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Non-invasive Analysis of Genomic Copy Number Variation in Patients with Hepatocellular Carcinoma by Next Generation DNA Sequencing.

Xu H, Zhu X, Xu Z, Hu Y, Bo S, Xing T, Zhu K - J Cancer (2015)

Bottom Line: Plasma samples from 31 patients with HCC and 8 patients with chronic hepatitis or cirrhosis were analyzed.CNV Z score analysis showed significant CNVs in samples with HCC and chronic liver diseases although more significant changes were found in HCC group, some are differentially valuable (such as gain in 1q, 7q, and 19q in HCC), while others are less differentially valuable (such as loss in 4q, 13q, gain in 17q, 22q).Although CNV analysis itself cannot establish the diagnosis, it can help identify patients at high risk for HCC among patients with chronic liver diseases, which would prompt closer and more frequent surveillance for early tumor detection and intervention.

View Article: PubMed Central - PubMed

Affiliation: 1. Department of Infectious Diseases, Taizhou People's Hospital, Taizhou, Jiangsu, China.

ABSTRACT
To explore new molecular diagnosis approaches for early detection and differential diagnosis of hepatocellular carcinoma (HCC), we analyzed genomic copy number variations (CNV) using plasma cell-free DNA from patients with HCC by next generation DNA sequencing. Plasma samples from 31 patients with HCC and 8 patients with chronic hepatitis or cirrhosis were analyzed. In HCC group, most samples with large tumor size (tumor dimension greater than 50 mm) showed CNVs that are visually recognizable at chromosome CNV plots, few samples with small tumor and none samples with chronic liver diseases showed CNVs recognizable at CNV plots. CNV Z score analysis showed significant CNVs in samples with HCC and chronic liver diseases although more significant changes were found in HCC group, some are differentially valuable (such as gain in 1q, 7q, and 19q in HCC), while others are less differentially valuable (such as loss in 4q, 13q, gain in 17q, 22q). We proposed a CNV scoring method that generated positive result in 26 of the 31 HCC patients (83.9%) or 11 of the 16 HCC with tumor dimension 50 mm or less (68.8%) or 4 of the 7 HCC with tumor dimension 30 mm or less (57.1%), while all the 8 samples with chronic hepatitis or cirrhosis scored negative. Ten HCC patients had normal or low serum AFP levels, among them, 7 were scored positive by CNV analysis, including 4 with tumor dimension 50 mm or less. Our study suggested that non-invasive genomic CNV analysis using plasma samples could be a valuable tool for early detection and differential diagnosis of HCC. Although CNV analysis itself cannot establish the diagnosis, it can help identify patients at high risk for HCC among patients with chronic liver diseases, which would prompt closer and more frequent surveillance for early tumor detection and intervention.

No MeSH data available.


Related in: MedlinePlus

CNV analysis. CNV analysis was performed as described in Materials and Methods. The plots were based on data with bin size at 150 kb. The five samples represent 5 different groups respectively: HCC with tumor <= 30 mm, HCC with tumor 31-50 mm, HCC with tumor >50 mm, cirrhosis, and chronic hepatitis.
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Figure 2: CNV analysis. CNV analysis was performed as described in Materials and Methods. The plots were based on data with bin size at 150 kb. The five samples represent 5 different groups respectively: HCC with tumor <= 30 mm, HCC with tumor 31-50 mm, HCC with tumor >50 mm, cirrhosis, and chronic hepatitis.

Mentions: The mapped reads from NGS were processed through GC correction, normalization, and comparison with the reads in the CNV control group in each window (bin) for chromosome CNV ratio calculation. Visual CNV change was defined as visible intense segmental increase or decrease in the CNV ratio in the 150 kb per bin CNV plots. Scattered dots above or below the baseline were not counted. Read breaks due to repeat sequences (close to centromere or telomere) that appear in every sample were ignored (such as in the middle of Chr 1 and Chr 9 in Figure 2). Among 31 samples from HCC patients, 13 showed visible CNV changes, including 4 with tumor size 50 mm or less, and 1 with tumor size 30 mm or less. None of the CH or CR samples showed CNV changes that can be recognized at 150 kb per bin CNV plots (Figure 2). Common CNVs observed include gain in 1q, 7q, 17q, 19q, 20q, and loss in 1p, 4q, 13q, 17p. Additional visual CNV change was summarized in Supplementary Material: Figure S1.


Non-invasive Analysis of Genomic Copy Number Variation in Patients with Hepatocellular Carcinoma by Next Generation DNA Sequencing.

Xu H, Zhu X, Xu Z, Hu Y, Bo S, Xing T, Zhu K - J Cancer (2015)

CNV analysis. CNV analysis was performed as described in Materials and Methods. The plots were based on data with bin size at 150 kb. The five samples represent 5 different groups respectively: HCC with tumor <= 30 mm, HCC with tumor 31-50 mm, HCC with tumor >50 mm, cirrhosis, and chronic hepatitis.
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Related In: Results  -  Collection

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Figure 2: CNV analysis. CNV analysis was performed as described in Materials and Methods. The plots were based on data with bin size at 150 kb. The five samples represent 5 different groups respectively: HCC with tumor <= 30 mm, HCC with tumor 31-50 mm, HCC with tumor >50 mm, cirrhosis, and chronic hepatitis.
Mentions: The mapped reads from NGS were processed through GC correction, normalization, and comparison with the reads in the CNV control group in each window (bin) for chromosome CNV ratio calculation. Visual CNV change was defined as visible intense segmental increase or decrease in the CNV ratio in the 150 kb per bin CNV plots. Scattered dots above or below the baseline were not counted. Read breaks due to repeat sequences (close to centromere or telomere) that appear in every sample were ignored (such as in the middle of Chr 1 and Chr 9 in Figure 2). Among 31 samples from HCC patients, 13 showed visible CNV changes, including 4 with tumor size 50 mm or less, and 1 with tumor size 30 mm or less. None of the CH or CR samples showed CNV changes that can be recognized at 150 kb per bin CNV plots (Figure 2). Common CNVs observed include gain in 1q, 7q, 17q, 19q, 20q, and loss in 1p, 4q, 13q, 17p. Additional visual CNV change was summarized in Supplementary Material: Figure S1.

Bottom Line: Plasma samples from 31 patients with HCC and 8 patients with chronic hepatitis or cirrhosis were analyzed.CNV Z score analysis showed significant CNVs in samples with HCC and chronic liver diseases although more significant changes were found in HCC group, some are differentially valuable (such as gain in 1q, 7q, and 19q in HCC), while others are less differentially valuable (such as loss in 4q, 13q, gain in 17q, 22q).Although CNV analysis itself cannot establish the diagnosis, it can help identify patients at high risk for HCC among patients with chronic liver diseases, which would prompt closer and more frequent surveillance for early tumor detection and intervention.

View Article: PubMed Central - PubMed

Affiliation: 1. Department of Infectious Diseases, Taizhou People's Hospital, Taizhou, Jiangsu, China.

ABSTRACT
To explore new molecular diagnosis approaches for early detection and differential diagnosis of hepatocellular carcinoma (HCC), we analyzed genomic copy number variations (CNV) using plasma cell-free DNA from patients with HCC by next generation DNA sequencing. Plasma samples from 31 patients with HCC and 8 patients with chronic hepatitis or cirrhosis were analyzed. In HCC group, most samples with large tumor size (tumor dimension greater than 50 mm) showed CNVs that are visually recognizable at chromosome CNV plots, few samples with small tumor and none samples with chronic liver diseases showed CNVs recognizable at CNV plots. CNV Z score analysis showed significant CNVs in samples with HCC and chronic liver diseases although more significant changes were found in HCC group, some are differentially valuable (such as gain in 1q, 7q, and 19q in HCC), while others are less differentially valuable (such as loss in 4q, 13q, gain in 17q, 22q). We proposed a CNV scoring method that generated positive result in 26 of the 31 HCC patients (83.9%) or 11 of the 16 HCC with tumor dimension 50 mm or less (68.8%) or 4 of the 7 HCC with tumor dimension 30 mm or less (57.1%), while all the 8 samples with chronic hepatitis or cirrhosis scored negative. Ten HCC patients had normal or low serum AFP levels, among them, 7 were scored positive by CNV analysis, including 4 with tumor dimension 50 mm or less. Our study suggested that non-invasive genomic CNV analysis using plasma samples could be a valuable tool for early detection and differential diagnosis of HCC. Although CNV analysis itself cannot establish the diagnosis, it can help identify patients at high risk for HCC among patients with chronic liver diseases, which would prompt closer and more frequent surveillance for early tumor detection and intervention.

No MeSH data available.


Related in: MedlinePlus