This study aimed to identify the predictive factors associated with the oncological outcomes of metastatic hormone-sensitive prostate cancer-related genes. A nomogram for predicting prostate cancer-specific survival (CSS) was constructed based on biopsy samples obtained from 103 patients with metastatic hormone-sensitive prostate cancer. We analyzed the association between clinical data and mRNA expression levels. The nomogram was externally validated in another cohort (n = 50) by using a concordance index. Based on the cutoff value, determined by a receiver operating characteristic analysis, longer CSS was observed in the high osteoglycin and androgen receptor expression level groups (> 1.133 and > 0.00; median CSS, 85.3 vs. 52.7 months, p = 0.045, and 69.1 vs. 32.1 months, p = 0.034, respectively), compared with that of the low expression level groups. The nomogram predicting CSS included hemoglobin (≥ 13.7 g/dL or < 13.7 g/dL), serum albumin (≥ 3.1 g/dL or < 3.1 g/dL), serum lactate dehydrogenase (≥ 222 IU/L or < 222 IU/L), total Japan Cancer of the Prostate Risk Assessment score, androgen receptor expression level, and osteoglycin expression level. The concordance indices for the internal and external validations were 0.664 and 0.798, respectively. In this study, a nomogram that integrated the expression levels of androgen receptors and osteoglycin to predict CSS in metastatic hormone-sensitive prostate cancer was established.

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-024-74443-zDOI Listing

Publication Analysis

Top Keywords

androgen receptor
8
prostate cancer
8
metastatic hormone-sensitive
8
hormone-sensitive prostate
8
nomogram predicting
8
expression level
8
level groups
8
receptor osteoglycin
4
osteoglycin gene
4
expression
4

Similar Publications

Purpose: No currently available phase III trial compared docetaxel vs. androgen receptor pathway inhibitors (ARPI) regarding cancer-control outcomes in metastatic hormone-sensitive prostate cancer (mHSPC). Moreover, few is known about the effect of sequential therapies in mHSPC and subsequent metastatic castration resistant prostate cancer (mCRPC).

View Article and Find Full Text PDF

This study aimed to identify the predictive factors associated with the oncological outcomes of metastatic hormone-sensitive prostate cancer-related genes. A nomogram for predicting prostate cancer-specific survival (CSS) was constructed based on biopsy samples obtained from 103 patients with metastatic hormone-sensitive prostate cancer. We analyzed the association between clinical data and mRNA expression levels.

View Article and Find Full Text PDF

Generation of an induced pluripotent stem cell (iPSC) line (INNDSUi007-A) from a patient with Kennedy disease.

Stem Cell Res

December 2024

Department of Neurology, Research Institute of Neuromuscular and Neurodegenerative Diseases, Shandong Key Laboratory of Mitochondrial Medicine and Rare Diseases, Jinan, Shandong, China. Electronic address:

Abnormal trinucleotide CAG repeat expansions in exon 1 of the Androgen Receptor (AR) gene has been identified as the cause of Kennedy disease (KD). We generated and characterized a human induced pluripotent stem cell (iPSC) line from peripheral blood mononuclear cells (PBMC) of a patient with genetically confirmed KD. The pluripotency of these iPSCs was verified by the expression of several pluripotency markers at both RNA and protein levels, as well as their capability to differentiate into all three germ layers.

View Article and Find Full Text PDF

Background: Triple-negative breast cancer (TNBC) is a serious disease with limited treatment options. We explored the significance of androgen receptor (AR) expression and tumor-infiltrating lymphocytes (TILs) in predicting neoadjuvant chemotherapy (NAC) resistance in TNBC, hypothesizing that AR/TIL classification using pretreatment biopsies can identify NAC-resistant subgroups and improve the understanding of apocrine differentiation.

Methods: This retrospective study included 156 consecutive patients with TNBC treated with NAC.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!