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Poster Display session 3

4945 - Liquid biopsy and Array Comparative Genomic Hybridization (aCGH)

Date

30 Sep 2019

Session

Poster Display session 3

Topics

Translational Research

Tumour Site

Presenters

Panagiotis Apostolou

Citation

Annals of Oncology (2019) 30 (suppl_5): v574-v584. 10.1093/annonc/mdz257

Authors

P. Apostolou, D. Ntanovasilis, I. Papasotiriou

Author affiliations

  • Research & Development, Research Genetic Cancer Centre S.A., 53100 - Florina/GR

Resources

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Abstract 4945

Background

Cancer of unknown primary origin (CUP) represents a metastatic cancer with unidentified primary origin. An efficient cancer treatment algorithm is based on detection and characterization of the tumor’s origin. CUP is characterized by chromosomal instability; therefore the detection of chromosomal aberrations might contribute in tumor characterization. aCGH combines DNA microarray with CGH providing better detection rates than conventional cytogenetic methods. The present study aimed to evaluate aCGH as a technique for detection the origin of tumor, based on liquid biopsy and particular in circulating tumor cells.

Methods

Blood samples were collected from five patients suffering from prostate (2), lung (2) and breast (1) cancer and five healthy individuals. CTCs isolated using enrichment protocols while CD45 (-ve) cells isolated from healthy individuals. In addition to patients’ samples, six commercial cancer cell lines provided by ECACC were used, representing prostate and lung cancer (DU145, 22Rv1, LNcaP, COLO699N, COR0L 105 and MOR). Genomic DNA extracted and aCGH experiments followed with Sureprint G3 platform (Agilent). The genes located in chromosomal aberrations were literately analyzed and potential cancer type suggested by another researcher. The researcher performed the analysis based only on aCGH raw data, ignoring the identity and medical history of all samples. Samples firstly analyzed based on normal vs cancer prediction and secondly whether the predicted type of cancer was correct.

Results

The sensitivity was around 90% while the specificity was 80%. Among eleven cancer samples only one predicted as normal, as well as one normal sample predicted as cancer. As far as the cancer type prediction the positive predictive value was 90.1%. Only one sample categorized wrongly in total cancer samples.

Conclusions

aCGH is a powerful technique with potential of discrimination of cancer and healthy samples, but most important with ability to distinguish the type of cancer. The identification of primary origin of cancer is very important in CUP, since it is correlated with more efficient treatment algorithm. The above encouraging data from the combination of aCGH and liquid biopsy need to be validated in more samples and types of cancer so to be used at clinical level.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Research Genetic Cancer Centre S.A.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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