Submitted 14 August 2015 Accepted 19 November 2015 Published 10 December 2015 Corresponding author Willeke F. Daamen, [email protected]Academic editor Offer Erez Additional Information and Declarations can be found on page 18 DOI 10.7717/peerj.1489 Copyright 2015 Raav´ e et al. Distributed under Creative Commons CC-BY 4.0 OPEN ACCESS Drug delivery systems for ovarian cancer treatment: a systematic review and meta-analysis of animal studies Ren´ e Raav´ e 1 , Rob B.M. de Vries 2 , Leon F. Massuger 3 , Toin H. van Kuppevelt 1 and Willeke F. Daamen 1 1 Department of Biochemistry, Radboud university medical center, Nijmegen, The Netherlands 2 Systematic Review Centre for Laboratory Animal Experimentation, Central Animal Facility, Radboud university medical center, Nijmegen, The Netherlands 3 Department of Obstetrics and Gynaecology, Radboud university medical center, Nijmegen, The Netherlands ABSTRACT Current ovarian cancer treatment involves chemotherapy that has serious limitations, such as rapid clearance, unfavorable biodistribution and severe side effects. To overcome these limitations, drug delivery systems (DDS) have been developed to encapsulate chemotherapeutics for delivery to tumor cells. However, no systematic assessment of the efficacy of chemotherapy by DDS compared to free chemotherapy (not in a DDS) has been performed for animal studies. Here, we assess the efficacy of chemotherapy in DDS on survival and tumor growth inhibition in animal studies. We searched PubMed and EMBASE (via OvidSP) to systematically identify studies evaluating chemotherapeutics encapsulated in DDS for ovarian cancer treatment in animal studies. Studies were assessed for quality and risk of bias. Study characteristics were collected and outcome data (survival/hazard ratio or tumor growth inhibition) were extracted and used for meta-analyses. Meta-analysis was performed to identify and explore which characteristics of DDS influenced treatment efficacy. A total of 44 studies were included after thorough literature screening (2,735 studies found after initial search). The risk of bias was difficult to assess, mainly because of incomplete reporting. A total of 17 studies (377 animals) and 16 studies (259 animals) could be included in the meta-analysis for survival and tumor growth inhibition, respectively. In the majority of the included studies chemotherapeutics entrapped in a DDS significantly improved efficacy over free chemotherapeutics regarding both survival and tumor growth inhibition. Subgroup analyses, however, revealed that cisplatin entrapped in a DDS did not result in additional tumor growth inhibition compared to free cisplatin, although it did result in improved survival. Micelles did not show a significant tumor growth inhibition compared to free chemotherapeutics, which indicates that micelles may not be a suitable DDS for ovarian cancer treatment. Other subgroup analyses, such as targeted versus non-targeted DDS or IV versus IP administration route, did not identify specific characteristics of DDS that affected treatment efficacy. This systematic review shows the potential, but also the limitations of chemotherapy by drug delivery systems for ovarian cancer treatment. For future animal research, we emphasize that data need to be reported with ample attention to detailed reporting. How to cite this article Raav´ e et al. (2015), Drug delivery systems for ovarian cancer treatment: a systematic review and meta-analysis of animal studies. PeerJ 3:e1489; DOI 10.7717/peerj.1489
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Submitted 14 August 2015Accepted 19 November 2015Published 10 December 2015
Additional Information andDeclarations can be found onpage 18
DOI 10.7717/peerj.1489
Copyright2015 Raave et al.
Distributed underCreative Commons CC-BY 4.0
OPEN ACCESS
Drug delivery systems for ovarian cancertreatment: a systematic review andmeta-analysis of animal studiesRene Raave1, Rob B.M. de Vries2, Leon F. Massuger3,Toin H. van Kuppevelt1 and Willeke F. Daamen1
1 Department of Biochemistry, Radboud university medical center, Nijmegen, The Netherlands2 Systematic Review Centre for Laboratory Animal Experimentation, Central Animal Facility,
Radboud university medical center, Nijmegen, The Netherlands3 Department of Obstetrics and Gynaecology, Radboud university medical center, Nijmegen,
The Netherlands
ABSTRACTCurrent ovarian cancer treatment involves chemotherapy that has seriouslimitations, such as rapid clearance, unfavorable biodistribution and severe sideeffects. To overcome these limitations, drug delivery systems (DDS) have beendeveloped to encapsulate chemotherapeutics for delivery to tumor cells. However,no systematic assessment of the efficacy of chemotherapy by DDS compared to freechemotherapy (not in a DDS) has been performed for animal studies. Here, we assessthe efficacy of chemotherapy in DDS on survival and tumor growth inhibition inanimal studies. We searched PubMed and EMBASE (via OvidSP) to systematicallyidentify studies evaluating chemotherapeutics encapsulated in DDS for ovariancancer treatment in animal studies. Studies were assessed for quality and risk ofbias. Study characteristics were collected and outcome data (survival/hazard ratio ortumor growth inhibition) were extracted and used for meta-analyses. Meta-analysiswas performed to identify and explore which characteristics of DDS influencedtreatment efficacy. A total of 44 studies were included after thorough literaturescreening (2,735 studies found after initial search). The risk of bias was difficult toassess, mainly because of incomplete reporting. A total of 17 studies (377 animals)and 16 studies (259 animals) could be included in the meta-analysis for survivaland tumor growth inhibition, respectively. In the majority of the included studieschemotherapeutics entrapped in a DDS significantly improved efficacy over freechemotherapeutics regarding both survival and tumor growth inhibition. Subgroupanalyses, however, revealed that cisplatin entrapped in a DDS did not result inadditional tumor growth inhibition compared to free cisplatin, although it did resultin improved survival. Micelles did not show a significant tumor growth inhibitioncompared to free chemotherapeutics, which indicates that micelles may not be asuitable DDS for ovarian cancer treatment. Other subgroup analyses, such as targetedversus non-targeted DDS or IV versus IP administration route, did not identifyspecific characteristics of DDS that affected treatment efficacy. This systematicreview shows the potential, but also the limitations of chemotherapy by drug deliverysystems for ovarian cancer treatment. For future animal research, we emphasize thatdata need to be reported with ample attention to detailed reporting.
How to cite this article Raave et al. (2015), Drug delivery systems for ovarian cancer treatment: a systematic review and meta-analysis ofanimal studies. PeerJ 3:e1489; DOI 10.7717/peerj.1489
Figure 1 Flow chart of study inclusion. PubMed and EMBASE via OvidSP were searched using developed search strings to identify studies thatused chemotherapeutics in a DDS in ovarian cancer animal models. All studies were first screened by title and abstract according to predefinedinclusion and exclusion criteria. Subsequently studies were more specifically assessed by full text. Screenings were performed by two reviewers (RRand WD). Full text studies excluded for “others” were: (1) no full text was available or only an abstract that did not include sufficient information(n = 12); (2) conference abstract of a previously assessed full-text study (n = 5); (3) the study included only a biodistribution experiment (n = 4).
different designed DDS as shown in Table S1. Active targeting to ovarian cancer cells using
antibodies and receptor ligands such as HER-2 (Cirstoiu-Hapca et al., 2010), OV-TL3
(Storm et al., 1994; Vingerhoeds et al., 1996), folate (Chaudhury et al., 2012; Tong et al., 2014;
Werner et al., 2011; Zeng et al., 2013) or luteinizing hormone-releasing hormone analogs
(Pu et al., 2014) conjugated to the DDS were used in 30% of the included studies.
Several studies applied specific modifications to create a triggered drug-release. Gilmore
et al. prepared nanoparticles from an acrylate monomer to create particles that are stable
at neutral pH and expand after endocytosis at low pH to release their payload (Gilmore
et al., 2013; Griset et al., 2009). Xu et al. (2006) prepared cisplatin nanoparticles from
poly[2-(N,N-diethylamino)ethyl methacrylate]-block-poly(ethylene glycol) that also
released its payload at low pH. Moreover, using a poly-isobutylene-maleic-glucosamine
cisplatin combination, an acid-triggered drug delivery system was developed and probed to
treat ovarian cancer by Paraskar et al. (2010) and Sengupta et al. (2012).
Other modifications were applied to ensure specific delivery and release of anti-tumor
drug to ovarian cancer cells and thus to increase the efficiency of the DDS in vivo. Lu et
al. (2008) designed two types of tumor penetrating microparticles from poly(DL-lactide-
coglycolide) that could either prime tumors with a rapid release, or sustain a specific
drug level using a slow release microparticle. Others applied a post-ultrasound strategy
to release the chemotherapeutic drug from micelles or to facilitate intracellular drug
uptake from microbubbles upon injection (Gao, Fain & Rapoport, 2005; Pu et al., 2014;
Rapoport et al., 2004).
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 7/24
Figure 2 Risk of bias analysis. The risk of bias for all included studies was analyzed using several signaling questions. Depicted results are theanswers for all studies per question.
with free chemotherapeutics. For four studies (due to small group numbers) no models
could be fitted, which resulted in a hazard ratio of 0 with a very wide confidence interval.
Type of DDS. As shown in Fig. 3B subgroup analysis was performed to evaluate the overall
effect of experiments that used liposomes (12 experiments) or micro/nanocapsules (15
experiments). No difference in effect on hazard ratio was found between experiments
that used liposomes or micro/nanocapsules; all resulted in a significant decrease of the
hazard ratio.
Type of chemotherapeutic. To investigate whether different tumor drugs encapsulated in
DDS affect the hazard ratio, subgroup analysis by chemotherapeutic cisplatin (7 exper-
iments), doxorubicin (4 experiments) and paclitaxel (16 experiments) was performed
(Fig. 3B). Cisplatin, doxorubicin and paclitaxel all resulted in a significant decrease in
hazard ratio. No significant differences were observed among the three drug subgroups.
Targeting vs. non-targeting. Drug delivery systems targeted specifically (12 experiments)
to ovarian cancer cells did not result in a lower hazard ratio compared to non-targeted
DDS (18 experiments). Both treatment strategies resulted in a lower subtotal hazard ratio,
suggesting that both targeted and non-targeted DDS treatment result in improved survival
rates (Fig. 3B).
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 9/24
Figure 3 Effects of survival outcome measure of chemotherapeutics in a DDS compared to freechemotherapeutics (not in a DDS). (A) The forest plot depicts hazard ratios with 95% confidenceinterval (CI) and the weight of the study. A hazard ratio below 1 indicates a smaller chance for the animalsto die over the course of the experiment due to treatment with (continued on next page...)
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 10/24
chemotherapeutics in a DDS. A hazard ratio higher than 1 suggests that animals have a smaller chance ofdying when treated with the free chemotherapeutic control condition. Statistical significance was reachedwhen hazard ratios with their 95% confidence interval did not include the value of 1. Numbers in bracketsbehind study names refer to details of the specific experiments; see Supplementary Information 1 fordetails. (B) Subgroup analysis for type of DDS, type of chemotherapeutic, targeted vs. non-targeted, IPvs. IV route of administration and inoculated cell type were performed. n is the number of experimentsin the subgroups. I2 was used as a measure of heterogeneity.
Route of administration. A subgroup analysis of the different routes of administration
was performed to explore whether this would affect the treatment outcome. Both IP (17
experiments) and IV (7 experiments) administration significantly lowered the risk of dying
over time (Fig. 3B). Moreover, experiments that used a combination strategy of IP and IV
treatment (6 experiments) also resulted in a lower hazard ratio. No statistical differences
between IV, IP or a combination of IV and IP administration were observed.
Figure 4 Effects on tumor growth inhibition outcome measure of chemotherapeutics in a DDS com-pared to free chemotherapeutics (not in a DDS). (A) The forest plot depicts SMDs with 95% confidenceinterval (CI) and the weight of the study. A statistically significant difference between interventionalconditions (chemotherapeutic in DDS) and control conditions (chemotherapeutics not in a DDS) wasreached when the SMD with its 95% confidence interval was greater or smaller than zero. If below zero,the interventional condition is more efficient in reducing the tumor size, while if greater than zero, thecontrol condition is more efficient in reducing the tumor size. Numbers in brackets behind study namesrefer to details of the specific experiments; see Supplementary Information 1 for details. (B) Subgroupanalysis for type of DDS, type of chemotherapeutic, targeted vs. non-targeted and IP vs. IV route ofadministration were performed. n is the number of experiments in the subgroups. I2 was used as ameasure of heterogeneity.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 12/24
Figure 5 Funnel scatter plot of time-to-event studies. Hazard ratios with a 95% confidence interval wereextracted and used to create a funnel scatter plot using Review Manager. Bullets represent individualexperiments from included studies. The x-axis shows the hazard ratio and the y-axis represents thestandard error of the log(hazard ratio). The funnel plot is missing studies in the bottom right area inwhich studies with a negative outcome are expected. Since there are no studies in this area, publicationbias is suggested.
be taken into account that these clinical studies were not performed with DDS and always
included an additional systemic chemotherapy over the IP therapy. This may explain the
lack of improved efficacy by IP treatment over IV treatment in our meta-analysis.
An interesting observation is that our results suggest that cisplatin, a first choice
chemotherapeutic for ovarian cancer treatment, may not be a suitable candidate for
treatment of ovarian cancer using DDS, since cisplatin in DDS did not lead to more
tumor growth inhibition than free cisplatin. However, this was not the case for survival, a
clinically more important outcome measure, where all chemotherapeutics in DDS resulted
in a significant improvement of survival compared to free chemotherapeutics. It should
be noted that results from tumor growth inhibition and survival outcome measures were
mostly not based on data from the same studies. Interestingly, in a phase II clinical study
evaluating liposomal cisplatin a lack of clinical response was observed (Seetharamu et
al., 2010). Moreover, in 1998, Sugiyama et al. (1998) evaluated microspheres containing
cisplatin compared to an aqueous solution of cisplatin and found in a small ovarian cancer
patient group similar toxicity profiles, but no data on efficacy was shown. No subsequent
phase I/II clinical trials of this DDS regarding ovarian cancer treatment could be identified
in current literature, which may suggest a possible lack of clinical outcome. These two
cisplatin DDS examples may confirm our results that cisplatin may not be the most suitable
drug to be used in a DDS for ovarian cancer treatment.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 15/24
Burger RA, Gynecologic Oncology G. 2006. Intraperitoneal cisplatin and paclitaxel in ovariancancer. New England Journal of Medicine 354:34–43 DOI 10.1056/NEJMoa052985.
Bae YH, Park K. 2011. Targeted drug delivery to tumors: myths, reality and possibility. Journal ofControlled Release 153:198–205 DOI 10.1016/j.jconrel.2011.06.001.
Barlin JN, Dao F, Bou Zgheib N, Ferguson SE, Sabbatini PJ, Hensley ML, Bell-McGuinn KM,Konner J, Tew WP, Aghajanian C, Chi DS. 2012. Progression-free and overall survival
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 19/24
of a modified outpatient regimen of primary intravenous/intraperitoneal paclitaxel andintraperitoneal cisplatin in ovarian, fallopian tube, and primary peritoneal cancer. GynecologicOncology 125:621–624 DOI 10.1016/j.ygyno.2012.03.027.
Bebarta V, Luyten D, Heard K. 2003. Emergency medicine animal research: does use ofrandomization and blinding affect the results?. Academic Emergency Medicine 10:684–687DOI 10.1111/j.1553-2712.2003.tb00056.x.
Bello S, Krogsboll LT, Gruber J, Zhao ZJ, Fischer D, Hrobjartsson A. 2014. Lack of blinding ofoutcome assessors in animal model experiments implies risk of observer bias. Journal of ClinicalEpidemiology 67:973–983 DOI 10.1016/j.jclinepi.2014.04.008.
Bergkvist K, Wengstrom Y. 2006. Symptom experiences during chemotherapy treatment–withfocus on nausea and vomiting. European Journal of Oncology Nursing 10:21–29DOI 10.1016/j.ejon.2005.03.007.
Chaudhury A, Das S, Bunte RM, Chiu GN. 2012. Potent therapeutic activity of folatereceptor-targeted liposomal carboplatin in the localized treatment of intraperitoneallygrown human ovarian tumor xenograft. International Journal of Nanomedicine 7:739–751DOI 10.2147/IJN.S26172.
Chen J, Shao R, Zhang XD, Chen C. 2013. Applications of nanotechnology for melanomatreatment, diagnosis, and theranostics. International Journal of Nanomedicine 8:2677–2688DOI 10.2147/IJN.S45429.
Cheng Y, Morshed RA, Auffinger B, Tobias AL, Lesniak MS. 2014. Multifunctional nanoparticlesfor brain tumor imaging and therapy. Advanced Drug Delivery Reviews 66:42–57DOI 10.1016/j.addr.2013.09.006.
Chon SY, Champion RW, Geddes ER, Rashid RM. 2012. Chemotherapy-induced alopecia.Journal of the American Academy of Dermatology 67:e37–e47 DOI 10.1016/j.jaad.2011.02.026.
Cirstoiu-Hapca A, Buchegger F, Lange N, Bossy L, Gurny R, Delie F. 2010. Benefit ofanti-HER2-coated paclitaxel-loaded immuno-nanoparticles in the treatment of disseminatedovarian cancer: therapeutic efficacy and biodistribution in mice. Journal of Controlled Release144:324–331 DOI 10.1016/j.jconrel.2010.02.026.
Danhier F, Feron O, Preat V. 2010. To exploit the tumor microenvironment: passive and activetumor targeting of nanocarriers for anti-cancer drug delivery. Journal of Controlled Release148:135–146 DOI 10.1016/j.jconrel.2010.08.027.
De Smet L, Ceelen W, Remon JP, Vervaet C. 2013. Optimization of drug delivery systems forintraperitoneal therapy to extend the residence time of the chemotherapeutic agent. ScientificWorld Journal 2013:720858 DOI 10.1155/2013/720858.
De Vries RB, Hooijmans CR, Tillema A, Leenaars M, Ritskes-Hoitinga M. 2014.Updated version of the Embase search filter for animal studies. Laboratory Animals48:88 DOI 10.1177/0023677213494374.
Domcke S, Sinha R, Levine DA, Sander C, Schultz N. 2013. Evaluating cell lines as tumourmodels by comparison of genomic profiles. Nature Communications 4:Article 2126DOI 10.1038/ncomms3126.
Ernsting MJ, Murakami M, Roy A, Li SD. 2013. Factors controlling the pharmacokinetics,biodistribution and intratumoral penetration of nanoparticles. Journal of Controlled Release172:782–794 DOI 10.1016/j.jconrel.2013.09.013.
Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H, Forman D,Bray F. 2013. Cancer incidence and mortality patterns in Europe: estimates for 40 countries in2012. European Journal of Cancer 49:1374–1403 DOI 10.1016/j.ejca.2012.12.027.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 20/24
Gao ZG, Fain HD, Rapoport N. 2005. Controlled and targeted tumor chemotherapy bymicellar-encapsulated drug and ultrasound. Journal of Controlled Release 102:203–222DOI 10.1016/j.jconrel.2004.09.021.
Gilmore D, Schulz M, Liu R, Zubris KA, Padera RF, Catalano PJ, Grinstaff MW, Colson YL.2013. Cytoreductive surgery and intraoperative administration of paclitaxel-loaded expansilenanoparticles delay tumor recurrence in ovarian carcinoma. Annals of Surgical Oncology20:1684–1693 DOI 10.1245/s10434-012-2696-5.
Gordon AN, Granai CO, Rose PG, Hainsworth J, Lopez A, Weissman C, Rosales R,Sharpington T. 2000. Phase II study of liposomal doxorubicin in platinum- andpaclitaxel-refractory epithelial ovarian cancer. Journal of Clinical Oncology 18:3093–3100.
Griset AP, Walpole J, Liu R, Gaffey A, Colson YL, Grinstaff MW. 2009. Expansile nanoparticles:synthesis, characterization, and in vivo efficacy of an acid-responsive polymeric drug deliverysystem. Journal of the American Chemical Society 131:2469–2471 DOI 10.1021/ja807416t.
Gunji S, Obama K, Matsui M, Tabata Y, Sakai Y. 2013. A novel drug delivery system ofintraperitoneal chemotherapy for peritoneal carcinomatosis using gelatin microspheresincorporating cisplatin. Surgery 154:991–999 DOI 10.1016/j.surg.2013.04.054.
Hirst JA, Howick J, Aronson JK, Roberts N, Perera R, Koshiaris C, Heneghan C. 2014. The needfor randomization in animal trials: an overview of systematic reviews. PLoS ONE 9:e98856DOI 10.1371/journal.pone.0098856.
Hooijmans CR, Leenaars M, Ritskens-Hoitinga M. 2010. A gold standard publication checklist toimprove the quality of animal studies, to fully integrate the Three Rs, and to make systematicreviews more feasible. Alternatives to Laboratory Animals 38:167–182.
Hooijmans CR, De Vries RB, Rovers MM, Gooszen HG, Ritskes-Hoitinga M. 2012. The effectsof probiotic supplementation on experimental acute pancreatitis: a systematic review andmeta-analysis. PLoS ONE 7:e48811 DOI 10.1371/journal.pone.0048811.
Hooijmans CR, IntHout J, Ritskes-Hoitinga M, Rovers MM. 2014a. Meta-analyses of animalstudies: an introduction of a valuable instrument to further improve healthcare. Institute forLaboratory Animal Research Journal 55:418–426 DOI 10.1093/ilar/ilu042.
Hooijmans CR, Rovers MM, De Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW.2014b. SYRCLE’s risk of bias tool for animal studies. BMC Medical Research Methodology14:43 DOI 10.1186/1471-2288-14-43.
Hooijmans CR, Tillema A, Leenaars M, Ritskes-Hoitinga M. 2010. Enhancing search efficiency bymeans of a search filter for finding all studies on animal experimentation in PubMed. LaboratoryAnimals 44:170–175 DOI 10.1258/la.2010.009117.
Iyer AK, Khaled G, Fang J, Maeda H. 2006. Exploiting the enhanced permeability and retentioneffect for tumor targeting. Drug Discovery Today 11:812–818 DOI 10.1016/j.drudis.2006.07.005.
Jaaback K, Johnson N, Lawrie TA. 2011. Intraperitoneal chemotherapy for the initial managementof primary epithelial ovarian cancer. Cochrane Database of Systematic Reviews 11:ArticleCD005340 DOI 10.1002/14651858.CD005340.pub.
Javid A, Ahmadian S, Saboury AA, Kalantar SM, Rezaei-Zarchi S, Shahzad S. 2014.Biocompatible APTES-PEG modified magnetite nanoparticles: effective carriers ofantineoplastic agents to ovarian cancer. Applied Biochemistry and Biotechnology 173:36–54DOI 10.1007/s12010-014-0740-6.
Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. 2010. Improving bioscienceresearch reporting: the ARRIVE guidelines for reporting animal research. PLoS Biology8:e1000412 DOI 10.1371/journal.pbio.1000412.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 21/24
Lammers T, Kiessling F, Hennink WE, Storm G. 2012. Drug targeting to tumors: principles,pitfalls and (pre-) clinical progress. Journal of Controlled Release 161:175–187DOI 10.1016/j.jconrel.2011.09.063.
Li SD, Howell SB. 2010. CD44-targeted microparticles for delivery of cisplatin to peritonealmetastases. Molecular Pharmaceutics 7:280–290 DOI 10.1021/mp900242f.
Loira-Pastoriza C, Todoroff J, Vanbever R. 2014. Delivery strategies for sustained drug release inthe lungs. Advanced Drug Delivery Reviews 75:81–91 DOI 10.1016/j.addr.2014.05.017.
Love RR, Leventhal H, Easterling DV, Nerenz DR. 1989. Side effects and emotional distressduring cancer chemotherapy. Cancer 63:604–612DOI 10.1002/1097-0142(19890201)63:3<604::AID-CNCR2820630334>3.0.CO;2-2.
Lu H, Li B, Kang Y, Jiang W, Huang Q, Chen Q, Li L, Xu C. 2007. Paclitaxel nanoparticle inhibitsgrowth of ovarian cancer xenografts and enhances lymphatic targeting. Cancer Chemotherapyand Pharmacology 59:175–181 DOI 10.1007/s00280-006-0256-z.
Lu Z, Tsai M, Lu D, Wang J, Wientjes MG, Au JL. 2008. Tumor-penetrating microparticlesfor intraperitoneal therapy of ovarian cancer. Journal of Pharmacology and ExperimentalTherapeutics 327:673–682 DOI 10.1124/jpet.108.140095.
Massey RL, Kim HK, Abdi S. 2014. Brief review: chemotherapy-induced painful peripheralneuropathy (CIPPN): current status and future directions. Canadian Journal of Anaesthesia61:754–762 DOI 10.1007/s12630-014-0171-4.
Monsuez JJ, Charniot JC, Vignat N, Artigou JY. 2010. Cardiac side-effects of cancerchemotherapy. International Journal of Cardiology 144:3–15 DOI 10.1016/j.ijcard.2010.03.003.
Muggia FM, Hainsworth JD, Jeffers S, Miller P, Groshen S, Tan M, Roman L, Uziely B,Muderspach L, Garcia A, Burnett A, Greco FA, Morrow CP, Paradiso LJ, Liang LJ. 1997.Phase II study of liposomal doxorubicin in refractory ovarian cancer: antitumor activity andtoxicity modification by liposomal encapsulation. Journal of Clinical Oncology 15:987–993.
O’Brien ME, Wigler N, Inbar M, Rosso R, Grischke E, Santoro A, Catane R, Kieback DG,Tomczak P, Ackland SP, Orlandi F, Mellars L, Alland L, Tendler C, Group CBCS. 2004.Reduced cardiotoxicity and comparable efficacy in a phase III trial of pegylated liposomaldoxorubicin HCl (CAELYX/Doxil) versus conventional doxorubicin for first-line treatment ofmetastatic breast cancer. Annals of Oncology 15:440–449 DOI 10.1093/annonc/mdh097.
Paraskar AS, Soni S, Chin KT, Chaudhuri P, Muto KW, Berkowitz J, Handlogten MW, Alves NJ,Bilgicer B, Dinulescu DM, Mashelkar RA, Sengupta S. 2010. Harnessing structure–activityrelationship to engineer a cisplatin nanoparticle for enhanced antitumor efficacy.Proceedings of the National Academy of Sciences of the United States of America 107:12435–12440DOI 10.1073/pnas.1007026107.
Patankar NA, Pritchard J, Van Grinsven M, Osooly M, Bally MB. 2013. Topotecan anddoxorubicin combination to treat recurrent ovarian cancer: the influence of drug exposuretime and delivery systems to achieve optimum therapeutic activity. Clinical Cancer Research19:865–877 DOI 10.1158/1078-0432.CCR-12-2459.
Perrault SD, Walkey C, Jennings T, Fischer HC, Chan WC. 2009. Mediating tumor targetingefficiency of nanoparticles through design. Nano Letters 9:1909–1915 DOI 10.1021/nl900031y.
Pu C, Chang S, Sun J, Zhu S, Liu H, Zhu Y, Wang Z, Xu RX. 2014. Ultrasound-mediateddestruction of LHRHa-targeted and paclitaxel-loaded lipid microbubbles for thetreatment of intraperitoneal ovarian cancer xenografts. Molecular Pharmaceutics 11:49–58DOI 10.1021/mp400523h.
Rapoport NY, Christensen DA, Fain HD, Barrows L, Gao Z. 2004. Ultrasound-triggered drug tar-geting of tumors in vitro and in vivo. Ultrasonics 42:943–950 DOI 10.1016/j.ultras.2004.01.087.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 22/24
Safra T, Groshen S, Jeffers S, Tsao-Wei DD, Zhou L, Muderspach L, Roman L, Morrow CP,Burnett A, Muggia FM. 2001. Treatment of patients with ovarian carcinoma with pegylatedliposomal doxorubicin: analysis of toxicities and predictors of outcome. Cancer 91:90–100DOI 10.1002/1097-0142(20010101)91:1<90::AID-CNCR12>3.0.CO;2-A.
Seetharamu N, Kim E, Hochster H, Martin F, Muggia F. 2010. Phase II study of liposomalcisplatin (SPI-77) in platinum-sensitive recurrences of ovarian cancer. Anticancer Research30:541–545.
Sengupta P, Basu S, Soni S, Pandey A, Roy B, Oh MS, Chin KT, Paraskar AS, Sarangi S,Connor Y, Sabbisetti VS, Kopparam J, Kulkarni A, Muto K, Amarasiriwardena C,Jayawardene I, Lupoli N, Dinulescu DM, Bonventre JV, Mashelkar RA, Sengupta S. 2012.Cholesterol-tethered platinum II-based supramolecular nanoparticle increases antitumorefficacy and reduces nephrotoxicity. Proceedings of the National Academy of Sciences of theUnited States of America 109:11294–11299 DOI 10.1073/pnas.1203129109.
Storm G, Nassander UK, Vingerhoeds MH, Steerenberg PA, Crommelin DJA. 1994.Antibody-targeted liposomes to deliver doxorubicin to ovarian cancer cells. Journal of LiposomeResearch 4:641–666 DOI 10.3109/08982109409037064.
Sugiyama T, Kumagai S, Nishida T, Ushijima K, Matsuo T, Yakushiji M, Hyon SH, Ikada Y.1998. Experimental and clinical evaluation of cisplatin-containing microspheres asintraperitoneal chemotherapy for ovarian cancer. Anticancer Research 18:2837–2842.
Tomasina J, Lheureux S, Gauduchon P, Rault S, Malzert-Freon A. 2013. Nanocarriers for thetargeted treatment of ovarian cancers. Biomaterials 34:1073–1101DOI 10.1016/j.biomaterials.2012.10.055.
Tong L, Chen W, Wu J, Li H. 2014. Folic acid-coupled nano-paclitaxel liposome reverses drugresistance in SKOV3/TAX ovarian cancer cells. Anti-Cancer Drugs 25:244–254DOI 10.1097/CAD.0000000000000047.
Truong J, Yan AT, Cramarossa G, Chan KK. 2014. Chemotherapy-induced cardiotoxicity:detection, prevention, and management. Canadian Journal of Cardiology 30:869–878DOI 10.1016/j.cjca.2014.04.029.
Ueno N. 1988. Experimental studies on the chemotherapy of gynecological neoplasm by meansof adriamycin entrapped in liposomes. Journal of the Aichi Medical University Association16:63–82.
Uziely B, Jeffers S, Isacson R, Kutsch K, Wei-Tsao D, Yehoshua Z, Libson E, Muggia FM,Gabizon A. 1995. Liposomal doxorubicin: antitumor activity and unique toxicities duringtwo complementary phase I studies. Journal of Clinical Oncology 13:1777–1785.
Vanderhyden BC, Shaw TJ, Ethier JF. 2003. Animal models of ovarian cancer. Reproductive Biologyand Endocrinology 1:Article 67 DOI 10.1186/1477-7827-1-67.
Vergote I, Amant F, Kristensen G, Ehlen T, Reed NS, Casado A. 2011. Primary surgery orneoadjuvant chemotherapy followed by interval debulking surgery in advanced ovarian cancer.European Journal of Cancer 47(Suppl 3):S88–S92 DOI 10.1016/S0959-8049(11)70152-6.
Vergote I, Trope CG, Amant F, Kristensen GB, Ehlen T, Johnson N, Verheijen RH, Vander Burg ME, Lacave AJ, Panici PB, Kenter GG, Casado A, Mendiola C, Coens C,Verleye L, Stuart GC, Pecorelli S, Reed NS, European Organization for R, Treatment ofCancer-Gynaecological Cancer G, Group NCT. 2010. Neoadjuvant chemotherapy or primarysurgery in stage IIIC or IV ovarian cancer. New England Journal of Medicine 363:943–953DOI 10.1056/NEJMoa0908806.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 23/24
Vingerhoeds MH, Steerenberg PA, Hendriks JJ, Dekker LC, Van Hoesel QG, Crommelin DJ,Storm G. 1996. Immunoliposome-mediated targeting of doxorubicin to human ovariancarcinoma in vitro and in vivo. British Journal of Cancer 74:1023–1029DOI 10.1038/bjc.1996.484.
Werner ME, Karve S, Sukumar R, Cummings ND, Copp JA, Chen RC, Zhang T, Wang AZ. 2011.Folate-targeted nanoparticle delivery of chemo- and radiotherapeutics for the treatment ofovarian cancer peritoneal metastasis. Biomaterials 32:8548–8554DOI 10.1016/j.biomaterials.2011.07.067.
Xu P, Van Kirk EA, Murdoch WJ, Zhan Y, Isaak DD, Radosz M, Shen Y. 2006. Anticancerefficacies of cisplatin-releasing pH-responsive nanoparticles. Biomacromolecules 7:829–835DOI 10.1021/bm050902y.
Yang M, Yu T, Wood J, Wang YY, Tang BC, Zeng Q, Simons BW, Fu J, Chuang CM, Lai SK,Wu TC, Hung CF, Hanes J. 2014. Intraperitoneal delivery of paclitaxel by poly(ether-anhydride)microspheres effectively suppresses tumor growth in a murine metastatic ovarian cancer model.Drug Delivery and Translational Research 4:203–209 DOI 10.1007/s13346-013-0190-7.
Ye L, He J, Hu Z, Dong Q, Wang H, Fu F, Tian J. 2013. Antitumor effect and toxicity of Lipusu inrat ovarian cancer xenografts. Food and Chemical Toxicology 52:200–206DOI 10.1016/j.fct.2012.11.004.
Yezhelyev MV, Gao X, Xing Y, Al-Hajj A, Nie S, O’Regan RM. 2006. Emerging use ofnanoparticles in diagnosis and treatment of breast cancer. The Lancet Oncology 7:657–667DOI 10.1016/S1470-2045(06)70793-8.
Zeng Q, Wen H, Wen Q, Chen X, Wang Y, Xuan W, Liang J, Wan S. 2013. Cucumber mosaic virusas drug delivery vehicle for doxorubicin. Biomaterials 34:4632–4642DOI 10.1016/j.biomaterials.2013.03.017.
Zhang Y, Kenny HA, Swindell EP, Mitra AK, Hankins PL, Ahn RW, Gwin K, Mazar AP,O’Halloran TV, Lengyel E. 2013. Urokinase plasminogen activator system-targeted deliveryof nanobins as a novel ovarian cancer therapy. Molecular Cancer Therapeutics 12:2628–2639DOI 10.1158/1535-7163.MCT-13-0204.
Raave et al. (2015), PeerJ, DOI 10.7717/peerj.1489 24/24