Whole-genome sequencing of matched primary and metastatic hepatocellular carcinomas
- Limei Ouyang†1,
- Jeeyun Lee†2,
- Cheol-Keun Park†3,
- Mao Mao4,
- Yujian Shi1,
- Zhuolin Gong1,
- Hancheng Zheng1,
- Yingrui Li1,
- Yonggang Zhao1,
- Guangbiao Wang1,
- Huiling Fu1,
- Jhingook Kim5Email author and
- Ho Yeong Lim2Email author
© Ouyang et al.; licensee BioMed Central Ltd. 2014
Received: 11 July 2013
Accepted: 27 December 2013
Published: 9 January 2014
To gain biological insights into lung metastases from hepatocellular carcinoma (HCC), we compared the whole-genome sequencing profiles of primary HCC and paired lung metastases.
We used whole-genome sequencing at 33X-43X coverage to profile somatic mutations in primary HCC (HBV+) and metachronous lung metastases (> 2 years interval).
In total, 5,027-13,961 and 5,275-12,624 somatic single-nucleotide variants (SNVs) were detected in primary HCC and lung metastases, respectively. Generally, 38.88-78.49% of SNVs detected in metastases were present in primary tumors. We identified 65–221 structural variations (SVs) in primary tumors and 60–232 SVs in metastases. Comparison of these SVs shows very similar and largely overlapped mutated segments between primary and metastatic tumors. Copy number alterations between primary and metastatic pairs were also found to be closely related. Together, these preservations in genomic profiles from liver primary tumors to metachronous lung metastases indicate that the genomic features during tumorigenesis may be retained during metastasis.
We found very similar genomic alterations between primary and metastatic tumors, with a few mutations found specifically in lung metastases, which may explain the clinical observation that both primary and metastatic tumors are usually sensitive or resistant to the same systemic treatments.
KeywordsCancer Hepatocellular carcinomas (HCC) Lung metastasis Somatic Next-generation sequencing (NGS)
Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with an estimated 500,000-1,000,000 new cases per year . It is also one of the few cancers with an increased incidence rate [2–4]. Although curative resection or liver transplant is widely adopted as treatment for HCC , a majority of HCC patients are not amenable to surgical resection due to the extensive intrahepatic tumor burden or limited donor resources. In nature, HCC is an invasive tumor and is metastasized hematogenously and lymphogenously to other organs, even after its local recurrence. The most common organs of distant metastases include lungs, lymph nodes, bone, and brain, in particular, with the lung metastasis occurring in 18-60% of HCC cases . While extrahepatic metastases are known to occur in HCC patients with an advanced intrahepatic tumor stage [6, 7], the prognosis in patients with extrahepatic metastases is extremely poor. To improve the prognosis for HCC metastases, we aim to investigate the genetic signatures of HCC through unbiased next-generation sequencing (NGS) in this whole genome-scale systematic study.
Recently, whole genome sequencing of metastatic acral melanomas and matched primary tumor and adjacent normal tissues showed high similarity of global gene copy number alterations, loss of heterozygosity and single nucleotide variation in primary and metastasis tissues . Meanwhile, de novo nonsynonymous coding single-nucleotide variants (SNVs) were identified in metastatic lesions from acral melanomas . In addition, recent studies that identified the clonal populations by sequencing the genomes of 7 pancreatic cancer metastases helped elucidate the mechanisms of distant metastases [9, 10]. Herein, we sequenced the whole genomes of 4 paired samples (primary tumor, metachronous lung metastases) obtained from HCC patients. These selected patients were treatment naïve at the time of primary HCC surgery and were later diagnosed with lung metastatic nodules more than 2 years after the first surgery. We compared the genetic landscape between primary liver and metastatic lung tumor tissues and performed an in-depth investigation of the genetic alterations to uncover potential biomarkers for tumor progression and metastasis.
Four patients who were pathologically diagnosed of HCC and lung metastases were included in this study.
A 50-year old man presented with a 9-cm sized mass at right hepatic lobe. The patient was a HBV carrier and his liver function was of Child-Pugh classification of A. The patient underwent right liver lobectomy when freshly frozen tissue of primary tumor and blood DNA was collected. The pathologic review of the surgical specimen revealed Edmonson grade II, tumor necrosis of 10%, microvascular tumor emboli and chronic active hepatitis with bridging fibrosis in background liver. Three years later, the patient developed a 2-cm sized single metastatic nodule in posterior basal segment of right lower lobe. The patient underwent right lower lobectomy and the pathologic diagnosis was metastatic hepatocellular carcinoma. Currently, the patient is in remission without recurrence since lung metastatectomy for more than 5 years.
A 46 year-old man presented with a 5.2 × 4.4 cm massive HCC involving S6 and S7. The patient was a hepatitis B carrier. The patient underwent right hemi-hepatectomy (tissue procurement of primary tumor). The pathologic features were as follows, Edmonson grade II, 0% necrosis, intrahepatic metastasis, segmental portal vein microinvasion and negative resection margin. Three months later, the patient developed small recurrent tumor in left lateral segment of left lobe of liver and underwent radiofrequency ablation and 6 cycles of transcatheter arterial chemoembolization (TACE) thereafter. Shortly after the 6th TACE, two nodules were detected in right lung. The patient underwent video-assisted thoracoscopic surgery wedge resection of right upper apical segment, posterior segment and RLL lobectomy. The pathologic diagnosis was metastatic hepatocellular carcinoma. Fresh frozen tissues were collected during the surgery at this time. Seven months later the patient developed another 2 cm lung metastatic nodule in right middle lobe and underwent metastatectomy. The patient is currently in remission for 4 years.
A 43-year old male presented with an 11-cm sized HCC-B (hepatitis B) and underwent right hepatectomy. The pathologic examination revealed Edmonson grade II HCC with 10% necrosis, no portal vein invasion with mild portoperiportal inflammation in background liver due to chronic hepatitis B. Four months following the surgical resection, a newly developed enhancing nodule in S3 of liver was detected which was subsequently treated with 5 cycles of TACE. Two years from the initial hepatic resection, a 1 cm nodule in left upper lobe was detected which was surgically removed with wedge resection. The tumor specimen was confirmed of metastatic HCC in lung and freshly frozen tissue was collected at this time. The patient underwent repeated multiple pulmonary metastatectomies for recurrent metastatases. The patient still has slowly progressive, multiple lung metastases which were refractory to sorafenib and sunitinib. The patient died of disease ten months later after failing to treatment due to disease progression.
A 51-year old male had a 6.6 c m sized liver mass and was diagnosed of HCC-B. The patient underwent S6 segmentectomy and the pathologic examination revealed Edmondson grade II, 60% necrosis, no microvessel or portal vein invasion and no intrahepatic metastasis. Two years later, a 14 cm solitary lung nodule was detected in left lower lobe superior segment which was surgically resected. Thirty months later, the patient developed multiple HCC nodules and received ten 10 cycles of TACE. The patient is still undergoing periodic TACE for multiple HCCs at the time of this writing. The core information is marked with specific notes (Additional file 1: Table S1 and Additional file 2: Figure S1).
Whole genome sequencing
Summary of somatic SNVs
# of somatic SNVs
Mutant allele frequency
In addition to the mutation frequency, we examined whether metastasis-derived mutations occur at certain genomic regions. However, we did not find any obvious hypermutation region in any of the 4 trio samples (Additional file 2: Figure S4). To further investigate the inter-somatic mutation distance, we compared the inter-somatic mutation distances to the simulated null distributions. The results show that the observed somatic mutation distances (<100 kb) were spaced more closely rather than randomly spotted (Additional file 2: Figures S2 and S3) and that the mutation events occurred in a similar manner in both primary and metastatic tumors (Additional file 2: Figure S5). We also analyzed the inter-somatic mutation distances across different cancer types, of which data was derived from public databases (Materials and methods), such as liver cancer, lung adenocarcinoma, and prostate cancer. Interestingly, we found that a specific tumor type may develop its own intrinsic mutation distance (Additional file 2: Figure S5). Together, our findings suggest that the scattered small regions with dense mutations are present in the cancer genomes and that specific cancer types are associated with their own mutation distance.
Short insertions and deletions
We predicted 2,514-4,925 and 4,366-7,968 indels in primary tumors and metastases, respectively, including a total of 25/34 (primary tumor/metastasis) events affecting protein coding (18/24 frameshift and 7/10 in-frame) in 42 genes (Additional file 1: Table S2F). Specifically, a frameshift insertion in the tumor suppressor RB1 was detected in both primary tumors and the matched metastases, whereas a metastasis-specific frameshift deletion was detected in the oncogene TFEB. In addition, a frameshift insertion in WNT5A and an in-frame deletion in DAAM2 were only detected in metastases; both WNT5A and DAAM2 are involved in the Wnt signaling pathway (Additional file 1: Table S10C).
Copy number alteration
Copy number alterations (CNAs) in primary tumors and metastases of 4 cases were detected by comparing with their respective matched normal samples. From primary tumors to metastases, the lengths of CNAs were changed, but the total sizes of CNAs were not significantly different (Additional file 1: Table S2G). As indicated by the CNA plots, primary tumors and their matched lung metastases generated similar global CNA patterns across 4 pairs (Additional file 2: Figure S6). The copy numbers across the genomes between primary tumors and metastases were found to be positively correlated with each other with correlation coefficient >0.5 for all 4 cases (Additional file 2: Figure S7), consistent with the conclusion that the genetic characteristics of metastases mostly originate from primary tumors. The copy numbers of CNA events were altered from primary tumors to metastases, and these CNAs were annotated to corresponding genes (Additional file 1: Table S7). Specifically, many CNAs with common regions but different copy number between primary tumor and metastasis are abserved in cases DD59 and D473. Such a pattern corresponds to the low percentage of somatic SNVs preserved in metastases (Figure 2). We found 26 CNA regions (26 deletions and no amplification) in primary tumors and 235 CNA regions (173 deletions and 62 amplifications) in metastases. Notably, 11 of the 26 deletions observed in primary tumors overlapped with 11 deletions in metastases (Additional file 2: Figure S7 and Additional file 1: Table S2H). The deletions detected in both primary tumors and metastases were mainly located in 1p, 4q, 8p, 9p, 9q, 16p, and 21q (Additional file 1: Table S7). By categorizing tumor-specific CNA regions in metastases, we found that alterations of oncogenes and tumor suppressors, for instance, tumor suppressor PMS2 and oncogenes TFPT, ZNF331, and others, may be linked to metastatic progression (Additional file 2: Figure S7 and Additional file 1: Table S7). In addition, frequent somatic copy number loss in the region spanning the tumor suppressor genes, CDKN2A and CDKN2B, was also observed across metastasis samples (Additional file 1: Table S7) .
We used CREST to detect structural variants (SV) in sequencing data . We identified 65–221 and 60–232 SVs in primary tumors and metastases, respectively. Indeed, the large portion of SVs in primary and metastatic tumors overlapped with each other (Figure 1). We identified 30 translocations that were only in metastases, 8 translocations that were only in primary tumors, as well as 30 overlapped translocations (Additional file 1: Table S2I). Some of the oncogenes and tumor suppressors, such as TPM3 and ZNF331, which were located in the breakpoints of somatic SVs, were detected in our study (Additional file 1: Table S6). Specific mutated genes that were identified in tumorigenesis pathways are summarized in Additional file 1: Table S10. Specifically, distinct mutated genes in metastasis, CNTNAP2 and PDCD1LG2, are the components of the cell adhesion pathway. The overexpression of CDH13 and AKAP13A, both of which were found to be truncated in our study, have been reported to correlate with a higher risk of late recurrence of hepatocellular carcinoma [17, 18]. In addition, the CDH13 and PDCD1LG2 genes located at the breakpoints of an inter-chromosome translocation may cause the CDH13-PDCD1LG2 fusion.
Potential regulation pathways of tumor progression
To identify genes as “driver” somatic mutations in either primary tumorigenesis or metastasis process, the genes with significant higher nonsynonymous mutation rates against a background were estimated . Tumor suppressors PRF1 and BRCA1, as well as oncogene TFEB, all of which may play an important role in cancer cell survival during the progress of metastasis, were predicted as driver genes only in metastases. WNT5A, PLCB3, and DAAM2, which can activate or inhibit canonical Wnt signaling, were predicted as metastasis-specific driver genes (Additional file 1: Table S10F). TP53, a tumor suppressor that was previously reported to be associated with liver cancer , was also weighted as a driver gene and is recurrently mutant in metastases (Additional file 2: Figure S2). In addition, we identified that shared mutations between primary tumors and metastases were significantly enriched in the pathways of bladder cancer, pancreatic cancer, non-small cell lung cancer, thyroid cancer, and melanoma, which implies that the general progress of different tumor types may be driven by several same mutations. The mTOR signaling pathway and some others were identified to be significant only in primary tumors (Additional file 1: Table S9A).
Similarity of genetic alterations in primary tumors and matched metastases
% of met_SSMs preserved in primary tumor
% of met_Indels preserved in primary tumor
Correlation coefficients of copy numbers between primary tumor and metastasis
% of met_SVs preserved in primary tumor
HCC is the fifth most common cancer and the third most common cause of cancer-related deaths worldwide. It has a high prevalence in Asia, including Korea, due to endemic hepatitis B virus infection. numerous clinical trials using cytotoxic chemotherapy or targeted agents have failed, except sorafenib . While intrahepatic recurrence is most common, lung metastases are the most common extrahepatic spread and account for up to 40% of metastatic HCC . survival of patients with metastatic HCC is usually less than 1 year . Recently, prolonged median survival durations have been reported from 6.4 months to 40.7 months following metastasectomies . However, despite advances in therapeutic strategies, extrahepatic metastasis is still a major impediment to better prognosis in HCC patients.
In this study, we employed whole-genome sequencing to profile somatic mutations and structural variations in primary HCC (HBV+) and their matched metachronous lung metastases. Several recent studies on HCCs of different etiologies (HBV, HCV, and alcohol) using whole-genome and exome sequencing have not only confirmed previously known mutations of β-catenin and TP53 but also identified novel genetic alterations in genes that are involved in epigenetic regulation, such as ARID1A, ARID1B, ARID2, MLL, and MLL3 . Wnt/β-catenin, p53 signaling, cell cycle, and chromatin remodeling have recently emerged as dominant cancer pathways in primary HCC . To the best of our knowledge, this study is the first to examine the genomic profiles of matched pairs of primary and metastatic HCC by whole-genome sequencing.
In summary, comparison of structural variations between primary and metastatic tumors shows very similar and largely overlapped mutated segments (Figure 1). In addition, CNVs in primary and metastatic pairs were found to be closely related, and 38.88-78.49% of SNVs detected in primary HCC tumors were also detected in lung metastases. These preservations in genomic profiles from liver primary tumors to metachronous lung metastases indicate that the genomic features during tumorigenesis may be retained during metastasis.
Despite similarities between primary and metastatic pairs, a few somatic mutations were detected only in metastatic tumors. Multiple mutations of zinc finger (ZNF) genes were detected in the metastasis samples, and mutated genes that are involved in apoptosis and transcription regulations were enriched in metastases (Additional file 1: Table S10B). The ZNF family represents a large group of proteins involved in various aspects of transcriptional regulation . It has been reported that there were almost twice as many ZNF mutated genes in the HBV-positive hepatitis . In our study, a total of 5 ZNF, namely ZNF257, ZNF682, ZNF404, ZNF514, and ZNF142, were mutated in lung metastases from HCC (Additional file 1: Table S10B). Among these, ZNF257 and ZNF682 were previously reported to be upregulated in lung and bone metastases, relative to the primary breast adenocarcinoma, and were speculated to be putative metastasis genes . In addition, ZNF mutations were found in head and neck squamous cell carcinoma (HNSCC); therefore, the genetic changes to these transcriptional regulators have been implicated in the development of HNSCC . Nevertheless, the functional role of ZNFs in HCC tumorigenesis is yet to be defined.
In addition, mutations in known cancer gene suppressor TP53 were also detected in our study samples, including a nonsense mutation (E343*) in the regulator of TAT binding and a missense mutation (N131D) in the DNA-binding domain, both were previously reported by COSMIC (http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/) (Additional file 1: Table S3).
Notably, a frameshift insertion in WNT5A and an in-frame deletion in DAAM2 were detected only in lung metastases; both WNT5A and DAAM2 are involved in the Wnt signaling pathway. Recent genome sequencing studies have revealed that the WNT signaling pathway is the most frequently altered oncogenic pathway in primary HCC . In addition to the high prevalence of CTNNB1 mutations, genetic alterations of other components, such AXIN1, AXIN2, and APC genes that encode proteins containing the destruction box, also occur at a lower frequency. Wnt5a, which is up-regulated in poorly differentiated and highly motile mesenchymal-like HCC cells, has been suggested to play a role in tumor progression by inducing epithelial mesenchymal transition . In line with this, Wnt5a up-regulation was significantly shown to enhance migration, proliferation, and invasiveness in pancreatic cancer cells in vitro. Importantly, Wnt signaling has been implicated in the activation of HCC-initiating cells [30, 31]. While Wnt5a has been described as a tumor promoter in melanoma, gastric, pancreatic, and prostate cancers, it was suggested to be a tumor suppressor in HCC, neuroblastoma, leukemia, colon, and thyroid cancers . The functional significance of Wnt5 aberrations in tumorigenesis of lung metastases from HCC primary tumors should be evaluated in subsequent studies.
Synthetically, primary tumor harbored more alterations located in Wnt, cell cycle, JAK-STAT pathways (Figure 5), which plays an important role in encoding protein molecular emphasizing the cell proliferation, apoptosis and inflammation, as well as focal adhesion pathway. Focal adhesion pathway has been implicated in the cell migration and initiated metastasis . For metastasis, specific alterations arose in tight junction and focal adhesion pathways (Figure 6), which enhanced the cell migration mechanism.
In this study, for the first time, the whole-genome sequencing profiles of primary HCC and paired lung metastases were compared. We found similar genomic alterations between them, with a few mutations that were found specifically in lung metastases, which may explain the clinical observation that both primary and metastatic tumors are usually sensitive or resistant to the same systemic treatments.
Tumor specimens and ethical statement
A total of 4 pairs of fresh frozen tumors and adjacent non-tumor liver tissues containing no necrosis or hemorrhage were collected from primary HCC patients treated with curative hepatectomy at the Samsung Medical Center, Seoul, Korea. Lung tumor specimens were collected at the time of lung metastasectomy. This study was approved by the Institutional Review Board of Samsung Medical Center, Seoul, Korea.
Genomic DNA was extracted from sliced tissue specimens using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany), respectively.
Library construction and whole-genome sequencing
Qualified genomic DNA samples were randomly fragmented by Covaris. After ligation of sequencing adapters to both ends of resulting fragments, successfully adapter-ligated DNA fragments were purified, and those with an insert size of approximately 500 bp were selected by electrophoresis. Insert fragments with correct sizes were harvested and prepared for cluster amplification by cBot (Hiseq 2000).
The qualified DNA library was then loaded on Hiseq2000 for high-throughput sequencing, to meet required sequencing depth with 90-bp paired-end reads. Raw image files were read by the Illumina’s base calling software with default parameters, and raw data were collected.
Read mapping and somatic variant detection
Sequencing reads from primary and metastatic tumors, as well as matched normal tissues, were gap-aligned to the hg19 reference genome by BWA program, followed by removal of PCR duplicates. Somatic variants in primary and metastatic tumors were detected by comparing tumor reads to those of matched normal samples. Somatic mutations in tumors were predicted by SOAPsnv (http://soap.genomics.org.cn/index.html) using a sensitive score threshold. Next, p values were calculated using Fisher’s exact test for all putative mutation sites, based on the distribution of read support with high stringent specificity and sensitivity . For mutations present in dbSNP (which are usually germline mutations), we removed potential germline mutations existing in database of dbSNP132 for the downstream analysis. Subsequently, we annotated potential somatic SNVs by mapping them to RefGene (http://refgene.com/) using an in-house annotation program.
Indels in tumors were examined through gapped alignment not allowing gap located 5 bp to either end of the mapped reads . From the indel pool, somatic indels were detected by filtering SNV which was also detected in adjacent normal samples. Somatic indels with ≤5 supporting reads were filtered for high confidence.
We used in-house software based on the read-depth method to infer copy number variation in primary and metastatic tumors. Copy number variants were called when the copy number in tumors was ≤0.75- or ≥1.25-fold of that in corresponding normal samples. To infer recurrently amplified or deleted genomic regions, we detected the focal copy number segments (≤1Mbp) by re-implementing the GISTIC algorithm  using copy numbers in 1-kb windows, instead of SNP array probes as markers. G-scores were calculated for genomic and gene-coding regions, based on the frequency and amplitude of amplification and deletion affecting each gene, respectively. A significant CNV region was defined as having an amplification G-score >0.08 or a deletion G-score <0.09, corresponding to a p-value threshold of 0.05 from the permutation-derived null distribution .
We further applied CREST  to whole-genome DNA sequence data obtained from primary and metastatic tumors to identify candidate structural variants (SV) at base-pair resolution.
Prediction of driver genes
Driver genes were predicted using in-house software by re-implementing the algorithm in which driver genes are the genes with a significant higher non-silent mutation (nonsynonymous/splice/coding indel) rate against a background mutation rate estimated from collected silent mutations . Similarly, driver pathways were predicted by computing the significance of enrichment of non-silent mutations in a certain pathway against background.
Pathway enrichment analysis
Genomic distribution of somatic mutations
We computed the inter-somatic mutation distance within individuals by defining the inter-somatic mutation distance as the distance from a somatic mutation to the very next one. We computed null distributions by randomly sampling positions from the genome (excluding assembly gaps), while maintaining the number of somatic mutations per chromosome . Using the Kolmogorov–Smirnov test, we calculated the differences between real distributions and corresponding null distributions and found that inter-somatic mutation distances were significantly smaller than expected (p < 0.05). The distribution of inter-somatic mutation distance in primary and metastatic tumors of sample D473 were compared to the distributions of inter-somatic mutation distances in HCC and other types of tumors, using published data downloaded from ICGC (ftp://data.dcc.icgc.org/version_11/). We used 2 lung adenocarcinoma samples, TCGA-05-4382-01A-01D-1265-08 and TCGA-05-4424-01A-22D-1855-08, from TCGA (http://cancergenome.nih.gov/), 2 prostate cancers, CPCG_0099_Pr_P_P1 and CPCG_0184_Pr_P_P4, from OICR (http://oicr.on.ca/), 2 liver cancers, HCC122T and RK020_C01, from NCC (http://www.ncc.go.jp/en/), and 1 liver cancer sample (sample 180) sample, sample180, from a collaboration HCC project of which some results have been published .
Sequencing data for this publication has been deposited in NCBI Short Reads Archive and is accessible through accession number SRA076160.
Written informed consent was obtained from the patient (who was not deceased at the time of writing or waived by the IRB if deceased) for the publication of this report and any accompanying images.
Copy number alterations
Somatic SNV mutations
Transcatheter arterial chemoembolization
Catalogue of somatic mutations in cancer
International cancer genome consortium
The cancer genome atlas
Ontario institute for cancer research
National cancer center.
This study was supported by a grant from the Korea Healthcare Technology R&D Project, Ministry for Health & Welfare Affairs, Republic of Korea (HI09C06580000).
- El-Serag HBRK: Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology. 2007, 132: 2557-2576. 10.1053/j.gastro.2007.04.061.View ArticlePubMedGoogle Scholar
- Jemal A, Center MM, DeSantis C, Ward EM: Global patterns of cancer incidence and mortality rates and trends. Cancer Epidemiol Biomarkers Prev. 2010, 19: 1893-1907. 10.1158/1055-9965.EPI-10-0437.View ArticlePubMedGoogle Scholar
- Bray F, Jemal A, Grey N, Ferlay J, Forman D: Global cancer transitions according to the human development index (2008–2030): a population-based study. Lancet Oncol. 2012, 13: 790-801. 10.1016/S1470-2045(12)70211-5.View ArticlePubMedGoogle Scholar
- Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D: Global cancer statistics. CA Cancer J Clin. 2011, 61: 69-90. 10.3322/caac.20107.View ArticlePubMedGoogle Scholar
- Rahbari NNMA, Mollberg NM, Müller SA, Koch M, Büchler MW, Weitz J: Hepatocellular carcinoma: current management and perspectives for the future. Ann Surg. 2011, 253: 453-469. 10.1097/SLA.0b013e31820d944f.View ArticlePubMedGoogle Scholar
- Natsuizaka MOT, Akaike T, Kuwata Y, Yamazaki K, Sato T, Karino Y, Toyota J, Suga T, Asaka M: Clinical features of hepatocellular carcinoma with extrahepatic metastases. J Gastroenterol Hepatol. 2005, 20: 1781-1787. 10.1111/j.1440-1746.2005.03919.x.View ArticlePubMedGoogle Scholar
- Katyal SOJ, Peterson MS, Ferris JV, Carr BS, Baron RL: Extrahepatic metastases of hepatocellular carcinoma. Radiology. 2000, 216: 698-703. 10.1148/radiology.216.3.r00se24698.View ArticlePubMedGoogle Scholar
- Turajlic SFS, Lambros MB, Mitsopoulos C, Kozarewa I, Geyer FC, Mackay A, Hakas J, Zvelebil M, Lord CJ, Ashworth A, Thomas M, Stamp G, Larkin J, Reis-Filho JS, Marais R: Whole genome sequencing of matched primary and metastatic acral melanomas. Genome Res. 2012, 22: 196-207. 10.1101/gr.125591.111.View ArticlePubMedPubMed CentralGoogle Scholar
- Campbell PJYS, Mudie LJ, Stephens PJ, Pleasance ED, Stebbings LA, Morsberger LA, Latimer C, McLaren S, Lin ML, McBride DJ, Varela I, Nik-Zainal SA, Leroy C, Jia M, Menzies A, Butler AP, Teague JW, Griffin CA, Burton J, Swerdlow H, Quail MA, Stratton MR, Iacobuzio-Donahue C, Futreal PA: The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature. 2010, 467: 1109-1113. 10.1038/nature09460.View ArticlePubMedPubMed CentralGoogle Scholar
- Yachida SJS, Bozic I, Antal T, Leary R, Fu B, Kamiyama M, Hruban RH, Eshleman JR, Nowak MA, Velculescu VE, Kinzler KW, Vogelstein B, Iacobuzio-Donahue CA: Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature. 2010, 467: 1114-1117. 10.1038/nature09515.View ArticlePubMedPubMed CentralGoogle Scholar
- Sung WKZH, Li S, Chen R, Liu X, Li Y, Lee NP, Lee WH, Ariyaratne PN, Tennakoon C, Mulawadi FH, Wong KF, Liu AM, Poon RT, Fan ST, Chan KL, Gong Z, Hu Y, Lin Z, Wang G, Zhang Q, Barber TD, Chou WC, Aggarwal A, Hao K, Zhou W, Zhang C, Hardwick J, Buser C, Xu J, Kan Z, Dai H, Mao M, Reinhard C, Wang J, Luk JM: Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma. Nat Genet. 2012, 44: 765-769. 10.1038/ng.2295.View ArticlePubMedGoogle Scholar
- Li SMMS, Mao M: Next generation sequencing reveals genetic landscape of hepatocellular carcinomas. Cancer Lett. 2013, 340 (2): 247-53. 10.1016/j.canlet.2012.09.027.View ArticlePubMedGoogle Scholar
- Ding LLT, Larson DE, Miller CA, Koboldt DC, Welch JS, Ritchey JK, Young MA, Lamprecht T, McLellan MD, McMichael JF, Wallis JW, Lu C, Shen D, Harris CC, Dooling DJ, Fulton RS, Fulton LL, Chen K, Schmidt H, Kalicki-Veizer J, Magrini VJ, Cook L, McGrath SD, Vickery TL, Wendl MC, Heath S, Watson MA, Link DC, Tomasson MH, Shannon WD, et al: Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012, 481: 506-510. 10.1038/nature10738.View ArticlePubMedPubMed CentralGoogle Scholar
- Futreal PA, Coin L, Marshall M, Down T, Hubbard T, Wooster R, Rahman N, Stratton MR: A census of human cancer genes. Nat Rev Cancer. 2004, 4: 177-183. 10.1038/nrc1299.View ArticlePubMedPubMed CentralGoogle Scholar
- Tavazoie SFAC, Oskarsson T, Padua D, Wang Q, Bos PD, Gerald WL, Massagué J: Endogenous human microRNAs that suppress breast cancer metastasis. Nature. 2008, 451: 147-152. 10.1038/nature06487.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang JMC, Easton J, Roberts S, Heatley SL, Ma J, Rusch MC, Chen K, Harris CC, Ding L, Holmfeldt L, Payne-Turner D, Fan X, Wei L, Zhao D, Obenauer JC, Naeve C, Mardis ER, Wilson RK, Downing JR, Zhang J: CREST maps somatic structural variation in cancer genomes with base-pair resolution. Nat Methods. 2011, 8: 652-654. 10.1038/nmeth.1628.View ArticlePubMedPubMed CentralGoogle Scholar
- Hoshida YVA, Kobayashi M, Peix J, Chiang DY, Camargo A, Gupta S, Moore J, Wrobel MJ, Lerner J, Reich M, Chan JA, Glickman JN, Ikeda K, Hashimoto M, Watanabe G, Daidone MG, Roayaie S, Schwartz M, Thung S, Salvesen HB, Gabriel S, Mazzaferro V, Bruix J, Friedman SL, Kumada H, Llovet JM, Golub TR: Gene expression in fixed tissues and outcome in hepatocellular carcinoma. N Engl J Med. 2008, 359: 1995-2004. 10.1056/NEJMoa0804525.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang L, Wu H, Jiang M, Huang J, Lin H, et al: Differential Differentiation- and Survival and Invasion-related T-/H-cadherin (CDH13) Computational Downstream Network from No-Tumor Hepatitis/Cirrhosis (HBV or HCV infection) to Human Hepatocellular Carcinoma (HCC) Malignant Transformation. J Mol Biomark Diagn. 2012, 2: 127.Google Scholar
- Youn ASR: Identifying cancer driver genes in tumor genome sequencing studies. Bioinformatics. 2011, 27: 175-181. 10.1093/bioinformatics/btq630.View ArticlePubMedGoogle Scholar
- Nguyen DX, Bos PD, Massague J: Metastasis: from dissemination to organ-specific colonization. Nat Rev Cancer. 2009, 9: 274-284. 10.1038/nrc2622.View ArticlePubMedGoogle Scholar
- Parkin DM: The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006, 118: 3030-3044. 10.1002/ijc.21731.View ArticlePubMedGoogle Scholar
- Kakumu S: Trends in liver cancer researched by the Liver Cancer Study Group of Japan. Hepatol Res. 2002, 24: S21-S27.View ArticleGoogle Scholar
- Zhang SMZZ, Tang ZY, Sun J, Cheng JM, Liu R, Wang P, Zhang BH: Prognostic analysis of pulmonary metastases from hepatocellular carcinoma. Hepatol Int. 2008, 2: 237-243. 10.1007/s12072-008-9052-7.View ArticlePubMedPubMed CentralGoogle Scholar
- Yoon YSKH, Kim J, Choi YS, Shim YM, Paik SW, Kim K: Long-term survival and prognostic factors after pulmonary metastasectomy in hepatocellular carcinoma. Ann Surg Oncol. 2010, 17: 2795-2801. 10.1245/s10434-010-1073-5.View ArticlePubMedGoogle Scholar
- Krishna SS, Majumdar I, Grishin NV: Structural classification of zinc fingers: survey and summary. Nucleic Acids Res. 2003, 31: 532-550. 10.1093/nar/gkg161.View ArticlePubMedPubMed CentralGoogle Scholar
- Cradick TJ, Keck K, Bradshaw S, Jamieson AC, McCaffrey AP: Zinc-finger nucleases as a novel therapeutic strategy for targeting hepatitis B virus DNAs. Mol Ther. 2010, 18: 947-954. 10.1038/mt.2010.20.View ArticlePubMedPubMed CentralGoogle Scholar
- Nichols AC, Chan-Seng-Yue M, Yoo J, Xu W, Dhaliwal S, Basmaji J, Szeto CC, Dowthwaite S, Todorovic B, Starmans MH, et al: A pilot study comparing HPV-positive and HPV-negative head and neck squamous cell carcinomas by whole exome sequencing. ISRN Oncol. 2012, 2012: 809370.PubMedPubMed CentralGoogle Scholar
- Yuzugullu H, Benhaj K, Ozturk N, Senturk S, Celik E, Toylu A, Tasdemir N, Yilmaz M, Erdal E, Akcali KC, Atabey N, Ozturk M: Canonical Wnt signaling is antagonized by noncanonical Wnt5a in hepatocellular carcinoma cells. Mol Cancer. 2009, 8: 90-10.1186/1476-4598-8-90.View ArticlePubMedPubMed CentralGoogle Scholar
- Ripka SKA, Buchholz M, Wagner M, Sipos B, Klöppel G, Downward J, Gress T, Michl P: WNT5A–target of CUTL1 and potent modulator of tumor cell migration and invasion in pancreatic cancer. Carcinogenesis. 2007, 28: 1178-1187. 10.1093/carcin/bgl255.View ArticlePubMedGoogle Scholar
- Hu MKM, Jeong YJ, Fuerer C, Ghole S, Nusse R, Sylvester KG: Wnt/beta-catenin signaling in murine hepatic transit amplifying progenitor cells. Gastroenterology. 2007, 133: 1579-1591. 10.1053/j.gastro.2007.08.036.View ArticlePubMedGoogle Scholar
- Yang WYH, Chen L, Liu Q, He YQ, Yu LX, Zhang SH, Huang DD, Tang L, Kong XN, Chen C, Liu SQ, Wu MC, Wang HY: Wnt/beta-catenin signaling contributes to activation of normal and tumorigenic liver progenitor cells. Cancer Res. 2008, 68: 4287-4295. 10.1158/0008-5472.CAN-07-6691.View ArticlePubMedGoogle Scholar
- McDonald SLSA: The opposing roles of Wnt-5a in cancer. Br J Cancer. 2009, 101: 209-214. 10.1038/sj.bjc.6605174.View ArticlePubMedPubMed CentralGoogle Scholar
- Welf ES, Haugh JM: Signaling pathways that control cell migration: models and analysis. Wiley Interdiscip Rev Syst Biol Med. 2011, 3: 231-240. 10.1002/wsbm.110.View ArticlePubMedPubMed CentralGoogle Scholar
- Beroukhim RGG, Nghiemphu L, Barretina J, Hsueh T, Linhart D, Vivanco I, Lee JC, Huang JH, Alexander S, Du J, Kau T, Thomas RK, Shah K, Soto H, Perner S, Prensner J, Debiasi RM, Demichelis F, Hatton C, Rubin MA, Garraway LA, Nelson SF, Liau L, Mischel PS, Cloughesy TF, Meyerson M, Golub TA, Lander ES, Mellinghoff IK, Sellers WR: Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc Natl Acad Sci U S A. 2007, 104: 20007-20012. 10.1073/pnas.0710052104.View ArticlePubMedPubMed CentralGoogle Scholar
- Subramanian ATP, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP, Source, Broad Institute of Massachusetts Institute of Technology and Harvard CS, Cambridge, MA 02141, USA: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005, 102: 15545-15550. 10.1073/pnas.0506580102.View ArticlePubMedPubMed CentralGoogle Scholar
- Mootha VKLC, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstråle M, Laurila E, Houstis N, Daly MJ, Patterson N, Mesirov JP, Golub TR, Tamayo P, Spiegelman B, Lander ES, Hirschhorn JN, Altshuler D, Groop LC: PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003, 34: 267-273. 10.1038/ng1180.View ArticlePubMedGoogle Scholar
- Michaelson JJSY, Gujral M, Zheng H, Malhotra D, Jin X, Jian M, Liu G, Greer D, Bhandari A, Wu W, Corominas R, Peoples A, Koren A, Gore A, Kang S, Lin GN, Estabillo J, Gadomski T, Singh B, Zhang K, Akshoomoff N, Corsello C, McCarroll S, Iakoucheva LM, Li Y, Wang J, Sebat J: Whole-genome sequencing in autism identifies hot spots for de novo germline mutation. Cell. 2012, 151: 1431-1442. 10.1016/j.cell.2012.11.019.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1755-8794/7/2/prepub
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.