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Comprehensive genomic analysis contrasting primary colorectal cancer and matched liver metastases: a retrospective study

Recent studies have revealed that colorectal cancer (CRC) displays intratumor genetic heterogeneity, and the cancer microenvironment play an important role in the proliferation, invasion, and metastasis of CRC. We performed genomic analysis on 22 paired patients with primary CRC and synchronous colorectal liver metastasis (CRLM) using whole-exome sequencing, cancer gene panels, and microarray gene expression proling.

This study was retrospectively registered.

Background
Colorectal cancer (CRC) is a common malignancy; it has the third highest incidence rate among all cancers and is the second leading cause of cancer-related deaths worldwide [1]. Despite advances in the understanding of the clinicopathological features of CRC as well as improved diagnosis and treatment, mortality from CRC is expected to continue to increase, with approximately 700,000 deaths each year [2].
Unfortunately, at the time of diagnosis, 18.2% of patients with primary CRC had concurrent distant metastases, with the highest frequency in liver (10.7%), peritoneum (5.0%), and lung (1.6%) [3]. The prognosis of patients with liver metastasis from colorectal cancer (CRLM) has dramatically improved with the availability of new effective cytotoxic and targeted agents as well as aggressive surgical resection. Moreover, recent remarkable improvements in innovative agents have led to an increased response rate in unresectable CRLM. The surgical resection rate after downstaging in initially unresectable CRLM has been reported to be up to 40% (so called "conversion therapy") [4]. In spite of these developments, the oncological outcomes for patients with CRLM remains unsatisfactory; CRLM recurrence after hepatectomy is common, with a 50% rate in remnant liver [5][6][7].
Advances in molecular biology over the past decade have enabled a greater understanding of the development of several kinds of cancers, and a more precise use of innovative targeted therapies. Recent studies have revealed that several cancers display intratumor genetic heterogeneity. Given the intratumor genetic heterogeneity described in several cancers, the metastatic process itself may result in clonal selection in the progression from primary to metastatic disease. The proliferation, invasion, and metastasis of cancer cells are not de ned by the nature of the cancer cell itself, but rather by the adaptation of the microenvironment via interactions between the cancer cell and its surrounding tissues [8,9].
Elucidation of intratumor genetic heterogeneity will lead to new diagnostic and therapeutic methods for CRC.
Herein, we performed molecular analysis on paired patients with primary CRC and synchronous CRLM, resected at the same institute. In this study, we investigated the molecular characteristics using whole-exome sequencing, cancer gene panels, fusion gene panels and microarray gene expression pro ling. A notable feature of this study is that it fully matches all clinicopathological data, as the cases are from the same medical institution. Most previously reported studies used metachronous or unpaired patient samples. Such analysis could be biased by intertumoral heterogeneity and the administration of chemotherapy between the resection of primary CRC and metastatic sites, which might alter the genetic clones. Moreover, the studies used a limited set of biomarkers.
To our knowledge, no other study has analyzed such a completely paired sample of primary CRC and synchronous CRLM using a major complement of exhaustive genetic analysis with next-generation sequencing.

Methods
Surgically resected tumor specimens and corresponding peripheral blood samples were obtained from 22 consecutive patients who underwent both colectomy and hepatectomy for CRC and synchronous CRLM between January 2014 and March 2015. All patients were enrolled in Project HOPE (High-tech Omics-based Patient Evaluation), a study launched at Shizuoka Cancer Center with the aim of evaluating the biological characteristics of cancer by multiomics-based analyses [10]. The clinicopathological data of patients were retrospectively reviewed. A prospective colorectal database, containing information regarding patient characteristics, preoperative assessment, operative characteristics, postoperative complications, pathological characteristics, and oncological outcomes, maintained at the hospital was used for this retrospective analysis.
Project HOPE (High-tech Omics-based Patient Evaluation) In the present study, we evaluated fresh frozen tumor tissues obtained from both primary CRC and CRLM using whole-exome sequencing (WES), cancer gene panel sequencing, fusion gene panel sequencing and microarray-based gene expression pro ling (GEP). We also acquired peripheral blood samples from patients and paired them with the corresponding resected tissue samples from the HOPE study. DNA was extracted from blood and tissues by the same method using a QIAamp DNA Blood Kit (QIAGEN, Hilden, Germany), except that tissues were treated with Proteinase K (QIAGEN) [11]. A board-certi ed pathologist determined that the tumor purity was > 50%. DNA was quanti ed using Nano-drop (Thermo Fisher Scienti c, Waltham, MA, USA) and Qubit 2.0 Fluorometer (Thermo Fisher Scienti c).

Ethical considerations
The research plan of Project HOPE was designed according to the revised Ethical Guidelines for Human Genome/Gene Analysis Research in Japan (http://www.lifescience.mext.go.jp/ les/pdf/n1115_01.pdf), and the study protocol was approved by the Institutional Review Board of Shizuoka Cancer Center (approval number #25-33). Written informed consent was obtained from all participants. This retrospective study was also approved by the same board (approval number #30-5-30-1-2).

Next-generation sequencing
The exome library used for WES was prepared using an Ion Torrent AmpliSeq RDY Exome Kit (Thermo Fisher Scienti c) in accordance with the manufacturer's protocol. A total of 100 ng of DNA was used for target ampli cation under the following conditions: 99 °C for 2 min, followed by 10 cycles at 95 °C for 15 s and 60 °C for 16 min, and a nal hold at 10 °C. Incorporated primer sequences were partially digested using a proprietary method. Ion Torrent Proton adapters were ligated to the amplicons at 22 °C for 30 min, followed by 72 °C for 10 min, and the library was puri ed with Agencourt Ampure XT beads (Thermo Fisher Scienti c).
Libraries were quanti ed using a quantitative polymerase chain reaction (qPCR), and DNA (8 pM) was sequenced using the semiconductor DNA sequencer (Ion Torrent Proton Sequencer, Thermo Fisher Scienti c) according to the manufacturer's protocol. Matched tumor-normal pair somatic variants were identi ed using Ion Reporter ver. 4.4 software (Thermo Fisher Scienti c) [12] after base calling, quality trimming, and mapping to the hg19/GRCh37 reference genome using Torrent Suite software ver. 4.4 (Thermo Fisher Scienti c) [13]. In this step, sequence data derived from tumor and blood samples were analyzed separately, and the latter were used as matched controls. In this process, only somatic variants remain after the subtraction of variants from blood data from those acquired from tumor data. In this variant-call work ow, we identi ed somatic mutations that satis ed the thresholds quality score ≥ 60 or depth of coverage ≥ 20.
Comprehensive gene expression analysis using DNA microarray Fresh tumor and adjacent normal tissues were soaked in RNAlater reagent (Thermo Fisher Scienti c), and total RNA was isolated and puri ed using a miRNeasy Mini Kit (QIAGEN) according to the manufacturer's protocol. RNA quality was evaluated by RNA integrity number, which was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA samples with an RNA integrity number ≥ 6.0 were used for gene expression analysis. Gene expression analysis was performed on a SurePrint G3 Human Gene Expression 8 × 60K v2 Microarray (Agilent Technologies) using a One-color Low Input Quick Amp Labeling kit (Agilent Technologies) according to the manufacturer's instructions. Data processing to generate raw signal intensity data was performed with GeneSpring version 13.1.1 software (Agilent Technologies). The raw signals were log-transformed and normalized (GeneSpring software, Agilent Technologies), and the difference in the normalized microarray signal intensities (fold change) between the tumor and adjacent normal tissues was calculated.

Immunohistochemical analysis
Routine pathological diagnosis was achieved using surgically resected tumors xed in 10% formalin and embedded in para n. Para n sections (3 µm thickness) containing representative histology of the tumor were used for immunohistochemical analysis. Immunohistochemical staining was performed using the Bond

Statistical analysis
Parametric variables are reported as medians (range). For comparisons between two groups, the chi-squared and Wilcoxon signed rank test were used. A p-value < 0.05 was considered to be signi cant. All statistical analyses were performed using IBM SPSS Statistics software for Windows, version 24 (SPSS Inc., Chicago, IL, USA).

Results
The data set consisted of 22 pairs of primary CRC and CRLM. The patients' characteristics are shown in Table 1. A total of 22 paired patients were enrolled in this study, including 13 (59.1%) colon and 9 (40.9%) rectal cancer patients. Right-sided colon was de ned as caecum, ascending, and transverse colon. Left-sided colon was de ned as descending and sigmoid colon. All patients had synchronous liver metastasis and did not have any other extrahepatic metastasis. Patients with multiple cancers such as synchronous or metachronous malignancy (within 5 years) other than carcinoma in situ, familial adenomatous polyposis, and appendiceal cancer were excluded. The median number of CRLM of patients was 2 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). The median size of CRLM was 30  mm. Of the cases, 21 of 22 (95.5%) received two-stage hepatectomy. The median interval between resection of primary CRC and CRLM was 6 (0-15) weeks. No patients received adjuvant/neoadjuvant chemo/chemoradiotherapy before and after the resection for primary CRC or hepatectomies for CRLM.

Comparison of tumor mutation burden between primary CRC and CRLM
The tumor mutation burden (TMB), also referred to as "mutation load", represents the number of single nucleotide variations (SNV) per mega base, and has received increasing attention owing to its potential responses to immune checkpoint inhibitors. TMB was determined for the 22 paired samples (Fig. 1). The median TMB in primary CRC was 2.8 (0.9-6.4), whereas it was 3.8 (2.0-6.6) in CRLM. The TMB counts in CRLM tended to be more frequent than those of primary CRC, although there were no statistically signi cant differences (p = 0.07).

Gene mutation pro ling
Genomic alterations contributing to tumorigenesis were analyzed using using an analysis pipeline called "Shizuoka Multi-omics Analysis Protocol (SMAP) [10]" developed in-house in primary CRC and CRLM.

Concordance of mutations in matched pairs of primary CRC and CRLM
The concordance of genomic alterations between paired primary CRC and CRLM varied from 15.8 to 80.6% in each paired case (median concordance, 49.2%; Fig. 2A). The mutational concordance of KRAS, which is known as an important factor related to tumor metastasis was 100%. On the other hand, the concordance of APC was only 59.1% (Fig. 2B).
Gene expression analysis using DNA microarray To select candidate genes that showed signi cantly higher expression in CRLM than primary CRC, gene expression was compared using the average expression value of 36022 probes in primary CRC, CRLM, and normal liver tissues (i.e., non-cancerous tissues of liver metastasis cases). First, we selected 1794 probes whose expression was up to 1.5 times higher in CRLM than primary CRC. Second, to remove contamination of normal liver tissues in liver metastasis samples, we compared expression levels in primary CRC with those in non-cancerous liver tissues and selected 198 probes whose expression was higher in primary CRC than normal liver. Third, we chose 20 probes (19 genes) as highly expressed probes in CRLM with a normalized ratio > 1.0. Finally, we examined the difference in expression level of these 20 probes in paired samples of CRC (Table 3 and Fig. 3). Figure 4A shows the characteristic expression pro les of the 11 probes in the 22 paired cases. Figure 4B shows the comparison of gene expression between primary CRC and CRLM; all 11 probes showed signi cantly higher expression in CRLM (Wilcoxon signed rank test, p < 0.001).

Immunohistochemical analysis
Immunohistochemical analysis was performed to con rm the protein expression of genes identi ed by DNA microarray analysis. Among the 10 genes that were highly expressed in CRLM, 5 genes classi ed as encoding "matricellular proteins", i.e., osteopontin, periostin, thrombospondin-2, MGP, and GPNMB, were

Comparison of number of immunoreactive factors
To determine whether differences in the complexity of expression patterns between primary CRC and CRLM can be veri ed, and to determine genomic heterogeneity, we compared the number of positive immunoreactivities for 22 pairs of primary CRC and CRLM (Table 5). Sixteen cases (72.7%) of primary CRC showed zero or one positive immunoreactivity, and 6 case (27.3%) revealed positivity for 2 or more factors.
On the other hand, CRLM revealed more frequent multiple immunoreactivities, 16 cases (72.7%) shared 2 or more factors, which was signi cantly more frequent in CRLM than in primary CRC (p = 0.007).

Discussion
In the present study, we clearly demonstrated genomic heterogeneity between paired primary CRC and CRLM by using a large complement of exhaustive genetic analyses with next-generation sequencing. No other study has analyzed such a completely paired sample of primary CRC and synchronous CRLM. Elucidation of the heterogeneity of microenvironment-related factors on the proliferation, invasion, and metastasis of cancer cells will lead to novel diagnostic and therapeutic targets for CRC in the era of genome-guided personalized cancer treatment.
Recent advances in next-generation sequencing technologies have made it possible to analyze large numbers of sequences, leading to international cancer genome analysis projects such as the Cancer Genome Atlas (mesenchymal, 23%) [20]. This intertumoral heterogeneity has led to the nding that different subtypes of CRC are represented by different genetic makeup, clinical behavior, pathological features, and responses to treatment [21][22][23].
In addition to the intertumoral heterogeneity mentioned above, intratumoral heterogeneity relates to the genetic heterogeneity between cancer cells within a single tumor. During carcinogenesis, genetic abnormalities accumulate continually, allowing the cells an increased ability to expand and invade. As a result of this continuous process, cancers become genetically heterogeneous, with an indeterminate number of coexisting genomic clones. These clones have different functional characteristics such as the ability to form metastases or respond to chemotherapy.

Cancer cells survive and proliferate in a microenvironment created by the cells themselves, various stromal cells, and the stromal tissue. The stromal cells that form cancer tissues include broblasts, vascular and lymphangial endothelial cells, lymphocytes, and macrophages. Both cells interact with cancer cells, imparting
their characteristic biological features on the cancer [24,25]. Distant metastasis of cancer has also been implicated in interactions between cancer cells and stromal cells in the cancer microenvironment [8,9].
In this study, we determined that many highly expressed genes by DNA microarray analysis were classi ed as encoding "matricellular proteins", which interact with the ECM. Periostin is a secreted adhesion-related protein expressed in the periosteum and periodontal ligaments, which acts as a critical regulator of the formation and maintenance of bone and teeth, and also plays an important role in tumorigenesis [26]. Recent studies have shown that periostin is highly expressed in various human cancers and have suggested that periostin promotes tumor growth and metastasis [27][28][29]. Moreover, periostin is reported to enhance the metastatic growth of colon cancer by both preventing stress-induced apoptosis in cancer cells and augmenting endothelial cell survival to promote angiogenesis. The expression level of periostin is reported to be noticeably higher in metastatic tumors than that in the matched primary colon cancer [30].
Osteopontin is a multifunctional ECM phosphorylated glycoprotein (glycol-phosphoprotein) classi ed into the Small Integrin-Binding Ligand N-linked Glycoprotein (SIBLING) family, and is reported to play an important role in the tumorigenesis, progression and prognosis of various cancers by regulating cell-matrix interactions and cell signaling through binding with integrins and CD44 receptors [31][32][33][34][35][36]. A pooled data analysis showed that high osteopontin expression was signi cantly associated with high tumor grade, invasion, lymph node metastasis, tumor distant metastasis and poor survival in CRC [37].
Thrombospondin-2 (THBS2) is a member of the ECM glycoproteins that mediate ECM assembly, cell-matrix interactions, degradation of matrix metalloproteinases (MMP)-2 and MMP-9, and interact with multiple cell receptors and growth factors. The implication of THBS2 expression in CRC has been controversial. Several studies reported an inverse correlation between THBS2 expression level and malignancy grade [38,39]. In contrast, resent studies reported that THBS2 expression in CRC was positively correlated with TNM stage and is a strong prognostic indicator [40,41].
GPNMB gene is reported to be overexpressed in numerous cancers and is often associated with the metastatic phenotype [42][43][44][45][46]. The extracellular domain of GPNMB interacts with integrins to facilitate the recruitment of immune-suppressive and proangiogenic cells to the tumor microenvironment, thereby enhancing tumor migration and invasion [47]. GPNMB expressed in immune cells such as macrophages and dendritic cells [14,29] may impair T-cell activation to down-modulate anti-tumor immune responses [48][49][50].
However, the role of GPNMB is complex; it appears to have an inhibitory role in some cancers but may promote metastasis in others.
MGP is an ECM protein containing post-translationally modi ed γ-carboxyglutamate residues due to vitamin K-dependent carboxylation. MGP was initially thought to be involved in the inhibition of calci cation of arteries and cartilage. Further investigation demonstrated that MGP had a wider range of activities, which were dependent of the phosphorylation-carboxylation status, protein expression and variants. Recent studies showed that MGP has a role in tumor angiogenesis by increasing vascular endothelial growth factor gene expression [51][52][53]. Recently, MGP was reported to be upregulated in a variety of tumors, including ovarian, breast, urogenital and skin cancer. However, in colon and lung cancers, an inverse correlation between MGP expression and survival was observed [54].
In the present study, exhaustive genetic analysis using next-generation sequencing and comparison of immunoreactive factors revealed the complexities of gene expression in CRLM. It is especially notable that CRLM has greater genomic heterogeneity associated with the ECM compared to primary CRC. This result suggests our hypotheses. To proliferate in the liver, which differs environmentally from the original colorectal tissue in which they naturally exist, cancer cells must modify their microenvironment to make it more amenable for survival. A suitable microenvironment cannot be regulated by a single factor; instead, complex factors are involved, especially in metastatic sites. The complexity of intratumor heterogeneity, which we revealed in this study, may be an underlying cause of the resistance to treatment for metastatic disease.
Differences in genomic mutational pro ling between primary and metastatic sites have been investigated in several studies [55][56][57]. However, most studies have used metachronous or unpaired patient samples.
Moreover, a limited set of biomarkers was employed to show that metastatic sites have more inherited mutations than primary CRC. These studies have potential biases related to both intra-and intertumoral heterogeneity.
It has been reported that the several kinds of systemic chemotherapy could alter the genomic landscape in several cancers [58,59]. Therefore, adjuvant chemotherapy has the potential to alter the genomic mutational pro les of recurrent cancers, so that they would differ from those of primary tumors [60]. Previous analyses evaluating the heterogeneity of metachronous tumors could be biased by the administration of chemotherapy between the resection of primary CRC and metastatic sites, potentially producing alterations in genomic clones [55,61]. Our study eliminates this bias since we selected paired samples of synchronous tumors.
This study has two important limitations. First, the study included a relatively small number of patients. We plan to continue our analysis using an increased number of cases in the future. Next, although the gene expression of thrombospondin-2, GPNMB, and MGP in CRLM was more frequent than in primary CRC according to the DNA microarray analysis, the immunohistochemical analysis revealed no differences in expression. We suggest that the discrepancy between the tissue regions analyzed by DNA microarray and those subjected to immunohistochemical analysis led to this result. The relatively low immunoreactivity scores of GPNMB and MGP may be attributed to the timing of degradation and wash-out of these proteins from the tissue [53].
There are three future perspectives from this study. First, we also obtained data of surgically resected tumor specimens and corresponding peripheral blood samples not only for CRLM, but also pulmonary metastasis, peritoneal metastasis, ovarian metastasis and so on, through WES, cancer gene panel sequencing, fusion gene panel sequencing and microarray-based GEP under the framework of "project HOPE". Thus, we will be able to perform further investigations using these samples. Second, studied of circulating tumor cells (liquid biopsy) may be useful in establishing early CRLM diagnosis. Additionally, it may lead to better predictive biomarkers to identify patients who might bene t from adjuvant chemotherapy. Third, the genes that were overexpressed in this study have the potential to be new therapeutic targets. For example, administration of anti-periostin antibody signi cantly inhibited the growth of primary tumors as well as metastatic tumors in a murine model of breast cancer [26]. Osteopontin-inhibition is also reported to be a favorable therapeutic approach to metastatic disease [62][63][64][65]. An antibody-drug conjugate targeting GPNMB, called glembatumumab vedotin (CDX-011), is currently in clinical studies for various cancers [66].

Conclusions
In conclusion, we revealed the genomic heterogeneity between paired primary CRC and CRLM in terms of the microenvironment on the proliferation, invasion, and metastasis of cancer cells. This will lead to new diagnostic and therapeutic targets for CRC in the era of genome-guided personalized cancer treatment. This retrospective study was also approved by the same board (approval number #30-5-30-1-2).

Consent for publication
Consent for publication were obtained from all participants.

Availability of data and materials
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interest.

Funding
We obtained no funding for this study.

Authors' contributions
Akio Shiomi, Masatoshi Kusuhara and Takashi Sugino designed the study.
Akio Shiomi drafted the manuscript.
All authors reviewed and revised the paper and approved the submitted version.  Bold letters indicate gene mutations found only in liver metastases      Heat map of the expression pro les from the microarray analysis Comparison of gene expression between primary CRC and CRLM Figure 7 Representative images of immunohistochemical staining for osteopontin, periostin, thrombospondin-2, GPNMB, and MGP in CRLM