Identification of fluorescence in situ hybridization assay markers for prediction of disease progression in prostate cancer patients on active surveillance

Identification of biomarkers for early diagnosis of Parkinson's disease by multi-omics joint analysis

Objective

The purpose of this study is to identify the biomarkers for early diagnosis of Parkinson's disease (PD) by multi-omics joint analysis, so as to identify the biomarkers for early diagnosis of PD, and to help clinicians make early diagnosis and treatment.

Methods

In this study, mice are taken as the study subjects. The model of PD mice is established, and then lymphocyte, striatum, substantia nigra protein and proteolysis are extracted. After that, the experiments of protein imprinting and 4¹⁸O labeling are carried out. Mass Spectrometry (MS) analysis technology is mainly used to study proteomics and to analyze the quantitative and qualitative situation of differential proteins in striatum, substantia nigra protein and lymphocyte. By this method, biomarkers for early diagnosis of PD are analyzed and identified.

Results

The biomarkers of Parkinson's early onset are related to the same quantitative differential expression of lymphocyte, striatum, substantia nigra protein, lymphocyte and substantia nigra.

Conclusion

This experimental method can analyze and identify the biomarkers of early diagnosis of PD, help to explore the pathophysiology and pathogenesis of PD, effectively help clinicians make timely diagnosis in advance, and improve the prevention and treatment effect of the disease.

Identification of Myoferlin Expression for Prediction of Subsequent Primary Malignancy in Patients With Clear Cell Renal Cell Carcinoma

BACKGROUND/AIM

Multiple primary malignant tumors are common in patients with renal cell carcinoma. However, reports on the factors that can identify patients with a risk for subsequent primary malignancies have been lacking. This study aimed to investigate whether myoferlin expression can be used as a potential marker to predict subsequent primary malignancies in patients with clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

We evaluated the relationship of subsequent primary malignancies with clinicopathological factors and myoferlin expression in 152 patients with ccRCC, and we analyzed the strength of the association with myoferlin expression.

RESULTS

The development of subsequent primary malignancies exhibited significant correlation with patient age (p=0.029), sex (p=0.015), T stage (p<0.001), and myoferlin expression (p=0.017). Furthermore, myoferlin hyperexpression was determined as an independent risk factor for developing a subsequent primary malignant tumor in patients with ccRCC (odds ratio(OR), 2.485, 95% Confidence Interval(CI)=1.052-5.870, p=0.038).

CONCLUSION

Myoferlin hyperexpression can be a useful marker for predicting the development of subsequent primary malignancies in patients with ccRCC.

Molecular Biomarkers in Localized Prostate Cancer: ASCO Guideline

PURPOSE

This guideline provides recommendations for available tissue-based prostate cancer biomarkers geared toward patient selection for active surveillance, identification of clinically significant disease, choice of postprostatectomy adjuvant versus salvage radiotherapy, and to address emerging questions such as the relative value of tissue biomarkers compared with magnetic resonance imaging.

METHODS

An ASCO multidisciplinary Expert Panel, with representatives from the European Association of Urology, American Urological Association, and the College of American Pathologists, conducted a systematic literature review of localized prostate cancer biomarker studies between January 2013 and January 2019. Numerous tissue-based molecular biomarkers were evaluated for their prognostic capabilities and potential for improving management decisions. Here, the Panel makes recommendations regarding the clinical use and indications of these biomarkers.

RESULTS

Of 555 studies identified, 77 were selected for inclusion plus 32 additional references selected by the Expert Panel. Few biomarkers had rigorous testing involving multiple cohorts and only 5 of these tests are commercially available currently: Oncotype Dx Prostate, Prolaris, Decipher, Decipher PORTOS, and ProMark. With various degrees of value and validation, multiple biomarkers have been shown to refine risk stratification and can be considered for select men to improve management decisions. There is a paucity of prospective studies assessing short- and long-term outcomes of patients when these markers are integrated into clinical decision making.

RECOMMENDATIONS

Tissue-based molecular biomarkers (evaluating the sample with the highest volume of the highest Gleason pattern) may improve risk stratification when added to standard clinical parameters, but the Expert Panel endorses their use only in situations in which the assay results, when considered as a whole with routine clinical factors, are likely to affect a clinical decision. These assays are not recommended for routine use as they have not been prospectively tested or shown to improve long-term outcomes-for example, quality of life, need for treatment, or survival. Additional information is available at www.asco.org/genitourinary-cancer-guidelines.

Metastatic risk stratification of clear cell renal cell carcinoma patients based on genomic aberrations

Prognostic markers for the definition of the individual metastatic risk in renal cell carcinoma are still missing. The aim of our study was to establish a total number of specific aberrations (TNSA) genetic score as a new prognostic test for metastatic risk evaluation. Fluorescence in situ hybridization (FISH) was performed on isolated cell nuclei of 100 ccRCCs (50 M1/50 M0) and 100 FFPE sections (second cohort, 32 M1/68 M0). For each chromosomal region (1q21.3, 7q36.3, 9p21.3p24.1, 20q11.21q13.32) cut-off values were determined by receiver-operator curve (ROC)-curve analysis. TNSA was calculated based on the dichotomized specific CNVs. The prognostic significance of CNVs was proven by Cox and logistic regression. TNSA was the best predictor of metastasis and recurrence free survival in both cohorts. We derived an algorithm for risk stratification by combining TNSA and T-category, which increased the prognostic accuracy to 87% (specificity = 86%, sensitivity = 88%). This model divides patients into two risk groups with significantly different RFS, CSS, and OS (P = 3.8×10^-5 , P = 5×10^-6 and P = 3.57×10^-8 respectively). The genetic risk model was superior to Leibovich score and was able to identify patients with metachronous metastatic spread which were incorrectly classified as "low" or "intermediate risk." We present a new tool for individual risk stratification by combining genetic alterations with clinico-pathologic parameters. Interphase FISH proves to be a dependable method for prognostic evaluation in primary tumor tissue on isolated cell nuclei as well as on FFPE sections. Especially in organ-confined tumors the genetic score seems to be an important tool to identify patients at high risk for metastatic disease.