ORCID Profile
0000-0002-4299-3018
Current Organisations
UCL Cancer Institute
,
Royal College of Physicians
,
The Francis Crick Institute
,
Cancer Research UK
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Publisher: Springer Science and Business Media LLC
Date: 23-12-2021
DOI: 10.1038/S41559-021-01586-X
Abstract: Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal ersification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal ersification, enabling interpretation of clonal ersity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and micro ersity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal ersification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283213
Abstract: S. Table 1: List of PEACE Consortium members. S. Table 2: S le database used for the study for Panel, Exome and RNASeq s les. S. Table 3: Overview of lines of treatment given to each patient. S. Table 4: Lesions and patients included in the lesion-level response to ICI analysis. S. Table 5: Hallmark genesets significantly upregulated in normal tissue vs tumor tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 6: Hallmark genesets significantly upregulated in tumor tissue vs normal tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 7: Genes included in the target panel. S. Table 8: Tree topology comparisons between manually constructed trees and pairtree-constructed trees.
Publisher: Springer Science and Business Media LLC
Date: 03-2019
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283216
Abstract: Supplementary figure 1: Cohort overview. Number of s les sequenced with whole exome, panel or whole RNA sequencing. Supplementary figure 2: Phylogeny and WGD events in CRUKP1047. Supplementary figure 3: Ploidy and SCNA burden. Supplementary figure 4: Overview of each case. Supplementary figure 5: MEDICC2 copy number s le trees. Supplementary figure 6: MEDICC tree of all exome s les demonstrating that s les cluster together by patient, and not by melanoma subtype. Supplementary figure 7: SCNA frequency of cutaneous (a), acral (b) and melanoma of unknown primary (MUP, c). Supplementary figure 8: Correlation between liver copy number distance to other sites and time of emergence after stage IV diagnosis. Supplementary figure 9: Examination of tumour heterogeneity of alterations to antigen-presentation machinery genes,with site and patient annotation. Supplementary figure 10: Boxplots indicating the proportion of losses in the cohort for each segment. Supplementary figure 11: Balance of expression between nonsynonymous mutations that were not predicted to be neoantigens and clonal predicted neoantigens. Supplementary figure 12: Barplot of TIL infiltration score frequencies, determined by pathologist assessment of histology, across all s les. Supplementary figure 13: Number of s les per patient that are classified as either none-low in terms of TILs or moderate-heavy. Supplementary figure 14: Histogram of purity for s les with RNA-seq data. Supplementary figure 15: TME deconvolution. Supplementary figure 16: The effect of metastatic site on transcriptional profiles. Supplementary figure 17: Association of PHF3 copy number with expression. Supplementary figure 18: Overview of gene fusions identified in RNA-seq data. Supplementary figure 19: Comparison of ploidy estimates from panel sequencing data, exome data and FISH. Supplementary figure 20: Comparison of ploidy estimates in panel, exome, FISH and single cell data. Supplementary figure 21: FACs sort plot for CRUKP2567 diaphragmatic metastasis. Supplementary figure 22: Ploidy and wGII values from single cell sequencing of FACS-sorted tumour cells. Supplementary figure 23: Copy number profiles on chromosome 5 for bulk s les from primary and DI_2_R2, a diaphragmatic metastasis. Supplementary figure 24: Histogram of purity of s les for which RNA-seq was performed faceted by patient. Supplementary figure 25: Histogram of purity of s les for which RNA-seq was performed faceted by tissue site.
Publisher: Springer Science and Business Media LLC
Date: 10-09-2020
DOI: 10.1038/S41467-020-18372-1
Abstract: Evasion of programmed cell death represents a critical form of oncogene addiction in cancer cells. Understanding the molecular mechanisms underpinning cancer cell survival despite the oncogenic stress could provide a molecular basis for potential therapeutic interventions. Here we explore the role of pro-survival genes in cancer cell integrity during clonal evolution in non-small cell lung cancer (NSCLC). We identify gains of MCL-1 at high frequency in multiple independent NSCLC cohorts, occurring both clonally and subclonally. Clonal loss of functional TP53 is significantly associated with subclonal gains of MCL-1 . In mice, tumour progression is delayed upon pharmacologic or genetic inhibition of MCL-1. These findings reveal that MCL-1 gains occur with high frequency in lung adenocarcinoma and can be targeted therapeutically.
Publisher: American Association for Cancer Research (AACR)
Date: 16-05-2023
DOI: 10.1158/2159-8290.22841335.V1
Abstract: Supplementary figure 1: Cohort overview. Number of s les sequenced with whole exome, panel or whole RNA sequencing. Supplementary figure 2: Phylogeny and WGD events in CRUKP1047. Supplementary figure 3: Ploidy and SCNA burden. Supplementary figure 4: Overview of each case. Supplementary figure 5: MEDICC2 copy number s le trees. Supplementary figure 6: MEDICC tree of all exome s les demonstrating that s les cluster together by patient, and not by melanoma subtype. Supplementary figure 7: SCNA frequency of cutaneous (a), acral (b) and melanoma of unknown primary (MUP, c). Supplementary figure 8: Correlation between liver copy number distance to other sites and time of emergence after stage IV diagnosis. Supplementary figure 9: Examination of tumour heterogeneity of alterations to antigen-presentation machinery genes, with site and patient annotation. Supplementary figure 10: Boxplots indicating the proportion of losses in the cohort for each segment. Supplementary figure 11: Balance of expression between nonsynonymous mutations that were not predicted to be neoantigens and clonal predicted neoantigens. Supplementary figure 12: Barplot of TIL infiltration score frequencies, determined by pathologist assessment of histology, across all s les. Supplementary figure 13: Number of s les per patient that are classified as either none-low in terms of TILs or moderate-heavy. Supplementary figure 14: Histogram of purity for s les with RNA-seq data. Supplementary figure 15: TME deconvolution. Supplementary figure 16: The effect of metastatic site on transcriptional profiles. Supplementary figure 17: Association of PHF3 copy number with expression. Supplementary figure 18: Overview of gene fusions identified in RNA-seq data. Supplementary figure 19: Comparison of ploidy estimates from panel sequencing data, exome data and FISH. Supplementary figure 20: Comparison of ploidy estimates in panel, exome, FISH and single cell data. Supplementary figure 21: FACs sort plot for CRUKP2567 diaphragmatic metastasis. Supplementary figure 22: Ploidy and wGII values from single cell sequencing of FACS-sorted tumour cells. Supplementary figure 23: Copy number profiles on chromosome 5 for bulk s les from primary and DI_2_R2, a diaphragmatic metastasis. Supplementary figure 24: Histogram of purity of s les for which RNA-seq was performed faceted by patient. Supplementary figure 25: Histogram of purity of s les for which RNA-seq was performed faceted by tissue site.
Publisher: Elsevier BV
Date: 04-2018
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283237.V1
Abstract: Driver mutations and SCNA overview. b A, /b Genomic landscape of the cohort, illustrating mutations in key melanoma driver genes, TMB (total mutations/Mb), ploidy, WGD status, weighted genome instability index (wGII, an SCNA burden metric), and the anatomic site of each s le. “Multi-variant” indicates the presence of more than one variant in the same gene within one s le. Panel and WES s les are included. AD, adrenal BR, brain LI, liver LMS, leptomeninges LN, lymph node LU, lung PE, peritoneum PR, primary ST, soft tissue. b B, /b The proportion of the genome altered by copy-number gains and losses per s le in diploid and WGD tumor s les. b C, /b The frequency of copy-number gains and losses along the genome (based on WES data only). Dark red and blue indicate clonal events, and light red and blue indicate subclonal events. Also shown are frequency of clonal and subclonal LOH and AI.
Publisher: Springer Science and Business Media LLC
Date: 29-05-2023
Publisher: Springer Science and Business Media LLC
Date: 22-05-2020
DOI: 10.1038/S43018-020-0066-Y
Abstract: Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours, and whether this affects patient outcomes is unknown. Here we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets, with significant phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC.
Publisher: Springer Science and Business Media LLC
Date: 24-11-2017
DOI: 10.1038/S41467-017-02002-4
Abstract: Mutations in PIK3CA are very frequent in cancer and lead to sustained PI3K pathway activation. The impact of acute expression of mutant PIK3CA during early stages of malignancy is unknown. Using a mouse model to activate the Pik3ca H1047R hotspot mutation in the heterozygous state from its endogenous locus, we here report that mutant Pik3ca induces centrosome lification in cultured cells (through a pathway involving AKT, ROCK and CDK2/Cyclin E-nucleophosmin) and in mouse tissues, and increased in vitro cellular tolerance to spontaneous genome doubling. We also present evidence that the majority of PIK3CA H1047R mutations in the TCGA breast cancer cohort precede genome doubling. These previously unappreciated roles of PIK3CA mutation show that PI3K signalling can contribute to the generation of irreversible genomic changes in cancer. While this can limit the impact of PI3K-targeted therapies, these findings also open the opportunity for therapeutic approaches aimed at limiting tumour heterogeneity and evolution.
Publisher: Elsevier BV
Date: 04-2018
Publisher: Springer Science and Business Media LLC
Date: 27-10-2021
DOI: 10.1038/S43018-021-00274-W
Abstract: Coronavirus disease 2019 (COVID-19) antiviral response in a pan-tumor immune monitoring (CAPTURE) ( NCT03226886 ) is a prospective cohort study of COVID-19 immunity in patients with cancer. Here we evaluated 585 patients following administration of two doses of BNT162b2 or AZD1222 vaccines, administered 12 weeks apart. Seroconversion rates after two doses were 85% and 59% in patients with solid and hematological malignancies, respectively. A lower proportion of patients had detectable titers of neutralizing antibodies (NAbT) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) versus wild-type (WT) SARS-CoV-2. Patients with hematological malignancies were more likely to have undetectable NAbT and had lower median NAbT than those with solid cancers against both SARS-CoV-2 WT and VOC. By comparison with in iduals without cancer, patients with hematological, but not solid, malignancies had reduced neutralizing antibody (NAb) responses. Seroconversion showed poor concordance with NAbT against VOC. Previous SARS-CoV-2 infection boosted the NAb response including against VOC, and anti-CD20 treatment was associated with undetectable NAbT. Vaccine-induced T cell responses were detected in 80% of patients and were comparable between vaccines or cancer types. Our results have implications for the management of patients with cancer during the ongoing COVID-19 pandemic.
Publisher: Research Square Platform LLC
Date: 20-04-2021
DOI: 10.21203/RS.3.RS-432815/V1
Abstract: Tissue-resident memory T cells (TRM) provide immune defence against local infection and can inhibit cancer progression. However, it is unclear to what extent chronic inflammation impacts TRM activation and how the immune pressure exerted by TRM affects developing tumours in humans. We performed deep profiling of lung cancers arising in never-smokers (NS) and ever-smokers (ES), finding evidence of enhanced TRM immunosurveillance in ES lung. Only tumours arising in ES patients underwent clonal immune escape, even when evaluating cancers with similar tumour mutational burden to NS patients, suggesting that the timing of immune pressure exerted by TRM is a critical factor in the evolution of tumour immune evasion. Tumours grown in T cell quiescent NS lungs displayed little evidence of immune evasion and had fewer neoantigens with low ersity, paradoxically making them amenable to treatment with agonist of the costimulatory molecule, ICOS. These data demonstrate local environmental insults enhance TRM immunosurveillance of human tissue, shape the evolution of tumour immunogenicity and that this interplay informs effective immunotherapeutic modalities.
Publisher: Springer Science and Business Media LLC
Date: 09-2014
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283228
Abstract: Mechanisms of resistance to therapy. b A, /b i KIT /i copy number vs. KIT expression in matching exome and RNA-seq s les. TPM, transcripts per million. b B, /b Hierarchical clustering tree of SCNAs found in the single cells of a representative s le of CRUKP9359. Bars on the right show the copy number of i KIT /i in each cell. b C, /b Diagram of split reads mapping at the edges of the lified region, from which a circular structure can be inferred. Created with a href="BioRender.com" target="_blank" BioRender.com /a . b D, /b Images showing FISH probes against i KIT /i (red) in in idual cells. b E, /b Heat map of alterations in antigen-presentation genes in the exome data. Each column represents a s le. LOH events are shown in red and blue, and nonsynonymous mutations are in red and purple. Bars on the i x /i -axis show the number of genes altered in each s le, whereas i y /i -axis bars show the number of s les altered per gene, colored by the type of event.
Publisher: Springer Science and Business Media LLC
Date: 10-04-2017
DOI: 10.1038/NG.3838
Publisher: American Association for Cancer Research (AACR)
Date: 29-05-2014
DOI: 10.1158/0008-5472.CAN-13-3375
Abstract: Gene signatures have failed to predict responses to breast cancer therapy in patients to date. In this study, we used bioinformatic methods to explore the hypothesis that the existence of multiple drug resistance mechanisms in different patients may limit the power of gene signatures to predict responses to therapy. In addition, we explored whether substratification of resistant cases could improve performance. Gene expression profiles from 1,550 breast cancers analyzed with the same microarray platform were retrieved from publicly available sources. Gene expression changes were introduced in cases defined as sensitive or resistant to a hypothetical therapy. In the resistant group, up to five different mechanisms of drug resistance causing distinct or overlapping gene expression changes were generated bioinformatically, and their impact on sensitivity, specificity, and predictive values of the signatures was investigated. We found that increasing the number of resistance mechanisms corresponding to different gene expression changes weakened the performance of the predictive signatures generated, even if the resistance-induced changes in gene expression were sufficiently strong and informative. Performance was also affected by cohort composition and the proportion of sensitive versus resistant cases or resistant cases that were mechanistically distinct. It was possible to improve response prediction by substratifying chemotherapy-resistant cases from actual datasets (non-bioinformatically perturbed datasets) and by using outliers to model multiple resistance mechanisms. Our work supports the hypothesis that the presence of multiple resistance mechanisms in a given therapy in patients limits the ability of gene signatures to make clinically useful predictions. Cancer Res 74(11) 2946–61. ©2014 AACR.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283228.V1
Abstract: Mechanisms of resistance to therapy. b A, /b i KIT /i copy number vs. KIT expression in matching exome and RNA-seq s les. TPM, transcripts per million. b B, /b Hierarchical clustering tree of SCNAs found in the single cells of a representative s le of CRUKP9359. Bars on the right show the copy number of i KIT /i in each cell. b C, /b Diagram of split reads mapping at the edges of the lified region, from which a circular structure can be inferred. Created with a href="BioRender.com" target="_blank" BioRender.com /a . b D, /b Images showing FISH probes against i KIT /i (red) in in idual cells. b E, /b Heat map of alterations in antigen-presentation genes in the exome data. Each column represents a s le. LOH events are shown in red and blue, and nonsynonymous mutations are in red and purple. Bars on the i x /i -axis show the number of genes altered in each s le, whereas i y /i -axis bars show the number of s les altered per gene, colored by the type of event.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283225
Abstract: Tissue-level lifications and deletions associated with response to ICI. A large proportion of s les underwent WGD ( b A /b ), with successive WGD events associated with increasing wGII ( b B /b ). Letters in brackets indicate melanoma subtype: A = acral, C = cutaneous, M = mucosal, U = melanoma of unknown primary. ***, i P /i 0.001. GISTIC permutation analysis ( b C /b ) associated i MYC /i lification (chromosome 8q) with a nonresponsive phenotype, as well as chromosome 1 lification with a responsive phenotype. Horizontal black dashed lines in top two panels of b C /b indicate significance ( i P /i 0.05). NR, nonresponse R, response. b D, /b Significant lifications on chromosomes 1 and 8 from b C /b with COSMIC genes labeled.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Springer Science and Business Media LLC
Date: 27-10-2021
DOI: 10.1038/S43018-021-00275-9
Abstract: Patients with cancer have higher COVID-19 morbidity and mortality. Here we present the prospective CAPTURE study, integrating longitudinal immune profiling with clinical annotation. Of 357 patients with cancer, 118 were SARS-CoV-2 positive, 94 were symptomatic and 2 died of COVID-19. In this cohort, 83% patients had S1-reactive antibodies and 82% had neutralizing antibodies against wild type SARS-CoV-2, whereas neutralizing antibody titers against the Alpha, Beta and Delta variants were substantially reduced. S1-reactive antibody levels decreased in 13% of patients, whereas neutralizing antibody titers remained stable for up to 329 days. Patients also had detectable SARS-CoV-2-specific T cells and CD4 + responses correlating with S1-reactive antibody levels, although patients with hematological malignancies had impaired immune responses that were disease and treatment specific, but presented compensatory cellular responses, further supported by clinical recovery in all but one patient. Overall, these findings advance the understanding of the nature and duration of the immune response to SARS-CoV-2 in patients with cancer.
Publisher: Elsevier BV
Date: 08-2017
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283234.V1
Abstract: b A, /b Phylogenies inferred for the 14 patients. Only WES s les are included. Letters in brackets indicate melanoma subtype: A = acral, C = cutaneous, M = mucosal, U = melanoma of unknown primary. Branch length is proportional to the number of mutations. Branch colors represent the mutational signatures of the mutations. For clarity, only the most common mutational signatures are shown the remainder are categorized as “unknown.” Scale bars indicate the number of mutations. The legend includes etiologies for each signature ( a href="#bib24" target="_blank" /a ). MMR, mismatch repair. b B, /b Boxplots indicate the ratio of subclonal mutations (length of branches) to clonal mutations (length of the trunk) by subtype and chemotherapy status. Values smaller than zero indicate the dominance of truncal mutations. Mann–Whitney i U /i test was used for statistical comparisons (**, i P /i 0.01 ***, i P /i 0.001). Cut., cutaneous mut., mutation.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283222
Abstract: Identification of a likely non–whole-genome–doubled clone that was not identifiable from bulk sequencing data in CRUKP2567. Clonal phylogeny of CRUKP2567 ( b A /b ), with anatomic diagram b (B) /b based on bulk SNVs mapping s les to clones on the tree. The scale indicates the number of mutations. b C, /b MEDICC2 copy-number tree for bulk exome s les from CRUKP2567. The cluster highlighted in blue has undergone one WGD event, while the other nonhighlighted cluster, containing brain metastasis and primary tumor s les, has not. Diamonds indicate the s les for which bulk copy-number profiles are displayed in Supplementary Fig. S23. b D, /b Hierarchical clustering tree containing all single cells (SS) from FACs-high-ploidy sorting (FH) and FACs-low-ploidy sorting (FL), as well as WGD bulk s les and non-WGD bulk s les. b E, /b Radiologic images of the patient indicating thorax upon initiation of stage IV disease and complete extracranial response to BRAF inhibitor, followed by rapid recolonization of the thorax with resistant clones (left to right). BR, brain BRAFi, BRAF inhibitor CR, complete response DI, diaphragm LN, lymph node LU, lung MEKi, MEK inhibitor PC, pericardium, PLFa, pleural fluid (archival) PR, primary.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283213.V1
Abstract: S. Table 1: List of PEACE Consortium members. S. Table 2: S le database used for the study for Panel, Exome and RNASeq s les. S. Table 3: Overview of lines of treatment given to each patient. S. Table 4: Lesions and patients included in the lesion-level response to ICI analysis. S. Table 5: Hallmark genesets significantly upregulated in normal tissue vs tumor tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 6: Hallmark genesets significantly upregulated in tumor tissue vs normal tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 7: Genes included in the target panel. S. Table 8: Tree topology comparisons between manually constructed trees and pairtree-constructed trees.
Publisher: Elsevier BV
Date: 02-2022
Publisher: American Association for Cancer Research (AACR)
Date: 16-05-2023
DOI: 10.1158/2159-8290.22841332.V1
Abstract: S. Table 1: List of PEACE Consortium members. S. Table 2: S le database used for the study for Panel, Exome and RNASeq s les. S. Table 3: Overview of lines of treatment given to each patient. S. Table 4: Lesions and patients included in the lesion-level response to ICI analysis. S. Table 5: Hallmark genesets significantly upregulated in normal tissue vs tumor tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 6: Hallmark genesets significantly upregulated in tumor tissue vs normal tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 7: Genes included in the target panel. S. Table 8: Tree topology comparisons between manually constructed trees and pairtree-constructed trees.
Publisher: Proceedings of the National Academy of Sciences
Date: 26-05-2009
Abstract: Microtubule-stabilizing (MTS) agents, such as taxanes, are important chemotherapeutics with a poorly understood mechanism of action. We identified a set of genes repressed in multiple cell lines in response to MTS agents and observed that these genes are overexpressed in tumors exhibiting chromosomal instability (CIN). Silencing 22/50 of these genes, many of which are involved in DNA repair, caused cancer cell death, suggesting that these genes are involved in the survival of aneuploid cells. Overexpression of these “CIN-survival” genes is associated with poor outcome in estrogen receptor–positive breast cancer and occurs frequently in basal-like and Her2-positive cases. In diploid cells, but not in chromosomally unstable cells, paclitaxel causes repression of CIN-survival genes, followed by cell death. In the OV01 ovarian cancer clinical trial, a high level of CIN was associated with taxane resistance but carboplatin sensitivity, indicating that CIN may determine MTS response in vivo. Thus, pretherapeutic assessment of CIN may optimize treatment stratification and clinical trial design using these agents.
Publisher: American Association for Cancer Research (AACR)
Date: 28-03-2023
DOI: 10.1158/2159-8290.CD-22-1427
Abstract: Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense s ling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. See related commentary by Shain, p. 1294. This article is highlighted in the In This Issue feature, p. 1275
Publisher: American Association for Cancer Research (AACR)
Date: 02-2014
DOI: 10.1158/2159-8290.CD-13-0285
Abstract: The contribution of whole-genome doubling to chromosomal instability (CIN) and tumor evolution is unclear. We use long-term culture of isogenic tetraploid cells from a stable diploid colon cancer progenitor to investigate how a genome-doubling event affects genome stability over time. Rare cells that survive genome doubling demonstrate increased tolerance to chromosome aberrations. Tetraploid cells do not exhibit increased frequencies of structural or numerical CIN per chromosome. However, the tolerant phenotype in tetraploid cells, coupled with a doubling of chromosome aberrations per cell, allows chromosome abnormalities to evolve specifically in tetraploids, recapitulating chromosomal changes in genomically complex colorectal tumors. Finally, a genome-doubling event is independently predictive of poor relapse-free survival in early-stage disease in two independent cohorts in multivariate analyses [discovery data: hazard ratio (HR), 4.70, 95% confidence interval (CI), 1.04–21.37 validation data: HR, 1.59, 95% CI, 1.05–2.42]. These data highlight an important role for the tolerance of genome doubling in driving cancer genome evolution. Significance: Our work sheds light on the importance of whole-genome–doubling events in colorectal cancer evolution. We show that tetraploid cells undergo rapid genomic changes and recapitulate the genetic alterations seen in chromosomally unstable tumors. Furthermore, we demonstrate that a genome-doubling event is prognostic of poor relapse-free survival in this disease type. Cancer Discov 4(2) 175–85. ©2014 AACR. This article is highlighted in the In This Issue feature, p. 131
Publisher: Springer Science and Business Media LLC
Date: 13-06-2022
DOI: 10.1038/S41587-022-01342-X
Abstract: Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283237
Abstract: Driver mutations and SCNA overview. b A, /b Genomic landscape of the cohort, illustrating mutations in key melanoma driver genes, TMB (total mutations/Mb), ploidy, WGD status, weighted genome instability index (wGII, an SCNA burden metric), and the anatomic site of each s le. “Multi-variant” indicates the presence of more than one variant in the same gene within one s le. Panel and WES s les are included. AD, adrenal BR, brain LI, liver LMS, leptomeninges LN, lymph node LU, lung PE, peritoneum PR, primary ST, soft tissue. b B, /b The proportion of the genome altered by copy-number gains and losses per s le in diploid and WGD tumor s les. b C, /b The frequency of copy-number gains and losses along the genome (based on WES data only). Dark red and blue indicate clonal events, and light red and blue indicate subclonal events. Also shown are frequency of clonal and subclonal LOH and AI.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283231
Abstract: Late-emerging brain metastases have a lower copy-number burden. b A, /b wGII per metastatic site. Site-specific null distributions of mean wGII were generated by randomizing s le sets (from any metastatic site) while keeping patient contributions constant (see Methods). **, i P /i ≤ 0.01. Leptomen., leptomeninges. b B, /b Correlation between brain copy-number (CN) distance to other sites and time of emergence of brain metastases after stage IV diagnosis in days. b C, /b Growth dynamics of tumors in patient CRUKP5107. The brain lesion (in orange) was detected in only the last two scans after the targeted therapy [BRAF inhibitor (i) + MEKi], ICI (PD-1i + CTLA4i), and chemotherapy courses. PD, progressive disease PR, partial response SD, stable disease. b D, /b SNV and indel phylogenetic tree of tumor clones in patient CRUKP5107. b E, /b The mutational signature contributions to each clone in the phylogeny in b D /b are shown. MMR, mismatch repair. b F, /b The anatomic distribution of clones. Each pie chart represents a s le with its clonal composition indicated by the colors. A multiregional s ling of the same tumor is indicated by the gray dashed lines. BR, brain LI, liver LU, lung PC, pericardium ST, soft tissue.
Publisher: Springer Science and Business Media LLC
Date: 14-04-2020
DOI: 10.1038/S41467-020-15615-Z
Abstract: Continuous cancer growth is driven by subsets of self-renewing malignant cells. Targeting of uncontrolled self-renewal through inhibition of stem cell-related signaling pathways has proven challenging. Here, we show that cancer cells can be selectively deprived of self-renewal ability by interfering with their epigenetic state. Re-expression of histone H1.0, a tumor-suppressive factor that inhibits cancer cell self-renewal in many cancer types, can be broadly induced by the clinically well-tolerated compound Quisinostat. Through H1.0, Quisinostat inhibits cancer cell self-renewal and halts tumor maintenance without affecting normal stem cell function. Quisinostat also hinders expansion of cells surviving targeted therapy, independently of the cancer types and the resistance mechanism, and inhibits disease relapse in mouse models of lung cancer. Our results identify H1.0 as a major mediator of Quisinostat’s antitumor effect and suggest that sequential administration of targeted therapy and Quisinostat may be a broadly applicable strategy to induce a prolonged response in patients.
Publisher: Elsevier BV
Date: 11-2021
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283234
Abstract: b A, /b Phylogenies inferred for the 14 patients. Only WES s les are included. Letters in brackets indicate melanoma subtype: A = acral, C = cutaneous, M = mucosal, U = melanoma of unknown primary. Branch length is proportional to the number of mutations. Branch colors represent the mutational signatures of the mutations. For clarity, only the most common mutational signatures are shown the remainder are categorized as “unknown.” Scale bars indicate the number of mutations. The legend includes etiologies for each signature ( a href="#bib24" target="_blank" /a ). MMR, mismatch repair. b B, /b Boxplots indicate the ratio of subclonal mutations (length of branches) to clonal mutations (length of the trunk) by subtype and chemotherapy status. Values smaller than zero indicate the dominance of truncal mutations. Mann–Whitney i U /i test was used for statistical comparisons (**, i P /i 0.01 ***, i P /i 0.001). Cut., cutaneous mut., mutation.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283231.V1
Abstract: Late-emerging brain metastases have a lower copy-number burden. b A, /b wGII per metastatic site. Site-specific null distributions of mean wGII were generated by randomizing s le sets (from any metastatic site) while keeping patient contributions constant (see Methods). **, i P /i ≤ 0.01. Leptomen., leptomeninges. b B, /b Correlation between brain copy-number (CN) distance to other sites and time of emergence of brain metastases after stage IV diagnosis in days. b C, /b Growth dynamics of tumors in patient CRUKP5107. The brain lesion (in orange) was detected in only the last two scans after the targeted therapy [BRAF inhibitor (i) + MEKi], ICI (PD-1i + CTLA4i), and chemotherapy courses. PD, progressive disease PR, partial response SD, stable disease. b D, /b SNV and indel phylogenetic tree of tumor clones in patient CRUKP5107. b E, /b The mutational signature contributions to each clone in the phylogeny in b D /b are shown. MMR, mismatch repair. b F, /b The anatomic distribution of clones. Each pie chart represents a s le with its clonal composition indicated by the colors. A multiregional s ling of the same tumor is indicated by the gray dashed lines. BR, brain LI, liver LU, lung PC, pericardium ST, soft tissue.
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.C.6649132.V2
Abstract: Abstract Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing s les from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery. We found i KIT /i extrachromosomal DNA may have contributed to the lack of response to KIT inhibitors of a KIT-driven melanoma. At the lesion-level, i MYC /i lifications were enriched in ICI nonresponders. Single-cell sequencing revealed polyclonal seeding of metastases originating from clones with different ploidy in one patient. Finally, we observed that brain metastases that erged early in molecular evolution emerge late in disease. Overall, our study illustrates the erse evolutionary landscape of advanced melanoma. Significance: Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense s ling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. i a href="ancerdiscovery/article/doi/10.1158/2159-8290.CD-23-0340" target="_blank" See related commentary by Shain, p. 1294. /a /i i a href="ancerdiscovery/article/doi/10.1158/2159-8290.CD-13-6-ITI" target="_blank" This article is highlighted in the In This Issue feature, p. 1275 /a /i /
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283216.V1
Abstract: Supplementary figure 1: Cohort overview. Number of s les sequenced with whole exome, panel or whole RNA sequencing. Supplementary figure 2: Phylogeny and WGD events in CRUKP1047. Supplementary figure 3: Ploidy and SCNA burden. Supplementary figure 4: Overview of each case. Supplementary figure 5: MEDICC2 copy number s le trees. Supplementary figure 6: MEDICC tree of all exome s les demonstrating that s les cluster together by patient, and not by melanoma subtype. Supplementary figure 7: SCNA frequency of cutaneous (a), acral (b) and melanoma of unknown primary (MUP, c). Supplementary figure 8: Correlation between liver copy number distance to other sites and time of emergence after stage IV diagnosis. Supplementary figure 9: Examination of tumour heterogeneity of alterations to antigen-presentation machinery genes,with site and patient annotation. Supplementary figure 10: Boxplots indicating the proportion of losses in the cohort for each segment. Supplementary figure 11: Balance of expression between nonsynonymous mutations that were not predicted to be neoantigens and clonal predicted neoantigens. Supplementary figure 12: Barplot of TIL infiltration score frequencies, determined by pathologist assessment of histology, across all s les. Supplementary figure 13: Number of s les per patient that are classified as either none-low in terms of TILs or moderate-heavy. Supplementary figure 14: Histogram of purity for s les with RNA-seq data. Supplementary figure 15: TME deconvolution. Supplementary figure 16: The effect of metastatic site on transcriptional profiles. Supplementary figure 17: Association of PHF3 copy number with expression. Supplementary figure 18: Overview of gene fusions identified in RNA-seq data. Supplementary figure 19: Comparison of ploidy estimates from panel sequencing data, exome data and FISH. Supplementary figure 20: Comparison of ploidy estimates in panel, exome, FISH and single cell data. Supplementary figure 21: FACs sort plot for CRUKP2567 diaphragmatic metastasis. Supplementary figure 22: Ploidy and wGII values from single cell sequencing of FACS-sorted tumour cells. Supplementary figure 23: Copy number profiles on chromosome 5 for bulk s les from primary and DI_2_R2, a diaphragmatic metastasis. Supplementary figure 24: Histogram of purity of s les for which RNA-seq was performed faceted by patient. Supplementary figure 25: Histogram of purity of s les for which RNA-seq was performed faceted by tissue site.
Publisher: Springer Science and Business Media LLC
Date: 17-05-2021
Publisher: American Association for Cancer Research (AACR)
Date: 16-05-2023
DOI: 10.1158/2159-8290.C.6649132.V1
Abstract: Abstract Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing s les from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery. We found i KIT /i extrachromosomal DNA may have contributed to the lack of response to KIT inhibitors of a KIT-driven melanoma. At the lesion-level, i MYC /i lifications were enriched in ICI nonresponders. Single-cell sequencing revealed polyclonal seeding of metastases originating from clones with different ploidy in one patient. Finally, we observed that brain metastases that erged early in molecular evolution emerge late in disease. Overall, our study illustrates the erse evolutionary landscape of advanced melanoma. Significance: Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense s ling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. /
Publisher: Springer Science and Business Media LLC
Date: 04-05-2020
DOI: 10.1038/S41467-020-15768-X
Abstract: While most testicular germ cell tumours (TGCTs) exhibit exquisite sensitivity to platinum chemotherapy, ~10% are platinum resistant. To gain insight into the underlying mechanisms, we undertake whole exome sequencing and copy number analysis in 40 tumours from 26 cases with platinum-resistant TGCT, and combine this with published genomic data on an additional 624 TGCTs. We integrate analyses for driver mutations, mutational burden, global, arm-level and focal copy number (CN) events, and SNV and CN signatures. Albeit preliminary and observational in nature, these analyses provide support for a possible mechanistic link between early driver mutations in RAS and KIT and the widespread copy number events by which TGCT is characterised.
Publisher: Elsevier BV
Date: 04-2017
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283225.V1
Abstract: Tissue-level lifications and deletions associated with response to ICI. A large proportion of s les underwent WGD ( b A /b ), with successive WGD events associated with increasing wGII ( b B /b ). Letters in brackets indicate melanoma subtype: A = acral, C = cutaneous, M = mucosal, U = melanoma of unknown primary. ***, i P /i 0.001. GISTIC permutation analysis ( b C /b ) associated i MYC /i lification (chromosome 8q) with a nonresponsive phenotype, as well as chromosome 1 lification with a responsive phenotype. Horizontal black dashed lines in top two panels of b C /b indicate significance ( i P /i 0.05). NR, nonresponse R, response. b D, /b Significant lifications on chromosomes 1 and 8 from b C /b with COSMIC genes labeled.
Publisher: Elsevier BV
Date: 03-2013
Publisher: Elsevier BV
Date: 04-2021
Publisher: Public Library of Science (PLoS)
Date: 27-12-2016
Publisher: Informa UK Limited
Date: 04-2012
DOI: 10.4161/AUTO.19496
Publisher: American Association for Cancer Research (AACR)
Date: 16-05-2023
DOI: 10.1158/2159-8290.22841335
Abstract: Supplementary figure 1: Cohort overview. Number of s les sequenced with whole exome, panel or whole RNA sequencing. Supplementary figure 2: Phylogeny and WGD events in CRUKP1047. Supplementary figure 3: Ploidy and SCNA burden. Supplementary figure 4: Overview of each case. Supplementary figure 5: MEDICC2 copy number s le trees. Supplementary figure 6: MEDICC tree of all exome s les demonstrating that s les cluster together by patient, and not by melanoma subtype. Supplementary figure 7: SCNA frequency of cutaneous (a), acral (b) and melanoma of unknown primary (MUP, c). Supplementary figure 8: Correlation between liver copy number distance to other sites and time of emergence after stage IV diagnosis. Supplementary figure 9: Examination of tumour heterogeneity of alterations to antigen-presentation machinery genes, with site and patient annotation. Supplementary figure 10: Boxplots indicating the proportion of losses in the cohort for each segment. Supplementary figure 11: Balance of expression between nonsynonymous mutations that were not predicted to be neoantigens and clonal predicted neoantigens. Supplementary figure 12: Barplot of TIL infiltration score frequencies, determined by pathologist assessment of histology, across all s les. Supplementary figure 13: Number of s les per patient that are classified as either none-low in terms of TILs or moderate-heavy. Supplementary figure 14: Histogram of purity for s les with RNA-seq data. Supplementary figure 15: TME deconvolution. Supplementary figure 16: The effect of metastatic site on transcriptional profiles. Supplementary figure 17: Association of PHF3 copy number with expression. Supplementary figure 18: Overview of gene fusions identified in RNA-seq data. Supplementary figure 19: Comparison of ploidy estimates from panel sequencing data, exome data and FISH. Supplementary figure 20: Comparison of ploidy estimates in panel, exome, FISH and single cell data. Supplementary figure 21: FACs sort plot for CRUKP2567 diaphragmatic metastasis. Supplementary figure 22: Ploidy and wGII values from single cell sequencing of FACS-sorted tumour cells. Supplementary figure 23: Copy number profiles on chromosome 5 for bulk s les from primary and DI_2_R2, a diaphragmatic metastasis. Supplementary figure 24: Histogram of purity of s les for which RNA-seq was performed faceted by patient. Supplementary figure 25: Histogram of purity of s les for which RNA-seq was performed faceted by tissue site.
Publisher: Springer Science and Business Media LLC
Date: 02-09-2020
Publisher: American Association for Cancer Research (AACR)
Date: 17-03-2023
DOI: 10.1158/1940-6207.CAPR-22-0469
Abstract: Histologically normal human tissues accumulate significant mutational burden with age. The extent and spectra of mutagenesis are comparable both in rapidly proliferating and post-mitotic tissues and in stem cells compared with their differentiated progeny. Some of these mutations provide increased fitness, giving rise to clones which, at times, can replace the entire surface area of tissues. Compared with cancer, somatic mutations in histologically normal tissues are primarily single-nucleotide variations. Interestingly though, the presence of these mutations and positive clonal selection in isolation remains a poor indicator of potential future cancer transformation in solid tissues. Common clonally expanded mutations in histologically normal tissues also do not always represent the most frequent early mutations in cancers of corresponding tissues, indicating differences in selection pressures. Preliminary evidence implies that stroma and immune system co-evolve with age, which may impact selection dynamics. In this review, we will explore the mutational landscape of histologically normal and premalignant human somatic tissues in detail and discuss cell-intrinsic and environmental factors that can determine the fate of positively selected mutations within them. Precisely pinpointing these determinants of cancer transformation would aid development of early cancer interventional and prevention strategies.
Publisher: Elsevier BV
Date: 04-2018
Publisher: American Association for Cancer Research (AACR)
Date: 16-05-2023
DOI: 10.1158/2159-8290.22841332
Abstract: S. Table 1: List of PEACE Consortium members. S. Table 2: S le database used for the study for Panel, Exome and RNASeq s les. S. Table 3: Overview of lines of treatment given to each patient. S. Table 4: Lesions and patients included in the lesion-level response to ICI analysis. S. Table 5: Hallmark genesets significantly upregulated in normal tissue vs tumor tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 6: Hallmark genesets significantly upregulated in tumor tissue vs normal tissue. Table shows p-values for tissue type, purity T value for tissue type, purity q-value for tissue type, purity (FDR corrected). S. Table 7: Genes included in the target panel. S. Table 8: Tree topology comparisons between manually constructed trees and pairtree-constructed trees.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 11-12-2020
Abstract: Immunological memory after infection with seasonal human coronaviruses (hCoVs) may potentially contribute to cross-protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Ng et al. report that in a cohort of 350 SARS-CoV-2–uninfected in iduals, a small proportion had circulating immunoglobulin G (IgG) antibodies that could cross-react with the S2 subunit of the SARS-CoV-2 spike protein (see the Perspective by Guthmiller and Wilson). By contrast, COVID-19 patients generated IgA, IgG, and IgM antibodies that recognized both the S1 and S2 subunits. The anti-S2 antibodies from SARS-CoV-2–uninfected patients showed specific neutralizing activity against both SARS-CoV-2 and SARS-CoV-2 S pseudotypes. A much higher percentage of SARS-CoV-2–uninfected children and adolescents were positive for these antibodies compared with adults. This pattern may be due to the fact that children and adolescents generally have higher hCoV infection rates and a more erse antibody repertoire, which may explain the age distribution of COVID-19 susceptibility. Science , this issue p. 1339 see also p. 1272
Publisher: American Association for the Advancement of Science (AAAS)
Date: 25-03-2016
Abstract: One contributing factor in antitumor immunity is the repertoire of neoantigens created by genetic mutations within tumor cells. Like the corresponding mutations, these neoantigens show intratumoral heterogeneity. Some are present in all tumor cells (clonal), and others are present in only a fraction of cells (subclonal). In a study of lung cancer and melanoma, McGranahan et al. found that a high burden of clonal tumor neoantigens correlated with improved patient survival, an increased presence of tumor-infiltrating lymphocytes, and a durable response to immunotherapy. Science , this issue p. 1463
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.23283222.V1
Abstract: Identification of a likely non–whole-genome–doubled clone that was not identifiable from bulk sequencing data in CRUKP2567. Clonal phylogeny of CRUKP2567 ( b A /b ), with anatomic diagram b (B) /b based on bulk SNVs mapping s les to clones on the tree. The scale indicates the number of mutations. b C, /b MEDICC2 copy-number tree for bulk exome s les from CRUKP2567. The cluster highlighted in blue has undergone one WGD event, while the other nonhighlighted cluster, containing brain metastasis and primary tumor s les, has not. Diamonds indicate the s les for which bulk copy-number profiles are displayed in Supplementary Fig. S23. b D, /b Hierarchical clustering tree containing all single cells (SS) from FACs-high-ploidy sorting (FH) and FACs-low-ploidy sorting (FL), as well as WGD bulk s les and non-WGD bulk s les. b E, /b Radiologic images of the patient indicating thorax upon initiation of stage IV disease and complete extracranial response to BRAF inhibitor, followed by rapid recolonization of the thorax with resistant clones (left to right). BR, brain BRAFi, BRAF inhibitor CR, complete response DI, diaphragm LN, lymph node LU, lung MEKi, MEK inhibitor PC, pericardium, PLFa, pleural fluid (archival) PR, primary.
Publisher: Elsevier BV
Date: 08-2010
DOI: 10.1016/J.EJCA.2010.03.019
Abstract: Primary or acquired drug resistance remains a fundamental cause of therapeutic failure in cancer therapy. Post-hoc analyses of clinical trials have revealed the importance of selecting patients with the appropriate molecular phenotype for maximal therapeutic benefit, as well as the requirement to avoid exposure and potential harm for those who have drug resistant disease, particularly with respect to targeted agents. Unravelling drug resistance mechanisms not only facilitates rational treatment strategies to overcome existing limitations in therapeutic efficacy, but will enhance biomarker discovery and the development of companion diagnostics. Advances in genomics coupled with state-of-the-art biomarker platforms such as multi-parametric functional imaging and molecular characterisation of circulating tumour cells are expanding the scope of clinical trials - providing unprecedented opportunities for translational objectives that inform on both treatment response and disease biology. In this review, we propose a shift towards innovative trial designs, which are prospectively set up to answer key biological hypotheses in parallel with the RNA interference elucidation of drug resistance pathways in monotherapy pre-operative or 'window of opportunity' early phase trials. Systematic collection of paired clinical s les before and after treatment amenable to genomics analysis in such studies is mandated. With concurrent functional RNA interference analysis of drug response pathways, the identification of robust predictive biomarkers of response and clinically relevant resistance mechanisms may become feasible. This represents a rational approach to accelerate biomarker discovery, maximising the potential for therapeutic benefit and minimising the health economic cost of ineffective therapy.
Publisher: Informa UK Limited
Date: 02-01-2016
Publisher: American Association for Cancer Research (AACR)
Date: 02-06-2023
DOI: 10.1158/2159-8290.C.6649132
Abstract: Abstract Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing s les from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery. We found i KIT /i extrachromosomal DNA may have contributed to the lack of response to KIT inhibitors of a KIT-driven melanoma. At the lesion-level, i MYC /i lifications were enriched in ICI nonresponders. Single-cell sequencing revealed polyclonal seeding of metastases originating from clones with different ploidy in one patient. Finally, we observed that brain metastases that erged early in molecular evolution emerge late in disease. Overall, our study illustrates the erse evolutionary landscape of advanced melanoma. Significance: Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense s ling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. i a href="ancerdiscovery/article/doi/10.1158/2159-8290.CD-23-0340" target="_blank" See related commentary by Shain, p. 1294. /a /i i a href="ancerdiscovery/article/doi/10.1158/2159-8290.CD-13-6-ITI" target="_blank" This article is highlighted in the In This Issue feature, p. 1275 /a /i /
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
Publisher: Cold Spring Harbor Laboratory
Date: 21-04-2021
DOI: 10.1101/2021.04.20.440373
Abstract: Tissue-resident memory T cells (T RM ) provide immune defence against local infection and can inhibit cancer progression. However, it is unclear to what extent chronic inflammation impacts T RM activation and how the immune pressure exerted by T RM affects developing tumours in humans. We performed deep profiling of lung cancers arising in never-smokers (NS) and ever-smokers (ES), finding evidence of enhanced T RM immunosurveillance in ES lung. Only tumours arising in ES patients underwent clonal immune escape, even when evaluating cancers with similar tumour mutational burden to NS patients, suggesting that the timing of immune pressure exerted by T RM is a critical factor in the evolution of tumour immune evasion. Tumours grown in T cell quiescent NS lungs displayed little evidence of immune evasion and had fewer neoantigens with low ersity, paradoxically making them amenable to treatment with agonist of the costimulatory molecule, ICOS. These data demonstrate local environmental insults enhance T RM immunosurveillance of human tissue, shape the evolution of tumour immunogenicity and that this interplay informs effective immunotherapeutic modalities.
Publisher: Springer Science and Business Media LLC
Date: 26-05-2021
DOI: 10.1038/S41591-021-01387-6
Abstract: Patients with cancer are currently prioritized in coronavirus disease 2019 (COVID-19) vaccination programs globally, which includes administration of mRNA vaccines. Cytokine release syndrome (CRS) has not been reported with mRNA vaccines and is an extremely rare immune-related adverse event of immune checkpoint inhibitors. We present a case of CRS that occurred 5 d after vaccination with BTN162b2 (tozinameran)—the Pfizer-BioNTech mRNA COVID-19 vaccine—in a patient with colorectal cancer on long-standing anti-PD-1 monotherapy. The CRS was evidenced by raised inflammatory markers, thrombocytopenia, elevated cytokine levels (IFN-γ/IL-2R/IL-18/IL-16/IL-10) and steroid responsiveness. The close temporal association of vaccination and diagnosis of CRS in this case suggests that CRS was a vaccine-related adverse event with anti-PD1 blockade as a potential contributor. Overall, further prospective pharmacovigillence data are needed in patients with cancer, but the benefit–risk profile remains strongly in favor of COVID-19 vaccination in this population.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Charles Swanton.