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A distinct pre-existing inflammatory tumour microenvironment is associated with chemotherapy resistance in high-grade serous epithelial ovarian cancer.

Koti M, Siu A, Clément I, Bidarimath M, Turashvili G, Edwards A, Rahimi K, Mes-Masson AM, Masson AM, Squire JA - Br. J. Cancer (2015)

Bottom Line: A total of 11 significantly differentially expressed genes were found to distinguish the two groups.As STAT1 was the most significantly differentially expressed gene (P=0.003), we validated the expression of STAT1 protein by immunohistochemistry using an independent cohort of 183 (52 resistant and 131 sensitive) HGSC cases on a primary tumour tissue microarray.Relative expression levels were subjected to Kaplan-Meier survival analysis and Cox proportional hazard regression models.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario K7L 3N6, Canada.

ABSTRACT

Background: Chemotherapy resistance is a major determinant of poor overall survival rates in high-grade serous ovarian cancer (HGSC). We have previously shown that gene expression alterations affecting the NF-κB pathway characterise chemotherapy resistance in HGSC, suggesting that the regulation of an immune response may be associated with this phenotype.

Methods: Given that intrinsic drug resistance pre-exists and is governed by both tumour and host factors, the current study was performed to examine the cross-talk between tumour inflammatory microenvironment and cancer cells, and their roles in mediating differential chemotherapy response in HGSC patients. Expression profiling of a panel of 184 inflammation-related genes was performed in 15 chemoresistant and 19 chemosensitive HGSC tumours using the NanoString nCounter platform.

Results: A total of 11 significantly differentially expressed genes were found to distinguish the two groups. As STAT1 was the most significantly differentially expressed gene (P=0.003), we validated the expression of STAT1 protein by immunohistochemistry using an independent cohort of 183 (52 resistant and 131 sensitive) HGSC cases on a primary tumour tissue microarray. Relative expression levels were subjected to Kaplan-Meier survival analysis and Cox proportional hazard regression models.

Conclusions: This study confirms that higher STAT1 expression is significantly associated with increased progression-free survival and that this protein together with other mediators of tumour-host microenvironment can be applied as a novel response predictive biomarker in HGSC. Furthermore, an overall underactive immune microenvironment suggests that the pre-existing state of the tumour immune microenvironment could determine response to chemotherapy in HGSC.

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Related in: MedlinePlus

Comparison of inflammatory gene expression levels in chemotherapy-resistant vs -sensitive high-grade serous ovarian tumours. The profile of inflammatory markers in the two study cohorts was determined by NanoString nCounter platform. Data normalisation was performed using nSolver software followed by application of Bonferroni test for multiple comparisons using Graphpad Prism software to determine significantly differentially expressed genes. The 11 most significantly differentially expressed genes (P<0.05) are shown.
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fig1: Comparison of inflammatory gene expression levels in chemotherapy-resistant vs -sensitive high-grade serous ovarian tumours. The profile of inflammatory markers in the two study cohorts was determined by NanoString nCounter platform. Data normalisation was performed using nSolver software followed by application of Bonferroni test for multiple comparisons using Graphpad Prism software to determine significantly differentially expressed genes. The 11 most significantly differentially expressed genes (P<0.05) are shown.

Mentions: In this study, inflammatory gene expression profiling, by NanoString technology, of HGSCs that were clinically classified as chemotherapy resistant and sensitive displayed significant (P<0.05) different expression levels in eleven genes. STAT1, CXCL10, CREB1, MKNK1, MAP3K7, CFL1, PTK2, RIPK1, MYD88, CCL8 and CCL7 were overexpressed in the sensitive cohort compared with the resistant (Figure 1), consistent with the rationale that these chemokines and immune factors could be active in the host microenvironment and promote a more favourable drug response. To determine the reproducibility of these findings, technical validation of 8 of the 11 genes was performed using qRT–PCR. Technical validation of the differentially expressed genes showed full concordance with the NanoString-based gene expression findings (Supplementary Figure 1). Of these eight genes more highly expressed in the sensitive cohort, the interferon (IFN)-inducible protein (IP-10)/CXCL10 is one of the major targets of STAT1 activation by IFNγ. We therefore performed Pearson's correlation analysis comparing the expressions of these two genes in the resistant (Figure 2A) and sensitive (Figure 2B) tumours to determine their respective correlation coefficients. This analysis revealed a strong positive correlation between the expression of STAT1 and CXCL10 genes within the resistant and sensitive groups with r2=0.81 (P<0.001) and r2 =0.77 (P<0.0002), respectively. Moreover, the greatly increased expression levels of STAT1 in the sensitive tumours is consistent with this protein having a functional role in mediating an improved response to chemotherapy, underscoring the importance of confirming these findings at the protein level.


A distinct pre-existing inflammatory tumour microenvironment is associated with chemotherapy resistance in high-grade serous epithelial ovarian cancer.

Koti M, Siu A, Clément I, Bidarimath M, Turashvili G, Edwards A, Rahimi K, Mes-Masson AM, Masson AM, Squire JA - Br. J. Cancer (2015)

Comparison of inflammatory gene expression levels in chemotherapy-resistant vs -sensitive high-grade serous ovarian tumours. The profile of inflammatory markers in the two study cohorts was determined by NanoString nCounter platform. Data normalisation was performed using nSolver software followed by application of Bonferroni test for multiple comparisons using Graphpad Prism software to determine significantly differentially expressed genes. The 11 most significantly differentially expressed genes (P<0.05) are shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4385963&req=5

fig1: Comparison of inflammatory gene expression levels in chemotherapy-resistant vs -sensitive high-grade serous ovarian tumours. The profile of inflammatory markers in the two study cohorts was determined by NanoString nCounter platform. Data normalisation was performed using nSolver software followed by application of Bonferroni test for multiple comparisons using Graphpad Prism software to determine significantly differentially expressed genes. The 11 most significantly differentially expressed genes (P<0.05) are shown.
Mentions: In this study, inflammatory gene expression profiling, by NanoString technology, of HGSCs that were clinically classified as chemotherapy resistant and sensitive displayed significant (P<0.05) different expression levels in eleven genes. STAT1, CXCL10, CREB1, MKNK1, MAP3K7, CFL1, PTK2, RIPK1, MYD88, CCL8 and CCL7 were overexpressed in the sensitive cohort compared with the resistant (Figure 1), consistent with the rationale that these chemokines and immune factors could be active in the host microenvironment and promote a more favourable drug response. To determine the reproducibility of these findings, technical validation of 8 of the 11 genes was performed using qRT–PCR. Technical validation of the differentially expressed genes showed full concordance with the NanoString-based gene expression findings (Supplementary Figure 1). Of these eight genes more highly expressed in the sensitive cohort, the interferon (IFN)-inducible protein (IP-10)/CXCL10 is one of the major targets of STAT1 activation by IFNγ. We therefore performed Pearson's correlation analysis comparing the expressions of these two genes in the resistant (Figure 2A) and sensitive (Figure 2B) tumours to determine their respective correlation coefficients. This analysis revealed a strong positive correlation between the expression of STAT1 and CXCL10 genes within the resistant and sensitive groups with r2=0.81 (P<0.001) and r2 =0.77 (P<0.0002), respectively. Moreover, the greatly increased expression levels of STAT1 in the sensitive tumours is consistent with this protein having a functional role in mediating an improved response to chemotherapy, underscoring the importance of confirming these findings at the protein level.

Bottom Line: A total of 11 significantly differentially expressed genes were found to distinguish the two groups.As STAT1 was the most significantly differentially expressed gene (P=0.003), we validated the expression of STAT1 protein by immunohistochemistry using an independent cohort of 183 (52 resistant and 131 sensitive) HGSC cases on a primary tumour tissue microarray.Relative expression levels were subjected to Kaplan-Meier survival analysis and Cox proportional hazard regression models.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario K7L 3N6, Canada.

ABSTRACT

Background: Chemotherapy resistance is a major determinant of poor overall survival rates in high-grade serous ovarian cancer (HGSC). We have previously shown that gene expression alterations affecting the NF-κB pathway characterise chemotherapy resistance in HGSC, suggesting that the regulation of an immune response may be associated with this phenotype.

Methods: Given that intrinsic drug resistance pre-exists and is governed by both tumour and host factors, the current study was performed to examine the cross-talk between tumour inflammatory microenvironment and cancer cells, and their roles in mediating differential chemotherapy response in HGSC patients. Expression profiling of a panel of 184 inflammation-related genes was performed in 15 chemoresistant and 19 chemosensitive HGSC tumours using the NanoString nCounter platform.

Results: A total of 11 significantly differentially expressed genes were found to distinguish the two groups. As STAT1 was the most significantly differentially expressed gene (P=0.003), we validated the expression of STAT1 protein by immunohistochemistry using an independent cohort of 183 (52 resistant and 131 sensitive) HGSC cases on a primary tumour tissue microarray. Relative expression levels were subjected to Kaplan-Meier survival analysis and Cox proportional hazard regression models.

Conclusions: This study confirms that higher STAT1 expression is significantly associated with increased progression-free survival and that this protein together with other mediators of tumour-host microenvironment can be applied as a novel response predictive biomarker in HGSC. Furthermore, an overall underactive immune microenvironment suggests that the pre-existing state of the tumour immune microenvironment could determine response to chemotherapy in HGSC.

Show MeSH
Related in: MedlinePlus