scholarly journals Karakteristik Histopatologik dan Imunofenotipik Kanker Payudara di Rumah Sakit Cipto Mangunkusumo Jakarta, Indonesia

Medicinus ◽  
2018 ◽  
Vol 6 (3) ◽  
Author(s):  
Primariadewi Rustamadji ◽  
Stephanie Marisca
Keyword(s):  
Breast Cancer ◽  
Molecular Subtype ◽  
Breast Cancer Subtype ◽  
Breast Cancer Case ◽  
Tumor Stage ◽  
Cancer Case ◽  
Genetic Profile ◽  
Luminal A ◽  
Cross Sectional ◽  
Luminal B

<p>Introduction: Breast cancer can be classified into luminal A, luminal B, Her2+, dan basal-like molecular subtype according to genetic profile and immunophenotype. The aim of this study is to assess histopathologic and immunophenotype characteristics of breast cancer in Cipto Mangunkusumo Hospital Jakarta, Indonesia.<br />Material and methods: This study is a cross-sectional retrospective study. The sample was 2632 breast cancer case in Department of Anatomical Pathology Cipto Mangunkusumo Hospital from the year 2011 until 2015. ER, PR, Her2, Top2 α, and Ki67 immunohistochemical stain was then grouped into luminal A (ER+/PR+/Her2-/Ki67&lt;20%) subtype, luminal B (ER+/PR+/Her2-/Ki67≥20%) subtype, Her2+ (ER-/PR-/Her2+) subtype, and basal-like (ER-/PR-/Her2-) subtype. Kendall’s Tau analysis was done to assess association between sample characteristics and molecular subtype, association between top2α positive and molecular subtype.<br />Result: The most prevalent to the less prevalent breast cancer molecular subtype was luminal B (43,9%), Her2+ (14,6%), luminal A (14,0%), and basal-like (11,3%). There was a significant association between the tumor stage and breast cancer subtype (p=0,0001). There is also a significant association between Top2α expression and molecular subtype (p=0,0001).<br />Conclusion: The most prevalent breast cancer molecular subtype was luminal B. There was an association between breast cancer molecular subtype and a higher degree and Top2α expression.</p>

Towards cancer mega-cohorts: A novel homogenization algorithm applied to diverse breast cancer RNA-Seq datasets.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13507-e13507
Author(s):  
Talal Ahmed ◽  
Mark Carty ◽  
Stephane Wenric ◽  
Raphael Pelossof
Keyword(s):  
Breast Cancer ◽  
Molecular Subtype ◽  
Breast Cancer Subtype ◽  
Model Performance ◽  
Test Results ◽  
Rna Seq ◽  
Luminal A ◽  
Test Set ◽  
Luminal B ◽  
Cancer Subtype

e13507 Background: Recent advances in transcriptomics have resulted in the emergence of several publicly available breast cancer RNA-Seq datasets, such as TCGA, SCAN-B, and METABRIC. However, molecular predictors cannot be applied across datasets without the correction of batch differences. In this study, we demonstrate a homogenization algorithm that allows the transfer of molecular subtype predictors from one RNA-Seq cohort to another. The algorithm only uses cohort-level RNA-Seq summary statistics, and therefore, does not require joint normalization of both datasets nor the transfer of patient information. Using this approach, we transferred a breast cancer subtype (Luminal A, Luminal B, HER2+, Basal) predictor trained on SCAN-B data to accurately predict subtypes from TCGA. Methods: First, we randomly split the TCGA cohort (n = 481 Luminal A, n = 189 Luminal B, n = 73 Her2+, n = 168 Basal) into two sets: TCGA-train and held-out TCGA-test (n = 455 and n = 456, respectively). Second, the SCAN-B cohort (n = 837) was homogenized with the TCGA-train set. Third, a molecular subtype predictor, based on a logistic regression model, was trained on homogenized SCAN-B RNA-Seq samples and used to predict the subtypes of TCGA-test RNA-Seq samples. For baseline comparison, a similar predictor trained on the non-homogenized SCAN-B cohort was tested on the TCGA-test set. The experimental framework was iterated 250 times. Reported P-values reflect a paired one-sided t-test. Results: To quantify model performance, we measured the average F1 score for each tumor subtype prediction from the held-out TCGA test set with and without cohort homogenization. The average F1 scores with vs. without homogenization were: Luminal A, 0.88 vs. 0.85 ( P< 1e-69); Luminal B, 0.74 vs. 0.51 ( P< 1e-183); Her2+, 0.73 vs. 0.53 ( P< 1e-99); Basal, 0.98 vs. 0.97 ( P< 1e-53). Overall, homogenization significantly outperformed no homogenization. Conclusions: We developed a novel homogenization algorithm that accurately transfers subtype predictors across diverse, independent breast cancer cohorts.

scholarly journals Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Alexey Surov ◽  
Yun-Woo Chang ◽  
Lihua Li ◽  
Laura Martincich ◽  
Savannah C. Partridge ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Diffusion Coefficient ◽  
Triple Negative ◽  
Molecular Subtype ◽  
Luminal A ◽  
Ki 67 ◽  
Luminal B ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Her 2

Abstract Background Radiological imaging plays a central role in the diagnosis of breast cancer (BC). Some studies suggest MRI techniques like diffusion weighted imaging (DWI) may provide further prognostic value by discriminating between tumors with different biologic characteristics including receptor status and molecular subtype. However, there is much contradictory reported data regarding such associations in the literature. The purpose of the present study was to provide evident data regarding relationships between quantitative apparent diffusion coefficient (ADC) values on DWI and pathologic prognostic factors in BC. Methods Data from 5 centers (661 female patients, mean age, 51.4 ± 10.5 years) were acquired. Invasive ductal carcinoma (IDC) was diagnosed in 625 patients (94.6%) and invasive lobular carcinoma in 36 cases (5.4%). Luminal A carcinomas were diagnosed in 177 patients (28.0%), luminal B carcinomas in 279 patients (44.1%), HER 2+ carcinomas in 66 cases (10.4%), and triple negative carcinomas in 111 patients (17.5%). The identified lesions were staged as T1 in 51.3%, T2 in 43.0%, T3 in 4.2%, and as T4 in 1.5% of the cases. N0 was found in 61.3%, N1 in 33.1%, N2 in 2.9%, and N3 in 2.7%. ADC values between different groups were compared using the Mann–Whitney U test and by the Kruskal-Wallis H test. The association between ADC and Ki 67 values was calculated by Spearman’s rank correlation coefficient. Results ADC values of different tumor subtypes overlapped significantly. Luminal B carcinomas had statistically significant lower ADC values compared with luminal A (p = 0.003) and HER 2+ (p = 0.007) lesions. No significant differences of ADC values were observed between luminal A, HER 2+ and triple negative tumors. There were no statistically significant differences of ADC values between different T or N stages of the tumors. Weak statistically significant correlation between ADC and Ki 67 was observed in luminal B carcinoma (r = − 0.130, p = 0.03). In luminal A, HER 2+ and triple negative tumors there were no significant correlations between ADC and Ki 67. Conclusion ADC was not able to discriminate molecular subtypes of BC, and cannot be used as a surrogate marker for disease stage or proliferation activity.

Adjuvant Chemotherapy: Which Patient? What Regimen?

2013 ◽  
pp. 3-8 ◽  
Author(s):  
Natalie Turner ◽  
Laura Biganzoli ◽  
Luca Malorni ◽  
Ilenia Migliaccio ◽  
Erica Moretti ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Adjuvant Chemotherapy ◽  
Breast Cancer Subtype ◽  
Tumor Biology ◽  
Patient Characteristics ◽  
Tumor Stage ◽  
Luminal A ◽  
Genomic Analyses ◽  
Cancer Subtype ◽  
Clinicopathologic Factors

In the past, treatment decisions regarding adjuvant chemotherapy in early breast cancer (EBC) were made solely based on clinicopathologic factors. However, with increased awareness of the importance of underlying tumor biology, we are now able to use genomic analyses to determine molecular breast cancer subtype and thus identify patients with tumors that are chemotherapy resistant and unlikely to benefit from the addition of chemotherapy. Although genomics has allowed some patients to avoid chemotherapy—specifically those with luminal A–like breast cancer—these assays do not indicate which regimen is most appropriate. For this, consideration must be given to the combination of underlying tumor biology, tumor stage, and patient characteristics, such as age and tolerability of side effects.

Epigenetic aspects of triple-negative in patients with breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1041-1041
Author(s):  
Joaquina Martínez-Galan ◽  
Sandra Rios ◽  
Juan Ramon Delgado ◽  
Blanca Torres-Torres ◽  
Jesus Lopez-Peñalver ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Dna Methylation ◽  
Triple Negative ◽  
Breast Cancer Subtype ◽  
Regulation Of Gene Expression ◽  
Breast Cancer Subtypes ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Luminal B

1041 Background: Identification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes. Methods: By using Real Time QMSPCR SYBR green we analyzed DNA methylation in regulatory regions of 107 pts with breast cancer and analyzed association with prognostics factor in triple negative breast cancer and methylation promoter ESR1, APC, E-Cadherin, Rar B and 14-3-3 sigma. Results: We identified novel subtype-specific epigenotypes that clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors. Of the cases, 37pts (40%) were Luminal A (LA), 32pts (33%) Luminal B (LB), 14pts (15%) Triple-negative (TN), and 9pts (10%) HER2+. DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression. Methylation of this panel of promoter was found more frequently in triple negative and HER2 phenotype. ESR1 was preferably associated with TN(80%) and HER2+(60%) subtype. With a median follow up of 6 years, we found worse overall survival (OS) with more frequent ESR1 methylation gene(p>0.05), Luminal A;ESR1 Methylation OS at 5 years 81% vs 93% when was ESR1 Unmethylation. Luminal B;ESR1 Methylation 86% SG at 5 years vs 92% in Unmethylation ESR1. Triple negative;ESR1 Methylation SG at 5 years 75% vs 80% in unmethylation ESR1. HER2;ESR1 Methylation SG at 5 years was 66.7% vs 75% in unmethylation ESR1. Conclusions: Our results provide evidence that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

Breast cancer molecular subtypes association with clinical outcomes and race.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e12575-e12575 ◽  
Author(s):  
Ramses F. Sadek ◽  
Li fang Zhang ◽  
Houssein Talal Abdul Sater
Keyword(s):  
Breast Cancer ◽  
Black Women ◽  
Clinical Outcomes ◽  
Cox Regression ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Cancer Stage ◽  
Luminal A ◽  
Luminal B ◽  
Race Disparity

e12575 Background: Breast Cancer (BC) has been classified into four subtypes: Luminal A (LABC), Luminal B (LBBC), Triple negative (TNBC) and HER2-enriched (HER2e). BC mortality in Black women is significantly higher than in Whites and Asians. BC in Blacks has been characterized by higher grade and later stage. Causes of the Black-White BC survival disparity have been investigated, including differences in: diagnostic stage, socioeconomics, and comorbidities. These have led researchers to investigate the differences in tumor molecular subtype and their association with clinical outcomes and races. Methods: This study used the Surveillance, Epidemiology, and End Results – 18 (SEER-18) Registries research data between 2010 and 2013 that included over 212,000 patients. Descriptive statistics, Odds ratios (OR) and 95%Confidence intervals (CI) were used to study the association between BC stage, grade, and mortality and BC molecular subtypes across different races. We employed Cox regression models to explore the race disparity in BC mortality before and after controlling for BC molecular subtype and other clinical and social factors. Results: TNBC had more high grade cancer compared to HER2e subtype (OR, 1.5; CI, 1.3 - 1.8), LBBC (OR, 4.5; CI, 4.0 - 5.0) and LABC (OR, 12.2; CI, 11.2 – 13.3) for Black. BC mortality was higher in TNBC subtype compared to HER2e subtype (OR, 1.3; CI, 1.1 - 1.6), LBBC (OR, 2.4; CI, 2.0 - 2.9), and LABC (OR, 2.8; CI, 2.4 – 3.2) for Blacks. Results are consistent for all races. HER2e subtype had more late cancer stage compare to LBBC (OR, 1.2; CI, 1.0 - 1.4), TNBC (OR, 1.4; CI, 1.2 - 1.6) and LABC (OR, 2.1; CI, 1.8 - 2.4) in Blacks with similar results in all races. BC mortality in Blacks was higher compare with Whites (HR, 1.9; CI, 1.8 - 2.0) and Asian (HR, 2.7; CI, 2.5 - 3.0). After controlling for cancer subtype and other factors in the Cox regression model, the corresponding HRs ware significantly decreased to 1.2 (CI, 1.1 -1.3) and 1.6 (9CI, 1.5 -1.8). Blacks have heighst percent in stage IV and grade higer grade of disease. Conclusions: Molecular subtypes of BC contribute differently to risks of late cancer stage, high cancer grade and BC specific mortality. These differences are consistent in all races. The molecular subtypes and other social and clinical factors may explain part of the BC mortality race disparity.

Breast cancer in Angola, molecular subtypes: The first preliminary study.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13075-e13075
Author(s):  
Lúcio Lara Santos ◽  
Fernando Miguel ◽  
Lygia Vieira Lopes ◽  
Julio Oliveira ◽  
Eduardo Ferreira ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Locally Advanced ◽  
Luminal A ◽  
Her2 Positive ◽  
Luminal B ◽  
Therapeutic Decisions ◽  
Ihc Markers

e13075 Background: Women in sub-Saharan African countries, as Angola, are experiencing an increasing burden of aggressive breast cancer. Breast cancer molecular subtypes may enable more accurate diagnoses and support therapeutic decisions, however several studies have suggested that African breast cancers are predominantly hormone receptor poor. We conduct a study, to correlate the clinical pathological profiles and molecular subtypes, according its surrogate immunohistochemistry (IHC) markers, of breast cancer in Luanda, Angola. Methods: From Jan. 2011 to Dec. 30, 2014, 179 consecutive cases of microscopically confirmed invasive breast carcinoma that were evaluable for histology and IHC (ER, PR, HER2, and Ki-67) were classified. However, 21.8% (n = 39) of cases were poorly preserved, therefore it was only possible to study IHC in 140 cases. Results: All patients were female, the median age was 47 years (24-84 years). Invasive ductal carcinoma was the most common type, 91.4% (n = 128), grade 2 (moderately differentiated) was prevalent, 67.1%. Most of the tumours were locally advanced, stage III 65% (n = 91) and stage IV 3.6% (n = 5). In 140 cases studied, 53.2% (n = 74 ) of malignancies were hormone receptors positive, whence 25.7% were luminal A like, 19.3% luminal B like/ HER2 negative, 7.9% luminal B like/HER2 positive, 15.7% HER2 positive and 31,4% were triple-negative. Conclusions: Woman with breast cancer in Luanda-Angola were caracterized by advance stage and younger age at diagnosis of disease. The two predominant molecular subtypes are triple negative and luminal A like. Therefore, determining the molecular subtype using surrogate IHC markers has important treatment and prognostic implications for Angola women with breast cancer.

Impact of the molecular pathology of breast cancer on mortality rates and overall survival in a Haitian cancer clinic.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13588-e13588
Author(s):  
Joseph Bernard ◽  
Rebecca Henderson ◽  
Lynn Gabrielle Alexis ◽  
Doukens Patrick Gilbert ◽  
Lenz Sacha Christyl Pierre ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Mortality Rate ◽  
Molecular Subtype ◽  
Metastatic Breast ◽  
Molecular Classification ◽  
Luminal A ◽  
Luminal B ◽  
The Impact ◽  
Cancer Clinic

e13588 Background: Breast cancer in the most common malignancy among women in Haiti and is mostly diagnosed at an advanced stage. While it is well known that molecular subtype is a prognostic factor, it needs to be investigated among Haitian patients with breast cancer. This study aimed to evaluate the impact of molecular classification of breast cancer on the survival of patients managed in Haiti’s largest cancer clinic. Methods: A retrospective study was conducted on the breast cancer patients of Innovating Health International (IHI) in Port-au-Prince, Haiti from January 2014 to December 2018. Chart review included all patients with breast cancer and tested for molecular classification. Data on variables such as date of admission, age, TNM staging, molecular classification, outcome and date of death were collected for the analysis. Mortality rate and median overall survival (OS) were estimated as of December 31st, 2019 and stratified according to molecular subtypes. Results: Among the 948 breast cancer cases diagnosed for the study period, 234 (24.7%) of them had a complete molecular classification. The mean age was 51.5 years [range: 23-94]. 55.1% of the patients were ER-positive, among them 33.7% ER+/PR+/HER2-, 15.4% ER+/PR-/HER2-, 2.1% ER+/PR-/HER2+ and 3.8% ER+/PR+/HER+ (triple positive). There were overall 25.6% of luminal A and 29.5% of luminal B cases. 44.9% were ER-negative, among them 14.1% ER-/PR-/HER2+ (HER2-enriched) and 29.1% ER-/PR-/HER2- (triple-negative). 92.2% of the patients had advanced breast cancer (stages IIB to IV). 29.5% had metastatic breast cancer, 22.8% for luminal A cases, 27.0% for luminal B, 36.7% for HER2-enriched and 32.8% for TNBC. Overall mortality rate was 42.3%, respectively 33.3% for luminal A cases, 37.7% for luminal B, 42.4% for HER2-enriched cases and 55.9% for TNBC. Median OS was not yet reached for luminal A, luminal B and HER2-enriched breast cancer, with a respective mean survival of 52.4 months, 51.3 months and 51.6 months. However, OS was 30.6 months for triple-positive breast cancer and 23.7 months for TNBC. Conclusions: Patients with luminal A breast cancer were less likely to have metastatic disease and thus had lower mortality rate and better overall survival. This was likely due to its less aggressive biology and the availability of hormone therapy. Poor availability and inaccessibility of HER2-targeted drugs were the main cause of the higher mortality rate among HER2-enriched patients. TNBC remains the most aggressive subtype.

scholarly journals Evaluation of FGFR targeting in breast cancer through interrogation of patient-derived models

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Nicole J. Chew ◽  
Terry C. C. Lim Kam Sian ◽  
Elizabeth V. Nguyen ◽  
Sung-Young Shin ◽  
Jessica Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Therapeutic Target ◽  
Breast Cancer Subtype ◽  
Breast Cancer Subtypes ◽  
Cancer Tissue ◽  
Breast Cancers ◽  
Luminal A ◽  
Tissue Samples ◽  
Cancer Subtypes ◽  
Luminal B

Abstract Background Particular breast cancer subtypes pose a clinical challenge due to limited targeted therapeutic options and/or poor responses to the existing targeted therapies. While cell lines provide useful pre-clinical models, patient-derived xenografts (PDX) and organoids (PDO) provide significant advantages, including maintenance of genetic and phenotypic heterogeneity, 3D architecture and for PDX, tumor–stroma interactions. In this study, we applied an integrated multi-omic approach across panels of breast cancer PDXs and PDOs in order to identify candidate therapeutic targets, with a major focus on specific FGFRs. Methods MS-based phosphoproteomics, RNAseq, WES and Western blotting were used to characterize aberrantly activated protein kinases and effects of specific FGFR inhibitors. PDX and PDO were treated with the selective tyrosine kinase inhibitors AZD4547 (FGFR1-3) and BLU9931 (FGFR4). FGFR4 expression in cancer tissue samples and PDOs was assessed by immunohistochemistry. METABRIC and TCGA datasets were interrogated to identify specific FGFR alterations and their association with breast cancer subtype and patient survival. Results Phosphoproteomic profiling across 18 triple-negative breast cancers (TNBC) and 1 luminal B PDX revealed considerable heterogeneity in kinase activation, but 1/3 of PDX exhibited enhanced phosphorylation of FGFR1, FGFR2 or FGFR4. One TNBC PDX with high FGFR2 activation was exquisitely sensitive to AZD4547. Integrated ‘omic analysis revealed a novel FGFR2-SKI fusion that comprised the majority of FGFR2 joined to the C-terminal region of SKI containing the coiled-coil domains. High FGFR4 phosphorylation characterized a luminal B PDX model and treatment with BLU9931 significantly decreased tumor growth. Phosphoproteomic and transcriptomic analyses confirmed on-target action of the two anti-FGFR drugs and also revealed novel effects on the spliceosome, metabolism and extracellular matrix (AZD4547) and RIG-I-like and NOD-like receptor signaling (BLU9931). Interrogation of public datasets revealed FGFR2 amplification, fusion or mutation in TNBC and other breast cancer subtypes, while FGFR4 overexpression and amplification occurred in all breast cancer subtypes and were associated with poor prognosis. Characterization of a PDO panel identified a luminal A PDO with high FGFR4 expression that was sensitive to BLU9931 treatment, further highlighting FGFR4 as a potential therapeutic target. Conclusions This work highlights how patient-derived models of human breast cancer provide powerful platforms for therapeutic target identification and analysis of drug action, and also the potential of specific FGFRs, including FGFR4, as targets for precision treatment.

scholarly journals Breast Cancer Case Using Tamoxifen during Pregnancy: A Case Report and Literature Review

2017 ◽  
Vol 12 (2) ◽  
pp. 114
Author(s):  
Sarah Mirghani
Keyword(s):  
Breast Cancer ◽  
Early Stage ◽  
Breast Cancer Case ◽  
Cancer Case ◽  
External Irradiation ◽  
Luminal A ◽  
Invasive Ductal Cancer ◽  
Estrogen Receptor Positive ◽  
Nulliparous Female ◽  
The Right

<p>This is a case of 32 years old nulliparous female who was diagnosed  in November 2004 as a case of carcinoma of the right breast , luminal A , (Estrogen Receptor positive Progesterone receptor negative, Her 2 negative, Ki67 10 %), poorly differentiated invasive ductal cancer, TNM stage,T2 N0 MO.  She had a wide local excision and axillary clearance. As she is a case of low risk early stage luminal A breast cancer; she was not given chemotherapy, instead she had a course of external irradiation and was put on Tamoxifen (Astra Zeneca, 20 mg daily), and was advised not to get pregnant during this treatment,but she got pregnant and delivered normally a healthy infant, although Tamoxifen is potentially teratogenic.</p>

scholarly journals The Analysis of bcl-2 in Association with p53 and Ki-67 in Triple Negative Breast Cancer and Other Molecular Subtypes in Ghana

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Charity Ameh-Mensah ◽  
Babatunde Moses Duduyemi ◽  
Kweku Bedu-Addo ◽  
Elijah Atta Manu ◽  
Francis Opoku ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Subtypes ◽  
Histological Grade ◽  
Her2 Overexpression ◽  
Luminal A ◽  
Ki 67 ◽  
Cross Sectional ◽  
Luminal B ◽  
Protein P53

Background. Little is known about the role of apoptosis in the tumorigenesis and prognosis of breast cancer in Ghana. Chemotherapeutic drug efficacy partially relates to apoptosis induction, rendering it a vital target in cancer therapy with unique biomarker opportunities that have not been exploited. Aberrations in this pathway are central to tumorigenesis, tumor progression, overall tumor growth, and regression during treatment therapies. Antiapoptotic bcl-2 (gene) and p53 are known to play roles in apoptosis while Ki-67 is a proliferative marker. The aim of our study is to determine the association of bcl-2 (protein) with p53 and Ki-67 in 203 consecutive breast cancer cases over a 10-year period. Method. A retrospective cross-sectional study on archival FFPE tissue blocks over a 9-year period with abstraction of clinicopathologic data. Two hundred and three consecutive and suitable FFPE blocks were selected for tissue microarray (TMA) construction, and IHC (bcl-2 (protein), Ki-67, p53, cyclin D, pan cytokeratins A and E, ER, PR, and HER2/neu) was done. Expressions of bcl-2 (protein), p53, and Ki-67 were related to histological grade, lymphovascular invasion, and molecular subtypes. SPSS version 23 was used to analyze results. Results. Most of our cases were in the fifth decade of life (31%); invasive carcinoma of no special type (NST) was predominant (87%); histological grade III (38%) was the highest; and Luminal A (19.8%), Luminal B (9.9%), HER2 (16%), and TNBC (54.3%) constituted the molecular classes. bcl-2 expression was found in 38% of the cases. Our cases also showed mutation in p53 (36.7%) and ki-67 expression (62.5%). bcl-2 (protein) and p53 significantly correlated with Luminal B and TNBC ( p < 0.01 ). Ki-67 also correlated significantly with Luminal A and B and HER2 overexpression ( p < 0.01 ). Premenopausal age (40–49) and histological grade inversely correlated with bcl-2 (protein) expression. p53 statistically correlated with Ki-67 ( p < 0.05 ). Conclusion. Our results show high expression of bcl-2 (protein) suggesting an important role of apoptosis in Ghanaian breast cancer cases. bcl-2 (protein), p53, and Ki-67 expressions emerged interdependently from this research and can thus be manipulated in prediction and prognosis of breast cancers in our setting.

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