Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach
Abstract
1. Introduction
2. Epidemiology
3. Risk Factors
4. Pathological Characteristics and Tumor Behavior
4.1. Pathology of BC in Adolescent and Young Adult Patients
4.2. Molecular Signatures of Early-Onset BC
5. Screening and Diagnostics
6. Therapy
7. The Advanced Approach by Predictive, Preventive, and Personalized Medicine in Overall BC Management
7.1. Risk Assessment: Phenotyping and Genotyping
7.1.1. Deficient Thermoregulation and Feeling Inappropriately Cold
7.1.2. Persistently Cold Extremities, Altered Endothelin-1 Blood Patterns, and Systemic Hypoxic Effects
7.1.3. Reduced Thirst and Body Dehydration
7.1.4. Altered Circadian and Sleep Patterns
7.2. Multi-Omic Diagnostic Approach
7.3. BC Prediction, Machine Learning, and Artificial Intelligence
8. Conclusions and Future Directions
Funding
Conflicts of Interest
References
- Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed]
- Leclère, B.; Molinié, F.; Trétarre, B.; Stracci, F.; Daubisse-Marliac, L.; Colonna, M.; GRELL Working Group. Trends in incidence of breast cancer among women under 40 in seven European countries: A GRELL cooperative study. Cancer Epidemiol. 2013, 37, 544–549. [Google Scholar] [CrossRef] [PubMed]
- Fröhlich, H.; Patjoshi, S.; Yeghiazaryan, K.; Kehrer, C.; Kuhn, W.; Golubnitschaja, O. Premenopausal breast cancer: Potential clinical utility of a multi-omics based machine learning approach for patient stratification. EPMA J. 2018, 9, 175–186. [Google Scholar] [CrossRef] [PubMed]
- Brenner, D.R.; Brockton, N.T.; Kotsopoulos, J.; Cotterchio, M.; Boucher, B.A.; Courneya, K.S.; Knight, J.A.; Olivotto, I.A.; Quan, M.L.; Friedenreich, C.M. Breast cancer survival among young women: A review of the role of modifiable lifestyle factors. Cancer Causes Control. 2016, 27, 459–472. [Google Scholar] [CrossRef]
- Golubnitschaja, O. Feeling cold and other underestimated symptoms in breast cancer: Anecdotes or individual profiles for advanced patient stratification? EPMA J. 2017, 8, 17–22. [Google Scholar] [CrossRef]
- Bubnov, R.; Polivka, J.; Zubor, P.; Konieczka, K.; Golubnitschaja, O. “Pre-metastatic niches” in breast cancer: Are they created by or prior to the tumour onset? “Flammer Syndrome” relevance to address the question. EPMA J. 2017, 8, 141–157. [Google Scholar] [CrossRef]
- Golubnitschaja, O. Flammer Syndrome: From Phenotype to Associated Pathologies, Prediction, Prevention and Personalisation; Springer: Berlin, Germany, 2019; ISBN 978-3-030-13550-8. [Google Scholar]
- Seely, J.M.; Alhassan, T. Screening for breast cancer in 2018—What should we be doing today? Curr. Oncol. 2018, 25, S115–S124. [Google Scholar] [CrossRef]
- Springer Nature. Change the World—One Article at a Time. Available online: https://www.springernature.com/gp/researchers/campaigns/change-the-world?wt_mc=SocialMedia.Twitter.10.CON417.ctw2018_tw_shared_button&utm_medium=socialmedia&utm_source=twitter&utm_content=ctw2018_tw_shared_button&utm_campaign=10_dann_ctw2018_tw_shared_button (accessed on 12 July 2018).
- Change the World—Medicine and Public Health. Available online: https://www.springernature.com/gp/researchers/campaigns/change-the-world/medicine-public-health (accessed on 12 July 2018).
- Polivka, J.; Altun, I.; Golubnitschaja, O. Pregnancy-associated breast cancer: The risky status quo and new concepts of predictive medicine. EPMA J. 2018, 9, 1–13. [Google Scholar] [CrossRef]
- Moreira, W.B.; Brandão, E.C.; Soares, A.N.; de Lucena, C.E.M.; Antunes, C.M.F. Prognosis for patients diagnosed with pregnancy-associated breast cancer: A paired case-control study. Sao Paulo Med. J. 2010, 128, 119–124. [Google Scholar] [CrossRef]
- Zubor, P.; Kubatka, P.; Kapustova, I.; Miloseva, L.; Dankova, Z.; Gondova, A.; Bielik, T.; Krivus, S.; Bujnak, J.; Laucekova, Z.; et al. Current approaches in the clinical management of pregnancy-associated breast cancer-pros and cons. EPMA J. 2018, 9, 257–270. [Google Scholar] [CrossRef]
- Kim, Y.G.; Jeon, Y.W.; Ko, B.K.; Sohn, G.; Kim, E.-K.; Moon, B.-I.; Youn, H.J.; Kim, H.-A.; Society, K.B.C. Clinicopathologic Characteristics of Pregnancy-Associated Breast Cancer: Results of Analysis of a Nationwide Breast Cancer Registry Database. J. Breast Cancer 2017, 20, 264–269. [Google Scholar] [CrossRef] [PubMed]
- Golubnitschaja, O.; Debald, M.; Yeghiazaryan, K.; Kuhn, W.; Pešta, M.; Costigliola, V.; Grech, G. Breast cancer epidemic in the early twenty-first century: Evaluation of risk factors, cumulative questionnaires and recommendations for preventive measures. Tumour Biol. 2016, 37, 12941–12957. [Google Scholar] [CrossRef] [PubMed]
- Cardoso, F.; Loibl, S.; Pagani, O.; Graziottin, A.; Panizza, P.; Martincich, L.; Gentilini, O.; Peccatori, F.; Fourquet, A.; Delaloge, S.; et al. The European Society of Breast Cancer Specialists recommendations for the management of young women with breast cancer. Eur. J. Cancer 2012, 48, 3355–3377. [Google Scholar] [CrossRef] [PubMed]
- Cancer Research UK. Available online: https://www.cancerresearchuk.org/home (accessed on 4 September 2019).
- Anders, C.K.; Johnson, R.; Litton, J.; Phillips, M.; Bleyer, A. Breast cancer before age 40 years. Semin. Oncol. 2009, 36, 237–249. [Google Scholar] [CrossRef] [PubMed]
- Pollán, M. Epidemiology of breast cancer in young women. Breast Cancer Res. Treat. 2010, 123 (Suppl. 1), 3–6. [Google Scholar] [CrossRef]
- Althuis, M.D.; Brogan, D.D.; Coates, R.J.; Daling, J.R.; Gammon, M.D.; Malone, K.E.; Schoenberg, J.B.; Brinton, L.A. Breast cancers among very young premenopausal women (United States). Cancer Causes Control. 2003, 14, 151–160. [Google Scholar] [CrossRef]
- Tavani, A.; Gallus, S.; Vecchia, C.L.; Negri, E.; Montella, M.; Maso, L.D.; Franceschi, S. Risk factors for breast cancer in women under 40 years. Eur. J. Cancer 1999, 35, 1361–1367. [Google Scholar] [CrossRef]
- Turnbull, C.; Rahman, N. Genetic predisposition to breast cancer: Past, present, and future. Ann. Rev. Genomics Hum. Genet. 2008, 9, 321–345. [Google Scholar] [CrossRef]
- Copson, E.R.; Maishman, T.C.; Tapper, W.J.; Cutress, R.I.; Greville-Heygate, S.; Altman, D.G.; Eccles, B.; Gerty, S.; Durcan, L.T.; Jones, L.; et al. Germline BRCA mutation and outcome in young-onset breast cancer (POSH): A prospective cohort study. Lancet Oncol. 2018, 19, 169–180. [Google Scholar] [CrossRef]
- Adank, M.A.; Hes, F.J.; van Zelst-Stams, W.A.G.; van den Tol, M.P.; Seynaeve, C.; Oosterwijk, J.C. CHEK2-mutation in Dutch breast cancer families: Expanding genetic testing for breast cancer. Ned. Tijdschr. Geneeskd. 2015, 159, A8910. [Google Scholar]
- Bakhuizen, J.J.; Velthuizen, M.E.; Stehouwer, S.; Bleiker, E.M.; Ausems, M.G. Genetic counselling of young women with breast cancer for Li-Fraumeni syndrome: A nationwide survey on the experiences and attitudes of genetics professionals. Fam. Cancer 2019, 18, 231–239. [Google Scholar] [CrossRef] [PubMed]
- Walsh, T.; Casadei, S.; Coats, K.H.; Swisher, E.; Stray, S.M.; Higgins, J.; Roach, K.C.; Mandell, J.; Lee, M.K.; Ciernikova, S.; et al. Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer. JAMA 2006, 295, 1379–1388. [Google Scholar] [CrossRef] [PubMed]
- Evans, D.G.R.; Moran, A.; Hartley, R.; Dawson, J.; Bulman, B.; Knox, F.; Howell, A.; Lalloo, F. Long-term outcomes of breast cancer in women aged 30 years or younger, based on family history, pathology and BRCA1/BRCA2/TP53 status. Br. J. Cancer 2010, 102, 1091–1098. [Google Scholar] [CrossRef] [PubMed]
- Stuckey, A.R.; Onstad, M.A. Hereditary breast cancer: An update on risk assessment and genetic testing in 2015. Am. J. Obstet. Gynecol. 2015, 213, 161–165. [Google Scholar] [CrossRef]
- Gallardo-Alvarado, L.N.; Tusié-Luna, M.T.; Tussié-Luna, M.I.; Díaz-Chávez, J.; Segura, Y.X.; Bargallo-Rocha, E.; Villarreal, C.; Herrera-Montalvo, L.A.; Herrera-Medina, E.M.; Cantu-de Leon, D.F. Prevalence of germline mutations in the TP53 gene in patients with early-onset breast cancer in the Mexican population. BMC Cancer 2019, 19, 118. [Google Scholar] [CrossRef]
- Zubor, P.; Gondova, A.; Polivka, J.; Kasajova, P.; Konieczka, K.; Danko, J.; Golubnitschaja, O. Breast cancer and Flammer syndrome: Any symptoms in common for prediction, prevention and personalised medical approach? EPMA J. 2017, 8, 129–140. [Google Scholar] [CrossRef]
- Bardia, A.; Hurvitz, S. Targeted Therapy for Premenopausal Women with HR+, HER2− Advanced Breast Cancer: Focus on Special Considerations and Latest Advances. Clin. Cancer Res. 2018, 24, 5206–5218. [Google Scholar] [CrossRef]
- Lian, W.; Fu, F.; Lin, Y.; Lu, M.; Chen, B.; Yang, P.; Zeng, B.; Huang, M.; Wang, C. The Impact of Young Age for Prognosis by Subtype in Women with Early Breast Cancer. Sci. Rep. 2017, 7, 1–8. [Google Scholar] [CrossRef]
- Engstrøm, M.J.; Opdahl, S.; Hagen, A.I.; Romundstad, P.R.; Akslen, L.A.; Haugen, O.A.; Vatten, L.J.; Bofin, A.M. Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients. Breast Cancer Res. Treat. 2013, 140, 463–473. [Google Scholar] [CrossRef]
- Zhen, H.; Yang, L.; Li, L.; Yu, J.; Zhao, L.; Li, Y.; Li, Q. Correlation analysis between molecular subtypes and Nottingham Prognostic Index in breast cancer. Oncotarget 2017, 8, 74096–74105. [Google Scholar] [CrossRef]
- Hashmi, A.A.; Aijaz, S.; Khan, S.M.; Mahboob, R.; Irfan, M.; Zafar, N.I.; Nisar, M.; Siddiqui, M.; Edhi, M.M.; Faridi, N.; et al. Prognostic parameters of luminal A and luminal B intrinsic breast cancer subtypes of Pakistani patients. World J. Surg. Oncol. 2018, 16, 1. [Google Scholar] [CrossRef]
- Tubtimhin, S.; Promthet, S.; Suwanrungruang, K.; Supaattagorn, P. Molecular Subtypes and Prognostic Factors among Premenopausal and Postmenopausal Thai Women with Invasive Breast Cancer: 15 Years Follow-up Data. Asian Pac. J. Cancer Prev. 2018, 19, 3167–3174. [Google Scholar] [CrossRef]
- Radecka, B.; Litwiniuk, M. Breast cancer in young women. Ginekologia Polska 2016, 87, 659–663. [Google Scholar] [CrossRef]
- Villarreal-Garza, C.; Mohar, A.; Bargallo-Rocha, J.E.; Lasa-Gonsebatt, F.; Reynoso-Noverón, N.; Matus-Santos, J.; Cabrera, P.; Arce-Salinas, C.; Lara-Medina, F.; Alvarado-Miranda, A.; et al. Molecular Subtypes and Prognosis in Young Mexican Women With Breast Cancer. Clin. Breast Cancer 2017, 17, e95–e102. [Google Scholar] [CrossRef]
- Chollet-Hinton, L.; Olshan, A.F.; Nichols, H.B.; Anders, C.K.; Lund, J.L.; Allott, E.H.; Bethea, T.N.; Hong, C.-C.; Cohen, S.M.; Khoury, T.; et al. Biology and Etiology of Young-Onset Breast Cancers among Premenopausal African American Women: Results from the AMBER Consortium. Cancer Epidemiol. Biomarkers Prev. 2017, 26, 1722–1729. [Google Scholar] [CrossRef]
- Ma, D.; Jiang, Y.-Z.; Xie, M.-D.; Xiao, Y.; Zhao, S.; Shao, Z.-M. Abstract P3-08-11: Multi-omics profiling reveals distinct molecular features in young and elderly triple negative breast cancer. Cancer Res. 2019, 79. [Google Scholar] [CrossRef]
- Ryu, J.M.; Yu, J.; Kim, S.I.; Kim, K.S.; Moon, H.-G.; Choi, J.E.; Jeong, J.; Do Byun, K.; Nam, S.J.; Lee, J.E.; et al. Different prognosis of young breast cancer patients in their 20s and 30s depending on subtype: A nationwide study from the Korean Breast Cancer Society. Breast Cancer Res. Treat. 2017, 166, 833–842. [Google Scholar] [CrossRef]
- Tang, L.-C.; Jin, X.; Yang, H.-Y.; He, M.; Chang, H.; Shao, Z.-M.; Di, G.-H. Luminal B subtype: A key factor for the worse prognosis of young breast cancer patients in China. BMC Cancer 2015, 15, 201. [Google Scholar] [CrossRef]
- Wang, W.; Wang, X.; Liu, J.; Gao, J.; Wang, J.; Wang, X.; Zhao, D. Breast cancer in young women of Chinese Han population: A retrospective study of patients under 25 years. Pathol. Res. Pract. 2016, 212, 1015–1020. [Google Scholar] [CrossRef]
- Sharma, D.; Singh, G. Breast cancer in young women: A retrospective study from tertiary care center of north India. South Asian J. Cancer 2017, 6, 51. [Google Scholar]
- Shoemaker, M.L.; White, M.C.; Wu, M.; Weir, H.K.; Romieu, I. Differences in breast cancer incidence among young women aged 20–49 years by stage and tumor characteristics, age, race, and ethnicity, 2004–2013. Breast Cancer Res. Treat. 2018, 169, 595–606. [Google Scholar] [CrossRef] [PubMed]
- Gómez-Flores-Ramos, L.; Castro-Sánchez, A.; Peña-Curiel, O.; Mohar-Betancourt, A. Molecular Biology in Young Women with Breast Cancer: From Tumor Gene Expression To DNA Mutations. Rev. Invest. Clin. 2017, 69, 181–192. [Google Scholar] [CrossRef] [PubMed]
- Suwinski, P.; Ong, C.; Ling, M.H.T.; Poh, Y.M.; Khan, A.M.; Ong, H.S. Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics. Front. Genet. 2019, 10, 49. [Google Scholar] [CrossRef]
- Jasek, K.; Kasubova, I.; Holubekova, V.; Stanclova, A.; Plank, L.; Lasabova, Z. Epigenetics: An alternative pathway in GISTs tumorigenesis. Neoplasma 2018, 65, 477–493. [Google Scholar] [CrossRef]
- Kašubová, I.; Kalman, M.; Jašek, K.; Burjanivová, T.; Malicherová, B.; Vaňochová, A.; Meršaková, S.; Lasabová, Z.; Plank, L. Stratification of patients with colorectal cancer without the recorded family history. Oncol. Lett. 2019, 17, 3649–3656. [Google Scholar] [CrossRef]
- Rummel, S.K.; Lovejoy, L.; Shriver, C.D.; Ellsworth, R.E. Contribution of germline mutations in cancer predisposition genes to tumor etiology in young women diagnosed with invasive breast cancer. Breast Cancer Res. Treat. 2017, 164, 593–601. [Google Scholar] [CrossRef]
- Colak, D.; Nofal, A.; AlBakheet, A.; Nirmal, M.; Jeprel, H.; Eldali, A.; AL-Tweigeri, T.; Tulbah, A.; Ajarim, D.; Malik, O.A.; et al. Age-Specific Gene Expression Signatures for Breast Tumors and Cross-Species Conserved Potential Cancer Progression Markers in Young Women. PLoS ONE 2013, 8, e63204. [Google Scholar] [CrossRef]
- Park, C.; Yoon, K.-A.; Kim, J.; Park, I.H.; Park, S.J.; Kim, M.K.; Jang, W.; Cho, S.Y.; Park, B.; Kong, S.-Y.; et al. Integrative molecular profiling identifies a novel cluster of estrogen receptor-positive breast cancer in very young women. Cancer Sci. 2019, 110, 1760–1770. [Google Scholar] [CrossRef]
- Azim, H.A.; Partridge, A.H. Biology of breast cancer in young women. Breast Cancer Res. 2014, 16, 427. [Google Scholar] [CrossRef]
- Azim, H.; Azim, H.A. Targeting RANKL in breast cancer: Bone metastasis and beyond. Expert Rev. Anticancer Ther. 2013, 13, 195–201. [Google Scholar] [CrossRef]
- Choi, Y.E.; Pan, Y.; Park, E.; Konstantinopoulos, P.; De, S.; D’Andrea, A.; Chowdhury, D. MicroRNAs down-regulate homologous recombination in the G1 phase of cycling cells to maintain genomic stability. eLife 2014, 3, e02445. [Google Scholar] [CrossRef] [PubMed]
- Söderlund, K.; Skoog, L.; Fornander, T.; Askmalm, M.S. The BRCA1/BRCA2/Rad51 complex is a prognostic and predictive factor in early breast cancer. Radiother. Oncol. 2007, 84, 242–251. [Google Scholar] [CrossRef] [PubMed]
- Gómez-Flores-Ramos, L.; Álvarez-Gómez, R.M.; Villarreal-Garza, C.; Wegman-Ostrosky, T.; Mohar, A. Breast cancer genetics in young women: What do we know? Mutat. Res. 2017, 774, 33–45. [Google Scholar] [CrossRef] [PubMed]
- Korobeinikova, E.; Myrzaliyeva, D.; Ugenskiene, R.; Raulinaityte, D.; Gedminaite, J.; Smigelskas, K.; Juozaityte, E. The prognostic value of IL10 and TNF alpha functional polymorphisms in premenopausal early-stage breast cancer patients. BMC Genet. 2015, 16, 70. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Zhang, Y.; Coogan, P.F.; Palmer, J.R.; Strom, B.L.; Rosenberg, L. Use of nonsteroidal antiinflammatory drugs and risk of breast cancer: The Case-Control Surveillance Study revisited. Am. J. Epidemiol. 2005, 162, 165–170. [Google Scholar] [CrossRef] [PubMed]
- Peña-Chilet, M.; Martínez, M.T.; Pérez-Fidalgo, J.A.; Peiró-Chova, L.; Oltra, S.S.; Tormo, E.; Alonso-Yuste, E.; Martinez-Delgado, B.; Eroles, P.; Climent, J.; et al. MicroRNA profile in very young women with breast cancer. BMC Cancer 2014, 14, 529. [Google Scholar] [CrossRef]
- Tsai, H.-P.; Huang, S.-F.; Li, C.-F.; Chien, H.-T.; Chen, S.-C. Differential microRNA expression in breast cancer with different onset age. PLoS ONE 2018, 13, e0191195. [Google Scholar] [CrossRef]
- Martínez, M.T.; Oltra, S.S.; Peña-Chilet, M.; Alonso, E.; Hernando, C.; Burgues, O.; Chirivella, I.; Bermejo, B.; Lluch, A.; Ribas, G. Breast Cancer in Very Young Patients in a Spanish Cohort: Age as an Independent Bad Prognostic Indicator. Breast Cancer (Auckl) 2019, 13, 117822341982876. [Google Scholar] [CrossRef]
- Gonzalez-Suarez, E.; Jacob, A.P.; Jones, J.; Miller, R.; Roudier-Meyer, M.P.; Erwert, R.; Pinkas, J.; Branstetter, D.; Dougall, W.C. RANK ligand mediates progestin-induced mammary epithelial proliferation and carcinogenesis. Nature 2010, 468, 103–107. [Google Scholar] [CrossRef]
- Odén, L.; Akbari, M.; Zaman, T.; Singer, C.F.; Sun, P.; Narod, S.A.; Salmena, L.; Kotsopoulos, J. Plasma osteoprotegerin and breast cancer risk in BRCA1 and BRCA2 mutation carriers. Oncotarget 2016, 7, 86687–86694. [Google Scholar] [CrossRef]
- Zolfaroli, I.; Tarín, J.J.; Cano, A. The action of estrogens and progestogens in the young female breast. Eur. J. Obstet. Gynecol. Reprod. Biol. 2018, 230, 204–207. [Google Scholar] [CrossRef]
- Loving, V.A.; DeMartini, W.B.; Eby, P.R.; Gutierrez, R.L.; Peacock, S.; Lehman, C.D. Targeted ultrasound in women younger than 30 years with focal breast signs or symptoms: Outcomes analyses and management implications. AJR Am. J. Roentgenol. 2010, 195, 1472–1477. [Google Scholar] [CrossRef]
- Pisano, E.D.; Hendrick, R.E.; Yaffe, M.J.; Baum, J.K.; Acharyya, S.; Cormack, J.B.; Hanna, L.A.; Conant, E.F.; Fajardo, L.L.; Bassett, L.W.; et al. Diagnostic Accuracy of Digital versus Film Mammography: Exploratory Analysis of Selected Population Subgroups in DMIST. Radiology 2008, 246, 376–383. [Google Scholar] [CrossRef]
- Chong, A.; Weinstein, S.P.; McDonald, E.S.; Conant, E.F. Digital Breast Tomosynthesis: Concepts and Clinical Practice. Radiology 2019, 292, 1–14. [Google Scholar] [CrossRef]
- Lång, K.; Andersson, I.; Rosso, A.; Tingberg, A.; Timberg, P.; Zackrisson, S. Performance of one-view breast tomosynthesis as a stand-alone breast cancer screening modality: Results from the Malmö Breast Tomosynthesis Screening Trial, a population-based study. Eur. Radiol. 2016, 26, 184–190. [Google Scholar] [CrossRef]
- Caumo, F.; Zorzi, M.; Brunelli, S.; Romanucci, G.; Rella, R.; Cugola, L.; Bricolo, P.; Fedato, C.; Montemezzi, S.; Houssami, N. Digital Breast Tomosynthesis with Synthesized Two-Dimensional Images versus Full-Field Digital Mammography for Population Screening: Outcomes from the Verona Screening Program. Radiology 2018, 287, 37–46. [Google Scholar] [CrossRef]
- Cai, S.; Yao, M.; Cai, D.; Yan, J.; Huang, M.; Yan, L.; Huang, H. Association between digital breast tomosynthesis and molecular subtypes of breast cancer. Oncol. Lett. 2019, 17, 2669–2676. [Google Scholar] [CrossRef]
- Gilbert, F.J.; Tucker, L.; Gillan, M.G.C.; Willsher, P.; Cooke, J.; Duncan, K.A.; Michell, M.J.; Dobson, H.M.; Lim, Y.Y.; Suaris, T.; et al. Accuracy of Digital Breast Tomosynthesis for Depicting Breast Cancer Subgroups in a UK Retrospective Reading Study (TOMMY Trial). Radiology 2015, 277, 697–706. [Google Scholar] [CrossRef]
- Paluch-Shimon, S.; Pagani, O.; Partridge, A.H.; Abulkhair, O.; Cardoso, M.-J.; Dent, R.A.; Gelmon, K.; Gentilini, O.; Harbeck, N.; Margulies, A.; et al. ESO-ESMO 3rd international consensus guidelines for breast cancer in young women (BCY3). Breast 2017, 35, 203–217. [Google Scholar] [CrossRef]
- Monticciolo, D.L.; Newell, M.S.; Moy, L.; Niell, B.; Monsees, B.; Sickles, E.A. Breast Cancer Screening in Women at Higher-Than-Average Risk: Recommendations From the ACR. J. Am. Coll. Radiol. 2018, 15, 408–414. [Google Scholar] [CrossRef]
- Crivelli, P.; Ledda, R.E.; Parascandolo, N.; Fara, A.; Soro, D.; Conti, M. A New Challenge for Radiologists: Radiomics in Breast Cancer. Biomed. Res. Int. 2018. [Google Scholar] [CrossRef]
- Xie, T.; Wang, Z.; Zhao, Q.; Bai, Q.; Zhou, X.; Gu, Y.; Peng, W.; Wang, H. Machine Learning-Based Analysis of MR Multiparametric Radiomics for the Subtype Classification of Breast Cancer. Front. Oncol. 2019, 9, 505. [Google Scholar] [CrossRef]
- Zubor, P.; Kubatka, P.; Kajo, K.; Dankova, Z.; Polacek, H.; Bielik, T.; Kudela, E.; Samec, M.; Liskova, A.; Vlcakova, D.; et al. Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management. Int. J. Mol. Sci. 2019, 20, 2878. [Google Scholar] [CrossRef]
- Partridge, A.H.; Hughes, M.E.; Ottesen, R.A.; Wong, Y.-N.; Edge, S.B.; Theriault, R.L.; Blayney, D.W.; Niland, J.C.; Winer, E.P.; Weeks, J.C.; et al. The effect of age on delay in diagnosis and stage of breast cancer. Oncologist 2012, 17, 775–782. [Google Scholar] [CrossRef]
- Lautner, M.; Lin, H.; Shen, Y.; Parker, C.; Kuerer, H.; Shaitelman, S.; Babiera, G.; Bedrosian, I. Disparities in the Use of Breast-Conserving Therapy Among Patients With Early-Stage Breast Cancer. JAMA Surg. 2015, 150, 778–786. [Google Scholar] [CrossRef]
- Lazow, S.P.; Riba, L.; Alapati, A.; James, T.A. Comparison of breast-conserving therapy vs mastectomy in women under age 40: National trends and potential survival implications. Breast J. 2019, 25, 578–584. [Google Scholar] [CrossRef]
- Rosenberg, S.M.; Sepucha, K.; Ruddy, K.J.; Tamimi, R.M.; Gelber, S.; Meyer, M.E.; Schapira, L.; Come, S.E.; Borges, V.F.; Golshan, M.; et al. Local Therapy Decision-Making and Contralateral Prophylactic Mastectomy in Young Women with Early-Stage Breast Cancer. Ann. Surg. Oncol. 2015, 22, 3809–3815. [Google Scholar] [CrossRef]
- Covelli, A.M.; Baxter, N.N.; Fitch, M.I.; McCready, D.R.; Wright, F.C. “Taking control of cancer”: Understanding women’s choice for mastectomy. Ann. Surg. Oncol. 2015, 22, 383–391. [Google Scholar] [CrossRef]
- Nichols, H.B.; Berrington de González, A.; Lacey, J.V.; Rosenberg, P.S.; Anderson, W.F. Declining incidence of contralateral breast cancer in the United States from 1975 to 2006. J. Clin. Oncol. 2011, 29, 1564–1569. [Google Scholar] [CrossRef]
- Sinnadurai, S.; Kwong, A.; Hartman, M.; Tan, E.Y.; Bhoo-Pathy, N.T.; Dahlui, M.; See, M.H.; Yip, C.H.; Taib, N.A.; Bhoo-Pathy, N. Breast-conserving surgery versus mastectomy in young women with breast cancer in Asian settings. BJS Open 2019, 3, 48–55. [Google Scholar] [CrossRef]
- van Maaren, M.C.; de Munck, L.; de Bock, G.H.; Jobsen, J.J.; van Dalen, T.; Linn, S.C.; Poortmans, P.; Strobbe, L.J.A.; Siesling, S. 10 year survival after breast-conserving surgery plus radiotherapy compared with mastectomy in early breast cancer in the Netherlands: A population-based study. Lancet Oncol. 2016, 17, 1158–1170. [Google Scholar] [CrossRef]
- Suter, M.B.; Pagani, O. Should age impact breast cancer management in young women? Fine tuning of treatment guidelines. Ther. Adv. Med. Oncol. 2018, 10. [Google Scholar] [CrossRef]
- Sauter, E.R. Breast Cancer Prevention: Current Approaches and Future Directions. Eur. J. Breast Health 2018, 14, 64–71. [Google Scholar] [CrossRef]
- Dumitrescu, R.G. Chapter 4—Cancer Genetic Screening and Ethical Considerations for Precision Medicine. In Progress and Challenges in Precision Medicine; Verma, M., Barh, D., Eds.; Academic Press: Cambridge, MA, USA, 2017; pp. 79–100. ISBN 978-0-12-809411-2. [Google Scholar]
- Tung, N.; Battelli, C.; Allen, B.; Kaldate, R.; Bhatnagar, S.; Bowles, K.; Timms, K.; Garber, J.E.; Herold, C.; Ellisen, L.; et al. Frequency of mutations in individuals with breast cancer referred for BRCA1 and BRCA2 testing using next-generation sequencing with a 25-gene panel. Cancer 2015, 121, 25–33. [Google Scholar] [CrossRef]
- Evans, D.G.; Brentnall, A.R.; Harvie, M.; Dawe, S.; Sergeant, J.C.; Stavrinos, P.; Astley, S.; Wilson, M.; Ainsworth, J.; Cuzick, J.; et al. Breast cancer risk in young women in the national breast screening programme: Implications for applying NICE guidelines for additional screening and chemoprevention. Cancer Prev. Res. (Phila.) 2014, 7, 993–1001. [Google Scholar] [CrossRef]
- Amir, E.; Freedman, O.C.; Seruga, B.; Evans, D.G. Assessing women at high risk of breast cancer: A review of risk assessment models. J. Natl. Cancer Inst. 2010, 102, 680–691. [Google Scholar] [CrossRef]
- Smokovski, I.; Risteski, M.; Polivka, J., Jr.; Zubor, P.; Konieczka, K.; Costigliola, V.; Golubnitschaja, O. Postmenopausal breast cancer: European challenge and innovative concepts. EPMA J. 2017, 8, 159. [Google Scholar] [CrossRef]
- Golubnitschaja, O.; Yeghiazaryan, K.; Abraham, J.A.; Schild, H.H.; Costigliola, V.; Debald, D.; Kuhn, W. Breast Cancer Risk Assessment: A Non-invasive Multiparametric Approach to Stratify Patients by MMP-9 Serum Activity and RhoA Expression Patterns in Circulating Leucocytes. Amino Acids 2017, 49, 273–281. [Google Scholar] [CrossRef]
- Polivka, J., Jr.; Kralickova, M.; Polivka, J.; Kaiser, C.; Kuhn, W.; Golubnitschaja, O. Mystery of the brain metastatic disease in breast cancer patients: Improved patient stratification, disease prediction and targeted prevention on the horizon? EPMA J. 2017, 8, 119–127. [Google Scholar] [CrossRef]
- Golubnitschaja, O.; Filep, N.; Yeghiazaryan, K.; Blom, H.J.; Konieczka-Apitius, M.; Kuhn, W. Multi-omic approach decodes paradoxes of the triple-negative breast cancer: Lessons for predictive, preventive and personalised medicine. Amino Acids 2018, 50, 383–395. [Google Scholar] [CrossRef]
- Konieczka, K.; Ritch, R.; Traverso, C.E.; Kim, D.M.; Kook, M.S.; Gallino, A.; Golubnitschaja, O.; Erb, C.; Reitsamer, H.A.; Kida, T.; et al. Flammer syndrome. EPMA J. 2014, 5, 11. [Google Scholar] [CrossRef]
- Mencalha, A.; Victorino, V.J.; Cecchini, R.; Panis, C. Mapping oxidative changes in breast cancer: Understanding the basic to reach the clinics. Anticancer Res. 2014, 34, 1127–1140. [Google Scholar]
- Gordon, C.J. Temperature and Toxicology: An Integrative, Comparative and Environmental Approach; Taylor & Francis: Boca Raton, FL, USA, 2005; pp. 169–171. [Google Scholar]
- Kurzrock, R. The role of cytokines in cancer-related fatigue. Cancer 2001, 92, 1684–1688. [Google Scholar] [CrossRef]
- Netea, M.G.; Kullberg, B.J.; Van derMeer, J.W.M. Circulating cytokines as mediators of fever. Clin. Infect. Dis. 2000, 31, S178–S184. [Google Scholar] [CrossRef]
- Wülfing, P.; Diallo, R.; Kersting, C.; Wülfing, C.; Poremba, C.; Rody, A.; Greb, R.R.; Böcker, W.; Kiesel, L. Expression of endothelin-1, endothelin-a, and endothelin-b receptor in human breast cancer and correlation with long-term followup. Clin. Cancer Res. 2003, 9, 4125–4131. [Google Scholar]
- Cox, T.R.; Rumney, R.M.; Schoof, E.M.; Perryman, L.; Hoye, A.M.; Agrawal, A. The hypoxic cancer secretome induces premetastatic bone lesions through lysyl oxidase. Nature 2015, 522, 106–110. [Google Scholar] [CrossRef]
- Vanharanta, S. A hypoxic ticket to the bone metastatic niche. Breast Cancer Res. 2015, 17, 122. [Google Scholar] [CrossRef]
- Kleiner, S.M. Water: An essential but overlooked nutrient. J. Am. Diet. Assoc. 1999, 99, 200–206. [Google Scholar] [CrossRef]
- Borkum, J.M. Migraine triggers and oxidative stress: A narrative review and synthesis. Headache 2016, 56, 12–35. [Google Scholar] [CrossRef]
- Ha, N.H.; Long, J.; Cai, Q.; Shu, X.O.; Hunter, K.W. The circadian rhythm geneArntl2 is ametastasis susceptibility gene for estrogen receptornegative breast cancer. PLoS Genet. 2016, 12, e1006267. [Google Scholar] [CrossRef]
- Reszka, E.; Przybek, M. Circadian genes in breast cancer. Adv. Clin. Chem. 2016, 75, 53–70. [Google Scholar]
- Kim, D.-H.; Kim, Y.-S.; Son, N.-I.; Kang, C.-K.; Kim, A.-R. Recent omics technologies and their emerging applications for personalised medicine. IET Syst. Biol. 2017, 11, 87–98. [Google Scholar] [CrossRef]
- Cancer Genome Atlas Network Comprehensive molecular portraits of human breast tumours. Nature 2012, 490, 61–70. [CrossRef]
- Zeidan, B.; Manousopoulou, A.; Garay-Baquero, D.J.; White, C.H.; Larkin, S.E.T.; Potter, K.N.; Roumeliotis, T.I.; Papachristou, E.K.; Copson, E.; Cutress, R.I.; et al. Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: A multi-center POSH cohort serum proteomics study. Breast Cancer Res. 2018, 20, 19. [Google Scholar] [CrossRef]
- Zhang, X.; Ju, S.; Wang, X.; Cong, H. Advances in liquid biopsy using circulating tumor cells and circulating cell-free tumor DNA for detection and monitoring of breast cancer. Clin. Exp. Med. 2019, 19, 271–279. [Google Scholar] [CrossRef]
- Aslebagh, R.; Channaveerappa, D.; Arcaro, K.F.; Darie, C.C. Proteomics analysis of human breast milk to assess breast cancer risk. Electrophoresis 2018, 39, 653–665. [Google Scholar] [CrossRef]
- Bohm, D.; Keller, K.; Pieter, J.; Boehm, N.; Wolters, D.; Siggelkow, W.; Lebrecht, A.; Schmidt, M.; Kolbl, H.; Pfeiffer, N. Comparison of tear protein levels in breast cancer patients and healthy controls using a de novo proteomic approach. Oncol. Rep. 2012, 28, 429–438. [Google Scholar] [CrossRef]
- Lebrecht, A.; Boehm, D.; Schmidt, M.; Koelbl, H.; Schwirz, R.L.; Grus, F.H. Diagnosis of breast cancer by tear proteomic pattern. Cancer Genomics Proteomics 2009, 6, 177–182. [Google Scholar]
- Kapinova, A.; Kubatka, P.; Golubnitschaja, O.; Kello, M.; Zubor, P.; Solar, P.; Pec, M. Dietary phytochemicals in breast cancer research: Anticancer effects and potential utility for effective chemoprevention. Environ. Health Prev. Med. 2018, 23, 36. [Google Scholar] [CrossRef]
- Ferroni, P.; Zanzotto, F.M.; Riondino, S.; Scarpato, N.; Guadagni, F.; Roselli, M. Breast Cancer Prognosis Using a Machine Learning Approach. Cancers 2019, 11, 328. [Google Scholar] [CrossRef]
- Zhao, M.; Tang, Y.; Kim, H.; Hasegawa, K. Machine Learning With K-Means Dimensional Reduction for Predicting Survival Outcomes in Patients with Breast Cancer. Cancer Inform. 2018, 17. [Google Scholar] [CrossRef]
- Sadoughi, F.; Kazemy, Z.; Hamedan, F.; Owji, L.; Rahmanikatigari, M.; Azadboni, T.T. Artificial intelligence methods for the diagnosis of breast cancer by image processing: A review. Breast Cancer (Dove Med. Press) 2018, 10, 219–230. [Google Scholar] [CrossRef]
- Frey, L.J. Artificial Intelligence and Integrated Genotype–Phenotype Identification. Genes 2019, 10, 18. [Google Scholar] [CrossRef]
- Rossing, M.; Sørensen, C.S.; Ejlertsen, B.; Nielsen, F.C. Whole genome sequencing of breast cancer. APMIS 2019, 127, 303–315. [Google Scholar] [CrossRef]
- Kunin, A.; Polivka, J.; Moiseeva, N.; Golubnitschaja, O. “Dry mouth” and “Flammer” syndromes—neglected risks in adolescents and new concepts by predictive, preventive and personalised approach. EPMA J. 2018, 9, 307–317. [Google Scholar] [CrossRef]
- Goncharenko, V.; Bubnov, R.; Polivka, J., Jr.; Zubor, P.; Biringer, K.; Bielik, T.; Kuhn, W.; Golubnitschaja, O. Vaginal dryness: Individualised patient profiles, risks and mitigating measures. EPMA J. 2019, 10, 73–79. [Google Scholar] [CrossRef]
- Hamam, R.; Hamam, D.; Alsaleh, K.A.; Kassem, M.; Zaher, W.; Alfayez, M.; Aldahmash, A.; Alajez, N.M. Circulating microRNAs in breast cancer: Novel diagnostic and prognostic biomarkers. Cell Death Dis. 2017, 8, e3045. [Google Scholar] [CrossRef]

| MODIFIABLE Risk Factors | NON-MODIFIABLE Risk Factors |
|---|---|
| Body mass index | BRCA1, BRCA2 mutations |
| Parity | Li Fraumeni syndrome (p53) |
| High alcohol intake | CHEK2*1100delC mutations and other genetic alterations |
| Smoking | Age |
| Lifestyle | |
| Breastfeeding | |
| Radiation exposure in utero |
| Molecular Signatures Groups | Most Common Genetic Alterations |
|---|---|
| Genomic alterations | SEPP1, ESR1, IL1RN, SCD, TIAM1, UBE2C, CCNB2, CEP55, TOP2A, BIRC5, TPX2, SHCBP1, KIAA0101, PTTG1, UBE2T, DEPDC1, NUSAP1, CCNB1, HELLS, KIF4A, RRM2, IGF1R, APOBEC3A/B, amplification of 11q13 (CCND1), 17q12 (ERBB2), Chr1p34, and copy number loss at Chr15q13 |
| Inflammatory biomarkers | TNF-308G>A polymorphism |
| miRNA | miR-1228, miR-3196, miR-1275 miR-1207, miR-92b, miR-139, miR-183, miR-182 and miR-96, miR-320, miR-10a, miR-130, miR-127-3p, miR-143, miR-10b, miR-125b, and miR-195 |
| Signaling pathways | RANK/RANKL |
| Questions | Answers (Yes/No) | Comments |
|---|---|---|
| Cold hands and/or feet | Yes | Very frequently |
| Feel cold | Yes | Very soon |
| Low blood pressure? | Yes | Very frequent |
| Dizziness | Yes | Very frequent |
| Prolong sleep onset | Yes | Very frequent |
| Do not feel thirsty | Yes | Even in hot weather |
| Headache/Migraine | No | |
| Accompanying symptoms (e.g., visual disturbances) | No | |
| Altered reaction towards drugs | Not known | |
| Altered pain sensitivity | No | |
| Strong smell perception | Yes | Extraordinary pronounced |
| Slim at 20–30 years of age | Yes | Extraordinary pronounced |
| Tendency towards perfectionism | Yes | Strongly pronounced |
| Tinnitus | No | |
| Reversible blotches (white or red) on your skin e.g., in stress situations | Yes | Strongly pronounced |
© 2019 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 (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kudela, E.; Samec, M.; Kubatka, P.; Nachajova, M.; Laucekova, Z.; Liskova, A.; Dokus, K.; Biringer, K.; Simova, D.; Gabonova, E.; et al. Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach. Cancers 2019, 11, 1791. https://doi.org/10.3390/cancers11111791
Kudela E, Samec M, Kubatka P, Nachajova M, Laucekova Z, Liskova A, Dokus K, Biringer K, Simova D, Gabonova E, et al. Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach. Cancers. 2019; 11(11):1791. https://doi.org/10.3390/cancers11111791
Chicago/Turabian StyleKudela, Erik, Marek Samec, Peter Kubatka, Marcela Nachajova, Zuzana Laucekova, Alena Liskova, Karol Dokus, Kamil Biringer, Denisa Simova, Eva Gabonova, and et al. 2019. "Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach" Cancers 11, no. 11: 1791. https://doi.org/10.3390/cancers11111791
APA StyleKudela, E., Samec, M., Kubatka, P., Nachajova, M., Laucekova, Z., Liskova, A., Dokus, K., Biringer, K., Simova, D., Gabonova, E., Dankova, Z., Biskupska Bodova, K., Zubor, P., & Trog, D. (2019). Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach. Cancers, 11(11), 1791. https://doi.org/10.3390/cancers11111791

