Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Feb 28:9:43.
doi: 10.1186/1746-1596-9-43.

Clinicopathologic features of triple negative breast cancers: an experience from Pakistan

Atif Ali Hashmi, Muhammad Muzzammil Edhi, Hanna Naqvi, Naveen Faridi, Amna Khurshid, Mehmood Khan  1
Affiliations

Clinicopathologic features of triple negative breast cancers: an experience from Pakistan

Atif Ali Hashmi et al. Diagn Pathol. .

Abstract

Background: Young age breast cancers are quite prevalent in our setup, a significant number of which exhibit triple negative phenotype. These cancers behave in an aggressive fashion and unresponsive to targeted adjuvant therapy. We aimed to evaluate clinical and histopathologic features of triple negative cancers in our population.

Methods: We retrospectively evaluated 1104 cases of primary breast cancers. Immunohistochemical studies for ER, PR and Her2neu followed by Her2neu gene amplification by FISH testing were done to identify 205 (18.6%) cases of triple negative breast cancers.

Results: Mean age for triple negative breast cancer patients was 48.4 years (±12.3) and 60% of patients were diagnosed at less than 50 years of age. Although ductal carcinoma was the most frequent histologic type, a meaningful number of cases exhibited metaplastic and medullary like features (10.7% and 5.9% respectively). Similarly geographic necrosis involving more than 40% of tumor and extensive lymphocytic infiltration was a considerable finding. Mean Ki67 index was 45.2% (±25.2) and as a reflection of tumor grade, a significantly higher proportion of cases (66.3%) were under high risk Ki67 category (>30%).

Conclusion: Triple negative breast cancers typify high grade breast cancers with a higher frequency of atypical medullary and metaplastic histologies. Their prevailing occurrence at a younger age raises question of under lying BRCA mutations in our population. Therefore, we suggest that risk factors including BRCA 1 mutations should be uncovered in reproductive age group breast cancers especially those disclosing basal like phenotype.

Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9042440621102239.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Micrographs of carcinoma with medullary features. (a-c) Infiltrating carcinoma with circumscribed pushing borders, dense peripheral lymphoid infiltrate and syncytial growth pattern. (d) High Ki-67 index in tumor cells.
Figure 2
Figure 2
Micrographs of metaplastic carcinoma, matrix producing type. (a-b) Tumor cells producing abundant myxoid matrix. (c) Microphotograph showing high Ki-67 index.
Figure 3
Figure 3
Micrographs showing metaplastic carcinoma. (a-b) Matrix producing type with area of necrosis.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Lønning PE, Børresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869–10874. doi: 10.1073/pnas.191367098. - DOI - PMC - PubMed
    1. Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, Quackenbush JF, Stijleman IJ, Palazzo J, Marron JS, Nobel AB, Mardis E, Nielsen TO, Ellis MJ, Perou CM, Bernard PS. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160–1167. doi: 10.1200/JCO.2008.18.1370. doi:10.1200/JCO.2008.18.1370. - DOI - PMC - PubMed
    1. Moldovan L, Mitroi A, Petrescu CM, Aschie M. Classification of breast carcinomas according to gene expression profiles. J Med Life. 2013;6(1):14–17. - PMC - PubMed
    1. Brenton JD, Carey LA, Ahmed AA, Caldas C. Molecular classification and molecular forecasting of breast cancer: ready for clinical application? J Clin Oncol. 2005;23:7350–7360. doi: 10.1200/JCO.2005.03.3845. - DOI - PubMed
    1. Alshareeda AT, Soria D, Garibaldi JM, Rakha E, Nolan C, Ellis IO, Green AR. Characteristics of basal cytokeratin expression in breast cancer. Breast Cancer Res Treat. 2013;139(1):23–37. doi: 10.1007/s10549-013-2518-x. - DOI - PubMed

Substances

LinkOut - more resources