Detection of circulating tumor-derived material in peripheral blood of pediatric sarcoma patients: A systematic review

Kjær, Eva Kristine Ruud; Vase, Christian Bach; Rossing, Maria; Ahlborn, Lise Barlebo; Hjalgrim, Lisa Lyngsie

doi:10.1016/j.tranon.2023.101690

Cited by 5 publications

(1 citation statement)

References 111 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this therapeutic pipeline, the process of deciding on each of these tasks is greatly influenced by medical imaging. To identify suspicious tumors, gauge the likelihood of malignancy, and assess the prognosis for cancer, radiologists traditionally use descriptive or partially quantitative material visually gleaned from medical pictures 8 . Information that is clinically significant might involve patterns of improvement, the existence or inability of necrosis or bleeding, the density and size of suspicious tumors, tumor border fringe speculation, or the position of the distrustful tumor.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence - A Primer for Diagnosis and Interpretation of Breast Cancer

Mohan Jha,

Prasada Kumar Mahapatra,

Abraham

et al. 2024

Int J Tre Onc Sci

View full text Add to dashboard Cite

Breast Cancer (BC) is a major universal health problem. Early detection and precise diagnosis are vital for enlightening outcomes. Artificial Intelligence (AI) technologies can potentially revolutionize the field of BC by providing quantitative representations of medical images to assist in segmentation, diagnosis, and prognosis. AI can improve image quality, detect and segment breast lesions, classify cancer and predict its behavior, and integrate data from multiple sources to predict clinical outcomes. It can lead to more personalized and effective treatment for BC patients. Challenges faced by AI in real-life solicitations include data curation, model interpretability, and run-through guidelines. However, the clinical implementation of AI is expected to deliver vital guidance for patient-tailored management. BC is a major global health problem; early detection and treatment are crucial for improving outcomes. Imaging detection is a key screening, diagnosis, and treatment effectiveness assessment tool. However, the irresistible number of images creates a heavy capacity for radiologists and delays reporting. AI has the potential to revolutionize BC imaging by improving efficiency and accuracy. AI can recognize, segment, and diagnose tumor lesions automatically and analyze tumor images on a molecular level. It could lead to more personalized treatment strategies. However, AI-assisted imaging diagnosis is still in its early stages of development, and more research is needed to validate its clinical effectiveness. Therefore, AI is a promising new technology that has the potential to progress the diagnosis and treatment of BC, and AI-assisted imaging diagnosis is a promising new technology for improving the early detection and diagnosis of BC. More research is needed to bring this technology to clinical practice.

show abstract

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence - A Primer for Diagnosis and Interpretation of Breast Cancer

Mohan Jha,

Prasada Kumar Mahapatra,

Abraham

et al. 2024

Int J Tre Onc Sci

View full text Add to dashboard Cite

show abstract

Sarcomas: Genetics, Cytogenetics, and Liquid Biopsy

Delmonico,

Chantre-Justino,

Alves

2024

Interdisciplinary Cancer Research

View full text Add to dashboard Cite

Phase II Trial of Gemcitabine and Nab-Paclitaxel for Recurrent Osteosarcoma with Serial Monitoring Using Liquid Biopsy: A Report from the National Pediatric Cancer Foundation

Dhir,

Hayashi,

Bodlak

et al. 2024

Clinical Cancer Research

View full text Add to dashboard Cite

Background: The combination of gemcitabine and docetaxel is often used to treat patients with recurrent osteosarcoma. Nab-paclitaxel has preclinical activity against osteosarcoma and is potentially less myelosuppressive than docetaxel. We conducted a prospective multi-institutional phase II trial combining gemcitabine and nab-paclitaxel for patients 12-30 years with recurrent osteosarcoma and measurable disease. Methods: A Simon’s two-stage design was used to test a 4-month progression-free survival (PFS-4) of 10% vs. 35%. Patients received nab-paclitaxel 125 mg/m2 and gemcitabine 1000 mg/m2 weekly x 3 in 4-week cycles. Immunohistochemical analysis of archival tissue and serial assessment of circulating tumor cells (CTC) and circulating tumor DNA (ctDNA) using ultralow passage whole-genome sequencing were performed to identify potential biomarkers of response. Results: Eighteen patients received 56 total cycles (median 2, range 1 – 12). Two patients (11%) experienced confirmed partial response, and 6 (33%) received > 2 cycles. The PFS-4 was 28% (95% CI 13-59%). Six patients required dose reductions and three patients were removed due to toxicities. All 18 patients had detectable CTCs, and 10 had ctDNA identified. All 8 patients with MYC amplification at study-entry experienced disease progression. Conclusions: Gemcitabine and nab-paclitaxel demonstrated similar clinical activity and toxicity compared to previous retrospective reports utilizing gemcitabine and docetaxel in patients with recurrent osteosarcoma. Serial analysis of CTC and ctDNA was feasible in this prospective multi-institution study and provides preliminary data on the use of these assays in patients with relapsed disease.

show abstract

Detection of circulating tumor-derived material in peripheral blood of pediatric sarcoma patients: A systematic review

Cited by 5 publications

References 111 publications

Artificial Intelligence - A Primer for Diagnosis and Interpretation of Breast Cancer

Artificial Intelligence - A Primer for Diagnosis and Interpretation of Breast Cancer

Sarcomas: Genetics, Cytogenetics, and Liquid Biopsy

Phase II Trial of Gemcitabine and Nab-Paclitaxel for Recurrent Osteosarcoma with Serial Monitoring Using Liquid Biopsy: A Report from the National Pediatric Cancer Foundation

Contact Info

Product

Resources

About