ORCID Profile
0000-0002-9436-5857
Current Organisations
Univerza v Ljubljani Veterinarska fakulteta
,
The University of Auckland
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Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6551082
Abstract: Tumor evolution underlies many challenges facing precision oncology, and improving our understanding has the potential to improve clinical care. This study represents a rare opportunity to study tumor heterogeneity and evolution in a patient with an understudied cancer type. A patient with pulmonary atypical carcinoid, a neuroendocrine tumor, metastatic to 90 sites, requested and consented to donate tissues for research. 42 tumor s les collected at rapid autopsy from 14 anatomically distinct sites were analyzed through DNA whole-exome sequencing and RNA sequencing, and five analyzed through linked-read sequencing. Targeted DNA sequencing was completed on two clinical tissue biopsies and one blood plasma s le. Chromosomal alterations and gene variants accumulated over time, and specific chromosomal alterations preceded the single predicted gene driver variant ( i ARID1A) /i . At the time of autopsy, all sites shared the gain of one copy of Chr 5, loss of one copy of Chr 6 and 21, chromothripsis of one copy of Chr 11, and 39 small variants. Two tumor clones (carrying additional variants) were detected at metastatic sites, and occasionally in different regions of the same organ (e.g., within the pancreas). Circulating tumor DNA (ctDNA) sequencing detected shared tumor variants in the blood plasma and captured marked genomic heterogeneity, including all metastatic clones but few private tumor variants. This study describes genomic tumor evolution and dissemination of a pulmonary atypical carcinoid donated by a single generous patient. It highlights the critical role of chromosomal alterations in tumor initiation and explores the potential of ctDNA analysis to represent genomically heterogeneous disease. Significance: DNA sequencing data from tumor s les and blood plasma from a single patient highlighted the critical early role of chromosomal alterations in atypical carcinoid tumor development. Common tumor variants were readily detected in the blood plasma, unlike emerging tumor variants, which has implications for using ctDNA to capture cancer evolution. /
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546065.V1
Abstract: Supplementary Figure S6: ctDNA detection of private variants While only four private variants were reported by the sequencing platform’s IonReporter software (indicated in orange, key top right), there were sequencing reads to support other private variants. Private variants unique to s les La1 (3 variants) and Pa6 (1 variant) were supported by 2 to 3 variant molecules, and there was a single variant molecule detected to support private variant detection in the following s les: Br2, Cr1, In2, Ki2, La1, Lh1, Lh2, Lu6, Lu7, Lu9, Pa2, Pa3, Pa6, Sc7, Th1, Th2, Ut1, Ve2, Ve3.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546068
Abstract: Supplementary Figure S5: Inference of putative sequences of genomic changes consistent with the data using the LICHeE and REVOLVER methods LICHeE and Revolver were used to further speculate the order of genomic changes in this patient's dataset. ClonEvol was also trialed, using PyClone putative clonal clusters as input, however the results did not converge. A, LICHeE was run according to the tool creator's instructions, using VAFs as input, to generate clonal relationships of tumor s les. Numbers inside colored circles represent the number of mutations defining a clone, and the squares represent the clonal structures of in idual s les. Shaded regions indicate the proportion of cells belonging to that clone, where the white regions represent normal cells. Four dominant tumor groups were apparent. Where two or more colors are present, LICHeE has predicted the s le to contain a mixture of clones (most apparent in Pa1 and Lu1 but also present in In2, Pa6 and others). This feature is also visible in the VAF plot (Figure 5a) but not represented on the DNA phylogram (Figure 5b). Technical reasons prevented the inclusion of some s les, e.g. Lu8 and Pa5. B, Clonal relationships between tumor s les as predicted by REVOLVER, using PyClone putative clonal clusters as input (from VAF and chromosomal copy number), and default tool parameters. Clones are labeled according to one variant defining that clone (e.g., MASTL), and the circle size is proportional to the number of variants defining the clone. Number refers to clone number. REVOLVER highlighted the same pattern of progression seen in other analyses: from normal cells, common variants accumulate (labeled as MASTL in Figure 5b), and a further set of variants shared by most tumors was identified (labeled GPAM) before a split into two dominant tumor groups, each characterized by their own set of variants (labeled SLIT1 and PAQR6 respectively). REVOLVER highlights the progression of variant accumulation across all s les, rather than indicating in idual s les. All coloring consistent with Figure 5. Overall, LICHeE and REVOLVER explore the clonal and subclonal structure of in idual tumor s les and suggest the same sequence of genomic progression evident in the DNA phylogram (Figure 5b). None of these cancer-specific methods attempts to time the evolutionary ergence events.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546065
Abstract: Supplementary Figure S6: ctDNA detection of private variants While only four private variants were reported by the sequencing platform’s IonReporter software (indicated in orange, key top right), there were sequencing reads to support other private variants. Private variants unique to s les La1 (3 variants) and Pa6 (1 variant) were supported by 2 to 3 variant molecules, and there was a single variant molecule detected to support private variant detection in the following s les: Br2, Cr1, In2, Ki2, La1, Lh1, Lh2, Lu6, Lu7, Lu9, Pa2, Pa3, Pa6, Sc7, Th1, Th2, Ut1, Ve2, Ve3.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546077
Abstract: Supplementary Figure S2: Breakpoints in 10x Loupe software linked-reads view. Each bar represents a sequencing read, and those joined with a horizontal line share the same barcode. Reads are grouped by haplotype (green and purple), with unphased reads in grey. Vertical orange lines indicate putative breakpoints defined by the software. Given that the maximum region of the chromosome phased was significantly shorter than the length of Chr 11 (as indicated in the ‘phase block view’ plot), some breakpoints are assigned to different haplotypes, therefore haplotypes should not be compared between regions (the breakpoint appears in purple in some regions and in green in others). The copy number patterns are consistent with all breakpoints occurring on the same copy of the chromosome.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546062.V1
Abstract: Supplementary Table S1 includes a description of the tumour s les analysed. Supplementary Table S2 includes DNA WES summary statistics. Supplementary Table S3 includes RNA-Seq summary statistics. Supplementary Table S4 includes WGS linked-read summary statistics. Supplementary Table S5 includes regions covered in the custom ThermoFisher Scientific Ampliseq HD panel. Supplementary Table S6 includes targeted DNA sequencing custom panel summary statistics. Supplementary Table S7 includes low-coverage DNA WES summary statistics. Supplementary Table S8 includes gene set enrichment of genes lost from Chr 11. Supplementary Table S9 includes variants identified in two or more tumour sites. Supplementary Table S10 includes the consequence of somatic variants in Biopsy 1.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546068.V1
Abstract: Supplementary Figure S5: Inference of putative sequences of genomic changes consistent with the data using the LICHeE and REVOLVER methods LICHeE and Revolver were used to further speculate the order of genomic changes in this patient's dataset. ClonEvol was also trialed, using PyClone putative clonal clusters as input, however the results did not converge. A, LICHeE was run according to the tool creator's instructions, using VAFs as input, to generate clonal relationships of tumor s les. Numbers inside colored circles represent the number of mutations defining a clone, and the squares represent the clonal structures of in idual s les. Shaded regions indicate the proportion of cells belonging to that clone, where the white regions represent normal cells. Four dominant tumor groups were apparent. Where two or more colors are present, LICHeE has predicted the s le to contain a mixture of clones (most apparent in Pa1 and Lu1 but also present in In2, Pa6 and others). This feature is also visible in the VAF plot (Figure 5a) but not represented on the DNA phylogram (Figure 5b). Technical reasons prevented the inclusion of some s les, e.g. Lu8 and Pa5. B, Clonal relationships between tumor s les as predicted by REVOLVER, using PyClone putative clonal clusters as input (from VAF and chromosomal copy number), and default tool parameters. Clones are labeled according to one variant defining that clone (e.g., MASTL), and the circle size is proportional to the number of variants defining the clone. Number refers to clone number. REVOLVER highlighted the same pattern of progression seen in other analyses: from normal cells, common variants accumulate (labeled as MASTL in Figure 5b), and a further set of variants shared by most tumors was identified (labeled GPAM) before a split into two dominant tumor groups, each characterized by their own set of variants (labeled SLIT1 and PAQR6 respectively). REVOLVER highlights the progression of variant accumulation across all s les, rather than indicating in idual s les. All coloring consistent with Figure 5. Overall, LICHeE and REVOLVER explore the clonal and subclonal structure of in idual tumor s les and suggest the same sequence of genomic progression evident in the DNA phylogram (Figure 5b). None of these cancer-specific methods attempts to time the evolutionary ergence events.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546074.V1
Abstract: Supplementary Figure S3: Mutational signatures across all s les collected at autopsy A, Overall mutational burden does not reveal significant mutational signatures (MuSiCa). The signature contribution is indicated by the degree of shading (key to right). The signature with the highest contribution was Signature 3, however it was not statistically significant in most s les according to tool Signal. B, The scarHRD method for quantifying homologous recombination deficiency did not identify any tumors to be HR-deficient with all having an HRD-sum score 20 (known HR-deficient tumors usually have HRD-sums of 40)28.
Publisher: Elsevier BV
Date: 02-2022
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546077.V1
Abstract: Supplementary Figure S2: Breakpoints in 10x Loupe software linked-reads view. Each bar represents a sequencing read, and those joined with a horizontal line share the same barcode. Reads are grouped by haplotype (green and purple), with unphased reads in grey. Vertical orange lines indicate putative breakpoints defined by the software. Given that the maximum region of the chromosome phased was significantly shorter than the length of Chr 11 (as indicated in the ‘phase block view’ plot), some breakpoints are assigned to different haplotypes, therefore haplotypes should not be compared between regions (the breakpoint appears in purple in some regions and in green in others). The copy number patterns are consistent with all breakpoints occurring on the same copy of the chromosome.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546080.V1
Abstract: Supplementary Figure S1: ADTEx copy number analysis of Biopsy 1 from low coverage WES Copy number profile of low-coverage WES of Biopsy 1 revealing A, likely lification of Chr 5 and B, loss of Chr 21. Top panels display DOC ratio, colored by predicted copy number state. Bottom panels display BAF, colored by predicted copy number alteration. The separation of BAF towards 0.3 and 0.6 in Chr 5 indicates chromosomal gain, whereas the separation of BAF towards 0 and 1 in Chr 21 indicates LoH. There was insufficient evidence conclusively identify the presence or absence of the loss of C, Chr 6 and D, chromothripsis of one copy of Chr 11 based on ADTEx analysis of the low-coverage WES of Biopsy 1, however it is likely that they were absent. Copy number analysis was plagued with high levels of noise from low coverage and large differences in coverage between the Biopsy 1 and normal s le. The sole Chr 11 breakpoint covered by the exome sequencing did not provide read support for chromothripsis. The apparent lifications of regions of each chromosome do not match up to any known alterations in high-quality DNA s les from tumours collected at autopsy and are likely attributable to noise in the low coverage WES.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546071.V1
Abstract: Supplementary Figure S4: Absence of ARID1A variant in targeted panel sequencing of Biopsy 1 despite adequate depth Top panel shows Biopsy 1 targeted panel sequencing. Bottom panel shows representative tumor s led at autopsy (Sc6) with heterozygous deletion in ARID1A, clearly absent from Biopsy 1 sequencing despite adequate depth (7240 unique molecules). The probability of not s ling the ARID1A variant in Biopsy 1 due to chance alone was calculated assuming tumor cellularity of 80% and the heterozygous ARID1A variant being present in 50% of tumor reads. 7240 unique molecules covered this genomic position. The binomial distribution in R was used to calculate the probability of not s ling this variant: dbinom(7240, size=7240, prob=0.6).
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546074
Abstract: Supplementary Figure S3: Mutational signatures across all s les collected at autopsy A, Overall mutational burden does not reveal significant mutational signatures (MuSiCa). The signature contribution is indicated by the degree of shading (key to right). The signature with the highest contribution was Signature 3, however it was not statistically significant in most s les according to tool Signal. B, The scarHRD method for quantifying homologous recombination deficiency did not identify any tumors to be HR-deficient with all having an HRD-sum score 20 (known HR-deficient tumors usually have HRD-sums of 40)28.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546062
Abstract: Supplementary Table S1 includes a description of the tumour s les analysed. Supplementary Table S2 includes DNA WES summary statistics. Supplementary Table S3 includes RNA-Seq summary statistics. Supplementary Table S4 includes WGS linked-read summary statistics. Supplementary Table S5 includes regions covered in the custom ThermoFisher Scientific Ampliseq HD panel. Supplementary Table S6 includes targeted DNA sequencing custom panel summary statistics. Supplementary Table S7 includes low-coverage DNA WES summary statistics. Supplementary Table S8 includes gene set enrichment of genes lost from Chr 11. Supplementary Table S9 includes variants identified in two or more tumour sites. Supplementary Table S10 includes the consequence of somatic variants in Biopsy 1.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22546071
Abstract: Supplementary Figure S4: Absence of ARID1A variant in targeted panel sequencing of Biopsy 1 despite adequate depth Top panel shows Biopsy 1 targeted panel sequencing. Bottom panel shows representative tumor s led at autopsy (Sc6) with heterozygous deletion in ARID1A, clearly absent from Biopsy 1 sequencing despite adequate depth (7240 unique molecules). The probability of not s ling the ARID1A variant in Biopsy 1 due to chance alone was calculated assuming tumor cellularity of 80% and the heterozygous ARID1A variant being present in 50% of tumor reads. 7240 unique molecules covered this genomic position. The binomial distribution in R was used to calculate the probability of not s ling this variant: dbinom(7240, size=7240, prob=0.6).
Publisher: American Association for Cancer Research (AACR)
Date: 10-01-2023
DOI: 10.1158/2767-9764.CRC-22-0101
Abstract: Tumor evolution underlies many challenges facing precision oncology, and improving our understanding has the potential to improve clinical care. This study represents a rare opportunity to study tumor heterogeneity and evolution in a patient with an understudied cancer type. A patient with pulmonary atypical carcinoid, a neuroendocrine tumor, metastatic to 90 sites, requested and consented to donate tissues for research. 42 tumor s les collected at rapid autopsy from 14 anatomically distinct sites were analyzed through DNA whole-exome sequencing and RNA sequencing, and five analyzed through linked-read sequencing. Targeted DNA sequencing was completed on two clinical tissue biopsies and one blood plasma s le. Chromosomal alterations and gene variants accumulated over time, and specific chromosomal alterations preceded the single predicted gene driver variant (ARID1A). At the time of autopsy, all sites shared the gain of one copy of Chr 5, loss of one copy of Chr 6 and 21, chromothripsis of one copy of Chr 11, and 39 small variants. Two tumor clones (carrying additional variants) were detected at metastatic sites, and occasionally in different regions of the same organ (e.g., within the pancreas). Circulating tumor DNA (ctDNA) sequencing detected shared tumor variants in the blood plasma and captured marked genomic heterogeneity, including all metastatic clones but few private tumor variants. This study describes genomic tumor evolution and dissemination of a pulmonary atypical carcinoid donated by a single generous patient. It highlights the critical role of chromosomal alterations in tumor initiation and explores the potential of ctDNA analysis to represent genomically heterogeneous disease. DNA sequencing data from tumor s les and blood plasma from a single patient highlighted the critical early role of chromosomal alterations in atypical carcinoid tumor development. Common tumor variants were readily detected in the blood plasma, unlike emerging tumor variants, which has implications for using ctDNA to capture cancer evolution.
Publisher: Elsevier BV
Date: 08-2018
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2018
DOI: 10.1158/2767-9764.22546080
Abstract: Supplementary Figure S1: ADTEx copy number analysis of Biopsy 1 from low coverage WES Copy number profile of low-coverage WES of Biopsy 1 revealing A, likely lification of Chr 5 and B, loss of Chr 21. Top panels display DOC ratio, colored by predicted copy number state. Bottom panels display BAF, colored by predicted copy number alteration. The separation of BAF towards 0.3 and 0.6 in Chr 5 indicates chromosomal gain, whereas the separation of BAF towards 0 and 1 in Chr 21 indicates LoH. There was insufficient evidence conclusively identify the presence or absence of the loss of C, Chr 6 and D, chromothripsis of one copy of Chr 11 based on ADTEx analysis of the low-coverage WES of Biopsy 1, however it is likely that they were absent. Copy number analysis was plagued with high levels of noise from low coverage and large differences in coverage between the Biopsy 1 and normal s le. The sole Chr 11 breakpoint covered by the exome sequencing did not provide read support for chromothripsis. The apparent lifications of regions of each chromosome do not match up to any known alterations in high-quality DNA s les from tumours collected at autopsy and are likely attributable to noise in the low coverage WES.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6551082.V1
Abstract: Tumor evolution underlies many challenges facing precision oncology, and improving our understanding has the potential to improve clinical care. This study represents a rare opportunity to study tumor heterogeneity and evolution in a patient with an understudied cancer type. A patient with pulmonary atypical carcinoid, a neuroendocrine tumor, metastatic to 90 sites, requested and consented to donate tissues for research. 42 tumor s les collected at rapid autopsy from 14 anatomically distinct sites were analyzed through DNA whole-exome sequencing and RNA sequencing, and five analyzed through linked-read sequencing. Targeted DNA sequencing was completed on two clinical tissue biopsies and one blood plasma s le. Chromosomal alterations and gene variants accumulated over time, and specific chromosomal alterations preceded the single predicted gene driver variant ( i ARID1A) /i . At the time of autopsy, all sites shared the gain of one copy of Chr 5, loss of one copy of Chr 6 and 21, chromothripsis of one copy of Chr 11, and 39 small variants. Two tumor clones (carrying additional variants) were detected at metastatic sites, and occasionally in different regions of the same organ (e.g., within the pancreas). Circulating tumor DNA (ctDNA) sequencing detected shared tumor variants in the blood plasma and captured marked genomic heterogeneity, including all metastatic clones but few private tumor variants. This study describes genomic tumor evolution and dissemination of a pulmonary atypical carcinoid donated by a single generous patient. It highlights the critical role of chromosomal alterations in tumor initiation and explores the potential of ctDNA analysis to represent genomically heterogeneous disease. Significance: DNA sequencing data from tumor s les and blood plasma from a single patient highlighted the critical early role of chromosomal alterations in atypical carcinoid tumor development. Common tumor variants were readily detected in the blood plasma, unlike emerging tumor variants, which has implications for using ctDNA to capture cancer evolution. /
No related grants have been discovered for Polona Le Quesne Stabej.