Browsing by Author "Larionov, Alexey"

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    Classification of endocrine resistant breast cancers from transcriptomic datasets using multi-gene signatures
    (Cranfield University, 2012-09) Larionov, Alexey; Cameron, David; Morgan, Sarah
    Breast cancer is the most frequent cancer in women in developed countries. Endocrine treatment is indicated to the majority of breast cancer patients. However, in some cases it does not work despite the current clinical indications. Eventually the resistance may develop in many of those who initially respond. Re-analysis of available breast cancer transcriptomic datasets using new multi-gene signatures associated with endocrine resistance may help to understand and overcome endocrine resistance. The goal of this project was to develop a bioinformatics pipeline to (i) select endocrine resistant cases from the available breast cancer datasets and (ii) classify the selected cases by multiple multi-gene signatures. The pipeline has been successfully designed and applied for classification of endocrineresistant samples from 9 breast cancer datasets using 7 transcriptional signatures. The obtained results have been presented in a dedicated web site. The pipeline consists of:  Procedures for a manually curated selection of relevant datasets and signatures;  Procedures for semi-automatic data pre-processing, allowing cross-platform analysis;  A new, fully automated, classification algorithm (Iterative Consensus PAM). The main features of the developed classification algorithm include:  It is based on un-supervised partitioning;  It allows for “non-classifiable” samples;  The procedure does not require a training set;  The procedure can be used in a cross-platform context (Affymetrix & Illumina). The developed pipeline and web site may constitute a prototype for a future web-hub collecting (i) data on endocrine-resistant breast cancer specimens, (ii) collecting multigene signatures relevant to endocrine resistance and (iii) providing tools to apply the signatures to the data. The web-repository could provide a tool to integrate the data and signatures and to produce new clinical and biological knowledge about endocrine resistance in breast cancer.
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    The contribution of germline pathogenic variants in breast cancer genes to contralateral breast cancer risk in BRCA1/BRCA2/PALB2-negative women
    (MDPI, 2023-01-08) Larionov, Alexey; Fewings, Eleanor; Redman, James; Goldgraben, Mae; Clark, Graeme; Boice, John; Concannon, Patrick; Bernstein, Jonine; Conti, David V.; The WECARE Study Collaborative Group; Tischkowitz, Marc
    Background: Contralateral breast cancer (CBC) is associated with younger age at first diagnosis, family history and pathogenic germline variants (PGVs) in genes such as BRCA1, BRCA2 and PALB2. However, data regarding genetic factors predisposing to CBC among younger women who are BRCA1/2/PALB2-negative remain limited. Methods: In this nested case-control study, participants negative for BRCA1/2/PALB2 PGVs were selected from the WECARE Study. The burden of PGVs in established breast cancer risk genes was compared in 357 cases with CBC and 366 matched controls with unilateral breast cancer (UBC). The samples were sequenced in two phases. Whole exome sequencing was used in Group 1, 162 CBC and 172 UBC (mean age at diagnosis: 42 years). A targeted panel of genes was used in Group 2, 195 CBC and 194 UBC (mean age at diagnosis: 50 years). Comparisons of PGVs burdens between CBC and UBC were made in these groups, and additional stratified sub-analysis was performed within each group according to the age at diagnosis and the time from first breast cancer (BC). Results: The PGVs burden in Group 1 was significantly higher in CBC than in UBC (p = 0.002, OR = 2.5, 95CI: 1.2–5.6), driven mainly by variants in CHEK2 and ATM. The proportions of PGVs carriers in CBC and UBC in this group were 14.8% and 5.8%, respectively. There was no significant difference in PGVs burden between CBC and UBC in Group 2 (p = 0.4, OR = 1.4, 95CI: 0.7–2.8), with proportions of carriers being 8.7% and 8.2%, respectively. There was a significant association of PGVs in CBC with younger age. Metanalysis combining both groups confirmed the significant association between the burden of PGVs and the risk of CBC (p = 0.006) with the significance driven by the younger cases (Group 1). Conclusion: In younger BRCA1/BRCA2/PALB2-negative women, the aggregated burden of PGVs in breast cancer risk genes was associated with the increased risk of CBC and was inversely proportional to the age at onset.
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    Frequency of pathogenic germline variants in cancer susceptibility genes in 1336 renal cell carcinoma cases
    (Oxford Academic, 2022-04-20) Yngvadottir, Bryndis; Andreou, Avgi; Bassaganyas, Laia; Larionov, Alexey; Cornish, Alex J.; Chubb, Daniel; Saunders, Charlie N.; Smith, Philip S.; Zhang, Huairen; Cole, Yasemin; Genomics England Research Consortium; Larkin, James; Browning, Lisa; Turajlic, Samra; Litchfield, Kevin; Houlston, Richard S.; Maher, Eamonn R.
    Background Renal cell carcinoma (RCC) occurs in a number of cancer predisposition syndromes but the genetic architecture of susceptibility to RCC is not well defined. We investigated the frequency of pathogenic germline variants in cancer susceptibility genes (CSGs) within a large series of unselected RCC participants. Methods Whole genome sequencing data on 1336 RCC participants and 5834 controls recruited to the UK 100000 Genomes Project, a nationwide multicentre study, was analysed to identify rare pathogenic or likely pathogenic (P/LP) short variants (SNVs and INDELs) and structural variants in 121 CSGs. Results Among 1336 RCC participants (mean 61.3 years [±12SD], range 13–88 years; 64% male), 85 participants (6.4%; 95% CI [5.1, 7.8]) had one or more P/LP germline variant in a wider range of CSGs than previously recognised. A further 64 intragenic variants in CSGs previously associated with RCC were classified as a variant of uncertain significance (VUS) (24 ‘hot VUSs’) and were considered to be of potential clinical relevance as further evaluation might result in their reclassification. Most patients with pathogenic variants in well-established RCC-CSGs were aged < 50 years. Burden test analysis for filtered variants in CSGs demonstrated a significant excess of CHEK2 variants RCC European participants compared to the healthy European controls (P = 0.0019). Conclusions Approximately 6% of patients with RCC unselected for family history have a germline variant requiring additional follow-up analysis. To improve diagnostic yield we suggest expanding the panel of RCC-CSGs tested to include CHEK2 and all SDHx subunits and raising the eligibility criteria for age-based testing.
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    The soil microbial methylome: a tool to explore the role of epigenetic memory in driving soil abiotic legacy effects
    (Elsevier, 2025-03) Sizmur, Tom; Larionov, Alexey
    Epigenetics is a phenomenon whereby a stable hereditable change in gene expression can occur without changing the DNA sequence. DNA methylation (the addition of a methyl group to specific nucleotides in specific DNA motifs) is the most studied epigenetic mechanism and is widely observed in both eukaryotic and prokaryotic cells. We hypothesise that the soil methylome may play an important role in the manifestation of soil abiotic legacy effects, whereby temporary exposure of soil microbial communities to particular environmental conditions influences future soil microbial function. These abiotic legacy effects are important because they underpin the delivery of key ecosystem services in response to global environmental change. Third generation long-read sequencing technologies, such as Pacific Bioscience Single-Molecule Real-Time sequencing (SMRT-seq) and Oxford Nanopore sequencing provide an opportunity to study methylome heterogeneity in complex microbial communities. The simultaneous measurement of epigenetic, transcriptional, and microbial community composition changes may lead to the development of biomarkers of historic environmental stress and a greater understanding of the role of the soil methylome in the resilience of soil microbial communities to future environmental perturbations. It is therefore timely to add the meta-epigenetic layer to the multi-omics analysis of the soil microbiome to advance our understanding of soil abiotic legacy effects.