Comparison of Clinico-Pathological Presentations of Triple-Negative versus Triple-Positive and HER2 Iraqi Breast Cancer Patients

A Prognostic Model for Breast Cancer Based on Cancer Incidence-Related DNA Methylation Pattern

Breast cancer (BC) is the most diagnosed cancer and the leading cause of cancer-related deaths in women. The purpose of this study was to develop a prognostic model based on BC-related DNA methylation pattern. A total of 361 BC incidence-related probes (BCIPs) were differentially methylated in blood samples from women at high risk of BC and BC tissues. Twenty-nine of the 361 BCIPs that significantly correlated with BC outcomes were selected to establish the BCIP score. BCIP scores based on BC-related DNA methylation pattern were developed to evaluate the mortality risk of BC. The correlation between overall survival and BCIP scores was assessed using Kaplan-Meier, univariate, and multivariate analyses. In BC, the BCIP score was significantly correlated with malignant BC characteristics and poor outcomes. Furthermore, we assessed the BCIP score-related gene expression profile and observed that genes with expressions associated with the BCIP score were involved in the process of cancer immunity according to GO and KEGG analyses. Using the ESTIMATE and CIBERSORT algorithms, we discovered that BCIP scores were negatively correlated with both T cell infiltration and immune checkpoint inhibitor response markers in BC tissues. Finally, a nomogram comprising the BCIP score and BC prognostic factors was used to establish a prognostic model for patients with BC, while C-index and calibration curves were used to evaluate the effectiveness of the nomogram. A nomogram comprising the BCIP score, tumor size, lymph node status, and molecular subtype was developed to quantify the survival probability of patients with BC. Collectively, our study developed the BCIP score, which correlated with poor outcomes in BC, to portray the variation in DNA methylation pattern related to BC incidence.

Correlation of Clinicopathological Features of Breast Cancer with Molecular Subtypes Taking Ki-67 into Consideration: Single Institution Experience Over 5 Years

BACKGROUND

Molecular classification of breast cancer is commonly done to determine response to therapy and cancer prognosis. Aim of the study was to compare prevalence of molecular subtypes of breast cancer in our institute using immunohistochemistry, including Ki-67, and correlate it with clinical and pathological prognostic factors.

RESULTS

300 cases of invasive breast cancer were included in the study. Average age at time of diagnosis was 44 years and average size of tumor was 3.4cms. Invasive ductal carcinoma was the most common histological type (75.3%). The most common molecular subtype was triple negative (34.3%) followed by Luminal B (33.4%), luminal A (17%) and Her-2 positive (15.3%). Large size and poorly differentiated tumors were predominantly triple negative tumors while lymph node metastasis was most commonly seen in Her-2 positive tumors.

CONCLUSION

Molecular subtype of breast carcinoma should routinely be done for all cases of carcinoma breast as it allows to identify aggressive tumors and target therapy accordingly.