Biology subjects

Devlin, S. M.

Publications and source records attributed to Devlin, S. M..

4 recordsLinked to original sources

bioRxiv2024

Targetable Treatment Resistance in Thyroid Cancer with Clonal Hematopoiesis

Anaplastic thyroid cancer (ATC) is a clinically aggressive malignancy with a dismal prognosis. Combined BRAF/MEK inhibition offers significant therapeutic benefit in patients with BRAFV600E-mutant ATCs. However, relapses are common and overall survival remains poor. Compared with differentiated thyroid cancer, a hallmark of ATCs is significant infiltration with myeloid cells, particularly macrophages. ATCs are most common in the aging population, which also has an increased incidence of TET2-mutant clonal hematopoiesis (CH). CH-mutant macrophages have been shown to accelerate CH-associated pathophysiology including atherosclerosis. However, the clinical and mechanistic contribution of CH-mutant clones to solid tumour biology, prognosis and therapeutic response has not been elucidated. Here we show that TET2-mutant CH is enriched in the tumour microenvironment of patients with solid tumours and associated with adverse prognosis in ATC patients. We find that Tet2-mutant macrophages selectively infiltrate mouse BrafV600E-mutant ATC and that their overexpression of Tgf{beta}-family ligands mediates resistance to BRAF/MEK inhibition. Importantly, inhibition of Tgf{beta} signaling restores sensitivity to MAPK pathway inhibition, opening a path for synergistic strategies to improve outcomes of patients with ATCs and concurrent CH.

cancer biology↗

bioRxiv2023

Scalable Log-ratio Lasso Regression Enhances Microbiome Feature Selection for Predictive Models

Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL (https://vdblab.github.io/FLORAL/), an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility of longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance testing methods for datasets with smaller sample size. In a survival analysis in allogeneic hematopoietic-cell transplant, we further demonstrated considerable improvement by FLORAL in microbial feature selection by utilizing longitudinal microbiome data over only using baseline microbiome data.

bioinformatics↗

bioRxiv2019

Implications of TP53 Allelic State for Genome Stability, Clinical Presentation and Outcomes in Myelodysplastic Syndromes

TP53 mutations are associated with poor clinical outcomes and treatment resistance in myelodysplastic syndromes. However, the biological and clinical relevance of the underlying mono- or bi-allelic state of the mutations is unclear. We analyzed 3,324 MDS patients for TP53 mutations and allelic imbalances of the TP53 locus and found that 1 in 3 TP53-mutated patients had mono-allelic targeting of the gene whereas 2 in 3 had multiple hits consistent with bi-allelic targeting. The established associations for TP53 with complex karyotype, high-risk presentation, poor survival and rapid leukemic transformation were specific to patients with multi-hit state only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System, while mono-allelic patients did not differ from TP53 wild-type patients. The separation by allelic state was retained in therapy-related MDS. Findings were validated in a cohort of 1,120 patients. Ascertainment of TP53 allelic state is critical for diagnosis, risk estimation and prognostication precision in MDS, and future correlative studies of treatment response should consider TP53 allelic state.

genomics↗

bioRxiv2019

Oncologic Therapy Shapes the Fitness Landscape of ClonalHematopoiesis

Clonal hematopoiesis (CH) is frequent in cancer patients and associated with increased risk of therapy related myeloid neoplasms (tMN). To define the relationship between CH, oncologic therapy, and tMN progression, we studied 24,439 cancer patients. We show that previously treated patients have increased rates of CH, with enrichment of mutations in DNA Damage Response (DDR) genes (TP53, PPM1D, CHEK2). Exposure to radiation, platinum and topoisomerase II inhibitors have the strongest association with CH with evidence of dose-dependence and gene-treatment interactions. We validate these associations in serial sampling from 525 patients and show that exposure to cytotoxic and radiation therapy imparts a selective advantage specifically in hematopoietic cells with DDR mutations. In patients who progressed to tMN, the clone at CH demarcated the dominant clone at tMN diagnosis. CH mutational features predict risk of therapy-related myeloid neoplasm in solid tumor patients with clinical implications for early detection and treatment decisions.

genetics↗