Analysis of Single Circulating Tumor Cells in Renal Cell Carcinoma Reveals Phenotypic Heterogeneity and Genomic Alterations Related to Progression

Cappelletti, Vera; Verzoni, Elena; Ratta, Raffaele; Vismara, Marta; Silvestri, M.; Montone, Rosanna; Miodini, Patrizia; Reduzzi, Carolina; Claps, Mélanie; Sepe, Pierangela; Daidone, Maria Grazia; Procopio, Giuseppe

doi:10.3390/ijms21041475

Cited by 29 publications

(32 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CTC heterogeneity has been shown and described in other tumor entities (21)(22)(23)(24). We also found a diverse population of CTC in a pilot study of 20 EAC patients undergoing multimodal treatment (14).…”

supporting

confidence: 66%

Cytopathological Heterogeneity of Circulating Tumor Cells in Non-metastatic Esophageal Adenocarcinoma

et al. 2020

View full text Add to dashboard Cite

Background/Aim: The presence of circulating tumor cells (CTC) has been reported to have an impact on prognosis in different tumor entities. Little is known about CTC morphology and heterogeneity. Patients and Methods: In a multicenter setting, pre-therapeutic peripheral blood specimens were drawn from patients with non-metastatic esophageal adenocarcinoma (EAC). CTCs were captured by size-based filtration (ScreenCell ®), subsequently Giemsa-stained and evaluated by two trained readers. The isolated cells were categorized in groups based on morphologic criteria. Results: Small and large single CTCs, as well as CTC-clusters, were observed in 69.2% (n=81) of the 117 specimens; small CTCs were observed most frequently (59%; n=69), followed by large CTCs (40%; n=47) and circulating cancer-associated macrophage-like cells (CAMLs; 34.2%, n=40). Clusters were rather rare (12%; n=14). CTC/CAML were heterogeneous in the cohort, but also within one specimen. Neither the presence of the CTC subtypes/CAMLs nor the exact cell count were associated with the primary clinical TNM stage. Conclusion: Morphologically heterogenic CTCs and CAMLs are present in patients with non-metastatic, non-pretreated EAC. Over the past decades the incidence of esophageal squamous cell carcinoma has decreased significantly in the U.S. and Europe. At the same time, the incidence of adenocarcinoma (EAC) has increased rapidly, especially among men (1). Although overall survival has improved over the years thanks to new treatment strategies, the prognosis is still limited (2). We still lack tools for better pre-therapeutic risk-stratification for cancer recurrence, which would enable us to design patientadapted treatment strategies. Currently, treatment decisions are being made based on CT-scans, endoscopic findings, endoscopic ultrasound and tumor biopsy. This momentary pretherapeutic "tumor-image" of the patient does not adequately reflect the actual tumor biology and aggressiveness. More than 50% of the patients initially considered curable will eventually relapse or develop metastasis after complete resection of the tumor (3). This relapse could be due to clinically invisible distant micro-metastases and tumor dissemination at an early time point, or due to lack of treatment response. A promising tool to evaluate these occult metastases for risk stratification and treatment surveillance is the use of liquid biopsy (4). Liquid biopsy summarizes the analysis of tumor cells and tumor-derived products in body fluids, like circulating tumor cells (CTC) (5-7), circulating tumor DNA (ctDNA) (8, 9) and extracellular vesicles (EVs) (10-12). In the case of EAC, there are very limited studies available regarding CTC presence and their significance in general (5, 13-16). CTC have been found in about 20% of patients using epithelial surface antigen (EpCAM)-dependent isolation devices in EAC. These patients 5679 This article is freely accessible online.

show abstract

supporting

confidence: 66%

Cytopathological Heterogeneity of Circulating Tumor Cells in Non-metastatic Esophageal Adenocarcinoma

et al. 2020

View full text Add to dashboard Cite

show abstract

“…For future work, the CTC count information from RCC patients can also be combined with molecular characterization for clinical applications. Recent studies 29,49 have shown that single-cell molecular characterization for CTC from RCC patients can unravel the information of clonal evolution. Characterization of CTCs that combines molecular characterization and statistical analysis by CellSearch during therapy can offer important information for the treatment selection for breast cancer patients 50 .…”

Section: Resultsmentioning

confidence: 99%

“…For example, CellSearch (Menarini Silicon Biosystems), an FDA-approved platform for CTC identification, is based on the overexpression of CK and EpCAM. However, detection of some types of CTCs such as CTCs in renal cell carcinoma (RCC) is limited by the lack of epithelial differentiation 28 , 29 . RCC shows low expression of epithelial markers, so such type of CTCs cannot be captured by labeling methods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Label-free detection of rare circulating tumor cells by image analysis and machine learning

Shen

Zhou

Qin

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Detection and characterization of rare circulating tumor cells (ctcs) in patients' blood is important for the diagnosis and monitoring of cancer. The traditional way of counting CTCs via fluorescent images requires a series of tedious experimental procedures and often impacts the viability of cells. Here we present a method for label-free detection of ctcs from patient blood samples, by taking advantage of data analysis of bright field microscopy images. The approach uses the convolutional neural network, a powerful image classification and machine learning algorithm to perform label-free classification of cells detected in microscopic images of patient blood samples containing white blood cells and ctcs. it requires minimal data pre-processing and has an easy experimental setup. through our experiments, we show that our method can achieve high accuracy on the identification of rare CTCs without the need for advanced devices or expert users, thus providing a faster and simpler way for counting and identifying ctcs. With more data becoming available in the future, the machine learning model can be further improved and can serve as an accurate and easy-to-use tool for ctc analysis. Circulating tumor cells (CTCs) found in peripheral blood are originated from solid tumors. They are cells shed by a primary tumor into the vasculature, circulating through bloodstream of cancer patients, and colonizing at distant sites which may form metastatic tumors 1. CTCs are an important biomarker for early tumor diagnosis and early evaluation of disease recurrence and metastatic spread in various types of cancer 2-6. Early detection of CTCs provides high chances for patients to survive before severe cancer growth occurs 7. The CTC count is also an important prognostic factor for patients with metastatic cancer 8-12. For example, a study has shown that the number of CTCs is an independent predictor of survival in patients for breast cancer and prostate cancer 8-10 , and the changes of the CTC count predict the survival in patients for lung cancer 12. However, the identification of the CTCs population is a challenging problem. Various approaches to identifying and isolating CTCs including antibody-based methods and physical-characteristics-based methods have been developed 13-19. This task is difficult because of the low concentration of CTCs existing in a patient's peripheral blood-a few CTCs out of 10 billion blood cells 20,21 , as well as heterogeneity in the characteristics of CTCs 22,23. For example, the mechanism of CTCs maintaining metastatic potential during circulating is not well understood 24 ; CTCs derived from some patients allow a cell line to be established, but CTCs from some others lose the capability of proliferation after a few hours of blood drawing 13. Therefore, the incapability to draw a large volume of blood from patients leads to the need for improvements of CTC isolation methods so that CTCs can be detected in small sample volumes. Further, the inconsistency in the viability of CTCs hinders further explorati...

show abstract

“…Two patients with detectable epithelial CTCs prior to systemic treatment start exhibited short PFS, however the positivity rate of non-epithelial CTCs was higher than conventional/epithelial CTCs. Again, CTC analysis at single-cell level in a case study showed genomic alterations (9p21.3 loss) known as drivers of metastases, thus potentially triggering cancer progression [ 97 ].…”

Section: Renal Cell Carcinomamentioning

confidence: 99%

Update on Circulating Tumor Cells in Genitourinary Tumors with Focus on Prostate Cancer

Cimadamore

Aurilio

Nolè

et al. 2020

Cells

View full text Add to dashboard Cite

Current developments in the treatment of genitourinary tumors underline the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting. The detection of circulating tumor cells (CTCs) has become one of the most exciting and important new approaches to identifying biomarkers at different stages of disease in a non-invasive way. Potential applications of CTCs include monitoring treatment efficacy and early detection of progression, selecting tailored therapies, as well as saving treatment costs. However, despite the promising implementation of CTCs in a clinical scenario, the isolation and characterization of these cells for molecular studies remain expensive with contemporary platforms, and significant technical challenges still need to be overcome. This updated, critical review focuses on the state of CTCs in patients with genitourinary tumor with focus on prostate cancer, discussing technical issues, main clinical results and hypothesizing potential future perspectives in clinical scenarios.

show abstract

Analysis of Single Circulating Tumor Cells in Renal Cell Carcinoma Reveals Phenotypic Heterogeneity and Genomic Alterations Related to Progression

Cited by 29 publications

References 36 publications

Cytopathological Heterogeneity of Circulating Tumor Cells in Non-metastatic Esophageal Adenocarcinoma

Cytopathological Heterogeneity of Circulating Tumor Cells in Non-metastatic Esophageal Adenocarcinoma

Label-free detection of rare circulating tumor cells by image analysis and machine learning

Update on Circulating Tumor Cells in Genitourinary Tumors with Focus on Prostate Cancer

Contact Info

Product

Resources

About