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

Bhowal, Ankur; Majumder, Subhadipa; Ghosh, S. K.; Basu, Supratim; Sen, Debrup; Roychowdhury, Susanta; Sengupta, Sanghamitra; Chatterji, Urmi

doi:10.1038/s41598-017-10068-9

Cited by 12 publications

(11 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FKBP4 was found to be associated with major depressive disorder (Binder et al, 2004;Tatro et al, 2009a,b) and might be critical to early steps in neuronal differentiation (Quintá and Galigniana, 2012), chemotropic guidance of neuronal growth cones (Shim et al, 2009), and regulating neuroprotective activities with calcium channels (Ruan et al, 2008). It was also reported in malignancies like prostate cancer (Bhowal et al, 2017;Joshi et al, 2017) and breast cancer (Ostrow et al, 2009). CCNY knockout can inhibit glioma cell proliferation (Xu et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

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 deathligand 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.

show abstract

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The scatterplot shown in Figure 1C depicts genes upregulated in specimens representing poor (relapsed) vs favorable (disease-free) outcomes. Among genes upregulated in patients with poor prognosis (genes depicted in the right upper area in Figure 1C ) were those related to cell proliferation, including MYC and its targets: FKBP4 , 26 SRM , 27 and PAICS . 28 All 4 of these genes were expressed at high levels in DLBCL cell lines relative to normal LN samples (supplemental Figure 2A).…”

Section: Resultsmentioning

confidence: 99%

A germinal center–associated microenvironmental signature reflects malignant phenotype and outcome of DLBCL

et al. 2022

View full text Add to dashboard Cite

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, 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 here 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.

show abstract

“…A growing body of studies observed that FKBP4 expression was also upregulated in different types of cancers, e.g., head and neck cancer, prostate cancer, glioblastoma, ovarian cancer, colon cancer and so forth [3,6,[18][19][20][21][22]. Particularly, data from Yang's study showed that FKBP4 was significantly upregulated in majority of BC cell lines [5], but its expression status and prognostic merit in LABC still remains unclear.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 12 publications

References 48 publications

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

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

A germinal center–associated microenvironmental signature reflects malignant phenotype and outcome of DLBCL

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

Contact Info

Product

Resources

About