Bridging Histopathology and Radiomics Toward Prognosis of Metastasis in Early Breast Cancer.

Tumor histomorphology is crucial for the prognostication of breast cancer outcomes because it contains histological, cellular, and molecular tumor heterogeneity related to metastatic potential. To enhance breast cancer prognosis, we aimed to apply radiomics analysis-traditionally used in 3D scans-to 2D histopathology slides. This study tested radiomics analysis in a cohort of 92 breast tumor specimens for outcome prognosis, addressing -omics dimensionality by comparing models with moderate and high feature counts, using least absolute shrinkage and selection operator for feature selection and machine learning for prognostic modeling. In the test folds, models with radiomics features [area under the curves (AUCs) range 0.799-0.823] significantly outperformed the benchmark model, which only included clinicopathological (CP) parameters (AUC = 0.584). The moderate-dimensionality model with 11 CP + 93 radiomics features matched the performance of the highly dimensional models with 1,208 radiomics or 11 CP + 1,208 radiomics features, showing average AUCs of 0.823, 0.799, and 0.807 and accuracies of 79.8, 79.3, and 76.6%, respectively. In conclusion, our application of deep texture radiomics analysis to 2D histopathology showed strong prognostic performance with a moderate-dimensionality model, surpassing a benchmark based on standard CP parameters, indicating that this deep texture histomics approach could potentially become a valuable prognostic tool.

Analysis of Spatial Distribution and Prognostic Value of Different Pan Cytokeratin Immunostaining Intensities in Breast Tumor Tissue Sections.

Cancer risk prognosis could improve patient survival through early personalized treatment decisions. This is the first systematic analysis of the spatial and prognostic distribution of different pan cytokeratin immunostaining intensities in breast tumors. The prognostic model included 102 breast carcinoma patients, with distant metastasis occurrence as the endpoint. We segmented the full intensity range (0-255) of pan cytokeratin digitized immunostaining into seven discrete narrow grey level ranges: 0-130, 130-160, 160-180, 180-200, 200-220, 220-240, and 240-255. These images were subsequently examined by 33 major (GLCM), fractal and first-order statistics computational analysis features. Interestingly, while moderate intensities were strongly associated with metastasis outcome, high intensities of pan cytokeratin immunostaining provided no prognostic value even after an exhaustive computational analysis. The intense pan cytokeratin immunostaining was also relatively rare, suggesting the low differentiation state of epithelial cells. The observed variability in immunostaining intensities highlighted the intratumoral heterogeneity of the malignant cells and its association with a poor disease outcome. The prognostic importance of the moderate intensity range established by complex computational morphology analyses was supported by simple measurements of its immunostaining area which was associated with favorable disease outcome. This study reveals intratumoral heterogeneity of the pan cytokeratin immunostaining together with the prognostic evaluation and spatial distribution of its discrete intensities.

Size and Shape Filtering of Malignant Cell Clusters within Breast Tumors Identifies Scattered Individual Epithelial Cells as the Most Valuable Histomorphological Clue in the Prognosis of Distant Metastasis Risk.

Survival and life quality of breast cancer patients could be improved by more aggressive chemotherapy for those at high metastasis risk and less intense treatments for low-risk patients. Such personalized treatment cannot be currently achieved due to the insufficient reliability of metastasis risk prognosis. The purpose of this study was therefore, to identify novel histopathological prognostic markers of metastasis risk through exhaustive computational image analysis of 80 size and shape subsets of epithelial clusters in breast tumors. The group of 102 patients had a follow-up median of 12.3 years, without lymph node spread and systemic treatments. Epithelial cells were stained by the AE1/AE3 pan-cytokeratin antibody cocktail. The size and shape subsets of the stained epithelial cell clusters were defined in each image by use of the circularity and size filters and analyzed for prognostic performance. Epithelial areas with the optimal prognostic performance were uniformly small and round and could be recognized as individual epithelial cells scattered in tumor stroma. Their count achieved an area under the receiver operating characteristic curve (AUC) of 0.82, total area (AUC = 0.77), average size (AUC = 0.63), and circularity (AUC = 0.62). In conclusion, by use of computational image analysis as a hypothesis-free discovery tool, this study reveals the histomorphological marker with a high prognostic value that is simple and therefore easy to quantify by visual microscopy.

Author Correction: Iscador Qu inhibits doxorubicin-induced senescence of MCF7 cells.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis.

Improved prognosis of breast cancer outcome could prolong patient survival by reliable identification of patients at high risk of metastasis occurrence which could benefit from more aggressive treatments. Based on such clinical need, we prognostically evaluated the malignant cells in breast tumors, as the obvious potential source of unexploited prognostic information. The patient group was homogeneous, without any systemic treatments or lymph node spread, with smaller tumor size (pT1/2) and a long follow-up. Epithelial cells were labeled with AE1/AE3 pan-cytokeratin antibody cocktail and comprehensively analyzed. Monofractal and multifractal analyses were applied for quantification of distribution, shape, complexity and texture of malignant cell clusters, while mean pixel intensity and total area were measures of the pan-cytokeratin immunostaining intensity. The results surprisingly indicate that simple binary images and monofractal analysis provided better prognostic information then grayscale images and multifractal analysis. The key findings were that shapes and distribution of malignant cell clusters (by binary fractal dimension; AUC = 0.29), their contour shapes (by outline fractal dimension; AUC = 0.31) and intensity of the pan-cytokeratin immunostaining (by mean pixel intensity; AUC = 0.30) offered significant performance in metastasis risk prognostication. The results reveal an association between the lower pan-cytokeratin staining intensity and the high metastasis risk. Another interesting result was that multivariate analysis could confirm the prognostic independence only for fractal but not for immunostaining intensity features. The obtained results reveal several novel and unexpected findings highlighting the independent prognostic efficacy of malignant cell cluster distribution and contour shapes in breast tumors.

Iscador Qu inhibits doxorubicin-induced senescence of MCF7 cells.

Chemotherapy in patients with inoperable or advanced breast cancer inevitably results in low-dose exposure of tumor-cell subset and senescence. Metabolically active senescent cells secrete multiple tumor promoting factors making their elimination a therapeutic priority. Viscum album is one of the most widely used alternative anti-cancer medicines facilitating chemotherapy tolerance of breast cancer patients. The aim of this study was to model and investigate how Viscum album extracts execute additive anti-tumor activity with low-dose Dox using ER + MCF7 breast cancer cells. We report that cotreatment of MCF7 with Viscum album and Dox abrogates G2/M cycle arrest replacing senescence with intrinsic apoptotic program. Mechanistically, this switch was associated with down-regulation of p21, p53/p73 as well as Erk1/2 and p38 activation. Our findings, therefore, identify a novel mechanistic axis of additive antitumor activity of Viscum album and low dose-Dox. In conclusion, ER + breast cancer patients may benefit from addition of Viscum album to low-dose Dox chemotherapy due to suppression of cancer cell senescence and induction of apoptosis.

Prognostic biomarker value of binary and grayscale breast tumor histopathology images.

AIM: Breast cancer prognosis is in the spotlight owing to its potentially major clinical importance in effective therapeutic management. Following our recent prognostic establishment of the fractal features calculated on binary breast tumor histopathology images, this study aimed to accomplish the first optimization of this methodology by direct comparison of monofractal, multifractal and co-occurrence algorithms in analysis of binary versus grayscale image formats. PATIENTS & METHODS: The study included 93 patients with invasive breast cancer, without systemic treatment and a long median follow-up of 150 months. RESULTS: Grayscale images provided a better prognostic source in comparison to binary, while monofractal, multifractal and co-occurrence image analysis algorithms exerted a comparable performance. CONCLUSION: The critical prognostic importance of the grayscale texture is revealed.

Comparison of Monofractal, Multifractal and gray level Co-occurrence matrix algorithms in analysis of Breast tumor microscopic images for prognosis of distant metastasis risk.

Breast cancer prognosis is a subject undergoing intense study due to its high clinical relevance for effective therapeutic management and a great patient interest in disease progression. Prognostic value of fractal and gray level co-occurrence matrix texture analysis algorithms has been previously established on tumour histology images, but without any direct performance comparison. Therefore, this study was designed to compare the prognostic power of the monofractal, multifractal and co-occurrence algorithms on the same set of images. The investigation was retrospective, with 51 patients selected on account of non-metastatic IBC diagnosis, stage IIIB. Image analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Bootstrap-corrected Cox proportional hazards regression P-values indicated a significant association with metastasis outcome of at least one of the features within each group. AUC values were far better for co-occurrence (0.66-0.77) then for fractal features (0.60-0.64). Correction by the split-sample cross-validation likewise indicated the generalizability only for the co-occurrence features, with their classification accuracies ranging between 67 and 72 %, while accuracies of monofractal and multifractal features were reduced to nearly random 52-55 %. These findings indicate for the first time that the prognostic value of texture analysis of tumour histology is less dependent on the morphological complexity of the image as measured by fractal analysis, but predominantly on the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features.

Sensitization of K562 Leukemia Cells to Doxorubicin by the Viscum album Extract.

Toxicity of conventional chemotherapeutics highlights the requirement for complementary or alternative medicines that would reduce side effects and improve their anticancer effectiveness. European mistletoe (Viscum album) has long been used as a complementary and alternative medicine supporting cancer therapy. The aim of this study was to investigate synergistic antitumor action of V. album extract and doxorubicin during co-treatment of chemoresistant chronic myelogenic leukemia K562 cells. Combined treatment of leukemia cells led to inhibitory synergism at sub-apoptotic doxorubicin concentrations and multifold reduction of cytotoxic effects in healthy control cells. Prolonged co-treatment was associated with reduced G2/M accumulation and increased expression of early and late apoptotic markers. Our data indicate that V. album extract increases antileukemic effectiveness of doxorubicin against resistant K562 cells by preventing G2/M arrest and inducing apoptosis.

Fractal dimension and lacunarity of tumor microscopic images as prognostic indicators of clinical outcome in early breast cancer.

AIM: Research in the field of breast cancer outcome prognosis has been focused on molecular biomarkers, while neglecting the discovery of novel tumor histology structural clues. We thus aimed to improve breast cancer prognosis by fractal analysis of tumor histomorphology. PATIENTS & METHODS: This retrospective study included 92 breast cancer patients without systemic treatment. RESULTS: Fractal dimension and lacunarity of the breast tumor microscopic histology possess prognostic value comparable to the major clinicopathological prognostic parameters. CONCLUSION: Fractal analysis was performed for the first time on routinely produced archived pan-tissue stained primary breast tumor sections, indicating its potential for clinical use as a simple and cost-effective prognostic indicator of distant metastasis risk to complement the molecular approaches for cancer risk prognosis.

Multifractal analysis of tumour microscopic images in the prediction of breast cancer chemotherapy response.

Due to the individual heterogeneity, highly accurate predictors of chemotherapy response in invasive breast cancer are needed for effective chemotherapeutic management. However, predictive molecular determinants for conventional chemotherapy are only emerging and still incorporate a high degree of predictive variability. Based on such pressing need for predictive performance improvement, we explored the value of pre-therapy tumour histology image analysis to predict chemotherapy response. Fractal analysis was applied to hematoxylin/eosin stained archival tissue of diagnostic biopsies derived from 106 patients diagnosed with invasive breast cancer. The tissue was obtained prior to neoadjuvant anthracycline-based chemotherapy and patients were subsequently divided into three groups according to their actual chemotherapy response: partial pathological response (pPR), pathological complete response (pCR) and progressive/stable disease (PD/SD). It was shown that multifractal analysis of breast tumour tissue prior to chemotherapy indeed has the capacity to distinguish between histological images of the different chemotherapy responder groups with accuracies of 91.4% for pPR, 82.9% for pCR and 82.1% for PD/SD. F(α)max was identified as the most important predictive parameter. It represents the maximum of multifractal spectrum f(α), where α is the Hölder's exponent. This is the first study investigating the predictive value of multifractal analysis as a simple and cost-effective tool to predict the chemotherapy response. Improvements in chemotherapy prediction provide clinical benefit by enabling more optimal chemotherapy decisions, thus directly affecting the quality of life and survival.

Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images.

Inflammatory breast cancer (IBC) is a rare and aggressive type of locally advanced breast cancer. The purpose of this study was to determine the value of microscopic tumour histomorphology texture for prognosis of local and systemic recurrence at the time of initial IBC diagnosis. This retrospective study included a group of 52 patients selected on the basis of non-metastatic IBC diagnosis, stage IIIB. Gray-Level-Co-Occurrence-Matrix (GLCM) texture analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Obtained values were categorized by use of both data- and outcome-based methods. All five acquired GLCM texture features significantly associated with metastasis outcome. By accuracies of 69-81% and AUCs of 0.71-0.81, prognostic performance of GLCM parameters exceeded that of standard major IBC clinical prognosticators such as tumour grade and response to induction chemotherapy. Furthermore, a composite score consisting of tumour grade, contrast and correlation as independent features resulted in further enhancement of prognostic performance by accuracy of 89%, discrimination efficiency by AUC of 0.93 and an outstanding hazard ratio of 71.6 (95%CI, 41.7-148.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the model is generalizable. This study indicates for the first time the potential use of primary breast tumour histology texture as a highly accurate, simple and cost-effective prognostic indicator of metastasis risk in IBC. Clinical relevance of the obtained results rests on the role of prognosis in decisions on induction chemotherapy and the resulting impact on quality of life and survival.

Gray-Level Co-Occurrence Matrix Texture Analysis of Breast Tumor Images in Prognosis of Distant Metastasis Risk.

Owing to exceptional heterogeneity in the outcome of invasive breast cancer it is essential to develop highly accurate prognostic tools for effective therapeutic management. Based on this pressing need, we aimed to improve breast cancer prognosis by exploring the prognostic value of tumor histology image analysis. Patient group (n=78) selection was based on invasive breast cancer diagnosis without systemic treatment with a median follow-up of 147 months. Gray-level co-occurrence matrix texture analysis was performed retrospectively on primary tumor tissue section digital images stained either nonspecifically with hematoxylin and eosin or specifically with a pan-cytokeratin antibody cocktail for epithelial malignant cells. Univariate analysis revealed stronger association with metastasis risk by texture analysis when compared with clinicopathological parameters. The combination of individual clinicopathological and texture variables into composite scores resulted in further powerful enhancement of prognostic performance, with an accuracy of up to 90%, discrimination efficiency by the area under the curve [95% confidence interval (CI)] of 0.94 (0.87-0.99) and hazard ratio (95% CI) of 20.1 (7.5-109.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the models are generalizable. Whereas further validation is needed on an external set of patients, this preliminary study indicates the potential use of primary breast tumor histology texture as a highly accurate, simple, and cost-effective prognostic indicator of distant metastasis risk.

Metformin effects on malignant cells and healthy PBMC; the influence of metformin on the phenotype of breast cancer cells.

The aim of research was to determine the effects of maximally therapeutically achievable concentrations of metformin on malignant cells and healthy peripheral blood mononuclear cells (PBMC). Eight patients with T2D or hyperglycemia and nine healthy volunteers were included in the study. For determination of the influence of metformin on the phenotype of breast carcinoma, 1,410 patients with surgically removed tumors were included. From this group 37 breast cancer patients had DM type 2 or hyperglycemia and were pretreated with metformin alone or sometimes in combination with other antidiabetic drugs. Our results proved that metformin at low concentrations induced mild decrease in survival of malignant cells and PBMC stimulated for proliferation, but it didn't affect survival of resting PBMC. The effects of plasma of hyperglycemic patients who were under metformin therapy on autologous PBMC-induced decrease in survival of MDA-MB-361 cells, was noticeable in some patients. Metformin pretreatment for 24 h of HER2+ MDA-MB-361 cells, which were subsequently treated for 48 h with Herceptin, induced additional decline in cell survival. The analysis of influence of metformin on phenotype of breast cancer cells revealed significantly lower number of diabetic cancer patients treated with metformin with overexpressed HER2+ tumors (p < 0.013), while the number of patients with ER+PR+ tumors was not significantly changed (p < 0.832). In conclusion, therapeutically used concentrations of metformin exhibit mild cytotoxic action on malignant and dividing normal cells pointing to its preferred role in malignant and autoimmune diseases. The use of metformin was associated with pronounced decrease in HER2 overexpressing tumors.

Trefoil factor 1 in early breast carcinoma: a potential indicator of clinical outcome during the first 3 years of follow-up.

BACKGROUND: A role of an estrogen-regulated, autocrine motogenic factor was assumed to be a major biological role of trefoil factor 1 (TFF1) in breast cancer. TFF1 is regarded as a predictive factor for positive response to endocrine therapy in breast cancer patients. The aim of our study was to examine TFF1 level distribution in breast carcinomas in order to distinguish estrogen-independent from estrogen-dependent TFF1 expression and to evaluate clinical usefulness of TFF1 status in early breast cancer during the first 3 years of follow-up. METHODS: The study included 226 patients with primary operable invasive early breast carcinomas for whom an equal, a 3-year follow-up was conducted. TFF1 levels as well as estrogen receptor (ER) and progesterone receptor (PR) levels were measured in cytosolic extracts of tumor samples by immunoradiometric assay or by use of classical biochemical method, respectively. Non-parametric statistical tests were applied for data analyses. RESULTS: Statistical analysis revealed that TFF1 levels were significantly higher in premenopausal patients (p=0.02), or in tumors with: lower histological grade (p<0.001), positive ER or PR status (p<0.001, in both cases). On the basis of TFF1 level distribution between ER-negative and ER-positive postmenopausal patients with tumors of different histological grade, 14 ng/mg was set as the cut-off value to distinguish estrogen-independent from estrogen-dependent TFF1 expression in breast cancer. Depending on menopausal and PR status, positive TFF1 status identified patients at opposite risk for relapse among ER-positive patients with grade II tumors. Among ER- and PR-positive premenopausal patients with grade II tumors, TFF1 status alone identified patients at opposite risk for relapse. CONCLUSIONS: Determination of TFF1 status might identify patients at different risk for relapse and help in making decision on administering adjuvant therapy for early breast cancer patients during the first 3 years of follow-up.

Cathepsin D as an indicator of clinical outcome in early breast carcinoma during the first 3 years of follow-up.

AIM: The aim of this study was to evaluate clinical usefulness of cathepsin D status in early breast cancer during the first 3 years of follow-up. PATIENTS & METHODS: The study included 226 patients with histologically verified, primary operable invasive early breast carcinomas. Concentrations of estrogen receptor (ER) and progesterone receptor (PR) in breast tumor cytosols were measured by use of the classical biochemical method. The concentration of three cathepsin D forms (52-, 48- and 34-kDa proteins) was determined by a radioimmunoassay RESULTS: On the basis of differences in cathepsin D levels either within an ER(-)/PR(-) phenotype or between this and either ER(+)/PR(+) or ER(+)/PR(-) phenotypes, a concentration of 39 pmol/mg was determined as the cutoff value for distinguishing estrogen-regulated cathepsin D expression. Estrogen-regulated cathepsin D expression was recognized as a high-risk biomarker for low-risk (histological grade I) breast cancer patients and as a low-risk biomarker for high-risk patients (pN(+) pT2,3). CONCLUSION: Determination of cathepsin D status in breast cancer might identify patients at different risk for relapse and might facilitate the selection of more or less aggressive adjuvant therapy for early breast cancer patients during the first 3 years of follow-up.

Treatment response to preoperative anthracycline-based chemotherapy in locally advanced breast cancer: the relevance of proliferation and apoptosis rates.

Objectives were to evaluate the relevance of proliferating fraction (Ki-67) along with apoptotic index (AI) which denoted growth index (Ki-67/AI ratio, GI) to predict pathological response to preoperative chemotherapy, and the pattern of their modifications following chemotherapy in women with locally advanced breast cancer. Archival material of diagnostic biopsies and surgical specimens from 106 patients were examined. Response rate to chemotherapy in this group was 95 %, eight (8 %) patients achieved a pathological complete remission (pCR) and five (5 %) had a progressive/stable disease (PD/SD). The expression of Ki-67 and AI were assessed using immunohistochemistry and in situ DNA nick labeling assay respectively. Higher baseline level of Ki-67 and GI were associated with an improved pathological response (p = 0.0001 and p = 0.008), but the degree of correlation with GI was no greater than that with Ki-67 alone. Ki-67 below 1 % highly indicated a lack of tumor response. High AI which characterized the opposite chemo-sensitive tumors, pCR vs. PD/SD (p = 0.72) implied that treatment response was not influenced by the "presence" or "absence" of apoptosis. A significant decrease in Ki-67 (p < 0.001), AI (p = 0.035) and GI (p = 0.008) was found following chemotherapy, but percentage change in biomarker values revealed an increase in a number of cases. Higher initial Ki-67 and AI was associated with profound reduction of GI and raising value of GI after treatment, respectively. Such a variance of a given parameter elicited by chemotherapy may have various impact on disease outcome.

Different associations of estrogen receptor ß isoforms, ERß1 and ERß2, expression levels with tumor size and survival in early- and late-onset breast cancer.

BACKGROUND: In breast cancer, little is known about the consequences of co-expression of ERα with the second estrogen receptor, ERß, and its isoforms in light of their joint prognostic value. Previously reported correlations have been based mostly on independent ERα and ERß expression levels in breast tumors. PURPOSE: To address whether the expression ratio of ERα and ERß and its isoforms may be a more important parameter than their absolute levels, we analyzed relative mRNA expression ratios of ERß1 to ERß2 and ERα in 74 clinical samples of invasive breast cancer including 39 early-onset and 35 late-onset breast cancers. Expression levels were correlated with clinical and histopathological parameters and disease-free interval. RESULTS: A specific correlation of ERß1 expression levels with tumor size was detected in early-onset breast cancer patients and of ERß2 levels with tumor size in late-onset patients. Expression of both ERß isoforms inversely correlated with expression of the two estrogen regulated genes, progesterone receptor and pS2 in both groups. Higher levels of ERß2 than ERß1 isoform were associated with a better outcome in late-onset patients. CONCLUSIONS: Our results suggest that different isoforms of ERß may be involved in suppression of tumor growth in young and elder patients and may have different prognostic values.

Estrogen-regulated cut-off values of pS2 and cathepsin D expression in breast carcinomas.

The purpose of the study was to asses the expression of estrogen-induced pS2 and cathepsin D (CD) that might facilitate biological subgrouping of patients with breast carcinomas (BC) and its potential applicability in clinical oncology. The study included 226 patients with histologically verified BC. Clinico-pathological findings were classified according to age, menopausal status, tumor size, histologic grade, and regional lymph node status. Estrogen and progesterone receptors (ER and PR), as well as CD and pS2 protein concentrations were assayed on the same cytosolic extract in accordance with the recommendation of EORTC. Statistically significant direct correlations were observed between CD expression and axillary node status and between pS2 expression and histologic grade, while the expression of both proteins was related to both ER and PR status. Baseline levels of CD expression were found in patients with SR-negative status and node-negative or tumors less than 2cm. Unfavorable carcinoma subgroups, in relation to pS2 expression, were defined as pre- and postmenopausal carcinomas with histologic grade III. The highest CD level observed in SR-negative unfavorable subgroups (38.7 pmol/mg) and the highest pS2 level observed in ER(-) unfavorable subgroups (14.7 ng/mg) were considered as the cut-off values. These values defined estrogen-regulated expression of CD and pS2 protein that might enable the identification of patients at high risk of disease progression, for whom more aggressive adjuvant approach would be warranted, as well as the identification of patients whose prognosis is so good that adjuvant therapy would not be cost-beneficial.

Expression of estrogen receptor beta wt isoform (ERbeta1) and ERbetaDelta5 splice variant mRNAs in sporadic breast cancer.

PURPOSE: In addition to Estrogen Receptor alpha (ERalpha) and Progesterone Receptor (PR), the Second Estrogen Receptor (ERbeta) appears to play an important role not only in estrogen signaling, but also in the pathogenesis of cancer in estrogen dependent tissues. The existence of various isoforms and splice variants of both ERs additionally complicates elucidation of their physiological role and involvement in the process of carcinogenesis. METHODS: In this study, the expression of ERbeta1 mRNA (wild type of beta receptor) and splice variant ERbetaDelta5 mRNA (which codes for truncated protein) was measured by the quantitative RT-PCR (q RT-PCR) in the 60 samples of Breast Cancer (BC) and correlated with ERalpha and PR protein levels and with clinical and histopathological parameters. RESULTS: We found the inverse correlation of ERbetaDelta5 mRNA expression with the levels of PR and ERalpha proteins in the group of postmenopausal patients; we also report the lower expression of ERbeta1 and ERbetaDelta5 mRNA in the larger tumors (>20 mm, T2, and T3) than in smaller ones (< or =20 mm, T1). The decrease of ERbetaDelta5 mRNA expression in larger tumors is found to arise from ER-positive breast carcinomas. In addition, the portion of tumors with concomitant high expression of both transcripts matches up the known percentage of tumors resistant to endocrine therapy in patients with different ER/PR status. CONCLUSIONS: As far as we know, this is the first study in which ERbetaDelta5 mRNA splice variant was quantified by real-time RT-PCR in the clinical samples of breast cancer tissue. Until now, the focus of clinical reports was the level of ERbeta1, ERbeta2, and ERbeta5 isoforms. The higher expression of ERbetaDelta5 mRNA is associated with the indicators of low biological aggressiveness of tumor (low tumor size within ER-positive status in our study) suggesting that the uncontrolled local tumor growth may occur as the expression of ERbetaDelta5 mRNA decreases in estrogen-dependent breast cancer.