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Intertumoral Heterogeneity of Primary Breast Tumors and Synchronous Axillary Lymph Node Metastases Reflected in IHC-Assessed Expression of Routine and Nonstandard Biomarkers.

ABSTRACT: Breast cancer (BC) remains a significant healthcare challenge. Routinely, the treatment strategy is determined by immunohistochemistry (IHC)-based assessment of the key proteins such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67. However, it is estimated that over 75% of deaths result from metastatic tumors, indicating a need to develop more accurate protocols for intertumoral heterogeneity assessment and their consequences on prognosis. Therefore, the aim of this preliminary study was the identification of the expression profiles of routinely used biomarkers (ER, PR, HER2, Ki-67) and additional relevant proteins [Bcl-2, cyclin D1, E-cadherin, Snail+Slug, gross cystic disease fluid protein 15 (GCDFP-15), programmed death receptor 1 (PD-L1), and phosphatase of regenerating liver 3 (PRL-3)] in breast primary tumors (PTs) and paired synchronous axillary lymph node (ALN) metastases. A total of 67 tissue samples met the inclusion criteria for the study. The expression status of biomarkers was assessed in PTs and ALN metastases using tissue microarrays followed by IHC. In 11 cases, the shift of intrinsic molecular BC subtype was noticed between PTs and paired ALN metastases. Moreover, a significant disproportion in E-cadherin presence (p = 0.0002) was noted in both foci, and the expression status of all proteins except for HER2 demonstrated considerable variance (k = 1, p < 0.0001). Importantly, in around 30% of cases, the ALN metastases demonstrated discordance, i.e., loss/gain of expression, compared to the PTs. Intertumoral synchronous heterogeneity in both foci (primary tumor and node metastasis) is an essential phenomenon affecting the clinical subtype and characteristics of BC. Furthermore, a greater understanding of this event could potentially improve therapeutic efficacy.

SUBMITTER: Kuncman W

PROVIDER: S-EPMC8595326 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Whether the expression status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2) receptor and Ki-67 show concordance between the primary tumors and the synchronous axillary lymph node (ALN) metastases has been discussed in numerous studies. However, to date, the results of these studies remain controversial. Therefore, the present study aimed to investigate whether the expression of ER, PR, HER-2 and Ki-67 was in concordance between the primary tumors and synchronous ALN metastases in patients with operable breast cancer (BC). A total of 60 tissue samples were collected from patients with primary operable BC diagnosed with primary tumors and synchronous ALN metastases. The expression levels of the four biomarkers, ER, PR, HER-2 and Ki-67, were assessed in primary lesions and synchronous ALN metastases samples using immunohistochemistry. The cut-off values were set to 10% for ER and PR, while the labeling index of Ki-67 was set to 14%. The immunostaining intensity of ER and PR was scored as negative (?), 1+, 2+ and 3+. The criteria for HER-2 testing in BC were implemented according to the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP) guidelines. The concordance rates for ER, PR and HER-2 were 96.7 (58/60), 96.7 (58/60) and 90% (54/60), respectively. In addition, the kappa values of consistency in the primary lesions and the synchronous ALN metastases were 0.773 for ER, 0.654 for PR and 0.785 for HER-2. Furthermore, the P-values of ER, PR and Ki-67 numerical variables between the two groups were 0.393, 0.400 and 0.331, respectively, as demonstrated using a non-parametric Wilcoxon signed rank test. The findings of the present study demonstrated a high degree of concordance between the expression of ER, PR, HER-2 and Ki-67 in the primary tumors and that in the synchronous ALN metastases, suggesting that the BC primary tumor biomarkers may be used for the prognosis of synchronous ALN metastases in patients with operable BC.

Project description:PurposeTo develop a clinical-radiomics model based on radiomics features extracted from MRI and clinicopathologic factors for predicting the axillary pathologic complete response (apCR) in breast cancer (BC) patients with axillary lymph node (ALN) metastases.Materials and methodsThe MR images and clinicopathologic data of 248 eligible invasive BC patients at the Peking University First Hospital from January 2013 to December 2020 were included in this study. All patients received neoadjuvant chemotherapy (NAC), and the presence of ALN metastases was confirmed through cytology pre-NAC. The data from January 2013 to December 2018 were randomly divided into the training and validation sets in a ratio of 7:3, and the data from January 2019 to December 2020 served as the independent testing set. The following three types of prediction models were investigated in this study. 1) A clinical model: the model was built by independently predicting clinicopathologic factors through logistic regression. 2) Radiomics models: we used an automatic segmentation model based on deep learning to segment the axillary areas, visible ALNs, and breast tumors on post-NAC dynamic contrast-enhanced MRI. Radiomics features were then extracted from the region of interest (ROI). Radiomics models were built based on different ROIs or their combination. 3) A clinical-radiomics model: it was built by integrating radiomics signature and independent predictive clinical factors by logistic regression. All models were assessed using a receiver operating characteristic curve analysis and by calculating the area under the curve (AUC).ResultsThe clinical model yielded AUC values of 0.759, 0.787, and 0.771 in the training, validation, and testing sets, respectively. The radiomics model based on the combination of MRI features of breast tumors and visible ALNs yielded the best AUC values of 0.894, 0.811, and 0.806 in the training, validation, and testing sets, respectively. The clinical-radiomics model yielded AUC values of 0.924, 0.851, and 0.878 in the training, validation, and testing sets, respectively, for predicting apCR.ConclusionWe developed a clinical-radiomics model by integrating radiomics signature and clinical factors to predict apCR in BC patients with ALN metastases post-NAC. It may help the clinicians to screen out apCR patients to avoid lymph node dissection.

Project description:BACKGROUND:Breast cancer is a very heterogeneous disease and some patients are cured by the surgical removal of the primary tumour whilst other patients suffer from metastasis and spreading of the disease, despite adjuvant therapy. A number of prognostic and treatment predictive factors have been identified such as tumour size, oestrogen (ER) and progesterone (PgR) receptor status, human epidermal growth factor receptor type 2 (HER2) status, histological grade, Ki67 and age. Lymph node involvement is also assessed during surgery to determine if the tumour has spread which requires dissection of the axilla and adjuvant treatment. The prognostic and treatment predictive factors assessing the nature of the tumour are all routinely based on the status of the primary tumour. RESULTS:We have analysed a unique tumour set of fourteen primary breast cancer tumours with matched synchronous axillary lymph node metastases and a set of nine primary tumours with, later developed, matched distant metastases from different sites in the body. We used a pairwise tumour analysis (from the same individual) since the difference between the same tumour-type in different patients was greater. Glycopeptide capture was used in this study to selectively isolate and quantify N-linked glycopeptides from tumours mixtures and the captured glycopeptides were subjected to label-free quantitative tandem mass spectrometry analysis. Differentially expressed proteins between primary tumours and matched lymph node metastasis and distant metastasis were identified. Two of the top hits, ATPIF1 and tubulin ?-chain were validated by immunohistochemistry to be differentially regulated. CONCLUSIONS:We show that the expression of a large number of glycosylated proteins change between primary tumours and matched lymph node metastases and distant metastases, confirming that cancer cells undergo a molecular transformation during the spread to a secondary site. The proteins are part of important pathways such as cell adhesion, migration pathways and immune response giving insight into molecular changes needed for the tumour to spread. The large difference between primary tumours and lymph node and distant metastases also suggest that treatment should be based on the phenotype of the lymph node and distant metastases.

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Intertumoral Heterogeneity of Primary Breast Tumors and Synchronous Axillary Lymph Node Metastases Reflected in IHC-Assessed Expression of Routine and Nonstandard Biomarkers.

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