The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients and Study Design
2.2. Immunohistochemical Staining and PAM50 Testing of Tumor Samples
2.3. Clinical Characteristics
2.4. Statistical Analysis
3. Results
3.1. PAM50 Results
3.2. Comparison of PAM50 and Immunohistochemical Staining Results
4. Discussion
- ER and/or PR below 35% for accurate breast cancer intrinsic subtyping.
- Those samples where the tumor response to a given therapy fails (e.g., residual disease after or progression on neoadjuvant therapy); testing these would be a rational approach.
- Grade 1 tumors that are ≥pT2.
- Grade 3 tumors that are ≤pT1c.
- An intermediate category with other tests to provide additional support for therapeutic decisions.
- An indication for extended hormone therapy after 5 years of hormone therapy.
Limitations of the Study
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- World Health Organization. Breast Cancer. Available online: https://www.who.int/cancer/prevention/diagnosis-screening/breast-cancer/en/ (accessed on 10 May 2023).
- American Cancer Society. Breast Cancer Facts & Figures 2021–2022. Available online: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/breast-cancer-facts-and-figures/breast-cancer-facts-and-figures-2021-2022.pdf (accessed on 10 May 2023).
- Perou, C.M.; Sorlie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; Rees, C.A.; Pollack, J.R.; Ross, D.T.; Johnsen, H.; Akslen, L.A.; et al. Molecular portraits of human breast tumours. Nature 2000, 406, 747–752. [Google Scholar] [CrossRef]
- Sorlie, T.; Tibshirani, R.; Parker, J.; Hastie, T.; Marron, J.S.; Nobel, A.; Deng, S.; Johnsen, H.; Pesich, R.; Geisler, S.; et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. USA 2003, 100, 8418–8423. [Google Scholar] [CrossRef] [PubMed]
- Osborne, C.K. Heterogeneity in hormone receptor status in primary and metastatic breast cancer. Semin. Oncol. 1985, 12, 317–326. [Google Scholar] [PubMed]
- Coates, A.S.; Winer, E.P.; Goldhirsch, A.; Gelber, R.D.; Gnant, M.; Piccart-Gebhart, M.; Thurlimann, B.; Senn, H.J.; Members, P. Tailoring therapies—Improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann. Oncol. 2015, 26, 1533–1546. [Google Scholar] [CrossRef]
- Harbeck, N.; Thomssen, C.; Gnant, M. St. Gallen 2013: Brief preliminary summary of the consensus discussion. Breast Care 2013, 8, 102–109. [Google Scholar] [CrossRef] [PubMed]
- Gnant, M.; Thomssen, C.; Harbeck, N. St. Gallen/Vienna 2015: A Brief Summary of the Consensus Discussion. Breast Care 2015, 10, 124–130. [Google Scholar] [CrossRef]
- Goldhirsch, A.; Winer, E.P.; Coates, A.S.; Gelber, R.D.; Piccart-Gebhart, M.; Thurlimann, B.; Senn, H.J.; Panel, M. Personalizing the treatment of women with early breast cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann. Oncol. 2013, 24, 2206–2223. [Google Scholar] [CrossRef]
- Prat, A.; Parker, J.S.; Karginova, O.; Fan, C.; Livasy, C.; Herschkowitz, J.I.; He, X.; Perou, C.M. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 2010, 12, R68. [Google Scholar] [CrossRef]
- Paik, S.; Shak, S.; Tang, G.; Kim, C.; Baker, J.; Cronin, M.; Baehner, F.L.; Walker, M.G.; Watson, D.; Park, T.; et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 2004, 351, 2817–2826. [Google Scholar] [CrossRef]
- Van ‘t Veer, L.J.; Dai, H.; van de Vijver, M.J.; He, Y.D.; Hart, A.A.; Mao, M.; Peterse, H.L.; van der Kooy, K.; Marton, M.J.; Witteveen, A.T.; et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415, 530–536. [Google Scholar] [CrossRef]
- Nielsen, T.O.; Parker, J.S.; Leung, S.; Voduc, D.; Ebbert, M.; Vickery, T.; Davies, S.R.; Snider, J.; Stijleman, I.J.; Reed, J.; et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin. Cancer Res. 2010, 16, 5222–5232. [Google Scholar] [CrossRef] [PubMed]
- Prat, A.; Parker, J.S.; Fan, C.; Perou, C.M. PAM50 assay and the three-gene model for identifying the major and clinically relevant molecular subtypes of breast cancer. Breast Cancer Res. Treat. 2012, 135, 301–306. [Google Scholar] [CrossRef] [PubMed]
- Chia, S.K.; Bramwell, V.H.; Tu, D.; Shepherd, L.E.; Jiang, S.; Vickery, T.; Mardis, E.; Leung, S.; Ung, K.; Pritchard, K.I.; et al. A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin. Cancer Res. 2012, 18, 4465–4472. [Google Scholar] [CrossRef] [PubMed]
- Wallden, B.; Storhoff, J.; Nielsen, T.; Dowidar, N.; Schaper, C.; Ferree, S.; Liu, S.; Leung, S.; Geiss, G.; Snider, J.; et al. Development and verification of the PAM50-based Prosigna breast cancer gene signature assay. BMC Med. Genom. 2015, 8, 54. [Google Scholar] [CrossRef]
- Gnant, M.; Filipits, M.; Greil, R.; Stoeger, H.; Rudas, M.; Bago-Horvath, Z.; Mlineritsch, B.; Kwasny, W.; Knauer, M.; Singer, C.; et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: Using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann. Oncol. 2014, 25, 339–345. [Google Scholar] [CrossRef] [PubMed]
- Martin, M.; Gonzalez-Rivera, M.; Morales, S.; de la Haba-Rodriguez, J.; Gonzalez-Cortijo, L.; Manso, L.; Albanell, J.; Gonzalez-Martin, A.; Gonzalez, S.; Arcusa, A.; et al. Prospective study of the impact of the Prosigna assay on adjuvant clinical decision-making in unselected patients with estrogen receptor positive, human epidermal growth factor receptor negative, node negative early-stage breast cancer. Curr. Med. Res. Opin. 2015, 31, 1129–1137. [Google Scholar] [CrossRef]
- Pascual, T.; Fernandez-Martinez, A.; Tanioka, M.; Dieci, M.V.; Pernas, S.; Gavila, J.; Guarnieri, V.; Cortes, J.; Villagrasa, P.; Chic, N.; et al. Independent Validation of the PAM50-Based Chemo-Endocrine Score (CES) in Hormone Receptor-Positive HER2-Positive Breast Cancer Treated with Neoadjuvant Anti-HER2-Based Therapy. Clin. Cancer Res. 2021, 27, 3116–3125. [Google Scholar] [CrossRef]
- Sestak, I.; Cuzick, J.; Dowsett, M.; Lopez-Knowles, E.; Filipits, M.; Dubsky, P.; Cowens, J.W.; Ferree, S.; Schaper, C.; Fesl, C.; et al. Prediction of late distant recurrence after 5 years of endocrine treatment: A combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J. Clin. Oncol. 2015, 33, 916–922. [Google Scholar] [CrossRef] [PubMed]
- Zhao, S.G.; Chang, S.L.; Erho, N.; Yu, M.; Lehrer, J.; Alshalalfa, M.; Speers, C.; Cooperberg, M.R.; Kim, W.; Ryan, C.J.; et al. Associations of Luminal and Basal Subtyping of Prostate Cancer with Prognosis and Response to Androgen Deprivation Therapy. JAMA Oncol. 2017, 3, 1663–1672. [Google Scholar] [CrossRef]
- Yoon, J.; Kim, M.; Posadas, E.M.; Freedland, S.J.; Liu, Y.; Davicioni, E.; Den, R.B.; Trock, B.J.; Karnes, R.J.; Klein, E.A.; et al. A comparative study of PCS and PAM50 prostate cancer classification schemes. Prostate Cancer Prostatic Dis. 2021, 24, 733–742. [Google Scholar] [CrossRef]
- Coleman, I.M.; DeSarkar, N.; Morrissey, C.; Xin, L.; Roudier, M.P.; Sayar, E.; Li, D.; Corey, E.; Haffner, M.C.; Nelson, P.S. Therapeutic Implications for Intrinsic Phenotype Classification of Metastatic Castration-Resistant Prostate Cancer. Clin. Cancer Res. 2022, 28, 3127–3140. [Google Scholar] [CrossRef] [PubMed]
- Jumppanen, M.; Gruvberger-Saal, S.; Kauraniemi, P.; Tanner, M.; Bendahl, P.O.; Lundin, M.; Krogh, M.; Kataja, P.; Borg, A.; Ferno, M.; et al. Basal-like phenotype is not associated with patient survival in estrogen-receptor-negative breast cancers. Breast Cancer Res. 2007, 9, R16. [Google Scholar] [CrossRef]
- Cserni, G.; Francz, M.; Jaray, B.; Kalman, E.; Kovacs, I.; Krenacs, T.; Toth, E.; Udvarhelyi, N.; Vass, L.; Voros, A.; et al. Pathological diagnosis, work-up and reporting of breast cancer. Recommendations from the 4th Breast Cancer Consensus Conference. Magy. Onkol. 2020, 64, 301–328. [Google Scholar] [PubMed]
- Wolff, A.C.; Hammond, M.E.; Hicks, D.G.; Dowsett, M.; McShane, L.M.; Allison, K.H.; Allred, D.C.; Bartlett, J.M.; Bilous, M.; Fitzgibbons, P.; et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J. Clin. Oncol. 2013, 31, 3997–4013. [Google Scholar] [CrossRef]
- Allison, K.H.; Hammond, M.E.H.; Dowsett, M.; McKernin, S.E.; Carey, L.A.; Fitzgibbons, P.L.; Hayes, D.F.; Lakhani, S.R.; Chavez-MacGregor, M.; Perlmutter, J.; et al. Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update. J. Clin. Oncol. 2020, 38, 1346–1366. [Google Scholar] [CrossRef] [PubMed]
- Nielsen, T.O.; Leung, S.C.Y.; Rimm, D.L.; Dodson, A.; Acs, B.; Badve, S.; Denkert, C.; Ellis, M.J.; Fineberg, S.; Flowers, M.; et al. Assessment of Ki67 in Breast Cancer: Updated Recommendations from the International Ki67 in Breast Cancer Working Group. J. Natl. Cancer Inst. 2021, 113, 808–819. [Google Scholar] [CrossRef]
- Wolff, A.C.; Hammond, M.E.H.; Allison, K.H.; Harvey, B.E.; Mangu, P.B.; Bartlett, J.M.S.; Bilous, M.; Ellis, I.O.; Fitzgibbons, P.; Hanna, W.; et al. Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Focused Update. J. Clin. Oncol. 2018, 36, 2105–2122. [Google Scholar] [CrossRef]
- Laenkholm, A.V.; Jensen, M.B.; Eriksen, J.O.; Buckingham, W.; Ferree, S.; Nielsen, T.O.; Ejlertsen, B. The ability of PAM50 risk of recurrence score to predict 10-year distant recurrence in hormone receptor-positive postmenopausal women with special histological subtypes. Acta Oncol. 2018, 57, 44–50. [Google Scholar] [CrossRef]
- Baskota, S.U.; Dabbs, D.J.; Clark, B.Z.; Bhargava, R. Prosigna(R) breast cancer assay: Histopathologic correlation, development, and assessment of size, nodal status, Ki-67 (SiNK) index for breast cancer prognosis. Mod. Pathol. 2021, 34, 70–76. [Google Scholar] [CrossRef]
- Nielsen, T.; Wallden, B.; Schaper, C.; Ferree, S.; Liu, S.; Gao, D.; Barry, G.; Dowidar, N.; Maysuria, M.; Storhoff, J. Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer 2014, 14, 177. [Google Scholar] [CrossRef]
- Ohnstad, H.O.; Borgen, E.; Falk, R.S.; Lien, T.G.; Aaserud, M.; Sveli, M.A.T.; Kyte, J.A.; Kristensen, V.N.; Geitvik, G.A.; Schlichting, E.; et al. Prognostic value of PAM50 and risk of recurrence score in patients with early-stage breast cancer with long-term follow-up. Breast Cancer Res. 2017, 19, 120. [Google Scholar] [CrossRef]
- Hortobagyi, G.N.; Connolly, J.L.; D’Orsi, C.J.; Edge, S.B.; Mittendorf, E.A.; Rugo, H.S.; Solin, L.J.; Weaver, D.L.; Winchester, D.J.; Guiliano, A. Breast. In AJCC Cancer Staging Manual, 8th ed.; Amin, M.B., Edge, S., Greene, F., Byrd, D.R., Brookland, R.K., Washington, M.K., Gershenwald, J.E., Compton, C.C., Hess, K.R., Sullivan, D.C., et al., Eds.; Springer International Publishing: Chicago, IL, USA, 2017; pp. 589–636. [Google Scholar]
- Horvath, Z.; Boer, K.; Dank, M.; Kahan, Z.; Kocsis, J.; Kover, E.; Mahr, K.; Piko, B.; Rubovszky, G. Systemic treatment of breast cancer: Professional guideline. Magy. Onkol. 2020, 64, 348–368. [Google Scholar]
- Cardoso, F.; Kyriakides, S.; Ohno, S.; Penault-Llorca, F.; Poortmans, P.; Rubio, I.T.; Zackrisson, S.; Senkus, E.; ESMO Guidelines Committee. Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-updagger. Ann. Oncol. 2019, 30, 1194–1220. [Google Scholar] [CrossRef]
- Gennari, A.; Andre, F.; Barrios, C.H.; Cortes, J.; de Azambuja, E.; DeMichele, A.; Dent, R.; Fenlon, D.; Gligorov, J.; Hurvitz, S.A.; et al. ESMO Clinical Practice Guideline for the diagnosis, staging and treatment of patients with metastatic breast cancer. Ann. Oncol. 2021, 32, 1475–1495. [Google Scholar] [CrossRef]
- Eisenhauer, E.A.; Therasse, P.; Bogaerts, J.; Schwartz, L.H.; Sargent, D.; Ford, R.; Dancey, J.; Arbuck, S.; Gwyther, S.; Mooney, M.; et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur. J. Cancer 2009, 45, 228–247. [Google Scholar] [CrossRef] [PubMed]
- Dix-Peek, T.; Phakathi, B.P.; van den Berg, E.J.; Dickens, C.; Augustine, T.N.; Cubasch, H.; Neugut, A.I.; Jacobson, J.S.; Joffe, M.; Ruff, P.; et al. Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer. Breast Cancer Res. Treat. 2023, 199, 1–12. [Google Scholar] [CrossRef]
- Bastien, R.R.; Rodriguez-Lescure, A.; Ebbert, M.T.; Prat, A.; Munarriz, B.; Rowe, L.; Miller, P.; Ruiz-Borrego, M.; Anderson, D.; Lyons, B.; et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med. Genom. 2012, 5, 44. [Google Scholar] [CrossRef]
- Erber, R.; Angeloni, M.; Stohr, R.; Lux, M.P.; Ulbrich-Gebauer, D.; Pelz, E.; Bankfalvi, A.; Schmid, K.W.; Walter, R.F.H.; Vetter, M.; et al. Molecular Subtyping of Invasive Breast Cancer Using a PAM50-Based Multigene Expression Test-Comparison with Molecular-like Subtyping by Tumor Grade/Immunohistochemistry and Influence on Oncologist’s Decision on Systemic Therapy in a Real-World Setting. Int. J. Mol. Sci. 2022, 23, 8716. [Google Scholar] [CrossRef]
- Guiu, S.; Michiels, S.; Andre, F.; Cortes, J.; Denkert, C.; Di Leo, A.; Hennessy, B.T.; Sorlie, T.; Sotiriou, C.; Turner, N.; et al. Molecular subclasses of breast cancer: How do we define them? The IMPAKT 2012 Working Group Statement. Ann. Oncol. 2012, 23, 2997–3006. [Google Scholar] [CrossRef] [PubMed]
- Ward, S.; Scope, A.; Rafia, R.; Pandor, A.; Harnan, S.; Evans, P.; Wyld, L. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: A systematic review and cost-effectiveness analysis. Health Technol. Assess. 2013, 17, 1–302. [Google Scholar] [CrossRef] [PubMed]
- Falato, C.; Schettini, F.; Pascual, T.; Braso-Maristany, F.; Prat, A. Clinical implications of the intrinsic molecular subtypes in hormone receptor-positive and HER2-negative metastatic breast cancer. Cancer Treat. Rev. 2023, 112, 102496. [Google Scholar] [CrossRef] [PubMed]
- Madaras, L.; Balint, N.; Gyorffy, B.; Tokes, A.M.; Barshack, I.; Yosepovich, A.; Friedman, E.; Paluch-Shimon, S.; Zippel, D.; Baghy, K.; et al. BRCA Mutation-Related and Claudin-Low Breast Cancer: Blood Relatives or Stepsisters. Pathobiology 2016, 83, 1–12. [Google Scholar] [CrossRef] [PubMed]
- Iwamoto, T.; Booser, D.; Valero, V.; Murray, J.L.; Koenig, K.; Esteva, F.J.; Ueno, N.T.; Zhang, J.; Shi, W.; Qi, Y.; et al. Estrogen receptor (ER) mRNA and ER-related gene expression in breast cancers that are 1% to 10% ER-positive by immunohistochemistry. J. Clin. Oncol. 2012, 30, 729–734. [Google Scholar] [CrossRef] [PubMed]
- Kjällquist, U.; Acs, B.; Margolin, S.; Karlsson, E.; Kessler, L.E.; Garcia Hernandez, S.; Ekholm, M.; Lundgren, C.; Olsson, E.; Lindman, H.; et al. Real World Evaluation of the Prosigna/PAM50 Test in a Node-Negative Postmenopausal Swedish Population: A Multicenter Study. Cancers 2022, 14, 2615. [Google Scholar] [CrossRef]
- Laenkholm, A.V.; Jensen, M.B.; Eriksen, J.O.; Rasmussen, B.B.; Knoop, A.S.; Buckingham, W.; Ferree, S.; Schaper, C.; Nielsen, T.O.; Haffner, T.; et al. PAM50 Risk of Recurrence Score Predicts 10-Year Distant Recurrence in a Comprehensive Danish Cohort of Postmenopausal Women Allocated to 5 Years of Endocrine Therapy for Hormone Receptor-Positive Early Breast Cancer. J. Clin. Oncol. 2018, 36, 735–740. [Google Scholar] [CrossRef]
- Hequet, D.; Callens, C.; Gentien, D.; Albaud, B.; Mouret-Reynier, M.A.; Dubot, C.; Cottu, P.; Huchon, C.; Zilberman, S.; Berseneff, H.; et al. Prospective, multicenter French study evaluating the clinical impact of the Breast Cancer Intrinsic Subtype-Prosigna(R) Test in the management of early-stage breast cancers. PLoS ONE 2017, 12, e0185753. [Google Scholar] [CrossRef]
- Zidan, J.; Leviov, M.; Kuchuk, I.; Bar-Sela, G.; Shai, A.; Kazarin, O.; Suheil, N. The use of clinical impact of the breast cancer intrinsic subtype-Prosigna assay for adjuvant treatment decision in early breast cancer with hormone receptor positive and HER-2 negative Middle East women. J. Clin. Oncol. 2022, 40, e12527. [Google Scholar] [CrossRef]
Clinical Characteristics | Study Participants (n = 42) |
---|---|
Age (years) | 56.78 ± 14.32 |
Sample obtained from | |
| 37 (88.10%) |
| 5 (11.90%) |
Type of specimen | |
| 10 (23.81%) |
| 32 (76.19%) |
Histology of the tumor | |
| 31 (73.81%) |
| 5 (11.90%) |
| 1 (2.38%) |
| 1 (2.38%) |
| 1 (2.38%) |
| 3 (7.14%) |
Nottingham histologic grade 1 | |
| 7 (18.2%) |
| 19 (51.35%) |
| 11 (29.72%) |
TNM staging [34] 1 | |
| 18:13:8:1 (42.86%:30.95%:19.05%:2.38%) |
| 19:17:3:1 (45.24%:40.48%:7.14%:2.38%) |
| 37:2 (88.10%:4.76%) |
Size of the tumor (mm) | 27.00 ± 22.82 |
Surgical procedures | |
| 18 (42.86%) |
| 19 (45.24%) |
| 15 (35.71%) |
| 19 (45.24%) 6 (14.29%) |
Neoadjuvant therapy | 12 (28.57%) |
Adjuvant therapy | |
| 30 (71.43%) |
| 26 (61.90) |
| 18 (42.86%) |
| 9 (21.43%) |
Median progression-free survival (months) | 55.03 (95% CI: 55.03–NA) 2 |
PAM50 Subtypes | Min. | 25% | Median | 75% | Max. | Mean | SD |
---|---|---|---|---|---|---|---|
ROR score | |||||||
Luminal A (n = 18) | 1 | 17 | 38.33 | 42 | 47 | 30.36 | 14.02 |
Luminal B (n = 10) | 54 | 66.75 | 73 | 81.33 | 86 | 72.80 | 10.24 |
HER2-positive (n = 8) | 16 | 53.38 | 66 | 69 | 80.67 | 59.15 | 20.33 |
Basal-like (n = 6) | 9 | 18.25 | 33 | 59 | 65 | 36.83 | 24.38 |
10-year recurrence risk score | |||||||
Luminal A (n = 18) | 3 | 4 | 7 | 8 | 43 | 10.20 | 10.31 |
Luminal B (n = 10) | 12 | 28.17 | 31.84 | 34.5 | 49 | 31.33 | 10.86 |
HER2-positive (n = 8) | 4 | 15.75 | 20.5 | 26.25 | 43 | 21.08 | 11.96 |
Basal-like (n = 6) | 4 | 10.25 | 14 | 25.25 | 43 | 18.83 | 14.36 |
Parameter | HR | 95% CI | p-Value |
---|---|---|---|
PAM50 subtypes | |||
| 5.7420 | 0.5963–55.2900 | 0.1304 |
| 20.7140 | 1.8078–237.3400 | 0.0149 |
| 31.8900 | 2.2086–460.4600 | 0.0110 |
| 3.6076 | 0.5861–22.2060 | 0.1660 |
| 5.5541 | 0.6709–45.9790 | 0.1120 |
| 1.5395 | 0.2385–9.9378 | 0.6502 |
ROR score | 1.0181 | 0.9878–1.0490 | 0.2450 |
ROR risk categories | |||
| 0.6004 | 0.0369–9.7590 | 0.7200 |
| 4.0626 | 0.4984–33.1190 | 0.1900 |
| 6.7661 | 0.8357–54.7800 | 0.0732 |
10-year recurrence risk score | 1.0529 | 1.0080–1.1000 | 0.0201 |
PAM50 Subtypes | Min. | 25% | Median | 75% | Max. | Mean | SD |
---|---|---|---|---|---|---|---|
Estrogen receptor positivity (%) | |||||||
Luminal A (n = 18) | 10 | 95.75 | 100 | 100 | 100 | 92.39 | 21.26 |
Luminal B (n = 10) | 1 | 92 | 99.5 | 100 | 100 | 87.80 | 30.76 |
HER2-positive (n = 8) | 0 | 0 | 0 | 15 | 90 | 18.75 | 35.63 |
Basal-like (n = 6) | 0 | 0 | 0 | 22.5 | 90 | 20.00 | 36.33 |
Progesterone receptor positivity (%) | |||||||
Luminal A (n = 18) | 0 | 36.25 | 82.5 | 93.75 | 100 | 62.83 | 38.38 |
Luminal B (n = 10) | 0 | 1 | 10.5 | 50 | 100 | 30.10 | 40.75 |
HER2-positive (n = 8) | 0 | 0 | 0 | 0 | 40 | 5.00 | 14.14 |
Basal-like (n = 6) | 0 | 0 | 35 | 77.5 | 95 | 40.83 | 45.43 |
Ki-67 proliferation marker ratio (%) | |||||||
Luminal A (n = 18) | 1 | 5 | 10 | 15 | 25 | 10.00 | 7.00 |
Luminal B (n = 10) | 10 | 15 | 17.5 | 20 | 40 | 19.50 | 9.26 |
HER2-positive (n = 8) | 10 | 25 | 25 | 30 | 80 | 34.00 | 26.79 |
Basal-like (n = 6) | 30 | 60 | 70 | 80 | 80 | 64.00 | 20.74 |
PAM50 Subtypes | 0 | 1+ | 2+ | 3+ |
---|---|---|---|---|
Luminal A (n = 18) | 11 | 2 | 5 | 0 |
Luminal B (n = 10) | 5 | 2 | 3 | 0 |
HER2-positive (n = 8) | 0 | 1 | 2 | 5 |
Basal-like (n = 6) | 2 | 0 | 0 | 4 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dank, M.; Mühl, D.; Pölhös, A.; Csanda, R.; Herold, M.; Kovacs, A.K.; Madaras, L.; Kulka, J.; Palhazy, T.; Tokes, A.-M.; et al. The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience. Genes 2023, 14, 1708. https://doi.org/10.3390/genes14091708
Dank M, Mühl D, Pölhös A, Csanda R, Herold M, Kovacs AK, Madaras L, Kulka J, Palhazy T, Tokes A-M, et al. The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience. Genes. 2023; 14(9):1708. https://doi.org/10.3390/genes14091708
Chicago/Turabian StyleDank, Magdolna, Dorottya Mühl, Annamária Pölhös, Renata Csanda, Magdolna Herold, Attila Kristof Kovacs, Lilla Madaras, Janina Kulka, Timea Palhazy, Anna-Maria Tokes, and et al. 2023. "The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience" Genes 14, no. 9: 1708. https://doi.org/10.3390/genes14091708
APA StyleDank, M., Mühl, D., Pölhös, A., Csanda, R., Herold, M., Kovacs, A. K., Madaras, L., Kulka, J., Palhazy, T., Tokes, A. -M., Toth, M., Ujhelyi, M., Szasz, A. M., & Herold, Z. (2023). The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience. Genes, 14(9), 1708. https://doi.org/10.3390/genes14091708