Profiling Pre-Replication Complex Mutations in Cancer
Аутори
Kusić Tisma, JelenaOrlić Milacić, Marija
Trinh, Quang
Ahluwalia, Rhea
Stein D., Lincoln
Остала ауторства
Morić, IvanaĐorđević, Valentina
Конференцијски прилог (Објављена верзија)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
The pre-replication complex (preRC) consists of 15 proteins that mark DNA replication
initiation sites and regulate replication timing. Deficiency in preRC proteins results in
genomic instability (re-replication) and developmental defects (Meier-Gorlin syndrome).
Our aim was to assess the scope of preRC gene aberrations in cancer. Variations in
preRC genes were studied using CBio Portal software and TCGA PanCancer dataset. The
functional impact of detected variants was evaluated in silico by three different prediction
tools: SIFT (sequence and evolutionary conservation - based), PolyPhen2 (protein
sequence and structure – based) and MutPred2 (supervised learning method based on
neural networks).
No mutational hotspots were observed in any of the 15 preRC genes and no mutual
exclusivity between mutations in preRC genes were detected. The highest alteration
incidence in preRC genes was found in endometrial carcinoma and melanoma. The majority
of the variations seen in preRC g...enes were non-synonymous. The functional assessment
has shown that 253/1215 (21%) preRC gene mutations were predicted to be pathogenic
with high confidence by 2/3 computational algorithms. None of the variants reached the
high confidence pathogenicity score by all 3 prediction tool. In contrast, 49% of variants
were predicted to be either benign by all three tools or benign by 2/3 or 1/3 tools, with the
remaining 1/3 or 2/3, respectively, classifying them as low confidence pathogenic.
These finding suggest that mutations in preRC proteins might be passenger mutations
and that cancer cells can tolerate them. The future step is to see whether incidence of
coding vs. noncoding preRC mutations correlates with Tumor Mutation Burden (TMB) and
Genome Instability Index (GII) of cancer.
Кључне речи:
preRC / data mining / cBioPortalИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 76-76Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Kusić Tisma, Jelena AU - Orlić Milacić, Marija AU - Trinh, Quang AU - Ahluwalia, Rhea AU - Stein D., Lincoln PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/2016 AB - The pre-replication complex (preRC) consists of 15 proteins that mark DNA replication initiation sites and regulate replication timing. Deficiency in preRC proteins results in genomic instability (re-replication) and developmental defects (Meier-Gorlin syndrome). Our aim was to assess the scope of preRC gene aberrations in cancer. Variations in preRC genes were studied using CBio Portal software and TCGA PanCancer dataset. The functional impact of detected variants was evaluated in silico by three different prediction tools: SIFT (sequence and evolutionary conservation - based), PolyPhen2 (protein sequence and structure – based) and MutPred2 (supervised learning method based on neural networks). No mutational hotspots were observed in any of the 15 preRC genes and no mutual exclusivity between mutations in preRC genes were detected. The highest alteration incidence in preRC genes was found in endometrial carcinoma and melanoma. The majority of the variations seen in preRC genes were non-synonymous. The functional assessment has shown that 253/1215 (21%) preRC gene mutations were predicted to be pathogenic with high confidence by 2/3 computational algorithms. None of the variants reached the high confidence pathogenicity score by all 3 prediction tool. In contrast, 49% of variants were predicted to be either benign by all three tools or benign by 2/3 or 1/3 tools, with the remaining 1/3 or 2/3, respectively, classifying them as low confidence pathogenic. These finding suggest that mutations in preRC proteins might be passenger mutations and that cancer cells can tolerate them. The future step is to see whether incidence of coding vs. noncoding preRC mutations correlates with Tumor Mutation Burden (TMB) and Genome Instability Index (GII) of cancer. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Profiling Pre-Replication Complex Mutations in Cancer EP - 76 SP - 76 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_2016 ER -
@conference{ author = "Kusić Tisma, Jelena and Orlić Milacić, Marija and Trinh, Quang and Ahluwalia, Rhea and Stein D., Lincoln", year = "2023", abstract = "The pre-replication complex (preRC) consists of 15 proteins that mark DNA replication initiation sites and regulate replication timing. Deficiency in preRC proteins results in genomic instability (re-replication) and developmental defects (Meier-Gorlin syndrome). Our aim was to assess the scope of preRC gene aberrations in cancer. Variations in preRC genes were studied using CBio Portal software and TCGA PanCancer dataset. The functional impact of detected variants was evaluated in silico by three different prediction tools: SIFT (sequence and evolutionary conservation - based), PolyPhen2 (protein sequence and structure – based) and MutPred2 (supervised learning method based on neural networks). No mutational hotspots were observed in any of the 15 preRC genes and no mutual exclusivity between mutations in preRC genes were detected. The highest alteration incidence in preRC genes was found in endometrial carcinoma and melanoma. The majority of the variations seen in preRC genes were non-synonymous. The functional assessment has shown that 253/1215 (21%) preRC gene mutations were predicted to be pathogenic with high confidence by 2/3 computational algorithms. None of the variants reached the high confidence pathogenicity score by all 3 prediction tool. In contrast, 49% of variants were predicted to be either benign by all three tools or benign by 2/3 or 1/3 tools, with the remaining 1/3 or 2/3, respectively, classifying them as low confidence pathogenic. These finding suggest that mutations in preRC proteins might be passenger mutations and that cancer cells can tolerate them. The future step is to see whether incidence of coding vs. noncoding preRC mutations correlates with Tumor Mutation Burden (TMB) and Genome Instability Index (GII) of cancer.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Profiling Pre-Replication Complex Mutations in Cancer", pages = "76-76", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_2016" }
Kusić Tisma, J., Orlić Milacić, M., Trinh, Q., Ahluwalia, R.,& Stein D., L.. (2023). Profiling Pre-Replication Complex Mutations in Cancer. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 76-76. https://hdl.handle.net/21.15107/rcub_imagine_2016
Kusić Tisma J, Orlić Milacić M, Trinh Q, Ahluwalia R, Stein D. L. Profiling Pre-Replication Complex Mutations in Cancer. in 4th Belgrade Bioinformatics Conference. 2023;4:76-76. https://hdl.handle.net/21.15107/rcub_imagine_2016 .
Kusić Tisma, Jelena, Orlić Milacić, Marija, Trinh, Quang, Ahluwalia, Rhea, Stein D., Lincoln, "Profiling Pre-Replication Complex Mutations in Cancer" in 4th Belgrade Bioinformatics Conference, 4 (2023):76-76, https://hdl.handle.net/21.15107/rcub_imagine_2016 .