Trends in Molecular Classification of Breast Carcinoma in a tertiary Health care centre: A 5 year retrospective study

Siddiqui, Bushra; Piyush, A R; Faridi, Shahbaz Habib; Ahmad, Sharique; Khan, Rehan Ahmed

doi:10.21276/iabcr.2016.2.2.15

Cited by 4 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…20,21 These Basal-like breast cancers are mitotically active, highgrade and are associated with younger age of the patient. 7,8 A readily available prognostic immunohistochemical surrogate marker, easily applied on formalin-fixed, paraffin embedded tissues, would therefore identify these molecular subtypes of breast cancer patients. 14 Study by Sofi GN et al, in their study of 101 cases, observed ER/PR positivity in 63 % cases.…”

Section: Resultsmentioning

confidence: 99%

“…In has been shown that patients of breast carcinoma overexpressing Her2 (Her2 positive cohort) do respond to targeted therapy such as herceptin. [5][6][7][8] Consistent with most widely accepted clinical practice, authors considered a tumour Her2: 2+as being scored as Her2: 3 +on IHC. FISH (Fluorescent In Situ Hybridization) was not done in.…”

Section: Resultsmentioning

confidence: 99%

“…Within estrogen/progesterone receptor (ER/PR) positive subtypes, the luminal B cohort is seen in younger age and has a significantly worse prognosis than luminal A which is associated with best prognosis and low recurrence rate. 7,8 Follow-up studies have shown these subtypes to be conserved across diverse patient series and array platforms have shown that different gene expression based predictors are likely tracking a similar, common set of biological subtypes, with significant agreement in predicting patient outcome. 9,10 Cost and complexity issues have to date rendered gene expression profiling impractical as a routine hospital diagnostic tool.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Immunohistochemical profile and its association with clinicopathological parameters in carcinoma breast: a prospective study in central India

Walke

Gunjkar²

2019

Int J Res Med Sci

View full text Add to dashboard Cite

Background: Carcinoma breast is one of the most common malignancies of women in India. The current study was conducted with the objective of assessing estrogen receptor (ER), progesterone receptor (PR), Her-2/neu (human epidermal growth factor receptor-2) expression and Ki67 index of breast carcinomas and its correlation with histological grade, tumour size and lymph node metastasis.Methods: Forty-seven lumpectomy or modified mastectomy specimens diagnosed as Infiltrating duct carcinoma (IDC): NOS, were selected for panel of imuno histochemistry (IHC) markers on tissue microarray blocks prepared from each case.Results: Maximum of our patients belonged to premenopausal 24/47 (51%) and 20% to younger age group (<30 year). Tumour size of 2-5 cm was observed in maximum females 29 (61%); while 13(27%) had size >5.0cm. The majority of cases diagnosed as grade I (40%) and lymph node involvement was seen in 31/47 (65%). Molecular classification revealed 10 (21%) luminal A, 4 (8%) luminal B, 9 (19%) Her2/neu positive, while triple negative phenotype comprised of maximum 24 (51%) patients. Most of the Luminal group tumours were low grade (14/15); while majority of Her2/neu positive 7/9(77%) and triple negative tumours 19/24 (80%) belonged to higher grades.Conclusions: Breast carcinoma among our patient is characterized by a large percentage of triple negative phenotype that is less susceptible to hormonal therapy. The empirical treatment with tamoxifen should therefore be reconsidered as it would be less effective. Assessment of prognostic markers in breast carcinoma is strongly advocated in order to provide the best therapeutic options.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Immunohistochemical profile and its association with clinicopathological parameters in carcinoma breast: a prospective study in central India

Walke

Gunjkar²

2019

Int J Res Med Sci

View full text Add to dashboard Cite

show abstract

“…Immunohistochemistry (IHC) or in situ hybridization (ISH) assays are well-established methods used to distinguish subtypes in breast cancer (BC) based on hormone receptor statuses [1]. Increasingly, RNA-based signature assays such as MammaPrint, Oncotype DX, and Predictor Analysis of Microarray 50 (PAM50) [2] are being employed as supplementary prognostic indicators due to studies demonstrating more significant differential survival between identified subtypes when compared to standard clinicopathological factors [3][4][5]. In particular, PAM50 intrinsic molecular subtyping, as part of the NanoString Prosigna [6] and the Agendia BluePrint panel [7], is becoming more widely used in early-stage breast cancers to determine the likelihood of responding to chemotherapy.…”

Section: Introductionmentioning

confidence: 99%

A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival

Jaber¹,

Song

Taylor

et al. 2020

Breast Cancer Res

View full text Add to dashboard Cite

Background: Breast cancer intrinsic molecular subtype (IMS) as classified by the expression-based PAM50 assay is considered a strong prognostic feature, even when controlled for by standard clinicopathological features such as age, grade, and nodal status, yet the molecular testing required to elucidate these subtypes is not routinely performed. Furthermore, when such bulk assays as RNA sequencing are performed, intratumoral heterogeneity that may affect prognosis and therapeutic decision-making can be missed. Methods: As a more facile and readily available method for determining IMS in breast cancer, we developed a deep learning approach for approximating PAM50 intrinsic subtyping using only whole-slide images of H&E-stained breast biopsy tissue sections. This algorithm was trained on images from 443 tumors that had previously undergone PAM50 subtyping to classify small patches of the images into four major molecular subtypes-Basal-like, HER2-enriched, Luminal A, and Luminal B-as well as Basal vs. non-Basal. The algorithm was subsequently used for subtype classification of a held-out set of 222 tumors. Results: This deep learning image-based classifier correctly subtyped the majority of samples in the held-out set of tumors. However, in many cases, significant heterogeneity was observed in assigned subtypes across patches from within a single whole-slide image. We performed further analysis of heterogeneity, focusing on contrasting Luminal A and Basal-like subtypes because classifications from our deep learning algorithm-similar to PAM50-are associated with significant differences in survival between these two subtypes. Patients with tumors classified as heterogeneous were found to have survival intermediate between Luminal A and Basal patients, as well as more varied levels of hormone receptor expression patterns. Conclusions: Here, we present a method for minimizing manual work required to identify cancer-rich patches among all multiscale patches in H&E-stained WSIs that can be generalized to any indication. These results suggest that advanced deep machine learning methods that use only routinely collected whole-slide images can approximate RNAseq-based molecular tests such as PAM50 and, importantly, may increase detection of heterogeneous tumors that may require more detailed subtype analysis.

show abstract

“…The author also claims the result to be attributed to predominantly younger patient population in their study group. 18…”

Section: Resultsmentioning

confidence: 99%

Study of hormone receptor status and HER/2-neu expression in breast malignancies and its implication in molecular subtyping in a tertiary care hospital

Daniel¹,

Goneppanavar²,

Subramanian³

et al. 2020

IJPO

View full text Add to dashboard Cite

Breast cancer has ranked number one cancer among Indian females. In addition to conventional histopathology based on morphology, the College of American Pathologists (CAP) and American Society of Clinical Oncology (ASCO) recommend evaluation of hormone receptors – Estrogen Receptor (ER), Progesterone Receptor (PR) as well as HER2. The role of hormone receptors as a prognostic and therapeutic tool in breast cancer is widely accepted. The molecular subtyping is formulated by immunohistochemical characterization as well as gene expression profiling though the latter is currently not feasible. In the present study we retrospectively measured the frequency of hormone receptor and HER2 positivity in breast cancer patients and classified into the molecular subtypes. We conducted a three year retrospective study on 45 cases of breast cancer who underwent Modified radical mastectomy (MRM), subjected to immunohistochemical evaluation for the status of hormone receptors and HER2 expression as per the ASCO/CAP guidelines. In addition, the clinical details pertaining to patient age, sex, tumour size and histological type were recorded. The molecular subtype of each case was determined and the prevalence compared with similar studies in literature. The predominant histopathological type in this study was Invasive ductal carcinoma (93.3%). Immunohistochemistry for hormone receptor status revealed ER positivity of 55.5%, PR positivity of 46.6% and HER2 positivity of 33.5%. Among molecular subtyping Luminal A attributed to 33.3% of the cases and was the most prevalent followed by HER2 enriched with 26.6%.The combined utility of conventional histopathology coupled with immunohistochemical assay based molecular subtyping for routine clinical practice enables diagnosis, estimating prognosis and predicting response to treatment.

show abstract

Trends in Molecular Classification of Breast Carcinoma in a tertiary Health care centre: A 5 year retrospective study

Cited by 4 publications

References 0 publications

Immunohistochemical profile and its association with clinicopathological parameters in carcinoma breast: a prospective study in central India

Immunohistochemical profile and its association with clinicopathological parameters in carcinoma breast: a prospective study in central India

A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival

Study of hormone receptor status and HER/2-neu expression in breast malignancies and its implication in molecular subtyping in a tertiary care hospital

Contact Info

Product

Resources

About