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Prognostic and functional role of subtype-specific tumor-stroma interaction in breast cancer.

ABSTRACT: None of the clinically relevant gene expression signatures available for breast cancer were specifically developed to capture the influence of the microenvironment on tumor cells. Here, we attempted to build subtype-specific signatures derived from an in vitro model reproducing tumor cell modifications after interaction with activated or normal stromal cells. Gene expression signatures derived from HER2+, luminal, and basal breast cancer cell lines (treated by normal fibroblasts or cancer-associated fibroblasts conditioned media) were evaluated in clinical tumors by in silico analysis on published gene expression profiles (GEPs). Patients were classified as microenvironment-positive (μENV+ve), that is, with tumors showing molecular profiles suggesting activation by the stroma, or microenvironment-negative (μENV-ve) based on correlation of their tumors' GEP with the respective subtype-specific signature. Patients with estrogen receptor alpha (ER)+/HER2-/μENV+ve tumors were characterized by 2.5-fold higher risk of developing distant metastases (HR = 2.546; 95% CI: 1.751-3.701, P = 9.84E-07), while μENV status did not affect, or only suggested the risk of distant metastases, in women with HER2+ (HR = 1.541; 95% CI: 0.788-3.012, P = 0.206) or ER-/HER2- tumors (HR = 1.894; 95% CI: 0.938-3.824; P = 0.0747), respectively. In ER+/HER2- tumors, the μENV status remained significantly associated with metastatic progression (HR = 2.098; CI: 1.214-3.624; P = 0.00791) in multivariable analysis including size, age, and Genomic Grade Index. Validity of our in vitro model was also supported by in vitro biological endpoints such as cell growth (MTT assay) and migration/invasion (Transwell assay). In vitro-derived gene signatures tracing the bidirectional interaction with cancer activated fibroblasts are subtype-specific and add independent prognostic information to classical prognostic variables in women with ER+/HER2- tumors.

SUBMITTER: Merlino G

PROVIDER: S-EPMC5623822 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe tumor microenvironment and intercellular communication between solid tumors and the surrounding stroma play crucial roles in cancer initiation, progression, and prognosis. Radiomics provides clinically relevant information from radiological images; however, its biological implications in uncovering tumor pathophysiology driven by cellular heterogeneity between the tumor and stroma are largely unknown. We aimed to identify radiogenomic signatures of cellular tumor-stroma heterogeneity (TSH) to improve breast cancer management and prognosis analysis.MethodsThis retrospective multicohort study included five datasets. Cell subpopulations were estimated using bulk gene expression data, and the relative difference in cell subpopulations between the tumor and stroma was used as a biomarker to categorize patients into good- and poor-survival groups. A radiogenomic signature-based model utilizing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was developed to target TSH, and its clinical significance in relation to survival outcomes was independently validated.ResultsThe final cohorts of 1330 women were included for cellular TSH biomarker identification (n = 112, mean age, 57.3 years ± 14.6) and validation (n = 886, mean age, 58.9 years ± 13.1), radiogenomic signature of TSH identification (n = 91, mean age, 55.5 years ± 11.4), and prognostic (n = 241) assessments. The cytotoxic lymphocyte biomarker differentiated patients into good- and poor-survival groups (p < 0.0001) and was independently validated (p = 0.014). The good survival group exhibited denser cell interconnections. The radiogenomic signature of TSH was identified and showed a positive association with overall survival (p = 0.038) and recurrence-free survival (p = 3 × 10-4).ConclusionRadiogenomic signatures provide insights into prognostic factors that reflect the imbalanced tumor-stroma environment, thereby presenting breast cancer-specific biological implications and prognostic significance.

Project description:BackgroundTumor associated macrophages (TAMs) are alternatively activated macrophages that enhance tumor progression by promoting tumor cell invasion, migration and angiogenesis. TAMs have an anti-inflammatory function resembling M2 macrophages. CD163 is regarded as a highly specific monocyte/macrophage marker for M2 macrophages. In this study we evaluated the specificity of using the M2 macrophage marker CD163 as a TAM marker and compared its prognostic value with the more frequently used pan-macrophage marker CD68. We also analyzed the prognostic value of the localization of CD163(+) and CD68(+) myeloid cells in human breast cancer.MethodsThe extent of infiltrating CD163(+) or CD68(+) myeloid cells in tumor nest versus tumor stroma was evaluated by immunohistochemistry in tissue microarrays with tumors from 144 breast cancer cases. Spearman's Rho and χ(2) tests were used to examine the correlations between CD163(+) or CD68(+) myeloid cells and clinicopathological parameters. Kaplan Meier analysis and Cox proportional hazards modeling were used to assess the impact of CD163(+) and CD68(+) myeloid cells in tumor stroma and tumor nest, respectively, on recurrence free survival, breast cancer specific and overall survival.ResultsWe found that infiltration of CD163(+) and CD68(+) macrophages into tumor stroma, but not into tumor nest, were of clinical relevance. CD163(+) macrophages in tumor stroma positively correlated with higher grade, larger tumor size, Ki67 positivity, estrogen receptor negativity, progesterone receptor negativity, triple-negative/basal-like breast cancer and inversely correlated with luminal A breast cancer. Some CD163(+) areas lacked CD68 expression, suggesting that CD163 could be used as a general anti-inflammatory myeloid marker with prognostic impact. CD68(+) macrophages in tumor stroma positively correlated to tumor size and inversely correlated to luminal A breast cancer. More importantly, CD68 in tumor stroma was an independent prognostic factor for reduced breast cancer specific survival.ConclusionThese findings highlight the importance of analyzing the localization rather than merely the presence of TAMs as a prognostic marker for breast cancer patients.

Project description:PurposeCHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC.Patients and methodsCHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies.ResultsProportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom.ConclusionThese CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.

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Prognostic and functional role of subtype-specific tumor-stroma interaction in breast cancer.

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