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International Journal of Molecular Sciences
  • Review
  • Open Access

15 November 2017

Novel Strategies on Personalized Medicine for Breast Cancer Treatment: An Update

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The Nethersole School of Nursing, The Chinese University of Hong Kong, Shatin, The New Territories, Hong Kong, China
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Author to whom correspondence should be addressed.
This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics

Abstract

Breast cancer is the most common cancer type among women worldwide. With breast cancer patients and survivors being reported to experience a repertoire of symptoms that are detrimental to their quality of life, the development of breast cancer treatment strategies that are effective with minimal side effects is therefore required. Personalized medicine, the treatment process that is tailored to the individual needs of each patient, is recently gaining increasing attention for its prospect in the development of effective cancer treatment regimens. Indeed, recent studies have identified a number of genes and molecules that may be used as biomarkers for predicting drug response and severity of common cancer-associated symptoms. These would provide useful clues not only for the determination of the optimal drug choice/dosage to be used in personalized treatment, but also for the identification of gene or molecular targets for the development of novel symptom management strategies, which ultimately would lead to the development of more personalized therapies for effective cancer treatment. In this article, recent studies that would provide potential new options for personalized therapies for breast cancer patients and survivors are reviewed. We suggest novel strategies, including the optimization of drug choice/dosage and the identification of genetic changes that are associated with cancer symptom occurrence and severity, which may help in enhancing the effectiveness and acceptability of the currently available cancer therapies.

1. Introduction

Breast cancer is currently the most prevalent cancer type among women worldwide. In 2012, more than 1.6 million new cases of breast cancer were reported, and it had resulted in more than 500,000 deaths [1]. Collectively, breast cancer can be classified into several sub-types based on the observed presence of certain breast cancer-associated biomarkers, such as estrogen receptor (ER), progesterone receptor (PR), Ki-67 (a protein marker with prognostic and predictive potential for adjuvant chemotherapy), and human epidermal receptor 2 (HER2), in the tumors (Table 1) [2]. In light of the high and increasing prevalence of breast cancer, the development of effective treatment strategies for breast cancer is warranted. Currently, the strategies that are used to treat breast cancer include chemotherapy, radiation therapy, hormonal therapy, and surgery, although immunotherapy, the use of monoclonal antibodies (mAbs), which is known to interfere with certain cancer-related molecular/signaling pathways in cancer treatment, is increasingly utilized. Furthermore, with the development and increased use of targeted therapies, which involve the use of therapeutic molecules that would specifically modulate the pathways implicated in tumor progression, the survival rate of breast cancer patients and their patient outcomes have improved over the past years [3]. However, oncologists still face challenges in the implementation of efficacious breast cancer treatment through targeted therapies, primarily due to the progressive development of therapeutic resistance by the tumors, which consequently leads to patient relapses [4]. Besides, certain cancer deaths may in fact be attributed to the detrimental effects of cancer treatment. A study in the United Kingdom revealed that about 2.5% of breast cancer patients who underwent systematic anticancer therapy died within 30 days of receiving the therapy [5]. Likewise, a population-based study also revealed that the 30-day mortality rate of a cohort of patients of various cancer types as a result of receiving palliative radiotherapy even reached 12.3% [6]. In addition, the immense cost that is required to receive such therapies, owing to the use of expensive therapeutics, has also imposed considerable economic burden to the patients’ families. In light of this, the development of further strategies in developing effective cancer treatment is of crucial importance. Over the past decade, personalized medicine has gained increasing attention in terms of its prospect in more effective cancer treatment and management.
Table 1. The classification of breast cancer sub-types based on the expression of biomarkers in tumors. ER: estrogen receptor; HER2: human epidermal receptor 2; Ki-67: a protein marker for proliferation; PR: progesterone receptor.
With the advances in the development of high-throughput DNA sequencing and bioinformatics analyses, the prospect of the use of personalized medicine has become increasingly realistic. As a result of the increased utilization of personalized medicine in recent years, the overall survival of cancer patients has generally been improved. This improvement was shown to be more prominent among metastatic breast cancer patients when compared to patients with colorectal cancer and metastatic non-small cell lung cancer [7]. Nevertheless, not all patients are able to benefit from personalized treatment and oncologists are still facing many challenges in its implementation. To date, some barriers to the successful implementation of personalized treatment among breast cancer patients have been suggested. These include cancer heterogeneity [8,9,10], and variations in the level of responses to different cancer treatment regimens (chemotherapy, radiation, or surgical treatments) among individuals that are currently not fully understood [11,12]. Nevertheless, it was cited that the heterogeneity of the single nucleotide polymorphisms (SNPs) in certain cancer-associated genes (such as genes coding for cytochrome P450 variants) that are possessed by different ethnic groups could be a potential factor for the variations in treatment response among individuals [13]. Such variations would impose challenges on the development of personalized therapies, where the choice of therapeutic drugs/molecules that are used for therapies and their dosages have to be specifically tailored to an individual. Specifically, the formulation of the optimal personalized therapy for different individuals possessing various SNPs is going to be costly and tedious due to the need to tailor the therapies for multiple genes with some still unidentified SNPs to date, based on the modified treatment responses of various individuals caused by these SNPs. Further research into personalized medicine for breast cancer patients should therefore address these challenges.
Previously, a number of reviews have been published providing an overview on the variety of therapies available during the initial treatment of breast cancer [14,15,16,17]. However, reviews that provide suggested strategies on how to improve on the current therapies, in terms of enhancing effectiveness and the reduction of side effects, are currently lacking. This review attempts to highlight some of the recent research that would provide clues to the exploration for new options in the development of personalized therapies available for breast cancer patients and survivors, which would potentially enhance the effectiveness and acceptability of the currently available cancer therapies.

2. Side Effects of Current Cancer Therapies Reduce the Quality of Life (QOL) of Breast Cancer Patients and Survivors

Current cancer therapies, including chemotherapy, are known to induce undesirable cancer-associated symptoms among breast cancer patients, which are detrimental to the QOL of these patients [18,19]. A previous study had evaluated the symptom experience of breast cancer patients who are undergoing chemotherapy, and they identified 38 common symptoms among these individuals, in which they were classified into five stable symptom clusters (psychological, hormonal, nutritional, gastrointestinal, and epithelial) [20]. In another study, the authors investigated the effect of chemotherapy on symptom experience and QOL of breast cancer survivors who received chemotherapy [21]. It involved an assessment among these individuals for their mental and physical QOL at various time points, including before chemotherapy, after cycle 3 of chemotherapy, within 2–3 weeks of completing adjuvant chemotherapy, and at least eight years after chemotherapy. Though no obvious decline in cognitive function was observed, the authors reported that patients experienced an increase in the severity of depressive symptoms and fatigue. Therefore, breast cancer patients undergoing chemotherapy normally experience multiple symptoms, which was suggested to exhibit a synergistic effect on patient outcomes [22,23]. Another point of note is that cancer patients at different cancer stages may possess different perceptions on the need in addressing these detrimental treatment-associated side effects. For example, these side effects may appear more acceptable to early-stage cancer patients, due to the perceived brighter prospect of the treatment in curing the disease at an early stage. In contrast, such side effects on patients with metastatic tumors should be more aggressively addressed as metastatic cancers are generally incurable and that ensuring a better QOL of these patients is of greater importance. Therefore, a better understanding on the common treatment-related side effects among advanced breast cancer patients and survivors is required, so as to provide clues to the development of strategies in tailoring treatment regimens that would effectively alleviate these side effects.
Overall, previous studies had identified a repertoire of more devastating symptoms that are experienced by these patients that would exhibit a more far-reaching impact, as described below.

2.1. Premature Menopause or Chemotherapy-Induced Menopause (CIM)

Breast cancer patients undergoing chemotherapy are known to be at an increased risk of premature menopause, resulting in menopausal symptoms that would decrease their QOL [24]. The incidence rate of premature menopause after chemotherapy of young breast cancer patients was reported to be 13.3% [25]. Although premature menopause might have been perceived to be less harmful among women with children, such a condition could predispose them to an increased risk of cardiovascular diseases [26]. Indeed, female cancer survivors who underwent cardio-toxic therapy and have experienced premature menopause appear to be at an increased risk of cardiac morbidity [27]. Premature menopause may also contribute to bone fragility, and could lead to spontaneous rib fractures [28]. Thus, interventions through exercise could be a useful strategy for breast cancer patients undergoing chemotherapy to reduce cardiovascular disease risk [29]. Besides the increase in long-term mortality risks as a result of premature menopause, women often experience unpleasant symptoms that reduce their QOL. Thus, even though ovary ablation (OA) was shown to reduce breast cancer relapse (in combination with the use of either tamoxifen or aromatase inhibitors) in high-risk women, adjuvant OA should still be utilized with careful considerations [30]. Overall, CIM is one of the treatment-associated symptoms for breast cancer patients that would lead to increased risk of further complications. Interventions that reduce the risk of these complications should be made available to these patients who are undergoing chemotherapy.

2.2. Chemotherapy-Induced Peripheral Neuropathy (CIPN)

Chemotherapy-induced peripheral neuropathy (CIPN) may occur in many breast cancer patients during treatment, or in some cases many years after they complete their treatment. One study reported that up to 45% of breast cancer survivors would still feel numbness in their peripheral limbs, a symptom that is associated with CIPN, six years after chemotherapy [31]. Patients with CIPN are more susceptible to falls, and therefore they are at increased risk of bone fractures [32]. Nevertheless, a Danish study found that peripheral neuropathy did not affect the relative dose intensity in the treatment of their patients with adjuvant chemotherapy [33], indicating that the experience of CIPN among breast cancer patients would not affect the course of cancer treatment, despite its detrimental effect on their locomotion.

2.3. Cognitive Dysfunction

Cognitive dysfunction is one of the treatment-associated symptoms that affects mainly older cancer patients [34]. One study [35] demonstrated that up to 46% of patients aged 65 or above, who were admitted for breast, prostate, or colorectal cancer, suffered from cognitive impairment. The authors also showed that patients who were determined to exhibit cognitive impairment using the Montreal Cognitive Assessment (MoCA > 26) were found to be at a higher risk of death than those who did not [35]. Although the exact mechanism of how chemotherapy can induce cognitive dysfunction is not known, previous studies suggested that neuroinflammation and oxidative stress might play a major role [36].

2.4. Depression

Depressive symptoms were previously reported in breast cancer patients who underwent chemotherapy. For example, mild to moderate levels of depression was observed in over one half of breast cancer survivors in one study, and their depressive symptoms were found to be accompanied by cognitive dysfunction [21]. Further, in an Indian study, 22% of breast cancer survivors were found to exhibit moderately severe to severe levels of depression. This condition was also demonstrated to be associated with a poorer QOL among these patients [37,38].

2.5. Pain

Pain is one of the most well-established symptoms that is suffered by cancer patients undergoing chemotherapy, primarily due to the occurrence of CIPN, where alterations in neurotransmissions and actions of pro-inflammatory cytokines in peripheral nerves are believed to be the major causes [39]. Moreover, a recent meta-analysis revealed a number of risk factors that may increase the odds of experience of pain among breast cancer survivors [40]. These include obesity, lower level of education, lymphedema, non-smokers, axillary lymph node dissection, and undertaking chemotherapy, hormonal therapy, and radiation therapy. The finding that undertaking cancer therapies is a risk factor of pain provides further evidence for the direct effect of cancer treatment on the experience of pain among breast cancer patients.

5. Conclusions

As a result of the unpleasant side effects of the currently practiced cancer treatment regimens, some breast cancer patients experience undesirable cancer-related symptoms during the process of cancer treatment. This potentially results in the reduced drug dosage used during treatment or even treatment cessation, rendering the treatment process ineffective. Personalized therapies, treatment that is provided according to the needs of individual patient, could potentially address this issue. Two strategies key to the development of personalized therapies are: (1) optimization of drug choice or dosage used in treatment; and (2) identification of genetic changes that are associated with cancer symptom occurrence and severity.
Recent studies have revealed a number of genomic changes (including SNPs and gene overexpression) and metabolomic changes that would lead to differences in the efficacy of the treatment and effect on symptom severity and QOL in different individuals. This thereby enables us to identify certain genetic biomarkers that can be used as tools for the determination of the optimal drug choice or dosage to be used in cancer treatment. This would enable the treatment process to achieve its required efficacy, yet it would not cause too much discomfort for patients undergoing such treatment. Furthermore, with the development of novel techniques and technologies, such as the use of microRNA for timely chemotherapeutic drug release and wearable sensors to detect any abnormal changes in metabolic rate of patients as a result of drug administration, the side effects that are caused by the treatment process itself could potentially be significantly ameliorated.
Gene profiling studies would also help to identify the genetic biomarkers that can predict the risk of individuals to develop common symptoms that are associated with cancer treatment. Studies on the metabolic changes that are associated with the occurrence and severity of certain cancer-associated symptoms have also helped identify a number of molecular candidates that can be used as determinants on whether patients are at higher risk of increased severity of a particular symptom, and whether these candidates can be targeted for symptom management in patients. All of these would inform the development of novel strategies in planning for personalized therapies in symptom amelioration, thereby ensuring a better QOL for patients undergoing cancer treatment.
Despite recent advances in the identification of novel biomarkers that affect treatment efficacy and symptom severity, the molecular mechanisms of how they exert their effects is still not fully understood. Furthermore, confirmation on the findings of the current studies on biomarker identification, through additional studies on the association of these biomarkers and treatment efficacy and symptom severity among breast cancer patients of various ethnicities, is generally lacking. Further studies on these issues are therefore warranted in order to enable the exploration and development of further strategies that can be utilized in optimizing cancer therapies for breast cancer patients, thereby augmenting the effectiveness of cancer treatment and improving the QOL of patients during the treatment process.

Acknowledgments

The Chinese University of Hong Kong funded the cost of publication of this manuscript with open access in this journal.

Author Contributions

Carmen W. H. Chan set the aim and focus of the manuscript. Mary M. Y. Waye and Bernard M. H. Law drafted the manuscript. Carmen W. H. Chan, Ka Ming Chow, Winnie K. W. So and Mary M. Y. Waye critically reviewed and revised the manuscript and were involved in the contribution of ideas to the content and presentation of the manuscript. All authors approved the final version of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Globocan 2012: Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2012. Available online: http://globocan.iarc.fr/Pages/fact_sheets_population.aspx (accessed on 22 September 2017).
  2. Inic, Z.; Zegarac, M.; Inic, M.; Markovic, I.; Kozomara, Z.; Djurisic, I.; Inic, I.; Pupic, G.; Jancic, S. Difference between Luminal A and Luminal B Subtypes According to Ki-67, Tumor Size, and Progesterone Receptor Negativity Providing Prognostic Information. Clin. Med. Insights Oncol. 2014, 8, 107–111. [Google Scholar] [CrossRef] [PubMed]
  3. Munagala, R.; Aqil, F.; Gupta, R.C. Promising molecular targeted therapies in breast cancer. Indian J. Pharmacol. 2011, 43, 236–245. [Google Scholar] [CrossRef] [PubMed]
  4. Masoud, V.; Pages, G. Targeted therapies in breast cancer: New challenges to fight against resistance. World J. Clin. Oncol. 2017, 8, 120–134. [Google Scholar] [CrossRef] [PubMed]
  5. Wallington, M.; Saxon, E.B.; Bomb, M.; Smittenaar, R.; Wickenden, M.; McPhail, S.; Rashbass, J.; Chao, D.; Dewar, J.; Talbot, D.; et al. 30-day mortality after systemic anticancer treatment for breast and lung cancer in England: A population-based, observational study. Lancet Oncol. 2016, 17, 1203–1216. [Google Scholar] [CrossRef]
  6. Spencer, K.; Morris, E.; Dugdale, E.; Newsham, A.; Sebag-Montefiore, D.; Turner, R.; Hall, G.; Crellin, A. 30 day mortality in adult palliative radiotherapy—A retrospective population based study of 14,972 treatment episodes. Radiother. Oncol. 2015, 115, 264–271. [Google Scholar] [CrossRef] [PubMed]
  7. Rossi, A.; Torri, V.; Garassino, M.C.; Porcu, L.; Galetta, D. The impact of personalized medicine on survival: Comparisons of results in metastatic breast, colorectal and non-small-cell lung cancers. Cancer Treat. Rev. 2014, 40, 485–494. [Google Scholar] [CrossRef] [PubMed]
  8. Dey, N.; Williams, C.; Leyland-Jones, B.; De, P. Mutation matters in precision medicine: A future to believe in. Cancer Treat. Rev. 2017, 55, 136–149. [Google Scholar] [CrossRef] [PubMed]
  9. Smith, B.; Agarwal, P.; Bhowmick, N.A. MicroRNA applications for prostate, ovarian and breast cancer in the era of precision medicine. Endocr.-Relat. Cancer 2017, 24, R157–R172. [Google Scholar] [CrossRef] [PubMed]
  10. Anastasiadi, Z.; Lianos, G.D.; Ignatiadou, E.; Harissis, H.V.; Mitsis, M. Breast cancer in young women: An overview. Updates Surg. 2017, 69, 313–317. [Google Scholar] [CrossRef] [PubMed]
  11. McVeigh, T.P.; Kerin, M.J. Clinical use of the Oncotype DX genomic test to guide treatment decisions for patients with invasive breast cancer. Breast Cancer (Dove Med. Press) 2017, 9, 393–400. [Google Scholar] [CrossRef] [PubMed]
  12. Lheureux, S.; Denoyelle, C.; Ohashi, P.S.; De Bono, J.S.; Mottaghy, F.M. Molecularly targeted therapies in cancer: A guide for the nuclear medicine physician. Eur. J. Nucl. Med. Mol. Imaging 2017, 44, 41–54. [Google Scholar] [CrossRef] [PubMed]
  13. Alwi, Z.B. The Use of SNPs in Pharmacogenomics Studies. Malays. J. Med. Sci. 2005, 12, 4–12. [Google Scholar] [PubMed]
  14. Bettaieb, A.; Paul, C.; Plenchette, S.; Shan, J.; Chouchane, L.; Ghiringhelli, F. Precision medicine in breast cancer: Reality or utopia? J. Transl. Med. 2017, 15, 139. [Google Scholar] [CrossRef] [PubMed]
  15. Bernier, J. Precision medicine for early breast cancer radiotherapy: Opening up new horizons? Crit. Rev. Oncol. Hematol. 2017, 113, 79–82. [Google Scholar] [CrossRef] [PubMed]
  16. Talens, F.; Jalving, M.; Gietema, J.A.; van Vugt, M.A. Therapeutic targeting and patient selection for cancers with homologous recombination defects. Expert Opin. Drug Discov. 2017, 12, 565–581. [Google Scholar] [CrossRef] [PubMed]
  17. Bhattacharya, P.; Abderrahman, B.; Jordan, V.C. Opportunities and challenges of long term anti-estrogenic adjuvant therapy: Treatment forever or intermittently? Expert Rev. Anticancer Ther. 2017, 17, 297–310. [Google Scholar] [CrossRef] [PubMed]
  18. Kayl, A.E.; Meyers, C.A. Side-effects of chemotherapy and quality of life in ovarian and breast cancer patients. Curr. Opin. Obstet. Gynecol. 2006, 18, 24–28. [Google Scholar] [CrossRef] [PubMed]
  19. So, W.K.W.; Chow, K.M.; Chan, H.Y.L.; Choi, K.C.; Wan, R.W.M.; Mak, S.S.S.; Chan, C.W.H. Quality of life and most prevalent unmet needs of Chinese breast cancer survivors at one year after cancer treatment. Eur. J. Oncol. Nurs. 2014, 18, 323–328. [Google Scholar] [CrossRef] [PubMed]
  20. Sullivan, C.W.; Leutwyler, H.; Dunn, L.B.; Cooper, B.A.; Paul, S.M.; Levine, J.D.; Hammer, M.; Conley, Y.P.; Miaskowski, C.A. Stability of Symptom Clusters in Patients with Breast Cancer Receiving Chemotherapy. J. Pain Symptom Manag. 2017. [Google Scholar] [CrossRef] [PubMed]
  21. Klemp, J.R.; Myers, J.S.; Fabian, C.J.; Kimler, B.F.; Khan, Q.J.; Sereika, S.M.; Stanton, A.L. Cognitive functioning and quality of life following chemotherapy in pre-and peri-menopausal women with breast cancer. Support. Care Cancer 2017, 1–9. [Google Scholar] [CrossRef] [PubMed]
  22. Oh, H.; Seo, Y.; Jeong, H.; Seo, W. The identification of multiple symptom clusters and their effects on functional performance in cancer patients. J. Clin. Nurs. 2012, 21, 2832–2842. [Google Scholar] [CrossRef] [PubMed]
  23. So, W.K.W.; Leung, D.Y.P.; Ho, S.S.M.; Lai, E.T.L.; Sit, J.W.H.; Chan, C.W.H. Associations between social support, prevalent symptoms and health-related quality of life in Chinese women undergoing treatment for breast cancer: A cross-sectional study using structural equation modelling. Eur. J. Oncol. Nurs. 2013, 17, 442–448. [Google Scholar] [CrossRef] [PubMed]
  24. Rosenberg, S.M.; Partridge, A.H. Premature menopause in young breast cancer: Effects on quality of life and treatment interventions. J. Thorac. Dis. 2013, 5, S55–S61. [Google Scholar] [CrossRef] [PubMed]
  25. Dohou, J.; Mouret-Reynier, M.A.; Kwiatkowski, F.; Arbre, M.; Herviou, P.; Pouget, M.; Abrial, C.; Penault-Llorca, F. A retrospective study on the onset of menopause after chemotherapy: Analysis of data extracted from the jean perrin comprehensive cancer center database concerning 345 young breast cancer patients diagnosed between 1994 and 2012. Oncology 2017, 92, 255–263. [Google Scholar] [CrossRef] [PubMed]
  26. Archer, D.F. Premature menopause increases cardiovascular risk. Climacteric 2009, 12, 26–31. [Google Scholar] [CrossRef] [PubMed]
  27. Myrehaug, S.; Pintilie, M.; Tsang, R.; Mackenzie, R.; Crump, M.; Chen, Z.; Sun, A.; Hodgson, D.C. Cardiac morbidity following modern treatment for Hodgkin lymphoma: Supra-additive cardiotoxicity of doxorubicin and radiation therapy. Leuk. Lymphoma 2008, 49, 1486–1493. [Google Scholar] [CrossRef] [PubMed]
  28. Harris, S.R. Differentiating the causes of spontaneous rib fracture after breast cancer. Clin. Breast Cancer 2016, 16, 431–436. [Google Scholar] [CrossRef] [PubMed]
  29. Knobf, M.T.; Jeon, S.; Smith, B.; Harris, L.; Thompson, S.; Stacy, M.R.; Insogna, K.; Sinusas, A.J. The Yale Fitness Intervention Trial in female cancer survivors: Cardiovascular and physiological outcomes. Heart Lung 2017, 46, 375–381. [Google Scholar] [CrossRef] [PubMed]
  30. Nourmoussavi, M.; Pansegrau, G.; Popesku, J.; Hammond, G.L.; Kwon, J.S.; Carey, M.S. Ovarian ablation for premenopausal breast cancer: A review of treatment considerations and the impact of premature menopause. Cancer Treat. Rev. 2017, 55, 26–35. [Google Scholar] [CrossRef] [PubMed]
  31. Winters-Stone, K.M.; Hilton, C.; Luoh, S.W.; Jacobs, P.; Faithfull, S.; Horak, F.B. Comparison of physical function and falls among women with persistent symptoms of chemotherapy-induced peripheral neuropathy. J. Clin. Oncol. 2016, 34, 130. [Google Scholar] [CrossRef]
  32. Winters-Stone, K.M.; Horak, F.; Jacobs, P.G.; Trubowitz, P.; Dieckmann, N.F.; Stoyles, S.; Faithfull, S. Falls, functioning, and disability among women with persistent symptoms of chemotherapy-induced peripheral neuropathy. J. Clin. Oncol. 2017, 35, 2604–2612. [Google Scholar] [CrossRef] [PubMed]
  33. Schraa, S.J.; Frerichs, K.A.; Agterof, M.J.; Hunting, J.C.B.; Los, M.; de Jong, P.C. Relative dose intensity as a proxy measure of quality and prognosis in adjuvant chemotherapy for breast cancer in daily clinical practice. Eur. J. Cancer 2017, 79, 152–157. [Google Scholar] [CrossRef] [PubMed]
  34. Cheng, K.K.F.; Wong, E.M.C.; Ling, W.M.; Chan, C.W.H.; Thompson, D.R. Measuring the symptom experience of Chinese cancer patients: A validation of the Chinese Version of the Memorial Symptom Assessment Scale. J. Pain Symptom Manag. 2009, 37, 44–57. [Google Scholar] [CrossRef] [PubMed]
  35. Libert, Y.; Dubruille, S.; Borghgraef, C.; Etienne, A.M.; Merckaert, I.; Paesmans, M.; Reynaert, C.; Roos, M.; Slachmuylder, J.L.; Vandenbossche, S.; et al. Vulnerabilities in older patients when cancer treatment is initiated: Does a cognitive impairment impact the two-year survival? PLoS ONE 2016, 11, e0159734. [Google Scholar] [CrossRef] [PubMed]
  36. Ahles, T.A.; Saykin, A.J. Candidate mechanisms for chemotherapy-induced cognitive changes. Nat. Rev. Cancer 2007, 7, 192–201. [Google Scholar] [CrossRef] [PubMed]
  37. Purkayastha, D.; Venkateswaran, C.; Nayar, K.; Unnikrishnan, U.G. Prevalence of depression in breast cancer patients and its association with their quality of life: A cross-sectional observational study. Indian J. Palliat. Care 2017, 23, 268–273. [Google Scholar] [CrossRef] [PubMed]
  38. Ho, S.S.M.; So, W.K.W.; Leung, D.Y.P.; Lai, E.T.L.; Chan, C.W.H. Anxiety, depression and quality of life in Chinese women with breast cancer during and after treatment: A comparative evaluation. Eur. J. Oncol. Nurs. 2013, 17, 877–882. [Google Scholar] [CrossRef] [PubMed]
  39. Boyette-Davis, J.A.; Walters, E.T.; Dougherty, P.M. Mechanisms involved in the development of chemotherapy-induced neuropathy. Pain Manag. 2015, 5, 285–296. [Google Scholar] [CrossRef] [PubMed]
  40. Leysen, L.; Beckwée, D.; Nijs, J.; Pas, R.; Bilterys, T.; Vermeir, S.; Adriaenssens, N. Risk factors of pain in breast cancer survivors: A systematic review and meta-analysis. Support. Care Cancer 2017. [Google Scholar] [CrossRef] [PubMed]
  41. Crombag, M.R.; Joerger, M.; Thürlimann, B.; Schellens, J.H.; Beijnen, J.H.; Huitema, A.D. Pharmacokinetics of selected anticancer drugs in elderly cancer patients: Focus on breast cancer. Cancers (Basel) 2016, 8, 6. [Google Scholar] [CrossRef] [PubMed]
  42. Ashdown, M.L.; Robinson, A.P.; Yatomi-Clarke, S.L.; Ashdown, M.L.; Allison, A.; Abbott, D.; Markovic, S.N.; Coventry, B.J. Chemotherapy for late-stage cancer patients: Meta-analysis of complete response rates. F1000Res 2015, 4, 232. [Google Scholar] [CrossRef] [PubMed]
  43. De Bruin, E.C.; Whiteley, J.L.; Corcoran, C.; Kirk, P.M.; Fox, J.C.; Armisen, J.; Lindemann, J.P.O.; Schiavon, G.; Ambrose, H.J.; Kohlmann, A. Accurate detection of low prevalence AKT1 E17K mutation in tissue or plasma from advanced cancer patients. PLoS ONE 2017, 12, e0175779. [Google Scholar] [CrossRef] [PubMed]
  44. Fruman, D.A.; Rommel, C. PI3K and cancer: Lessons, challenges and opportunities. Nat. Rev. Drug Discov. 2014, 13, 140–156. [Google Scholar] [CrossRef] [PubMed]
  45. Xu, B.; Krie, A.; De, P.; Williams, C.; Elsey, R.; Klein, J.; Leyland-Jones, B. Utilizing tumor and plasma liquid biopsy in treatment decision making for an estrogen receptor-positive advanced breast cancer patient. Cureus 2017, 9, e1408. [Google Scholar] [CrossRef] [PubMed]
  46. Rudolph, M.; Anzeneder, T.; Schulz, A.; Beckmann, G.; Byrne, A.T.; Jeffers, M.; Pena, C.; Politz, O.; Köchert, K.; Vonk, R.; et al. AKT1 (E17K) mutation profiling in breast cancer: Prevalence, concurrent oncogenic alterations, and blood-based detection. BMC Cancer 2016, 16, 622. [Google Scholar] [CrossRef] [PubMed]
  47. Andersen, J.N.; Sathyanarayanan, S.; Di Bacco, A.; Chi, A.; Zhang, T.; Chen, A.H.; Dolinski, B.; Kraus, M.; Roberts, B.; Arthur, W.; et al. Pathway-based identification of biomarkers for targeted therapeutics: Personalized oncology with PI3K pathway inhibitors. Sci. Transl. Med. 2010, 2, 43ra55. [Google Scholar] [CrossRef] [PubMed]
  48. Matikas, A.; Foukakis, T.; Bergh, J. Tackling endocrine resistance in ER-positive HER2-negative advanced breast cancer: A tale of imprecision medicine. Crit. Rev. Oncol. Hematol. 2017, 114, 91–101. [Google Scholar] [CrossRef] [PubMed]
  49. Turnbull, A.K.; Arthur, L.M.; Renshaw, L.; Larionov, A.A.; Kay, C.; Dunbier, A.K.; Thomas, J.S.; Dowsett, M.; Sims, A.H.; Dixon, J.M. Accurate prediction and validation of response to endocrine therapy in breast cancer. J. Clin. Oncol. 2015, 33, 2270–2278. [Google Scholar] [CrossRef] [PubMed]
  50. Smith, I.; Procter, M.; Gelber, R.D.; Guillaume, S.; Feyereislova, A.; Dowsett, M.; Goldhirsch, A.; Untch, M.; Mariani, G.; Baselga, J.; et al. HERA study team. 2-year follow-up of trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer: A randomised controlled trial. Lancet 2007, 369, 29–36. [Google Scholar] [CrossRef]
  51. Timmer, M.; Werner, J.M.; Röhn, G.; Ortmann, M.; Blau, T.; Cramer, C.; Stavrinou, P.; Krischek, B.; Mallman, P.; Goldbrunner, R. Discordance and conversion rates of progesterone-, estrogen-, and her2/neu-receptor status in primary breast cancer and brain metastasis mainly triggered by hormone therapy. Anticancer Res. 2017, 37, 4859–4865. [Google Scholar] [PubMed]
  52. Shachar, S.S.; Fried, G.; Drumea, K.; Shafran, N.; Bar-Sela, G. Physicians’ considerations for repeat biopsy in patients with recurrent metastatic breast cancer. Clin. Breast Cancer 2016, 16, e43–e48. [Google Scholar] [CrossRef] [PubMed]
  53. Chen, W.; Li, X.; Zhu, L.; Liu, J.; Xu, W.; Wang, P. Preclinical and clinical applications of specific molecular imaging for HER2-positive breast cancer. Cancer Biol. Med. 2017, 14, 271–280. [Google Scholar] [CrossRef] [PubMed]
  54. Nie, H.; Shu, H.; Vartak, R.; Milstein, A.C.; Mo, Y.; Hu, X.; Fang, H.; Shen, L.; Ding, Z.; Lu, J.; et al. Mitochondrial common deletion, a potential biomarker for cancer occurrence, is selected against in cancer background: A meta-analysis of 38 studies. PLoS ONE 2013, 8, e67953. [Google Scholar] [CrossRef] [PubMed]
  55. Shen, L.; Fang, H.; Chen, T.; He, J.; Zhang, M.; Wei, X.; Xin, Y.; Jiang, Y.; Ding, Z.; Ji, J.; et al. Evaluating mitochondrial DNA in cancer occurrence and development. Ann. N. Y. Acad. Sci. 2010, 1201, 26–33. [Google Scholar] [CrossRef] [PubMed]
  56. Singh, K.K.; Russell, J.; Sigala, B.; Zhang, Y.; Williams, J.; Keshav, K.F. Mitochondrial DNA determines the cellular response to cancer therapeutic agents. Oncogene 1999, 18, 6641–6646. [Google Scholar] [CrossRef] [PubMed]
  57. Guerra, F.; Perrone, A.M.; Kurelac, I.; Santini, D.; Ceccarelli, C.; Cricca, M.; Zamagni, C.; De Iaco, P.; Gasparre, G. Mitochondrial DNA mutation in serous ovarian cancer: Implications for mitochondria-coded genes in chemoresistance. J. Clin. Oncol. 2012, 30, e373–e378. [Google Scholar] [CrossRef] [PubMed]
  58. Hosokawa, Y.; Masaki, N.; Takei, S.; Horikawa, M.; Matsushita, S.; Sugiyama, E.; Ogura, H.; Shiiya, N.; Setou, M. Recurrent triple-negative breast cancer (TNBC) tissues contain a higher amount of phosphatidylcholine (32:1) than non-recurrent TNBC tissues. PLoS ONE 2017, 12, e0183724. [Google Scholar] [CrossRef] [PubMed]
  59. Secreto, G.; Muti, P.; Sant, M.; Meneghini, E.; Krogh, V. Medical ovariectomy in menopausal breast cancer patients with high testosterone levels. Endocr. Relat. Cancer 2017, 24, C21–C29. [Google Scholar] [CrossRef] [PubMed]
  60. Pachmann, K.; Camara, O.; Kroll, T.; Gajda, M.; Gellner, A.K.; Wotschadlo, J.; Runnebaum, I.B. Efficacy control of therapy using circulating epithelial tumor cells (CETC) as “liquid biopsy”: Trastuzumab in HER2/neu-positive breast carcinoma. J. Cancer Res. Clin. Oncol. 2011, 137, 1317–1327. [Google Scholar] [CrossRef] [PubMed]
  61. Gulbahce, N.; Magbanua, M.J.M.; Chin, R.; Agarwal, M.R.; Luo, X.; Liu, J.; Hayden, D.M.; Mao, Q.; Ciotlos, S.; Li, Z.; et al. Quantitative whole genome sequencing of circulating tumor cells enables personalized combination therapy of metastatic cancer. Cancer Res. 2017, 77, 4530–4541. [Google Scholar] [CrossRef] [PubMed]
  62. Wheler, J.J.; Atkins, J.T.; Janku, F.; Moulder, S.L.; Stephens, P.J.; Yelensky, R.; Valero, V.; Miller, V.; Kurzrock, R.; Meric-Bernstam, F. Presence of both alterations in FGFR/FGF and PI3K/AKT/mTOR confer improved outcomes for patients with metastatic breast cancer treated with PI3K/AKT/mTOR inhibitors. Oncoscience 2016, 3, 164–172. [Google Scholar] [CrossRef] [PubMed]
  63. De Souza, J.A.; Olopadem, O.I. CYP2D6 genotyping and tamoxifen: An unfinished story in the quest for personalized medicine. Semin. Oncol. 2011, 38, 263–273. [Google Scholar] [CrossRef] [PubMed]
  64. Rae, J.M.; Sikora, M.J.; Henry, N.L.; Li, L.; Kim, S.; Oesterreich, S.; Skaar, T.C.; Nguyen, A.T.; Desta, Z.; Storniolo, A.M.; et al. COBRA investigators. Cytochrome P450 2D6 activity predicts discontinuation of tamoxifen therapy in breast cancer patients. Pharm. J. 2009, 9, 258–264. [Google Scholar] [CrossRef]
  65. Marcath, A.L.; Deal, A.M.; Van Wieren, E.; Danko, W.; Walko, C.M.; Ibrahim, J.G.; Weck, K.E.; Jones, D.R.; Desta, Z.; McLeod, H.L.; et al. Comprehensive assessment of cytochromes P450 and transporter genetics with endoxifen concentration during tamoxifen treatment. Pharm. Genom. 2017, 27, 402–409. [Google Scholar] [CrossRef] [PubMed]
  66. Macfarlane, L.A.; Murphy, P.R. MicroRNA: Biogenesis, function and role in cancer. Curr. Genom. 2010, 11, 537–561. [Google Scholar] [CrossRef] [PubMed]
  67. Yang, F.; Zhang, T.T.; Li, S.S.; Song, P.; Zhang, K.; Guan, Q.Y.; Kang, B.; Xu, J.J.; Chen, H.Y. Endogenous microRNA-triggered and real-time monitored drug release via cascaded energy transfer payloads. Anal. Chem. 2017, 89, 10239–10247. [Google Scholar] [CrossRef] [PubMed]
  68. Kleinhans, R.; Brischwein, M.; Wang, P.; Becker, B.; Demmel, F.; Schwarzenberger, T.; Zottmann, M.; Wolf, P.; Niendorf, A.; Wolf, B. Sensor-based cell and tissue screening for personalized cancer chemotherapy. Med. Biol. Eng. Comput. 2012, 50, 117–126. [Google Scholar] [CrossRef] [PubMed]
  69. Zu, X.L.; Guppy, M. Cancer metabolism: Facts, fantasy, and fiction. Biochem. Biophys. Res. Commun. 2004, 313, 459–465. [Google Scholar] [CrossRef] [PubMed]
  70. Michard, F. A sneak peek into digital innovations and wearable sensors for cardiac monitoring. J. Clin. Monit. Comput. 2017, 31, 253–259. [Google Scholar] [CrossRef] [PubMed]
  71. Nass, N.; Sel, S.; Ignatov, A.; Roessner, A.; Kalinski, T. Oxidative stress and glyoxalase I activity mediate dicarbonyl toxicity in MCF-7 mamma carcinoma cells and a tamoxifen resistant derivative. Biochim. Biophys. Acta 2016, 1860, 1272–1280. [Google Scholar] [CrossRef] [PubMed]
  72. Naha, P.C.; Lau, K.C.; Hsu, J.C.; Hajfathalian, M.; Mian, S.; Chhour, P.; Uppuluri, L.; McDonald, E.S.; Maidment, A.D.; Cormode, D.P. Gold silver alloy nanoparticles (GSAN): An imaging probe for breast cancer screening with dual-energy mammography or computed tomography. Nanoscale 2016, 8, 13740–13754. [Google Scholar] [CrossRef] [PubMed]
  73. Scott, J.G.; Berglund, A.; Schell, M.J.; Mihaylov, I.; Fulp, W.J.; Yue, B.; Welsh, E.; Caudell, J.J.; Ahmed, K.; Strom, T.S.; et al. A genome-based model for adjusting radiotherapy dose (GARD): A retrospective, cohort-based study. Lancet Oncol. 2017, 18, 202–211. [Google Scholar] [CrossRef]
  74. Spratt, D.E.; Wahl, D.R.; Lawrence, T.S. Genomic-adjusted radiation dose. Lancet Oncol. 2017, 18, e127. [Google Scholar] [CrossRef]
  75. Cheng, H.; Sit, J.W.H.; Chan, C.W.H.; So, W.K.W.; Choi, K.C.; Cheng, K.K.F. Social support and quality of life among Chinese breast cancer survivors: Findings from a mixed methods study. Eur. J. Oncol. Nurs. 2013, 17, 788–796. [Google Scholar] [CrossRef] [PubMed]
  76. Okeke, T.; Anyaehie, U.; Ezenyeaku, C. Premature menopause. Ann. Med. Health Sci. Res. 2013, 3, 90–95. [Google Scholar] [CrossRef] [PubMed]
  77. Abrahamson, P.E.; Tworoger, S.S.; Aiello, E.J.; Bernstein, L.; Ulrich, C.M.; Gilliland, F.D.; Stanczyk, F.Z.; Baumgartner, R.; Baumgartner, K.; et al. Associations between the CYP17, CYPIB1, COMT and SHBG polymorphisms and serum sex hormones in post-menopausal breast cancer survivors. Breast Cancer Res. Treat. 2007, 105, 45–54. [Google Scholar] [CrossRef] [PubMed]
  78. Riancho, J.A.; Valero, C.; Zarrabeitia, M.T.; García-Unzueta, M.T.; Amado, J.A.; González-Macías, J. Genetic polymorphisms are associated with serum levels of sex hormone binding globulin in postmenopausal women. BMC Med. Genet. 2008, 9, 112. [Google Scholar] [CrossRef] [PubMed]
  79. Cordts, E.B.; Santos, A.A.; Peluso, C.; Bianco, B.; Barbosa, C.P.; Christofolini, D.M. Risk of premature ovarian failure is associated to the PvuII polymorphism at estrogen receptor gene ESR1. J. Assist. Reprod. Genet. 2012, 29, 1421–1425. [Google Scholar] [CrossRef] [PubMed]
  80. Swain, S.M.; Jeong, J.H.; Wolmark, N. Amenorrhea from breast cancer therapy—Not a matter of dose. N. Engl. J. Med. 2010, 363, 2268–2270. [Google Scholar] [CrossRef] [PubMed]
  81. Kus, T.; Aktas, G.; Kalender, M.E.; Demiryurek, A.T.; Ulasli, M.; Oztuzcu, S.; Sevinc, A.; Kul, S.; Camci, C. Polymorphism of CYP3A4 and ABCB1 genes increase the risk of neuropathy in breast cancer patients treated with paclitaxel and docetaxel. Onco Targets Ther. 2016, 9, 5073–5080. [Google Scholar] [CrossRef] [PubMed]
  82. Sundar, R.; Jeyasekharan, A.D.; Pang, B.; Soong, R.C.; Kumarakulasinghe, N.B.; Ow, S.G.; Ho, J.; Lim, J.S.; Tan, D.S.; Wilder-Smith, E.P.; et al. Low levels of NDRG1 in nerve tissue are predictive of severe paclitaxel-induced neuropathy. PLoS ONE 2016, 11, e0164319. [Google Scholar] [CrossRef] [PubMed]
  83. Lam, S.W.; Frederiks, C.N.; van der Straaten, T.; Honkoop, A.H.; Guchelaar, H.J.; Boven, E. Genotypes of CYP2C8 and FGD4 and their association with peripheral neuropathy or early dose reduction in paclitaxel-treated breast cancer patients. Br. J. Cancer 2016, 115, 1335–1342. [Google Scholar] [CrossRef] [PubMed]
  84. Loh, K.P.; Janelsins, M.C.; Mohile, S.G.; Holmes, H.M.; Hsu, T.; Inouye, S.K.; Karuturi, M.S.; Kimmick, G.G.; Lichtman, S.M.; Magnuson, A.; et al. Chemotherapy-related cognitive impairment in older patients with cancer. J. Geriatr. Oncol. 2016, 7, 270–280. [Google Scholar] [CrossRef] [PubMed]
  85. Myers, J.S.; Koleck, T.A.; Sereika, S.M.; Conley, Y.P.; Bender, C.M. Perceived cognitive function for breast cancer survivors: Association of genetic and behaviorally related variables for inflammation. Support. Care Cancer 2017, 25, 2475–2484. [Google Scholar] [CrossRef] [PubMed]
  86. Fiorentino, L.; Rissling, M.; Liu, L.; Ancoli-Israel, S. The symptom cluster of sleep, fatigue and depressive symptoms in breast cancer patients: Severity of the problem and treatment options. Drug Discov. Today Dis. Model. 2011, 8, 167–173. [Google Scholar] [CrossRef] [PubMed]
  87. Thornton, L.M.; Andersen, B.L.; Blakely, W.P. The pain, depression, and fatigue symptom cluster in advanced breast cancer: Covariation with the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system. Health Psychol. 2010, 29, 333–337. [Google Scholar] [CrossRef] [PubMed]
  88. Dooley, L.N.; Ganz, P.A.; Cole, S.W.; Crespi, C.M.; Bower, J.E. Val66Met BDNF polymorphism as a vulnerability factor for inflammation-associated depressive symptoms in women with breast cancer. J. Affect. Disord. 2016, 197, 43–50. [Google Scholar] [CrossRef] [PubMed]
  89. Smith, H.R. Depression in cancer patients: Pathogenesis, implications and treatment (Review). Oncol. Lett. 2015, 9, 1509–1514. [Google Scholar] [CrossRef] [PubMed]
  90. DiSipio, T.; Rye, S.; Newman, B.; Hayes, S. Incidence of unilateral arm lymphoedema after breast cancer: A systematic review and meta-analysis. Lancet Oncol. 2013, 14, 500–515. [Google Scholar] [CrossRef]
  91. Ryu, E.; Yim, S.Y.; Do, H.J.; Lim, J.Y.; Yang, E.J.; Shin, M.J.; Lee, S.M. Risk of secondary lymphedema in breast cancer survivors is related to serum phospholipid fatty acid desaturation. Support. Care Cancer 2016, 24, 3767–3774. [Google Scholar] [CrossRef] [PubMed]
  92. Galley, H.F.; McCormick, B.; Wilson, K.L.; Lowes, D.A.; Colvin, L.; Torsney, C. Melatonin limits paclitaxel-induced mitochondrial dysfunction in vitro and protects against paclitaxel-induced neuropathic pain in the rat. J. Pineal Res. 2017, 63. [Google Scholar] [CrossRef] [PubMed]
  93. Ozben, T. Antioxidant supplementation on cancer risk and during cancer therapy: An update. Curr. Top. Med. Chem. 2015, 15, 170–178. [Google Scholar] [CrossRef] [PubMed]
  94. D’Andrea, G.M. Use of antioxidants during chemotherapy and radiotherapy should be avoided. CA Cancer J. Clin. 2005, 55, 319–321. [Google Scholar] [CrossRef] [PubMed]
  95. Lissoni, P.; Meregalli, S.; Nosetto, L.; Barni, S.; Tancini, G.; Fossati, V.; Maestroni, G. Increased survival time in brain glioblastomas by a radioneuroendocrine strategy with radiotherapy plus melatonin compared to radiotherapy alone. Oncology 1996, 53, 43–46. [Google Scholar] [CrossRef] [PubMed]
  96. Misirlioglu, C.H.; Erkal, H.; Elgin, Y.; Ugur, I.; Altundag, K. Effect of concomitant use of pentoxifylline and alpha-tocopherol with radiotherapy on the clinical outcome of patients with stage IIIB non-small cell lung cancer: A randomized prospective clinical trial. Med. Oncol. 2006, 23, 185–189. [Google Scholar] [CrossRef]
  97. Rizvi, S.; Raza, S.T.; Ahmed, F.; Ahmad, A.; Abbas, S.; Mahdi, F. The role of vitamin e in human health and some diseases. Sultan Qaboos Univ. Med. J. 2014, 14, e157–e165. [Google Scholar] [PubMed]
  98. Araki, T.; Sasaki, Y.; Milbrandt, J. Increased nuclear NAD biosynthesis and SIRT1 activation prevent axonal degeneration. Science 2004, 305, 1010–1013. [Google Scholar] [CrossRef] [PubMed]
  99. Hamity, M.V.; White, S.R.; Walder, R.Y.; Schmidt, M.S.; Brenner, C.; Hammond, D.L. Nicotinamide riboside, a form of vitamin B3 and NAD+ precursor, relieves the nociceptive and aversive dimensions of paclitaxel-induced peripheral neuropathy in female rats. Pain 2017, 158, 962–972. [Google Scholar] [CrossRef] [PubMed]
  100. Wang, X.; Zhang, Z.F.; Zheng, G.H.; Wang, A.M.; Sun, C.H.; Qin, S.P.; Zhuang, J.; Lu, J.; Ma, D.F.; Zheng, Y.L. The inhibitory effects of purple sweet potato color on hepatic inflammation is associated with restoration of NAD+ levels and attenuation of NLRP3 inflammasome activation in high-fat-diet-treated mice. Molecules 2017, 22, E1315. [Google Scholar] [CrossRef] [PubMed]
  101. Makari-Judson, G.; Braun, B.; Jerry, D.J.; Mertens, W.C. Weight gain following breast cancer diagnosis: Implication and proposed mechanisms. World J. Clin. Oncol. 2014, 5, 272–282. [Google Scholar] [CrossRef] [PubMed]
  102. Sadim, M.; Xu, Y.; Selig, K.; Paulus, J.; Uthe, R.; Agarwl, S.; Dubin, I.; Oikonomopoulou, P.; Zaichenko, L.; McCandlish, S.A.; et al. A prospective evaluation of clinical and genetic predictors of weight changes in breast cancer survivors. Cancer 2017, 123, 2413–2421. [Google Scholar] [CrossRef] [PubMed]
  103. Loughney, L.; West, M.A.; Kemp, G.J.; Grocott, M.P.; Jack, S. Exercise intervention in people with cancer undergoing neoadjuvant cancer treatment and surgery: A systematic review. Eur. J. Surg. Oncol. 2016, 42, 28–38. [Google Scholar] [CrossRef] [PubMed]

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