Systemic Chromosome Instability Resulted in Colonic Transcriptomic Changes in Metabolic, Proliferation, and Stem Cell Regulators in Sgo1^−/+ Mice

Chromosome instability (CIN) is primarily caused by impaired mitotic fidelity, and leads to aneuploidy (1). CIN and aneuploidy are hallmarks of numerous cancers. In addition, CIN is especially prevalent in colon cancer (80%–90%) and is associated with poor prognosis (2). A study in Mad2-CIN mice model even suggested that CIN is causal to higher cancer recurrence (3). The remaining 10% to 20% of cases are associated with microsatellite instability (MIN), which is primarily caused by defects in DNA metabolism, especially in mismatch repair pathways (4). As colon cancer is the second most lethal cancer and is predicted to claim 49,700 lives this year in the United States alone (5), investigating CIN has high clinical relevance. The high prevalence of CIN among colon cancer may be due to CIN-causing mutations' involvement in colonic carcinogenesis itself. Many gene mutations that occur frequently in colon cancer, such as mutations in TP53, APC, and FBXW7 (6), can cause CIN, suggesting a strong link between the initiation and progression of colonic carcinogenesis and CIN (7). Researchers have attempted to use various model systems, including Drosophila (8), yeast (9), and aneuploid mice (10), to characterize CIN and aneuploidy, in hopes of elucidating the relationship between CIN and carcinogenesis and of developing a CIN/aneuploidy-targeting approach for cancer prevention or therapy (11–14). Models of CIN, including BubR1^−/+, Mad2^−/+, and cenpe^−/+ mice, demonstrated organ-specific oncogenic and tumor-suppressing effects (15. 16).

We developed a mouse model of CIN, the haploinsufficient (−/+) Shugoshin 1 (Sgo1) mouse. Approximately 48% of human colon cancers expressed less than 50% of Sgo1 mRNA (17), and 13% expressed abnormal dominant-negative Sgo1 transcript (18), suggesting a role of Sgo1 in human colon cancer. Sgo1 protein plays dual roles in cells as a centrosome component and as an accessory factor for the cohesin-mediated tethering of mitotic chromosomes. Sgo1 insufficiency resulted in reduced Sgo1 protein and partial loss of function. Consistently, Sgo1^−/+ fibroblasts showed an increase in multiple centrosomes and mitotic abnormalities, for example, premature chromosome separation and lagging chromosomes, that led to CIN (19), supporting the notion that the Sgo1 model would be valid for investigating the CIN-carcinogenesis relationship in select organs.

From the cancer profile, we hypothesized that the Sgo1 mouse may also provide a valid study model for lung and liver cancers, in addition to colon cancer. The mitotic process and the centrosome are both also targeted by hepatitis viruses like HBV and HCV (20–24). We have recently shown that the Sgo1 mouse as a possible model for viral liver cancer. Liver tissues from Sgo1^−/+ mice showed an increase in hepatocytes with multiple centrosomes (25). After treatment with colonic and hepatic carcinogen azoxymethane (AOM), Sgo1^−/+ mice showed rapid development of precancerous aberrant crypt foci (ACF; P < 0.05; ref. 19) and hepatocarcinoma (P < 0.05; ref. 25), indicating that CIN can aggravate colonic and hepatic carcinogenesis.

From the previous result in colon cancer (19), we anticipated that with AOM treatments, Sgo1 would develop later stage colon tumors straightforwardly. To test the prediction, we performed time course experiment monitoring carcinogenesis in three endpoints (12, 24, 36 weeks) after AOM treatments (26). Consistent with the prediction, Sgo1 mice rapidly developed more ACF due to activation of the oncogenic IL6 and Bcl2 pathways. However, unexpectedly, by the 24 weeks endpoint, many of the ACF and microtumors regressed in Sgo1. The result was partially explained by activated tumor suppressors INK4A (p16) and CDKN1A (p21; ref. 26). Thus carcinogenesis seemed to depend on balance among antagonizing pathways, yet the characterization was limited to select markers and was not comprehensive (19, 26). We posited that molecular events that are innate to the high CIN tissue of Sgo1^−/+ are responsible for the differential dynamics in colonic carcinogenesis, and intended to identify the specific events.

Here, we report colonic transcriptomic signatures in Sgo1^−/+ mice by comparing the transcriptome in normal-looking colonic mucosal tissues from Sgo1 mice with those from control wild-type mice. Although the use of genetically defined models aids in the identification of key changes without the complications of human tumor heterogeneity, to our knowledge, transcriptome analysis for transgenic CIN models has never been published. The human colon cancer transcriptome has been investigated (e.g., refs. 27, 28), yet characterization of the relationship between high CIN and the cancer transcriptome is limited (29). Our transcriptomic analyses showed unexpected results. As CIN starts early in colonic carcinogenesis (7), our results will aid in developing the framework for a targeted approach to chemoprevention at a seminal stage of carcinogenesis, and/or to identify markers for risk assessment.

Details for the generation of Sgo1 haploinsufficient (−/+) mice, the carcinogenesis assay with AOM treatment and sample collection were described previously (25, 26). Briefly, we bred 45 female wild-type mice and 45 female Sgo1^−/+ mice. All mice were generated with the low cancer-susceptible C57BL/6 background, and maintained in the Oklahoma Health Sciences Center (OUHSC) Biomedical Research Center rodent barrier facility. Standard diet (Purina) was fed throughout the experiment. On the seventh week after birth, the mice were grouped. Beginning in the eighth week, all mice were intraperitoneally injected with 4 mg/kg AOM diluted in 0.9% saline, twice a week for four weeks (8 administrations in total). We euthanized 15 wild-type mice and 15 Sgo1^−/+ mice using CO₂ asphyxiation at three different time points: the 12, 24, and 36 weeks after completion of AOM treatment. At each end point, we performed necropsies with gross examinations for tumors and any abnormalities, and collected normal-looking colonic mucosal tissue by scraping. Visible tumors were collected separately. The scraped colonic mucosal tissues and tumors were snap-frozen in liquid nitrogen, and stored in an −80°C freezer. For ACF and tumor counting, colons were cut open longitudinally and fixed in 10% formalin. ACF were counted using methylene blue staining and bright field microscopy. Once the ACF counting was complete, we embedded the colons in paraffin and made sections with a microtome for IHC. All treatments were in compliance with protocols approved by the OUHSC Institutional Animal Care and Use Committee. For CD36 expression analysis, untreated WT, Sgo1, and BubR1 mice were maintained for 12 months, and for apc mice, 3.5 months. For immune function analysis, we used 11- to 12-month-old untreated female WT (N = 3) and Sgo1 (N = 3) mice. Colons were collected and cut longitudinally. A half of colon was used for colonocytes recovery and FACS sorting, and the other half was preserved in OTC in dry ice/methanol bath then at −80°C for cryosectioning and immunofluorescence. The authors thank Histology and Immunohistochemistry Core at PC Stephenson Cancer Center, OUHSC for their help with tissue processing and cryosectioning.

Normal-looking parts of colonic mucosal tissues were scraped from at least 6 wild-type and 6 Sgo1 mice, all treated with AOM, at 24 weeks after the completion of AOM treatment. Total RNA was extracted with TRIzol reagent (Life Technologies) and subjected to cDNA library construction, followed by NGS as per the NGS protocol with an Illumina sequencer in the OUHSC core facility (Microgen) with the aid of Dr. Allison Gillaspy and Dr. Lydgia Jackson. The sequence data were deposited to the Geospiza/Perkin Elmer company server and analyzed with GeneSifter Bioinformatics software. The dataset was also deposited to NIH-GEO database (accession number GSE73100).

The same dataset was also analyzed with Strand Bioinformatics software (Strand-NGS). Illumina MiSeq-paired fastq files were aligned in Strand NGS software version 2.1 (www.strand-ngs.com) using mouse mm10 (UCSC) assembly. The December 2011 Mus musculus assembly [Genome Reference Consortium Mouse Build 38 (GCA_000001635.5)] was produced by the Mouse Genome Reference Consortium (http://genome.ucsc.edu/). Reads were normalized using DESeq and the normalized read counts were log-transformed and base-lined to the dataset, resulting in normalized signal values. Differential gene expression of the normalized signal values between the control and experimental group was done using a moderated t test, P < 0.05. The differentially expressed gene list was subsequently used for clustering and pathway analysis.

We used Student t test to analyze the data. Statistical significance was evaluated by algorisms integral to the aforementioned software. P values of <0.05 were considered significant.

We followed the previously described method of lipid composition analysis (30). The colonic mucosal tissue extracts were subjected to acid hydrolysis/methanolysis to generate fatty acid methyl esters (FAME). FAMEs were separated from other lipids by TLC on Silica Gel 60 plates using a solvent system of 80:20 hexane/ether. FAMEs were quantified using an Agilent Technologies 6890N gas chromatograph with a flame ionization detector. We measured the following fatty acids: (i) saturated fatty Acids—myristic acid (14:0), pentadecanoic acid (15:0), palmitic acid (16:0), and stearic acid (18:0); (ii) monounsaturated fatty acids—palmitoleic acid (16:1n-7) and oleic acid (18:1n-9); and (iii) polyunsaturated fatty acids (PUFA)—n-3 PUFA, α-linolenic acid (ALA, 18:3n-3), EPA (20:5n-3), DHA (22:6n-3), docosapentaenoic acid (DPA, 22:5n-3), n-6 PUFA, linoleic acid (18:2n-6), dihomo-γ-linolenic acid (DGLA, 20:3n-6), and arachidonic acid (20:4n-6). Fatty acids with a readout below detection levels were assigned the value of 0. We thank Lipid Analysis Core at Dean McGee Eye institute for fatty acid analysis.

We used the following primary antibodies in 1–2 μg/mL: anti-CD36 (Santa Cruz Biotechnology, sc-9154), anti-actin (Santa Cruz Biotechnology, sc-1616), anti-Numb (Biorbyt, orb6554), anti-JAG1 (Jagged1; Santa Cruz Biotechnology, SC-8303), anti-MSI1 (Musashi1; Santa Cruz Biotechnology, sc-98845), anti-CD24 (Santa Cruz Biotechnology, sc-11406), anti-CDKN1 p27 (Novus Biologicals, NB100-82093), and anti-γ-tubulin (Sigma, T9026). Standard immunoblotting procedures were followed as described previously (19). Colonic mucosal tissues were extracted in extraction buffer with homogenizer, then boiled with SDS-loading buffer for 5 minutes. Protein concentration was quantified using a protein assay dye reagent (Bio-Rad), and equalized. Immune complexes were detected with appropriate secondary antibodies conjugated with horseradish peroxidase (Sigma) and with chemiluminescence reagents (Thermo Scientific). For statistical analysis, signals in blots were quantified with ImageJ software (http://rsb.info.nih.gov/ij/). Protein expressions were standardized with control (actin or tubulin) expression in the corresponding lane, and compared with unpaired t test with Welch correction with GraphPad Prism 6 software. P values of <0.05 were considered significant.

Our IHC and immunofluorescence protocols were described in ref. 25 in detail. For calculating percentage, three to seven slides from different animals were analyzed, and at least 400 cells per picture were counted.

Mouse colons were dissociated for isolation of CD24, CD8a, and NK cells using a gentleMACS Dissociator and a MACSmixTM Tube Rotator according to the manufacturer's instructions (Miltenyi Biotech). The dissociated single-cell suspensions from colons were labeled with the respective antibodies for CD24-Alexa Fluor-488, CD8a-APC, and NK cells (Nkp1.1-APC and Nkp46-PE), and active cells by IFNγ-Alexa Fluor-488 staining, analyzed on a FACScalibur and data were analyzed by FlowJo software.

To investigate transcriptomic changes in colonic tissues from Sgo1^+/− mice (hereafter, Sgo1 mice), we performed NGS/RNA-Seq using the normal-looking part of colonic mucosal tissues of Sgo1 and control wild-type animals from a previous study (26), as the samples were well characterized. At the endpoint, numbers in ACF and microscopic tumor were counted under microscope and determined comparable (26), thus cancer tissue contamination in the samples affecting the results was improbable. The sample numbers met the requirements for statistical significance per Mead's resource equation (6/group). Overall, the gene expression profiles showed a pattern of differences between the control and Sgo1 groups in the heatmap (Fig. 1). A principal component analysis indicated that the control and Sgo1 samples were grouping together.

Using the dataset, we identified differentially expressed genes. There were total 349 hits with a 2-fold expression difference threshold, P < 0.05 (217 upregulated genes, 132 downregulated genes; examples in Table 1A). Significantly affected pathways (z-score >2) were identified, and indicated as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (Table 1B, upregulated pathways; downregulated pathways).

We anticipated that DNA damage and/or growth-regulatory pathways would appear among the most affected. However, the most affected upregulated genes were involved in biosynthesis of unsaturated fatty acids (z = 4.47). The Notch signaling (z = 4.47), insulin signaling (z = 3.81), PPAR signaling (z = 3.75), colorectal cancer–associated (z = 3.64), and mismatch repair (z = 3.47) pathways were also strongly affected (Table 1B). Thus, the regulation of metabolism and receptor-ligand–based growth were most affected. Activation of mismatch repair may be due to an increase in DNA damage.

The downregulated genes that were most impacted were involved in the allograft rejection (z = 6.69), cyanoamino acid metabolism (z = 6.61), graft-versus-host disease (z = 6.54), and type I diabetes mellitus (z = 6.20) pathways (Table 1B). These findings strongly suggest the impairment of or a modulation in immune responses in colonic tissues from Sgo1 mice.

Notably upregulated genes [e.g., CD36 (11.49-fold), perilipin (6.21-fold), adiponectin (5.73-fold); Fig. 2A] involved in lipid metabolism. Sgo1 (reduced expression) and β-actin (equal expression) are shown as controls (Fig. 2A). CD36 is an integral membrane glycoprotein, a scavenger receptor, and is also known as fatty acid translocase (31, 32). Consistent with the findings from NGS/RNA-Seq, CD36 protein was shown to be upregulated in results from immunoblots and IHC (Fig. 2B). Detailed immunofluorescence analysis in AOM-untreated colon revealed the presence of CD36 in small infiltrating cells (Fig. 2C, orange arrow) and a few distinctive colonocytes in Sgo1 colon tissues (Fig. 2C, white arrow), but CD36 was not found in the extracellular matrix. In wild-type tissues, CD36 was detected primarily in small infiltrating cells. To test whether the CD36⁺ colonocytes have CIN, we observed untreated colons from other transgenic model mice known to generate high CIN, namely spindle checkpoint BubR1^−/+ mice and apc^min/+ mice. Percentages of CD36⁺ colonocytes in Sgo1, BubR1, and apc mice were significantly higher than that in wild type, providing a circumstantial evidence that CD36 is a marker of colon with high CIN.

Perilipin, also known as lipid droplet–binding protein, coats and mobilizes lipid droplets in adipose tissue (33). Adiponectin functions as a protein hormone and modulates metabolic processes, including glucose regulation and fatty acid oxidation (34). Transgenic overexpression of perilipin in adipocytes protected the mice from obesity as a result of feeding a high-fat diet (35). Overexpression of adiponectin in white adipocytes led to abrogation of adipocyte differentiation and weight loss in mice (36). However, the average body weight of the Sgo1 mice was comparable with that of controls (26).

From these results, we hypothesized that the colonic tissues of Sgo1 mice would show altered lipid composition. We analyzed the fatty acid composition in the mucosal tissues from AOM-treated and untreated wild-type (n = 3) and Sgo1 colonic mucosal tissues (n = 3; Table 2). Notable differences in the lipid composition were found (marked in asterisks), implying that lipid metabolism is indeed affected in Sgo1 mice. In particular, DHA levels were consistently lower in Sgo1 mice both in AOM-treated and untreated conditions.

Consistent with gene expression changes in multiple pathways in Sgo1 mouse tissues, we found that several transcription factors are significantly upregulated in colonic tissues of Sgo1 mice. Among these were Tcf7 (2.73-fold), Foxa2 (2.10-fold), Foxq1 (2.14-fold), and Hox genes [Hoxa9 (2.97-fold), Hoxa13 (2.83-fold), Hoxa3 (2.14-fold)], which are involved in differentiation and in many cancers, including colon cancers (37).

The NGS analysis detected upregulation in the Notch signaling pathway, which is highly relevant to colon cancer (38, 39). Activation of Notch signaling is involved in colonic cancer stem cell maintenance (40, 41). We investigated the amount and localization of selected colonic (normal) stem cell markers (Fig. 3). Immunoblots showed an increase in the Notch pathway inhibitory regulator Numb, and in colonic stem cell markers JAG1 (Jagged-1; P < 0.05), while MSI1 (Musahi-1), and Lgr5 showed a tendency toward increase but the high variance resulted in nonsignificant P values. In contrast, levels of CD24, a cell adhesion protein involved in leukocyte migration to the colon (42) and a colonic cancer stem cell marker (43), decreased in Sgo1 mice (P < 0.05).

We used IHC to investigate the localizations of the stem cell markers. Among the markers tested, Numb and Jag1 showed most notable differences (Fig. 3B and C). Jag1 normally localizes to the bottom of colonic crypts, corresponding with normal stem cells. However, in a small number of crypts in Sgo1 mice, Jag1 localized in areas up to the midsection of the crypts. Overall, stem cell marker analysis indicated misregulation of stem cell markers in Sgo1 mice.

Next, with the pathway analysis suggesting a decrease in immune response, we tested functions of immune system components in colons of 11- to 12-month-old AOM-untreated wild-type control (N = 3) and Sgo1 (n = 3; Fig. 4). CD24 expressions were measured among all immune cells. In wild type, 68.27% ± 4.819% were CD24-high expressing cells. In contrast, only 43.70% ± 4.330% of total CD24-expressing cells in Sgo1 were high expressors, and there were clear separations between CD24-high expressing cells and CD24-low expressing cells (Fig. 4A), confirming immunoblots in Fig. 3A. CD24⁺ cells were infrequent in Sgo1 colon tissues (Fig. 4A). Next (Fig. 4B), we monitored CD8⁺ cytotoxic T cells. 80.27% ± 8.877% of CD8⁺ cells recovered from wild-type colons are IFNγ-positive, but only 34.83% ± 2.975% were from Sgo1 (P < 0.05), indicating a majority of CD8⁺ cytotoxic T cells in Sgo1 were either not activated or incapable of producing IFNγ and exert cytotoxicity. Consistently, in wild-type CD8⁺ cells were also IFN-γ positive, but in Sgo1 they did not always colocalize (Fig. 4B). Next, NK cell functions were tested with two sorting markers Nkp46 (Fig. 4C) and Nkp1.1 (Fig. 4D). Similar to CD8⁺ cytotoxic T cells, there was a significant decrease in IFNγ-expressing NK cells in Sgo1 (Fig. 4C and D). Together, the FACS results indicated that a significant population of CD8⁺ cytotoxic T cells and Nkp46+ or Nkp1.1+ NK cells in the colons of Sgo1 mice were either not activated or incapable of producing IFNγ, confirming prediction from NGS analysis that the immune cell functions were partly dysfunctional in Sgo1.

Previously, we observed that transgenic mice that carry mutations causing systemic CIN developed colon cancers differently from controls (7, 26). We questioned the underlying cause of the altered carcinogenesis profiles in the CIN models. In this study, we identified several affected pathways in the colons of the AOM-treated CIN model Sgo1^−/+ mice. In the absence of histologic carcinogenesis, CIN tissues activated or repressed multiple pathways, some of which were previously reported to be involved in colonic carcinogenesis. Also notably, the gene expression changes were not associated with a change in overall crypt structure (e.g., elongation of crypts observed in apc mice; refs. 44, 45). Our results showed that some characteristics of cancer can be acquired with CIN prior to the development of histologic abnormalities, dysplasia, and cancer. At this stage, cells probably still maintain most anticarcinogenic signaling pathways, such as cell death and senescence. This likelihood makes it an ideal stage in which to introduce preventive agents to intervene in carcinogenesis.

The fatty acid biosynthesis, Notch signaling, PPAR, and insulin signaling pathways were activated, while immune responses such as the allograft rejection and graft-versus-host disease pathways were unexpectedly repressed in the NGS analysis. Consistently, our results showed that immune cell functions were indeed compromised in AOM-untreated Sgo1-CIN mice (Fig. 4). Together, the modulations of the pathways may provide favorable microenvironment to early colonic carcinogenesis (a hypothetical model is presented in Fig. 5).

A legitimate question is that whether the NGS results from AOM-treated mice are the same with those from untreated mice. For following reasons it seems likely; (i) our pilot small-scale NGS in untreated mice did show similar pattern (data not shown), (ii) lipid compositions and CD36 expression showed differences between untreated control and Sgo1, and (iii) immune repression indicated in NGS with AOM-treated mice was confirmed in untreated Sgo1 (Fig. 4). Expanding NGS approach to untreated mice and other conditions will shed light on effects of CIN in vivo.

Colon cancer transcriptome analysis indicated that fatty acid metabolism is altered in cancer. The lipidome is shown to correlate with colon cancer (46). Fatty acid binding protein 1 (FABP1) is usually among the most upregulated genes in the colon cancer transcriptome (28), potentially to meet altered requirements for energy metabolism and to adopt to cancer's hypoxic and acidic microenvironment. However, it was surprising for histologically normal-looking tissues to already exhibit modifications in fatty acid metabolism.

We observed changes in the lipid composition in Sgo1 mice (Table 2). Lipid metabolism and the associated lipid-based signaling modulation can influence colon carcinogenesis in different ways. For example, the COX-2 and arachidonic acid–mediated inflammatory pathways, and amounts of omega-3 EPA and DHA, are well-established to influence colonic carcinogenesis (47). We observed unexpected reduction of arachidonic acid in Sgo1 (that may work as anti-inflammatory), as well as a decrease in DHA (that may work as proinflammatory). Our results suggest that modulating the lipid metabolism with a pharmaceutical agent or through diet may be a valid strategy to influence CIN.

The Notch signaling pathway plays an important role in embryogenesis and cellular homeostasis, differentiation, and apoptosis through “canonical” and “noncanonical” pathways, a ligand- or transcription-independent function (38, 39). The canonical Notch pathway includes at least four Notch receptors (Notch 1–4) and five Notch ligands: Delta-like 1, 3, and 4, and Jagged 1 and 2. Numb functions as an inhibitor of Notch signaling by degrading Notch. During neurogenesis, Notch signaling promotes proliferative signaling, and Numb-mediated Notch inhibition promotes neural differentiation. Activation of the Notch pathway may play an oncogenic role in colon and pancreatic cancers (38). Notch signaling has also been found to play a pivotal role in cancer stem cell development. A number of Notch signaling and cancer stem cell–targeting strategies have been proposed for colon cancer prevention and therapy (40, 41). We observed misregulations in stem cell markers in Sgo1 mice, and this is the first report for CIN itself affecting stem cell regulations. This finding will lead to investigations on underlying mechanisms. For example, as Sgo1 defect can cause multiple centrosomes, it is tempting to speculate that the defect may disturb spindle orientation in the colonic stem cells, which may serve as a mechanistic basis for maintaining asymmetric division of stem cell and stemness (48). High-resolution imaging analysis focusing on dividing stem cells in Sgo1 mice is warranted to test the speculation.

PPAR α, γ, and β/δ are nuclear transcription factors that form heterodimers with Retinoid X receptor. Numerous studies indicated that PPARs are involved in colon cancer, although the mode of involvement has proved to be complex (49). Insulin receptor signaling is involved in glucose uptake and storage, lipid synthesis, protein synthesis, and mitogenic responses. These pathways have been associated with colon cancer (28). Our study placed the involvement of the PPAR and insulin signaling at the onset of CIN, an unexpectedly early stage in colon cancer development.

Current cancer chemoprevention strategies lean on anti-inflammatory reagents, and downregulation of immune responses with CIN was counterintuitive. Our results and the mechanism investigation may allow fine tuning of immunomodulation approach.

Immunosurveillance is involved in suppressing tetraploid cells in the colon (50). A weakened immune system may provide a microenvironment that promotes the survival of aneuploid cells and carcinogenesis. This study, for the first time, provided evidence that CIN may be involved in immune system suppression. Further study will reveal the mechanisms by which Sgo1-CIN leads to potential immune suppression. Current hypotheses under investigation include: (i) CIN causes direct injury to immune cells, (ii) CIN mediates damage to colonocytes, leading to activation of an anergic response, and (iii) CIN mediates proteotoxicity, leading to suppression of proinflammatory factors, such as IL1 and IFNγ. Proteotoxicity and ER stress is a downstream event of CIN (9, 10) and is also reported to inhibit IL1 and IFNγ (51). Alternatively, (iv) altered expression of CD24 (Figs. 3A and 4A) may have a negative effect on leukocyte recruitment in the Sgo1 colon. CD24^−/− mice have fewer leukocytes in the colon than do wild-type mice (42). Further identifying the sequence of events connecting CIN and immune responses would lead to immunopreventive/therapeutic agents for cells with CIN.

This study uncovered many pathways that were not previously associated with CIN. Although unexpected, our results were at least partly consistent with findings using other model systems. In synthetic lethal screenings with a genetically tractable Drosophila Melanogaster model, a CIN-causing Mad2 mutant showed synthetic lethality with metabolism modulator genes (8). Taken together, these findings suggest that the cellular responses to CIN may be conserved among species, including insects.

For clinical translation, we aim to use our results to identify genes that indicate (i) that CIN can be used as a risk assessment marker or to distinguish CIN cells for targeting, and/or (ii) that CIN are involved in early-stage carcinogenesis, and can thus be inhibited to prevent cancer. We identified CD36 by applying additional criteria: a cell surface protein and the knockdown or inhibition of which is not known to cause disease (Fig. 2). A gene product that meets all of these criteria may be an ideal target for vaccination and other antibody-based targeting approaches. The validity of CD36 for the targeting approach is being tested, yet the use of the transcriptome would be beneficial for identifying potential targets that could be used in combination with secondary screening.

In summary, we used a transgenic CIN model to identify several pathways that were not previously connected to CIN. These results and further validation would provide numerous unexpected targets for intervention in colonic carcinogenesis for chemo- and dietary-prevention purposes.

No potential conflicts of interest were disclosed.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conception and design: C.V. Rao, A. Mohammed, H.Y. Yamada

Development of methodology: C.V. Rao, N.B. Janakiram, A. Mohammed, H.Y. Yamada

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): C.V. Rao, S. Sanghera, Y. Zhang, A. Reddy, S. Lightfoot, N.B. Janakiram, A. Mohammed, W. Dai, H.Y. Yamada

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): C.V. Rao, S. Lightfoot, N.B. Janakiram, A. Mohammed, W. Dai, H.Y. Yamada

Writing, review, and/or revision of the manuscript: C.V. Rao, N.B. Janakiram, H.Y. Yamada

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): C.V. Rao, L. Biddick, H.Y. Yamada

Study supervision: C.V. Rao, H.Y. Yamada

Other (technical work: animal care and maintenance, histologic work): L. Biddick

Other (specifically performed and analyzed immunologic impacts observed in Sgo1 mice): N.B. Janakiram

This work was supported by grants from the U.S. NIH NCI R01CA094962 (C.V. Rao), RO1CA090658 (W. Dai), and NCI (RO3CA162538 to H.Y. Yamada). H.Y. Yamada was also supported by a Chris4Life Colon Cancer Foundation pilot study grant. In addition, this project (or publication) was supported by the National Center for Research Resources and the National Institute of General Medical Sciences of the NIH through grant number 8P20GM103447 [Oklahoma's IDeA Network for Biomedical Research Excellence (OK-INBRE)] to the OUHSC Microgen core facility.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.