Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning

Makielski, Kelly M.; Donnelly, Alicia J.; Khammanivong, Ali; Scott, Milcah C.; Ortiz, Andrea R; Galvan, Dana; Tomiyasu, Hirotaka; Amaya, Clarissa; Ward, Kristin; Montoya, Alexa; Garbe, John; Mills, Lauren J.; Cutter, Gary; Fenger, Joelle M.; Kisseberth, William C.; O’Brien, Timothy; Weigel, Brenda; Spector, Logan G.; Bryan, Brad Allen; Subramanian, Subbaya; Modiano, Jaime F.

doi:10.1038/s41374-021-00655-w

Cited by 6 publications

(3 citation statements)

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“…One example is the Shine-On project 169,170 (Figure 5), where we have developed a blood test to detect rare events associated with the presence (or risk) of hemangiosarcoma (a malignant tumor of blood vessel-forming cells that is relatively common in dogs), and which is meant to be used once dogs reach an age where risk for this cancer is meaningful (i.e., older than 6 years). 12,142,171,172 Another example from our group is a serum exosomal mRNA signature associated with the presence of osteosarcoma 173 that is currently being investigated for early detection in at-risk breeds of dogs. By design, these early detection and risk assessment tests would be F I G U R E 5 The Shine-On concept of paired early detection and strategic prevention.…”

Section: If Cancer Is Virtually Inevitable What Is the Solutionmentioning

confidence: 99%

Increased risk of cancer in dogs and humans: A consequence of recent extension of lifespan beyond evolutionarily determined limitations?

et al. 2022

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Cancer is among the most common causes of death for dogs (and cats) and humans in the developed world, even though it is uncommon in wildlife and other domestic animals. We provide a rationale for this observation based on recent advances in our understanding of the evolutionary basis of cancer. Over the course of evolutionary time, species have acquired and fine-tuned adaptive cancer-protective mechanisms that are intrinsically related to their energy demands, reproductive strategies, and expected lifespan. These cancer-protective mechanisms are general across species and/or specific to each species and their niche, and they do not seem to be limited in diversity. The evolutionarily acquired cancer-free longevity that defines a species' life history can explain why the relative cancer risk, rate, and incidence are largely similar across most species in the animal kingdom despite differences in body size and life expectancy. The molecular, cellular, and metabolic events that promote malignant transformation and cancerous growth can overcome these adaptive, species-specific protective mechanisms in a small proportion of individuals, while independently, some individuals in the population might achieve exceptional longevity. In dogs and humans, recent dramatic alterations in healthcare and social structures have allowed increasing numbers of individuals in both species to far exceed their species-adapted longevities (by two to four times) without allowing the time necessary for compensatory natural selection. In other words, the cancer-protectiveThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: If Cancer Is Virtually Inevitable What Is the Solutionmentioning

confidence: 99%

Increased risk of cancer in dogs and humans: A consequence of recent extension of lifespan beyond evolutionarily determined limitations?

et al. 2022

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“…Despite decades of intensive research and multicenter clinical trials, the persistence of poor clinical outcomes for metastatic and relapse disease suggests that current methods may not be sensitive enough in detecting persistent minimal residual disease (MRD) [ 7 , [10] , [11] , [12] , [13] , [14] , [15] , [16] ]. This small load of cancer cells that escape detection by conventional tests may persist in patients who have achieved clinical remission, putting them at risk of relapse.…”

Section: Introductionmentioning

confidence: 99%

Exosomal mRNA Cargo are biomarkers of tumor and immune cell populations in pediatric osteosarcoma

Ong,

Jalaludin,

Wong

et al. 2024

Translational Oncology

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“…This type of tumor consists of a higher extent of malignity and is vulnerable to the lungs and metastases; as such, its medication seems to be very complex. Initial identification and medication could improve the survival rate of patients and decrease the chances of amputation [ 3 ]. In clinical prognoses, MRI images cannot pose significant biological and radiation hazards to the tissue in the course of inspection and are very apparent in tissue elements, such as the blood vessels and tumors [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model

2022

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Osteosarcoma is a kind of bone cancer which generally starts to develop in the lengthy bones in the legs and arms. Because of an increase in occurrence of cancer and patient-specific treatment options, the detection and classification of cancer becomes a difficult process. The manual recognition of osteosarcoma necessitates expert knowledge and is time consuming. An earlier identification of osteosarcoma can reduce the death rate. With the development of new technologies, automated detection models can be exploited for medical image classification, thereby decreasing the expert’s reliance and resulting in timely identification. In recent times, an amount of Computer-Aided Detection (CAD) systems are available in the literature for the segmentation and detection of osteosarcoma using medicinal images. In this view, this research work develops a wind driven optimization with deep transfer learning enabled osteosarcoma detection and classification (WDODTL-ODC) method. The presented WDODTL-ODC model intends to determine the presence of osteosarcoma in the biomedical images. To accomplish this, the osteosarcoma model involves Gaussian filtering (GF) based on pre-processing and contrast enhancement techniques. In addition, deep transfer learning using a SqueezNet model is utilized as a featured extractor. At last, the Wind Driven Optimization (WDO) algorithm with a deep-stacked sparse auto-encoder (DSSAE) is employed for the classification process. The simulation outcome demonstrated that the WDODTL-ODC technique outperformed the existing models in the detection of osteosarcoma on biomedical images.

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Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning

Cited by 6 publications

References 44 publications

Increased risk of cancer in dogs and humans: A consequence of recent extension of lifespan beyond evolutionarily determined limitations?

Increased risk of cancer in dogs and humans: A consequence of recent extension of lifespan beyond evolutionarily determined limitations?

Exosomal mRNA Cargo are biomarkers of tumor and immune cell populations in pediatric osteosarcoma

Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model

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