Cancer Cell Secretome in Driving Breast Cancer Progression: History
Please note this is an old version of this entry, which may differ significantly from the current revision.

Breast cancer is a complex disease that remains a significant public health challenge. The breast cancer cells secrete various substances collectively known as the secretome, which include proteins, lipids, and nucleic acids that contribute to the growth and spread of breast cancer. The secretome plays a crucial role in the development and progression of breast cancer by modifying signaling pathways and creating an environment supporting cancer growth while evading the immune system. Additionally, the secretome is responsible for the development of resistance to cancer drugs, making it a significant challenge for effective treatment.

  • metastasis
  • secretome
  • immune modulation
  • tumor microenvironment
  • drug resistance
  • therapeutic targets

1. Introduction

Breast cancer is a disease that exhibits genetic and clinical heterogeneities with multiple cellular origins, encompassing various subtypes [1]. Breast cancer is the most diagnosed and life-threatening malignancy in women and the leading cause of cancer death in women worldwide [2]. According to GLOBOCAN 2020, the estimated prevalence of breast cancer in both sexes and for all ages is 7.79 million in 5 years, ranking number one in incidence at 2.26 million worldwide and fourth in the mortality rate [2]. In the United States, breast cancer is the second most significant cause of death by cancer among women overall, but ranks highest among Black and Hispanic women [3][4]. A localized breast cancer incidence has a good prognosis, with a five-year survival rate of more than 80% [5]. Usually, metastatic breast cancer is rare at initial diagnosis (around 6–7%). However, approximately 30% of patients diagnosed with early stages will eventually acquire recurrent or metastatic breast cancer [5][6][7]. Cases of patients with recurrent breast cancer are often fatal; survival is typically within five years of diagnosis [5].
Breast cancer has undergone several classifications over time, but the most used and widely accepted classification system of breast cancer involves the assessment of the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER2) hormone receptors via immunohistochemical analysis. This renders breast cancer into four main subtypes: luminal A, luminal B, HER2-enriched, and basal-like [8][9]. Luminal-like breast cancer subtypes, characterized by ER and/or PR on the surface of breast cancer cells, are the most common breast cancer [10][11]. Luminal breast cancers are generally considered less aggressive than other breast cancer subtypes, such as the basal-like that do not express hormone receptors. Between the two Luminal subtypes, Luminal A breast cancers are less aggressive and have a better prognosis [12]. HER2-positive subtype overexpresses HER2, which accounts for about 20–25% of all breast cancer. Basal-like or triple-negative breast cancer (TNBC) lacks the above three key receptors. HER2 and TNBC tend to be more aggressive than other breast cancer subtypes, and are associated with a higher risk of recurrence and poorer prognosis if left untreated. Standard treatments for all subtypes would be surgical resection, radiotherapy, and chemotherapy, whereas targeted and immunotherapy would be the options to treat the specific subtypes [13][14][15]. This classification is, therefore, crucial to tailor specified treatment for the breast cancer patient. Recent therapeutic approaches have emerged, such as targeting metabolic pathways, immunotherapy, conjugated antibodies, and vaccines [16]. Therefore, it is crucial to comprehend the onset and course of breast cancer pathogenesis to create interventions that can improve cancer patients’ health and well-being.
While there have been significant advances and breakthroughs in breast cancer research, there is still much to learn about this disease. This is partly due to the complexity and heterogeneity of the disease. In recent years, breast cancer’s onset and metastatic properties have been linked to the extracellular moieties surrounding the tumor cells [17][18][19]. This includes the proteins secreted by cancer cells and other cellular constituents within the tumor microenvironment (TME). These secreted molecules released by tumor cells (termed the secretome) could influence the therapeutic response and clinical outcome, such as gaining resistance to cancer drugs and therapies, making its pathological evaluation indispensable in cancer management.

2. The Topography of Breast Cancer Secretome

The secretome can be defined as both soluble and insoluble factors that are released or secreted into the extracellular environment. These include chemokines, cytokines, growth factors, coagulation factors, hormones, enzymes, glycoproteins, and nucleic acids. These factors can be secreted as naked components or cargo in vesicular compartments, such as extracellular vesicles (EVs). The latest human secretome atlas project highlighted that 2641 genes encode proteins predicted to be secreted in humans [20]. This number observably varies on cellular perturbation and disease development. Studies have shown that cancer cells, for example, have abnormal secretomes compared to their non-cancerous counterparts and therefore have functional impacts on cancer development [21][22][23]. The secretome is typically identified by high-throughput omics platforms, particularly protein identification by mass-spectrometry-based analysis.
The most basic and extensively researched secretome type is the cancer cell-derived conditioned medium (CM) of cancer cells grown in 2D or 3D culture [24]. Typically, serum proteins and scaffold-free (formation of spheroids without hydrogels, laminin, collagen, or ECM gel) are removed from the medium, and then culturing the cancer cells in serum-starved media in a short period (24 or 48 h). The medium is collected and centrifuged to remove apoptotic bodies, concentrated, and further subjected to secretome identification. This method’s benefits include obtaining relatively large sample sizes and comparing data quantitatively following cancer cell modification [25][26]. In an in vivo setting, on the other hand, the cancer cell secretome, including breast cancer, can be isolated from the bodily fluids of the cancer patient. Often time, for most cancer types, serum or plasma is the primary source of secretomic studies.
In breast cancer patients, there are additional essential avenues to breast cancer research in that several localities of the breast ductal/lobular system are enriched with the secretome population. For example, the proteins can be secreted or shed by the tumor or stromal cells into the tumor interstitial fluid (TIF). This fluid, which surrounds the stromal and tumor cells, is thought to contain signaling constituents crucial for intercellular communication and the growth of the tumor. To obtain this TIF, small fragments of fresh tumor tissue are cultured in a buffered solution [27]. After centrifugation, the secretome will be released into the supernatant [28]. In addition, the secretome fractions from nipple aspirate fluid (NAF), pleural effusion (PE), stool, and ascites are other types of fluids that can be analyzed and have been previously shown to contain cancer-specific proteins as compared to the baseline patient. NAF extraction has been accomplished with varying success rates by using either a breast pump, massage, warming of the breast or combinations of these methods [29][30]. The release of NAF into the ducts could be enhanced by administering nasal oxytocin, increasing the yield of NAF in breast cancer patients [31]. It is known that breast cancer spreads into the pleural space via lymph vessels [32]. Hence, the PE sample is withdrawn from this pleural space localized between the inside of the chest wall and the outside of the lung via thoracentesis. Studies have shown that the gut microbiota induces multiple pathways linked to breast tumor growth [33][34] through endogenous estrogen regulation and systemic inflammation activation [33][35][36][37]. Therefore, stool samples are subjected to secretome studies that are usually extracted using a fecal swab test kit. Malignant ascites, a severe occurrence in cancer patients, are typically signs of late-stage cancer, particularly in those with stage IV breast cancer. Paracentesis is used to drain ascites from the abdominal cavity [38][39]. Overall, the breast components have the potential to add another essential avenue to the efforts to advance breast cancer research.

3. The Crosstalk between Cancer Cell Secretome and the Tumor Microenvironment

The tissue secretome is markedly changed during cancer development compared to normal tissue. The aberrant gene mutations in cancer cells cause high protein synthesis and secretion demand. The increased secretion levels resulted in the alteration of critical processes that augment tumor growth. The release of the secretome also could modulate the cancer extracellular space, particularly the TME behavior. The TME is an ecosystem that includes a heterogenous group of invading and resident host cells within a body surrounding the tumor [40]. TME composition is complex and varies according to tumor type.
Nevertheless, its hallmark features consist of cancer stem cells (CSC), immune cells, extracellular matrix (ECM), blood vessels, and cancer-associated fibroblast (CAFs) [41][42]. In the early onset of cancer, reciprocal heterotypic paracrine signaling between tumor cells and other TME components triggers a cascade of biochemical and biomechanical changes, leading to a dynamic interaction between TME components. The prerequisite of malignancy for many solid cancers is the alteration of ECM. This involves the secretion of ECM remodeling enzymes by newly transformed tumor cells to degrade the basement membrane, which provides a conducive environment for tumor invasion.
During malignancy, the stroma will undergo alterations to incite growth, invasion, and metastasis of cancer cells. These changes include CAF formation, which comprises a significant portion of the reactive tissue stroma and is critical in regulating tumor progression. The rearrangement of TME components via dynamic and mutual crosstalk is thought to drive tumor fitness and metastatic potentials [40][43][44]. The relationship between the components of TME also imposes a varying degree of response to therapy and drug resistance [45][46]. Most cancer types demonstrated fibrotic or rigid TME architecture [47][48]. Other TMEs have a more vascular microenvironment compacted with blood vessels [49][50]. The different architecture and variety of components of TMEs may also obscure the delivery of drugs to reach cancer cells [51].

4. Targeting the Breast Cancer Cell Secretome

Extensive studies of the breast cancer secretome have identified several potential targets for new cancer therapies, including antibodies or small molecules that can block the activity of specific proteins in the secretome [52][53]. In addition, analysis of the breast cancer secretome may also be useful for developing new biomarkers that can help for early detection and predict the likelihood of cancer recurrence or response to therapy. Therefore, it is imperative to develop novel therapeutic approaches to target secreted factors that are released into TME in order to prevent chemoresistance and relapse or enhance anti-tumor immunity. Several approaches have been used to target unique secretomes or constituents responsible for the secretion in breast cancer cells. For example, targeting the HER2 receptor using the FDA-approved monoclonal antibody trastuzumab to block its signaling pathway has been deemed efficacious for early and advanced breast cancer treatment [54]. Another FDA-approved alternative with the HER2 inhibitor lapatinib led to changes in the breast cancer cell secretome, promoting immune cell infiltration and activation [55][56]. The study found that lapatinib treatment led to an increase in the secretion of chemokines, such as CCL5 and CXCL10, that recruit immune cells, as well as an increase in the secretion of cytokines that activate immune cells, such as IFN-γ and TNF-α.
Another approach in targeting secretome is using drugs that block specific molecules’ secretion rate, such as IL-6, to reduce breast cancer proliferation. In breast cancer, the IL-6 signaling axis is a promising therapeutic target since it promotes growth and invasion, mediates the spread of metastatic capabilities, and is associated with poor prognosis [57][58]. Anti-IL-6 monoclonal antibodies such as sirukumab, olokizumab, MEDI5117, and clazakizumab have been used as inhibitors of the IL-6/JAK/STAT3 signaling pathway in various cancers. Still, the FDA has yet to approve these drugs for breast cancer treatment [58]. Reports also show that the secretome can be induced by targeted therapy with kinase inhibitors, resulting in significant alterations in the expressed secretome and enhanced drug resistance [59]. However, the study was performed in melanoma and lung cancer models, but the observation could be transferable to breast cancer.
Targeting the epidermal growth factor receptor (EGFR) inhibitor in breast cancer with gefitinib was found to reduce the secretion of several proteins that promote tumor angiogenesis and invasion, including vascular endothelial growth factor (VEGF) and interleukin-8 (IL-8) [60]. The study also found that treatment with gefitinib increased the tumor suppressor protein thrombospondin-1 (TSP-1) secretion, which can inhibit tumor angiogenesis and promote apoptosis. Reports of other approved drugs targeting the secretome or TME components are listed in Table 1:
Table 1. Reports of drugs targeting the components of TME.
Breast cancer is a complex disease with a high recurrent rate. Drug combination therapy and precision medicine have emerged as promising strategies for improving treatment outcomes and reducing the risk of relapse [70][71][72]. The high relapse rate in breast cancer is caused by acquired resistance, which suggests the need for combination therapy [73]. Targeting one specialized microenvironment may lead to changes in other TME-related pathways because TME comprises numerous cells that frequently overlap and communicate. Therefore, a combination therapy targeting a specific microenvironment or niche may improve cancer treatment. Drug combination therapy involves using two or more drugs with different mechanisms of action to target multiple pathways involved in tumor survival and growth. This approach can improve treatment outcomes by enhancing the effectiveness of individual drugs, reducing the risk of drug resistance, and minimizing toxicity. Common practice would be the combination of chemotherapy and targeted therapy which has been shown to improve survival outcomes of patients compared to chemotherapy alone. For example, curcuminoid, a phenolic compound that has been utilized as a therapeutic agent in combination with chemotherapy, demonstrated enhanced efficacy in terms of reduced adverse effects and improved life quality in patients with solid tumors such as colorectal, gastric, and breast cancer in a phase II double-blind, randomized study [74][75][76][77].
The precision medicine approach would be tailoring treatment to the individual based on specific cancer characteristics, such as specific genetic mutations such as BRCA1/BRCA2 or the expression of specific biomarkers [78]. For example, the use of poly (ADP-ribose) polymerase (PARP) inhibitors has shown promising results in patients with BRCA mutations, which are associated with defects in DNA repair [79]. PARP inhibitors can block an alternative DNA repair pathway in these patients, leading to breast cancer cell death. In addition, emerging research suggests that combining precision medicine approaches with drug combination therapy may improve treatment outcomes and reduce the risk of relapse [80]. For example, combining a PARP inhibitor with a checkpoint inhibitor, pembrolizumab, enhances the immune system’s ability to target improved treatment outcomes in patients with BRCA-mutated breast cancer [79].
Understanding the landscape of breast cancer cell secretomes is essential for developing new cancer therapies. By targeting specific proteins involved in cancer cell signaling, researchers may be able to create more effective treatments that can slow or halt tumor growth. In addition, understanding the breast cancer cell secretome may also lead to the development of new diagnostic tools that can detect cancer earlier.

This entry is adapted from the peer-reviewed paper 10.3390/cancers15092653

References

  1. Sørlie, T. Molecular Portraits of Breast Cancer: Tumour Subtypes as Distinct Disease Entities. Eur. J. Cancer 2004, 40, 2667–2675.
  2. Cancer Today. Available online: http://gco.iarc.fr/today/home (accessed on 28 September 2022).
  3. Giaquinto, A.N.; Miller, K.D.; Tossas, K.Y.; Winn, R.A.; Jemal, A.; Siegel, R.L. Cancer Statistics for African American/Black People 2022. CA. Cancer J. Clin. 2022, 72, 202–229.
  4. Giaquinto, A.N.; Sung, H.; Miller, K.D.; Kramer, J.L.; Newman, L.A.; Minihan, A.; Jemal, A.; Siegel, R.L. Breast Cancer Statistics, 2022. CA. Cancer J. Clin. 2022, 72, 524–541.
  5. Allemani, C.; Sant, M.; Weir, H.K.; Richardson, L.C.; Baili, P.; Storm, H.; Siesling, S.; Torrella-Ramos, A.; Voogd, A.C.; Aareleid, T.; et al. Breast Cancer Survival in the US and Europe: A CONCORD High-Resolution Study. Int. J. Cancer 2013, 132, 1170–1181.
  6. Redig, A.J.; McAllister, S.S. Breast Cancer as a Systemic Disease: A View of Metastasis. J. Intern. Med. 2013, 274, 113–126.
  7. Berman, A.T.; Thukral, A.D.; Hwang, W.-T.; Solin, L.J.; Vapiwala, N. Incidence and Patterns of Distant Metastases for Patients with Early-Stage Breast Cancer after Breast Conservation Treatment. Clin. Breast Cancer 2013, 13, 88–94.
  8. Perou, C.M.; Sørlie, 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.
  9. van ’t Veer, L.J.; Dai, H.; van de Vijver, M.J.; He, Y.D.; Hart, A.A.M.; 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.
  10. Miah, S.; Bagu, E.; Goel, R.; Ogunbolude, Y.; Dai, C.; Ward, A.; Vizeacoumar, F.S.; Davies, G.; Vizeacoumar, F.J.; Anderson, D.; et al. Estrogen Receptor Signaling Regulates the Expression of the Breast Tumor Kinase in Breast Cancer Cells. BMC Cancer 2019, 19, 78.
  11. Zhang, M.H.; Man, H.T.; Zhao, X.D.; Dong, N.; Ma, S.L. Estrogen Receptor-Positive Breast Cancer Molecular Signatures and Therapeutic Potentials (Review). Biomed. Rep. 2014, 2, 41–52.
  12. 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, CMO-S18006.
  13. Gibson, G.R.; Qian, D.; Ku, J.K.; Lai, L.L. Metaplastic Breast Cancer: Clinical Features and Outcomes. Am. Surg. 2005, 71, 725–730.
  14. Lehmann, B.D.; Pietenpol, J.A. Identification and Use of Biomarkers in Treatment Strategies for Triple-Negative Breast Cancer Subtypes. J. Pathol. 2014, 232, 142–150.
  15. Lehmann, B.D.; Bauer, J.A.; Chen, X.; Sanders, M.E.; Chakravarthy, A.B.; Shyr, Y.; Pietenpol, J.A. Identification of Human Triple-Negative Breast Cancer Subtypes and Preclinical Models for Selection of Targeted Therapies. J. Clin. Investig. 2011, 121, 2750–2767.
  16. Takahashi, R.; Toh, U.; Iwakuma, N.; Takenaka, M.; Otsuka, H.; Furukawa, M.; Fujii, T.; Seki, N.; Kawahara, A.; Kage, M.; et al. Feasibility Study of Personalized Peptide Vaccination for Metastatic Recurrent Triple-Negative Breast Cancer Patients. Breast Cancer Res. 2014, 16, R70.
  17. McHenry, P.R.; Prosperi, J.R. Proteins Found in the Triple-Negative Breast Cancer Secretome and Their Therapeutic Potential. Int. J. Mol. Sci. 2023, 24, 2100.
  18. Sirven, P.; Faucheux, L.; Grandclaudon, M.; Michea, P.; Vincent-Salomon, A.; Mechta-Grigoriou, F.; Scholer-Dahirel, A.; Guillot-Delost, M.; Soumelis, V. Definition of a Novel Breast Tumor-Specific Classifier Based on Secretome Analysis. Breast Cancer Res. 2022, 24, 94.
  19. Ritchie, S.; Reed, D.A.; Pereira, B.A.; Timpson, P. The Cancer Cell Secretome Drives Cooperative Manipulation of the Tumour Microenvironment to Accelerate Tumourigenesis. Fac. Rev. 2021, 10, 4.
  20. Uhlén, M.; Karlsson, M.J.; Hober, A.; Svensson, A.-S.; Scheffel, J.; Kotol, D.; Zhong, W.; Tebani, A.; Strandberg, L.; Edfors, F.; et al. The Human Secretome. Sci. Signal. 2019, 12, eaaz0274.
  21. Blanco, M.A.; LeRoy, G.; Khan, Z.; Alečković, M.; Zee, B.M.; Garcia, B.A.; Kang, Y. Global Secretome Analysis Identifies Novel Mediators of Bone Metastasis. Cell Res. 2012, 22, 1339–1355.
  22. Mustafa, S.; Pan, L.; Marzoq, A.; Fawaz, M.; Sander, L.; Rückert, F.; Schrenk, A.; Hartl, C.; Uhler, R.; Yildirim, A.; et al. Comparison of the Tumor Cell Secretome and Patient Sera for an Accurate Serum-Based Diagnosis of Pancreatic Ductal Adenocarcinoma. Oncotarget 2017, 8, 11963–11976.
  23. Pappa, K.I.; Kontostathi, G.; Makridakis, M.; Lygirou, V.; Zoidakis, J.; Daskalakis, G.; Anagnou, N.P. High Resolution Proteomic Analysis of the Cervical Cancer Cell Lines Secretome Documents Deregulation of Multiple Proteases. Cancer Genom. Proteom. 2017, 14, 507–521.
  24. Dowling, P.; Clynes, M. Conditioned Media from Cell Lines: A Complementary Model to Clinical Specimens for the Discovery of Disease-Specific Biomarkers. Proteomics 2011, 11, 794–804.
  25. Carter, K.; Lee, H.J.; Na, K.-S.; Fernandes-Cunha, G.M.; Blanco, I.J.; Djalilian, A.; Myung, D. Characterizing the Impact of 2D and 3D Culture Conditions on the Therapeutic Effects of Human Mesenchymal Stem Cell Secretome on Corneal Wound Healing in Vitro and Ex Vivo. Acta Biomater. 2019, 99, 247–257.
  26. Cases-Perera, O.; Blanco-Elices, C.; Chato-Astrain, J.; Miranda-Fernández, C.; Campos, F.; Crespo, P.V.; Sánchez-Montesinos, I.; Alaminos, M.; Martín-Piedra, M.A.; Garzón, I. Development of Secretome-Based Strategies to Improve Cell Culture Protocols in Tissue Engineering. Sci. Rep. 2022, 12, 10003.
  27. Celis, J.E.; Gromov, P.; Cabezón, T.; Moreira, J.M.A.; Ambartsumian, N.; Sandelin, K.; Rank, F.; Gromova, I. Proteomic Characterization of the Interstitial Fluid Perfusing the Breast Tumor Microenvironment: A Novel Resource for Biomarker and Therapeutic Target Discovery. Mol. Cell. Proteom. 2004, 3, 327–344.
  28. Fijneman, R.J.A.; de Wit, M.; Pourghiasian, M.; Piersma, S.R.; Pham, T.V.; Warmoes, M.O.; Lavaei, M.; Piso, C.; Smit, F.; Delis-van Diemen, P.M.; et al. Proximal Fluid Proteome Profiling of Mouse Colon Tumors Reveals Biomarkers for Early Diagnosis of Human Colorectal Cancer. Clin. Cancer Res. 2012, 18, 2613–2624.
  29. Sauter, E.R.; Ross, E.; Daly, M.; Klein-Szanto, A.; Engstrom, P.F.; Sorling, A.; Malick, J.; Ehya, H. Nipple Aspirate Fluid: A Promising Non-Invasive Method to Identify Cellular Markers of Breast Cancer Risk. Br. J. Cancer 1997, 76, 494–501.
  30. Shaheed, S.; Tait, C.; Kyriacou, K.; Linforth, R.; Salhab, M.; Sutton, C. Evaluation of Nipple Aspirate Fluid as a Diagnostic Tool for Early Detection of Breast Cancer. Clin. Proteom. 2018, 15, 3.
  31. Zhang, L.; Shao, Z.-M.; Beatty, P.; Sartippour, M.; Wang, H.-J.; Elashoff, R.; Chang, H.; Brooks, M.N. The Use of Oxytocin in Nipple Fluid Aspiration. Breast J. 2003, 9, 266–268.
  32. Skok, K.; Hladnik, G.; Grm, A.; Crnjac, A. Malignant Pleural Effusion and Its Current Management: A Review. Medicina 2019, 55, 490.
  33. Kwa, M.; Plottel, C.S.; Blaser, M.J.; Adams, S. The Intestinal Microbiome and Estrogen Receptor-Positive Female Breast Cancer. J. Natl. Cancer Inst. 2016, 108, djw029.
  34. Garcia-Estevez, L.; Moreno-Bueno, G. Updating the Role of Obesity and Cholesterol in Breast Cancer. Breast Cancer Res. BCR 2019, 21, 35.
  35. Flores, R.; Shi, J.; Fuhrman, B.; Xu, X.; Veenstra, T.D.; Gail, M.H.; Gajer, P.; Ravel, J.; Goedert, J.J. Fecal Microbial Determinants of Fecal and Systemic Estrogens and Estrogen Metabolites: A Cross-Sectional Study. J. Transl. Med. 2012, 10, 253.
  36. Maynard, C.L.; Elson, C.O.; Hatton, R.D.; Weaver, C.T. Reciprocal Interactions of the Intestinal Microbiota and Immune System. Nature 2012, 489, 11551.
  37. Belkaid, Y.; Hand, T. Role of the Microbiota in Immunity and Inflammation. Cell 2014, 157, 121–141.
  38. Ayantunde, A.A.; Parsons, S.L. Pattern and Prognostic Factors in Patients with Malignant Ascites: A Retrospective Study. Ann. Oncol. 2007, 18, 945–949.
  39. Elsherbiny, N.M.; Younis, N.N.; Shaheen, M.A.; Elseweidy, M.M. The Synergistic Effect between Vanillin and Doxorubicin in Ehrlich Ascites Carcinoma Solid Tumor and MCF-7 Human Breast Cancer Cell Line. Pathol. Res. Pract. 2016, 212, 767–777.
  40. Ni, C.; Huang, J. Dynamic Regulation of Cancer Stem Cells and Clinical Challenges. Clin. Transl. Oncol. 2013, 15, 253–258.
  41. Jahanban-Esfahlan, R.; Seidi, K.; Zarghami, N. Tumor Vascular Infarction: Prospects and Challenges. Int. J. Hematol. 2017, 105, 244–256.
  42. Jahanban-Esfahlan, R.; Seidi, K.; Banimohamad-Shotorbani, B.; Jahanban-Esfahlan, A.; Yousefi, B. Combination of Nanotechnology with Vascular Targeting Agents for Effective Cancer Therapy. J. Cell. Physiol. 2018, 233, 2982–2992.
  43. Jahanban-Esfahlan, R.; Seidi, K.; Monhemi, H.; Adli, A.D.F.; Minofar, B.; Zare, P.; Farajzadeh, D.; Farajnia, S.; Behzadi, R.; Abbasi, M.M.; et al. RGD Delivery of Truncated Coagulase to Tumor Vasculature Affords Local Thrombotic Activity to Induce Infarction of Tumors in Mice. Sci. Rep. 2017, 7, 8126.
  44. Truffi, M.; Sorrentino, L.; Corsi, F. Fibroblasts in the Tumor Microenvironment. In Tumor Microenvironment: Non-Hematopoietic Cells; Birbrair, A., Ed.; Advances in Experimental Medicine and Biology; Springer International Publishing: Cham, Switzerland, 2020; pp. 15–29. ISBN 978-3-030-37184-5.
  45. Nassar, D.; Blanpain, C. Cancer Stem Cells: Basic Concepts and Therapeutic Implications. Annu. Rev. Pathol. Mech. Dis. 2016, 11, 47–76.
  46. Chen, K.; Huang, Y.; Chen, J. Understanding and Targeting Cancer Stem Cells: Therapeutic Implications and Challenges. Acta Pharmacol. Sin. 2013, 34, 732–740.
  47. Almagro, J.; Messal, H.A.; Elosegui-Artola, A.; van Rheenen, J.; Behrens, A. Tissue Architecture in Tumor Initiation and Progression. Trends Cancer 2022, 8, 494–505.
  48. Baghban, R.; Roshangar, L.; Jahanban-Esfahlan, R.; Seidi, K.; Ebrahimi-Kalan, A.; Jaymand, M.; Kolahian, S.; Javaheri, T.; Zare, P. Tumor Microenvironment Complexity and Therapeutic Implications at a Glance. Cell Commun. Signal. 2020, 18, 59.
  49. Fukumura, D.; Duda, D.G.; Munn, L.L.; Jain, R.K. Tumor Microvasculature and Microenvironment: Novel Insights Through Intravital Imaging in Pre-Clinical Models. Microcirculation 2010, 17, 206–225.
  50. Lamplugh, Z.; Fan, Y. Vascular Microenvironment, Tumor Immunity and Immunotherapy. Front. Immunol. 2021, 12, 811485.
  51. Cosentino, G.; Plantamura, I.; Tagliabue, E.; Iorio, M.V.; Cataldo, A. Breast Cancer Drug Resistance: Overcoming the Challenge by Capitalizing on MicroRNA and Tumor Microenvironment Interplay. Cancers 2021, 13, 3691.
  52. Masoud, V.; Pagès, G. Targeted Therapies in Breast Cancer: New Challenges to Fight against Resistance. World J. Clin. Oncol. 2017, 8, 120–134.
  53. Swain, S.M.; Shastry, M.; Hamilton, E. Targeting HER2-Positive Breast Cancer: Advances and Future Directions. Nat. Rev. Drug Discov. 2023, 22, 101–126.
  54. Gajria, D.; Chandarlapaty, S. HER2-Amplified Breast Cancer: Mechanisms of Trastuzumab Resistance and Novel Targeted Therapies. Expert Rev. Anticancer Ther. 2011, 11, 263–275.
  55. Opdam, F.L.; Guchelaar, H.-J.; Beijnen, J.H.; Schellens, J.H.M. Lapatinib for Advanced or Metastatic Breast Cancer. Oncologist 2012, 17, 536–542.
  56. Yang, F.; Huang, X.; Sun, C.; Li, J.; Wang, B.; Yan, M.; Jin, F.; Wang, H.; Zhang, J.; Fu, P.; et al. Lapatinib in Combination with Capecitabine versus Continued Use of Trastuzumab in Breast Cancer Patients with Trastuzumab-Resistance: A Retrospective Study of a Chinese Population. BMC Cancer 2020, 20, 255.
  57. Felcher, C.M.; Bogni, E.S.; Kordon, E.C. IL-6 Cytokine Family: A Putative Target for Breast Cancer Prevention and Treatment. Int. J. Mol. Sci. 2022, 23, 1809.
  58. Manore, S.G.; Doheny, D.L.; Wong, G.L.; Lo, H.-W. IL-6/JAK/STAT3 Signaling in Breast Cancer Metastasis: Biology and Treatment. Front. Oncol. 2022, 12, 866014.
  59. Obenauf, A.C.; Zou, Y.; Ji, A.L.; Vanharanta, S.; Shu, W.; Shi, H.; Kong, X.; Bosenberg, M.C.; Wiesner, T.; Rosen, N.; et al. Therapy-Induced Tumour Secretomes Promote Resistance and Tumour Progression. Nature 2015, 520, 368–372.
  60. Ye, J.; Tian, T.; Chen, X. The Efficacy of Gefitinib Supplementation for Breast Cancer. Medicine 2020, 99, e22613.
  61. Miyashita, M.; Hattori, M.; Takano, T.; Toyama, T.; Iwata, H. Risks and Benefits of Bevacizumab Combined with Chemotherapy for Advanced or Metastatic Breast Cancer: A Meta-Analysis of Randomized Controlled Trials. Breast Cancer 2020, 27, 347–354.
  62. Khan, M.; Zhao, Z.; Arooj, S.; Zheng, T.; Liao, G. Lapatinib Plus Local Radiation Therapy for Brain Metastases From HER-2 Positive Breast Cancer Patients and Role of Trastuzumab: A Systematic Review and Meta-Analysis. Front. Oncol. 2020, 10, 576926.
  63. Masuda, N.; Iwata, H.; Aogi, K.; Xu, Y.; Ibrahim, A.; Gao, L.; Dalal, R.; Yoshikawa, R.; Sasaki, Y. Safety and Pharmacokinetics of Ramucirumab in Combination with Docetaxel in Japanese Patients with Locally Advanced or Metastatic Breast Cancer: A Phase Ib Study. Jpn. J. Clin. Oncol. 2016, 46, 1088–1094.
  64. Schmid, P.; Cortes, J.; Dent, R.; Pusztai, L.; McArthur, H.; Kümmel, S.; Bergh, J.; Denkert, C.; Park, Y.H.; Hui, R.; et al. Event-Free Survival with Pembrolizumab in Early Triple-Negative Breast Cancer. N. Engl. J. Med. 2022, 386, 556–567.
  65. Tulotta, C.; Lefley, D.V.; Moore, C.K.; Amariutei, A.E.; Spicer-Hadlington, A.R.; Quayle, L.A.; Hughes, R.O.; Ahmed, K.; Cookson, V.; Evans, C.A.; et al. IL-1B Drives Opposing Responses in Primary Tumours and Bone Metastases; Harnessing Combination Therapies to Improve Outcome in Breast Cancer. NPJ Breast Cancer 2021, 7, 95.
  66. Zhou, J.; Tulotta, C.; Ottewell, P.D. IL-1β in Breast Cancer Bone Metastasis. Expert Rev. Mol. Med. 2022, 24, e11.
  67. Zhang, X.; Li, Y.; Wei, M.; Liu, C.; Yu, T.; Yang, J. Cetuximab-Modified Silica Nanoparticle Loaded with ICG for Tumor-Targeted Combinational Therapy of Breast Cancer. Drug Deliv. 2019, 26, 129–136.
  68. Barroso-Sousa, R.; Keenan, T.E.; Li, T.; Tayob, N.; Trippa, L.; Pastorello, R.G.; Richardson III, E.T.; Dillon, D.; Amoozgar, Z.; Overmoyer, B.; et al. Nivolumab in Combination with Cabozantinib for Metastatic Triple-Negative Breast Cancer: A Phase II and Biomarker Study. NPJ Breast Cancer 2021, 7, 110.
  69. Kang, C.; Syed, Y.Y. Atezolizumab (in Combination with Nab-Paclitaxel): A Review in Advanced Triple-Negative Breast Cancer. Drugs 2020, 80, 601–607.
  70. Correia, A.S.; Gärtner, F.; Vale, N. Drug Combination and Repurposing for Cancer Therapy: The Example of Breast Cancer. Heliyon 2021, 7, e05948.
  71. Fares, J.; Kanojia, D.; Rashidi, A.; Ulasov, I.; Lesniak, M.S. Landscape of Combination Therapy Trials in Breast Cancer Brain Metastasis. Int. J. Cancer 2020, 147, 1939–1952.
  72. Fisusi, F.A.; Akala, E.O. Drug Combinations in Breast Cancer Therapy. Pharm. Nanotechnol. 2019, 7, 3–23.
  73. Aumeeruddy, M.Z.; Mahomoodally, M.F. Combating Breast Cancer Using Combination Therapy with 3 Phytochemicals: Piperine, Sulforaphane, and Thymoquinone. Cancer 2019, 125, 1600–1611.
  74. Panahi, Y.; Saadat, A.; Beiraghdar, F.; Nouzari, S.M.H.; Jalalian, H.R.; Sahebkar, A. Antioxidant Effects of Bioavailability-Enhanced Curcuminoids in Patients with Solid Tumors: A Randomized Double-Blind Placebo-Controlled Trial. J. Funct. Foods 2014, 6, 615–622.
  75. Fuchs-Tarlovsky, V. Role of Antioxidants in Cancer Therapy. Nutrition 2013, 29, 15–21.
  76. Block, K.I.; Koch, A.C.; Mead, M.N.; Tothy, P.K.; Newman, R.A.; Gyllenhaal, C. Impact of Antioxidant Supplementation on Chemotherapeutic Efficacy: A Systematic Review of the Evidence from Randomized Controlled Trials. Cancer Treat. Rev. 2007, 33, 407–418.
  77. Mokhtari, R.B.; Homayouni, T.S.; Baluch, N.; Morgatskaya, E.; Kumar, S.; Das, B.; Yeger, H. Combination Therapy in Combating Cancer. Oncotarget 2017, 8, 38022–38043.
  78. 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.
  79. Tung, N.; Garber, J.E. PARP Inhibition in Breast Cancer: Progress Made and Future Hopes. NPJ Breast Cancer 2022, 8, 47.
  80. Barchiesi, G.; Roberto, M.; Verrico, M.; Vici, P.; Tomao, S.; Tomao, F. Emerging Role of PARP Inhibitors in Metastatic Triple Negative Breast Cancer. Current Scenario and Future Perspectives. Front. Oncol. 2021, 11, 769280.
More
This entry is offline, you can click here to edit this entry!
ScholarVision Creations