Krüppel-like factor 9 (KLF9) prevents colorectal cancer through inhibition of interferon-related signaling.

UNLABELLED: Expression of the transcription factor Krüppel-like factor 9 (KLF9) is frequently reduced in colorectal cancers, although a tumor suppressive role has not been established. To determine if KLF9 suppresses intestinal adenoma formation, we generated mice of distinct Klf9 genotypes in the background of the Apc (Min/+) mouse and compared their adenoma burdens at 16 weeks of age. While small intestine adenoma burden remained unchanged among Klf9 genotypes, male and female Apc(Min/+)/Klf9(-/-) and Apc(Min/+)/Klf9(+/-) mice exhibited significantly more colon adenomas than their Apc(Min/+)/Klf9(+/+) counterparts. Microarray analysis showed significant increases in the expression of interferon-induced genes in the colon mucosa of female Apc (Min/+)/Klf9(+/-) and Apc(Min/+)/Klf9(-/-) compared to Apc(Min/+)/Klf9(+/+) mice, prior to overt adenoma occurrence. Gene upregulation was confirmed by qPCR of colon mucosa and by siRNA knockdown of KLF9 in human HT29 colorectal cancer cells. Increases in expression of these genes were further augmented by supplementation with Interferon ß1. Circulating levels of the cytokine, interferon-stimulated gene 15 (ISG15) were increased in Apc(Min/+)/Klf9(+/-) and Apc(Min/+)/Klf9(-/-) mice relative to Apc(Min/+)/Klf9(+/+). Additionally, colon mucosal levels of ISG15 were increased in Apc(Min/+)/Klf9(+/-) mice. Chromatin immunoprecipitation demonstrated KLF9 recruitment to the ISG15 promoter. Lastly, treatment with ISG15 suppressed apoptosis in HT29 cells, in the presence and absence of 5-fluorouracil (5FU). Results show KLF9 to be a haploinsufficient suppressor of colon tumorigenesis in Apc(Min/+) mice in part, by repression of ISG15 and the latter's antiapoptotic function. SUMMARY: Krüppel-like factor 9 (KLF9) is a haploinsufficient tumor suppressor in the ApcMin/+ mouse colon by suppressing expression of ISG15, an apoptosis-inhibiting cytokine.

GWAS of 972 autologous stem cell recipients with multiple myeloma identifies 11 genetic variants associated with chemotherapy-induced oral mucositis.

PURPOSE: High-dose chemotherapy and autologous stem cell transplant (ASCT) to treat multiple myeloma (MM) and other cancers carries the risk of oral mucositis (OM) with sequelae including impaired nutritional and fluid intake, pain, and infectious complications. As a result of these problems, cancer treatment may have to be interrupted or delayed. In this study, we looked beyond OM's known risk factors of renal function and melphalan dose with a genome-wide association study (GWAS) to evaluate whether genetic variants in conjunction with clinical risk factors influence predisposition for OM. METHODS: Genotyping was performed using Illumina HumanOmni1-Quad v1.0 BeadChip and further assessed for data quality. We tested 892,589 germline single-nucleotide polymorphisms (SNPs) for association with OM among 972 Caucasian patients treated with high-dose melphalan and ASCT in Total Therapy clinical trials (TT2, TT3, TT4) for newly diagnosed MM. Statistical analyses included t tests, stepwise regression modeling, and logistic regression modeling to find baseline clinical factors and genotypes associated with OM. RESULTS: We found that 353 (36.3 %) patients had grades 2-4 OM. Type of treatment protocol, baseline estimated glomerular filtration rate, and melphalan dose along with baseline serum albumin and female gender predicted 43.6 % of grades 2-4 OM cases. Eleven SNPs located in or near matrix metalloproteinase 13, JPH3, DHRS7C, CEP192, CPEB1/LINC00692, FBN2, ALDH1A1, and DMRTA1/FLJ35282 were associated with grades 2-4 OM. The addition of these SNPs increased sensitivity in detecting grades 2-4 OM cases to 52 %. CONCLUSIONS: These SNPs may be important for their roles in inflammatory pathways, epithelial healing, and chemotherapy detoxification.

Germline Genetic Variants in TEK, ANGPT1, ANGPT2, MMP9, FGF2 and VEGFA Are Associated with Pathologic Complete Response to Bevacizumab in Breast Cancer Patients.

BACKGROUND: We previously reported improved pathologic complete response (pCR) in a prospective phase II study using neoadjuvant bevacizumab in combination with chemotherapy compared to chemotherapy alone in breast cancer patients (41% vs. 25%, p = 0.0291). In this study, we queried germline single-nucleotide polymorphisms (SNPs) in angiogenesis-related genes for their impact on pCR and overall survival (OS). METHODS: DNA for genotyping was available from 34 subjects who received bevacizumab in addition to chemotherapy and 29 subjects who did not. Using Illumina® technology, we queried 504 SNPs with a minor allele frequency (MAF) of at least 5%, located in 10 angiogenesis-related genes, for their effect on pCR via logistic regression with an additive-inheritance model while adjusting for race and bevacizumab treatment. SNPs that showed significant associations with pCR were selected for additional characterization. RESULTS: After adjusting for race and tumor type, patients who had bevacizumab added to their neoadjuvant therapy were found to experience a significantly improved rate of pCR compared to patients who did not (adjusted OR 8.40, 95% CI 1.90-37.1). When patients were analyzed for SNP effects via logistic regression with race and bevacizumab treatment included as covariates, two SNPs in angiopoietin 1 (ANGPT1), six in ANGPT2, three in fibroblast growth factor 2 (FGF2), four in matrix metalloproteinase 9 (MMP9), three in tyrosine kinase, endothelial (TEK) and two in vascular endothelial growth factor A (VEGFA) were associated with pCR (P<0.05). However, when overall survival was considered, there was no difference between treatment groups or between genotypes. CONCLUSION: Genetic variability in TEK, ANGPT1, ANGPT2, FGF2, MMP9 and VEGFA is associated with pCR in bevacizumab-treated patients. Consistent with other studies, adding bevacizumab to standard chemotherapy did not impact OS, likely due to other factors and thus, while SNPs in TEK, ANGPT1, ANGPT2, FGF2, MMP9 and VEGFA were associated with pCR, they were not predictive of OS in this patient population. TRIAL REGISTRATION: ClinicalTrials.gov NCT00203502.

Impact of elevated plasma serotonin on global gene expression of murine megakaryocytes.

BACKGROUND: Serotonin (5-HT) is a biogenic amine that also acts as a mitogen and a developmental signal early in rodent embryogenesis. Genetic and pharmacological disruption of 5-HT signaling causes various diseases and disorders via mediating central nervous system, cardiovascular system, and serious abnormalities on a growing embryo. Today, neither the effective modulators on 5-HT signaling pathways nor the genes affected by 5-HT signal are well known yet. METHODOLOGY/PRINCIPAL FINDINGS: In an attempt to identify the genes altered by 5-HT signaling pathways, we analyzed the global gene expression via the Illumina array platform using the mouse WG-6 v2.0 Expression BeadChip containing 45,281 probe sets representing 30,854 genes in megakaryocytes isolated from mice infused with 5-HT or saline. We identified 723 differentially expressed genes of which 706 were induced and 17 were repressed by elevated plasma 5-HT. CONCLUSIONS/SIGNIFICANCE: Hierarchical gene clustering analysis was utilized to represent relations between groups and clusters. Using gene ontology mining tools and canonical pathway analyses, we identified multiple biological pathways that are regulated by 5-HT: (i) cytoskeletal remodeling, (ii) G-protein signaling, (iii) vesicular transport, and (iv) apoptosis and survival. Our data encompass the first extensive genome-wide based profiling in the progenitors of platelets in response to 5-HT elevation in vivo.

Standardization of Gene Expression Quantification by Absolute Real-Time qRT-PCR System Using a Single Standard for Marker and Reference Genes.

In the last decade, genome-wide gene expression data has been collected from a large number of cancer specimens. In many studies utilizing either microarray-based or knowledge-based gene expression profiling, both the validation of candidate genes and the identification and inclusion of biomarkers in prognosis-modeling has employed real-time quantitative PCR on reverse transcribed mRNA (qRT-PCR) because of its inherent sensitivity and quantitative nature. In qRT-PCR data analysis, an internal reference gene is used to normalize the variation in input sample quantity. The relative quantification method used in current real-time qRT-PCR analysis fails to ensure data comparability pivotal in identification of prognostic biomarkers. By employing an absolute qRT-PCR system that uses a single standard for marker and reference genes (SSMR) to achieve absolute quantification, we showed that the normalized gene expression data is comparable and independent of variations in the quantities of sample as well as the standard used for generating standard curves. We compared two sets of normalized gene expression data with same histological diagnosis of brain tumor from two labs using relative and absolute real-time qRT-PCR. Base-10 logarithms of the gene expression ratio relative to ACTB were evaluated for statistical equivalence between tumors processed by two different labs. The results showed an approximate comparability for normalized gene expression quantified using a SSMR-based qRT-PCR. Incomparable results were seen for the gene expression data using relative real-time qRT-PCR, due to inequality in molar concentration of two standards for marker and reference genes. Overall results show that SSMR-based real-time qRT-PCR ensures comparability of gene expression data much needed in establishment of prognostic/predictive models for cancer patients-a process that requires large sample sizes by combining independent sets of data.

Establishment of prognostic models for astrocytic and oligodendroglial brain tumors with standardized quantification of marker gene expression and clinical variables.

BACKGROUND: Prognosis models established using multiple molecular markers in cancer along with clinical variables should enable prediction of natural disease progression and residual risk faced by patients. In this study, multivariate Cox proportional hazards analyses were done based on overall survival (OS) of 100 glioblastoma multiformes (GBMs, 92 events), 49 anaplastic astrocytomas (AAs, 33 events), 45 gliomas with oligodendroglial features, including anaplastic oligodendroglioma (AO, 13 events) and oligodendraglioma (O, 9 events). The modeling included two clinical variables (patient age and recurrence at the time of sample collection) and the expression variables of 13 genes selected based on their proven biological and/or prognosis functions in gliomas (ABCG2, BMI1, MELK, MSI1, PROM1, CDK4, EGFR, MMP2, VEGFA, PAX6, PTEN, RPS9, and IGFBP2). Gene expression data was a log-transformed ratio of marker and reference (ACTB) mRNA levels quantified using absolute real-time qRT-PCR. RESULTS: Age is positively associated with overall grade (4 for GBM, 3 for AA, 2_1 for AO_O), but lacks significant prognostic value in each grade. Recurrence is an unfavorable prognostic factor for AA, but lacks significant prognostic values for GBM and AO_O. Univariate models revealed opposing prognostic effects of ABCG2, MELK, BMI1, PROM1, IGFBP2, PAX6, RPS9, and MSI1 expressions for astrocytic (GBM and AA) and oligodendroglial tumors (AO_O). Multivariate models revealed independent prognostic values for the expressions of MSI1 (unfavorable) in GBM, CDK4 (unfavorable) and MMP2 (favorable) in AA, while IGFBP2 and MELK (unfavorable) in AO_O. With all 13 genes and 2 clinical variables, the model R(2) was 14.2% (P = 0.358) for GBM, 45.2% (P = 0.029) for AA, and 62.2% (P = 0.008) for AO_O. CONCLUSION: The study signifies the challenge in establishing a significant prognosis model for GBM. Our success in establishing prognosis models for AA and AO_O was largely based on identification of a set of genes with independent prognostic values and application of standardized gene expression quantification to allow formation of a large cohort in analysis.