dc.contributor.author |
Puranik, Ameya D.
|
|
dc.contributor.author |
Dromain, Clarisse
|
|
dc.contributor.author |
Fleshner, Neil
|
|
dc.contributor.author |
Sathekge, Mike Machaba
|
|
dc.contributor.author |
Pavel, Marianne
|
|
dc.contributor.author |
Eberhardt, Nina
|
|
dc.contributor.author |
Zengerling, Friedemann
|
|
dc.contributor.author |
Marienfeld, Ralf
|
|
dc.contributor.author |
Grunert, Michael
|
|
dc.contributor.author |
Prasad, Vikas
|
|
dc.date.accessioned |
2021-09-13T07:32:14Z |
|
dc.date.available |
2021-09-13T07:32:14Z |
|
dc.date.issued |
2021 |
|
dc.description.abstract |
Tumor or target heterogeneity (TH) implies presence of variable cellular populations having
different genomic characteristics within the same tumor, or in different tumor sites of the same
patient. The challenge is to identify this heterogeneity, as it has emerged as the most common cause
of ‘treatment resistance’, to current therapeutic agents. We have focused our discussion on ‘Prostate
Cancer’ and ‘Neuroendocrine Tumors’, and looked at the established methods for demonstrating
heterogeneity, each with its advantages and drawbacks. Also, the available theranostic radiotracers
targeting PSMA and somatostatin receptors combined with targeted systemic agents, have been
described. Lu-177 labeled PSMA and DOTATATE are the ‘standard of care’ radionuclide therapeutic
tracers for management of progressive treatment-resistant prostate cancer and NET. These approved
therapies have shown reasonable benefit in treatment outcome, with improvement in quality of
life parameters. Various biomarkers and predictors of response to radionuclide therapies targeting
TH which are currently available and those which can be explored have been elaborated in details.
Imaging-based features using artificial intelligence (AI) need to be developed to further predict the
presence of TH. Also, novel theranostic tools binding to newer targets on surface of cancer cell should
be explored to overcome the treatment resistance to current treatment regimens. |
en_ZA |
dc.description.department |
Nuclear Medicine |
en_ZA |
dc.description.librarian |
pm2021 |
en_ZA |
dc.description.uri |
http://www.mdpi.com/journal/cancers |
en_ZA |
dc.identifier.citation |
Puranik, A.D.; Dromain, C.;
Fleshner, N.; Sathekge, M.; Pavel, M.;
Eberhardt, N.; Zengerling, F.;
Marienfeld, R.; Grunert, M.; Prasad, V.
Target Heterogeneity in Oncology:
The Best Predictor for Differential
Response to Radioligand Therapy in
Neuroendocrine Tumors and Prostate
Cancer. Cancers 2021, 13, 3607.
https://doi.org/10.3390/cancers13143607. |
en_ZA |
dc.identifier.issn |
2072-6694 (online) |
|
dc.identifier.other |
10.3390/ cancers13143607 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/81768 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
MDPI |
en_ZA |
dc.rights |
© 2021 by the authors.
Licensee: MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license. |
en_ZA |
dc.subject |
Heterogeneity |
en_ZA |
dc.subject |
Prostate cancer |
en_ZA |
dc.subject |
Neuroendocrine tumor |
en_ZA |
dc.subject |
Target heterogeneity |
en_ZA |
dc.subject |
Tumor |
en_ZA |
dc.title |
Target heterogeneity in oncology : the best predictor for differential response to radioligand therapy in neuroendocrine tumors and prostate cancer |
en_ZA |
dc.type |
Article |
en_ZA |