Aging-US: Biomarkers of biochemical recurrence in prostate adenocarcinoma
07-25-2021Aging-US published "Identification of microenvironment related potential biomarkers of biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma" which reported that the authors aimed to identify the potential prognostic genes in the prostate adenocarcinoma microenvironment and to estimate the causal effects simultaneously.
They obtained the gene expression data of prostate adenocarcinoma from the TCGA project and identified the differentially expressed genes based on immune-stromal components.
Among these genes, 68 were associated with biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma.
POSTN and NETO1 were correlated with androgen receptor expression, a main driver of prostate adenocarcinoma progression.
Finally, five genes were validated in another prostate adenocarcinoma cohort.
Dr. Fuzhong Xue from The Shandong University said, "Prostate cancer is a common malignant tumor and the leading cause of cancer-related mortality in men."
Dr. Fuzhong Xue from The Shandong University said, "Prostate cancer is a common malignant tumor and the leading cause of cancer-related mortality in men."
Prostate adenocarcinoma is the most common type of prostate cancer, whereas other types of prostate cancer are relatively rare.
In this study, the authors used targeted maximum likelihood estimation, a doubly robust method to detect the prognostic genes and estimate both the average and individual causal effects.
When estimating the causal effect of the prognostic gene on the BCR status, controlling too many covariates might result in the poor performance of the estimator.
Thus, they applied the algorithm CovSel to select the minimal conditioning set that was sufficient for unbiased effect estimations of the target gene on the BCR.
Figure 9. The expressions of (A) POSTN, (B) NETO1 and (C) CXCL5 in AR- and non-AR-driven groups using GSE101607. T-test was used to measure the difference between the two groups.
Moreover, the causal effects of these genes were estimated for individual therapies.
The Xue Research Team concluded in their Aging-US Research Output, "we used TCGA dataset to identify the potential prognostic genes in PRAD. Using the associations between the immune/stromal scores and the prognosis of PRAD, we revealed a set of genes related to the TME and the BCR of PRAD. These findings might facilitate the prognosis of PRAD. Based on our study, previously neglected genes could be used as biomarkers for PRAD. Finally, further studies of these genes could provide a more comprehensive understanding of the potential relationship between the prognosis of PRAD and the TME."
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DOI - https://doi.org/10.18632/aging.203121
Full Text - https://www.aging-us.com/article/203121/text
Correspondence to: Fuzhong Xue email: xuefzh@sdu.edu.cn
Keywords: prostate adenocarcinoma, biochemical recurrence, gene expression, tumor microenvironment, targeted maximum likelihood estimation
About Aging-US:
Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.
Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed Central, Web of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).
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