Immunohistochemical Classification of Breast Invasive Duct Carcinoma (NOS).

Transcription

1 Immunohistochemical Classification of Breast Invasive Duct Carcinoma (NOS). Thesis Submitted In Fulfillment of Master Degree in Pathology BY Habiba Mohammed Saleh EL-Fendy M.B.B.Ch Supervisors Prof. Dr. Badaweya Bayomi Ibraheem Professor of pathology Faculty of Medicine - Cairo University Prof. Dr. Sahar Mohammed Talaat Professor of pathology Faculty of Medicine - Cairo University Assistant Prof. Dr. Asmaa Ibraheem Salama Assistant Professor of pathology National Cancer Institute - Cairo University Cairo University 2012

2 Abstract Different breast cancer subtypes were newly recognized based on immunohistochemistry for ER, PR, HER2/neu and Ki-67. This classification reflected on patients prognosis and management. We conducted this study to determine the prevalence of breast cancer subtypes in Egypt (National Cancer Institute, Cairo University) according to immunohistochemistry panel and to explore their association with patients prognosis. To determine breast cancer subtypes, we characterized 100 tumor specimens obtained from (National Cancer Institute, Cairo University) by performing ER, PR, HER2/neu, CK5/6 and Ki-67 immunohistochemistry. Correlation with disease free survival (DFS) was done. Cases were categorized into luminal A (22%), luminal B (33%), luminal HER2/neu (9%), HER2/neu-enriched (26%) and TNBC (10%). Nodal metastasis was observed mostly in HER2/neu-enriched (35.4%) and luminal B (33.8%). TNM staging appeared to be strong predicator of DFS. Worst 2-year DFS was for HER/neu-enriched subtype (40.77%) followed by luminal A (63.25%). HER2/neu-enriched subtype is considered the worst subtype with poor outcome. Luminal A is intermediate subtype with underlying several factors that can turn its prognosis adversely. TNBC may behave in a favorable way due to TNBC paradox. Key words :- Immunohistochemical - Classification - Breast - Invasive Duct Carcinoma (NOS).

3 Acknowledgement First and foremost, I thank Allah (SWT) for answering my prayers and endowing me with patience and knowledge to complete this work. This thesis would not have been possible without the help, support, encouragement and keen supervision with useful suggestions, guidance and patience of my principal supervisors, Prof. Dr. Badaweya Bayomi and Prof. Dr. Sahar Talaat, Professors of pathology, Faculty of Medicine, Cairo University. I would like to express my deepest gratitude and sincere appreciation to my supervisor Assistant Prof. Dr. Asmaa Salama, assistant professor of oncologic pathology, NCI, Cairo University for her excellent guidance, caring, patience, kind encouragement, revision of the manuscript and providing me with an excellent atmosphere for doing this research. I would also like to thank Prof. Dr. Nabil El-Bolkainy and Prof. Dr. Akram Nouh, professors of oncologic pathology, NCI, Cairo University for guiding my research by helping me to develop my background in pathology and provision of facilities to finish my work. Special thanks go to Prof. Dr. Magda Mourad, head of pathology department, NCI, Cairo University for generous help, encouragement, provision of facilities and supplies to carry out this work.

4 Many thanks to Prof. Dr. Manar Moneer, Professor of statistic and cancer epidemiology, NCI, Cairo University for her help, effort and support to accomplish the statistical work of this study. I would like to thank all my senior colleagues, who as wonderful sisters were always willing to help and give their best suggestions, especially Eman Naguib for providing her experience and valuable researches concerned in breast cancer. I wish to express my gratitude to the whole staff members of pathology departments at the National Cancer Institute, Cairo University for their hearted support, encouragement and advices. Special thanks for my parents for their prayers and all the support they have provided me over the years. Their care was the greatest gift anyone has ever given me. They taught me the value of hard work and were always there cheering me up and stood by me through the good times and bad. For any errors or inadequacies that may remain in this work, of course, the responsibility is entirely my own.

5 LIST OF CONTENTS Introduction Aim of work Review of Literature Breast histology Breast carcinoma.. 6 Epidemiology.. 6 Risk factors WHO classification of epithelial tumors of breast Infiltrating duct carcinoma, NOS. 18 Histologic picture and grading Tumor stage. 21 AJCC cancer staging changes from sixth to seventh edition Prognostic and predictive factors Molecular subtypes of breast carcinoma Steroid hormone receptor proteins Relationship between ER/PR and breast carcinoma. 41 Significance of ER and PR receptor status... 42

6 Definition of positive and negative ER and PR tests ASCO recommendations for ER and PR test HER2/neu Clinical utility of HER2 testing Assessment of HER2/neu status Anti-HER2 Herceptin in Breast Cancer. 49 Ki Localization of Ki-67 within the nucleus.. 51 The clinical value of ki-67 immunostaining.. 52 Materials and Methods Results Discussion Summary Conclusions and recommendations References Arabic Summary

7 LIST OF FIGURES Page Figure (1): Normal histology of the breast (Tabár et al., 1996).. 5 Figure (2): Invasive duct carcinoma. Tumor with stellate border and chalky white streaks of necrosis (Rosen and Paul, 2009b) Figure (3): Presumed relations between breast cancer subtypes and their histopathological subtypes, expression of histological markers, intrinsic subtypes and prognosis. 37 Figure (4): Action of Tamoxifen on ER positive breast cancer (Kleinsmith et al., 2010) Figure (5): Diagrammatic description of Allred Score (Choudhury et al., 2010) Figure (6): Herceptin acting on HER2-positive breast cancer cells (Genentech, Inc. 2012) Figure (7): Cell cycle (Franklin, 2012) Figure (8): Frequency distribution of studied cases according to gender Figure (9): Frequency distribution of studied cases according to laterality.. 64 Figure (10): Frequency distribution of studied cases according to location.. 64 Figure (11): Frequency distribution of studied cases according to tumor size 65 Figure (12): Frequency distribution of tumor grades among the studied cases.. 66 Figure (13): A case of invasive duct carcinoma, grade I, showing ductal formation > 90% of tumor (hematoxylin and eosin; original magnification X200) Figure (14): A case of invasive duct carcinoma, grade II, showing ductal formation in 10% of tumor and moderate pleomorphism and mitosis 8/10HPF, insit illustrated mitotic figures, (hematoxylin and eosin; original magnification X400) Figure (15): A case of invasive duct carcinoma, grade III with no ductal differentiation, marked pleomorphism and high mitotic activity >20/10HPF, insit illustrated mitotic figures (hematoxylin and eosin; original magnification X400)

8 Figure (16): A case of invasive duct carcinoma, grade II associated with major DCIS, comedo type, (hematoxylin and eosin; original magnification X400) Figure (17): A case of invasive duct carcinoma, grade II associated with major DCIS, solid type, (hematoxylin and eosin; original magnification X200) Figure (18): A case of invasive duct carcinoma, grade II associated with Paget s disease, (hematoxylin and eosin; original magnification X200) 69 Figure (19): LN metastasis in a case of invasive duct carcinoma, garde II, showing nodal capsule invasion by tumor cells, (hematoxylin and eosin; original magnification X200) Figure (20): Frequency distribution of lymph node status among studied cases. 71 Figure (21): Frequency distribution of different metastatic sites Figure (22): Frequency distribution of studied cases according to surgical procedure...73 Figure (23): Distribution of breast cancer subtypes among studied cases Figure (24): A case of invasive duct carcinoma, grade II, in a female patient 69 years old, stage T2N0M0, classified as luminal A. (A) Hematoxylin and eosin; original magnification X400. (B) ER: (positive), (C) PR: (positive), (D) HER2/neu: negative, score (0) and (E) Ki-67 LI: 6% (low proliferation index), {immunoperoxidase with hematoxylin counterstain; original magnification X400 in (B- E)} Figure (25): A case of invasive duct carcinoma, grade II, in a female patient 62 years old, stage T2N1M0, classified as luminal B. (A) Hematoxylin and eosin; original magnification X400. (B) ER: (positive), (C) PR: (positive), (D) HER2/neu: negative, score (0) and (E) Ki-67 LI: 48% (high proliferation index), {immunoperoxidase with hematoxylin counter stain; original magnification x400 in (B-E)}.. 77 Figure (26): A case of invasive duct carcinoma, grade II, in a female patient 72 years old, stage T2N1M0, classified as luminal HER2/neu. (A) Hematoxylin and eosin; original magnification X400. (B) ER: (positive), (C) PR: (positive), (D) HER2/neu: positive, score (3) and (E) Ki-67 LI: 16.18% (high proliferation index), {immunoperoxidase with hematoxylin counter stain; original magnification x400 in (B-E)}.. 79 Figure (27): A case of invasive duct carcinoma, grade II, in a female patient 60 years old, stage T2N3M0, classified as HER2/neu enriched. (A) Hematoxylin and eosin; original magnification X400. (B) ER: (negative), (C) PR: (negative), (D) HER2/neu:

9 positive, score (3), {immunoperoxidase with hematoxylin counter stain; original magnification X400 in (B-D)} Figure (28): A case of invasive duct carcinoma, grade II, in a female patient 60 years old, stage T2N3M0, classified as TNBC, basal-like. (A) Hematoxylin and eosin; original magnification x400. (B) ER: (negative), (C) PR: (negative), (D) HER2/neu: negative, score (0). (E) CK5/6: (cytoplasmic positive reaction). {immunoperoxidase with hematoxylin counter stain; original magnification x400 in (B-E)}.. 80 Figure (29): Association between breast cancer subtypes and patient s age.. 81 Figure (30): Association between breast cancer subtypes and sex. 82 Figure (31): Association between breast cancer subtypes and nodal status Figure (32): Association between breast cancer subtypes and tumor size (median).. 85 Figure (33): Association between breast cancer subtypes and (T) stage Figure (34): Association between breast cancer subtypes and (N) stage Figure (35): Association between breast cancer subtypes and anatomic stage.. 87 Figure (36): Distribution of hormone positive cases according to Ki-67 LI Figure (37): Association between Ki-67 and tumor grade in hormone positive cases Figure (38): Association between Ki-67 and tumor size in hormone positive cases.. 90 Figure (39): Association between Ki-67 and nodal status in hormone positive cases Figure (40): Association between Ki-67 and (T) stage in hormone positive cases Figure (41): Association between Ki-67 and (N) stage in hormone positive cases 92 Figure (42): Association between Ki-67 and anatomic stage in hormone positive cases 93 Figure (43): DFS in relation to tumor size of the studied cases. 97 Figure (44): DFS in relation to hormone receptor status of the studied cases... 98

10 Figure (45): DFS in relation to HER2/neu status of the studied cases. 98 Figure (46): DFS in relation to nodal status of the studied cases. 98 Figure (47): DFS in relation to T stage of the studied cases. 99 Figure (48): DFS in relation to N stage of the studied cases Figure (49): DFS in relation to anatomic stage of the studied cases Figure (50): DFS in relation to tumor type of surgery of the studied cases Figure (51): DFS in relation to breast cancer subtypes 100

11 LIST OF TABLES Page Table (1): Nottingham combined histologic grade (Elston-Ellis modification of Scarff- Bloom-Richardson grading system) (Tavassoli and Devilee, 2003) Table (2): TNM staging system of breast cancer, 7 th edition (Edge and Compton., 2010).. 23 Table (3): Immunohistochemical Criteria for Defining Breast Cancer Molecular Subtypes (Voduc et al., 2010) 34 Table (4): Systemic treatment recommendations for subtypes (Goldhirsch et al., 2011).. 34 Table (5): HER2/neu score used to evaluate Hercept Test (Lester, 2006) Table (6): Nottingham combined histologic grade (Tavassoli and Devilee, 2003) Table (7): HER2/neu score used to evaluate Hercept Test (Lester, 2006) Table (8): The used primary antibodies.. 57 Table (9): Immunohistochemical Criteria for Defining Breast Cancer Molecular subtypes (Voduc et al., 2010). 59 Table (10): TNM staging system of breast cancer, 7 th edition (Edge and Compton., 2010).. 60 Table (11): Distribution of tumor size among studied cases.. 65 Table (12): Frequency distribution of tumor grades among the studied cases Table (13): Frequency distribution according to extent of DCIS among studied cases. 66 Table (14): Frequency distribution of lymph nodal status among studied cases Table (15): Distribution of tumor anatomic stage among studied cases. 71

12 Table (16): Frequency distribution according to metastasis among studied cases..73 Table (17): Distribution of hormonal therapy among the cases.. 74 Table (18): Distribution of breast cancer subtypes among studied cases 75 Table (19): Association between breast cancer subtypes and patient s age Table (20): Association between breast cancer subtypes and sex Table (21): Association between breast cancer subtypes and site.. 83 Table (22): Association between breast cancer subtypes and nodal status. 83 Table (23): Association between breast cancer subtypes and tumor size (median) Table (24): Association between breast cancer subtypes and (T) stage. 85 Table (25): Association between breast cancer subtypes and (N) stage. 86 Table (26): Association between breast cancer subtypes and anatomic stage 87 Table (27): Distribution of hormone positive cases according to Ki-67 LI 88 Table (28): Association between Ki-67 and tumor grade in hormone positive cases. 89 Table (29): Association between Ki-67 and tumor size in hormone positive cases Table (30): Association between Ki-67 and nodal status in hormone positive cases. 90 Table (31): Association between Ki-67 and (T) stage in hormone positive cases.. 91 Table (32): Association between Ki-67 and (N) stage in hormone positive cases. 92 Table (33): Association between Ki-67 and anatomic stage in hormone positive cases 93 Table (34): Disease free survival (DFS) in relation to prognostic factors.. 96

13 LIST OF ABBREVIATIONS ABC: Avidin biotin complex AgNOR: Argyrophilic nucleolar organizer regions AJCC: American Joint Committee on Cancer Akt, also known as Protein Kinase B (PKB) ASCO: American Society of Clinical Oncology BC: breast cancer BCS: breast conservative surgery BM: bone marrow. BMI: body mass index BrdU: Thymidine labeling index, bromodeoxyuridine CCs: Clear cells CISH: Chromogenic in situ hybridization CMF: Cyclophosphamide, Methotrexate & Fluorouracil CXCL12: Chemokine, essential for hematopoietic stem cell function. DAB: 3, 3 diaminobenzinetetrachloride DCIS: Ductal carcinoma in situ DFS: Disease free survival EGFR: epidermal growth factor receptor

14 ELISA: enzyme-linked immunosorbent assay ER: Estrogen receptor FEC: 5-fluorouracil, epirubicin and cyclophosphamide FISH: Fluorescence in situ hybridization GEP-NETs: Neuroendocrine gastrointestinal and pancreatic tumors HER2: The human epidermal growth factor receptor 2 gene HER/ErbB: human epidermal growth factor H 2 O 2: hydrogen peroxide HT: Hormonal therapy Hx & E: hematoxilin and eosin staining IARC: International Agency for Research and Cancer IDC: invasive ductal carcinoma IHC: immunohistochemistry IM: internal mammary node (i+): +ve by IHC Ki-67 LI: Ki-67 labeling index LN: lymph node LR: local recurrence M: distant metastases MCL: Mantle cell lymphoma

15 MoAbs: Monoclonal antibodies (mol ): negative molecular findings (-ve RT-PCR) (mol+): positive molecular findings (+ve RT-PCR) N: regional lymph nodes NBF: Neutral buffered formalin NCCN: National Comprehensive Cancer Network NCI: National Cancer Institute NOS: not otherwise specified NS: not specified PAI-1: plasminogen activator inhibitor-1 PARP inhibitors: Poly(ADP-Ribose)polymerase inhibitors PBS: Phosphate-buffered saline PCB s: polychlorinated biphenyls PCNA: proliferating cell nuclear antigen PCR: polymerase chain reaction pcr: pathologic complete response PKB : Protein Kinase B PR: Progesterone RP-PCR: reverse transcriptase polymerization chain reaction RR: regional relapse

16 SES: Socioeconomic standards SISH: Silver-enhanced in situ hybridization T: primary tumor TDLU: Terminal duct-lobular unit Tis: Carcinoma in situ Tis (DCIS): Ductal carcinoma in situ. Tis (LCIS): Lobular carcinoma in situ. TNBC: triple-negative breast cancer Tis (Paget s): Paget s disease of the nipple NOT associated with invasive carcinoma and/or carcinoma in situ (DCIS and/or LCIS) in the underlying breast parenchyma. TRAIL: TNF-related apoptosis-inducing ligand UICC: International Union for Cancer Control Upa: urokinase plasminogen activator WHI: Women's Health Initiative WHO: World Health Organization yct: based on clinical or imaging ypt: T on pathologic findings

17 Introduction Intoduction Breast cancer in women is a major public health problem throughout the world. It is the most common cancer among women both in developed and developing countries. One out of ten of all new cancers diagnosed worldwide each year is a cancer of the female breast. It is also the principal cause of death from cancer among women globally. More than 1.38 million cases of breast cancer are diagnosed worldwide in2008, representing 10.9 % of all cancers. It is the second most common cancer now, after lung cancer, when ranked by cancer occurrence in both sexes. About 55% of the global burden is currently experienced in developed countries, but incidence rates are rapidly rising in developing countries (Ferlay et al., 2010). In the National Cancer Institute, breast cancer came as number one in ranking malignant tumors constituting 17.5% of total malignancies. Females showed a vast majority of 98.35%, while only 1.65% were males. Duct carcinoma formed a majority of 85.02%, 2.04% of which were intraduct carcinomas. Hormone receptors were positive in 57.8% of cases, while Her-2/neu was positive in 44.5% of cases. Lymph nodes were positive for metastasis in 69.5% of cases (Mokhtar et al., 2007) Breast cancer is a heterogeneous disease whose evolution is difficult to predict. Consequently, treatment is not as adapted as it should be. Gene expression studies have identified five molecularly distinct subtypes of breast cancer that have prognostic value across multiple treatments and can predict distinct clinical outcomes. These subtypes are termed hormone receptor(s) positive luminal A (luminal A), hormone receptor(s) positive luminal B, luminal HER2/neu, HER2-enriched (i.e, tumors that overexpress ERBB2- associated genes but donot express genes that define the luminal subtype) and basal-like (triple negative) (Carey et al., 2012). These subtypes are associated with differences in clinical outcome, HER2-enriched and basal-like subtypes are hormone receptor negative and have poorer prognosis with shorter survival times than other types (Sørlie et al., 2003). In contrast, the expression of hormone receptor(s) characterizes the luminal breast cancers, with luminal B tumors that having intermediate survival time & poorer outcomes than luminal A tumors that having the longest survival. Although some luminal B tumors 1

18 Introduction can be identified by their expression of HER2, the major biological distinction between luminala and B is the proliferation signature, including genes such as MKI67 (encoding Ki67), which has higher expression in luminal B tumors than in luminal A tumors. Thus, a distinction between luminal A and B tumors that is based on proliferation status among hormone receptor(s) positive luminal patients may be important to breast cancer biology and prognosis since luminal B tumors having a higher rate of tumor cell proliferation and poorer prognosis than luminal A tumors.thus luminal A and B breast cancers appear to be distinguished by the expression of estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 proteins (Cheang et al., 2009). The Nottingham modification of the Scarff-Bloom-Richardson (NSBR) histological grading system for invasive breast cancer has been recommended by the World Health Organization (WHO) (Tavassoli and Devilee, 2003). In the NSBR system, histological grading consists of three components: tubule formation, nuclear pleomorphism and mitotic count. Each of these are allocated a score of 1 3, and the final histological grade is determined according to the sum of the three components (grade 1: sum=3 5; grade 2: sum=6 7; and grade 3: sum=8 9). Patients with the luminal A subtype were less likely to have grade 3 tumors while patients with triple negative tumors had the greatest likelihood of having grade 3 (Hugh et al., 2009). The high cost of gene expression profiling has limited its incorporation into most randomized clinical trials, and therefore, immunohistochemistry-based surrogate assay is proposed to distinguish between various breast cancer subtypes with emphasis on the role of the Ki-67 labeling index as a clinically valuable biomarker for the luminal B subtype. In addition, association between this classification system and established prognostic factors of breast carcinoma will be explored (Cheang et al., 2009). 2

19 Aim of work Aim of Work Classification of breast duct carcinoma cases into corresponding molecular subtypes (luminal A, luminal B, luminal HER2/neu, HER2/neu-enriched and TNBC) by immunohistochemistry using ER, PR, HER2/neu and Ki-67. Correlation of breast cancer subtypes with prognostic clinicopathologic parameters (tumor size, tumor grade, lymph nodal status and tumor stage). Correlation of breast cancer subtypes with 2-year DFS 3

20 Review of literature Breast Histology The breast is a modified sweat gland composed of ducts, lobules, connective tissue, and fat, with most of the benign and malignant pathology arising in the duct and lobular network. The morpho-functional unit of the organ is the single gland, a complex branching structure that is composed of two major parts: the terminal duct-lobular unit (TDLU) and the large duct system (figure 1). Specifically, most breast cancer is thought to originate in the terminal ductal lobular unit. The TDLU is formed by the lobule and the terminal ductule and represents the secretory portion of the gland. It connects with the subsegmental duct, which in turn leads to the segmental duct and this leads to a collecting (lactiferous) duct, which empties into the nipple. A fusiform dilatation located beneath the nipple between the collecting and the segmental duct is known as the lactiferous sinus (Moinfar, 2007). The TDLU is recognized because of its distinctly lobular architecture; the presence of specialized hormone responsive connective tissue; and the absence of elastic fibers. The large ducts have a lesser amount of specialized stroma and are enveloped by well developed layer of elastic tissue (Cunha, 1994). The entire ductal-lobular epithelial system of the breast is covered by a specialized two cell type epithelial lining: the inner epithelium with secretory and absorptive functions (often simply called epithelium), and the outer myoepithelial cells. The entire glandular epithelial system rests on a continuous basement membrane (Monteagudo et al., 1990). Montgomery`s tubercles are areolar protuberances usually between 10 and 20 in number which become prominent during pregnancy; microscopically they are formed by a collecting duct associated with a sebaceous apparatus. The nipple has a very characteristic microscopic appearance. In addition to the large collecting ducts opening into the surface, it contains numerous sebaceous glands that open independently of hair follicles and a dense fibrous stroma in which erectile smooth muscle tissue is embedded. The nipple is rich in sensory nerve endings. Clear cells (CCs) without cytologic atypia may be present in the surface epithelium (Moinfar, 2007). These cells have been called epidermal CCs fit the features of pagetoid dyskeratosis, a selective 4