Harnessing Protease Activity to Improve Cancer Care

Jaideep S. Dudani; Andrew D. Warren; Sangeeta N. Bhatia

doi:10.1146/annurev-cancerbio-030617-050549

Annual Review of Cancer Biology

Volume 2, 2018

Review Article

Free

Harnessing Protease Activity to Improve Cancer Care

Jaideep S. Dudani^1,2, Andrew D. Warren^1,3, and Sangeeta N. Bhatia^1,3,4,5,6,7
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Affiliations: ¹Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; email: [email protected], [email protected], [email protected] ²Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA ³Harvard–MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA ⁴Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA ⁵Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA ⁶Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts 02139, USA ⁷Howard Hughes Medical Institute, Cambridge, Massachusetts 02139, USA
Vol. 2:353-376 (Volume publication date March 2018) https://doi.org/10.1146/annurev-cancerbio-030617-050549
First published as a Review in Advance on December 08, 2017
© Annual Reviews

Abstract

Proteolysis plays critical roles in normal and pathologic physiology; these enzymes are intricately involved in cancer progression and spread. Our understanding of protease function has advanced from nonspecific degrading enzymes to a modern appreciation of their diverse roles in posttranslational modification and signaling in a complex microenvironment. This new understanding has led to next-generation diagnostics and therapeutics that exploit protease activity in cancer. For diagnostics, protease activity may be measured as a biomarker of cancer, with wide-ranging utility from early detection to monitoring therapeutic response. Therapeutically, while broad inhibition of protease activity proved disappointing, new approaches that more specifically modulate proteases in concert with secondary targets might enable potent combination therapies. In addition, clinical evaluation is underway for tools that leverage protease activity to activate therapeutics, ranging from imaging agents that monitor surgical margins to immunotherapies with improved specificity. Technologies that interact with, measure, or modulate proteases are poised to improve cancer management on diagnostic and therapeutic fronts to realize the promise of precision medicine.

Keyword(s): activity-based biomarkers, degradomics, protease activity, protease-targeted therapeutics, protease-triggered therapeutics, responsive nanomaterials

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2018-03-04

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Literature Cited

Agard NJ, Mahrus S, Trinidad JC, Lynn A, Burlingame AL, Wells JA. 2012. Global kinetic analysis of proteolysis via quantitative targeted proteomics. PNAS 109:61913–18 [Google Scholar]
Akkari L, Gocheva V, Quick ML, Kester JC, Spencer AK. et al. 2016. Combined deletion of cathepsin protease family members reveals compensatory mechanisms in cancer. Genes Dev 30:2220–32 [Google Scholar]
Bachovchin DA, Koblan LW, Wu W, Liu Y, Li Y. et al. 2014. A high-throughput, multiplexed assay for superfamily-wide profiling of enzyme activity. Nat. Chem. Biol. 10:656–63 [Google Scholar]
Barreira da Silva R, Laird ME, Yatim N, Fiette L, Ingersoll MA, Albert ML. 2015. Dipeptidylpeptidase 4 inhibition enhances lymphocyte trafficking, improving both naturally occurring tumor immunity and immunotherapy. Nat. Immunol. 16:8850–58 [Google Scholar]
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF. et al. 2013. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res 41:D991–95 [Google Scholar]
Basel MT, Shrestha TB, Troyer DL, Bossmann SH. 2011. Protease-sensitive, polymer-caged liposomes: a method for making highly targeted liposomes using triggered release. ACS Nano 5:32162–75 [Google Scholar]
Bergers G, Benjamin LE. 2003. Tumorigenesis and the angiogenic switch. Nat. Rev. Cancer 3:6401–10 [Google Scholar]
Biswas A, Joo K-I, Liu J, Zhao M, Fan G. et al. 2011. Endoprotease-mediated intracellular protein delivery using nanocapsules. ACS Nano 5:21385–94 [Google Scholar]
Blum G, von Degenfeld G, Merchant MJ, Blau HM, Bogyo M. 2007. Noninvasive optical imaging of cysteine protease activity using fluorescently quenched activity-based probes. Nat. Chem. Biol. 3:10668–77 [Google Scholar]
Borgoño CA, Diamandis EP. 2004. The emerging roles of human tissue kallikreins in cancer. Nat. Rev. Cancer 4:11876–90 [Google Scholar]
Boulware KT, Daugherty PS. 2006. Protease specificity determination by using cellular libraries of peptide substrates (CLiPS). PNAS. 103207583–88
Braun GB, Sugahara KN, Yu OM, Kotamraju VR, Mölder T. et al. 2016. Urokinase-controlled tumor penetrating peptide. J. Control. Release 232:188–95 [Google Scholar]
Bremer C, Tung CH, Weissleder R. 2001. In vivo molecular target assessment of matrix metalloproteinase inhibition. Nat. Med. 7:6743–48 [Google Scholar]
Brown PO, Palmer C. 2009. The preclinical natural history of serous ovarian cancer: defining the target for early detection. PLOS Med 6:7e1000114 [Google Scholar]
Chang PV, Dube DH, Sletten EM, Bertozzi CR. 2010. A strategy for the selective imaging of glycans using caged metabolic precursors. J. Am. Chem. Soc. 132:289516–18 [Google Scholar]
Chen C-H, Miller MA, Sarkar A, Beste MT, Isaacson KB. et al. 2013. Multiplexed protease activity assay for low-volume clinical samples using droplet-based microfluidics and its application to endometriosis. J. Am. Chem. Soc. 135:51645–48 [Google Scholar]
Choi J, Kim S, Yoo D, Shin T-H, Kim H. et al. 2017. Distance-dependent magnetic resonance tuning as a versatile MRI sensing platform for biological targets. Nat. Mater. 18:537–42 [Google Scholar]
Choi KY, Swierczewska M, Lee S, Chen X. 2012. Protease-activated drug development. Theranostics 2:2156–78 [Google Scholar]
Chuang C-H, Chuang K-H, Wang H-E, Roffler SR, Shiea J. et al. 2012. In vivo positron emission tomography imaging of protease activity by generation of a hydrophobic product from a noninhibitory protease substrate. Clin. Cancer Res. 18:1238–47 [Google Scholar]
Coussens LM, Fingleton B, Matrisian LM. 2002. Matrix metalloproteinase inhibitors and cancer—trials and tribulations. Science 295:55642387–92 [Google Scholar]
Cravatt BF, Wright AT, Kozarich JW. 2008. Activity-based protein profiling: from enzyme chemistry to proteomic chemistry. Annu. Rev. Biochem. 77:383–414 [Google Scholar]
Crisp JL, Savariar EN, Glasgow HL, Ellies LG, Whitney MA, Tsien RY. 2014. Dual targeting of integrin α_vβ₃ and matrix metalloproteinase-2 for optical imaging of tumors and chemotherapeutic delivery. Mol. Cancer Ther. 13:61514–25 [Google Scholar]
Danino T, Prindle A, Kwong GA, Skalak M, Li H. et al. 2015. Programmable probiotics for detection of cancer in urine. Sci. Transl. Med. 7:289289ra84 [Google Scholar]
Darragh MR, Schneider EL, Lou J, Phojanakong PJ, Farady CJ. et al. 2010. Tumor detection by imaging proteolytic activity. Cancer Res 70:41505–12 [Google Scholar]
Deng SJ, Bickett DM, Mitchell JL, Lambert MH, Blackburn RK. et al. 2000. Substrate specificity of human collagenase 3 assessed using a phage-displayed peptide library. J. Biol. Chem. 275:4031422–27 [Google Scholar]
Desnoyers LR, Vasiljeva O, Richardson JH, Yang A, Menendez EEM. et al. 2013. Tumor-specific activation of an EGFR-targeting probody enhances therapeutic index. Sci. Transl. Med. 5:207207ra144 [Google Scholar]
Devy L, Huang L, Naa L, Yanamandra N, Pieters H. et al. 2009. Selective inhibition of matrix metalloproteinase-14 blocks tumor growth, invasion, and angiogenesis. Cancer Res 69:41517–26 [Google Scholar]
Din MO, Danino T, Prindle A, Skalak M, Selimkhanov J. et al. 2016. Synchronized cycles of bacterial lysis for in vivo delivery. Nature 536:761481–85 [Google Scholar]
Doronina SO, Toki BE, Torgov MY, Mendelsohn BA, Cerveny CG. et al. 2003. Development of potent monoclonal antibody auristatin conjugates for cancer therapy. Nat. Biotechnol. 21:7778–84 [Google Scholar]
Dudani JS, Buss CG, Akana RTK, Kwong GA, Bhatia SN. 2016. Sustained-release synthetic biomarkers for monitoring thrombosis and inflammation using point-of-care compatible readouts. Adv. Funct. Mater. 26:2919–28 [Google Scholar]
Dudani JS, Jain PK, Kwong GA, Stevens KR, Bhatia SN. 2015. Photoactivated spatiotemporally-responsive nanosensors of in vivo protease activity. ACS Nano 9:1211708–17 [Google Scholar]
Dufour A, Sampson NS, Li J, Kuscu C, Rizzo RC. et al. 2011. Small-molecule anticancer compounds selectively target the hemopexin domain of matrix metalloproteinase-9. Cancer Res 71:144977–88 [Google Scholar]
Edgington LE, Berger AB, Blum G, Albrow VE, Paulick MG. et al. 2009. Noninvasive optical imaging of apoptosis by caspase-targeted activity-based probes. Nat. Med. 15:8967–73 [Google Scholar]
Edgington LE, Verdoes M, Bogyo M. 2011. Functional imaging of proteases: recent advances in the design and application of substrate-based and activity-based probes. Curr. Opin. Chem. Biol. 15:6798–805 [Google Scholar]
Edgington LE, Verdoes M, Ortega A, Withana NP, Lee J. et al. 2013. Functional imaging of legumain in cancer using a new quenched activity-based probe. J. Am. Chem. Soc. 135:1174–82 [Google Scholar]
Egeblad M, Werb Z. 2002. New functions for the matrix metalloproteinases in cancer progression. Nat. Rev. Cancer 2:3161–74 [Google Scholar]
Etzioni R, Urban N, Ramsey S, McIntosh M, Schwartz S. et al. 2003. The case for early detection. Nat. Rev. Cancer 3:4243–52 [Google Scholar]
Fortelny N, Cox JH, Kappelhoff R, Starr AE, Lange PF. et al. 2014. Network analyses reveal pervasive functional regulation between proteases in the human protease web. PLOS Biol 12:5e1001869 [Google Scholar]
Fosgerau K, Hoffmann T. 2015. Peptide therapeutics: current status and future directions. Drug Discov. Today 20:1122–28 [Google Scholar]
Friedman AA, Letai A, Fisher DE, Flaherty KT. 2015. Precision medicine for cancer with next-generation functional diagnostics. Nat. Rev. Cancer. 15:12747–56 [Google Scholar]
Gocheva V, Joyce JA. 2007. Cysteine cathepsins and the cutting edge of cancer invasion. Cell Cycle 6:160–64 [Google Scholar]
Grimm J, Kirsch DG, Windsor SD, Kim CFB, Santiago PM. et al. 2005. Use of gene expression profiling to direct in vivo molecular imaging of lung cancer. PNAS 102:4014404–9 [Google Scholar]
GTEx Consort. 2013. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45:6580–85 [Google Scholar]
Haeckel A, Appler F, Ariza de Schellenberger A, Schellenberger E. 2016. XTEN as biological alternative to PEGylation allows complete expression of a protease-activatable killin-based cytostatic. PLOS ONE 11:6e0157193 [Google Scholar]
Han X, Bryson PD, Zhao Y, Cinay GE, Li S. et al. 2017. Masked chimeric antigen receptor for tumor-specific activation. Mol. Ther. 25:1274–84 [Google Scholar]
Hanahan D, Weinberg RA. 2011. Hallmarks of cancer: the next generation. Cell 144:5646–74 [Google Scholar]
Hanash SM, Pitteri SJ, Faca VM. 2008. Mining the plasma proteome for cancer biomarkers. Nature 452:7187571–79 [Google Scholar]
Harris JL, Backes BJ, Leonetti F, Mahrus S, Ellman JA, Craik CS. 2000. Rapid and general profiling of protease specificity by using combinatorial fluorogenic substrate libraries. PNAS 97:147754–59 [Google Scholar]
Harris TJ, von Maltzahn G, Derfus AM, Ruoslahti E, Bhatia SN. 2006. Proteolytic actuation of nanoparticle self-assembly. Angew. Chem. Int. Ed. 45:193161–65 [Google Scholar]
Harris TJ, von Maltzahn G, Lord ME, Park J-H, Agrawal A. et al. 2008. Protease-triggered unveiling of bioactive nanoparticles. Small 4:91307–12 [Google Scholar]
Hatakeyama H, Akita H, Ito E, Hayashi Y, Oishi M. et al. 2011. Systemic delivery of siRNA to tumors using a lipid nanoparticle containing a tumor-specific cleavable PEG-lipid. Biomaterials 32:184306–16 [Google Scholar]
Hilderbrand SA, Weissleder R. 2010. Near-infrared fluorescence: application to in vivo molecular imaging. Curr. Opin. Chem. Biol. 14:171–79 [Google Scholar]
Hockla A, Miller E, Salameh MA, Copland JA, Radisky DC, Radisky ES. 2012. PRSS3/mesotrypsin is a therapeutic target for metastatic prostate cancer. Mol. Cancer Res. 10:121555–66 [Google Scholar]
Hori SS, Gambhir SS. 2011. Mathematical model identifies blood biomarker-based early cancer detection strategies and limitations. Sci. Transl. Med. 3:109109ra116 [Google Scholar]
Huang S, Shao K, Liu Y, Kuang Y, Li J. et al. 2013. Tumor-targeting and microenvironment-responsive smart nanoparticles for combination therapy of antiangiogenesis and apoptosis. ACS Nano 7:32860–71 [Google Scholar]
Igarashi Y, Eroshkin A, Gramatikova S, Gramatikoff K, Zhang Y. et al. 2007. CutDB: a proteolytic event database. Nucleic Acids Res 35:D546–49 [Google Scholar]
Inst. Med. 2007. Cancer Biomarkers: The Promises and Challenges of Improving Detection and Treatment Washington, DC: Natl. Acad. Press
Jessani N, Liu Y, Humphrey M, Cravatt BF. 2002. Enzyme activity profiles of the secreted and membrane proteome that depict cancer cell invasiveness. PNAS 99:1610335–40 [Google Scholar]
Jiang T, Olson ES, Nguyen QT, Roy M, Jennings PA, Tsien RY. 2004. Tumor imaging by means of proteolytic activation of cell-penetrating peptides. PNAS 101:5117867–72 [Google Scholar]
Joyce JA, Baruch A, Chehade K, Meyer-Morse N, Giraudo E. et al. 2004. Cathepsin cysteine proteases are effectors of invasive growth and angiogenesis during multistage tumorigenesis. Cancer Cell 5:5443–53 [Google Scholar]
Kanavos P. 2006. The rising burden of cancer in the developing world. Ann. Oncol. 17:Suppl. 8viii15–23 [Google Scholar]
Kasperkiewicz P, Poreba M, Snipas SJ, Parker H, Winterbourn CC. et al. 2014. Design of ultrasensitive probes for human neutrophil elastase through hybrid combinatorial substrate library profiling. PNAS 111:72518–23 [Google Scholar]
Kaufman HL, Kohlhapp FJ, Zloza A. 2015. Oncolytic viruses: a new class of immunotherapy drugs. Nat. Rev. Drug Discov. 14:9642–62 [Google Scholar]
Kessenbrock K, Plaks V, Werb Z. 2010. Matrix metalloproteinases: regulators of the tumor microenvironment. Cell 141:152–67 [Google Scholar]
Kinoh H, Inoue M, Washizawa K, Yamamoto T, Fujikawa S. et al. 2004. Generation of a recombinant Sendai virus that is selectively activated and lyses human tumor cells expressing matrix metalloproteinases. Gene Ther 11:141137–45 [Google Scholar]
Kleifeld O, Doucet A, auf dem Keller U, Prudova A, Schilling O. et al. 2010. Isotopic labeling of terminal amines in complex samples identifies protein N-termini and protease cleavage products. Nat. Biotechnol. 28:3281–88 [Google Scholar]
Klezovitch O, Chevillet J, Mirosevich J, Roberts RL, Matusik RJ, Vasioukhin V. 2004. Hepsin promotes prostate cancer progression and metastasis. Cancer Cell 6:2185–95 [Google Scholar]
Kromann-Hansen T, Oldenburg E, Yung KWY, Ghassabeh GH, Muyldermans S. et al. 2016. A camelid-derived antibody fragment targeting the active site of a serine protease balances between inhibitor and substrate behavior. J. Biol. Chem. 291:2915156–68 [Google Scholar]
Kwon EJ, Dudani JS, Bhatia SN. 2017. Ultrasensitive tumour-penetrating nanosensors of protease activity. Nat. Biomed. Eng. 1:0054 [Google Scholar]
Kwon EJ, Lo JH, Bhatia SN. 2015. Smart nanosystems: bio-inspired technologies that interact with the host environment. PNAS 112:4714460–66 [Google Scholar]
Kwong GA, Dudani JS, Carrodeguas E, Mazumdar EV, Zekavat SM, Bhatia SN. 2015. Mathematical framework for activity-based cancer biomarkers. PNAS 112:4112627–32 [Google Scholar]
Kwong GA, von Maltzahn G, Murugappan G, Abudayyeh O, Mo S. et al. 2013. Mass-encoded synthetic biomarkers for multiplexed urinary monitoring of disease. Nat. Biotechnol. 31:163–70 [Google Scholar]
La Thangue NB, Kerr DJ. 2011. Predictive biomarkers: a paradigm shift towards personalized cancer medicine. Nat. Rev. Clin. Oncol. 8:10587–96 [Google Scholar]
LeBeau AM, Denmeade SR. 2015. Protease-activated pore-forming peptides for the treatment and imaging of prostate cancer. Mol. Cancer Ther. 14:3659–68 [Google Scholar]
LeBeau AM, Lee M, Murphy ST, Hann BC, Warren RS. et al. 2013. Imaging a functional tumorigenic biomarker in the transformed epithelium. PNAS 110:193–98 [Google Scholar]
Li J, Dowdy S, Tipton T, Podratz K, Lu W-G. et al. 2009. HE4 as a biomarker for ovarian and endometrial cancer management. Expert Rev. Mol. Diagn. 9:6555–66 [Google Scholar]
Liu S, Aaronson H, Mitola DJ, Leppla SH, Bugge TH. 2003. Potent antitumor activity of a urokinase-activated engineered anthrax toxin. PNAS 100:2657–62 [Google Scholar]
Liu S, Netzel-Arnett S, Birkedal-Hansen H, Leppla SH. 2000. Tumor cell-selective cytotoxicity of matrix metalloproteinase-activated anthrax toxin. Cancer Res 60:216061–67 [Google Scholar]
Liu S, Redeye V, Kuremsky JG, Kuhnen M, Molinolo A. et al. 2005. Intermolecular complementation achieves high-specificity tumor targeting by anthrax toxin. Nat. Biotechnol. 23:6725–30 [Google Scholar]
López-Otín C, Bond JS. 2008. Proteases: multifunctional enzymes in life and disease. J. Biol. Chem. 283:4530433–37 [Google Scholar]
López-Otín C, Matrisian LM. 2007. Emerging roles of proteases in tumour suppression. Nat. Rev. Cancer 7:10800–8 [Google Scholar]
López-Otín C, Overall CM. 2002. Protease degradomics: a new challenge for proteomics. Nat. Rev. Mol. Cell Biol. 3:7509–19 [Google Scholar]
Luo Y, Zhou H, Krueger J, Kaplan C, Lee S-H. et al. 2006. Targeting tumor-associated macrophages as a novel strategy against breast cancer. J. Clin. Investig. 116:82132–41 [Google Scholar]
Manasanch EE, Orlowski RZ. 2017. Proteasome inhibitors in cancer therapy. Nat. Rev. Clin. Oncol. 14:417–33 [Google Scholar]
Marshall DC, Lyman SK, McCauley S, Kovalenko M, Spangler R. et al. 2015. Selective allosteric inhibition of MMP9 is efficacious in preclinical models of ulcerative colitis and colorectal cancer. PLOS ONE 10:5e0127063 [Google Scholar]
Mehan MR, Ayers D, Thirstrup D, Xiong W, Ostroff RM. et al. 2012. Protein signature of lung cancer tissues. PLOS ONE 7:4e35157 [Google Scholar]
Miller MA, Barkal L, Jeng K, Herrlich A, Moss M. et al. 2011. Proteolytic Activity Matrix Analysis (PrAMA) for simultaneous determination of multiple protease activities. Integr. Biol. 3:4422–38 [Google Scholar]
Miller MA, Oudin MJ, Sullivan RJ, Wang SJ, Meyer AS. et al. 2016. Reduced proteolytic shedding of receptor tyrosine kinases is a post-translational mechanism of kinase inhibitor resistance. Cancer Discov 6:4382–99 [Google Scholar]
Mitsiades N, Yu W, Poulaki V, Tsokos M, Stamenkovic I. 2001. Matrix metalloproteinase-7-mediated cleavage of Fas ligand protects tumor cells from chemotherapeutic drug cytotoxicity. Cancer Res 61:2577–81 [Google Scholar]
Mühlebach MD, Schaser T, Zimmermann M, Armeanu S, Hanschmann K-MO. et al. 2010. Liver cancer protease activity profiles support therapeutic options with matrix metalloproteinase-activatable oncolytic measles virus. Cancer Res 70:197620–29 [Google Scholar]
Naba A, Clauser KR, Hoersch S, Liu H, Carr SA, Hynes RO. 2012. The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices. Mol. Cell. Proteom. 11:4M111.014647 [Google Scholar]
Naba A, Clauser KR, Lamar JM, Carr SA, Hynes RO. 2014. Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters. eLife 3:e01308 [Google Scholar]
Nakasone ES, Askautrud HA, Kees T, Park J-H, Plaks V. et al. 2012. Imaging tumor-stroma interactions during chemotherapy reveals contributions of the microenvironment to resistance. Cancer Cell 21:4488–503 [Google Scholar]
Nam DH, Rodriguez C, Remacle AG, Strongin AY, Ge X. 2016. Active-site MMP-selective antibody inhibitors discovered from convex paratope synthetic libraries. PNAS 113:5214970–75 [Google Scholar]
Natl. Cancer Inst. 2017. Cancer stat facts: ovarian cancer SEER (Surveill. Epidemiol. End Results) cancer stat facts. https://seer.cancer.gov/statfacts/html/ovary.html
Nguyen QT, Olson ES, Aguilera TA, Jiang T, Scadeng M. et al. 2010. Surgery with molecular fluorescence imaging using activatable cell-penetrating peptides decreases residual cancer and improves survival. PNAS 107:94317–22 [Google Scholar]
O'Donoghue AJ, Eroy-Reveles AA, Knudsen GM, Ingram J, Zhou M. et al. 2012. Global identification of peptidase specificity by multiplex substrate profiling. Nat. Methods 9:111095–100 [Google Scholar]
Olson ES, Jiang T, Aguilera TA, Nguyen QT, Ellies LG. et al. 2010. Activatable cell penetrating peptides linked to nanoparticles as dual probes for in vivo fluorescence and MR imaging of proteases. PNAS 107:94311–16 [Google Scholar]
Olson OC, Joyce JA. 2015. Cysteine cathepsin proteases: regulators of cancer progression and therapeutic response. Nat. Rev. Cancer 15:12712–29 [Google Scholar]
Overall CM, Blobel CP. 2007. In search of partners: linking extracellular proteases to substrates. Nat. Rev. Mol. Cell Biol. 8:3245–57 [Google Scholar]
Pastan I, Hassan R, FitzGerald DJ, Kreitman RJ. 2007. Immunotoxin treatment of cancer. Annu. Rev. Med. 58:221–37 [Google Scholar]
Pérez-Silva JG, Español Y, Velasco G, Quesada V. 2016. The Degradome database: expanding roles of mammalian proteases in life and disease. Nucleic Acids Res 44:D1D351–55 [Google Scholar]
Peschon JJ, Slack JL, Reddy P, Stocking KL, Sunnarborg SW. et al. 1998. An essential role for ectodomain shedding in mammalian development. Science 282:53921281–84 [Google Scholar]
Prensner JR, Rubin MA, Wei JT, Chinnaiyan AM. 2012. Beyond PSA: the next generation of prostate cancer biomarkers. Sci. Transl. Med. 4:127127rv3 [Google Scholar]
Quail DF, Joyce JA. 2013. Microenvironmental regulation of tumor progression and metastasis. Nat. Med. 19:111423–37 [Google Scholar]
Ratnikov B, Cieplak P, Smith JW. 2009. High throughput substrate phage display for protease profiling. Proteases and Cancer TH Bugge, TM Antalis 93–114 New York: Humana [Google Scholar]
Rawlings ND, Barrett AJ, Finn R. 2016. Twenty years of the MEROPS database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res 44:D343–50 [Google Scholar]
Rawlings ND, Salvesen G. 2013. Handbook of Proteolytic Enzymes London: Academic, 3rd ed..
Romee R, Foley B, Lenvik T, Wang Y, Zhang B. et al. 2013. NK cell CD16 surface expression and function is regulated by a disintegrin and metalloprotease-17 (ADAM17). Blood 121:183599–608 [Google Scholar]
Roy R, Yang J, Moses MA. 2009. Matrix metalloproteinases as novel biomarkers and potential therapeutic targets in human cancer. J. Clin. Oncol. 27:315287–97 [Google Scholar]
Ruoslahti E, Bhatia SN, Sailor MJ. 2010. Targeting of drugs and nanoparticles to tumors. J. Cell Biol. 188:6759–68 [Google Scholar]
Saghatelian A, Jessani N, Joseph A, Humphrey M, Cravatt BF. 2004. Activity-based probes for the proteomic profiling of metalloproteases. PNAS 101:2710000–5 [Google Scholar]
Salisbury CM, Maly DJ, Ellman JA. 2002. Peptide microarrays for the determination of protease substrate specificity. J. Am. Chem. Soc. 124:5014868–70 [Google Scholar]
Sandersjöö L, Jonsson A, Löfblom J. 2015. A new prodrug form of Affibody molecules (pro-Affibody) is selectively activated by cancer-associated proteases. Cell. Mol. Life Sci. 72:71405–15 [Google Scholar]
Sanman LE, Bogyo M. 2014. Activity-based profiling of proteases. Annu. Rev. Biochem. 83:249–73 [Google Scholar]
Savariar EN, Felsen CN, Nashi N, Jiang T, Ellies LG. et al. 2013. Real-time in vivo molecular detection of primary tumors and metastases with ratiometric activatable cell-penetrating peptides. Cancer Res 73:2855–64 [Google Scholar]
Sawyers CL. 2008. The cancer biomarker problem. Nature 452:7187548–52 [Google Scholar]
Schellenberger V, Wang C, Geething NC, Spink BJ, Campbell A. et al. 2009. A recombinant polypeptide extends the in vivo half-life of peptides and proteins in a tunable manner. Nat. Biotechnol. 27:121186–90 [Google Scholar]
Schilling O, Overall CM. 2008. Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites. Nat. Biotechnol. 26:6685–94 [Google Scholar]
Schneider EL, Craik CS. 2009. Positional scanning synthetic combinatorial libraries for substrate profiling. Proteases and Cancer TH Bugge, TM Antalis 59–78 New York: Humana [Google Scholar]
Schuerle S, Dudani JS, Christiansen MG, Anikeeva P, Bhatia SN. 2016. Magnetically actuated protease sensors for in vivo tumor profiling. Nano Lett 16:106303–10 [Google Scholar]
Singh N, Karambelkar A, Gu L, Lin K, Miller JS. et al. 2011. Bioresponsive mesoporous silica nanoparticles for triggered drug release. J. Am. Chem. Soc. 133:4919582–85 [Google Scholar]
Stein V, Alexandrov K. 2014. Protease-based synthetic sensing and signal amplification. PNAS 111:4515934–39 [Google Scholar]
Thorek DLJ, Watson PA, Lee S-G, Ku AT, Bournazos S. et al. 2016. Internalization of secreted antigen–targeted antibodies by the neonatal Fc receptor for precision imaging of the androgen receptor axis. Sci. Transl. Med. 8:367367ra167 [Google Scholar]
Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC. et al. 2012. Safety, activity, and immune correlates of anti–PD-1 antibody in cancer. N. Engl. J. Med. 366:262443–54 [Google Scholar]
Tranchant I, Vera L, Czarny B, Amoura M, Cassar E. et al. 2014. Halogen bonding controls selectivity of FRET substrate probes for MMP-9. Chem. Biol. 21:3408–13 [Google Scholar]
Turk BE, Huang LL, Piro ET, Cantley LC. 2001. Determination of protease cleavage site motifs using mixture-based oriented peptide libraries. Nat. Biotechnol. 19:7661–67 [Google Scholar]
Uhland K. 2006. Matriptase and its putative role in cancer. Cell. Mol. Life Sci. 63:242968–78 [Google Scholar]
Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P. et al. 2015. Tissue-based map of the human proteome. Science 347:62201260419 [Google Scholar]
Vandenbroucke RE, Libert C. 2014. Is there new hope for therapeutic matrix metalloproteinase inhibition?. Nat. Rev. Drug Discov. 13:12904–27 [Google Scholar]
Vandooren J, Geurts N, Martens E, Van den Steen PE, Opdenakker G. 2013. Zymography methods for visualizing hydrolytic enzymes. Nat. Methods 10:3211–20 [Google Scholar]
Verdoes M, Oresic Bender K, Segal E, van der Linden WA, Syed S. et al. 2013. Improved quenched fluorescent probe for imaging of cysteine cathepsin activity. J. Am. Chem. Soc. 135:3914726–30 [Google Scholar]
Villanueva J, Shaffer DR, Philip J, Chaparro CA, Erdjument-Bromage H. et al. 2006. Differential exoprotease activities confer tumor-specific serum peptidome patterns. J. Clin. Investig. 116:1271–84 [Google Scholar]
von Maltzahn G, Harris TJ, Park J-H, Min D-H, Schmidt AJ. et al. 2007. Nanoparticle self-assembly gated by logical proteolytic triggers. J. Am. Chem. Soc. 129:196064–65 [Google Scholar]
Warren AD, Gaylord ST, Ngan KC, Dumont Milutinovic M, Kwong GA. et al. 2014.a Disease detection by ultrasensitive quantification of microdosed synthetic urinary biomarkers. J. Am. Chem. Soc. 136:13709–14 [Google Scholar]
Warren AD, Kwong GA, Wood DK, Lin KY, Bhatia SN. 2014.b Point-of-care diagnostics for noncommunicable diseases using synthetic urinary biomarkers and paper microfluidics. PNAS 111:103671–76 [Google Scholar]
Weissleder R. 2006. Molecular imaging in cancer. Science 312:57771168–71 [Google Scholar]
Weissleder R, Tung C-H, Mahmood U, Bogdanov A. 1999. In vivo imaging of tumors with protease-activated near-infrared fluorescent probes. Nat. Biotechnol. 17:4375–78 [Google Scholar]
Welser K, Adsley R, Moore BM, Chan WC, Aylott JW. 2011. Protease sensing with nanoparticle based platforms. Analyst 136:129–41 [Google Scholar]
Whitley MJ, Cardona DM, Lazarides AL, Spasojevic I, Ferrer JM. et al. 2016. A mouse-human phase 1 co-clinical trial of a protease-activated fluorescent probe for imaging cancer. Sci. Transl. Med. 8:320320ra4 [Google Scholar]
Whitney M, Crisp JL, Olson ES, Aguilera TA, Gross LA. et al. 2010. Parallel in vivo and in vitro selection using phage display identifies protease-dependent tumor-targeting peptides. J. Biol. Chem. 285:2922532–41 [Google Scholar]
WHO (World Health Organ.). 2017. Cancer Fact sheet, Feb. 2017 Geneva: WHO http://www.who.int/mediacentre/factsheets/fs297/en/
Wiernik A, Foley B, Zhang B, Verneris MR, Warlick E. et al. 2013. Targeting natural killer cells to acute myeloid leukemia in vitro with a CD16 × 33 bispecific killer cell engager and ADAM17 inhibition. Clin. Cancer Res. 19:143844–55 [Google Scholar]
Withana NP, Garland M, Verdoes M, Ofori LO, Segal E, Bogyo M. 2016. Labeling of active proteases in fresh-frozen tissues by topical application of quenched activity-based probes. Nat. Protoc. 11:1184–91 [Google Scholar]
Wolff AC, Hammond MEH, Schwartz JN, Hagerty KL, Allred DC. et al. 2007. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. Arch. Pathol. Lab. Med. 131:118–43 [Google Scholar]
Ye D, Shuhendler AJ, Cui L, Tong L, Tee SS. et al. 2014. Bioorthogonal cyclization-mediated in situ self-assembly of small-molecule probes for imaging caspase activity in vivo. Nat. Chem. 6:6519–26 [Google Scholar]
Zhou Q, Gil-Krzewska A, Peruzzi G, Borrego F. 2013. Matrix metalloproteinases inhibition promotes the polyfunctionality of human natural killer cells in therapeutic antibody-based anti-tumour immunotherapy. Clin. Exp. Immunol. 173:1131–39 [Google Scholar]
Zhu L, Wang T, Perche F, Taigind A, Torchilin VP. 2013. Enhanced anticancer activity of nanopreparation containing an MMP2-sensitive PEG-drug conjugate and cell-penetrating moiety. PNAS 110:4217047–52 [Google Scholar]