Frameshift mutation of a histone methylation-related gene SETD1B and its regional heterogeneity in gastric and colorectal cancers with high microsatellite instability Youn Jin Choi MD, Hye Rim Oh BS, Mi Ryoung Choi BS, Min Gwak BS, Chang Hyeok An MD, Yeun Jun Chung MD, Nam Jin Yoo MD, Sug Hyung Lee MD PII: DOI: Reference:
S0046-8177(14)00166-X doi: 10.1016/j.humpath.2014.04.013 YHUPA 3299
To appear in:
Human Pathology
Received date: Revised date: Accepted date:
6 March 2014 3 April 2014 9 April 2014
Please cite this article as: Choi Youn Jin, Oh Hye Rim, Choi Mi Ryoung, Gwak Min, An Chang Hyeok, Chung Yeun Jun, Yoo Nam Jin, Lee Sug Hyung, Frameshift mutation of a histone methylation-related gene SETD1B and its regional heterogeneity in gastric and colorectal cancers with high microsatellite instability, Human Pathology (2014), doi: 10.1016/j.humpath.2014.04.013
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Revision YHUPA-D-14-00149 Frameshift mutation of a histone methylation-related gene SETD1B and its regional
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heterogeneity in gastric and colorectal cancers with high microsatellite instability Youn Jin Choi MDa, Hye Rim Oh BSa, Mi Ryoung Choi BSa, Min Gwak BSa, Chang Hyeok
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An MDb, Yeun Jun Chung MDc, Nam Jin Yoo MDa and Sug Hyung Lee MDa, * Departments of Pathologya General Surgeryb and Microbiology,c College of Medicine, The
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Catholic University of Korea, Seoul, Korea
Running title: SETD1B mutations and heterogeneity
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Key words: SETD1B, heterogeneity, mutation, cancer, microsatellite instability
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* Corresponding author: Department of Pathology, College of Medicine, The Catholic University of Korea, 505 Banpo-dong, Socho-gu, Seoul 137-701, Korea. Phone: 82-2-2258-
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7311; Fax: 82-2-537-6586
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E-mail:
[email protected]
Conflict of interest statement: All of the authors declare the absence of any conflict of interest.
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Summary Histone methyltransferase (HMT), which catalyzes a histone methylation, is frequently
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altered in cancers at mutation and expression levels. The aims of this study were to explore
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whether SETD1B, SETDB2 and SETD2, SET domain-containing HMT genes, are mutated and expressionally altered in gastric (GC) and colorectal cancers (CRC). In a public database, we
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found that SETD1B, SETDB2 and SETD2 had mononucleotide repeats in coding sequences
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that might be mutation targets in cancers with microsatellite instability (MSI). We analyzed the mutations in 76 GC and 93 CRC and found SETD1B (38.7% of GC and 35.6% of CRC with high MSI (MSI-H)), SETDB2 (11.1% of CRC with MSI-H) and SETD2 frameshift mutations (6.7% of CRC with MSI-H). These mutations were not found in stable MSI/low
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MSI (MSS/MSI-L). Additionally, we analyzed intratumoral heterogeneity (ITH) of SETD1B mutation in six CRC and found that two CRC harbored regional ITH of SETD1B. We also
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analyzed SETD1B expression in GC and CRC by immunohistochemistry. Loss of SETD1B
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expression was identified in 15 - 55% of the GC and CRC with respect to the MSI status. Of note, the loss of expression was more common in those with SETD1B mutations than those
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with wild-type SETD1B. We identified alterations of SET domain-containing HMT at various levels (frameshift mutations, genetic ITH and expression loss), which together might play a role in tumorigenesis of GC and CRC with MSI-H. Our data suggest that mutation analysis in multiple regions is needed for a better evaluation of mutation status in CRC with MSI-H.
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Introduction Epigenetic modification of histone, including methylation, acetylation and phosphorylation is
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important in regulation of gene expression, DNA replication and DNA repair [1, 2]. It
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becomes clear that dysregulated histone modification is involved in cancer pathogenesis [1, 2]. Histone methylation, a process by which methyl groups are transferred to amino acids of
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histone proteins, causes transcription repression or activation, depending on the amino acid
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being methylated and the presence of other methyl or acetyl groups in the vicinity target sites [3]. Histones can be methylated on lysine (K) and arginine (R) residues only, but methylation is most commonly observed on lysine residues of histone tails H3 and H4 [4]. Common sites of methylation associated with gene activation include lysine 4 of histone 3 (H3K4), H3K48,
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and H3K79, while those for gene inactivation include H3K9 and H3K27 [1, 2, 5]. Homeostasis of histone methylation is regulated by histone methyltransferase (HMT) that
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catalyzes a histone methylation, histone demethylase that removes a histone methylation, and
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effector proteins that specifically translate the histone code into a biological outcome [1, 2]. H3K4 methylation is associated with biological processes such as aberrant gene
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expression (MYC, HOX, BRCA1, hTERT and CDK2), genome instability and cell cycle checkpoint alterations that are implicated in cancers [2]. H3K4 methylation is catalyzed by the SET family HMT and mixed lineage leukemia (MLL) family of HMTs and removed by LSD1 and JARID1 [1, 6]. Expressional and genetic alterations of the genes involved in H3K4 methylation is frequently altered during tumorigenesis [1]. For example, decrease of H3K4 methylation was observed in various cancer tissues and might serve as a predictive factor for clinical outcome [7-9]. Translocation of MLL gene leads to ectopic expression of Hox genes and contributes to leukemic progression [10]. H3K9 histone methylation regulates cell adhesion and apoptosis, while H3K36 methylation regulates cell proliferation and senescence [11, 12]. More recently, Zhu et al. [13] identified SETD2 gene (encoding H3K36 HMT)
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mutations in acute leukemias, which contributed to leukemia development by enhancing selfrenewal of stem cells, suggesting that SETD2 may be a tumor suppressor gene (TSG).
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In a public genome database (http://genome.cse.ucsc.edu/), we found that some SET
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family genes (H3K4 HMT-encoding SETD1B, H3K9 HMT-encoding SETDB2 and H3K36 HMT-encoding SETD2) have mononucleotide repeats in their coding sequences that could be
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targets for frameshift mutation in cancers with microsatellite instability (MSI). Frameshift
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mutations of genes with mononucleotide repeats are features of gastric (GC) and CRC with microsatellite instability (MSI) [14]. We hypothesized that inactivating frameshift mutations in SETD1B, SETDB2 and SETD2 might cause alterations of H3K4 methylation and contribute to cancer pathogenesis. However, the data on mutations in SETD1B, SETDB2 and SETD2
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genes are known neither in GC nor CRC.
A cancer is established by clonal expansion of a single cell by multiple mutations and
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becomes heterogenous. Such an intratumoral heterogeneity (ITH) is crucial in acquiring
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aggressiveness in cancers and may impede accurate diagnosis as well as a proper selection of cancer therapies [15]. In this study, we found frameshift mutations in SETD1B, SETDB2 and
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SETD2, and ITH of SETD1B mutation in GC and CRC with MSI.
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Materials and Methods Tissue samples and microdissection
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For the mutation analysis, methacarn-fixed tissues of sporadic 76 GC and 93 CRC were used
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in this study. All of the patients with the cancers were Koreans. The GC consisted of 31 GC with high MSI (MSI-H), 45 GC with stable MSI/low MSI (MSS/MSI-L), 45 CRC with MSI-
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H and 48 CRC with MSS/MSI-L. The MSI evaluation system used five mononucleotide
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repeats (BAT25, BAT26, NR-21, NR-24 and MONO-27), tumoral MSI status of which was characterized as: MSI-H, if two or more of these markers show instability, MSI-L, if one of the markers shows instability and MSS, if none of the markers shows instability [16]. For 39 CRC of the 93 CRC, we collected four to seven different tumor areas and one normal mucosal
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area from each fresh CRC specimen. The tumor areas were 0.027-1 cm3 and at least 1.0 cm apart from each other. These four to seven different tumor areas in the 39 CRC were used for
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detecting regional heterogeneity of SETD1B gene.
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In each patient’s sample, histologic grades of the selected areas were not different from each other, indicating that the selected areas represented the most common histologic patterns
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with minimal histologic differences in each sample. The pathologic features of the cancers are summarized in Table 1. The histologic features of CRC with MSI-H, including mucinous histology, tumor infiltrating lymphocytes, medullary pattern, and Crohn's like inflammation, were evaluated in all blocks of all cases by a pathologist. Tumor-infiltrating lymphocytes were considered positive, when at least four intraepithelial lymphocytes were identified in one field at high magnification [17]. Peritumoral lymphocytes were defined as the cuff of lymphocytes surrounding the deepest point of advancing front of the tumor [17]. Malignant cells and normal cells were selectively procured from hematoxylin and eosin-stained slides using a 30G1/2 hypodermic needle by microdissection as described previously [18-21]. DNA extraction was performed by a modified single-step DNA extraction method by proteinase K
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treatment. Approval of this study was obtained from the Catholic University of Korea,
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Single strand conformation polymorphism (SSCP) analysis
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College of Medicine’s institutional review board for this study.
SETD1B exon 1 (C8 repeat), SETDB2 exon 13 (A8) and SETD2 exon 3 (A7) have
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mononucleotide repeats in their coding sequences. Genomic DNA from the microdissected
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cells was isolated, and was amplified by polymerase chain reaction (PCR) with specific primer pairs. Radioisotope ([32P]dCTP) was incorporated into the PCR products for detection by autoradiogram. After SSCP, mobility shifts on the SSCP gels (FMC Mutation Detection Enhancement system; Intermountain Scientific, Kaysville, UT, USA) were determined by
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visual inspection. Direct DNA sequencing reactions in both forward and reverse sequences were performed in the cancers with the mobility shifts in the SSCP using a capillary
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automatic sequencer (3730 DNA Analyzer, Applied Biosystem, Carlsbad, CA, USA). When
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mutations in the SETD1B, SETDB2 and SETD2 genes were suspected by SSCP, analysis of an independently isolated DNA from another tissue section of the same patients was performed
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to exclude potential artifacts originated from PCR.
Immunohistochemistry Using the sections from GC and CRC tissues, immunohistochemistry for SETD1B was performed. The tissues consisted of 31 GC and 45 CRC with MSI-H, and 45 GC and 48 CRC with MSS/MSI-L. We used ImmPRESS System (Vector Laboratories, Burlingame, CA, USA) and rabbit polyclonal antibody for human SETD1B (Bethyl Laboratories, Montgomery, TX, USA; dilution 1/800). After deparaffinization, heat-induced epitope retrieval was conducted by immersing the slides in Coplin jars filled with 10 mmol/L citrate buffer (pH 6.0) and boiling the buffer for 30 min in a pressure cooker (Nordic Ware, Minneapolis, MN, USA)
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inside a microwave oven at 700 W; the jars were then cooled for 20 min. The immunohistochemical procedure was performed as described previously [22, 23]. The
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reaction products were developed with diaminobenzidine and counterstained with
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hematoxylin. The staining intensity was graded as follows: 0, negative; 1+ when the cells showed weak staining in nuclei; 2+, moderate; and 3+, intense. The extent was graded
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according to the percentage of positive cells as follows: 0, 0–5%; 1, 6-19%; 2, 20–49%; 3, >
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50%. The percentage of positive cells and the staining intensity were then multiplied to generate the immunohistochemistry score (IS). We categorized the IS 0-3 as negative, 4-5 as + and 6-9 as ++. Both + and ++ were considered positive. The results were reviewed independently by two pathologists. The immunostaining was judged to be specific by absence
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of consistent immunostaining of cells with replacement of primary antibody with the blocking reagent and reduction of immunostaining intensity as dilution of the antibody was increased.
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For the statistical analysis of the immunohistochemical data, we used Fisher’s exact test and
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χ2 test.
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Statistical Analysis
Statistical analysis was performed using a commercially available statistical software package (SPSS statistical software version 18.0 (SPSS Inc, Chicago, IL, USA)). Fisher’s exact test and χ2 test were used to analyze the statistical analysis of the immunohistochemical data. The level of significance was set at p < 0.05. The Cohen’s Kappa coefficient was calculated to determine inter-rater agreement between the evaluations by two pathologists.
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Results Mutational analysis
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Genomic DNAs isolated from normal and tumor tissues of the 76 GC and 93 CRC were
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analyzed for detection of mutation in SETD1B (exon 1 (C8), SETDB2 (exon 13 (A8) and SETD2 (exon 3 (A7)) by PCR-SSCP analysis. On the SSCP, we observed aberrant bands in
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28 cases of SETD1B, five cases of SETDB2 and three cases of SETD2 (Figure 1 and Table 2).
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DNA from normal tissues from the same patients showed no evidence of aberrant migration in SSCP, indicating the aberrant bands had risen somatically (Figure 1). All of the mutations were interpreted as heterozygous according to the SSCP and direct DNA sequencing analyses (Figure 1). Direct DNA sequencing analyses of the cancer tissues with aberrantly migrating
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bands confirmed that the aberrant bands represented somatic mutations of SETD1B, SETDB2 and SETD2 genes (Figure 1). All of the mutations were deletion or duplication of bases in the
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repeats that would cause premature stop codons, which lead to the termination of translation
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(Table 2). Twelve of 31 GC (38.7%) and 16 of 45 CRC (35.6%) with MSI-H harbored SETD1B frameshift mutations, while five of 45 CRC (11.1%) with MSI-H harbored SETDB2
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frameshift mutations. SETD2 frameshift mutation was detected in three of 45 CRC (6.7%) with MSI-H.
The mutations were detected in the cancers with MSI-H, but not in those with MSS/MSIL (Table 2). There was a statistical difference in the SETD1B frameshift mutation frequencies between the cancers with MSI-H (28/76) and MSS/MSI-L (0/93) (Fisher’s exact test, p < 0.001). Also, there was a statistical difference in the SETDB2 frameshift mutation frequencies between the cancers with MSI-H (5/76) and MSS/MSI-L (0/93) (Fisher’s exact test, p = 0.017). In terms of tissue origins, there was no statistical difference in SETD1B nor SETDB2 nor SETD2 mutations between GC and CRC (Fisher’s exact test, p > 0.05). There was no significant association of the mutations with the clinicopathologic data of the patient (age,
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sex, histologic grade and stage) (χ2 test, p > 0.05). As for cancer stages, SETD1B mutations in the CRC were detected not only in TNM stages II and III, but also in TNM stage I, suggesting
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that the mutations might affect the pathogenesis at a relatively early stage of the cancers.
Regional heterogeneity of SETD1B mutation
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From 227 regional fragments of 39 CRC patients were collected and analyzed with respect to
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their regional status of SETD1B frameshift mutation. The 39 CRC consisted of six MSI-H (15.4%), three MSI-L (7.7%) and 30 MSS (76.9%). SETD1B frameshift mutations were detected in four CRC (10.3%), all of which were MSI-H. Of the four CRC with the mutations, two showed regional heterogeneity of the SETD1B frameshift mutation (#26 and 34), while
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the other two showed no heterogeneity (Figure 2). In a CRC (#26), the mutation was detected in two of three regions (Figure 2A). In the other case (#34), the mutation was detected in five
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of seven regions (Figure 2B). Neither case were proven to have regional ITH of MSI marker
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status (BAT25, BAT26, NR-21, NR-24 and MONO-27).
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Immunohistochemical analysis To see whether SETD1B was altered at protein level as well, we analyzed SETD1B protein expression in 31 GC and 45 CRC with MSI-H, and 45 GC and 48 CRC with MSS/MSI-L by immunohistochemistry (Figure 3). The immunostainings of SETD1B protein, when present, were observed in nuclei and cytoplasm, but nuclear staining was stronger than cytoplasmic staining (Figure 3). Immunopositivity for SETD1B was observed in 48 (60.8%) of the GC and 64 (68.8%) of the CRC (Table 3). The SETD1B expression was significantly different with respect to the MSI status (MSI-H Vs. MSI-L/MSS) (Fisher’s exact test, p < 0.01), but not with respect to the origin (GC Vs. CRC) (Fisher’s exact test, p > 0.05) (Table 3). SETD1B was expressed in both non-neoplastic gastric and colonic mucosal cells (IS ++). Negative
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controls using the blocking solution instead of the primary antibody showed no signal. On the initial score evaluation, the two pathologists had some disagreement (Cohen’s kappa
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coefficient; 0.75). For the remaining cases with disagreement, the pathologists examined the
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slides together and finally reached to an agreement.
Of the 28 cancers with SETD1B frameshift mutations, all except three (25/28) showed
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negative SETD1B immunostaining, and there was a significant difference of SETD1B
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immunostaining between MSI-H cancers with SETD1B frameshift mutations and those without SETD1B frameshift mutations (Fisher’s exact test, p < 0.001) (Table 3). There was no association of SETD1B expression with clinicopathologic parameters, including age, sex,
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depth of invasion and TNM stages (χ2 test, p > 0.05).
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Discussion It is becoming clear that alteration of histone methylation is important in cancer development.
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Although overall regulatory mechanisms of histone methylation are relatively well known,
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alterations of individual genes in tumorigenesis involved in histone methylation are largely unknown [1]. Based on earlier reports that gene in H3K4 methylation were mutationally and
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expressionally altered in some cancers and enhanced tumorigenesis [7-10, 13, 19], we
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attempted to disclose whether somatic frameshift mutations of SETD1B, SETDB2 and SETD2 were present in GC and CRC. Since nucleotide repeat sequences are targets for somatic mutations in cancers with MSI-H, we focused our study on the repeats in SETD1B, SETDB2 and SETD2 genes. We found SETD1B (38.7% of GC and 35.6% of CRC with MSI-H),
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SETDB2 (11.1% of CRC with MSI-H) and SETD2 frameshift mutations (6.7% of CRC with MSI-H). In addition, there was a significant difference of the mutation prevalence between the
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cancers with MSI-H and MSS/MSI-L, indicating that associations of the gene mutations with
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MSI-H were specific. We also analyzed the expression of SETD1B in GC and CRC tissues, and found that there was a significant difference of SETD1B expression between those with
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SETD1B mutation and those without the mutation. These data indicate that SETD1B, SETDB2 and SETD2 genes are altered in GC and CRC by somatic frameshift mutation and that SETD1B mutation might underlie the expression loss of SETD1B. In the present study, we observed two types of SETD1B, two types of SETDB2 and a type of SETD2 mutation (Table 2). All of them would replace amino acids after the frameshift mutations. The SETD1B mutations would delete amino acids after the 8th residue (Fulllength: 1923 amino acids) and remove almost all of the functional domains (RNA recognition motif, HCF-1-binding motif, N-SET, SET and post-SET domains) that are essential for the functions of SETD1B [24]. A SETD1B/GTF2H3 fusion devoid of these domains has been reported in hematologic neoplasia [25], suggesting that SETD1B truncation might possibly
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contribute to oncogenic activity. Currently, however, there is no other data on SETD1B functions with respect to tumorigenesis. In a recent report, SETD2 gene mutations in acute
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leukemias consisted of both missense and truncation mutations that were widespread in
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coding sequences [13]. Such mutation patterns and functional consequences of the SETD2 mutations (enhancing self-renewal of stem cells) suggested that SETD2 might be a TSG in
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leukemogenesis [13]. In solid tumors, renal cell carcinomas harbored large deletions of
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SETD2 locus as well [26, 27]. Together with these, our data suggest that inactivation of SETD2 by frameshift mutation might be involved in solid tumor development. There are reports that showed genetic ITH of microsatellite markers as well as ITH of repeat sequences in coding genes [28]. In the present study, we found ITH of SETD1B
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mutation among the CRC with SETD1B mutation (2/4: 50%). As for the clinicopathologic parameters, however, there was no definite difference between the CRCs with and without
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SETD1B ITH. Roles of ITH of SETD1B mutation remain to be clarified in conjunction with
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the identification of biological functions of SETD1B in cancers. The generation ITH may have implications for predictive and prognostic biomarker strategies. For example, low frequency
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mutations with a potential to metastasize or resistance against therapies define clinical outcomes since the clones with ITH can achieve clonal dominance during the disease progression and affect treatment efficacy [15]. In the context of pathology practice, the data suggest a possibility that there could be under- or over-estimation of SETD1B frameshift mutation in cancers with MSI-H. The data also suggest that when performing mutation analysis in cancers with MSI-H, multiple regional biopsies should be considered for a better evaluation of mutation status. We observed that SETD1B immunostaining was very weak or negative in most cancers with the frameshift mutations (Table 3). Because the anti-SETD1B antibody had been raised using a peptide that is located between amino acids 350 and 400 that would be removed by
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the SETD1B frameshift mutations, the SETD1B mutants may not be detected by the antibody. Direct DNA sequencing showed that all of the SETD1B mutations were heterozygous,
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suggesting that the second alleles were intact (Figure 1). Loss of SETD1B immunostaining in
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the mutant cases could be explained by the mutant alleles and any other gene silencing of the second alleles. Another possibility is that quantity of SETD1B expression from one allele
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might not be enough to be detected by the immunohistochemistry.
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It is generally agreed that SET domain-containing HMT genes are involved in tumorigenesis, but the alterations and mechanisms in detail remain elusive. In approximately 40% of GC and CRC with MSI-H, we found frameshift mutations of SETD1B, SETDB2 and SETD2 that may inactivate HMT functions and possibly alter gene expression. However, it is
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not known at current stage whether the mutations indeed play a causal role in tumorigenesis, or they simply reflect the fact that MSI-H tumors have a greater frequency of mutations in
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many genes because of the fact that they are unable to repair mismatch mutations. Our data
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support a possibility that SETD1B, SETDB2 and SETD2 mutations, especially in SETD1B, might not be passenger mutations. The most plausible explanation may be that the mutations
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were typical loss-of-function mutations occurred in important genes (chromatin-modulating genes) potentially involved in tumorigenesis. Recent flurry of mutation reports in chromatinrelated genes in human cancers also supports our idea [2]. Although our study provides evidence for the alterations, it did not disclose functional (e.g. changes of specific gene expression) and clinical consequences (e.g. clinical outcomes, MSI-status correlation). While somatic mutations of coding genes in cancers with MSI-H are much more common than those with MSS, chromosomal alterations (losses or gains) in cancers with MSI-H are much less common than those with MSS [29], suggesting that many of the mutated genes in MSI-H appear to be causal mutations. In addition, it is of interest that there were no statistical differences in mutations of these
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three genes between GC and CRC. An earlier study identified that the frequencies of frameshift mutations in CRC and endometrial carcinomas with MSI-H were moderately
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correlated, although some mutations showed tumor type specificity [29]. Many cancer-
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associated genes including TGFBR2 and BAX have been found to harbor frameshift mutations in both GC and CRC with MSI-H as well [14]. With this background, the prevalence of
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pathogenesis of GC and CRC with MSI-H.
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SETD1B, SETDB2 and SETD2 mutations may imply that they play similar role in the
In summary, our study identified mutational, expressional and ITH alterations of SET domain-containing HMT in GC and CRC with MSI-H. Many HMT are ideal targets as their enzymatic activities are druggable [2]. However, developing such inhibitors is being curbed
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by potential side effects [2]. Our study has added concerns about the application of such targets in cancer therapies, i.e., structural alterations of HTM by the mutation and ITH of the
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mutations, which should be considered in the clinical application to GC and CRC with MSI-
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H.
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Acknowledgements: This study was supported by a grant from National Research Foundation of Korea (2012R1A5A2047939).
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Table 1. Summary of pathologic features of the cancers. No. of colorectal carcinomas
MSI-H (n=31) MSS/MSI-L (n=45)
II
12
18
III
7
11
IV
1
1
Lauren’s subtype 18
25
Intestinal
13
20
EGC Vs. AGC
AC
Diffuse
D
15
TE
11
CE P
I
NU S
TNM
MSI-H (n=45) MSS/MSI-L (n=48)
I
5
6
II
25
21
III
13
17
IV
2
4
Cecum
10
1
Ascending
28
4
Transverse
6
3
MA
TNM
CR I
No. of gastric carcinomas
Location (colon)
EGC
3
4
Descending & sigmoid
1
15
AGC
28
41
Rectum
0
25
EGC: early gastric cancer, AGC: advanced gastric cancer, TNM: tumor, lymph node, metastasis, MSI-H: high microsatellite instability, MSI-L: low microsatellite instability, MSS: stable microsatellite instability
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Table 2. Summary of SETD1B, SETDB2 and SETD2 mutations in gastric and colorectal cancers
C7
MSI-H (25)
SETD1B Exon 1
C8
C6
MSI-H (3)
SETDB2 Exon 13
A8
A7
MSI-H (4)
A8
A9
MSI-H (1)
A7
A6
SETD2 Exon 3
MSI-H: high microsatellite instability
TE
13
CE P
Exon
MSI-H (3)
AC
SETDB2
Gastric: 10/31 (32.2)
Colorectal: 15/45 (33.3)
MA
C8
D
SETD1B Exon 1
NU S
Gene Location Wild type Mutation MSI status of the mutation cases (n) Incidence in MSI-H cancers (%)
Gastric: 2/31 (6.5) Colorectal: 1/45 (2.2)
Nucleotide change (predicted amino acid change) c.22delC (p.His8ThrfsX27)
c.21_22delCC (p.His8ProfsX29)
Colorectal: 4/45 (8.9)
c.2116delA (p.Ile706TyrfsX11)
Colorectal: 1/45 (2.2)
c.2116dupA (p.Ile706AsnfsX6)
Colorectal: 3/45 (6.7)
c.4219delA (p.Arg1407GlyfsX5)
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Table 3. Summary of SETD1B expression in gastric and colorectal cancers Positive expression (%)
CR I
(number of subcategory
NU S
positivity)
GC with MSI-H (n = 31)
14 (45.2) (+: 8, ++:6)
23 (51.1) (+: 11, ++: 12)
MA
CRC with MSI-H (n = 45)
TE
CRC with MSS/MSI-L (n = 48)
34 (75.5) (+: 18, ++: 16)
D
GC with MSS/MSI-L (n = 45)
41 (85.4) (+: 17, ++: 24) 3 (10.7) (+: 3)
MSI-H GC and CRC without SETD1B mutation (n = 141)
109 (77.3) (+: 51, ++; 58)
AC
CE P
MSI-H GC and CRC with SETD1B mutation (n = 28)
GC: gastric cancer, CRC: colorectal cancer, MSI-H: high microsatellite instability, MSI-L: low microsatellite instability, MSS: stable microsatellite instability
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Figure legends Figure 1. Representative SSCP and DNA sequencing of SETD1B, SETDB2 and SETD2 genes. SSCP (A) and DNA sequencing
CR I
analyses (B) of SETD1B (left), SETDB2 (middle) and SETD2 (right) from tumor (Lane T) and normal tissues (Lane N). A. In the SSCP,
NU S
the arrows (Lane T) indicate aberrant bands (arrows) compared to the SSCP from normal tissues (N). B. Direct DNA sequencing analyses of the PCR product of SETD1B (left), SETDB2 (middle) and SETD2 (right) show heterozygous deletions of a nucleotide in tumor tissues as
D
MA
compare to normal tissues.
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Figure 2. Intratumoral heterogeneity of SETD1B frameshift mutations in colon cancers. A: Direct DNA sequencing data show
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SETD1B c.22delC mutation (MT) in two (26-1 and 26-2) regional biopsies and wild-type (WT) SETD1B in a biopsy (26-7). B: Direct DNA
two biopsies (34-1 and 34-3).
AC
sequencing data show SETD1B c.22delC mutation (MT) in five (34-2, -4, -5, -6 and -7) regional biopsies and wild-type (WT) SETD1B in
Figure 3. Visualization of SET1B expression in gastric and colorectal cancer tissues by immunohistochemistry. A: Normal gastric mucosal cells show positive SETD1B immunostaining (IS ++). B: A gastric cancer shows positive SETD1B immunostaining in the cancer cells (IS ++). C: In a gastric cancer with SETD1B mutation, the cancer cells show negative SETD1B immunostaining (IS negative). D: Normal colonic mucosal cells show positive SETD1B immunostaining (IS ++). E: A colon cancer (T) shows positive SETD1B
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immunostaining in the cancer cells (IS ++). F: In a colon cancer with SETD1B mutation, the cancer cells show negative SETD1B
AC
CE P
TE
D
MA
NU S
CR I
immunostaining (IS negative).
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