Back

CUB domain containing protein 1 (CDPC1) is a target for radioligand therapy in castration resistant prostate cancer

Zhao, N.; Trepka, k.; Wang, Y.-h.; Chopra, S.; Hooshdaran, N.; Kim, H.; Yang, J.; Zhuo, J.; Lim, S.; Leung, K. K.; Egusa, E.; Zhang, L. K.; Foye, A.; Chou, J.; Feng, F. Y.; Small, E. J.; Evans, M. J.; Wells, J. A.; Aggarwal, R.

2021-06-17 cancer biology
10.1101/2021.06.17.448569 bioRxiv
Show abstract

PurposeRadioligand therapy (RLT) is relatively unexplored in metastatic castration resistant prostate cancer (mCRPC), with much of the focus having been on bone seeking radionuclides and PSMA-directed RLT. Herein, we evaluated if CUB domain containing protein 1 (CDCP1) can be exploited to treat mCRPC with RLT, particularly for subsets like small cell neuroendocrine prostate cancer (SCNC) that would not be expected to respond to current options. Experimental DesignCDCP1 mRNA levels were evaluated in the RNA-seq data from 119 recent mCRPC biopsies. Protein expression was assessed in twelve SCNC and adenocarcinoma patient derived xenografts. Saturation binding assays were performed with 4A06, a recombinant human antibody that targets the CDCP1 ectodomain. The feasibility of imaging and treating mCRPC in vivo was tested with 89Zr-4A06 and 177Lu-4A06. ResultsCDCP1 mRNA expression was observed in over 90% of mCRPC biopsies, including SCNC and in adenocarcinoma with low FOLH1 (PSMA) levels. A modest anticorrelation was observed between CDCP1 and PTEN. Overall survival was not significantly different based on CDCP1 mRNA levels, regardless of PTEN status. Full length and/or cleaved CDCP1 was expressed in ten of twelve PDX samples. Bmax values of ~22,000 and ~6,200 fmol/mg were calculated for two human prostate cancer cell lines. Five prostate cancer models were readily detected in vivo with 89Zr-4A06. 177Lu-4A06 significantly suppressed the growth of DU145 tumors compared to control. ConclusionsThe antitumor data and the overexpression of CDCP1 reported herein provide the first evidence promoting CDCP1 directed RLT as a treatment strategy for mCRPC. Statement of Translational RelevanceNew targets for RLT are needed to address the subset of mCRPC that cannot be treated with bone seeking radionuclides or PSMA directed RLT. We report herein the first data credentialing CDCP1 as a target for mCRPC, in both adenocarcinoma and neuroendocrine subtypes. Combined with low expression in normal human tissues, these data provide a compelling scientific rationale for testing CDCP1 directed RLT clinically in mCRPC patients alone or in combination with other systemic therapies.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Molecular Cancer Therapeutics
33 papers in training set
Top 0.1%
38.2%
2
The Prostate
11 papers in training set
Top 0.1%
6.4%
3
Frontiers in Oncology
95 papers in training set
Top 0.5%
6.4%
50% of probability mass above
4
Clinical Cancer Research
58 papers in training set
Top 0.3%
4.9%
5
PLOS ONE
4510 papers in training set
Top 33%
4.4%
6
British Journal of Cancer
42 papers in training set
Top 0.4%
3.6%
7
Scientific Reports
3102 papers in training set
Top 35%
3.6%
8
International Journal of Radiation Oncology*Biology*Physics
21 papers in training set
Top 0.2%
3.3%
9
International Journal of Cancer
42 papers in training set
Top 0.5%
2.1%
10
Neuro-Oncology
30 papers in training set
Top 0.4%
2.1%
11
BMC Cancer
52 papers in training set
Top 1%
1.7%
12
Neoplasia
22 papers in training set
Top 0.2%
1.7%
13
Journal for ImmunoTherapy of Cancer
64 papers in training set
Top 0.6%
1.7%
14
Cancer Research Communications
46 papers in training set
Top 0.5%
1.5%
15
Genome Medicine
154 papers in training set
Top 6%
1.2%
16
JCI Insight
241 papers in training set
Top 5%
1.0%
17
Cancer Epidemiology, Biomarkers & Prevention
17 papers in training set
Top 0.5%
1.0%
18
Journal of Translational Medicine
46 papers in training set
Top 2%
1.0%
19
Cancers
200 papers in training set
Top 4%
0.9%
20
Modern Pathology
21 papers in training set
Top 0.3%
0.9%
21
Neuro-Oncology Advances
24 papers in training set
Top 0.4%
0.8%
22
Cell Reports Medicine
140 papers in training set
Top 8%
0.8%
23
Nature Communications
4913 papers in training set
Top 64%
0.7%