Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer

Alwadi, Diaaidden; Felty, Quentin; Yoo, Changwon; Roy, Deodutta; Deoraj, Alok

doi:10.3390/ijms24043191

Cited by 5 publications

(2 citation statements)

References 113 publications

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“…Our analysis is limited to the human species only. The information about EDCs was obtained from previous literature ( 22 ).…”

Section: Methodsmentioning

confidence: 99%

“…RCB is a highly intuitive indicator for assessing the effectiveness of NAC regimens and has also found utility in predicting clinical outcomes in BC patients ( 22 ). Nevertheless, several studies have indicated that even patients achieving pCR after preoperative or postoperative chemotherapy might not experience complete recovery or local control, with some of these tumors still at risk of recurrence ( 23 – 25 ).…”

Section: Discussmentioning

confidence: 99%

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Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Huang,

Zhang,

Ang

et al. 2023

Front. Endocrinol.

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BackgroundHigh relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.Materials and methodsMicroarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package ‘Limma’. We used the Metascape tool for enrichment analyses, and ‘WGCNA’ was utilized to establish co-expression networks, selecting the soft threshold power with the ‘pickSoftThreshold’ algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package ‘ConsensusCluster Plus’. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.ResultsOur analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60–6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95–0.86), with a C-index of 0.85 (95% CI: 0.81–0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.ConclusionThis study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

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“…Our analysis is limited to the human species only. The information about EDCs was obtained from previous literature ( 22 ).…”

Section: Methodsmentioning

confidence: 99%

Section: Discussmentioning

confidence: 99%

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Huang,

Zhang,

Ang

et al. 2023

Front. Endocrinol.

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Expression and function of NF-Y subunits in cancer

Dolfini,

Gnesutta,

Mantovani

2024

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer

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Identification of biomarkers associated with pathological tumor staging and their utility in the diagnosis and prognosis of prostate cancer

Xu,

Shi,

Liu

et al. 2024

Laboratory Medicine

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Objective Pathological tumor (pT) staging plays a crucial role in prostate cancer (PCa) diagnosis. This study aimed to identify pT stage-associated biomarkers and explored their utility in PCa prognosis. Methods GSE69223 was used to identify potential targets differentially expressed between level 2 of pT staging (pT2) and level 3 of pT staging (pT3). Quantitative reverse transcriptase–polymerase chain reaction and immunohistochemistry were performed on tissues from patients with PCa to screen the pT stage-associated targets and to explore the prognostic value of these targets in PCa. Results CENPI and SLC38A11 were most significantly upregulated, whereas ANO6 and KANK2 were mostly decreased in pT3 tumors compared with pT2 staging. ANO6 levels were negatively associated with preoperative prostate-specific antigen (PSA) levels, lymph node staging (N staging), Gleason score, and overall survival (OS); CENPI was positively associated with preoperative PSA levels, N staging, and OS, but was not associated with the Gleason score; SLC38A11 and KANK2 were not associated with OS. ANO6 and KANK2 were correlated with neutrophil markers, whereas CENPI was correlated with macrophage M2 types. Conclusion We identified 4 reliable PCa biomarkers associated with pT staging that would be valuable for diagnosing and determining PCa prognosis.

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Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer

Cited by 5 publications

References 113 publications

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Expression and function of NF-Y subunits in cancer

Identification of biomarkers associated with pathological tumor staging and their utility in the diagnosis and prognosis of prostate cancer

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