Literature DB >> 26580488

Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models.

Qinghua Du1, Qingshan Li1, Daochun Sun2, Xiaoyan Chen1, Bizhen Yu1, Yi Ying1.   

Abstract

Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff.
© 2015 International Society for Advancement of Cytometry.

Keywords:  cell nucleus/genetics; fluorescence in situ hybridization; mathematical model; reference standards; spot counting

Mesh:

Substances:

Year:  2015        PMID: 26580488     DOI: 10.1002/cyto.a.22797

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  3 in total

1.  Diagnosing Cutaneous leishmaniasis using Fluorescence in Situ Hybridization: the Sri Lankan Perspective.

Authors:  Thilini Dilhara Jayasena Kaluarachchi; Manjula Manoji Weerasekera; Andrew J McBain; Shalindra Ranasinghe; Renu Wickremasinghe; Surangi Yasawardene; Nisal Jayanetti; Rajitha Wickremasinghe
Journal:  Pathog Glob Health       Date:  2019-08-20       Impact factor: 2.894

2.  Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features.

Authors:  Dongzhi Cen; Li Xu; Siwei Zhang; Zhiguang Chen; Yan Huang; Ziqi Li; Bo Liang
Journal:  Eur Radiol       Date:  2019-03-15       Impact factor: 5.315

3.  Diagnosing human cutaneous leishmaniasis using fluorescence in situ hybridization.

Authors:  Thilini Jayasena Kaluarachchi; Rajitha Wickremasinghe; Manjula Weerasekera; Surangi Yasawardene; Andrew J McBain; Bandujith Yapa; Hiromel De Silva; Chandranie Menike; Subodha Jayathilake; Anuradha Munasinghe; Renu Wickremasinghe; Shalindra Ranasinghe
Journal:  Pathog Glob Health       Date:  2021-03-09       Impact factor: 2.894

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.