SJPedPanel : A pan-cancer gene panel for childhood malignancies
Background: Large scale genomics projects have identified driver alterations for most childhood cancers that provide reliable biomarkers for clinical diagnosis and disease monitoring using targeted sequencing. However, there is lack of a comprehensive panel that matches the list of known driver genes. Here we fill this gap by developing SJPedPanel for childhood cancers.
Results: SJPedPanel covers 5,275 coding exons of 357 driver genes, 297 introns frequently involved in rearrangements that generate fusion oncoproteins, commonly amplified/deleted regions (e.g., MYCN for neuroblastoma, CDKN2A and PAX5 for B-/T-ALL, and SMARCB1 for AT/RT), and 7,590 polymorphism sites for interrogating tumors with aneuploidy, such as hyperdiploid and hypodiploid B-ALL or 17q gain neuroblastoma. We used driver alterations reported from an established real-time clinical genomics cohort (n=253) to validate this gene panel. Among the 485 pathogenic variants reported, our panel covered 417 variants (86%). For 90 rearrangements responsible for oncogenic fusions, our panel covered 74 events (82%). We re-sequenced 113 previously characterized clinical specimens at an average depth of 2,500X using SJPedPanel and recovered 354 (91%) of the 389 reported pathogenic variants. We then investigated the power of this panel in detecting mutations from specimens with low tumor purity (as low as 0.1%) using cell line-based dilution experiments and discovered that this gene panel enabled us to detect ∼80% variants with allele fraction of 0.2%, while the detection rate decreases to ∼50% when the allele fraction is 0.1%. We finally demonstrate its utility in disease monitoring on clinical specimens collected from AML patients in morphologic remission.
Conclusions: SJPedPanel enables the detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions for childhood cancers by targeted sequencing of ∼0.15% of human genome. It will enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
medRxiv : the preprint server for health sciences - (2024) vom: 09. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kolekar, Pandurang [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Revised 21.02.2024 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2023.11.27.23299068 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM365677515 |
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| 520 | |a Background: Large scale genomics projects have identified driver alterations for most childhood cancers that provide reliable biomarkers for clinical diagnosis and disease monitoring using targeted sequencing. However, there is lack of a comprehensive panel that matches the list of known driver genes. Here we fill this gap by developing SJPedPanel for childhood cancers | ||
| 520 | |a Results: SJPedPanel covers 5,275 coding exons of 357 driver genes, 297 introns frequently involved in rearrangements that generate fusion oncoproteins, commonly amplified/deleted regions (e.g., MYCN for neuroblastoma, CDKN2A and PAX5 for B-/T-ALL, and SMARCB1 for AT/RT), and 7,590 polymorphism sites for interrogating tumors with aneuploidy, such as hyperdiploid and hypodiploid B-ALL or 17q gain neuroblastoma. We used driver alterations reported from an established real-time clinical genomics cohort (n=253) to validate this gene panel. Among the 485 pathogenic variants reported, our panel covered 417 variants (86%). For 90 rearrangements responsible for oncogenic fusions, our panel covered 74 events (82%). We re-sequenced 113 previously characterized clinical specimens at an average depth of 2,500X using SJPedPanel and recovered 354 (91%) of the 389 reported pathogenic variants. We then investigated the power of this panel in detecting mutations from specimens with low tumor purity (as low as 0.1%) using cell line-based dilution experiments and discovered that this gene panel enabled us to detect ∼80% variants with allele fraction of 0.2%, while the detection rate decreases to ∼50% when the allele fraction is 0.1%. We finally demonstrate its utility in disease monitoring on clinical specimens collected from AML patients in morphologic remission | ||
| 520 | |a Conclusions: SJPedPanel enables the detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions for childhood cancers by targeted sequencing of ∼0.15% of human genome. It will enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection | ||
| 650 | 4 | |a Preprint | |
| 700 | 1 | |a Balagopal, Vidya |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Li |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Yanling |e verfasserin |4 aut | |
| 700 | 1 | |a Foy, Scott |e verfasserin |4 aut | |
| 700 | 1 | |a Tran, Quang |e verfasserin |4 aut | |
| 700 | 1 | |a Mulder, Heather |e verfasserin |4 aut | |
| 700 | 1 | |a Huskey, Anna Lw |e verfasserin |4 aut | |
| 700 | 1 | |a Plyler, Emily |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Zhikai |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Jingqun |e verfasserin |4 aut | |
| 700 | 1 | |a Nakitandwe, Joy |e verfasserin |4 aut | |
| 700 | 1 | |a Gu, Jiali |e verfasserin |4 aut | |
| 700 | 1 | |a Namwanje, Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Maciaszek, Jamie |e verfasserin |4 aut | |
| 700 | 1 | |a Payne-Turner, Debbie |e verfasserin |4 aut | |
| 700 | 1 | |a Mallampati, Saradhi |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Lu |e verfasserin |4 aut | |
| 700 | 1 | |a Easton, John |e verfasserin |4 aut | |
| 700 | 1 | |a Klco, Jeffery M |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Xiaotu |e verfasserin |4 aut | |
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