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Stromal gene expression predictive of metastatic primary prostate cancer
M.S.Salomov
Department of Otorhinolaryngology, Ophthalmology, Oncology and Medical
Radiology Termez branch of the Tashkent Medical Academy
Relevance.
Clinical grading systems that use clinical characteristics, as well as nomograms, do not
have the accuracy to guide treatment decisions for prostate cancer (prostate cancer). There is a critical
need to identify biomarkers that can more accurately stratify men with primary prostate cancer.
The purpose of the study.
To identify an effective prognostic signature that can better distinguish
between indolent and aggressive prostate cancer (prostate cancer).
Design, conditions and participants of the study.
To develop the signature, whole genome and
whole transcriptome were sequenced on five prostate cancer models with xenographs from patients
(PG) obtained from independent foci of a single primary tumor and demonstrating different metastatic
phenotypes. Several independent clinical cohorts, including the intermediate risk cohort, were used
to validate biomarkers.
Determination of results and statistical analysis
Metastasis after radical prostatectomy was the
outcome that determined aggressive prostate cancer. A general linear model with lasso regularization
was used to construct a 93-gene stromal metastasis signature (SDMS). The association between
SDMS and metastasis was assessed using the Wilcoxon rank sum test. Efficiency was evaluated using
the area under the curve (AUC) for receiver performance and Kaplan-Meyer curves. Univariable and
multivariable regression models were used to compare SDMS with clinical histological variables and
other signatures. AUC was evaluated to determine whether SDMS is additive or synergistic with
respect to other previously defined signatures.
Results and limitations
There was a close association
between stromal gene expression and metastatic phenotype. Accordingly, SDMS was modeled and
validated in several independent clinical cohorts. Patients with high SDMS scores, as it turned out,
had a worse prognosis. Moreover, SDMS was an independent predictive factor, was able to stratify
the risk of intermediate-risk prostate cancer, and can improve the effectiveness of other previously
presented signatures.
Conclusion
Profiling of stromal gene expression led to the development of
SDMS, which has been validated as an independent prognostic factor for the metastatic potential of
prostate tumors
