Pathway-based expression profiling of benign prostatic hyperplasia and prostate cancer delineates an immunophilin molecule associated with cancer progression

FKBP4 regulates 5-fluorouracil sensitivity in colon cancer by controlling mitochondrial respiration

FKBP4 controls mitochondrial respiration via modulating COA6-mediated biogenesis and activity of mitochondrial complex IV, thereby regulating 5-fluorouracil sensitivity in colon cancer.

Mitochondrial respiration and metabolism play a key role in the pathogenesis and progression of colon adenocarcinoma (COAD). Here, we report a functional pool of FKBP4, a co-chaperone protein, in the mitochondrial intermembrane space (IMS) of colon cancer cells. We found that IMS-localized FKBP4 is essential for the maintenance of mitochondrial respiration, thus contributing to the sensitivity of COAD cells to 5-fluorouracil (5-FU). Mechanistically, FKBP4 interacts with COA6 and controls the assembly of the mitochondrial COA6/SCO1/SCO2 complex, thereby governing COA6-regulated biogenesis and activity of mitochondrial cytochrome c oxidase (complex IV). Thus, our data reveal IMS-localized FKBP4 as a novel regulator of 5-FU sensitivity in COAD, linking mitochondrial respiration to 5-FU sensitivity in COAD.

A Germinal Center-Associated Microenvironmental Signature Reflects Malignant Phenotype and Outcome of DLBCL

The DLBCL microenvironment signature scoring system was established using nCounter-based profiling of GC-related microenvironmental genes.

DMS scores stratified DLBCL patients with different prognosis independently of existing prognostic models.

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy, with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin (COO), genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using the nCounter-based gene expression profiling of untreated DLBCL tissues, we assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.

Stromal-AR influences the growth of epithelial cells in the development of benign prostate hyperplasia

Activation of epithelial-AR signaling is identified as the major cause of hyperproliferation of the cells during benign and malignant prostate conditions. However, the contribution of stromal-AR is also precarious due to its secretory actions that contribute to the progression of benign and malignant tumors. The present study was aimed to understand the influence of stromal-AR mediated actions on epithelial cells during BPH condition. The secretome (conditioned media-CM) was collected from AR agonist (testosterone-propionate-TP) and antagonist (Nilutamide-Nil) treated BPH patient-derived stromal cells and exposed to BPH epithelial cells. Epithelial cells exhibited increased cell proliferation with the treatment of CM derived from TP-treated stromal cells (TP-CM) but did not support the clonogenic growth of BPH epithelial cells. However, CM derived from Nil-treated stromal cells (Nil-CM) depicted delayed and aggressive BPH epithelial cell proliferation with increased clonogenicity of BPH epithelial cells. Further, decreased AR levels with increased cMyc transcripts and pAkt levels also validated the clonogenic transformation under the paracrine influence of inhibition of stromal-AR. Moreover, the CM of stromal-AR activation imparted positive regulation of basal/progenitor pool through LGR4, β-Catenin, and ΔNP63α expression. Hence, the present study highlighted the restricted disease progression and retains the basal/progenitor state of BPH epithelial cells through the activation of stromal-AR. On the contrary, AR-independent aggressive BPH epithelial cell growth due to paracrine action of loss stromal-AR directs us to reform AR pertaining treatment regimes for better clinical outcomes.

Construction and Validation of a 13-Gene Signature for Prognosis Prediction in Medulloblastoma

Background: Recent studies have identified several molecular subgroups of medulloblastoma associated with distinct clinical outcomes; however, no robust gene signature has been established for prognosis prediction. Our objective was to construct a robust gene signature-based model to predict the prognosis of patients with medulloblastoma.

Methods: Expression data of medulloblastomas were acquired from the Gene Expression Omnibus (GSE85217, n = 763; GSE37418, n = 76). To identify genes associated with overall survival (OS), we performed univariate survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. A risk score model was constructed based on selected genes and was validated using multiple datasets. Differentially expressed genes (DEGs) between the risk groups were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein–protein interaction (PPI) analyses were performed. Network modules and hub genes were identified using Cytoscape. Furthermore, tumor microenvironment (TME) was evaluated using ESTIMATE algorithm. Tumor-infiltrating immune cells (TIICs) were inferred using CIBERSORTx.

Results: A 13-gene model was constructed and validated. Patients classified as high-risk group had significantly worse OS than those as low-risk group (Training set: p < 0.0001; Validation set 1: p < 0.0001; Validation set 2: p = 0.00052). The area under the curve (AUC) of the receiver operating characteristic (ROC) analysis indicated a good performance in predicting 1-, 3-, and 5-year OS in all datasets. Multivariate analysis integrating clinical factors demonstrated that the risk score was an independent predictor for the OS (validation set 1: p = 0.001, validation set 2: p = 0.004). We then identified 265 DEGs between risk groups and PPI analysis predicted modules that were highly related to central nervous system and embryonic development. The risk score was significantly correlated with programmed death-ligand 1 (PD-L1) expression (p < 0.001), as well as immune score (p = 0.035), stromal score (p = 0.010), and tumor purity (p = 0.010) in Group 4 medulloblastomas. Correlations between the 13-gene signature and the TIICs in Sonic hedgehog and Group 4 medulloblastomas were revealed.

Conclusion: Our study constructed and validated a robust 13-gene signature model estimating the prognosis of medulloblastoma patients. We also revealed genes and pathways that may be related to the development and prognosis of medulloblastoma, which might provide candidate targets for future investigation.

FKBP4 is a malignant indicator in luminal A subtype of breast cancer

Purpose: FKBP4 is a member of the immunophilin protein family, which plays a role in immunoregulation and basic cellular processes involving protein folding and trafficking associated with HSP90. However, the relationship between abnormal expression of FKBP4 and clinical outcome in luminal A subtype breast cancer (LABC) patients remains to be elucidated.

Methods: Oncomine, bc-GenExMiner and HPA database were used for data mining and analyzing FKBP4 and its co-expressed genes. GEPIA database was used for screening co-expressed genes of FKBP4.

Results: For the first time, we found that higher FKBP4 expression correlated with LABC patients and worse survival. Moreover, the upregulated co-expressed genes of FKBP4 were assessed to be significantly correlated with worse survival in LABC, and might be involved in the biological role of FKBP4.

Conclusion: The expression status of FKBP4 is a significant prognostic indicator and a potential drug target for LABC.

Multi-omics Biomarker Pipeline Reveals Elevated Levels of Protein-glutamine Gamma-glutamyltransferase 4 in Seminal Plasma of Prostate Cancer Patients

Seminal plasma, because of its proximity to prostate, is a promising fluid for biomarker discovery and noninvasive diagnostics. In this study, we investigated if seminal plasma proteins could increase diagnostic specificity of detecting primary prostate cancer and discriminate between high- and low-grade cancers. To select 147 most promising biomarker candidates, we combined proteins identified through five independent experimental or data mining approaches: tissue transcriptomics, seminal plasma proteomics, cell line secretomics, tissue specificity, and androgen regulation. A rigorous biomarker development pipeline based on selected reaction monitoring assays was designed to evaluate the most promising candidates. As a result, we qualified 76, and verified 19 proteins in seminal plasma of 67 negative biopsy and 152 prostate cancer patients. Verification revealed a prostate-specific, secreted and androgen-regulated protein-glutamine gamma-glutamyltransferase 4 (TGM4), which predicted prostate cancer on biopsy and outperformed age and serum Prostate-Specific Antigen (PSA). A machine-learning approach for data analysis provided improved multi-marker combinations for diagnosis and prognosis. In the independent verification set measured by an in-house immunoassay, TGM4 protein was upregulated 3.7-fold (p = 0.006) and revealed AUC = 0.66 for detecting prostate cancer on biopsy for patients with serum PSA ≥4 ng/ml and age ≥50. Very low levels of TGM4 (120 pg/ml) were detected in blood serum. Collectively, our study demonstrated rigorous evaluation of one of the remaining and not well-explored prostate-specific proteins within the medium-abundance proteome of seminal plasma. Performance of TGM4 warrants its further investigation within the distinct genomic subtypes and evaluation for the inclusion into emerging multi-biomarker panels.

Prostate volume index and prostatic chronic inflammation predicted low tumor load in 945 patients at baseline prostate biopsy

PURPOSE

To assess associations of prostate volume index (PVI), defined as the ratio of the volume of the central transition zone to the volume of the peripheral zone of the prostate and prostatic chronic inflammation (PCI) as predictors of tumor load by number of positive cores (PC) in patients undergoing baseline random biopsies.

METHODS

Parameters evaluated included age, PSA, total prostate volume, PSA density, digital rectal exam, PVI, and PCI. All patients underwent standard transperineal random biopsies. Tumor load was evaluated as absent (no PC), limited (1-3 PC), and extensive (more than 3 PC). The association of factors with the risk of tumor load was evaluated by the multinomial logistic regression model.

RESULTS

The study evaluated 945 patients. Cancer PC were detected in 477 (507%) cases of whom 207 (43.4%) had limited tumor load and 270 (56.6%) had extensive tumor load. Among other factors, comparing patients with limited tumor load with negative cases, PVI [odds ratio, OR = 0.521, 95% confidence interval (CI) 0.330-0.824; p < 0.005] and PCI (OR = 0.289, 95% CI 0.180-0.466; p < 0.0001) were inversely associated with the PCA risk. Comparing patients with extensive tumor load with negative patients, PVI (OR = 0.579, 95% CI 0.356-0.944; p = 0.028), and PCI (OR = 0.150, 95% CI 0.085-0.265; p < 0.0001), predicted PCA risk. Comparing extensive tumor load with limited tumor load patients, PVI and PCI did not show any association with the tumor load.

CONCLUSIONS

Increased PVI and the presence of PCI decreased the risk of increased tumor load and associated with less aggressive prostate cancer biology in patients at baseline random biopsies.