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Molecular characterization of a marine turtle tumor epizootic, profiling external, internal and postsurgical regrowth tumors.

ABSTRACT: Sea turtle populations are under threat from an epizootic tumor disease (animal epidemic) known as fibropapillomatosis. Fibropapillomatosis continues to spread geographically, with prevalence of the disease also growing at many longer-affected sites globally. However, we do not yet understand the precise environmental, mutational and viral events driving fibropapillomatosis tumor formation and progression.Here we perform transcriptomic and immunohistochemical profiling of five fibropapillomatosis tumor types: external new, established and postsurgical regrowth tumors, and internal lung and kidney tumors. We reveal that internal tumors are molecularly distinct from the more common external tumors. However, they have a small number of conserved potentially therapeutically targetable molecular vulnerabilities in common, such as the MAPK, Wnt, TGF? and TNF oncogenic signaling pathways. These conserved oncogenic drivers recapitulate remarkably well the core pan-cancer drivers responsible for human cancers. Fibropapillomatosis has been considered benign, but metastatic-related transcriptional signatures are strongly activated in kidney and established external tumors. Tumors in turtles with poor outcomes (died/euthanized) have genes associated with apoptosis and immune function suppressed, with these genes providing putative predictive biomarkers.Together, these results offer an improved understanding of fibropapillomatosis tumorigenesis and provide insights into the origins, inter-tumor relationships, and therapeutic treatment for this wildlife epizootic.

SUBMITTER: Yetsko K

PROVIDER: S-EPMC7851172 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Molecular characterization of a marine turtle tumor epizootic, profiling external, internal and postsurgical regrowth tumors.

Yetsko Kelsey K Farrell Jessica A JA Blackburn Nicholas B NB Whitmore Liam L Stammnitz Maximilian R MR Whilde Jenny J Eastman Catherine B CB Ramia Devon Rollinson DR Thomas Rachel R Krstic Aleksandar A Linser Paul P Creer Simon S Carvalho Gary G Devlin Mariana A MA Nahvi Nina N Leandro Ana Cristina AC deMaar Thomas W TW Burkhalter Brooke B Murchison Elizabeth P EP Schnitzler Christine C Duffy David J DJ

Communications biology 20210201 1

Sea turtle populations are under threat from an epizootic tumor disease (animal epidemic) known as fibropapillomatosis. Fibropapillomatosis continues to spread geographically, with prevalence of the disease also growing at many longer-affected sites globally. However, we do not yet understand the precise environmental, mutational and viral events driving fibropapillomatosis tumor formation and progression.Here we perform transcriptomic and immunohistochemical profiling of five fibropapillomatosi ...[more]

PMID: 33526843

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Project description:Rehabilitation of marine turtles in Queensland has multifaceted objectives. It treats individual animals, serves to educate the public, and contributes to conservation. We examined the outcome from rehabilitation, time in rehabilitation, and subsequent recapture and restranding rates of stranded marine turtles between 1996 and 2013 to determine if the benefits associated with this practice are cost-effective as a conservation tool. Of 13,854 marine turtles reported as stranded during this 18-year period, 5,022 of these turtles were stranded alive with the remainder verified as dead or of unknown condition. A total of 2,970 (59%) of these live strandings were transported to a rehabilitation facility. Overall, 1,173/2,970 (39%) turtles were released over 18 years, 101 of which were recaptured: 77 reported as restrandings (20 dead, 13 alive subsequently died, 11 alive subsequently euthanized, 33 alive) and 24 recaptured during normal marine turtle population monitoring or fishing activities. Of the turtles admitted to rehabilitation exhibiting signs of disease, 88% of them died, either unassisted or by euthanasia and 66% of turtles admitted for unknown causes of stranding died either unassisted or by euthanasia. All turtles recorded as having a buoyancy disorder with no other presenting problem or disorder recorded, were released alive. In Queensland, rehabilitation costs approximately $1,000 per animal per year admitted to a center, $2,583 per animal per year released, and $123,750 per animal per year for marine turtles which are presumably successfully returned to the functional population. This practice may not be economically viable in its present configuration, but may be more cost effective as a mobile response unit. Further there is certainly benefit giving individual turtles a chance at survival and educating the public in the perils facing marine turtles. As well, rehabilitation can provide insight into the diseases and environmental stressors causing stranding, arming researchers with information to mitigate negative impacts.

Project description:BackgroundPatients with localized prostate cancer have historically been assigned to clinical risk groups based on local disease extent, serum prostate specific antigen (PSA), and tumor grade. Clinical risk grouping is used to determine the intensity of treatment with external beam radiotherapy (EBRT) and androgen deprivation therapy (ADT), yet a substantial proportion of patients with intermediate and high risk localized prostate cancer will develop biochemical recurrence (BCR) and require salvage therapy. Prospective identification of patients destined to experience BCR would allow treatment intensification or selection of alternative therapeutic strategies.MethodsTwenty-nine individuals with intermediate or high risk prostate cancer were prospectively recruited to a clinical trial designed to profile the molecular and imaging features of prostate cancer in patients undergoing EBRT and ADT. Whole transcriptome cDNA microarray and whole exome sequencing were performed on pretreatment targeted biopsy of prostate tumors (n=60). All patients underwent pretreatment and 6-month post EBRT multiparametric MRI (mpMRI), and were followed with serial PSA to assess presence or absence of BCR. Genes differentially expressed in the tumor of patients with and without BCR were investigated using pathways analysis tools and were similarly explored in alternative datasets. Differential gene expression and predicted pathway activation were evaluated in relation to tumor response on mpMRI and tumor genomic profile. A novel TGF-β gene signature was developed in the discovery dataset and applied to a validation dataset.FindingsBaseline MRI lesion volume and PTEN/TP53 status in prostate tumor biopsies correlated with the activation state of TGF-β signaling measured using pathway analysis. All three measures correlated with the risk of BCR after definitive RT. A prostate cancer-specific TGF-β signature discriminated between patients that experienced BCR vs. those that did not. The signature retained prognostic utility in an independent cohort.InterpretationTGF-β activity is a dominant feature of intermediate-to-unfavorable risk prostate tumors prone to biochemical failure after EBRT with ADT. TGF-β activity may serve as a prognostic biomarker independent of existing risk factors and clinical decision-making criteria.FundingThis research was supported by the Prostate Cancer Foundation, the Department of Defense Congressionally Directed Medical Research Program, National Cancer Institute, and the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

Project description:Objectives: The complexity and specificity of lung tumor motion render it necessary to determine the external and internal correlation individually before applying indirect tumor tracking. However, the correlation cannot be determined from patient respiratory and tumor clinical characteristics before treatment. The purpose of this study is to present a machine learning model for an external/internal correlation prediction that is based on computed tomography (CT) radiomic features. Methods: 4-dimensional computed tomography (4DCT) images of 67 patients were collected retrospectively, and the external/internal correlation of lung tumor was calculated based on Spearman's rank correlation coefficient. Radiomic features were extracted from average intensity projection and the light gradient boosting machine (LightGBM)-based cross-validation (the recursive elimination method) was used for feature selection. The LightGBM framework forecasting models with classification thresholds 0.7, 0.8, and 0.9 are established using stratified 5-fold cross-validation. Model performance was assessed using receiver operating characteristics, sensitivity, and specificity. Results: There were 16, 18, and 13 features selected for models 0.7, 0.8, and 0.9, respectively. Texture features are of great importance in external/internal correlation prediction compared to other features in all models. The sensitivities of the predictions in models 0.7, 0.8, and 0.9 were 0.800 ± 0.126, 0.829 ± 0.140, and 0.864 ± 0.086, respectively. The specificities were 0.771 ± 0.114, 0.936 ± 0.0581, and 0.839 ± 0.101, whereas the area under the curve (AUC) was 0.837, 0.946, and 0.877, respectively. Conclusions: Our findings indicate that radiomics is an effective tool for respiratory motion correlation prediction, which can extract tumor motion characteristics. We proposed a machine learning framework for correlation prediction in the motion management strategy for lung tumor patients.

Dataset Information

Molecular characterization of a marine turtle tumor epizootic, profiling external, internal and postsurgical regrowth tumors.

Publications

Molecular characterization of a marine turtle tumor epizootic, profiling external, internal and postsurgical regrowth tumors.

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