Nontoxic Fluorescent Nanoprobes for Multiplexed Detection and 3D Imaging of Tumor Markers in Breast Cancer
Abstract
:1. Introduction
2. Tumor Biomarkers in the Diagnosis, Classification, and Treatment of Breast Cancer
2.1. Markers Differentiating between Benign Neoplasms and Invasive or In Situ Carcinomas
2.2. Markers Differentiating between In Situ Carcinomas: Lobular and Ductal Carcinomas
2.3. Markers of Invasive Carcinomas: Lobular and Ductal Carcinomas
2.4. Markers for Determining whether the Breast Tunor Is Primary or Metastatic
2.5. Markers for Determining the Prognosis and Selecting the Treatment
3. Tumor Microenvironment Biomarkers in the Diagnosis, Classification, and Treatment of Breast Cancer
4. Studying the 2D/3D Structure of the Tumor and Its Microenvironment
5. Fluorescent Labels for Multiplexed 3D Imaging
6. Capture Molecules for 3D Imaging
7. Conclusions
- Narrow fluorescence spectra in a wide range of wavelengths, making fluorescent NCs suitable for multiplexed detection;
- A high photostability allowing long-term scanning and signal accumulation and simplifying tissue staining procedures;
- The possibility to tune the fluorescence spectrum by varying the NC size and composition, including the possibility to obtain NCs emitting in the infrared and near-infrared spectral ranges;
- A large two-photon absorption cross section allowing excitation in the infrared range, thus ensuring deeper penetration of radiation, a stronger useful signal, and a weaker background signal;
- Low blinking allowing detection of signals from individual fluorophores;
- A long fluorescence lifetime providing conditions for FLIM.
- A small size allowing a greater number of capture molecules to be linked to the fluorescent label;
- A small size of sdAb–NC conjugates promoting tissue penetration and detection of hidden epitopes inaccessible for full-length antibodies;
- The possibility of obtaining a functionally active conjugate with the highest possible avidity where all sdAb molecules are bound to the NC in a strictly oriented manner;
- High stability and hydrophilicity allowing the staining and signal detection within a wider range of physical and chemical parameters, thus optimizing and simplifying the permeabilization, fixation, and staining procedures.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef]
- Nover, A.B.; Jagtap, S.; Anjum, W.; Yegingil, H.; Shih, W.Y.; Shih, W.H.; Brooks, A.D. Modern breast cancer detection: A technological review. Int. J. Biomed. Imaging 2009, 2009, 902326. [Google Scholar] [CrossRef]
- He, Z.; Chen, Z.; Tan, M.; Elingarami, S.; Liu, Y.; Li, T.; Deng, Y.; He, N.; Li, S.; Fu, J.; et al. A review on methods for diagnosis of breast cancer cells and tissues. Cell Prolif. 2020, 53, e12822. [Google Scholar] [CrossRef]
- Tokheim, C.J.; Papadopoulos, N.; Kinzler, K.W.; Vogelstein, B.; Karchin, R. Evaluating the evaluation of cancer driver genes. Proc. Natl. Acad. Sci. USA 2016, 113, 14330–14335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Huang, K.K.; Jang, K.W.; Kim, S.; Kim, H.S.; Kim, S.M.; Kwon, H.J.; Kim, H.R.; Yun, H.J.; Ahn, M.J.; Park, K.U.; et al. Exome sequencing reveals recurrent REV3L mutations in cisplatin-resistant squamous cell carcinoma of head and neck. Sci. Rep. 2016, 6, 19552. [Google Scholar] [CrossRef] [Green Version]
- Esfahani, K.; Roudaia, L.; Buhlaiga, N.; Del Rincon, S.V.; Papneja, N.; Miller, W.H., Jr. A review of cancer immunotherapy: From the past, to the present, to the future. Curr. Oncol. 2020, 27, S87–S97. [Google Scholar] [CrossRef] [PubMed]
- Henriques, B.; Mendes, F.; Martins, D. Immunotherapy in breast cancer: When, how, and what challenges? Biomedicines 2021, 9, 1687. [Google Scholar] [CrossRef]
- Bonacho, T.; Rodrigues, F.; Liberal, J. Immunohistochemistry for diagnosis and prognosis of breast cancer: A review. Biotech. Histochem. 2020, 95, 71–91. [Google Scholar] [CrossRef]
- Modi, B.N.; Machin, J.T.; Ravichandran, D. Punch biopsy: A useful adjunct in a rapid diagnosis breast clinic. Breast 2010, 19, 150–151. [Google Scholar] [CrossRef]
- McCampbell, A.S.; Raghunathan, V.; Tom-Moy, M.; Workman, R.K.; Haven, R.; Ben-Dor, A.; Rasmussen, O.F.; Jacobsen, L.; Lindberg, M.; Yamada, N.A.; et al. Tissue thickness effects on immunohistochemical staining intensity of markers of cancer. Appl. Immunohistochem. Mol. Morphol. 2019, 27, 345–355. [Google Scholar] [CrossRef] [PubMed]
- Yeh, I.T.; Mies, C. Application of immunohistochemistry to breast lesions. Arch. Pathol. Lab. Med. 2008, 132, 349–358. [Google Scholar] [CrossRef]
- Otterbach, F.; Bànkfalvi, À.; Bergner, S.; Decker, T.; Krech, R.; Boecker, W. Cytokeratin 5/6 immunohistochemistry assists the differential diagnosis of atypical proliferations of the breast. Histopathology 2000, 37, 232–240. [Google Scholar] [CrossRef]
- Duivenvoorden, H.M.; Spurling, A.; O’Toole, S.A.; Parker, B.S. Discriminating the earliest stages of mammary carcinoma using myoepithelial and proliferative markers. PLoS ONE 2018, 13, e0201370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kesse-Adu, R.; Shousha, S. Myoepithelial markers are expressed in at least 29% of oestrogen receptor negative invasive breast carcinoma. Modern Pathol. 2004, 17, 646–652. [Google Scholar] [CrossRef] [Green Version]
- Martinez, A.P.; Cohen, C.; Hanley, K.Z.; Li, X. Estrogen receptor and cytokeratin 5 are reliable markers to separate usual ductal hyperplasia from atypical ductal hyperplasia and low-grade ductal carcinoma in situ. Arch. Pathol. Lab. Med. 2016, 140, 686–689. [Google Scholar] [CrossRef] [Green Version]
- Wei, S. Papillary Lesions of the breast: An update. Arch. Pathol. Lab. Med. 2016, 140, 628–643. [Google Scholar] [CrossRef] [Green Version]
- Tse, G.M.; Ni, Y.-B.; Tsang, J.Y.S.; Shao, M.-M.; Huang, Y.-H.; Luo, M.-H.; Lacambra, M.D.; Yamaguchi, R.; Tan, P.-H. Immunohistochemistry in the diagnosis of papillary lesions of the breast. Histopathology 2014, 65, 839–853. [Google Scholar] [CrossRef]
- Grin, A.; O’Malley, F.P.; Mulligan, A.M. Cytokeratin 5 and estrogen receptor immunohistochemistry as a useful adjunct in identifying atypical papillary lesions on breast needle core biopsy. Am. J. Surg. Pathol. 2009, 33, 1615–1623. [Google Scholar] [CrossRef]
- Nofech-Mozes, S.; Holloway, C.; Hanna, W. The role of cytokeratin 5/6 as an adjunct diagnostic tool in breast core needle biopsies. Int. J. Surg. Pathol. 2008, 16, 399–406. [Google Scholar] [CrossRef] [PubMed]
- Wen, X.; Cheng, W. Nonmalignant breast papillary lesions at core-needle biopsy: A meta-analysis of underestimation and influencing factors. Ann. Surg. Oncol. 2013, 20, 94–101. [Google Scholar] [CrossRef] [PubMed]
- Acs, G.; Lawton, T.J.; Rebbeck, T.R.; LiVolsi, V.A.; Zhang, P.J. Differential expression of E-cadherin in lobular and ductal neoplasms of the breast and its biologic and diagnostic implications. Am. J. Clin. Pathol. 2001, 115, 85–98. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bratthauer, G.L.; Moinfar, F.; Stamatakos, M.D.; Mezzetti, T.P.; Shekitka, K.M.; Man, Y.G.; Tavassoli, F.A. Combined E-cadherin and high molecular weight cytokeratin immunoprofile differentiates lobular, ductal, and hybrid mammary intraepithelial neoplasias. Hum. Pathol. 2002, 33, 620–627. [Google Scholar] [CrossRef] [PubMed]
- Singhai, R.; Patil, V.W.; Jaiswal, S.R.; Patil, S.D.; Tayade, M.B.; Patil, A.V. E-Cadherin as a diagnostic biomarker in breast cancer. N. Am. J. Med. Sci. 2011, 3, 227–233. [Google Scholar] [CrossRef]
- Lehr, H.A.; Folpe, A.; Yaziji, H.; Kommoss, F.; Gown, A. Cytokeratin 8 immunostaining pattern and e-cadherinexpression distinguish lobular from ductal breast carcinoma. Am. J. Clin. Pathol. 2000, 114, 190–196. [Google Scholar] [CrossRef] [Green Version]
- Eheman, C.R.; Shaw, K.M.; Ryerson, A.B.; Miller, J.W.; Ajani, U.A.; White, M.C. The changing incidence of in situ and invasive ductal and lobular breast carcinomas: United States, 1999–2004. Cancer Epidemiol. Biomark. Prev. 2009, 18, 1763–1769. [Google Scholar] [CrossRef] [Green Version]
- Lakhani, S.R.; Ellis, I.O.; Schnitt, S.; Tan, P.H.; van de Vijver, M. WHO Classification of Tumours of the Breast; IARC: Lyon, France, 2012. [Google Scholar]
- Moinfar, F. Essentials of Diagnostic Breast Pathology: A Practical Approach; Springer: Berlin, Germany, 2007. [Google Scholar]
- Fulga, V.; Rudico, L.; Balica, A.R.; Cimpean, A.M.; Saptefrati, L.; Raica, M. Invasive ductal carcinoma of no special type and its corresponding lymph node metastasis: Do they have the same immunophenotypic profile? Pol. J. Pathol. 2015, 66, 30–37. [Google Scholar] [CrossRef] [Green Version]
- Schnitt, S.J. Spindle Cell lesions of the breast. Surg. Pathol. Clin. 2009, 2, 375–390. [Google Scholar] [CrossRef]
- Rakha, E.A.; Coimbra, N.D.; Hodi, Z.; Juneinah, E.; Ellis, I.O.; Lee, A.H. Immunoprofile of metaplastic carcinomas of the breast. Histopathology 2017, 70, 975–985. [Google Scholar] [CrossRef]
- Koker, M.M.; Kleer, C.G. p63 expression in breast cancer: A highly sensitive and specific marker of metaplastic carcinoma. Am. J. Surg. Pathol. 2004, 28, 1506–1512. [Google Scholar] [CrossRef]
- Altaf, F.J.; Mokhtar, G.A.; Emam, E.; Bokhary, R.Y.; Mahfouz, N.B.; Al Amoudi, S.; Al-Gaithy, Z.K. Metaplastic carcinoma of the breast: An immunohistochemical study. Diagn. Pathol. 2014, 9, 139. [Google Scholar] [CrossRef] [Green Version]
- Dunne, B.; Lee, A.H.; Pinder, S.E.; Bell, J.A.; Ellis, I.O. An immunohistochemical study of metaplastic spindle cell carcinoma, phyllodes tumor and fibromatosis of the breast. Hum. Pathol. 2003, 34, 1009–1015. [Google Scholar] [CrossRef]
- Pezzi, C.M.; Patel-Parekh, L.; Cole, K.; Franko, J.; Klimberg, V.S.; Bland, K. Characteristics and treatment of metaplastic breast cancer: Analysis of 892 cases from the National Cancer Data Base. Ann. Surg. Oncol. 2007, 14, 166–173. [Google Scholar] [CrossRef]
- Naderi, A.; Meyer, M. Prolactin-induced protein mediates cell invasion and regulates integrin signaling in estrogen receptor-negative breast cancer. Breast Cancer Res. 2012, 14, R111. [Google Scholar] [CrossRef] [Green Version]
- Chen, Y.Y.; Hwang, E.S.; Roy, R.; DeVries, S.; Anderson, J.; Wa, C.; Fitzgibbons, P.L.; Jacobs, T.W.; MacGrogan, G.; Peterse, H.; et al. Genetic and phenotypic characteristics of pleomorphic lobular carcinoma in situ of the breast. Am. J. Surg. Pathol. 2009, 33, 1683–1694. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Monhollen, L.; Morrison, C.; Ademuyiwa, F.O.; Chandrasekhar, R.; Khoury, T. Pleomorphic lobular carcinoma: A distinctive clinical and molecular breast cancer type. Histopathology 2012, 61, 365–377. [Google Scholar] [CrossRef]
- Choi, J.; Jung, W.H.; Koo, J.S. Clinicopathologic features of molecular subtypes of triple negative breast cancer based on immunohistochemical markers. Histol. Histopathol. 2012, 27, 1481–1493. [Google Scholar] [CrossRef] [PubMed]
- Bishop, J.A.; Sharma, R.; Illei, P.B. Napsin A and thyroid transcription factor-1 expression in carcinomas of the lung, breast, pancreas, colon, kidney, thyroid, and malignant mesothelioma. Hum. Pathol. 2010, 41, 20–25. [Google Scholar] [CrossRef] [PubMed]
- Whithaus, K.; Fukuoka, J.; Prihoda, T.J.; Jagirdar, J. Evaluation of napsin A, cytokeratin 5/6, p63, and thyroid transcription factor 1 in adenocarcinoma versus squamous cell carcinoma of the lung. Arch. Pathol. Lab. Med. 2012, 136, 155–162. [Google Scholar] [CrossRef] [PubMed]
- Tornos, C.; Soslow, R.; Chen, S.; Akram, M.; Hummer, A.J.; Abu-Rustum, N.; Norton, L.; Tan, L.K. Expression of WT1, CA 125, and GCDFP-15 as useful markers in the differential diagnosis of primary ovarian carcinomas versus metastatic breast cancer to the ovary. Am. J. Surg. Pathol. 2005, 29, 1482–1489. [Google Scholar] [CrossRef]
- Bombonati, A.; Lerwill, M.F. Metastases to and from the Breast. Surg. Pathol. Clin. 2012, 5, 719–747. [Google Scholar] [CrossRef]
- Werling, R.W.; Yaziji, H.; Bacchi, C.E.; Gown, A.M. CDX2, a highly sensitive and specific marker of adenocarcinomas of intestinal origin: An immunohistochemical survey of 476 primary and metastatic carcinomas. Am. J. Surg. Pathol. 2003, 27, 303–310. [Google Scholar] [CrossRef]
- Otsuki, Y.; Yamada, M.; Shimizu, S.; Suwa, K.; Yoshida, M.; Tanioka, F.; Ogawa, H.; Nasuno, H.; Serizawa, A.; Kobayashi, H. Solid-papillary carcinoma of the breast: Clinicopathological study of 20 cases. Pathol. Int. 2007, 57, 421–429. [Google Scholar] [CrossRef]
- Busam, K.J.; Jungbluth, A.A. Melan-A, a new melanocytic differentiation marker. Adv. Anat. Pathol. 1999, 6, 12–18. [Google Scholar] [CrossRef] [PubMed]
- Filie, A.C.; Simsir, A.; Fetsch, P.; Abati, A. Melanoma metastatic to the breast: Utility of fine needle aspiration and immunohistochemistry. Acta Cytol. 2002, 46, 13–18. [Google Scholar] [CrossRef]
- Ren, M.; Kong, Y.Y.; Cai, X.; Shen, X.X.; Lyu, J.J. Application of sentinel lymph node biopsy in patients with melanoma. Zhonghua Bing Li Xue Za Zhi/Chin. J. Pathol. 2018, 47, 360–365. [Google Scholar] [CrossRef]
- Honma, N.; Horii, R.; Iwase, T.; Saji, S.; Younes, M.; Ito, Y.; Akiyama, F. Proportion of estrogen or progesterone receptor expressing cells in breast cancers and response to endocrine therapy. Breast 2014, 23, 754–762. [Google Scholar] [CrossRef] [PubMed]
- Nicolini, A.; Ferrari, P.; Duffy, M.J. Prognostic and predictive biomarkers in breast cancer: Past, present and future. Sem. Cancer Biol. 2018, 52, 56–73. [Google Scholar] [CrossRef]
- Smith, T.J.; Khatcheressian, J. Review: Chemotherapy and hormonal therapy reduce recurrence and mortality at 15 years in early breast cancer. ACP J. Club 2005, 143, 58. [Google Scholar] [CrossRef]
- Zubair, M.; Wang, S.; Ali, N. Advanced approaches to breast cancer classification and diagnosis. Front. Pharmacol. 2021, 11, 632079. [Google Scholar] [CrossRef]
- Iqbal, N.; Iqbal, N. Human epidermal growth factor receptor 2 (HER2) in cancers: Overexpression and therapeutic implications. Mol. Biol. Int. 2014, 2014, 852748. [Google Scholar] [CrossRef]
- Bradley, R.; Braybrooke, J.; Gray, R.; Hills, R.; Liu, Z.; Peto, R.; Davies, L.; Dodwell, D.; McGale, P.; Pan, H.; et al. Trastuzumab for early-stage, HER2-positive breast cancer: A meta-analysis of 13,864 women in seven randomised trials. Lancet Oncol. 2021, 22, 1139–1150. [Google Scholar] [CrossRef] [PubMed]
- Slamon, D.; Eiermann, W.; Robert, N.; Pienkowski, T.; Martin, M.; Press, M.; Mackey, J.; Glaspy, J.; Chan, A.; Pawlicki, M.; et al. Adjuvant trastuzumab in HER2-positive breast cancer. N. Eng. J. Med. 2011, 365, 1273–1283. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Milde-Langosch, K.; Bamberger, A.M.; Methner, C.; Rieck, G.; Löning, T. Expression of cell cycle-regulatory proteins rb, p16/MTS1, p27/KIP1, p21/WAF1, cyclin D1 and cyclin E in breast cancer: Correlations with expression of activating protein-1 family members. Int. J. Cancer 2000, 87, 468–472. [Google Scholar] [CrossRef]
- Thomssen, C.; Balic, M.; Harbeck, N.; Gnant, M.S. Gallen/Vienna 2021: A brief summary of the consensus discussion on customizing therapies for women with early breast cancer. Breast Care 2021, 16, 135–143. [Google Scholar] [CrossRef]
- Eliyatkın, N.; Yalçın, E.; Zengel, B.; Aktaş, S.; Vardar, E. Molecular classification of breast carcinoma: From traditional, old-fashioned way to a new age, and a new way. J. Breast Health 2015, 11, 59–66. [Google Scholar] [CrossRef] [Green Version]
- Tsang, J.Y.S.; Tse, G.M. Molecular classification of breast cancer. Adv. Anat. Pathol. 2020, 27, 27–35. [Google Scholar] [CrossRef]
- Qin, G.; Wang, X.; Ye, S.; Li, Y.; Chen, M.; Wang, S.; Qin, T.; Zhang, C.; Li, Y.; Long, Q.; et al. NPM1 upregulates the transcription of PD-L1 and suppresses T cell activity in triple-negative breast cancer. Nat. Commun. 2020, 11, 1669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Johansson, A.L.V.; Trewin, C.B.; Hjerkind, K.V.; Ellingjord-Dale, M.; Johannesen, T.B.; Ursin, G. Breast cancer-specific survival by clinical subtype after 7 years follow-up of young and elderly women in a nationwide cohort. Int. J. Cancer 2019, 144, 1251–1261. [Google Scholar] [CrossRef]
- Yersal, O.; Barutca, S. Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J. Clin. Oncol. 2014, 5, 412–424. [Google Scholar] [CrossRef]
- Hurvitz, S.A.; McAndrew, N.P.; Bardia, A.; Press, M.F.; Pegram, M.; Crown, J.P.; Fasching, P.A.; Ejlertsen, B.; Yang, E.H.; Glaspy, J.A.; et al. A careful reassessment of anthracycline use in curable breast cancer. npj Breast Cancer 2021, 7, 134. [Google Scholar] [CrossRef]
- Chen, K.; Zhang, J.; Beeraka, N.M.; Tang, C.; Babayeva, Y.V.; Sinelnikov, M.Y.; Zhang, X.; Zhang, J.; Liu, J.; Reshetov, I.V.; et al. Advances in the Prevention and Treatment of Obesity-Driven Effects in Breast Cancers. Front. Oncol. 2022, 12, 820968. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Sun, Y.; Guo, Y.; Shi, X.; Chen, X.; Feng, W.; Wu, L.L.; Zhang, J.; Yu, S.; Wang, Y.; et al. An Overview: The Diversified Role of Mitochondria in Cancer Metabolism. Int. J. Biol. Sci. 2023, 19, 897–915. [Google Scholar] [CrossRef] [PubMed]
- Chen, K.; Lu, P.; Beeraka, N.M.; Sukocheva, O.A.; Madhunapantula, S.V.; Liu, J.; Sinelnikov, M.Y.; Nikolenko, V.N.; Bulygin, K.V.; Mikhaleva, L.M.; et al. Mitochondrial mutations and mitoepigenetics: Focus on regulation of oxidative stress-induced responses in breast cancers. Semin. Cancer Biol. 2022, 83, 556–569. [Google Scholar] [CrossRef] [PubMed]
- Khalaf, K.; Hana, D.; Chou, J.T.-T.; Singh, C.; Mackiewicz, A.; Kaczmarek, M. Aspects of the tumor microenvironment involved in immune resistance and drug resistance. Front. Immunol. 2021, 12, 656364. [Google Scholar] [CrossRef] [PubMed]
- Palazón-Carrión, N.; Jiménez-Cortegana, C.; Sánchez-León, M.L.; Henao-Carrasco, F.; Nogales-Fernández, E.; Chiesa, M.; Caballero, R.; Rojo, F.; Nieto-García, M.-A.; Sánchez-Margalet, V.; et al. Circulating immune biomarkers in peripheral blood correlate with clinical outcomes in advanced breast cancer. Sci. Rep. 2021, 11, 14426. [Google Scholar] [CrossRef]
- Petitprez, F.; Meylan, M.; de Reyniès, A.; Sautès-Fridman, C.; Fridman, W.H. The tumor microenvironment in the response to immune checkpoint blockade therapies. Front. Immunol. 2020, 11, 784. [Google Scholar] [CrossRef]
- Zhang, M.; Sun, H.; Zhao, S.; Wang, Y.; Pu, H.; Wang, Y.; Zhang, Q. Expression of PD-L1 and prognosis in breast cancer: A meta-analysis. Oncotarget 2017, 8, 31347–31354. [Google Scholar] [CrossRef] [Green Version]
- Vranic, S.; Cyprian, F.S.; Gatalica, Z.; Palazzo, J. PD-L1 status in breast cancer: Current view and perspectives. Sem. Cancer Biol. 2021, 72, 146–154. [Google Scholar] [CrossRef]
- Castagnoli, L.; Cancila, V.; Cordoba-Romero, S.L.; Faraci, S.; Talarico, G.; Belmonte, B.; Iorio, M.V.; Milani, M.; Volpari, T.; Chiodoni, C.; et al. WNT signaling modulates PD-L1 expression in the stem cell compartment of triple-negative breast cancer. Oncogene 2019, 38, 4047–4060. [Google Scholar] [CrossRef] [Green Version]
- Azadi, S.; Aboulkheyr Es, H.; Razavi Bazaz, S.; Thiery, J.P.; Asadnia, M.; Ebrahimi Warkiani, M. Upregulation of PD-L1 expression in breast cancer cells through the formation of 3D multicellular cancer aggregates under different chemical and mechanical conditions. Biochim. Biophys. Acta 2019, 1866, 118526. [Google Scholar] [CrossRef]
- Liu, Q.; Qi, Y.; Zhai, J.; Kong, X.; Wang, X.; Wang, Z.; Fang, Y.; Wang, J. Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples. Front. Immunol. 2021, 12, 599207. [Google Scholar] [CrossRef] [PubMed]
- Shan, C.; Li, X.; Zhang, J. Progress of immune checkpoint LAG-3 in immunotherapy (Review). Oncol. Lett. 2020, 20, 207. [Google Scholar] [CrossRef] [PubMed]
- Larkin, J.; Chiarion-Sileni, V.; Gonzalez, R.; Grob, J.J.; Cowey, C.L.; Lao, C.D.; Schadendorf, D.; Dummer, R.; Smylie, M.; Rutkowski, P.; et al. Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma. N. Eng. J. Med. 2015, 373, 23–34. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Q.; Gao, C.; Shao, J.; Wang, Z. TIGIT-related transcriptome profile and its association with tumor immune microenvironment in breast cancer. Biosci. Rep. 2021, 41, BSR20204340. [Google Scholar] [CrossRef] [PubMed]
- Stamm, H.; Oliveira-Ferrer, L.; Grossjohann, E.-M.; Muschhammer, J.; Thaden, V.; Brauneck, F.; Kischel, R.; Müller, V.; Bokemeyer, C.; Fiedler, W.; et al. Targeting the TIGIT-PVR immune checkpoint axis as novel therapeutic option in breast cancer. Oncoimmunology 2019, 8, e1674605. [Google Scholar] [CrossRef] [Green Version]
- Chauvin, J.M.; Zarour, H.M. TIGIT in cancer immunotherapy. J. Immunother. Cancer 2020, 8, e000957. [Google Scholar] [CrossRef]
- Debacker, J.M.; Gondry, O.; Lahoutte, T.; Keyaerts, M.; Huvenne, W. The prognostic value of CD206 in solid malignancies: A systematic review and meta-analysis. Cancers 2021, 13, 3422. [Google Scholar] [CrossRef]
- Bobrie, A.; Massol, O.; Ramos, J.; Mollevi, C.; Lopez-Crapez, E.; Bonnefoy, N.; Boissière-Michot, F.; Jacot, W. Association of CD206 Protein Expression with Immune Infiltration and Prognosis in Patients with Triple-Negative Breast Cancer. Cancers 2022, 14, 4829. [Google Scholar] [CrossRef]
- Zhang, W.; Huang, Q.; Xiao, W.; Zhao, Y.; Pi, J.; Xu, H.; Zhao, H.; Xu, J.; Evans, C.E.; Jin, H. Advances in anti-tumor treatments targeting the CD47/SIRPα axis. Front. Immunol. 2020, 11, 18. [Google Scholar] [CrossRef] [Green Version]
- Sturtz, L.A.; Deyarmin, B.; van Laar, R.; Yarina, W.; Shriver, C.D.; Ellsworth, R.E. Gene expression differences in adipose tissue associated with breast tumorigenesis. Adipocyte 2014, 3, 107–114. [Google Scholar] [CrossRef] [Green Version]
- Zheng, F.; Put, S.; Bouwens, L.; Lahoutte, T.; Matthys, P.; Muyldermans, S.; De Baetselier, P.; Devoogdt, N.; Raes, G.; Schoonooghe, S. Molecular imaging with macrophage CRIg-targeting nanobodies for early and preclinical diagnosis in a mouse model of rheumatoid arthritis. J. Nucl. Med. 2014, 55, 824. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liao, Y.; Guo, S.; Chen, Y.; Cao, D.; Xu, H.; Yang, C.; Fei, L.; Ni, B.; Ruan, Z. VSIG4 expression on macrophages facilitates lung cancer development. Lab. Investig. 2014, 94, 706–715. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ni, C.; Yang, L.; Xu, Q.; Yuan, H.; Wang, W.; Xia, W.; Gong, D.; Zhang, W.; Yu, K. CD68- and CD163-positive tumor infiltrating macrophages in non-metastatic breast cancer: A retrospective study and meta-analysis. J. Cancer 2019, 10, 4463–4472. [Google Scholar] [CrossRef] [Green Version]
- Shabo, I.; Midtbö, K.; Andersson, H.; Åkerlund, E.; Olsson, H.; Wegman, P.; Gunnarsson, C.; Lindström, A. Macrophage traits in cancer cells are induced by macrophage-cancer cell fusion and cannot be explained by cellular interaction. BMC Cancer 2015, 15, 922. [Google Scholar] [CrossRef] [Green Version]
- Garvin, S.; Oda, H.; Arnesson, L.-G.; Lindström, A.; Shabo, I. Tumor cell expression of CD163 is associated to postoperative radiotherapy and poor prognosis in patients with breast cancer treated with breast-conserving surgery. J. Cancer Res. Clin. Oncol. 2018, 144, 1253–1263. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jin, Y.W.; Hu, P. Tumor-infiltrating CD8 T cells predict clinical breast cancer outcomes in young women. Cancers 2020, 12, 1076. [Google Scholar] [CrossRef]
- Oshi, M.; Asaoka, M.; Tokumaru, Y.; Yan, L.; Matsuyama, R.; Ishikawa, T.; Endo, I.; Takabe, K. CD8 T cell score as a prognostic biomarker for triple negative breast cancer. Int. J. Mol. Sci. 2020, 21, 6968. [Google Scholar] [CrossRef]
- So, Y.K.; Byeon, S.-J.; Ku, B.M.; Ko, Y.H.; Ahn, M.-J.; Son, Y.-I.; Chung, M.K. An increase of CD8+ T cell infiltration following recurrence is a good prognosticator in HNSCC. Sci. Rep. 2020, 10, 20059. [Google Scholar] [CrossRef]
- Mita, Y.; Kimura, M.Y.; Hayashizaki, K.; Koyama-Nasu, R.; Ito, T.; Motohashi, S.; Okamoto, Y.; Nakayama, T. Crucial role of CD69 in anti-tumor immunity through regulating the exhaustion of tumor-infiltrating T cells. Int. Immunol. 2018, 30, 559–567. [Google Scholar] [CrossRef] [Green Version]
- Li, A.; Gong, H.; Zhang, B.; Wang, Q.; Yan, C.; Wu, J.; Liu, Q.; Zeng, S.; Luo, Q. Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 2010, 330, 1404–1408. [Google Scholar] [CrossRef] [Green Version]
- Koh, J.; Kwak, Y.; Kim, J.; Kim, W.H. High-Throughput Multiplex Immunohistochemical Imaging of the Tumor and Its Microenvironment. Cancer Res. Treat. 2020, 52, 98–108. [Google Scholar] [CrossRef] [PubMed]
- Lee, S.S.-Y.; Bindokas, V.P.; Kron, S.J. Multiplex three-dimensional optical mapping of tumor immune microenvironment. Sci. Rep. 2017, 7, 17031. [Google Scholar] [CrossRef] [Green Version]
- Chung, K.; Wallace, J.; Kim, S.Y.; Kalyanasundaram, S.; Andalman, A.S.; Davidson, T.J.; Mirzabekov, J.J.; Zalocusky, K.A.; Mattis, J.; Denisin, A.K.; et al. Structural and molecular interrogation of intact biological systems. Nature 2013, 497, 332–337. [Google Scholar] [CrossRef] [PubMed]
- Richardson, D.S.; Lichtman, J.W. Clarifying Tissue Clearing. Cell 2015, 162, 246–257. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Park, S.; Kang, W.; Kwon, Y.-D.; Shim, J.; Kim, S.; Kaang, B.-K.; Hohng, S. Superresolution fluorescence microscopy for 3D reconstruction of thick samples. Mol. Brain 2018, 11, 17. [Google Scholar] [CrossRef] [Green Version]
- Schnitzbauer, J.; Strauss, M.T.; Schlichthaerle, T.; Schueder, F.; Jungmann, R. Super-resolution microscopy with DNA-PAINT. Nat. Prot. 2017, 12, 1198–1228. [Google Scholar] [CrossRef]
- Khairi, S.S.M.; Bakar, M.A.A.; Alias, M.A.; Bakar, S.A.; Liong, C.Y.; Rosli, N.; Farid, M. Deep Learning on Histopathology Images for Breast Cancer Classification: A Bibliometric Analysis. Healthcare 2021, 10, 10. [Google Scholar] [CrossRef]
- Gupta, K.; Chawla, N. Analysis of Histopathological Images for Prediction of Breast Cancer Using Traditional Classifiers with Pre-Trained CNN. Procedia Comput. Sci. 2020, 167, 878–889. [Google Scholar] [CrossRef]
- Wells, W.A.; Wang, X.; Daghlian, C.P.; Paulsen, K.D.; Pogue, B.W. Phase contrast microscopy analysis of breast tissue: Differences in benign vs. malignant epithelium and stroma. Anal. Quant. Cytol. Histol. 2009, 31, 197–207. [Google Scholar]
- Mann, C.J.; Yu, L.; Lo, C.-M.; Kim, M.K. High-resolution quantitative phase-contrast microscopy by digital holography. Opt. Express 2005, 13, 8693–8698. [Google Scholar] [CrossRef] [Green Version]
- Kunz, L.; Coutu, D.L. Multicolor 3D Confocal Imaging of Thick Tissue Sections. Methods Mol. Biol. 2021, 2350, 95–104. [Google Scholar] [CrossRef] [PubMed]
- Fouquet, C.; Gilles, J.F.; Heck, N.; Dos Santos, M.; Schwartzmann, R.; Cannaya, V.; Morel, M.P.; Davidson, R.S.; Trembleau, A.; Bolte, S. Improving axial resolution in confocal microscopy with new high refractive index mounting media. PLoS ONE 2015, 10, e0121096. [Google Scholar] [CrossRef] [Green Version]
- Doi, A.; Oketani, R.; Nawa, Y.; Fujita, K. High-resolution imaging in two-photon excitation microscopy using in situ estimations of the point spread function. Biomed. Opt. Express 2018, 9, 202–213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kwon, J.; Jun, S.W.; Choi, S.I.; Mao, X.; Kim, J.; Koh, E.K.; Kim, Y.H.; Kim, S.K.; Hwang, D.Y.; Kim, C.S.; et al. FeSe quantum dots for in vivo multiphoton biomedical imaging. Sci. Adv. 2019, 5, eaay0044. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhao, Y.; Eldridge, W.J.; Maher, J.R.; Kim, S.; Crose, M.; Ibrahim, M.; Levinson, H.; Wax, A. Dual-axis optical coherence tomography for deep tissue imaging. Opt. Lett. 2017, 42, 2302–2305. [Google Scholar] [CrossRef]
- Aumann, S.; Donner, S.; Fischer, J.; Müller, F. Optical Coherence Tomography (OCT): Principle and Technical Realization. In High Resolution Imaging in Microscopy and Ophthalmology: New Frontiers in Biomedical Optics; Bille, J.F., Ed.; Springer International Publishing: Cham, Switzerland, 2019; pp. 59–85. [Google Scholar]
- Hanna, K.; Krzoska, E.; Shaaban, A.M.; Muirhead, D.; Abu-Eid, R.; Speirs, V. Raman spectroscopy: Current applications in breast cancer diagnosis, challenges and future prospects. Br. J. Cancer 2022, 126, 1125–1139. [Google Scholar] [CrossRef]
- Wang, M.; Zhang, C.; Yan, S.; Chen, T.; Fang, H.; Yuan, X. Wide-Field Super-Resolved Raman Imaging of Carbon Materials. ACS Photonics 2021, 8, 1801–1809. [Google Scholar] [CrossRef]
- Stuker, F.; Ripoll, J.; Rudin, M. Fluorescence molecular tomography: Principles and potential for pharmaceutical research. Pharmaceutics 2011, 3, 229–274. [Google Scholar] [CrossRef]
- Hui, X.; Malik, M.O.A.; Pramanik, M. Looking deep inside tissue with photoacoustic molecular probes: A review. J. Biomed. Opt. 2022, 27, 070901. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Y.S.; Wang, L.V.; Xia, Y. Seeing Through the Surface: Non-invasive Characterization of Biomaterial-Tissue Interactions Using Photoacoustic Microscopy. Ann. Biomed. Eng. 2016, 44, 649–666. [Google Scholar] [CrossRef] [Green Version]
- Zhang, W.; Hubbard, A.; Jones, T.; Racolta, A.; Bhaumik, S.; Cummins, N.; Zhang, L.; Garsha, K.; Ventura, F.; Lefever, M.R.; et al. Fully automated 5-plex fluorescent immunohistochemistry with tyramide signal amplification and same species antibodies. Lab. Investig. 2017, 97, 873–885. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wan, H.; Yue, J.; Zhu, S.; Uno, T.; Zhang, X.; Yang, Q.; Yu, K.; Hong, G.; Wang, J.; Li, L.; et al. A bright organic NIR-II nanofluorophore for three-dimensional imaging into biological tissues. Nat. Commun. 2018, 9, 1171. [Google Scholar] [CrossRef] [PubMed]
- Montecinos-Franjola, F.; Lin, J.Y.; Rodriguez, E.A. Fluorescent proteins for in vivo imaging, where’s the biliverdin? Biochem. Soc. Trans. 2020, 48, 2657–2667. [Google Scholar] [CrossRef] [PubMed]
- Deshayes, S.; Divita, G. Fluorescence technologies for monitoring interactions between biological molecules in vitro. Prog. Mol. Biol. Transl. Sci. 2013, 113, 109–143. [Google Scholar] [CrossRef] [PubMed]
- Shao, W.; Chen, G.; Kuzmin, A.; Kutscher, H.L.; Pliss, A.; Ohulchanskyy, T.Y.; Prasad, P.N. Tunable narrow band emissions from dye-sensitized core/shell/shell nanocrystals in the second near-infrared biological window. J. Am. Chem. Soc. 2016, 138, 16192–16195. [Google Scholar] [CrossRef] [Green Version]
- Li, B.; Lu, L.; Zhao, M.; Lei, Z.; Zhang, F. An Efficient 1064 nm NIR-II excitation fluorescent molecular dye for deep-tissue high-resolution dynamic bioimaging. Angew. Chem. 2018, 57, 7483–7487. [Google Scholar] [CrossRef]
- Bilan, R.; Nabiev, I.; Sukhanova, A. Quantum dot-based nanotools for bioimaging, diagnostics, and drug delivery. ChemBioChem 2016, 17, 2103–2114. [Google Scholar] [CrossRef]
- Sukhanova, A.; Nabiev, I. Fluorescent nanocrystal quantum dots as medical diagnostic tools. Expert Opin. Med. Diagn. 2008, 2, 429–447. [Google Scholar] [CrossRef]
- Liu, Y.; Tang, X.; Deng, M.; Zhu, T.; Edman, L.; Wang, J. Hydrophilic AgInZnS quantum dots as a fluorescent turn-on probe for Cd2+ detection. J. Alloys Compd. 2021, 864, 158109. [Google Scholar] [CrossRef]
- Sukhanova, A.; Bozrova, S.; Sokolov, P.; Berestovoy, M.; Karaulov, A.; Nabiev, I. Dependence of nanoparticle toxicity on their physical and chemical properties. Nanoscale Res. Lett. 2018, 13, 44. [Google Scholar] [CrossRef] [Green Version]
- Linkov, P.A.; Vokhmintcev, K.V.; Samokhvalov, P.S.; Laronze-Cochard, M.; Sapi, J.; Nabiev, I.R. The effect of quantum dot shell structure on fluorescence quenching by acridine ligand. KnE Energy 2018, 3, 194–201. [Google Scholar] [CrossRef]
- Kalsoom, U.e.; Yi, R.; Qu, J.; Liu, L. Nonlinear optical properties of CdSe and CdTe core-shell quantum dots and their applications. Front. Phys. 2021, 9, 612070. [Google Scholar] [CrossRef]
- Moreels, I.; Lambert, K.; Smeets, D.; De Muynck, D.; Nollet, T.; Martins, J.C.; Vanhaecke, F.; Vantomme, A.; Delerue, C.; Allan, G.; et al. Size-dependent optical properties of colloidal PbS quantum dots. ACS Nano 2009, 3, 3023–3030. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chandra, S.; Beaune, G.; Shirahata, N.; Winnik, F.M. A one-pot synthesis of water soluble highly fluorescent silica nanoparticles. J. Mater. Chem. B 2017, 5, 1363–1370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Damera, D.P.; Manimaran, R.; Krishna Venuganti, V.V.; Nag, A. Green synthesis of full-color fluorescent carbon nanoparticles from eucalyptus twigs for sensing the synthetic food colorant and bioimaging. ACS Omega 2020, 5, 19905–19918. [Google Scholar] [CrossRef]
- Zheng, P.; Wu, N. Fluorescence and sensing applications of graphene oxide and graphene quantum dots: A review. Chem. Asian J. 2017, 12, 2343–2353. [Google Scholar] [CrossRef]
- Wang, Y.H.; Chen, Z.; Zhou, X.Q. Synthesis and photoluminescence of ZnS quantum dots. J. Nanosci. Nanotechnol. 2008, 8, 1312–1315. [Google Scholar] [CrossRef]
- Leach, A.D.P.; Macdonald, J.E. Optoelectronic properties of CuInS2 nanocrystals and their origin. J. Phys. Chem. Lett. 2016, 7, 572–583. [Google Scholar] [CrossRef]
- Uematsu, T.; Wajima, K.; Sharma, D.K.; Hirata, S.; Yamamoto, T.; Kameyama, T.; Vacha, M.; Torimoto, T.; Kuwabata, S. Narrow band-edge photoluminescence from AgInS2 semiconductor nanoparticles by the formation of amorphous III–VI semiconductor shells. NPG Asia Mater. 2018, 10, 713–726. [Google Scholar] [CrossRef] [Green Version]
- Litvinov, I.K.; Belyaeva, T.N.; Salova, A.V.; Aksenov, N.D.; Leontieva, E.A.; Orlova, A.O.; Kornilova, E.S. Quantum dots based on indium phosphide (InP): The effect of chemical modifications of the organic shell on interaction with cultured cells of various origins. Cell Tissue Biol. 2018, 12, 135–145. [Google Scholar] [CrossRef]
- Nagamine, G.; McDaniel, H.; Brito Cruz, C.H.; Padilha, L.A. Two-photon absorption spectroscopy in CuInS2 (CIS) quantum dots for bio-imaging. In Frontiers in Optics 2017; Optica Publishing Group: Washington, DC, USA, 2017; p. FTu5B.5. [Google Scholar]
- Kim, S.H.; Man, M.T.; Lee, J.W.; Park, K.-D.; Lee, H.S. Influence of size and shape anisotropy on optical properties of CdSe quantum dots. Nanomaterials 2020, 10, 1589. [Google Scholar] [CrossRef] [PubMed]
- Raevskaya, A.; Lesnyak, V.; Haubold, D.; Dzhagan, V.; Stroyuk, O.; Gaponik, N.; Zahn, D.R.T.; Eychmüller, A. A fine size selection of brightly luminescent water-soluble Ag–In–S and Ag–In–S/ZnS quantum dots. J. Phys. Chem. C 2017, 121, 9032–9042. [Google Scholar] [CrossRef] [Green Version]
- Mićić, O.I.; Cheong, H.M.; Fu, H.; Zunger, A.; Sprague, J.R.; Mascarenhas, A.; Nozik, A.J. Size-dependent spectroscopy of InP quantum dots. J. Phys. Chem. B 1997, 101, 4904–4912. [Google Scholar] [CrossRef]
- Brunetti, V.; Chibli, H.; Fiammengo, R.; Galeone, A.; Malvindi, M.A.; Vecchio, G.; Cingolani, R.; Nadeau, J.L.; Pompa, P.P. InP/ZnS as a safer alternative to CdSe/ZnS core/shell quantum dots: In vitro and in vivo toxicity assessment. Nanoscale 2013, 5, 307–317. [Google Scholar] [CrossRef] [PubMed]
- Bang, E.; Choi, Y.; Cho, J.; Suh, Y.-H.; Ban, H.W.; Son, J.S.; Park, J. Large-scale synthesis of highly luminescent InP@ZnS quantum dots using elemental phosphorus precursor. Chem. Mater. 2017, 29, 4236–4243. [Google Scholar] [CrossRef]
- Friedfeld, M.R.; Johnson, D.A.; Cossairt, B.M. Conversion of InP clusters to quantum dots. Inorg. Chem. 2019, 58, 803–810. [Google Scholar] [CrossRef]
- Clarke, M.T.; Viscomi, F.N.; Chamberlain, T.W.; Hondow, N.; Adawi, A.M.; Sturge, J.; Erwin, S.C.; Bouillard, J.-S.G.; Tamang, S.; Stasiuk, G.J. Synthesis of super bright indium phosphide colloidal quantum dots through thermal diffusion. Commun. Chem. 2019, 2, 36. [Google Scholar] [CrossRef] [Green Version]
- Tamang, S.; Lincheneau, C.; Hermans, Y.; Jeong, S.; Reiss, P. Chemistry of InP nanocrystal syntheses. Chem. Mater. 2016, 28, 2491–2506. [Google Scholar] [CrossRef]
- Kim, Y.; Ham, S.; Jang, H.; Min, J.H.; Chung, H.; Lee, J.; Kim, D.; Jang, E. Bright and uniform green light emitting InP/ZnSe/ZnS quantum dots for wide color gamut displays. ACS Appl. Nano Mater. 2019, 2, 1496–1504. [Google Scholar] [CrossRef]
- Reid, K.R.; McBride, J.R.; Freymeyer, N.J.; Thal, L.B.; Rosenthal, S.J. Chemical structure, ensemble and single-particle spectroscopy of thick-shell InP–ZnSe quantum dots. Nano Lett. 2018, 18, 709–716. [Google Scholar] [CrossRef]
- Zhou, L.; Yu, B.; Huang, L.; Cao, H.; Lin, D.; Jing, Y.; Wali, F.; Qu, J. Nonblinking core–multishell InP/ZnSe/ZnS quantum dot bioconjugates for super-resolution imaging. ACS Appl. Nano Mater. 2022, 5, 18742–18752. [Google Scholar] [CrossRef]
- Resch-Genger, U.; Grabolle, M.; Cavaliere-Jaricot, S.; Nitschke, R.; Nann, T. Quantum dots versus organic dyes as fluorescent labels. Nat. Meth. 2008, 5, 763–775. [Google Scholar] [CrossRef] [PubMed]
- Seixas de Melo, J.; Takato, S.; Sousa, M.; Melo, M.J.; Parola, A.J. Revisiting Perkin’s dye(s): The spectroscopy and photophysics of two new mauveine compounds (B2 and C). Chem. Commun. 2007, 25, 2624–2626. [Google Scholar] [CrossRef]
- Müllerová, L.; Marková, K.; Obruča, S.; Mravec, F. Use of flavin-related cellular autofluorescence to monitor processes in microbial biotechnology. Microorganisms 2022, 10, 1179. [Google Scholar] [CrossRef] [PubMed]
- Nadeau, J.; Carlini, L. Fluorescence Lifetime Imaging Microscopy (FLIM) of quantum dots in living cells. Proc. SPIE 2013, 8595, 96–105. [Google Scholar] [CrossRef]
- Damalakiene, L.; Karabanovas, V.; Bagdonas, S.; Rotomskis, R. Fluorescence-lifetime imaging microscopy for visualization of quantum dots’ endocytic pathway. Int. J. Mol. Sci. 2016, 17, 473. [Google Scholar] [CrossRef] [Green Version]
- Ramos-Gomes, F.; Bode, J.; Sukhanova, A.; Bozrova, S.V.; Saccomano, M.; Mitkovski, M.; Krueger, J.E.; Wege, A.K.; Stuehmer, W.; Samokhvalov, P.S.; et al. Single- and two-photon imaging of human micrometastases and disseminated tumour cells with conjugates of nanobodies and quantum dots. Sci. Rep. 2018, 8, 4595. [Google Scholar] [CrossRef] [Green Version]
- Ni, H.; Wang, Y.; Tang, T.; Yu, W.; Li, D.; He, M.; Chen, R.; Zhang, M.; Qian, J. Quantum dots assisted in vivo two-photon microscopy with NIR-II emission. Photon. Res. 2022, 10, 189–196. [Google Scholar] [CrossRef]
- Parray, H.A.; Shukla, S.; Samal, S.; Shrivastava, T.; Ahmed, S.; Sharma, C.; Kumar, R. Hybridoma technology a versatile method for isolation of monoclonal antibodies, its applicability across species, limitations, advancement and future perspectives. Int. Immunopharmacol. 2020, 85, 106639. [Google Scholar] [CrossRef]
- Sakakibara, S.; Arimori, T.; Yamashita, K.; Jinzai, H.; Motooka, D.; Nakamura, S.; Li, S.; Takeda, K.; Katayama, J.; El Hussien, M.A.; et al. Clonal evolution and antigen recognition of anti-nuclear antibodies in acute systemic lupus erythematosus. Sci. Rep. 2017, 7, 16428. [Google Scholar] [CrossRef] [Green Version]
- Bannas, P.; Hambach, J.; Koch-Nolte, F. Nanobodies and nanobody-based human heavy chain antibodies as antitumor therapeutics. Front. Immunol. 2017, 8, 1603. [Google Scholar] [CrossRef] [PubMed]
- Fan, Q.; Cai, H.; Yang, H.; Li, L.; Yuan, C.; Lu, X.; Wan, L. Biological evaluation of 131I- and CF750-labeled Dmab(scFv)-Fc antibodies for xenograft imaging of CD25-positive tumors. BioMed Res. Int. 2014, 2014, 459676. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sukhanova, A.; Even-Desrumeaux, K.; Kisserli, A.; Tabary, T.; Reveil, B.; Millot, J.-M.; Chames, P.; Baty, D.; Artemyev, M.; Oleinikov, V.; et al. Oriented conjugates of single-domain antibodies and quantum dots: Toward a new generation of ultrasmall diagnostic nanoprobes. Nanomed. Nanotechnol. Biol. Med. 2012, 8, 516–525. [Google Scholar] [CrossRef] [PubMed]
- Dumoulin, M.; Conrath, K.; Van Meirhaeghe, A.; Meersman, F.; Heremans, K.; Frenken, L.G.; Muyldermans, S.; Wyns, L.; Matagne, A. Single-domain antibody fragments with high conformational stability. Protein Sci. 2002, 11, 500–515. [Google Scholar] [CrossRef] [PubMed]
- Staus, D.P.; Wingler, L.M.; Strachan, R.T.; Rasmussen, S.G.; Pardon, E.; Ahn, S.; Steyaert, J.; Kobilka, B.K.; Lefkowitz, R.J. Regulation of β2-adrenergic receptor function by conformationally selective single-domain intrabodies. Mol. Pharmacol. 2014, 85, 472–481. [Google Scholar] [CrossRef] [Green Version]
- Liu, J.L.; Goldman, E.R.; Zabetakis, D.; Walper, S.A.; Turner, K.B.; Shriver-Lake, L.C.; Anderson, G.P. Enhanced production of a single domain antibody with an engineered stabilizing extra disulfide bond. Microb. Cell Fact. 2015, 14, 158. [Google Scholar] [CrossRef] [Green Version]
- Brun, M.P.; Gauzy-Lazo, L. Protocols for lysine conjugation. Methods Mol. Biol. 2013, 1045, 173–187. [Google Scholar] [CrossRef]
- Brazhnik, K.; Nabiev, I.; Sukhanova, A. Oriented conjugation of single-domain antibodies and quantum dots. Methods Mol. Biol. 2014, 1199, 129–140. [Google Scholar] [CrossRef]
- Gainkam, L.O.; Huang, L.; Caveliers, V.; Keyaerts, M.; Hernot, S.; Vaneycken, I.; Vanhove, C.; Revets, H.; De Baetselier, P.; Lahoutte, T. Comparison of the biodistribution and tumor targeting of two 99mTc-labeled anti-EGFR nanobodies in mice, using pinhole SPECT/micro-CT. J. Nucl. Med. 2008, 49, 788–795. [Google Scholar] [CrossRef] [Green Version]
- Keyaerts, M.; Xavier, C.; Heemskerk, J.; Devoogdt, N.; Everaert, H.; Ackaert, C.; Vanhoeij, M.; Duhoux, F.P.; Gevaert, T.; Simon, P.; et al. Phase I study of 68Ga-HER2-nanobody for PET/CT assessment of HER2 expression in breast carcinoma. J. Nucl. Med. 2016, 57, 27–33. [Google Scholar] [CrossRef] [Green Version]
- Lv, G.; Sun, X.; Qiu, L.; Sun, Y.; Li, K.; Liu, Q.; Zhao, Q.; Qin, S.; Lin, J. PET imaging of tumor PD-L1 expression with a highly specific nonblocking single-domain antibody. J. Nucl. Med. 2020, 61, 117–122. [Google Scholar] [CrossRef] [PubMed]
- Lecocq, Q.; Zeven, K.; De Vlaeminck, Y.; Martens, S.; Massa, S.; Goyvaerts, C.; Raes, G.; Keyaerts, M.; Breckpot, K.; Devoogdt, N. Noninvasive imaging of the immune checkpoint LAG-3 using nanobodies, from development to pre-clinical use. Biomolecules 2019, 9, 548. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Movahedi, K.; Schoonooghe, S.; Laoui, D.; Houbracken, I.; Waelput, W.; Breckpot, K.; Bouwens, L.; Lahoutte, T.; De Baetselier, P.; Raes, G.; et al. Nanobody-based targeting of the macrophage mannose receptor for effective in vivo imaging of tumor-associated macrophages. Cancer Res. 2012, 72, 4165–4177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cortez-Retamozo, V.; Lauwereys, M.; Hassanzadeh Gh, G.; Gobert, M.; Conrath, K.; Muyldermans, S.; De Baetselier, P.; Revets, H. Efficient tumor targeting by single-domain antibody fragments of camels. Int. J. Cancer 2002, 98, 456–462. [Google Scholar] [CrossRef]
- Coppieters, K.; Dreier, T.; Silence, K.; de Haard, H.; Lauwereys, M.; Casteels, P.; Beirnaert, E.; Jonckheere, H.; Van de Wiele, C.; Staelens, L.; et al. Formatted anti-tumor necrosis factor alpha VHH proteins derived from camelids show superior potency and targeting to inflamed joints in a murine model of collagen-induced arthritis. Arthritis Rheum. 2006, 54, 1856–1866. [Google Scholar] [CrossRef]
- Kibria, M.G.; Akazawa-Ogawa, Y.; Rahman, N.; Hagihara, Y.; Kuroda, Y. The immunogenicity of an anti-EGFR single domain antibody (V(HH)) is enhanced by misfolded amorphous aggregation but not by heat-induced aggregation. Eur. J. Pharm. Biopharm. Off. J. Arb. Pharm. Verfahr. e.V 2020, 152, 164–174. [Google Scholar] [CrossRef]
- Wu, Y.; Jiang, S.; Ying, T. Single-Domain Antibodies As Therapeutics against Human Viral Diseases. Front. Immunol. 2017, 8, 1802. [Google Scholar] [CrossRef] [Green Version]
- Rossotti, M.A.; Bélanger, K.; Henry, K.A.; Tanha, J. Immunogenicity and humanization of single-domain antibodies. FEBS J. 2022, 289, 4304–4327. [Google Scholar] [CrossRef]
- Jovčevska, I.; Muyldermans, S. The Therapeutic Potential of Nanobodies. BioDrugs Clin. Immunother. Biopharm. Gene Ther. 2020, 34, 11–26. [Google Scholar] [CrossRef] [Green Version]
- Sukhanova, A.; Ramos-Gomes, F.; Chames, P.; Sokolov, P.; Baty, D.; Alves, F.; Nabiev, I. Multiphoton Deep-Tissue Imaging of Micrometastases and Disseminated Cancer Cells Using Conjugates of Quantum Dots and Single-Domain Antibodies. Methods Mol. Biol. 2021, 2350, 105–123. [Google Scholar] [CrossRef]
- Zhao, L.; Liu, C.; Xing, Y.; He, J.; O’Doherty, J.; Huang, W.; Zhao, J. Development of a 99mTc-Labeled Single-Domain Antibody for SPECT/CT Assessment of HER2 Expression in Breast Cancer. Mol. Pharm. 2021, 18, 3616–3622. [Google Scholar] [CrossRef] [PubMed]
- Broos, K.; Lecocq, Q.; Xavier, C.; Bridoux, J.; Nguyen, T.T.; Corthals, J.; Schoonooghe, S.; Lion, E.; Raes, G.; Keyaerts, M.; et al. Evaluating a Single Domain Antibody Targeting Human PD-L1 as a Nuclear Imaging and Therapeutic Agent. Cancers 2019, 11, 872. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Feng, Y.; Meshaw, R.; McDougald, D.; Zhou, Z.; Zhao, X.-G.; Jannetti, S.A.; Reiman, R.E.; Pippen, E.; Marjoram, R.; Schaal, J.L.; et al. Evaluation of an 131I-labeled HER2-specific single domain antibody fragment for the radiopharmaceutical therapy of HER2-expressing cancers. Sci. Rep. 2022, 12, 3020. [Google Scholar] [CrossRef] [PubMed]
- Villalva, M.D.; Agarwal, V.; Ulanova, M.; Sachdev, P.S.; Braidy, N. Quantum dots as a theranostic approach in Alzheimer’s disease: A systematic review. Nanomed. Nanotechnol. Biol. Med. 2021, 16, 1595–1611. [Google Scholar] [CrossRef] [PubMed]
- Kunheri, B.; Raj, R.V.; Vijaykumar, D.K.; Pavithran, K. Impact of St. Gallen surrogate classification for intrinsic breast cancer sub-types on disease features, recurrence, and survival in South Indian patients. Ind. J. Cancer 2020, 57, 49–54. [Google Scholar] [CrossRef] [PubMed]
- Smith, A.M.; Mancini, M.C.; Nie, S. Bioimaging: Second window for in vivo imaging. Nat. Nanotechnol. 2009, 4, 710–711. [Google Scholar] [CrossRef] [Green Version]
- Gómez-Gaviro, M.V.; Sanderson, D.; Ripoll, J.; Desco, M. Biomedical applications of tissue clearing and three-dimensional imaging in health and disease. iScience 2020, 23, 101432. [Google Scholar] [CrossRef]
Proportion of Epithelial Cells Expressing Ki-67 * | Normal Tissue | Hyperplasia | Mammary Intraepithelial Neoplasia | Carcinoma |
---|---|---|---|---|
7% | 39% | 55% | 72% | |
SMA | ++ | ++− | +−− | - |
SMMHC | ++ | ++ | ++− | - |
CK14 | ++ | ++ | ++− | - |
p63 | ++ | ++− | +−− | - |
Imaging Method | Multiplexing | Quantity | Depth of Imaging | Resolution | Refs. |
---|---|---|---|---|---|
Phase-contrast microscopy | few | semi | ~1–10 μm | ~10 nm | [101,102] |
Confocal microscopy | yes | yes | ~100–100 μm | ~100 nm | [103,104] |
Multiphoton microscopy | yes | yes | ~100–1000 μm | ~10–100 nm | [105,106] |
Optical coherence tomography | no | semi | ~1 mm | ~1–10 μm | [107,108] |
Raman spectroscopy | few | semi | ~1–10 mm | ~10–100 nm | [109,110] |
Fluorescence molecular tomography | yes | yes | ~1 cm | ~1 mm | [111] |
Photoacoustic microscopy | few | yes | ~1–10 cm | ~10–100 μm | [112,113] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sokolov, P.; Nifontova, G.; Samokhvalov, P.; Karaulov, A.; Sukhanova, A.; Nabiev, I. Nontoxic Fluorescent Nanoprobes for Multiplexed Detection and 3D Imaging of Tumor Markers in Breast Cancer. Pharmaceutics 2023, 15, 946. https://doi.org/10.3390/pharmaceutics15030946
Sokolov P, Nifontova G, Samokhvalov P, Karaulov A, Sukhanova A, Nabiev I. Nontoxic Fluorescent Nanoprobes for Multiplexed Detection and 3D Imaging of Tumor Markers in Breast Cancer. Pharmaceutics. 2023; 15(3):946. https://doi.org/10.3390/pharmaceutics15030946
Chicago/Turabian StyleSokolov, Pavel, Galina Nifontova, Pavel Samokhvalov, Alexander Karaulov, Alyona Sukhanova, and Igor Nabiev. 2023. "Nontoxic Fluorescent Nanoprobes for Multiplexed Detection and 3D Imaging of Tumor Markers in Breast Cancer" Pharmaceutics 15, no. 3: 946. https://doi.org/10.3390/pharmaceutics15030946