5′/ 3′ imbalance strategy to detect ALK fusion genes in circulating tumor RNA from patients with non-small cell lung cancer

Yongqing Tong, Zhijun Zhao, Bei Liu, Anyu Bao, Hongyun Zheng, Jian Gu, Mary McGrath, Ying Xia, Bihua Tan, Chunhua Song, Yan Li

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Detecting an ALK fusion gene in patients with non-small cell lung cancer (NSCLC) could provide evidence to guide individualized therapy. Methods: The 5′/3′ imbalance strategy for quantitative reverse transcription-PCR (RT-qPCR) was developed to detect ALK fusion genes in circulating tumor RNA (ctRNA) of NSCLC patients. Results: This method was validated in patients with the ALK fusion gene confirmed by next generation sequencing (NGS). The amount of the ALK fusion gene detected by the new method ranged from 33.2 to 987.4, (mean 315.2), in the patients confirmed to have the ALK fusion gene (+). This is much higher than the amount of fusion gene detected in the patients who are negative for the ALK fusion gene (-). The amount detected in the ALK fusion gene (-) samples ranged from 0.36 to 13.04, (mean 4.58). In 188 NSCLC patients, the specificity and sensitivity of the method was compared to that of the FISH method. About 10.64% of the patients showed higher ALK fusion gene expression, and were classified as ALK fusion gene (+). This is identical to the percentage of patients detected by the FISH method to be ALK fusion gene (+). The cutoff value for diagnosis of ALK fusion (+) is 32.9 as determined by this method. Conclusions: A new RT-PCR method using a 5′/3′ imbalance strategy was developed, with high specificity and sensitivity, for detection of the ALK fusion gene in ctRNA of NSCLC patients. This method can rapidly detect ALK fusion genes in patients, which will be helpful for guiding targeted therapy, particularly the individualized usage of TKIs in these patients.

Original languageEnglish (US)
Article number68
JournalJournal of Experimental and Clinical Cancer Research
Volume37
Issue number1
DOIs
StatePublished - Mar 27 2018

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Gene Fusion
Non-Small Cell Lung Carcinoma
RNA
Neoplasms
Sensitivity and Specificity
Polymerase Chain Reaction
Reverse Transcription

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

Cite this

Tong, Yongqing ; Zhao, Zhijun ; Liu, Bei ; Bao, Anyu ; Zheng, Hongyun ; Gu, Jian ; McGrath, Mary ; Xia, Ying ; Tan, Bihua ; Song, Chunhua ; Li, Yan. / 5′/ 3′ imbalance strategy to detect ALK fusion genes in circulating tumor RNA from patients with non-small cell lung cancer. In: Journal of Experimental and Clinical Cancer Research. 2018 ; Vol. 37, No. 1.
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abstract = "Background: Detecting an ALK fusion gene in patients with non-small cell lung cancer (NSCLC) could provide evidence to guide individualized therapy. Methods: The 5′/3′ imbalance strategy for quantitative reverse transcription-PCR (RT-qPCR) was developed to detect ALK fusion genes in circulating tumor RNA (ctRNA) of NSCLC patients. Results: This method was validated in patients with the ALK fusion gene confirmed by next generation sequencing (NGS). The amount of the ALK fusion gene detected by the new method ranged from 33.2 to 987.4, (mean 315.2), in the patients confirmed to have the ALK fusion gene (+). This is much higher than the amount of fusion gene detected in the patients who are negative for the ALK fusion gene (-). The amount detected in the ALK fusion gene (-) samples ranged from 0.36 to 13.04, (mean 4.58). In 188 NSCLC patients, the specificity and sensitivity of the method was compared to that of the FISH method. About 10.64{\%} of the patients showed higher ALK fusion gene expression, and were classified as ALK fusion gene (+). This is identical to the percentage of patients detected by the FISH method to be ALK fusion gene (+). The cutoff value for diagnosis of ALK fusion (+) is 32.9 as determined by this method. Conclusions: A new RT-PCR method using a 5′/3′ imbalance strategy was developed, with high specificity and sensitivity, for detection of the ALK fusion gene in ctRNA of NSCLC patients. This method can rapidly detect ALK fusion genes in patients, which will be helpful for guiding targeted therapy, particularly the individualized usage of TKIs in these patients.",
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5′/ 3′ imbalance strategy to detect ALK fusion genes in circulating tumor RNA from patients with non-small cell lung cancer. / Tong, Yongqing; Zhao, Zhijun; Liu, Bei; Bao, Anyu; Zheng, Hongyun; Gu, Jian; McGrath, Mary; Xia, Ying; Tan, Bihua; Song, Chunhua; Li, Yan.

In: Journal of Experimental and Clinical Cancer Research, Vol. 37, No. 1, 68, 27.03.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - 5′/ 3′ imbalance strategy to detect ALK fusion genes in circulating tumor RNA from patients with non-small cell lung cancer

AU - Tong, Yongqing

AU - Zhao, Zhijun

AU - Liu, Bei

AU - Bao, Anyu

AU - Zheng, Hongyun

AU - Gu, Jian

AU - McGrath, Mary

AU - Xia, Ying

AU - Tan, Bihua

AU - Song, Chunhua

AU - Li, Yan

PY - 2018/3/27

Y1 - 2018/3/27

N2 - Background: Detecting an ALK fusion gene in patients with non-small cell lung cancer (NSCLC) could provide evidence to guide individualized therapy. Methods: The 5′/3′ imbalance strategy for quantitative reverse transcription-PCR (RT-qPCR) was developed to detect ALK fusion genes in circulating tumor RNA (ctRNA) of NSCLC patients. Results: This method was validated in patients with the ALK fusion gene confirmed by next generation sequencing (NGS). The amount of the ALK fusion gene detected by the new method ranged from 33.2 to 987.4, (mean 315.2), in the patients confirmed to have the ALK fusion gene (+). This is much higher than the amount of fusion gene detected in the patients who are negative for the ALK fusion gene (-). The amount detected in the ALK fusion gene (-) samples ranged from 0.36 to 13.04, (mean 4.58). In 188 NSCLC patients, the specificity and sensitivity of the method was compared to that of the FISH method. About 10.64% of the patients showed higher ALK fusion gene expression, and were classified as ALK fusion gene (+). This is identical to the percentage of patients detected by the FISH method to be ALK fusion gene (+). The cutoff value for diagnosis of ALK fusion (+) is 32.9 as determined by this method. Conclusions: A new RT-PCR method using a 5′/3′ imbalance strategy was developed, with high specificity and sensitivity, for detection of the ALK fusion gene in ctRNA of NSCLC patients. This method can rapidly detect ALK fusion genes in patients, which will be helpful for guiding targeted therapy, particularly the individualized usage of TKIs in these patients.

AB - Background: Detecting an ALK fusion gene in patients with non-small cell lung cancer (NSCLC) could provide evidence to guide individualized therapy. Methods: The 5′/3′ imbalance strategy for quantitative reverse transcription-PCR (RT-qPCR) was developed to detect ALK fusion genes in circulating tumor RNA (ctRNA) of NSCLC patients. Results: This method was validated in patients with the ALK fusion gene confirmed by next generation sequencing (NGS). The amount of the ALK fusion gene detected by the new method ranged from 33.2 to 987.4, (mean 315.2), in the patients confirmed to have the ALK fusion gene (+). This is much higher than the amount of fusion gene detected in the patients who are negative for the ALK fusion gene (-). The amount detected in the ALK fusion gene (-) samples ranged from 0.36 to 13.04, (mean 4.58). In 188 NSCLC patients, the specificity and sensitivity of the method was compared to that of the FISH method. About 10.64% of the patients showed higher ALK fusion gene expression, and were classified as ALK fusion gene (+). This is identical to the percentage of patients detected by the FISH method to be ALK fusion gene (+). The cutoff value for diagnosis of ALK fusion (+) is 32.9 as determined by this method. Conclusions: A new RT-PCR method using a 5′/3′ imbalance strategy was developed, with high specificity and sensitivity, for detection of the ALK fusion gene in ctRNA of NSCLC patients. This method can rapidly detect ALK fusion genes in patients, which will be helpful for guiding targeted therapy, particularly the individualized usage of TKIs in these patients.

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