Document Type : Original Research


1 Department of Anatomic Pathology, Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo National Hospital, Jakarta, Indonesia

2 Department of Medical Science, Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo National Hospital, Jakarta, Indonesia


Background & Objective: Invasive breast carcinoma of no special type (IBC-NST) is the most common type of breast cancer, which mainly causes axillary lymph-node metastasis (ALNM). Building on our previous research, we wanted to explore the optimal combination of AKT2, CD44v6, and MT1-MMP for the ALNM prediction.
Methods: The presence or absence of ALNM was used to separate 46 paraffin blocks containing IBC-NST primary tumors into two groups. Age, tumor grade, tumor size, receptor status (ER, PR, HER2, Ki-67, TOP2A), and test biomarker expression were evaluated. Biomarker expressions were assessed by IHC staining and categorized according to their respective cut-offs from our previous study, while other data were collected from archives. Data was gathered and analyzed using univariate, multivariate, and AUROC models.
Results: The expression of CD44v6 (OR: 12.77, 95% CI: 2.18-87.12, P=0.005) was identified as the independent variable for ALNM. Meanwhile, AKT2 expression (OR: 3.22, 95% CI: 0.36-22.41, P=0.237) and MT1-MMP expression (OR: 5.35, 95% CI: 0.83-34.54, P=0.078) did not demonstrate a statistically significant independent association in respect to ALNM. Combining AKT2 and MT1-MMP on CD44v6 increased overall accuracy by 4% compared to CD44v6 alone (AUROC 0.89 vs. 0.85).
Conclusion: The combined usage of AKT2, CD44v6, and MT1-MMP revealed no significant change compared to CD44v6 alone. Due to cost and practicality, we propose using CD44v6 as a biomarker predictor of ALNM in IBC-NST.


Main Subjects

  1. Estimated cancer incidence, mortality and prevalence in 2020: International Agency for Research on Cancer-WHO; 2020 [updated 2020/03/. Available from:
  2. Sharma GN, Dave R, Sanadya J, Sharma P, Sharma KK. Various types and management of breast cancer: an overview. J Adv Pharm Technol Res. 2010;1(2):109-26.
  3. Oluogun WA, Adedokun KA, Oyenike MA, Adeyeba OA. Histological classification, grading, staging, and prognostic indexing of female breast cancer in an African population: A 10-year retrospective study. Int J Health Sci (Qassim). 2019;13(4):3-9.
  4. Sun Y, Liang F, Cao W, Wang K, He J, Wang H, et al. Prognostic value of poorly differentiated clusters in invasive breast cancer. World J Surg Oncol. 2014;12. [DOI:10.1186/1477-7819-12-310] [PMID] [PMCID]
  5. Xu Q, Yuan J-P, Chen Y-Y, Zhang H-Y, Wang L-W, Xiong B. Prognostic Significance of the Tumor-Stromal Ratio in Invasive Breast Cancer and a Proposal of a New Ts-TNM Staging System. Journal of Oncology. 2020;2020(310):9050631. [DOI:10.1155/2020/9050631] [PMID] [PMCID]
  6. Chiang AC, Massagué J. Molecular Basis of Metastasis. N Engl J Med. 2008;359(26):2814-23. [DOI:10.1056/NEJMra0805239] [PMID] [PMCID]
  7. Zhang Y, Li J, Fan Y, Li X, Qiu J, Zhu M, et al. Risk factors for axillary lymph node metastases in clinical stage T1-2N0M0 breast cancer patients. Medicine. 2019;98(40). [PMID] [PMCID] [DOI:10.1097/MD.0000000000017481]
  8. Rustamadji P, Wiyarta E, Bethania KA, Kusmardi K. Potential of AKT2 expression as a predictor of lymph-node metastasis in invasive breast carcinoma of no special type. J Pathol Transl Med. 2021;0(0). [DOI:10.4132/jptm.2021.04.26] [PMID] [PMCID]
  9. Song M, Bode AM, Dong Z, Lee M-H. AKT as a Therapeutic Target for Cancer. Cancer Res. 2019;79(6):1019-31. [DOI:10.1158/0008-5472.CAN-18-2738] [PMID]
  10. Yang ZY, Di MY, Yuan JQ, Shen WX, Zheng DY, Chen JZ, et al. The prognostic value of phosphorylated Akt in breast cancer: a systematic review. Sci Rep. 2015;5:7758. [DOI:10.1038/srep07758] [PMID] [PMCID]
  11. Riggio M, Perrone MC, Polo ML, Rodriguez MJ, May M, Abba M, et al. AKT1 and AKT2 isoforms play distinct roles during breast cancer progression through the regulation of specific downstream proteins. Sci Rep. 2017;7:44244. [DOI:10.1038/srep44244] [PMID] [PMCID]
  12. Umeda T, Ishida M, Murata S, Mori T, Kawai Y, Itoi N, et al. Immunohistochemical analyses of CD44 variant isoforms in invasive micropapillary carcinoma of the breast: comparison with a concurrent conventional invasive carcinoma of no special type component. Breast Cancer. 2016;23(6):869-75. [DOI:10.1007/s12282-015-0653-4] [PMID]
  13. Chen C, Zhao S, Karnad A, Freeman JW. The biology and role of CD44 in cancer progression: therapeutic implications. Journal of Hematology & Oncology. 2018;11(1):64. [PMID] [PMCID] [DOI:10.1186/s13045-018-0605-5]
  14. Diaz LK, Zhou X, Wright ET, Cristofanilli M, Smith T, Yang Y, et al. CD44 expression is associated with increased survival in node-negative invasive breast carcinoma. Clin Cancer Res. 2005;11(9):3309-14. [DOI:10.1158/1078-0432.CCR-04-2184] [PMID]
  15. Ren L, Wang Y, Zhu L, Shen L, Zhang J, Wang J, et al. Optimization of a MT1-MMP-targeting Peptide and Its Application in Near-infrared Fluorescence Tumor Imaging. Scientific Reports. 2018;8(1):10334. [DOI:10.1038/s41598-018-28493-9] [PMID] [PMCID]
  16. Jiang WG, Davies G, Martin TA, Parr C, Watkins G, Mason MD, et al. expression of membrane type-1 matrix metalloproteinase, MT1-MMP in human breast cancer and its impact on invasiveness of breast cancer cells. Int J Mol Med. 2006;17(4):583-90. [DOI:10.3892/ijmm.17.4.583] [PMID]
  17. Rustamadji PA-O, Wiyarta EA-O, Bethania KA-O. CD44 Variant Exon 6 Isoform Expression as a Potential Predictor of Lymph Node Metastasis in Invasive Breast Carcinoma of No Special Type. (2090-3170 (Print)).
  18. Rickham PP. Human Experimentation. Code of Ethics of The World Medical Association. Declaration of Helsinki. Br Med J. 1964;2(5402): 177. [DOI:10.1136/bmj.2.5402.177] [PMID] [PMCID]
  19. Kusmardi K, Wiyarta E, Estuningtyas A, Sahar N, Midoen YH, Tedjo A. Potential of Phaleria macrocarpa Leaves Ethanol Extract to Upregulate the Expression of Caspase-3 in Mouse Distal Colon after Dextran Sodium Sulphate Induction. Pharmacognosy Journal. 2021;13:23-9. [DOI:10.5530/pj.2021.13.4]
  20. Kusmardi K, Wiyarta E, Estuningtyas A, Sahar N, Midoen YH, Tedjo A, et al. Potential Inhibition by Phaleria macrocarpa Leaves Ethanol Extract on Ki-67 Expression in Distal Colon Mouse. Pharmacognosy Journal. 2021;13:443-9. [DOI:10.5530/pj.2021.13.56]
  21. Kusmardi K, Wiyarta EA-O, Rusdi NA-O, Maulana AM, Estuningtyas A, Sunaryo H. The potential of lunasin extract for the prevention of breast cancer progression by upregulating E-Cadherin and inhibiting ICAM-1. (2046-1402 (Electronic)).
  22. Rustamadji P, Wiyarta E, Anggreani I. Exploring the Expression of Survivin on Neoadjuvant Chemotherapy in Invasive Breast Carcinoma. Open Access Macedonian Journal of Medical Sciences. 2022;10(B):1440-5. [DOI:10.3889/oamjms.2022.9940]
  23. Hashimoto K, Tsuda H, Koizumi F, Shimizu C, Yonemori K, Ando M, et al. Activated PI3K/AKT and MAPK pathways are potential good prognostic markers in node-positive, triple-negative breast cancer. Annals of Oncology. 2014;25(10):1973-9. [DOI:10.1093/annonc/mdu247] [PMID]
  24. O'Brien J, Hayder H, Peng C. Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins. JoVE. 2016(117):e54719. [DOI:10.3791/54719] [PMID] [PMCID]
  25. Choudhury KR, Yagle KJ, Swanson PE, Krohn KA, Rajendran JG. A Robust Automated Measure of Average Antibody Staining in Immunohistochemistry Images. J Histochem Cytochem. 2010;58(2):95-107. [PMID] [PMCID] [DOI:10.1369/jhc.2009.953554]
  26. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 2016;15(2): 155-63. [DOI:10.1016/j.jcm.2016.02.012] [PMID] [PMCID]
  27. Wiyarta E, Kusmardi K, Tedjo A, Sunaryo H. In Vitro and In Vivo Study of Pandanus conoideus Oil Extract in the Maturation of Mouse Peritoneal Macrophages. Open Access Macedonian Journal of Medical Sciences. 2022;10(A):419-25. [DOI:10.3889/oamjms.2022.8005]
  28. Ruopp MD, Perkins NJ, Whitcomb BW, Schisterman EF. Youden Index and Optimal Cut-Point Estimated from Observations Affected by a Lower Limit of Detection. Biom J. 2008;50(3): 419-30. [DOI:10.1002/bimj.200710415] [PMID] [PMCID]
  29. Kallner A. Formulas. In: Kallner A, editor. Laboratory Statistics (Second Edition): Elsevier; 2018. p. 1-140. [DOI:10.1016/B978-0-12-814348-3.00001-0]
  30. Peng C-YJ, Lee KL, Ingersoll GM. An Introduction to Logistic Regression Analysis and Reporting. The Journal of Educational Research. 2002;96(1):3-14. [DOI:10.1080/00220670209598786]
  31. Pepe MS, Feng Z, Janes H, Bossuyt PM, Potter JD. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst. 2008;100(20):1432-8. [DOI:10.1093/jnci/djn326] [PMID] [PMCID]
  32. Seshan VE, Gönen M, Begg CB. Comparing ROC curves derived from regression models. Stat Med. 2013;32(9):1483-93. [DOI:10.1002/sim.5648] [PMID] [PMCID]
  33. Zou KH, O'Malley AJ, Mauri L. Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models. Circulation. 2007;115(5):654-7. [PMID] [DOI:10.1161/CIRCULATIONAHA.105.594929]
  34. Hu S, Cao M, He Y, Zhang G, Liu Y, Du Y, et al. CD44v6 Targeted by miR-193b-5p in the Coding Region Modulates the Migration and Invasion of Breast Cancer Cells. Journal of Cancer. 2020; 11(1):260-71. [DOI:10.7150/jca.35067] [PMID] [PMCID]
  35. Louderbough JMV, Schroeder JA. Understanding the Dual Nature of CD44 in Breast Cancer Progression. Molecular Cancer Research. 2011;9 (12):1573. [DOI:10.1158/1541-7786.MCR-11-0156] [PMID]
  36. Martin TA, Harrison G, Mansel RE, Jiang WG. The role of the CD44/ezrin complex in cancer metastasis. Crit Rev Oncol Hematol. 2003;46(2): 165-86. [DOI:10.1016/S1040-8428(02)00172-5]
  37. Kaufmann M, Heider KH, Sinn HP, von Minckwitz G, Ponta H, Herrlich P. CD44 variant exon epitopes in primary breast cancer and length of survival. Lancet. 1995;345(8950):615-9. [DOI:10.1016/S0140-6736(95)90521-9]
  38. Günthert U, Hofmann M, Rudy W, Reber S, Zöller M, Haussmann I, et al. A new variant of glycoprotein CD44 confers metastatic potential to rat carcinoma cells. Cell. 1991;65(1):13-24. [DOI:10.1016/0092-8674(91)90403-L]
  39. Lyzak JS, Yaremko ML, Recant W, Baunoch DA, Joseph L. Role of CD44 in nonpalpable T1a and T1b breast cancer. Human Pathology. 1997;28(7):772-8. [DOI:10.1016/S0046-8177(97)90148-9]
  40. Bànkfalvi A, Terpe HJ, Breukelmann D, Bier B, Rempe D, Pschadka G, et al. Gains and losses of CD44 expression during breast carcinogenesis and tumour progression. Histopathology. 1998;33 (2):107-16. [PMID] [DOI:10.1046/j.1365-2559.1998.00472.x]
  41. Hinz N, Jücker M. Distinct functions of AKT isoforms in breast cancer: a comprehensive review. Cell Commun Signal. 2019;17. [DOI:10.1186/s12964-019-0450-3] [PMID] [PMCID]
  42. Boxer RB, Stairs DB, Dugan KD, Notarfrancesco KL, Portocarrero CP, Keister BA, et al. Isoform-specific requirement for Akt1 in the developmental regulation of cellular metabolism during lactation. Cell Metab. 2006;4(6):475-90. [DOI:10.1016/j.cmet.2006.10.011] [PMID]
  43. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406 (6797):747-52. [DOI:10.1038/35021093] [PMID]
  44. Rädler PD, Wehde BL, Triplett AA, Shrestha H, Shepherd JH, Pfefferle AD, et al. Highly metastatic claudin-low mammary cancers can originate from luminal epithelial cells. Nature Communications. 2021;12(1):3742. [PMID] [PMCID] [DOI:10.1038/s41467-021-23957-5]
  45. Lodillinsky C, Infante E, Guichard A, Chaligne R, Fuhrmann L, Cyrta J, et al. p63/MT1-MMP axis is required for in situ to invasive transition in basal-like breast cancer. Oncogene. 2015;35 [DOI:10.1038/onc.2015.87] [PMID]