How to Agree on a CTC: Evaluating the Consensus in Circulating Tumor Cell Scoring

Zeune, Leonie L.; Wit, Sanne de; Berghuis, A.M. Sofie; IJzerman, Maarten J.; Terstappen, Leon W.M.M.; Brüne, Christoph

doi:10.1002/cyto.a.23576

Cited by 36 publications

(33 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…39 The operator bias in CTC classification can be improved by providing quantitative information of the objects in the thumbnails and can be eliminated by the use of gates with the open-source ACCEPT software (http://github.com/LeonieZ/ ACCEPT). 14,[41][42][43] Further improvements in the classification of CTCs can be obtained through the use of deep learning; 44 however, for its implementation on larger data sets, significant improvements in the software are still needed. Therefore, in this study, we elected to use the original CTC scores of the studies.…”

Section: Discussionmentioning

confidence: 99%

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Nanou

Miller²,

Zeune

et al. 2020

Br J Cancer

Self Cite

View full text Add to dashboard Cite

BACKGROUND: Circulating tumour cells (CTCs) in blood associate with overall survival (OS) of cancer patients, but they are detected in extremely low numbers. Large tumour-derived extracellular vesicles (tdEVs) in castration-resistant prostate cancer (CRPC) patients are present at around 20 times higher frequencies than CTCs and have equivalent prognostic power. In this study, we explored the presence of tdEVs in other cancers and their association with OS. METHODS:The open-source ACCEPT software was used to automatically enumerate tdEVs in digitally stored CellSearch® images obtained from previously reported CTC studies evaluating OS in 190 CRPC, 450 metastatic colorectal cancer (mCRC), 179 metastatic breast cancer (MBC) and 137 non-small cell lung cancer (NSCLC) patients before the initiation of a new treatment. RESULTS: Presence of unfavourable CTCs and tdEVs is predictive of OS, with respective hazard ratios (HRs) of 2.4 and 2.2 in CRPC, 2.7 and 2.2 in MBC, 2.3 and 1.9 in mCRC and 2.0 and 2.4 in NSCLC, respectively. CONCLUSIONS: tdEVs have equivalent prognostic value as CTCs in the investigated metastatic cancers. CRPC, mCRC, and MBC (but not NSCLC) patients with favourable CTC counts can be further prognostically stratified using tdEVs. Our data suggest that tdEVs could be used in clinical decision-making.

show abstract

Section: Discussionmentioning

confidence: 99%

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Nanou

Miller²,

Zeune

et al. 2020

Br J Cancer

Self Cite

View full text Add to dashboard Cite

show abstract

“…Zeune et al. [56] reported that the manual counting for CTCs of prostate cancer and non‐small cell lung cancer on fluorescent images varied among human reviewers and counting platforms, whereas DL‐based CTC recognition was relatively stable with higher accuracy than the average level of human reviewers.…”

Section: Application Of Dl‐based Ai In Tumor Pathologymentioning

confidence: 99%

Emerging role of deep learning‐based artificial intelligence in tumor pathology

Jiang

Yue

Wang

et al. 2020

Cancer Communications

269

147

View full text Add to dashboard Cite

The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)-based AI, in tumor pathology. The DL-based algorithms have been developed to conduct all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction, as well as the identification of pathological features, biomarkers and genetic changes. The applications of AI in pathology not only contribute to improve diagnostic accuracy and objectivity but also reduce the workload of pathologists and subsequently enable them to spend additional time on high-level decision-making tasks. In addition, AI is useful for pathologists to meet the requirements of precision oncology. However, there are still some challenges relating to the implementation of AI, including the issues of algorithm validation and interpretability, computing systems, the unbelieving attitude of pathologists, clinicians and patients, as well as regulators and reimbursements. Herein, we present an overview on how AI-based approaches could be integrated into the workflow of pathologists and discuss the challenges and perspectives of the implementation of AI in tumor pathology.

show abstract

“…Capture of CTCs and tumorderived DNA samples for genetic, proteomic and other analyses has been termed "liquid biopsy" (26) since simple blood samples, often obtained repeatedly over time, yield information regarding otherwise difficult to access solid tissue tumors. Over the past years, multiple commercial platforms involving negative and positive immune and nonimmune-based identification of leukocyte and tumor antigens, respectively, were used in oncology, and recently efforts are underway to assess agreement across platforms and methods (28). Over the past years, multiple commercial platforms involving negative and positive immune and nonimmune-based identification of leukocyte and tumor antigens, respectively, were used in oncology, and recently efforts are underway to assess agreement across platforms and methods (28).…”

mentioning

confidence: 99%

“…Initial carcinoma CTC assays were immune-based using fluorescent antibodies to antigens widely expressed by epithelial cells, such as cytokeratin and cell adhesion molecules (27). Over the past years, multiple commercial platforms involving negative and positive immune and nonimmune-based identification of leukocyte and tumor antigens, respectively, were used in oncology, and recently efforts are underway to assess agreement across platforms and methods (28). The number of CTCs detected in humans with carcinoma is extremely low, and significant prognostic differences have been attributed to 3 versus 5 CTC/7.5 ml of blood (25,29).…”

mentioning

confidence: 99%

Flow Cytometric Detection of Circulating Osteosarcoma Cells in Dogs

et al. 2019

View full text Add to dashboard Cite

Osteosarcoma (OSA) is a malignant tumor of middle-aged dogs and adolescent humans. The clinical outcome of OSA has not improved over more than three decades, and dogs typically succumb to metastatic disease within 6 months despite tumor resection through limb amputation and adjuvant chemotherapy. Therefore, undetectable tumor cells with potential to form metastases are present at diagnosis. An assay to identify canine immortalized and primary OSA cells through flow cytometric detection of intracellular collagen 1 (Col I) and osteocalcin was optimized, and applied to blood samples from tumorbearing dogs for detection of circulating tumor cells (CTCs). Spiking variable number of OSA cells into normal dog blood recovered 50-60% of Col I positive cells with high forward and variable side light scatter. An algorithm to exclude nonviable, doublet, and autofluorescent cells was applied to sequential blood samples from three dogs obtained prior to and after limb amputation, and at approximately, triweekly intervals over 121, 142, and 183 days of chemotherapy, respectively. Dogs had >100 CTC/10 6 leukocytes prior to amputation, variably frequent CTC during chemotherapy, and an increase up to 4,000 CTC/10 6 leukocytes within 4 weeks before overt metastases or death. Sorted CTCs were morphologically similar to direct tumor aspirates and positive for Col I. Although preliminary, findings suggest that CTCs are frequent in canine OSA, more numerous than carcinoma CTC in humans, and that an increase in CTC frequency may herald clinical deterioration. This assay may enable enumeration and isolation of OSA CTC for prognostic and functional studies, respectively. OSTEOSARCOMA (OSA) is a primary bone cancer that is common in middle-aged to older, large breed dogs, and less common in humans, where children and young adults are most often affected. Therapy consisting of limb amputation or limbsparing tumor resection followed by chemotherapy (typically platinum or doxorubicin-based) is the gold standard, but the clinical outcome of OSA in dogs and humans remains poor (1-3). Dogs with OSA of the appendicular skeleton treated with amputation and chemotherapy had median survival times (STs) of 235-540 days (4), while in humans 5-year survival has been stagnant at about 60% (5). Although the median ST is relatively homogeneous, the range of ST in dogs with OSA treated identically varies from 2 to >30 months, illustrating that there is extensive heterogeneity in tumor biology and/or host response (6-8). Metastatic disease is the usual cause of spontaneous death or euthanasia, but fewer than 10% of dogs have radiographic evidence of metastasis at the time of diagnosis (2).Computed tomography also lacks sensitivity for identifying metastases, and histologic grading schemes for canine OSA poorly predict biological behavior (9-11).

show abstract

How to Agree on a CTC: Evaluating the Consensus in Circulating Tumor Cell Scoring

Cited by 36 publications

References 25 publications

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Emerging role of deep learning‐based artificial intelligence in tumor pathology

Flow Cytometric Detection of Circulating Osteosarcoma Cells in Dogs

Contact Info

Product

Resources

About