ORCID Profile
0000-0001-5877-8657
Current Organisations
Peter MacCallum Cancer Centre
,
RIKEN Center for Integrative Medical Sciences
,
Juntendo University
,
University of Melbourne
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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: Oxford University Press (OUP)
Date: 13-08-2021
DOI: 10.1111/CED.14852
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: Informa UK Limited
Date: 23-01-2019
DOI: 10.1080/14737159.2019.1568873
Abstract: Blood draw or collection of other body fluids, known as 'liquid biopsies' are generally less invasive procedures than tumor biopsies. Cell-free tumor DNA (ctDNA) is widely evaluated in cancer for early detection, diagnosis, prognosis, therapy monitoring or determination of minimal residual disease. In body fluid s les, ctDNA can represent a small fraction of total cell-free DNA (cfDNA), requiring highly sensitive assays. Areas covered: The first part of this review is dedicated to critical preanalytical points necessary to obtain suitable s les for cfDNA analysis. The second part describes the available techniques for ctDNA analysis. Expert commentary: Detection of ctDNA is emerging as a powerful adjunct in the management of patients with cancer. For reliable ctDNA detection, preanalytical steps from s ling to DNA extraction are crucial. Various techniques are available for cfDNA detection, but one needs to consider the appropriate application for the patient's clinical trajectory, whether it is for diagnosis or disease monitoring. Broad screening assays like Next-Generation Sequencing should be used for early cancer detection or for tumor molecular characterization to guide therapy options in a molecular board context. Techniques designed for unique hotspot or well-identified mutations are the most sensitive and should be used for monitoring purposes.
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: Public Library of Science (PLoS)
Date: 06-03-2017
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 08-2021
DOI: 10.1016/J.EJCA.2021.04.045
Abstract: Combination ipilimumab and nivolumab is approved for several malignancies. Toxicity most often occurs 6-10 weeks into treatment. Whether very early toxicity is harder to manage or influences efficacy is unknown. Consecutive metastatic melanoma patients who developed hyperacute toxicity, defined as Grade 2+ irAE within 21 days of receiving ipilimumab + anti-PD-1 were retrospectively identified from nine centres. A total of 82 patients developed hyperacute toxicity (estimated incidence 9%), at a median 10 days (range 1-21). Toxicities included colitis (N = 23), rash (17), hepatitis (9), endocrine (9), pneumonitis (6) and neurotoxicity (4) and were G2 (38%), G3 (52%), G4 (6%) and G5 (2% myocarditis). Fifty-nine percent required treatment beyond oral steroids, including IV steroids (28%), infliximab and other immunosuppression (30%). A total of 29% patients developed an additional hyperacute toxicity and 26% another toxicity >21 days after treatment commencement but before further immunotherapy. The objective response rate (ORR) was 54%, and after a median 11.6 mo follow-up, median PFS was 7.4 mo. Increasing levels of immunosuppression was associated with a reduced PFS (12-month PFS 62% no immunosuppression versus 49% oral steroids versus 33% IV steroids versus 20% further immunosuppressants, p = 0.006). There was no significant difference in ORR or PFS by duration of immunosuppression. Hyperacute toxicities from combination immunotherapy have a wide spectrum and can be severe. Many patients require significant immunosuppression for prolonged durations and remain at risk of further severe toxicity. Melanoma outcomes in such patients appear similar to those of trial populations, although greater immunosuppression requirements may be associated with inferior outcomes.
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: Cold Spring Harbor Laboratory
Date: 07-2020
Abstract: Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2 .
Publisher: Elsevier BV
Date: 04-2018
Publisher: Elsevier BV
Date: 2021
DOI: 10.1016/J.EUF.2019.12.005
Abstract: A erse range of clinical phenotypes are observed in clear-cell renal cell carcinoma (ccRCC) with resultant therapeutic implications. Molecular characterisation underpinning the ersity observed has been qualified, where the near ubiquitous loss of the short arm of chromosome 3 precedes distinct evolutionary trajectories involving different sequences and combinations of genetic events. Primary tumours are characterised by varying degrees of intratumoural heterogeneity and chromosomal complexity associated with distinct metastatic phenotypes. An evolutionary understanding reconciles the erse clinical phenotypes observed in metastatic ccRCC and has the potential to impact patient management. PATIENT SUMMARY: Re-tracing the evolutionary paths taken by clear-cell kidney cancer through analyses at the gene level gives an insight into genetic changes that are correlated to metastatic potential. This may provide a framework to guide therapeutic interventions, especially in identifying candidates for surgical intervention.
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: 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: 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: Ovid Technologies (Wolters Kluwer Health)
Date: 03-2018
DOI: 10.1016/J.IJSU.2018.01.020
Abstract: Adjuvant chemotherapy for Stage II colon cancer offers a small (2-3%) overall survival benefit and is not universally recommended. Mismatch repair deficiency (dMMR) confers an improved prognosis identifying patients unlikely to benefit from adjuvant chemotherapy. The aim of this study was to investigate the use of dMMR immunohistochemistry in two major cancer treatment centres. Prospective data were collected on all patients with resected Stage II colon cancer between 2010 and 2015 across two large Australian hospitals. Data collected included patient demographics, tumour histology, dMMR immunohistochemistry, chemotherapy use, and outcomes. All 355 patients (56.1% female, median age 81) with resected Stage 2 Colon cancer entered on to the surgical database were included in this analysis. MMR testing was performed on 167 patient s les (47%), most occurred post-2013 (73.1% vs. 26.9% patients). dMMR rates were 34.1%. 25 (7.3%) received adjuvant chemotherapy, with no patient >80 years receiving treatment. Presence of ≥2 high-risk feature increased the likelihood of adjuvant chemotherapy. Only 3.6% dMMR patients received chemotherapy both were young with high-risk features. 27/288 (7.6%) patients (with follow up) relapsed, with 7 disease-free post-resection of metastatic disease, 9 are alive with metastatic disease, and 11 deceased. Unlike clinical trial populations, Stage 2 colon cancer patients are often elderly, have high rates of dMMR tumours, are rarely offered chemotherapy, yet still have excellent outcomes. dMMR immunohistochemistry is being increasingly used to identify Stage 2 patients who do not require chemotherapy.
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: 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: Elsevier BV
Date: 03-2023
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: Springer Science and Business Media LLC
Date: 03-2014
DOI: 10.1038/NATURE13182
Publisher: Elsevier BV
Date: 02-2022
Publisher: Informa UK Limited
Date: 26-04-2019
DOI: 10.1080/14656566.2019.1601700
Abstract: Melanoma therapies have evolved rapidly, and initial successes have translated into survival gains for patients with advanced melanoma. Both targeted and immune-therapy now have evidence in earlier stage disease. There are many new agents and combinations of treatments in development as potential future treatment options. This highlights the need for a reflection on current treatment practice trends that are guiding the development of potential new therapies. In this review, the authors discuss the evidence for currently approved therapies for cutaneous melanoma, including adjuvant therapy, potential new biomarkers, and emerging treatments with early phase clinical trial data. The authors have searched both the PubMed and clinicaltrials.gov databases for published clinical trials and discuss selected landmark trials of current therapies and of investigational treatment strategies with early evidence for the treatment of melanoma. Significant efficacy has been demonstrated with both immune checkpoint inhibitors and targeted therapies in treating advanced melanoma. A multitude of novel therapies are in development and there is need for instructive biomarker assessment to identify patients likely to respond or be refractory to current therapies, to identify mechanisms of resistance and to direct further treatment options to patients based on in idual disease biology.
Publisher: Springer Science and Business Media LLC
Date: 12-04-2023
DOI: 10.1038/S41586-023-05771-9
Abstract: B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS) 1,2 . Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive 1,2 . Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma 3 . We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are lified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.
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: American Association for the Advancement of Science (AAAS)
Date: 27-02-2015
Abstract: In order to understand cellular differentiation, it is important to understand the timing of the regulation of gene expression. Arner et al. used cap analysis of gene expression (CAGE) to analyze gene enhancer and promoter activities in a number of human and mouse cell types. The RNA of enhancers was transcribed first, followed by that of transcription factors, and finally by genes that are not transcription factors. Science , this issue p. 1010
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: Elsevier BV
Date: 04-2022
Publisher: Springer Science and Business Media LLC
Date: 29-08-2017
Abstract: In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of s les, consisting of a variety of primary cells, tissues, cell lines, and time series s les during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.
Publisher: Elsevier BV
Date: 2020
Publisher: Public Library of Science (PLoS)
Date: 18-12-2015
Publisher: Elsevier BV
Date: 05-2020
DOI: 10.1016/J.CELREP.2020.107550
Abstract: Although thousands of solid tumors have been sequenced to date, a fundamental under-s ling bias is inherent in current methodologies. This is caused by a tissue s le input of fixed dimensions (e.g., 6 mm biopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue s ling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB but low clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative s ling methodology is used. Rep-Seq offers an improved s ling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure.
Publisher: Springer Science and Business Media LLC
Date: 02-06-2021
DOI: 10.1038/S41467-021-23143-7
Abstract: Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
Publisher: Springer Science and Business Media LLC
Date: 14-05-2019
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: 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: Informa UK Limited
Date: 03-08-2019
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: Elsevier BV
Date: 10-2020
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: Elsevier BV
Date: 10-2022
Publisher: Future Medicine Ltd
Date: 09-2017
Publisher: Public Library of Science (PLoS)
Date: 17-04-2015
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: Wiley
Date: 16-03-2017
DOI: 10.1111/AJCO.12671
Abstract: Current efforts to understand patient management in clinical practice are largely based on clinician surveys with uncertain reliability. The TRACC (Treatment of Recurrent and Advanced Colorectal Cancer) database is a multisite registry collecting comprehensive treatment and outcome data on consecutive metastatic colorectal cancer (mCRC) patients at multiple sites across Australia. This study aims to determine the accuracy of oncologists' impressions of real-word practice by comparing clinicians' estimates to data captured by TRACC. Nineteen medical oncologists from nine hospitals contributing data to TRACC completed a 34-question survey regarding their impression of the management and outcomes of mCRC at their own practice and other hospitals contributing to the database. Responses were then compared with TRACC data to determine how closely their impressions reflected actual practice. Data on 1300 patients with mCRC were available. Median clinician estimated frequency of KRAS testing within 6 months of diagnosis was 80% (range: 20-100%) the TRACC documented rate was 43%. Clinicians generally overestimated the rates of first-line treatment, particularly in patients over 75 years. Estimate for bevacizumab in first line was 60% (35-80%) versus 49% in TRACC. Estimated rate for liver resection varied substantially (5-35%), and the estimated median (27%) was inconsistent with the TRACC rate (12%). Oncologists generally felt their practice was similar to other hospitals. Oncologists' estimates of current clinical practice varied and were discordant with the TRACC database, often with a tendency to overestimate interventions. Clinician surveys alone do not reliably capture contemporary clinical practices in mCRC.
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: Springer Science and Business Media LLC
Date: 03-2017
DOI: 10.1038/NATURE21374
Publisher: Springer Science and Business Media LLC
Date: 16-07-2015
DOI: 10.1038/SREP11999
Abstract: The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been proposed by the FANTOM5 Consortium to extend the understanding of the sequence of events facilitating cell state transition at the level of promoter regulation. To identify the most prominent transcriptional regulations induced by growth factors in human breast cancer, we apply here the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis approach to the CAGE time-course datasets of MCF-7 cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). We identify a multi-level cascade of regulations rooted by the Serum Response Factor (SRF) transcription factor, connecting the MAPK-mediated transduction of the HRG stimulus to the negative regulation of the MAPK pathway by the members of the DUSP family phosphatases. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation induced by the estrogen receptors) by the activity of the AP-1 complex, specific to HRG response. The results indicate that a ergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.
Publisher: Elsevier BV
Date: 12-2022
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: Elsevier BV
Date: 07-2021
DOI: 10.1016/J.JHEP.2021.02.008
Abstract: Checkpoint inhibitor-related hepatitis (CPI-Hep) is an emerging clinical challenge. We aimed to gain insights into the immunopathology of CPI-Hep by comprehensively characterising myeloid and lymphoid subsets. CPI-treated patients with or without related hepatitis (CPI-Hep n = 22 and CPI-noHep n = 7) were recruited. Phenotypic and transcriptional profiling of peripheral immune subsets was performed and compared with 19 healthy controls (HCs). In vitro monocyte-derived macrophages (MoMFs) were assessed for activation and cytokine production. CD163, CCR2, CD68, CD3, CD8 and granzyme B expression was assessed using immunohistochemistry/immunofluorescence (n = 4). A significant total monocyte depletion was observed in CPI-Hep compared with HCs (p = 0.04), along with a proportionate increase in the classical monocyte population (p = 0.0002) and significant upregulation of CCR2, CD163 and downregulation of CCR7. Soluble CD163 levels were significantly elevated in CPI-Hep compared with HCs (p <0.0001). In vitro MoMFs from CPI-Hep showed enhanced production of pro-inflammatory cytokines. CD8 CPI-Hep is associated with activation of peripheral monocytes and an enhanced cytotoxic, effector CD8 Some patients who receive immunotherapy for cancer develop liver inflammation, which requires cessation of cancer treatment. Herein, we describe ways in which the white blood cells of patients who develop liver inflammation differ from those of patients who receive the same immunotherapy but do not experience liver-related side effects. Targeting some of the pathways we identify may help to prevent or manage this side effect and facilitate cancer treatment.
Publisher: Elsevier BV
Date: 05-2023
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: Public Library of Science (PLoS)
Date: 03-2018
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: 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: Japan
Location: United States of America
No related grants have been discovered for Lewis Au.