Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5346_Библиотеки_им_академика_М_И_Перельмана
.pdf
metabolic remodeling during tumor treatment, as a result of environmental stressors,
which may co nf ound interpretation of the image signal output [ 204].
6.6 Adoptively transferred T-cell imaging
Extensive clinical interest in CAR T-cell therapy, especially in hematological cancers, has
been noted in recent years [205]. Tumor-specific T lymphocytes, usually from the
patient, are collected and expanded in vitro, subsequently transduced to express a
CAR targeting the tumor antigen of interest for the patient’s malignancy, before being
reintroduced back into the patient. An important component contributing to the success
of CAR T-cell therapy is the localization of the T-cells to the tumor target. Furthermore,
identifying their functional status in real-time is also likely useful. Longitudinal noninvasive imaging is therefore crucial for monitoring the dynamics of these processes [206].
Multiple T-cell labeling strategies have been developed for this purpose. Passive
uptake of labeled lipophilic complexes has been explored for T-cell labeling. Initial studies utilized ex vivo labeling with 111In-oxine of CD4 + T-cells to monitor infiltrating
lymphocytes in Hodgkin’s lymphoma [207] and melanoma patients [208, 209] using
SPECT/CT. Pittet et al. confirmed the requirement of antigen-specific binding for infiltration of adoptively transferred T-cells using SPECT/CT imaging of 111In-oxine
labeled T-cells combined with intravital microscopy [210]. Currently, a clinical trial is
underway to monitor the dynamics of ex vivo 111In-oxine-labeled autologous CD8 +
T-cell tumor infiltration in nonsmall cell lung cancer patients receiving neo-adjuvant
PD-L1 (NCT03853187). T-cell populations can be radiation-sensitive, although recent
studies suggest that certain T-cell subsets (e.g., CD4, Treg) are more radioresistant than
others [178]. Stanton et al. found that 111In-oxine labeled adoptively labeled T-cells
did not significantly impact their viability or function [211]. Further studies should continue to monitor the effect of radioisotopes upon T-cell function.
PET agents have also been explored to directly label T-cells [32], including using
64Cu conjugated to lipophilic complexes such as tropolonate, polyethylenimine, and
pyruvaldehyde-bis(N
of these agents within cells, and subsequent accumulation of the effluxed agents in the
liver, limit their use for clinical purposes. 89Zr-oxine labeling has been alternatively pursued, with better labeling yield compared with 111In-oxine, and 89Zr-oxine labeled γδ
T-cells were able to be followed for over a week in mouse models of breast cancer [212].
Given concern for the sequestration of free 89Zr to the bone marrow, Bansal et al.
explored the use of 89Zr-desferrioxamine-NCS (89Zr-DBN) for cell labeling, showing
stable labeling to the cell surface of human mesenchymal stem cells for up to seven days.
Other direct T-cell labeling approaches include labeling with iron oxide nanoparticles
[213], gold nanoparticles complexed to 64Cu, and PFC nanoparticles for 19F-MRI
[214, 215], although none have been translated for human use to date. T-cell labeling
4
-methylthiosemicarbazone). However, the short residence time
451Image-guided cancer immunotherapy
452 Thomas S.C. Ng and Miles A. Miller
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
with an optimized highly derivatized cross-linked iron oxide nanoparticle was efficient,
nontoxic, and allowed high-resolution visualization of heterogeneous tumor accumulation of T-cells. PFC labeling of T-cells offers high sensitivity given low background signal in tissue and quantification capabilities using 19F-MRI but may suffer from dilution
of signal upon cell division and PFC persistence in dead cells.
With the need for ex vivo transduction before reintroduction to patients, CAR T-cells
may be well-suited for reporter gene labeling. Gene reporters for several imaging modalities have been developed. Moroz et al. performed a comparative analysis of multiple
report gene systems for nuclear imaging of T-cells [216], including a human
deoxycytidine kinase double mutant (hdCKDM), the human sodium-iodide symporter
(hNIS), human norepinephrine transporter (hNET), and herpes simplex virus type 1 thymidine kinase (hsvTK) reporter gene systems. They found the hNET/meta-18Ffluorobenzylguanidine (18F-MFBG) reporter system to be the most sensitive, detecting
35-40 10
3
Tcells without significant toxicity. Krebs et al. transduced DOTA antibody
reporter 1 (DAbr1) with GFP in CD3/CD28 activated human T-cells and 1928z CAR
T cells. This moiety is expressed on the cell surface and binds irreversibly to lanthanoid
(S)-2-(4-acrylamidobenzyl)-DOTA (AABD) [217]. They showed the feasibility of this
system for PET and SPECT imaging using 86Y and 177Lu AABD and demonstrated the
highest T-cell to background contrast in animal models within 16 h postinjection.
Somatostatin receptor 2 (SSTR2) is the target for the FDA-approved agents 68GaDOTATATE and DOTATOC. While used clinically to image neurorendocrine
tumors, among other malignancies, it is not significantly expressed in normal tissues.
Vedvyas et al. thus expressed SSTR2 in CAR T-cells for monitoring by 68GaDOTATOC [218]. In this system, peak T-cell tumor accumulation lagged tumor cell
burden by several days in CAR-T cell therapy responders, using a mouse model of metastatic anaplastic thyroid cancer. Results suggested enduring cognate antigen-mediated
signals, causing continued CAR T cell expansion before eventual exhaustion and contraction of the T-cell population. This pattern was not observed in nonresponders. In a
similar vein, Minn et al. transduced anti-CD19 CAR T-cells with the prostate-specific
membrane antigen (PSMA). In a mouse model of acute lymphoblastic leukemia, PET/CT
imaging of CD19 dynamics showed a discrepancy between CAR T-cells levels in peripheral blood compared to uptake levels within the tumor, highlighting the need for T-cell
infiltration monitoring by imaging [219]. A reporter gene system that has no background
expression and minimal immunogenicity are ideal. Sellmyer et al. adapted the expression
of the Escherichia coli dihydrofolate reductase enzyme (eDHFR) together with fluorine-18
labeled small-molecule antibiotic trimethoprim (18F-TMP) as a novel CAR T-cell
reporter system [220]. GD2+ CAR T-cells engineered with eDHFR, yellow fluorescent
protein (YFP), and Renilla luciferase (rLuc) showed preferential targeting for GD2+
tumors in mice and showed gradual migration from the spleen to the tumor over 2 weeks.
Given its small size, eDHFR (18kDa, compared to 46 kDa for HSV-tk) is potentially less
immunogenic than the other tested systems while maintaining high specificity in
targeting.
To date, only one T-cell reporter gene system has been tested in patients. Keu et al.
expressed the HSV1-tk reporter gene in IL13Ra2-CAR T-cells. Using 9-[4-[18F]
fluoro-3-(hydroxymethyl)butyl]guanine (18F-FHBG), cell trafficking was monitored
by PET/CT in patients with recurrent glioma [221, 222] (Fig. 9). Significantly increased
imaging signal was noted in tumors injected with T-cells, suggestive of their localization.
453Image-guided cancer immunotherapy
Fig. 9 CAR T-cell imaging in clinical trials. 18F-FHBG PET imaging was performed in a 60-year-old male
with multifocal left-hemispheric glioma. T-cells were injected into the medial left frontal lobe tumor
(yellow arrows). (A) Tumor size was delineated with T
panels). PET images were fused with MRI images (bottom left panels), and 3D volumes of interest were
outlined in red. (B) MRI and MR-PET images 1 week after T-cell infusions. 18F-FHBG activity was additionally assessed in a noninjected tumor focus (red arrows) before (C) and after (D) T-cell infusions.
These findings show both local and region trafficking of injected labeled CAR T-cells. Further, images
show nonspecific uptake pre-T-cell injection which needs to be accounted for during analysis.
(Adapted from Keu KV, Witney TH, Yaghoubi S, Rosenberg J, Kurien A, Magnusson R, et al. Reporter gene
imaging of targeted T cell immunotherapy in recurrent glioma. Sci Transl Med. 2017;9(373):eaag2196.)
-weighted (T1W) contrast-enhanced MRI (top left
1
454 Thomas S.C. Ng and Miles A. Miller
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
However, the slightly increased signal was also found in untreated tumors, underscoring
the need to account for nonspecific uptake.
Understanding the functional status of CAR T-cells localized at the tumor site may
offer insights into mechanisms affecting their efficacy and resistance. To this end,
reporter gene technology may be tailored to be expressed under T-cell activation promoters. In a proof of concept study, P onomarev et al. monitored T-cell receptor
(TCR) dependent, nuclear factor of activated T cells (NFAT) mediated activation
of T cells by optical fluorescence imaging (OFI) and positron emission tomography
(PET), enabling moni toring of T-cell activation in vivo [223].Toimprovethespecificity of the T-cell activation signal, Uchibori et al. transduced CD-19 targeting CAR
T-cells with an inducible reporter (CAR-T/iReporter) that is strongly induced only in
the presence of CD19 positive cells. Imaging applicability of this system was demonstrated in vivo with a coexpressed lucifer ase reporter, showing targeted induction only
at CD19 + tumor sites [224].
7. Imaging to guide bispecific T-cell engager therapy (BiTE)
Bispecific T-cell engager (BiTE) therapy is another promising immunotherapy
modality explored for clinical use [225]. BiTe is a recombinant bispecific proteincontaining single-chain variable fragments (scFv) targeting a tumor-associated antigen
and a T-cell activating molecule, thus supporting the coengagement of tumor cells with
activated T-cells. Imaging can play an important role in evaluating BiTE therapy by (1)
identifying patients with appropriate tumor burden expressing the tumor antigen of
interest, and (2) monitoring appropriate T-cell recruitment and response.
In a phase I study, Moek et al. evaluated the use of
directed to carcinoembryonic antigen (CEA) on tumor cells and CD3 on T-cells
89
[226].
Zr- AMG 211 was imaged in patients with gastric adenocarcinoma over 2 days,
showing uptake in lymphoid tissues (spleen and bone marrow) commensurate with its
CD3 targeting capabilities as well as heterogeneous tumor uptake. Imaging of other BiTE
constructs is being actively explored [227]. Successful translation of BiTe therapies to the
clinic may also benefit from patient stratification offered by imaging. For example,
PSMA-targeting PET tracers may identify potentially responsive prostate cancer patients
(NCT04221542, NCT03792841), while immunoPET agents may inform BiTE treatment for hematologic malignancies (NCT00274742, NCT01741792).
89
Zr-labeled BiTE AMG 211
8. Image-guided interventional immunotherapies
Conventional delivery of chemotherapy is via intravenous injection or oral ingestion. However, these modes of delivery have several limitations. Systemic delivery can
result in dose-limiting toxicities precluding adequate dosing and poor tumor drug
penetration. This can hamper efficacy and can potentially result in drug resistance. Localized drug delivery can overcome some of these barriers, and imaging can guide these
modes of tumor drug delivery. Transarterial delivery of chemo- (TACE) and radioembolization (TARE) therapies directed at hepatocellular carcinoma lesions exemplify
the concept [228]. For these therapies, 99mTc-MAA agents are used to identifying
appropriate hepatic arterial selection for subsequent therapy delivery and ensure minimal
off-target delivery to the lungs and adjacent bowel. Interventional devices and imaging
techniques used for these treatments can similarly be applied for the guided delivery of
immunotherapies. For example, preclinical studies have explored both intraarterial and
intravenous delivery of adoptive cell therapy. Using fluorescently labeled OT1 T-cells
and immunofluorescence, Visioni et al. demonstrated improved infiltration of activated
T-cells into tumors via intraarterial infusion as compared with intravenous injection. The
latter resulted in increased lung retention of T-cells [229].
Recent preclinical studies have demonstrated the improved efficacy of concentrated
delivery of immunostimulatory agents into the local tumor site, both for a sustained localized and systemic response. In 2015, the US FDA approved the first oncolytic virus,
talimogene laherparepvec (TVEC), as immunotherapy for the treatment of metastatic
melanoma lesions that cannot be surgically resected. There are many clinical trials ongoing
for intratumoral injections of oncolytic viruses (NCT02977156), immune checkpoint
inhibitors (NCT03707808, NCT02812524, NCT03892525), immunostimulatory compounds such as polymers (NCT03993678), cytokines (NCT04362722), or mRNA
(NCT03788083) and CAR T cells (NCT01837602).
Multimodal interventional imaging techniques can be harnessed for the tumoral
delivery of immunotherapy agents. Noninvasive imaging probes described in earlier sections can be used to identify the target tumors and intratumoral targets for precise delivery
of immunotherapeutic agents. These can be combined with novel deployment devices to
ensure adequate drug injection. Sheth et al. performed a case study review of 85 cases with
patients receiving intratumoral guided delivery of immunotherapies in advanced solid
organ malignancies [230]. No adverse events were noted with the technical component
of the procedures, with major adverse events due to immune-related systemic toxic
effects occurring in 2% of investigational agents and 4% of standard-of-care procedures
(4%). These results suggest that intratumoral delivery of immunotherapeutics is feasible.
Interventional oncology (IO) is a subspecialty within interventional radiology.
Several techniques actively in use in IO can stimulate the immune system (e.g., thermal
ablation, TACE, TARE, high-intensity focused ultrasound) and can be synergistic
with concurrently administered immunotherapy to sustain an immune response
[231]. For example, anti-CTLA-4 can be combined with TACE to unmask tumor-
associated antigen-specific responses [232], which has been associated with improved
patient survival. Efforts are underway to understand t he evolving tumor response of
455Image-guided cancer immunotherapy
456 Thomas S.C. Ng and Miles A. Miller
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
IO therapies. Imaging probes described above are well-poised to monitor these processes in vivo.
9. Summary and future directions
As reviewed in this chapter, many promising clinical imaging approaches are being
explored to monitor cancer immunotherapies. These companion imaging diagnostics
promise to give more precise readouts of immune system activation in vivo and complement the current mainstay of anatomic clinical imaging. These strategies must be robustly
evaluated in concert with the therapies that they seek to monitor. Rigorous clinical trials
providing evidence-based motivation for using the imaging modalities described above
will facilitate their widespread adoption. Concurrently it should be recognized that these
imaging techniques can also improve or fine-tune the indications for immunotherapies
based on precise patient stratification and early treatment response monitoring. Furthermore, imaging data are increasingly being analyzed in the context of the broader clinical
and laboratory information available. Integration of genomic information from tissue
samples [233, 234], biomarkers from liquid biopsies [235, 236], for example, will maximize the utility of the combined data to tailor individual patient care. Identification and
realization of such opportunities will require close collaboration between imaging scientists, physicians, cancer biology researchers, and clinical oncologists.
References
[1] Mellman I, Coukos G, Dranoff G. Cancer immunotherapy comes of age. Nature 2011;480
(7378):480–9.
[2] Farkona S, Diamandis EP, Blasutig IM. Cancer immunotherapy: the beginning of the end of cancer?
BMC Med 2016;14(1):73.
[3] Martin-Liberal J, Ochoa de Olza M, Hierro C, Gros A, Rodon J, Tabernero J. The expanding role of
immunotherapy. Cancer Treat Rev 2017;54:74–86.
[4] Gross S, Moss BL, Piwnica-Worms D. Veni, Vidi, Vici: in vivo molecular imaging of immune
response. Immunity 2007;27(4):533–8.
[5] Weissleder R, Schwaiger MC, Gambhir SS, Hricak H. Imaging approaches to optimize molecular
therapies. Sci Transl Med 2016;8(355). 355ps16.
[6] Najmi Varzaneh F, Baradaran NB. Cancer molecular and functional imaging. In: Rezaei N, editor.
Cancer immunology: a translational medicine context. Cham: Springer International Publishing;
2020. p. 729–38.
[7] Tirkes T, Hollar MA, Tann M, Kohli MD, Akisik F, Sandrasegaran K. Response criteria in oncologic
imaging: review of traditional and new criteria. Radiographics 2013;33(5):1323–41.
[8] Kasten BB, Udayakumar N, Leavenworth JW, Wu AM, Lapi SE, McConathy JE, et al. Current and
future imaging methods for evaluating response to immunotherapy in neuro-oncology. Theranostics
2019;9(17):5085–104.
[9] Yeh BM, FitzGerald PF, Edic PM, Lambert JW, Colborn RE, Marino ME, et al. Opportunities for
new CT contrast agents to maximize the diagnostic potential of emerging spectral CT technologies.
Adv Drug Deliv Rev 2017;113:201–22.
[10] De Cecco CN, Darnell A, Rengo M, Muscogiuri G, Bellini D, Ayuso C, et al. Dual-energy CT:
oncologic applications. Am J Roentgenol 2012;199(5_Suppl):S98–S105.
[11] Harisinghani MG, O’Shea A, Weissleder R. Advances in clinical MRI technology. Sci Transl Med
2019;11(523).
[12] Morone M, Bali MA, Tunariu N, Messiou C, Blackledge M, Grazioli L, et al. Whole-body MRI:
current applications in oncology. Am J Roentgenol 2017;209(6):W336–49.
[13] Ng TS, Wert D, Sohi H, Procissi D, Colcher D, Raubitschek AA, et al. Serial diffusion MRI to mon-
itor and model treatment response of the targeted nanotherapy CRLX101. Clin Cancer Res 2013;19
(9):2518–27.
[14] Shahbazi-Gahrouei D. Novel MR imaging contrast agents for cancer detection. J Res Med Sci
2009;14(3):141–7.
[15] Fujita N, Nishie A, Asayama Y, Ishigami K, Ushijima Y, Kakihara D, et al. Hyperintense liver masses
at hepatobiliary phase gadoxetic acid–enhanced MRI: imaging appearances and clinical importance.
Radiographics 2020;40(1):72–94.
[16] Winkel DJ, Heye TJ, Benz MR, Glessgen CG, Wetterauer C, Bubendorf L, et al. Compressed sensing
radial sampling MRI of prostate perfusion: utility for detection of prostate cancer. Radiology
2019;290(3):702–8.
[17] Gallagher FA, Woitek R, McLean MA, Gill AB, Manzano Garcia R, Provenzano E, et al. Imaging
breast cancer using hyperpolarized carbon-13 MRI. Proc Natl Acad Sci U S A 2020;117(4):2092.
[18] Zhu A, Lee D, Shim H. Metabolic positron emission tomography imaging in cancer detection and
therapy response. Semin Oncol 2011;38(1):55–69.
[19] Ehlerding EB, England CG, McNeel DG, Cai W. Molecular Imaging of immunotherapy targets in
cancer. J Nucl Med 2016;57(10):1487–92.
[20] Bockisch A, Freudenberg LS, Schmidt D, Kuwert T. Hybrid imaging by SPECT/CT and PET/CT:
proven outcomes in cancer imaging. Semin Nucl Med 2009;39(4):276–89.
[21] Rosenkrantz AB, Friedman K, Chandarana H, Melsaether A, Moy L, Ding Y-S, et al. Current status
of hybrid PET/MRI in oncologic imaging. Am J Roentgenol 2015;206(1):162–72.
[22] Vandenberghe S, Moskal P, Karp JS. State of the art in total body PET. EJNMMI Phys 2020;7(1):35.
[23] Saeed M, Xu Z, De Geest BG, Xu H, Yu H. Molecular imaging for cancer immunotherapy: seeing is
believing. Bioconjug Chem 2020;31(2):404–15.
[24] Zhao S, Pan W, Jiang H, Zhang R, Jiang H, Liang Z, et al. Cerenkov luminescence imaging is an
effective preclinical tool for assessing colorectal cancer PD-L1 levels in vivo. EJNMMI Res
2020;10(1):64.
[25] Liu H, Carpenter CM, Jiang H, Pratx G, Sun C, Buchin MP, et al. Intraoperative imaging of tumors
using Cerenkov luminescence endoscopy: a feasibility experimental study. J Nucl Med 2012;53
(10):1579–84.
[26] Darr C, Krafft U, Fendler WP, Costa PF, Barbato F, Praus C, et al. First-in-man intraoperative Cere-
nkov luminescence imaging for oligometastatic prostate cancer using 68Ga-PSMA-11. Eur J Nucl
Med Mol Imaging 2020;47(13):3194–5.
[27] Balkin ER, Kenoyer A, Orozco JJ, Hernandez A, Shadman M, Fisher DR, et al. In Vivo localization
90
of
Y and
177
Lu radioimmunoconjugates using Cerenkov luminescence imaging in a disseminated
murine leukemia model. Cancer Res 2014;74(20):5846–54.
[28] Dey S, Trau M, Koo KM. Surface-enhanced Raman spectroscopy for cancer immunotherapy appli-
cations: opportunities, challenges, and current progress in nanomaterial strategies. Nanomaterials
(Basel, Switzerland) 2020;10(6).
[29] Ng TSC, Garlin MA, Weissleder R, Miller MA. Improving nanotherapy delivery and action through
image-guided systems pharmacology. Theranostics 2020;10(3):968–97.
[30] Aalipour A, Chuang H-Y, Murty S, D’Souza AL, Park S-M, Gulati GS, et al. Engineered immune
cells as highly sensitive cancer diagnostics. Nat Biotechnol 2019;37(5):531–9.
[31] Talebloo N, Gudi M, Robertson N, Wang P. Magnetic particle imaging: current applications in bio-
medical research. J Magn Reson Imaging 2020;51(6):1659–68.
[32] Krekorian M, Fruhwirth GO, Srinivas M, Figdor CG, Heskamp S, Witney TH, et al. Imaging of
T-cells and their responses during anti-cancer immunotherapy. Theranostics 2019;9(25):7924–47.
[33] Kim MH, Lee YJ, Kang JH. Stem cell monitoring with a direct or indirect labeling method. Nucl Med
Mol Imaging 2016;50(4):275–83.
[34] Kircher MF, Gambhir SS, Grimm J. Noninvasive cell-tracking methods. Nat Rev Clin Oncol 2011;8
(11):677–88.
457Image-guided cancer immunotherapy
458 Thomas S.C. Ng and Miles A. Miller
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
[35] Naylor LH. Reporter gene technology: the future looks bright. Biochem Pharmacol 1999;58
(5):749–57.
[36] Li M, Wang Y, Liu M, Lan X. Multimodality reporter gene imaging: construction strategies and appli-
cation. Theranostics 2018;8(11):2954–73.
[37] Pickar-Oliver A, Gersbach CA. The next generation of CRISPR–Cas technologies and applications.
Nat Rev Mol Cell Biol 2019;20(8):490–507.
[38] Mukherjee A, Wu D, Davis HC, Shapiro MG. Non-invasive imaging using reporter genes altering
cellular water permeability. Nat Commun 2016;7(1):13891.
[39] Mestel R. Cancer: imaging with antibodies. Nature 2017;543(7647):743–6.
[40] Ou Y-C, Wen X, Bardhan R. Cancer immunoimaging with smart nanoparticles. Trends Biotechnol
2020;38(4):388–403.
[41] He S, Li J, Lyu Y, Huang J, Pu K. Near-infrared fluorescent macromolecular reporters for real-time
imaging and urinalysis of cancer immunotherapy. J Am Chem Soc 2020;142(15):7075–82.
[42] Arlauckas SP, Garris CS, Kohler RH, Kitaoka M, Cuccarese MF, Yang KS, et al. In vivo imaging
reveals a tumor-associated macrophage-mediated resistance pathway in anti-PD-1 therapy. Sci Transl
Med 2017;9(389).
[43] Pantel AR, Ackerman D, Lee SC, Mankoff DA, Gade TP. Imaging cancer metabolism: underlying
biology and emerging strategies. J Nucl Med 2018;59(9):1340–9.
[44] Sengupta D, Pratx G. Imaging metabolic heterogeneity in cancer. Mol Cancer 2016;15(1):4.
[45] Zaidi N, Jaffee EM. Immunotherapy transforms cancer treatment. J Clin Invest 2019;129(1):46–7.
[46] Weiss SA, Wolchok JD, Sznol M. Immunotherapy of melanoma: facts and hopes. Clin Cancer Res
2019;25(17):5191–201.
[47] Nixon NA, Blais N, Ernst S, Kollmannsberger C, Bebb G, Butler M, et al. Current landscape of
immunotherapy in the treatment of solid tumours, with future opportunities and challenges. Curr
Oncol 2018;25(5):e373–84.
[48] Nelson MH, Paulos CM. Novel immunotherapies for hematologic malignancies. Immunol Rev
2015;263(1):90–105.
[49] Topalian SL, Taube JM, Pardoll DM. Neoadjuvant checkpoint blockade for cancer immunotherapy.
Science 2020;367(6477):eaax0182.
[50] Ott PA, Hodi FS, Kaufman HL, Wigginton JM, Wolchok JD. Combination immunotherapy: a road
map. J Immunother Cancer 2017;5(1):16.
[51] Nishino M, Hatabu H, Hodi FS. Imaging of cancer immunotherapy: current approaches and future
directions. Radiology 2019;290(1):9–22.
[52] Wierstra P, Sandker G, Aarntzen E, Gotthardt M, Adema G, Bussink J, et al. Tracers for non-invasive
radionuclide imaging of immune checkpoint expression in cancer. EJNMMI Radiopharm Chem
2019;4(1):29.
[53] Dromain C, Beigelman C, Pozzessere C, Duran R, Digklia A. Imaging of tumour response to immu-
notherapy. Eur Radiol Exp 2020;4(1):2.
[54] L€utje S, Feldmann G, Essler M, Brossart P, Bundschuh RA. Immune checkpoint imaging in
oncology—a game changer towards personalized immunotherapy? J Nucl Med 2020;61(8):1137–44.
[55] van de Donk PP, Kist de Ruijter L, Lub-de Hooge MN, Brouwers AH, van der Wekken AJ, Oosting
SF, et al. Molecular imaging biomarkers for immune checkpoint inhibitor therapy. Theranostics
2020;10(4):1708–18.
[56] Ehlerding EB, England CG, Majewski RL, Valdovinos HF, Jiang D, Liu G, et al. ImmunoPET imag-
ing of CTLA-4 expression in mouse models of non-small cell lung cancer. Mol Pharm 2017;14
(5):1782–9.
[57] Tavare R, Escuin-Ordinas H, McCracken M, Zettlitz K, Salazar F, Witte O, et al. Detection of anti-
body therapy-induced anti-tumor immune responses using anti-CD8 immuno-pet. J Immunother
Cancer 2015;3(2):P391.
[58] Chanier T, Chames P. Nanobody engineering: toward next generation immunotherapies and
immunoimaging of cancer. Antibodies (Basel, Switzerland) 2019;8(1).
[59] Rashidian M, Keliher EJ, Bilate AM, Duarte JN, Wojtkiewicz GR, Jacobsen JT, et al. Noninvasive
imaging of immune responses. Proc Natl Acad Sci U S A 2015;112(19):6146–51.
[60] Vorobyeva A, Westerlund K, Mitran B, Altai M, Rinne S, S€orensen J, et al. Development of an opti-
mal imaging strategy for selection of patients for affibody-based PNA-mediated radionuclide therapy.
Sci Rep 2018;8(1):9643.
[61] Chatterjee S, Lesniak WG, Gabrielson M, Lisok A, Wharram B, Sysa-Shah P, et al. A humanized
antibody for imaging immune checkpoint ligand PD-L1 expression in tumors. Oncotarget 2016;7
(9):10215–27.
[62] Mayer AT, Gambhir SS. The immunoimaging toolbox. J Nucl Med 2018;59(8):1174–82.
[63] Xing Y, Chand G, Liu C, Cook GJR, O’Doherty J, Zhao L, et al. Early Phase I study of a (99m)Tc-
labeled anti-programmed death ligand-1 (PD-L1) single-domain antibody in SPECT/CT assessment
of PD-L1 expression in non-small cell lung cancer. J Nucl Med 2019;60(9):1213–20.
[64] Bensch F, van der Veen EL, Lub-de Hooge MN, Jorritsma-Smit A, Boellaard R, Kok IC, et al. (89)
Zr-atezolizumab imaging as a non-invasive approach to assess clinical response to PD-L1 blockade in
cancer. Nat Med 2018;24(12):1852–8.
[65] Niemeijer AN, Leung D, Huisman MC, Bahce I, Hoekstra OS, van Dongen G, et al. Whole body
PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer. Nat
Commun 2018;9(1):4664.
[66] Meir R, Shamalov K, Sadan T, Motiei M, Yaari G, Cohen CJ, et al. Fast image-guided stratification
using anti-programmed death ligand 1 gold nanoparticles for cancer immunotherapy. ACS Nano
2017;11(11):11127–34.
[67] Du Y, Liang X, Li Y, Sun T, Xue H, Jin Z, et al. Liposomal nanohybrid cerasomes targeted to PD-L1
enable dual-modality imaging and improve antitumor treatments. Cancer Lett 2018;414:230–8.
[68] Higashikawa K, Yagi K, Watanabe K, Kamino S, Ueda M, Hiromura M, et al. 64Cu-DOTA-anti-
CTLA-4 mAb enabled PET visualization of CTLA-4 on the T-cell infiltrating tumor tissues. PLoS
One 2014;9(11), e109866.
[69] Ingram JR, Blomberg OS, Rashidian M, Ali L, Garforth S, Fedorov E, et al. Anti-CTLA-4 therapy
requires an Fc domain for efficacy. Proc Natl Acad Sci U S A 2018;115(15):3912–7.
[70] Meletta R, M€uller Herde A, Dennler P, Fischer E, Schibli R, Kr€amer SD. Preclinical imaging of the
co-stimulatory molecules CD80 and CD86 with indium-111-labeled belatacept in atherosclerosis.
EJNMMI Res 2016;6(1):1.
[71] Meletta R, Steier L, Borel N, Mu L, Keller C, Chiotellis A, et al. CD80 is upregulated in a mouse
model with shear stress-induced atherosclerosis and allows for evaluating CD80-targeting PET tracers.
Mol Imaging Biol 2017;19(1):90–9.
[72] Picarda E, Ohaegbulam KC, Zang X. Molecular pathways: targeting B7-H3 (CD276) for human can-
cer immunotherapy. Clin Cancer Res 2016;22(14):3425–31.
[73] Burvenich IJG, Parakh S, Lee FT, Guo N, Liu Z, Gan HK, et al. Molecular imaging of T cell
co-regulator factor B7-H3 with (89)Zr-DS-5573a. Theranostics 2018;8(15):4199–209.
[74] Sek K, Mølck C, Stewart GD, Kats L, Darcy PK, Beavis PA. Targeting adenosine receptor signaling in
cancer immunotherapy. Int J Mol Sci 2018;19(12).
[75] Alam IS, Mayer AT, Sagiv-Barfi I, Wang K, Vermesh O, Czerwinski DK, et al. Imaging activated
T cells predicts response to cancer vaccines. J Clin Invest 2018;128(6):2569–80.
[76] Ng TSC, Gunda V, Li R, Prytyskach M, Iwamoto Y, Kohler RH, et al. Detecting immune response
to therapies targeting PDL1 and BRAF by using ferumoxytol MRI and macrin in anaplastic thyroid
cancer. Radiology 2020;298(1):123–32.
[77] Wittrup KD, Thurber GM, Schmidt MM, Rhoden JJ. Practical theoretic guidance for the design of
tumor-targeting agents. In: Wittrup KD, Verdine GL, editors. Methods in enzymology, 503. Aca-
demic Press; 2012. p. 255–68 [Chapter ten].
[78] Onesti CE, Fre`res P, Jerusalem G. Atypical patterns of response to immune checkpoint inhibitors:
interpreting pseudoprogression and hyperprogression in decision making for patients’ treatment.
J Thorac Dis 2019;11(1):35–8.
[79] Nishino M, Ramaiya NH, Hatabu H, Hodi FS. Monitoring immune-checkpoint blockade: response
evaluation and biomarker development. Nat Rev Clin Oncol 2017;14(11):655
–68.
[80] Wolchok JD, Hoos A, O’Day S, Weber JS, Hamid O, Lebbe C, et al. Guidelines for the evaluation of
immune therapy activity in solid tumors: immune-related response criteria. Clin Cancer Res 2009;15
(23):7412–20.
459Image-guided cancer immunotherapy
460 Thomas S.C. Ng and Miles A. Miller
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
[81] Hodi FS, Hwu WJ, Kefford R, Weber JS, Daud A, Hamid O, et al. Evaluation of immune-related
response criteria and RECIST v1.1 in patients with advanced melanoma treated with pembrolizumab.
J Clin Oncol 2016;34(13):1510–7.
[82] Nishino M. Immune-related response evaluations during immune-checkpoint inhibitor therapy: esta-
blishing a "common language" for the new arena of cancer treatment. J Immunother Cancer
2016;4:30.
[83] Seymour L, Bogaerts J, Perrone A, Ford R, Schwartz LH, Mandrekar S, et al. iRECIST: guidelines for
response criteria for use in trials testing immunotherapeutics. Lancet Oncol 2017;18(3):e143–52.
[84] Evangelista L, De Rimini ML, Bianchi A, Schillaci O. Immunotherapy and 18F-FDG PET/CT:
standardised procedures are needed. Clin Transl Imaging 2019;7(5):313–5.
[85] Cheson BD, Ansell S, Schwartz L, Gordon LI, Advani R, Jacene HA, et al. Refinement of the Lugano
classification lymphoma response criteria in the era of immunomodulatory therapy. Blood 2016;128
(21):2489–96.
[86] Ribas A, Benz MR, Allen-Auerbach MS, Radu C, Chmielowski B, Seja E, et al. Imaging of CTLA4
blockade-induced cell replication with (18)F-FLT PET in patients with advanced melanoma treated
with tremelimumab. J Nucl Med 2010;51(3):340–6.
[87] Ng TSC, Seethamraju RT, Bueno R, Gill RR. Clinical implementation of a free-breathing, motion-
robust dynamic contrast-enhanced MRI protocol to evaluate pleural tumors. Am J Roentgenol
2020;215(1):94–104.
[88] Garcı´a-Figueiras R, Baleato-Gonza´lez S, Luna A, Mun˜oz-Iglesias J, Oleaga L, Casas JAV, et al.
Assessing immunotherapy with functional and molecular imaging and radiomics. Radiographics
2020;40(7):1987–2010.
[89] Stenberg L, Englund E, Wirestam R, Siesj€o P, Salford LG, Larsson E-M. Dynamic susceptibility
contrast-enhanced perfusion magnetic resonance (MR) imaging combined with contrast-enhanced
MR imaging in the follow-up of immunogene-treated glioblastoma multiforme. Acta Radiol
2006;47(8):852–61.
[90] Saida Y, Brender JR, Yamamoto K, Mitchell JB, Krishna MC, Kishimoto S. Detecting early response
to immune checkpoint blockade by multimodal molecular imaging. bioRxiv 2020;, 070508.
[91] Zakaria R, Platt-Higgins A, Rathi N, Radon M, Das S, Das K, et al. T-cell densities in brain metas-
tases are associated with patient survival times and diffusion tensor MRI changes. Cancer Res 2018;78
(3):610–6.
[92] Daghighi S, Bahrami N, Tom WJ, Coley N, Seibert TM, Hattangadi-Gluth JA, et al. Restriction
spectrum imaging differentiates true tumor progression from immune-mediated pseudoprogression:
case report of a patient with glioblastoma. Front Oncol 2020;10:24.
[93] Nishino M, Giobbie-Hurder A, Manos MP, Bailey N, Buchbinder EI, Ott PA, et al. Immune-related
tumor response dynamics in melanoma patients treated with pembrolizumab: identifying markers for
clinical outcome and treatment decisions. Clin Cancer Res 2017;23(16):4671–9.
[94] Champiat S, Dercle L, Ammari S, Massard C, Hollebecque A, Postel-Vinay S, et al. Hyperprogressive
disease is a new pattern of progression in cancer patients treated by Anti-PD-1/PD-L1. Clin Cancer
Res 2017;23(8):1920–8.
[95] Khorrami M, Prasanna P, Gupta A, Patil P, Velu PD, Thawani R, et al. Changes in CT radiomic
features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non–small cell lung cancer. Cancer Immunol Res 2020;8(1):108–19.
[96] He B, Dong D, She Y, Zhou C, Fang M, Zhu Y, et al. Predicting response to immunotherapy in
advanced non-small-cell lung cancer using tumor mutational burden radiomic biomarker.
J Immunother Cancer 2020;8(2).
[97] Dercle L, Fronheiser M, Lu L, Du S, Hayes W, Leung DK, et al. Identification of non–small cell lung
cancer sensitive to systemic cancer therapies using radiomics. Clin Cancer Res 2020;26(9):2151–62.
[98] Trebeschi S, Drago SG, Birkbak NJ, Kurilova I, Cǎlin AM, Delli Pizzi A, et al. Predicting response to
cancer immunotherapy using noninvasive radiomic biomarkers. Ann Oncol 2019;30(6):998
[99] Kwak JJ, Tirumani SH, Abbeele ADVd, Koo PJ, Jacene HA. Cancer immunotherapy: imaging assess-
ment of novel treatment response patterns and immune-related adverse events. Radiographics
2015;35(2):424–37.
–1004.
Соседние файлы в папке Библиотека им академика М.И. Перельмана