Cell Cycle Progression Gene Expression Research Articles

Targeting fatty acid synthase in preclinical models of TNBC brain metastases synergizes with SN-38 and impairs invasion

Fatty acid synthesis (FAS) has been shown to play a key role in the survival of brain-metastatic (BM) breast cancer. We demonstrate that the fatty acid synthase inhibitor TVB-2640 synergizes with the topoisomerase inhibitor SN-38 in triple-negative breast cancer (TNBC) BM cell lines, upregulates FAS and downregulates cell cycle progression gene expression, and slows the motility of TNBC BM cell lines. The combination of SN-38 and TVB-2640 warrants further consideration as a potential therapeutic option in TNBC BMs.

Effect and mechanism of chitosan-based nano-controlled release system on the promotion of cell cycle progression gene expression

Effect and mechanism of chitosan-based nano-controlled release system on the promotion of cell cycle progression gene expression

Role of Host GPR120 in Mediating Dietary Omega-3 Fatty Acid Inhibition of Prostate Cancer.

GPR120, a G protein-coupled receptor for long-chain polyunsaturated fatty acids (FAs), mediates the anti-inflammatory effects of omega-3 (ω-3) FAs. We investigated whether host or tumor GPR120 plays a role in the anti-prostate cancer effects of ω-3 FAs. MycCap prostate cancer allografts were grown in immunocompetent wild-type (WT) and GPR120 knockout (KO) mice fed ω-3 (fish oil) or ω-6 (corn oil) diets. Immune cell infiltration was quantified by flow cytometry, and gene expression of immune cell markers in isolated tumor-associated macrophages (TAMs) was quantified by quantitative real-time polymerase chain reaction. Archived tissue from a fish oil intervention trial was used to correlate gene expression of GPR120 with cell cycle progression (CCP) genes and Ki67 index (n = 11-15 per group). All statistical tests were two-sided. In WT mice (n = 7 per group), dietary ω-3 FAs decreased MycCap allograft tumor growth (mean [SD] final tumor volume ω-6 = 491 [437] mm3 vs ω-3 = 127 [77] mm3, P = .04), whereas in global GPR120KO mice (n = 7 per group) ω-3 FAs had no anticancer effects. Dietary ω-3 FAs inhibited GPR120KO-MycCaP allografts grown in WT mice (n = 8 per group; mean [SD] final tumor volume ω-6 = 776 [767] mm3 vs ω-3 = 36 [34] mm3, P = .02). Omega-3 FA treatment decreased the number of M2-like TAMs in tumor tissue and gene expression of M2 markers in isolated TAMs compared with ω-6 controls in WT (n = 7 per group) but not in GPR120KO mice (n = 7 per group). In human tissue, higher expression of stromal GPR120 correlated with greater reduction in expression of CCP genes in men with prostate cancer on a high-ω-3 diet (r = -.57, P = .04). Host GPR120 plays a central role in the anti-prostate cancer effects of dietary ω-3 FAs. Future studies are required to determine if the anticancer effects of ω-3 FAs are mediated through inhibition of M2-like macrophages and if host GPR120 status predicts anticancer effects of dietary ω-3 FAs in men with prostate cancer.

Evaluation of microarrays for measuring cell cycle progression (CCP) gene expression.

e16566 Background: A CCP score has been developed and validated to provide prognostic information in prostate cancer. To date, our studies have exclusively used qRT-PCR to measure CCP gene expression, which is generally considered the ‘gold-standard’ for measuring RNA expression levels. However, qRT-PCR allows for the interrogation of a relatively small number of genes. Because prostate cancer biopsies provide very limited tissue, there is interest in evaluating RNA expression platforms that could simultaneously integrate CCP genes and other less characterized targets that might be clinically useful. Here we evaluate the ability of microarrays to measure CCP gene expression. Methods: CCP scores for 1636 radical prostatectomy samples submitted for commercial testing were generated from the mean expression of 31 CCP genes and 15 housekeeping genes as determined by qRT-PCR. CCP scores were also generated from several publically available Affymetrix microarray expression data sets (Nakagawa et al. 2008, Karnes et al. 2013, Klein et al. 2014, Boormans et al. 2013, Taylor et al. 2013) by averaging the intensities (RMA processed, base 2 log scale) of the 31 CCP genes. Expression data were evaluated by comparing CCP score range and pairwise correlations between CCP genes. Results: The average pair-wise correlation in the commercial cohort using qRT-PCR was 0.67. The pair-wise correlations in the microarray studies were significantly lower, ranging from 0.17 (Klein) to 0.58 (Boormans). Importantly, the data in Boormans et al. was generated from frozen tissue. The CCP score in our commercial cohort ranged from -2 to 3 (base 2 log scale) with a standard deviation (SD) of 0.79. In contrast, the CCP score range in microarray studies was highly truncated with SDs ranging from 0.12 (Nakagawa) to 0.46 (Boormans). Conclusions: Expression of CCP genes as determined by microarrays correlates weakly with expression measured by qRT-PCR, with reduction in normally observed pairwise correlations among CCP genes and the range of CCP scores. This is especially true if the RNA is derived from fixed tissue. As a result, microarray generated CCP scores cannot be assumed to be a valid surrogate for qRT-PCR generated scores for prediction of patient outcome.

Prognostic utility of the cell cycle progression (CCP) score generated from needle biopsy in men treated with prostatectomy.

17 Background: We developed a prognostic RNA signature that is strongly associated with prostate cancer outcomes. The cell cycle progression (CCP) score has proven to have prognostic utility in predicting disease progression in various clinical settings utilizing biopsy, transurethral resection of the prostate (TURP) and post-prostatectomy specimens. Previous studies evaluating post-surgical outcomes were conducted using CCP gene expression measured in the prostatectomy specimen. Here, we demonstrate the ability of the CCP score to predict cancer progression, as measured by both biochemical recurrence (BCR) and metastatic disease after radical prostatectomy, using needle biopsy tissue. Methods: We evaluated the CCP score in three patient cohorts. These included men from the Martini Clinic (MC, N=283), the Durham VA Medical Center (DVA, N=176), and Intermountain Healthcare (IHC, N=123). The CCP score was derived from a simulated biopsy (MC) or diagnostic biopsy (DVA and IHC), and evaluated for association with BCR and metastatic disease in univariable analysis and after adjusting for other clinical information. Results: In all three cohorts, the CCP score was associated with BCR and metastatic disease. The association with BCR remained significant after adjusting for other prognostic clinical variables. In a combined analysis of all three cohorts (N=582), the CCP score was a strong predictor of BCR in both univariable (HR per Interquartile Range [IQR] = 1.68 [95% CI: 1.41, 1.99), p value<10−6]) and multivariable analyses (HR per IQR = 1.53 [95%CI: 1.28, 1.84], p value < 10−4). CCP score was the strongest predictor of metastatic disease in both univariable analysis (HR per IQR = 6.32 [95% CI: 3.41, 11.71, p value<10−7]), and after adjusting for clinical variables (HR per IQR = 4.83 [95% CI: 2.40, 9.74, p value<10−5]). Conclusions: The CCP score derived from a needle biopsy sample was strongly associated with adverse outcome after surgery. It was the strongest predictor of eventual metastatic disease of the tested variables including Gleason and PSA. These results indicate that the CCP score can be used at disease diagnosis to better define patient prognosis and appropriate clinical care.

Abstract IA6: Cell cycle progression genes differentiate indolent from aggressive prostate cancer

Abstract Background: In cancers with variable natural history, prognostic biomarkers are needed for selecting patients for therapeutic intervention. This is particularly true for prostate cancer, where many screen-detected cases are indolent and predicting adverse outcomes is difficult. Therefore, we developed an expression signature composed of genes involved in cell cycle progression (CCP) and tested its utility in prostate cancer. Methods: We developed a 46-gene prognostic RNA signature that is based on measuring the expression of CCP genes. The expression score (CCP score) is derived as the normalized mean expression all CCP genes in the signature. Results: The prognostic utility of the CCP score has been tested in both multiple clinical settings and patient populations. First, it was tested in a post-prostatectomy cohort from the U.S. where the CCP score predicted biochemical recurrence in univariate (χ2 = 34.0, 1df, p = 5·6 × 10-9) and multivariate analysis (χ2 = 21.65, 1df, p = 3.3 × 10-6). CCP score and PSA were the dominant variables in the best predictive model and were much more significant than any other clinical measure. Second, it was tested in a conservatively managed TURP cohort from the UK where the CCP score was the dominant variable for predicting death from prostate cancer in both univariate (χ2 = 92.7, 1df, p = 6.1 × 10-22) and multivariate analyses (χ2 = 42.2, p = 8.2 × 10-11). Third, it was tested in a conservatively managed needle biopsy cohort from the UK where the CCP score was a better univariate predictor of prostate cancer death than any other variable (χ2 = 37·6, 1df, p = 8.6 × 10-10). The best multivariate model from this study included Gleason and PSA, but CCP dominated (HR for one unit increase = 1.65, 95% CI (1.31, 2.09) χ2 = 17.7, P = 3 × 10-5) with Gleason score (χ2 = 12.1, P = 5 × 10-4) and baseline PSA (χ2 = 5.7, P = 0.017) providing significant, but smaller additional contributions. Conclusions: A CCP expression signature is prognostic in prostate cancer patients at diagnosis and after prostatectomy. It consistently provides information beyond clinical and pathological variables to help differentiate aggressive from indolent disease. Studies aimed at expanding the clinical utility of this signature are warranted and ongoing. Citation Format: Steven Stone, On behalf of the Transatlantic Prostate Group, Jack Cuzick, Dan Berney, Julia Reid, Gabrielle Fisher, Jerry Lanchbury, Alexander Gutin, Greg Swanson. Cell cycle progression genes differentiate indolent from aggressive prostate cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr IA6.