title: Molecular biomarkers for prediction of response to treatment and survival in triple negative breast cancer patients from Egypt.
abstract: BACKGROUND
  Triple negative breast cancer (TNBC) is an aggressive phenotype of breast cancer with reduced survival and poor prognosis. Increased VEGF-A, IGF-I, IGF-IR and TGF-β1 expressions were detected in breast cancer. However, little is known about their prognostic and predictive roles in TNBC.
  
  
  OBJECTIVE
  We assessed the possible prognostic and predictive values of VEGF-A, IGF-I/IGF-IR and TGF-β1 in TNBC cases by measuring their protein and mRNA expression in TNBC and non-TNBC cases.
  
  
  METHODS
  VEGF-A, IGF-I, IGF-IR and TGF-β1 RNA and their corresponding proteins were assessed in 43 TNBCs, 53 non-TNBCs and 30 normal breast tissues (NBT) by real time PCR (qPCR) and immunohistochemistry (IHC); respectively. Results were related to clinico-pathological factors, response to treatment and survival rates.
  
  
  RESULTS
  Increased mRNA expression of VEGF-A, IGF-I, and IGF-IR was significantly higher in TNBC (65.1%, 65.1%, and 72.1%) than non-TNBC (28.1%, 33.96% and 28.3%) and NBT (0.00%) (P<0.001). Similarly, TNBC patients were significantly associated with high expression of VEGF-A, IGF-I, and IGF-IR proteins (67.44%, 62.79% and 83.72%) than non-TNBC (20.75%, 35.86% and 20.75%) and NBT (0.00%) (P<0.001). Protein and RNA expression levels of all studied markers showed high concordance in all investigated patients (correlation coefficient exceeding 0.5 and 0.4, respectively). In the TNBC group, metastasis and poor response to treatment were significantly associated with VEGF-A (P<0.001, P=0.007, respectively), IGF-I (P<0.001, P<0.001, respectively), IGF-IR (P=0.001, P=0.015, respectively) and TGF-β1 (P<0.001, P=0.007, respectively) protein levels. Multivariate logistic regression showed that IGF-I was the only independent prognostic factor for reduced OS (P=0.034) and DFS (P=0.026) in the TNBC patients.
  
  
  CONCLUSIONS
  VEGF-A, IGF-I and IGF-IR play an important role in the development and progression of TNBC compared to non-TNBC. Therefore, they could be used as prognostic and predictive biomarkers as well as candidates for targeted therapy. However, only IGF-I can predict survival in those patients.
authors.affiliation: Molecular Pathology Unit, Pathology Department, National Cancer Institute, Cairo University, Egypt. Electronic address: chaya2000@hotmail.com.
authors.forename: Abeer
authors.initials: A
authors.lastname: Bahnassy
authors.affiliation: Department of Biochemistry, Faculty of Pharmacy, Misr University for Science and Technology, Egypt.
authors.forename: Marwa
authors.initials: M
authors.lastname: Mohanad
authors.affiliation: Department of Biochemistry, Faculty of Pharmacy, Cairo University, Egypt.
authors.forename: Manal F
authors.initials: MF
authors.lastname: Ismail
authors.affiliation: Department of Cancer Biology, National Cancer Institute, Cairo University, Egypt.
authors.forename: Sabry
authors.initials: S
authors.lastname: Shaarawy
authors.affiliation: Department of Medical Oncology, National Cancer Institute, Cairo University, Egypt.
authors.forename: Ahmed
authors.initials: A
authors.lastname: El-Bastawisy
authors.affiliation: Department of Cancer Biology, National Cancer Institute, Cairo University, Egypt.
authors.forename: Abdel-Rahman N
authors.initials: AR
authors.lastname: Zekri
mesh_terms: D000328:Adult; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D004534:Egypt; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007124:Immunoenzyme Techniques; D007334:Insulin-Like Growth Factor I / Q000235:genetics / Q000378:metabolism*; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D012333:RNA, Messenger / Q000235:genetics; D060888:Real-Time Polymerase Chain Reaction; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D017526:Receptor, IGF Type 1; D011960:Receptors, Estrogen / Q000378:metabolism; D011980:Receptors, Progesterone / Q000378:metabolism; D017451:Receptors, Somatomedin / Q000235:genetics / Q000378:metabolism*; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015996:Survival Rate; D053773:Transforming Growth Factor beta1 / Q000235:genetics / Q000378:metabolism*; D064726:Triple Negative Breast Neoplasms / Q000188:drug therapy / Q000378:metabolism* / Q000401:mortality* / Q000473:pathology; D042461:Vascular Endothelial Growth Factor A / Q000235:genetics / Q000378:metabolism*
chemical_list: D014408:Biomarkers, Tumor; D007334:Insulin-Like Growth Factor I; D012333:RNA, Messenger; D018719:Erb-b2 Receptor Tyrosine Kinases; D017526:Receptor, IGF Type 1; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; D017451:Receptors, Somatomedin; D053773:Transforming Growth Factor beta1; D042461:Vascular Endothelial Growth Factor A; C000597236:IGF1R protein, human; C467484:VEGFA protein, human
keywords: IGF-I/IGF-IR; Predictive marker; Prognostic factor; TGF-β1; Triple negative breast cancer; VEGF-A