers with high mtDNA mutant heteroplasmy to immune checkpoint blockade. Strikingly, patient lesions bearing >50% mtDNA mutation load demonstrated a >2.5-fold improved response rate to checkpoint inhibitor blockade. Taken together these data nominate mtDNA mutations as functional regulators of cancer metabolism and tumour biology, with potential for therapeutic exploitation and treatment stratification.
Project description:Immune checkpoint blockade (ICB) therapy provides remarkable clinical gains, where melanoma is at the forefront of its success. However, only a subset of patients with advanced tumors currently benefit from these therapies, which at times incur considerable side-effects and costs. Constructing such predictors of patient’s response has remained a serious challenge due to the complexity of the immune response and the shortage of large ICB-treated patient cohorts including both omics and response data. Here we build IMPRES, a predictor of ICB-response in melanoma which encompasses 15 pairwise transcriptomics relations between immune checkpoint genes. It is based on two key conjectures: (a) immune mechanisms underlining spontaneous regression in neuroblastoma can predict ICB response in melanoma, and (b) key immune interactions can be captured via specific pairwise relations of immune checkpoint genes’ expression. IMPRES is validated on 9 published datasets1–6 and on a newly generated dataset of 31 tumor samples treated with anti-PD-1 and 10 tumor samples treated with anti-CTLA-4 (some of these are treated with both antibodies), spanning 297 samples in total. It achieves an overall accuracy of AUC=0.83, outperforming existing predictors, capturing almost all true responders while misclassifying less than half of the non-responders. Future studies are warranted to determine the value of the approach presented here in other cancer types.