Survival of breast cancer patients according to changes in expression of selected markers between primary tumor and lymph node metastases

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.

Breast cancer prognosis and P-cadherin expression: systematic review and study-level meta-analysis

OBJECTIVE

P-cadherin can act both as a tumour suppressor and an oncogene. The clinical prognostic value of P-cadherin overexpression in breast cancer (BC) remains unclear. We conducted a study-level meta-analysis to determine whether P-cadherin expression can help predict prognosis in BC.

METHODS

A systematic literature search was performed to review eligible studies and clarify the relationship between P-cadherin overexpression and overall survival (OS), disease-free survival (DFS), pathological features, molecular subtypes and molecular phenotypes in BC.

RESULTS

Thirty-one studies including 12 332 patients were included. P-cadherin overexpression was correlated with significantly worse OS (HR=1.77, p<0.00001) and DFS (HR=1.96, p<0.00001) than P-cadherin-negative. P-cadherin overexpression could lead to high histological grade (OR=3.33, p<0.00001) and lymph node metastasis (OR=1.62, p<0.00001). Moreover, P-cadherin overexpression was associated with low odds of the luminal A subtype and high odds of the human epidermal growth factor receptor-2 (HER2)-positive and triple-negative subtypes. P-cadherin expression led to low expression of oestrogen and progesterone receptor (OR=0.37 and OR=0.36, respectively, both p<0.00001) and high expression of HER2 (OR=2.31, p<0.00001), Ki-67 (OR=2.79, p<0.00001), epidermal growth factor receptor (OR=5.85, p<0.00001) and cytokeratin 5/6 (OR=6.79, p<0.00001).

CONCLUSIONS

P-cadherin was found to be associated with invasiveness and metastasis. P-cadherin expression can probably be a useful biomarker for predicting poor survival and may act as an independent prognostic predictor.

NRSN2 promotes breast cancer metastasis by activating PI3K/AKT/mTOR and NF-κB signaling pathways

Breast cancer is a leading cause of cancer-associated mortality globally amongst gynecologic tumors due to aggressive metastasis. A previous study reported that neurensin-2 (NRSN2) was implicated in human cancer cells, and that NRSN2 gene and protein expression levels were significantly upregulated in human breast cancer tissues compared with adjacent non-tumor tissues. The purpose of the present study was to analyze the role of NRSN2 in the metastasis of breast cancer cells and explore its potential mechanism. Reverse transcription-quantitative PCR, MTT, western blotting and immunohistochemistry was used to analyze the role of NRSN2 both in vitro and in vivo. The present study demonstrated that NRSN2 knockdown inhibited the proliferation, migration and invasion of breast cancer cells in vitro. NRSN2 upregulation promoted breast cancer cell proliferation and tissue growth in vitro and in vivo. In addition, the results demonstrated that the regulatory effects of NRSN2 on breast cancer cells were associated with PI3K/AKT/mTOR and NF-κB signaling pathway dysregulation. Furthermore, NRSN2 overexpression in mice significantly promoted breast cancer cell proliferation. In conclusion, the results from the present study indicated that NRSN2 may be considered as a novel oncogenic protein and may represent a potential therapeutic target for breast cancer.

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.

Prognostic value of ALDH1 and Nestin in advanced cancer: a systematic meta-analysis with trial sequential analysis

Background

Novel prognostic markers and therapeutic targets for advanced cancer are urgently needed. This report with trial sequential analysis (TSA) was first conducted to provide robust estimates of the correlation between aldehyde dehydrogenase 1 (ALDH1) and Nestin and clinical outcomes of advanced cancer patients.

Methods

Hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized for overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), relapse/recurrence-free survival (RFS), and metastasis-free survival (MFS) from multivariable analysis. TSA was performed to control for random errors.

Results

A total of 20 studies with 2050 patients (ALDH1: 15 studies with 1557 patients and Nestin: 5 studies with 493 patients) were identified. ALDH1 (HR = 2.28, p < 0.001) and Nestin (HR = 2.39, p < 0.001) were associated with a worse OS, as confirmed by TSA. Nestin positivity was linked to a poor PFS (HR = 2.08, p < 0.001), but ALDH1 was not linked to DFS, RFS, MFS, or PFS, and TSA showed that more studies were needed. Subgroup analysis by tumor type indicated that ALDH1 positivity may be associated with shorter OS in breast, head and neck cancers, but there was no association with colorectal cancer. Subgroup analysis by study source showed that ALDH1 positivity was correlated with a worse OS for Japanese (HR = 1.94, p = 0.002) and European patients (HR = 4.15, p < 0.001), but there was no association for Chinese patients. Subgroup analysis by survival rate showed that ALDH1 positivity correlated with poor OS at ⩾ 5 years (HR = 2.33, p < 0.001) or 10 years (HR = 1.76, p = 0.038).

Conclusions

ALDH1 may be more valuable as an effective therapeutic target than Nestin for improving the long-term survival rate of advanced cancer. Additional prospective clinical trials are needed across different cancer types.

Breast cancer primary tumor ER expression pattern predicts its expression concordance in matched synchronous lymph node metastases

Background

Estrogen receptor (ER) expression is important for treatment selection and prognostication of breast cancer patients. Although the metastases are the main targets of endocrine therapy, ER status is often based on the primary tumor. However, ER expression in breast cancer primary lesion may not match with its synchronous metastatic lesions in some cases. In this study, we analyzed ER expression concordance between breast cancer primary tumor and metastatic lesions.

Methods

Paraffin blocks of 100 primary breast invasive ductal carcinoma cases with axillary lymph node metastases were collected. Five tissue cores were punched out from individual primary breast cancer, and one tissue core from each lymph node metastases to assemble tissue microarrays for ER staining. Samples were then scored as 0, 1+, 2+, and 3+ according to the number and intensity of ER stained tumor cells.

Results

For cases with ER 3+ (strong expression) in all cores of primary lesions (n = 38), ER expression in metastatic lymph node was found in 94.7% of the patients. 91.0% of the metastatic lymph nodes were ER positive, and 84.3% of them to be 3+. Among the 46 cases of ER negative expression in all cores of primary lesions, 39 of them had all the metastatic nodes being ER negative, and ER negative nodes were seen in 95.7% of the metastases. As for 16 cases of ER inconsistent expression in primary lesions, 4 cases showed negative ER expression in all metastatic nodes, 2 cases displayed diffuse consistent ER 3+ expression, and 10 cases displayed variant ER expression.

Conclusions

The findings suggest that ER expression concordance between breast cancer primary lesion and its matched metastatic lesions could be estimated by primary tumor ER expression pattern.

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.

P-cadherin: a useful biomarker for axillary-based breast cancer decisions in the clinical practice

Axillary lymph node metastases represent the most powerful breast cancer prognostic factor, dictating disease staging and clinical therapeutic decisions. Nonetheless, breast cancer patients with positive lymph nodes still exhibit a heterogeneous behavior regarding disease progression. Stem-like subpopulations of cancer cells show high migratory and metastatic capacity, thus we hypothesize that breast cancer stem cell markers evaluation in metastasized lymph nodes could provide a more accurate prediction of patient's prognosis. Therefore, the expression profile of P-cadherin, CD44, and CD49f, which have been already associated to stem cell properties in breast cancer, has been evaluated by immunohistochemistry in a series of 135 primary tumors and matched axillary lymph node metastases from 135 breast cancer patients. Taking in consideration the expression of the stem cell markers only in axillary nodes, P-cadherin was the only biomarker significantly associated with poor disease-free and overall patient's survival. Moreover, although a concordant expression between primary tumors and matched lymph nodes has been found in the majority of the cases, a small but significant percentage displayed divergent expression (18.2-26.2%). Remarkably, although CD44 and CD49f changes between primary tumors and lymph node metastasis did not impact survival, the cases that were positive for P-cadherin in lymph node metastases being negative in the primary tumor, presented the worst disease-free and overall survival of the whole series. Accordingly, negative cases for this marker in the lymph nodes with positive expression in the matched breast carcinoma demonstrated a better prognosis, which overlapped with tumors that were negative in both sites. P-cadherin and CD49f gain of expression was mainly found in triple-negative carcinomas. Our results indicate for the first time that the evaluation of P-cadherin expression in lymph node metastases is an important predictor of disease outcome, being a putative valuable marker for axillary-based breast cancer decisions in the clinical practice.

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.

Molecular Portrait of the Normal Human Breast Tissue and Its Influence on Breast Carcinogenesis

Normal human breast tissue consists of epithelial and nonepithelial cells with different molecular profiles and differentiation grades. This molecular heterogeneity is known to yield abnormal clones that may contribute to the development of breast carcinomas. Stem cells that are found in developing and mature breast tissue are either positive or negative for cytokeratin 19 depending on their subtype. These cells are able to generate carcinogenesis along with mature cells. However, scientific data remains controversial regarding the monoclonal or polyclonal origin of breast carcinomas. The majority of breast carcinomas originate from epithelial cells that normally express BRCA1. The consecutive loss of the BRCA1 gene leads to various abnormalities in epithelial cells. Normal breast epithelial cells also express hypoxia inducible factor (HIF) 1α and HIF-2α that are associated with a high metastatic rate and a poor prognosis for malignant lesions. The nuclear expression of estrogen receptor (ER) and progesterone receptor (PR) in normal human breast tissue is maintained in malignant tissue as well. Several controversies regarding the ability of ER and PR status to predict breast cancer outcome remain. Both ER and PR act as modulators of cell activity in normal human breast tissue. Ki-67 positivity is strongly correlated with tumor grade although its specific role in applied therapy requires further studies. Human epidermal growth factor receptor 2 (HER2) oncoprotein is less expressed in normal human breast specimens but is highly expressed in certain malignant lesions of the breast. Unlike HER2, epidermal growth factor receptor expression is similar in both normal and malignant tissues. Molecular heterogeneity is not only found in breast carcinomas but also in normal breast tissue. Therefore, the molecular mapping of normal human breast tissue might represent a key research area to fully elucidate the mechanisms of breast carcinogenesis.