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Endosomal gene expression: a new indicator for prostate cancer patient prognosis?

ABSTRACT: Prostate cancer continues to be a major cause of morbidity and mortality in men, but a method for accurate prognosis in these patients is yet to be developed. The recent discovery of altered endosomal biogenesis in prostate cancer has identified a fundamental change in the cell biology of this cancer, which holds great promise for the identification of novel biomarkers that can predict disease outcomes. Here we have identified significantly altered expression of endosomal genes in prostate cancer compared to non-malignant tissue in mRNA microarrays and confirmed these findings by qRT-PCR on fresh-frozen tissue. Importantly, we identified endosomal gene expression patterns that were predictive of patient outcomes. Two endosomal tri-gene signatures were identified from a previously published microarray cohort and had a significant capacity to stratify patient outcomes. The expression of APPL1, RAB5A, EEA1, PDCD6IP, NOX4 and SORT1 were altered in malignant patient tissue, when compared to indolent and normal prostate tissue. These findings support the initiation of a case-control study using larger cohorts of prostate tissue, with documented patient outcomes, to determine if different combinations of these new biomarkers can accurately predict disease status and clinical progression in prostate cancer patients.

SUBMITTER: Johnson IR

PROVIDER: S-EPMC4741974 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Endosomal gene expression: a new indicator for prostate cancer patient prognosis?

Johnson Ian R D IR Parkinson-Lawrence Emma J EJ Keegan Helen H Spillane Cathy D CD Barry-O'Crowley Jacqui J Watson William R WR Selemidis Stavros S Butler Lisa M LM O'Leary John J JJ Brooks Doug A DA

Oncotarget 20151101 35

Prostate cancer continues to be a major cause of morbidity and mortality in men, but a method for accurate prognosis in these patients is yet to be developed. The recent discovery of altered endosomal biogenesis in prostate cancer has identified a fundamental change in the cell biology of this cancer, which holds great promise for the identification of novel biomarkers that can predict disease outcomes. Here we have identified significantly altered expression of endosomal genes in prostate cance ...[more]

PMID: 26473288

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Project description:Kallikreins are a group of serine proteases with diverse physiological functions. KLK13 (previously known as KLK-L4) is a novel kallikrein gene located on chromosome 19q13.4 and shares a high degree of homology with other kallikrein family members. Many kallikrein genes were found to be differentially expressed in various malignancies, and their regulation is controlled by steroid hormones in prostate and breast cancer cell lines. We studied the expression of KLK13 by quantitative reverse transcriptase-polymerase chain reaction in 173 patients with epithelial breast carcinoma. An optimal cutoff point equal to the 40th percentile was defined, based on the ability of KLK13 to predict disease-free survival. KLK13 values were then associated with other established prognostic factors and with disease-free survival and overall survival. Higher positivity for KLK13 expression was found in older, oestrogen receptor positive patients. In univariate analysis, KLK13 expression is a significant predictor of improved disease-free survival and overall survival (P<0.001 and P=0.009, respectively). Cox multivariate analysis indicated that KLK13 was an independent prognostic variable in the subgroups of patients with Grade I-II tumours and in patients who were oestrogen receptor and progesterone receptor positive, and node positive. Hazard ratios derived from Cox analysis, related to disease-free survival and overall survival were 0.22 (P=0.001) and 0.24 (P=0.008), respectively, for the Grade I-II group; 0.36 (P=0.008) and 0.44 (P=0.038), respectively, for the node positive group and 0.36 (P=0.008) and 0.18 (P=0.008), respectively, for the oestrogen receptor positive group. The adjusted hazard ratio for progesterone receptor positive patients for disease-free survival was 0.25 (P=0.012). For patients in the node positive and oestrogen receptor positive subgroup (n=51) the adjusted hazard ratio was 0.25 (P=0.006) and for the node positive and progesterone receptor positive subgroup (n=46) the hazard ratio was 0.24 (P=0.008). Taken together, these data suggest that higher KLK13 expression in these subgroups of breast cancer patients is associated with an approximately 55 to 80% reduction in the risk of relapse or death. We conclude that KLK13 expression, as assessed by quantitative reverse transcriptase-polymerase chain reaction, is an independent favourable prognostic marker for breast carcinoma.

Project description:BackgroundProstate cancer (PCa) is one of the most prevalent cancers that occur in men worldwide. Autophagy-related genes (ARGs) may play an essential role in multiple biological processes of prostate cancer. However, ARGs expression signature has rarely been used to investigate the association between autophagy and prognosis in PCa. This study aimed to identify and assess prognostic ARGs signature to predict overall survival (OS) and disease-free survival (DFS) in PCa patients.MethodsFirst, a total of 234 autophagy-related genes were obtained from The Human Autophagy Database. Then, differentially expressed ARGs were identified in prostate cancer patients based on The Cancer Genome Atlas (TCGA) database. The univariate and multivariate Cox regression analysis was performed to screen hub prognostic ARGs for overall survival and disease-free survival, and the prognostic model was constructed. Finally, the correlation between the prognostic model and clinicopathological parameters was further analyzed, including age, T status, N status, and Gleason score.ResultsThe OS-related prognostic model was constructed based on the five ARGs (FAM215A, FDD, MYC, RHEB, and ATG16L1) and significantly stratified prostate cancer patients into high- and low-risk groups in terms of OS (HR = 6.391, 95% CI = 1.581- 25.840, P < 0.001). The area under the receiver operating characteristic curve (AUC) of the prediction model was 0.84. The OS-related prediction model values were higher in T3-4 than in T1-2 (P = 0.008), and higher in Gleason score > 7 than ≤ 7 (P = 0.015). In addition, the DFS-related prognostic model was constructed based on the 22 ARGs (ULK2, NLRC4, MAPK1, ATG4D, MAPK3, ATG2A, ATG9B, FOXO1, PTEN, HDAC6, PRKN, HSPB8, P4HB, MAP2K7, MTOR, RHEB, TSC1, BIRC5, RGS19, RAB24, PTK6, and NRG2), with AUC of 0.85 (HR = 7.407, 95% CI = 4.850-11.320, P < 0.001), which were firmly related to T status (P < 0.001), N status (P = 0.001), and Gleason score (P < 0.001).ConclusionsOur ARGs based prediction models are a reliable prognostic and predictive tool for overall survival and disease-free survival in prostate cancer patients.

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Endosomal gene expression: a new indicator for prostate cancer patient prognosis?

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Endosomal gene expression: a new indicator for prostate cancer patient prognosis?

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