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Bladder carcinoma data with clinical risk factors and molecular markers: a cluster analysis.

Redondo-Gonzalez E, de Castro LN, Moreno-Sierra J, Maestro de las Casas ML, Vera-Gonzalez V, Ferrari DG, Corchado JM - Biomed Res Int (2015)

Bottom Line: Clusterings were performed to find groups with clinical, molecular markers, histopathological prognostic factors, and statistics about recurrence, progression, and overall survival of patients with NMIBC.Four groups were found according to tumor sizes, risk of relapse or progression, and biological behavior.Outlier patients were also detected and categorized according to their clinical characters and biological behavior.

View Article: PubMed Central - PubMed

Affiliation: Urology Department, Hospital Clinico San Carlos, Complutense University, Instituto de Investigacion Sanitaria San Carlos (IdISSC), 28040 Madrid, Spain.

ABSTRACT
Bladder cancer occurs in the epithelial lining of the urinary bladder and is amongst the most common types of cancer in humans, killing thousands of people a year. This paper is based on the hypothesis that the use of clinical and histopathological data together with information about the concentration of various molecular markers in patients is useful for the prediction of outcomes and the design of treatments of nonmuscle invasive bladder carcinoma (NMIBC). A population of 45 patients with a new diagnosis of NMIBC was selected. Patients with benign prostatic hyperplasia (BPH), muscle invasive bladder carcinoma (MIBC), carcinoma in situ (CIS), and NMIBC recurrent tumors were not included due to their different clinical behavior. Clinical history was obtained by means of anamnesis and physical examination, and preoperative imaging and urine cytology were carried out for all patients. Then, patients underwent conventional transurethral resection (TURBT) and some proteomic analyses quantified the biomarkers (p53, neu, and EGFR). A postoperative follow-up was performed to detect relapse and progression. Clusterings were performed to find groups with clinical, molecular markers, histopathological prognostic factors, and statistics about recurrence, progression, and overall survival of patients with NMIBC. Four groups were found according to tumor sizes, risk of relapse or progression, and biological behavior. Outlier patients were also detected and categorized according to their clinical characters and biological behavior.

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Related in: MedlinePlus

Hierarchical clustering of the NMIBC patients using the selected variables. (a) Clustering of the whole dataset. (b) Clustering of the dataset after removing patients 13, 26, 30, 35, 37, 38, 44, and 45.
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fig3: Hierarchical clustering of the NMIBC patients using the selected variables. (a) Clustering of the whole dataset. (b) Clustering of the dataset after removing patients 13, 26, 30, 35, 37, 38, 44, and 45.

Mentions: In this last experiment, the goal was to observe if there is any relationship between the molecular markers (proteins neu, EGFR, and p53) and the tumoral tissue of NMIBC. To investigate that, a subset of the variables was selected manually and the clustering algorithm was applied. The following variables were chosen: Age, Gender, Tabaco, Tumor, Multiple, Tam, TAM3CM, ASPESUPE, G, G23, Tnm, GRIES, GRX, Tipoap, p53iha, p53ria, neu, Recidiv, Progres, Nrecidiv, Metas, Muerte, Egfr, Logneu, Superv, Ile, Tprogre, Tmetas, Np53ria, Nneu, Negfr, and Edad70. The patients with missing values (3, 8, 10, 11, 17, 18, 22, 23, 24, 27, 28, 31, and 34) were removed from the dataset. The results are presented in Figure 3. In Figure 3(a) the clustering of the whole dataset is presented, and the presence of eight outliers can be observed: 13, 26, 30, 35, 37, 38, 44, and 45.


Bladder carcinoma data with clinical risk factors and molecular markers: a cluster analysis.

Redondo-Gonzalez E, de Castro LN, Moreno-Sierra J, Maestro de las Casas ML, Vera-Gonzalez V, Ferrari DG, Corchado JM - Biomed Res Int (2015)

Hierarchical clustering of the NMIBC patients using the selected variables. (a) Clustering of the whole dataset. (b) Clustering of the dataset after removing patients 13, 26, 30, 35, 37, 38, 44, and 45.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383273&req=5

fig3: Hierarchical clustering of the NMIBC patients using the selected variables. (a) Clustering of the whole dataset. (b) Clustering of the dataset after removing patients 13, 26, 30, 35, 37, 38, 44, and 45.
Mentions: In this last experiment, the goal was to observe if there is any relationship between the molecular markers (proteins neu, EGFR, and p53) and the tumoral tissue of NMIBC. To investigate that, a subset of the variables was selected manually and the clustering algorithm was applied. The following variables were chosen: Age, Gender, Tabaco, Tumor, Multiple, Tam, TAM3CM, ASPESUPE, G, G23, Tnm, GRIES, GRX, Tipoap, p53iha, p53ria, neu, Recidiv, Progres, Nrecidiv, Metas, Muerte, Egfr, Logneu, Superv, Ile, Tprogre, Tmetas, Np53ria, Nneu, Negfr, and Edad70. The patients with missing values (3, 8, 10, 11, 17, 18, 22, 23, 24, 27, 28, 31, and 34) were removed from the dataset. The results are presented in Figure 3. In Figure 3(a) the clustering of the whole dataset is presented, and the presence of eight outliers can be observed: 13, 26, 30, 35, 37, 38, 44, and 45.

Bottom Line: Clusterings were performed to find groups with clinical, molecular markers, histopathological prognostic factors, and statistics about recurrence, progression, and overall survival of patients with NMIBC.Four groups were found according to tumor sizes, risk of relapse or progression, and biological behavior.Outlier patients were also detected and categorized according to their clinical characters and biological behavior.

View Article: PubMed Central - PubMed

Affiliation: Urology Department, Hospital Clinico San Carlos, Complutense University, Instituto de Investigacion Sanitaria San Carlos (IdISSC), 28040 Madrid, Spain.

ABSTRACT
Bladder cancer occurs in the epithelial lining of the urinary bladder and is amongst the most common types of cancer in humans, killing thousands of people a year. This paper is based on the hypothesis that the use of clinical and histopathological data together with information about the concentration of various molecular markers in patients is useful for the prediction of outcomes and the design of treatments of nonmuscle invasive bladder carcinoma (NMIBC). A population of 45 patients with a new diagnosis of NMIBC was selected. Patients with benign prostatic hyperplasia (BPH), muscle invasive bladder carcinoma (MIBC), carcinoma in situ (CIS), and NMIBC recurrent tumors were not included due to their different clinical behavior. Clinical history was obtained by means of anamnesis and physical examination, and preoperative imaging and urine cytology were carried out for all patients. Then, patients underwent conventional transurethral resection (TURBT) and some proteomic analyses quantified the biomarkers (p53, neu, and EGFR). A postoperative follow-up was performed to detect relapse and progression. Clusterings were performed to find groups with clinical, molecular markers, histopathological prognostic factors, and statistics about recurrence, progression, and overall survival of patients with NMIBC. Four groups were found according to tumor sizes, risk of relapse or progression, and biological behavior. Outlier patients were also detected and categorized according to their clinical characters and biological behavior.

Show MeSH
Related in: MedlinePlus