Cytogenetics and Clinical Correlations in Breast Cancer

Author(s):  
Julia C. Emerson ◽  
Sydney E. Salmon ◽  
William Dalton ◽  
Daniel L. McGee ◽  
Jin-Ming Yang ◽  
...  
2021 ◽  
Author(s):  
Sadia Ajaz ◽  
Sani-e-Zehra Zaidi ◽  
Saleema Mehboob Ali ◽  
Aisha Siddiqa ◽  
Mohammad Ali Memon

Demographics for breast cancers vary widely among nations. The frequency of germline mutations in breast cancers, which reflects the hereditary cases, has not been investigated adequately in Pakistani population. In the present study, germ-line mutations in twenty-seven breast cancer candidate genes were investigated in eighty-four sporadic breast cancer patients along with the clinical correlations. The germ-line variants were also assessed in two healthy controls. The most frequent parameters associated with hereditary cancer cases are age and ethnicity. Therefore, the clinico-pathological features were evaluated by descriptive analysis and Pearson χ2 test (with significant p-value <0.05). The analyses were stratified on the basis of age (<40 years vs >40 years) and ethnicity. The breast cancer gene panel assay was carried out by a genomic capture, massively parallel next generation sequencing assay on Illumina Hiseq2000 assay with 100bp read lengths. Copy number variations were determined by partially-mapped read algorithm. Once the mutation was identified, it was validated by Sanger sequencing. The ethnic analysis stratified on the basis of age showed that the frequency of breast cancer at young age (<40 years) was higher in Sindhis (n=12/19; 64%) in contrast to patients in other ethnic groups. Majority of the patients had stage III (38.1%), grades II and III (46.4%), tumor size 2-5cm (54.8%), and invasive ductal carcinoma (81%). Overall, the analysis revealed germ-line mutations in 11.9% of the patients. The mutational spectrum was restricted to three genes: BRCA1, BRCA2, and TP53. The identified mutations consist of seven novel germ-line mutations, while three mutations have been reported previously. All the mutations are predicted to result in protein truncation. No mutations were identified in the remaining twenty-four candidate breast cancer genes. The present study provides the framework for the development of preventive and treatment strategies against breast cancers in Pakistani population.


2020 ◽  
Author(s):  
Rodrigo Vismari de Oliveira

In the last two decades, new discoveries concerning on breast cancer have contributed to important changes on its classification, from purely morphologic to molecular embased, to establish better correlation with clinicopathologic features. The classification in molecular subtypes, based on hormonal receptor and HER-2 status, have been remarkable not only for its more accurated clinical correlations, but also for its easy applicability in diagnostic routine, better replication of tumor microenvironment through the selection of paraffinized tumor amounts and cost-effectiveness of the detection method, the immunohistochemistry. Hence, this classification may predict the breast cancer prognosis and became an important target for therapy with hormonal and HER-2 antagonist drugs. Other study models, like cancer-stem cell hypothesis and immunological aspects of human cancer, have brought new emerging ideas regarding on molecular pathways and accurated prognostic preditions. Putative stem-cell markers and PD-1/PDL-1, have highlighted among several emerging molecular markers because of the bad cancer prognosis determinated by stem-cell markers expression and for emerging new drugs with selective action to PD-1/PDL-1, with promising results. The therapy of breast cancer have became diverse, target directed and personalized, in order to take in consideration the clinicopathologic cancer aspects, molecular tumor profile and clinical status of the patient.


Tumor Biology ◽  
2016 ◽  
Vol 37 (6) ◽  
pp. 7033-7045 ◽  
Author(s):  
Ebubekir Dirican ◽  
Mustafa Akkiprik ◽  
Ayşe Özer

Oncotarget ◽  
2013 ◽  
Vol 4 (10) ◽  
pp. 1748-1762 ◽  
Author(s):  
Roxana S Redis ◽  
Anieta M Sieuwerts ◽  
Maxime P Look ◽  
Oana Tudoran ◽  
Cristina Ivan ◽  
...  

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