Limits...
Identification of stromal ColXα1 and tumor-infiltrating lymphocytes as putative predictive markers of neoadjuvant therapy in estrogen receptor-positive/HER2-positive breast cancer.

Brodsky AS, Xiong J, Yang D, Schorl C, Fenton MA, Graves TA, Sikov WM, Resnick MB, Wang Y - BMC Cancer (2016)

Bottom Line: We performed gene expression profiling on pre-NAC+H tumor samples from responding (no or minimal residual disease at surgery) and non-responding patients.Increased expression of genes encoding for stromal collagens, including Col10A1, and reduced expression of immune-associated genes, reflecting lower levels of total tumor-infiltrating lymphocytes (TILs), were strongly associated with poor pathologic response.ROC analysis suggests strong specificity and sensitivity for this combination in predicting treatment response.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Laboratory Medicine, Rhode Island Hospital and Lifespan Medical Center, Warren Alpert Medical School of Brown University, Providence, USA. alex_brodsky@brown.edu.

ABSTRACT

Background: The influence of the tumor microenvironment and tumor-stromal interactions on the heterogeneity of response within breast cancer subtypes have just begun to be explored. This study focuses on patients with estrogen receptor-positive/human epidermal growth factor receptor 2-positive (ER+/HER2+) breast cancer receiving neoadjuvant chemotherapy and HER2-targeted therapy (NAC+H), and was designed to identify novel predictive biomarkers by combining gene expression analysis and immunohistochemistry with pathologic response.

Methods: We performed gene expression profiling on pre-NAC+H tumor samples from responding (no or minimal residual disease at surgery) and non-responding patients. Gene set enrichment analysis identified potentially relevant pathways, and immunohistochemical staining of pre-treatment biopsies was used to measure protein levels of those pathways, which were correlated with pathologic response in both univariate and multivariate analysis.

Results: Increased expression of genes encoding for stromal collagens, including Col10A1, and reduced expression of immune-associated genes, reflecting lower levels of total tumor-infiltrating lymphocytes (TILs), were strongly associated with poor pathologic response. Lower TILs in tumor biopsies correlated with reduced likelihood of achieving an optimal pathologic response, but increased expression of the Col10A1 gene product, colXα1, had greater predictive value than stromal abundance for poor response (OR = 18.9, p = 0.003), and the combination of increased colXα1 expression and low TILs was significantly associated with poor response in multivariate analysis. ROC analysis suggests strong specificity and sensitivity for this combination in predicting treatment response.

Conclusions: Increased expression of stromal colXα1 and low TILs correlate with poor pathologic response in ER+/HER2+ breast tumors. Further studies are needed to confirm their predictive value and impact on long-term outcomes, and to determine whether this collagen exerts a protective effect on the cancer cells or simply reflects other factors within the tumor microenvironment.

No MeSH data available.


Related in: MedlinePlus

ColXα1 IHC scoring is strongly associated with NAC response. a ROC analysis of colXα1 IHC scores, stroma scores, and percent TIL. AUC = Area Under the Curve, SE = Standard Error. b Stroma and sTIL scores did not distinguish responders as strongly as colXα1 IHC. Box and whisker plots of each parameter show distinct separation between tumors that responded to NAC and those that with no response. *P < 0.05, ***P < 0.001
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4835834&req=5

Fig4: ColXα1 IHC scoring is strongly associated with NAC response. a ROC analysis of colXα1 IHC scores, stroma scores, and percent TIL. AUC = Area Under the Curve, SE = Standard Error. b Stroma and sTIL scores did not distinguish responders as strongly as colXα1 IHC. Box and whisker plots of each parameter show distinct separation between tumors that responded to NAC and those that with no response. *P < 0.05, ***P < 0.001

Mentions: Multiple lines of evidence suggest that colXα1 IHC is a strong candidate marker. ColXα1 IHC discriminates good from poor responding patients with a low false positive rate. This is also reflected in the ROC curves where the colXα1 IHC is a more specific and sensitive marker of good response compared to stroma (Fig. 4a). ROC curves and box plots demonstrate that colXα1 and TIL strongly separate patients by good response, while the stroma score did not (Fig. 4). This indicated that high colXα1 expression by itself is an independent predictive factor, and not merely a reflection of more tumor associated stroma. Clinical biomarkers need to have very high specificity and sensitivity [20]. The high sensitivity, specificity, and accuracy of the colXα1 scoring support its further development as a marker for response in the NAC setting.Fig. 4


Identification of stromal ColXα1 and tumor-infiltrating lymphocytes as putative predictive markers of neoadjuvant therapy in estrogen receptor-positive/HER2-positive breast cancer.

Brodsky AS, Xiong J, Yang D, Schorl C, Fenton MA, Graves TA, Sikov WM, Resnick MB, Wang Y - BMC Cancer (2016)

ColXα1 IHC scoring is strongly associated with NAC response. a ROC analysis of colXα1 IHC scores, stroma scores, and percent TIL. AUC = Area Under the Curve, SE = Standard Error. b Stroma and sTIL scores did not distinguish responders as strongly as colXα1 IHC. Box and whisker plots of each parameter show distinct separation between tumors that responded to NAC and those that with no response. *P < 0.05, ***P < 0.001
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4835834&req=5

Fig4: ColXα1 IHC scoring is strongly associated with NAC response. a ROC analysis of colXα1 IHC scores, stroma scores, and percent TIL. AUC = Area Under the Curve, SE = Standard Error. b Stroma and sTIL scores did not distinguish responders as strongly as colXα1 IHC. Box and whisker plots of each parameter show distinct separation between tumors that responded to NAC and those that with no response. *P < 0.05, ***P < 0.001
Mentions: Multiple lines of evidence suggest that colXα1 IHC is a strong candidate marker. ColXα1 IHC discriminates good from poor responding patients with a low false positive rate. This is also reflected in the ROC curves where the colXα1 IHC is a more specific and sensitive marker of good response compared to stroma (Fig. 4a). ROC curves and box plots demonstrate that colXα1 and TIL strongly separate patients by good response, while the stroma score did not (Fig. 4). This indicated that high colXα1 expression by itself is an independent predictive factor, and not merely a reflection of more tumor associated stroma. Clinical biomarkers need to have very high specificity and sensitivity [20]. The high sensitivity, specificity, and accuracy of the colXα1 scoring support its further development as a marker for response in the NAC setting.Fig. 4

Bottom Line: We performed gene expression profiling on pre-NAC+H tumor samples from responding (no or minimal residual disease at surgery) and non-responding patients.Increased expression of genes encoding for stromal collagens, including Col10A1, and reduced expression of immune-associated genes, reflecting lower levels of total tumor-infiltrating lymphocytes (TILs), were strongly associated with poor pathologic response.ROC analysis suggests strong specificity and sensitivity for this combination in predicting treatment response.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Laboratory Medicine, Rhode Island Hospital and Lifespan Medical Center, Warren Alpert Medical School of Brown University, Providence, USA. alex_brodsky@brown.edu.

ABSTRACT

Background: The influence of the tumor microenvironment and tumor-stromal interactions on the heterogeneity of response within breast cancer subtypes have just begun to be explored. This study focuses on patients with estrogen receptor-positive/human epidermal growth factor receptor 2-positive (ER+/HER2+) breast cancer receiving neoadjuvant chemotherapy and HER2-targeted therapy (NAC+H), and was designed to identify novel predictive biomarkers by combining gene expression analysis and immunohistochemistry with pathologic response.

Methods: We performed gene expression profiling on pre-NAC+H tumor samples from responding (no or minimal residual disease at surgery) and non-responding patients. Gene set enrichment analysis identified potentially relevant pathways, and immunohistochemical staining of pre-treatment biopsies was used to measure protein levels of those pathways, which were correlated with pathologic response in both univariate and multivariate analysis.

Results: Increased expression of genes encoding for stromal collagens, including Col10A1, and reduced expression of immune-associated genes, reflecting lower levels of total tumor-infiltrating lymphocytes (TILs), were strongly associated with poor pathologic response. Lower TILs in tumor biopsies correlated with reduced likelihood of achieving an optimal pathologic response, but increased expression of the Col10A1 gene product, colXα1, had greater predictive value than stromal abundance for poor response (OR = 18.9, p = 0.003), and the combination of increased colXα1 expression and low TILs was significantly associated with poor response in multivariate analysis. ROC analysis suggests strong specificity and sensitivity for this combination in predicting treatment response.

Conclusions: Increased expression of stromal colXα1 and low TILs correlate with poor pathologic response in ER+/HER2+ breast tumors. Further studies are needed to confirm their predictive value and impact on long-term outcomes, and to determine whether this collagen exerts a protective effect on the cancer cells or simply reflects other factors within the tumor microenvironment.

No MeSH data available.


Related in: MedlinePlus