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Julka et al. J Transl Genet Genom 2020;4:455-63              Journal of Translational
               DOI: 10.20517/jtgg.2020.46                                  Genetics and Genomics




               Case Report                                                                   Open Access


               Adenoid cystic carcinoma of the prostate: an
               unusual subtype of prostate cancer



               Pramod Kumar Julka *, Amit Verma *, Sanjay Gupta , Kush Gupta , Rahul Rathod 4
                                              2,
                                 1,
                                                                        3
                                                            3
               1 Department of Medical Oncology, Max Institute of Cancer Care, New Delhi 110024, India.
               2 Department of Molecular Oncology, Max Institute of Cancer Care, New Delhi 110024, India.
               3 Department of Clinical Operations, Catalyst Clinical Services Pvt. Ltd., New Delhi 110089, India.
               4 Department of Medical Affairs, MitraRxDx India Pvt. Ltd, Bengaluru 560037, India.
               *Equal contribution.
               Correspondence to: Dr. Pramod Kumar Julka, Department of Medical Oncology, Max Institute of Cancer Care, Lajpat Nagar,
               New Delhi 110024, India. E-mail: pkjulka18@yahoo.co.in; Dr. Amit Verma, Department of Molecular Oncology, Max Institute of
               Cancer Care, New Delhi 110024, India. E-mail: amitverma.dr@gmail.com
               How to cite this article: Julka PK, Verma A, Gupta S, Gupta K, Rathod R. Adenoid cystic carcinoma of the prostate: an unusual
               subtype of prostate cancer. J Transl Genet Genom 2020;4:455-63. http://dx.doi.org/10.20517/jtgg.2020.46
               Received: 10 Sep 2020    First Decision: 9 Oct 2020    Revised: 15 Oct 2020    Accepted: 3 Nov 2020    Available online: 13 Nov 2020

               Academic Editor: Sanjay Gupta    Copy Editor: Cai-Hong Wang    Production Editor: Jing Yu


               Abstract
               Adenoid cystic carcinoma (ACC) of the prostate is an extremely rare disease that arises from the basal cells of
               prostate acini and presents a poor prognosis for metastatic cases. Multiple treatment options exist for different
               stages of prostate cancer that include prostatectomy, radiation therapy, chemotherapy, and hormone therapy
               with gonadrotropin-releasing hormone (GnRH) agonists and antagonists for androgen receptor (AR)-positive
               cases. Although ACC has a biological potential that allows metastasis in a few cases; the current treatment option
               consists primarily of surgical resection along with close, long-term follow-up. Herein, we report this rare entity in
               a 79-year-old man who presented with liver metastasis. The tumor expressed GnRH receptor (GnRHR) and a very
               low level of Programmed death-ligand 1 (PD-L1). Immunohistochemical analysis revealed that the primary tumor
               was highly proliferative and AR-negative. We employed a clinically validated technology that utilizes patient's
               tumor and blood to recreate the tumor microenvironment ex vivo. After the diagnosis, we used the platform to test
               the efficacy of degarelix (a GnRHR antagonist), atezolizumab (a PD-L1 antagonist) and paclitaxel + carboplatin
               chemotherapeutic regimen. The assay output predicted response with chemotherapeutics and degarelix, without
               any sign of efficacy for PD-L1 antagonist. On the basis of these data, the patient was treated with paclitaxel +
               carboplatin combination chemotherapy first and showed clinical and radiological response as predicted by the
               ex vivo platform. After 4 cycles of chemotherapy, the patient received maintenance therapy with degarelix and
               demonstrated a favorable clinical response. Taken together, our results not only showed the accurate prediction


                           © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
                sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long
                as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
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