scholarly journals Cathepsin K Expression in Castration-Resistant Prostate Carcinoma: A Therapeutical Target for Patients at Risk for Bone Metastases

2017 ◽  
Vol 32 (2) ◽  
pp. 243-247 ◽  
Author(s):  
Enrico Munari ◽  
Luca Cima ◽  
Francesco Massari ◽  
Francesco Bertoldo ◽  
Antonio Benito Porcaro ◽  
...  
Keyword(s):  
Bone Metastases ◽  
Tumor Cells ◽  
Prostate Carcinoma ◽  
Cathepsin K ◽  
Predictive Biomarker ◽  
Tissue Microarrays ◽  
Resistant Disease ◽  
Castration Resistant ◽  
Cathepsin K Inhibitors ◽  
Peritumoral Stroma

Background The lysosomal cysteine protease cathepsin K is involved in bone remodeling and is also expressed in the peritumoral stroma of carcinomas arising from different organs. A new generation of cathepsin K inhibitors blocking the RANKL/RANK pathway are being developed. We sought to investigate cathepsin K expression in a cohort of castration-resistant prostate carcinomas. Methods Sixteen cases of castration-resistant disease with at least 5 years of follow-up were selected from a cohort of 280 patients who underwent surgery. Cathepsin K was evaluated on formalin-fixed and paraffin-embedded tissue microarrays with 5 tissue spots per case. These were scored as high 2+ (≥30% of cells), low 1+ (<30% of cells) or zero (absence), distinguishing tumor cells and peritumoral stroma cells. Low (1+) and absence (0) of scoring were interpreted as negative, and high (2+) as positive. Results The castration-resistant group was composed of 15 acinar adenocarcinomas and 1 neuroendocrine carcinoma, and all showed at least Gleason score 8 at prostatectomy. Two out of 16 cases (12%) scored positive for cathepsin K in tumor cells; and 5 of 16 cases (31%) scored positive in peritumoral stroma cells. The neuroendocrine and acinar subtypes of carcinoma with positive immunoexpression in neoplastic cells developed bone metastases after 4 and 5 years, respectively, and subsequently died. Conclusions Patients affected by castration-resistant prostate carcinoma may be tested for cathepsin K, and a positive strong expression (2+) could be a useful predictive biomarker of response to targeted agents, aiding in the selection of patients eligible for these treatments.

scholarly journals Systemic Alterations of Wnt Inhibitors in Patients with Prostate Cancer and Bone Metastases

2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Stefan Aufderklamm ◽  
Jörg Hennenlotter ◽  
Phillip Leidenberger ◽  
Steffen Rausch ◽  
Andrea Hohneder ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastases ◽  
Serum Levels ◽  
Enzyme Linked Immunosorbent Assay ◽  
Study Cohort ◽  
Resistant Disease ◽  
Castration Resistant ◽  
Osteoblast Activity ◽  
Osteolytic Metastases ◽  
Post Hoc

Purpose. Dickkopf-1 (DKK-1) and sclerostin seem to inhibit osteoblast activity by blocking the Wnt pathway, which leads to progression of metastatic prostate cancer (PC). However, it is unknown whether serum levels of these proteins are altered in PC patients with or without metastasis. The aim of this study was to assess DKK-1 and sclerostin serum levels in PC patients, including patients with bone metastases. Methods. The study cohort (N=143) consisted of 53 controls with benign prostatic hyperplasia (BPH), 43 with localized PC (PC cM0), and 47 had PC with metastasis (PC cM1). Serum levels of DKK-1 and sclerostin were measured by enzyme-linked immunosorbent assay. Results were compared using the Kruskal-Wallis tests; post hoc analysis was performed using the Tukey-Kramer test. Results. Mean DKK-1 levels in patients with BPH (2809.4 pg/ml) (p<0.001) as well as PC cM1 (2575.5 pg/ml) (p=0.001) were significantly higher than in patients with PC cN0 cM0 (1551.8 pg/ml). Among PC cM1 patients, median DKK-1 levels were significantly lower in patients with castration-resistant disease compared to those with hormone-sensitive PC (p=0.02); in contrast, sclerostin concentrations were elevated (p=0.04). DKK-1 correlated with PSA in the cM1 group (p=0.03) and sclerostin correlated with PSA in the PC group (0.01). Conclusions. DKK-1 is involved in the progression of PC. DKK-1-mediated inhibition of osteoblasts, which contributes to tumor progression and osteolytic metastases, may also play a role in the development of metastases with osteoblastic features. The use of DKK-1 antibodies should be considered for studies including metastatic PC patients.

scholarly journals Cathepsin K: A Novel Diagnostic and Predictive Biomarker for Renal Tumors

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2441
Author(s):  
Anna Caliò ◽  
Matteo Brunelli ◽  
Stefano Gobbo ◽  
Pedram Argani ◽  
Enrico Munari ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Therapy Response ◽  
Cathepsin K ◽  
Mtor Inhibitors ◽  
Predictive Marker ◽  
Predictive Biomarker ◽  
Renal Tumors ◽  
Epithelioid Angiomyolipoma

Cathepsin K is a papain-like cysteine protease with high matrix-degrading activity. Among several cathepsins, cathepsin K is the most potent mammalian collagenase, mainly expressed by osteoclasts. This review summarizes most of the recent findings of cathepsin K expression, highlighting its role in renal tumors for diagnostic purposes and as a potential molecular target. Indeed, cathepsin K is a recognized diagnostic tool for the identification of TFE3/TFEB-rearranged renal cell carcinoma, TFEB-amplified renal cell carcinoma, and pure epithelioid PEComa/epithelioid angiomyolipoma. More recently, its expression has been observed in a subgroup of eosinophilic renal neoplasms molecularly characterized by TSC/mTOR gene mutations. Interestingly, both TSC mutations or TFE3 rearrangement have been reported in pure epithelioid PEComa/epithelioid angiomyolipoma. Therefore, cathepsin K seems to be a downstream marker of TFE3/TFEB rearrangement, TFEB amplification, and mTOR pathway activation. Given the established role of mTOR inhibitors as a pharmacological option in renal cancers, cathepsin K could be of use as a predictive marker of therapy response and as a potential target. In the future, uropathologists may implement the use of cathepsin K to establish a diagnosis among renal tumors with clear cells, papillary architecture, and oncocytic features.

Erratum to ‘Cathepsin K inhibitors prevent matrix-derived growth factor degradation by human osteoclasts’

Bone ◽  
2021 ◽  
Vol 145 ◽  
pp. 115354
Author(s):  
Karen Fuller ◽  
Kevin M. Lawrence ◽  
Jade L. Ross ◽  
Urszula B. Grabowska ◽  
Masahiro Shiroo ◽  
...  
Keyword(s):  
Growth Factor ◽  
Cathepsin K ◽  
Cathepsin K Inhibitors ◽  
Human Osteoclasts

Cathepsin K inhibitors based on 2-amino-1,3,4-oxadiazole derivatives

2021 ◽  
Vol 109 ◽  
pp. 104662
Author(s):  
Talita B. Gontijo ◽  
Patrícia S. Lima ◽  
Marcelo Y. Icimoto ◽  
Raquel Leão Neves ◽  
Érika C. de Alvarenga ◽  
...  
Keyword(s):  
Cathepsin K ◽  
Cathepsin K Inhibitors ◽  
Oxadiazole Derivatives

scholarly journals piNET–An Automated Proliferation Index Calculator Framework for Ki67 Breast Cancer Images

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 11
Author(s):  
Rokshana Stephny Geread ◽  
Abishika Sivanandarajah ◽  
Emily Rita Brouwer ◽  
Geoffrey A. Wood ◽  
Dimitrios Androutsos ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Tissue Microarrays ◽  
False Positives ◽  
Proliferation Index ◽  
Tumor Segmentation ◽  
Significant Activity ◽  
Hotspot Analysis ◽  
Weak Supervision ◽  
Wide Variability ◽  
Whole Slide Images

In this work, a novel proliferation index (PI) calculator for Ki67 images called piNET is proposed. It is successfully tested on four datasets, from three scanners comprised of patches, tissue microarrays (TMAs) and whole slide images (WSI), representing a diverse multi-centre dataset for evaluating Ki67 quantification. Compared to state-of-the-art methods, piNET consistently performs the best over all datasets with an average PI difference of 5.603%, PI accuracy rate of 86% and correlation coefficient R = 0.927. The success of the system can be attributed to several innovations. Firstly, this tool is built based on deep learning, which can adapt to wide variability of medical images—and it was posed as a detection problem to mimic pathologists’ workflow which improves accuracy and efficiency. Secondly, the system is trained purely on tumor cells, which reduces false positives from non-tumor cells without needing the usual pre-requisite tumor segmentation step for Ki67 quantification. Thirdly, the concept of learning background regions through weak supervision is introduced, by providing the system with ideal and non-ideal (artifact) patches that further reduces false positives. Lastly, a novel hotspot analysis is proposed to allow automated methods to score patches from WSI that contain “significant” activity.

Sign in / Sign up

Export Citation Format

Share Document