Dylan O'Sullivan

Dr. Dylan O'Sullivan


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2022 in Clinical Gastroenterology and Hepatology
Verified
Journal Article
Closed access
DODylan O'Sullivan
Dylan O'Sullivan
RSR. Liam Sutherland
R. Liam Sutherland
STSusanna Town
Susanna Town
KCKristian Chow
Kristian Chow
JFJeremy Fan
Jeremy Fan
DBDarren R. Brenner
Darren R. Brenner

13 August 2021 in Current Oncology
Verified
Journal Article
Open access
PDF file
DODylan O'Sullivan
Dylan O'Sullivan
WCWinson Cheung
Winson Cheung
ISIqra A. Syed
Iqra A. Syed
DMDaniel Moldaver
Daniel Moldaver
MSMary Kate Shanahan
Mary Kate Shanahan
DBDevon Boyne
Devon Boyne
The prognosis for extensive-stage small cell lung cancer (ES-SCLC) is poor. Real-world evidence can highlight the unmet clinical need within this population. We conducted a population-based cohort study of ES-SCLC patients diagnosed in a large Canadian province (2010–2018) using electronic medical records and administrative claims data. In all, 1941 ES-SCLC patients were included, of which 476 (25%) were recurrent cases. Median age at diagnosis was 70 years (range: 39–94) and 50.2% were men. Of the 1941 ES-SCLC patients, 29.5% received chemotherapy and radiotherapy, 17.0% chemotherapy alone, 8.7% radiotherapy alone, and 44.8% received best supportive care. Chemotherapy was initiated by 46.5%, 8.5%, and 1.4% of first-, second-, and third-line patients, with lower uptake for recurrent cases. Median survival from first-, second-, and third-line chemotherapy was 7.82 months (95% CI: 7.50–8.22), 5.72 months (95% CI: 4.90–6.87), and 3.83 months (95% CI: 2.99–4.60). Among patients who received first-line therapy, the 2-year and 5-year survival was 7.3% (95% CI: 5.7–9.2) and 2.9% (95% CI: 1.8–4.5). In conclusion, initiation of first-line treatment in ES-SCLC was low with significant attrition in subsequent lines. These results underscore the need for effective front-line treatments and highlight the potential for novel therapies to improve patient outcomes.

1 November 2018 in Cancer Epidemiology, Biomarkers & Prevention
Verified
Journal Article
Open access
PDF file
DBDevon J. Boyne
Devon J. Boyne
DODylan O'Sullivan
Dylan O'Sullivan
BOBranko F. Olij
Branko F. Olij
WKWill D. King
Will D. King
CFChristine M. Friedenreich
Christine M. Friedenreich
DBDarren R. Brenner
Darren R. Brenner
The extent to which physical activity reduces breast cancer risk through changes in global DNA methylation is unknown. We systematically identified studies that investigated the association between: (i) physical activity and global DNA methylation; or (ii) global DNA methylation and breast cancer risk. Associations were quantified using random-effects models. Heterogeneity was investigated through subgroup analyses and the Q-test and I2 statistics. Twenty-four studies were reviewed. We observed a trend between higher levels of physical activity and higher levels of global DNA methylation [pooled standardized mean difference = 0.19; 95% confidence interval (CI), −0.03–0.40; P = 0.09] which, in turn, had a suggestive association with a reduced breast cancer risk (pooled relative risk = 0.70; 95% CI, 0.49–1.02; P = 0.06). In subgroup analyses, a positive association between physical activity and global DNA methylation was observed among studies assessing physical activity over long periods of time (P = 0.02). Similarly, the association between global DNA methylation and breast cancer was statistically significant for prospective cohort studies (P = 0.007). Despite the heterogeneous evidence base, the literature suggests that physical activity reduces the risk of breast cancer through increased global DNA methylation. This study is the first to systematically overview the complete biologic pathway between physical activity, global DNA methylation, and breast cancer. Cancer Epidemiol Biomarkers Prev; 27(11); 1320–31. ©2018 AACR.

12 March 2020 in BMC Cancer
Verified
Journal Article
Open access
PDF file
NMNicole E. Mealey
Nicole E. Mealey
DODylan O'Sullivan
Dylan O'Sullivan
JPJoy Pader
Joy Pader
YRYibing Ruan
Yibing Ruan
EWEdwin Wang
Edwin Wang
DBDarren R. Brenner
Darren R. Brenner
Background: The incidence of breast cancer among young women (aged ≤40 years) has increased in North America and Europe. Fewer than 10% of cases among young women are attributable to inheritedBRCA1orBRCA2mutations, suggesting an important role for somatic mutations. This study investigated genomic differences between young- and older-onset breast tumours.Methods: In this study we characterized the mutational landscape of 89 young-onset breast tumours (≤40 years) and examined differences with 949 older-onset tumours (> 40 years) using data from The Cancer Genome Atlas. We examined mutated genes, mutational load, and types of mutations. We used complementary R packages “deconstructSigs” and “SomaticSignatures” to extract mutational signatures. A recursively partitioned mixture model was used to identify whether combinations of mutational signatures were related to age of onset.Results: Older patients had a higher proportion of mutations inPIK3CA,CDH1, andMAP3K1genes, while young-onset patients had a higher proportion of mutations inGATA3andCTNNB1. Mutational load was lower for young-onset tumours, and a higher proportion of these mutations were C > A mutations, but a lower proportion were C > T mutations compared to older-onset tumours. The most common mutational signatures identified in both age groups were signatures 1 and 3 from the COSMIC database. Signatures resembling COSMIC signatures 2 and 13 were observed among both age groups. We identified a class of tumours with a unique combination of signatures that may be associated with young age of onset.Conclusions: The results of this exploratory study provide some evidence that the mutational landscape and mutational signatures among young-onset breast cancer are different from those of older-onset patients. The characterization of young-onset tumours could provide clues to their etiology which may inform future prevention. Further studies are required to confirm our findings.

1 April 2019 in Cancer Epidemiology
Verified
Journal Article
Closed access
DODylan O'Sullivan
Dylan O'Sullivan
DBDarren R. Brenner
Darren R. Brenner
PDPaul A. Demers
Paul A. Demers
PVPaul Villeneuve
Paul Villeneuve
CFChristine M. Friedenreich
Christine M. Friedenreich
WKWill D. King
Will D. King

3 July 2017 in Epigenetics
Verified
Journal Article
Open access
LSLucas A Salas
Lucas A Salas
KJKevin C. Johnson
Kevin C. Johnson
DKDevin C Koestler
Devin C Koestler
DODylan O'Sullivan
Dylan O'Sullivan
BCBrock C. Christensen
Brock C. Christensen
Genetic and epigenetic alterations are required for carcinogenesis and the mutation burden across tumor types has been investigated. Here, we investigate epigenetic alterations with a novel measure of global DNA methylation dysregulation, the methylation dysregulation index (MDI), across 14 cancer types in The Cancer Genome Atlas (TCGA) database. DNA methylation data—obtained using Illumina HumanMethylation450 BeadChip—was accessed from TCGA. We calculated the MDI in 14 tumor types (n = 5,592 tumors), using adjacent normal tissues (n = 701) from each tumor site. Copy number alteration, and mutation burden were retrieved from cBioportal (n = 5,152). We tested the relation of subject MDI across tumors and with age, gender, tumor stage, estimated tumor purity, and copy number alterations for both overall MDI and genomic-context-specific MDI. We also investigated the top most dysregulated loci shared across tumor types. There was a broad range of extent in methylation dysregulation across tumor types (P < 2.2E-16). However, a consistent pattern of methylation dysregulation stratified by genomic context was observed across tumor types where the highest dysregulation occurred at non-CpG island regions. Considering other summary measures of somatic alteration, MDI was correlated with copy number alterations but not with mutation burden. Using the top dysregulated CpG sites in common across tumors, 4 classes of cancer types were observed, and the functional consequences of these alterations to gene expression were confirmed. This work identified the global DNA methylation dysregulation patterns across 14 cancer types showing a higher impact for the non-CpG island areas. The most dysregulated loci across cancer types identified common clusters across cancer types that may have implications for future treatment and prevention measures.