Assessment of micro RNAs expression in leukemic cells as prognostic markers in chronic lymphocytic leukemia: micro RNAs can predict survival in a course of the disease

miR-221/222 as biomarkers and targets for therapeutic intervention on cancer and other diseases: A systematic review

Among deregulated microRNAs (miRs) in human malignancies, miR-221 has been widely investigated for its oncogenic role and as a promising biomarker. Moreover, recent evidence suggests miR-221 as a fine-tuner of chronic liver injury and inflammation-related events. Available information also supports the potential of miR-221 silencing as promising therapeutic intervention. In this systematic review, we selected papers from the principal databases (PubMed, MedLine, Medscape, ASCO, ESMO) between January 2012 and December 2020, using the keywords "miR-221" and the specific keywords related to the most important hematologic and solid malignancies, and some non-malignant diseases, to define and characterize deregulated miR-221 as a valuable therapeutic target in the modern vision of molecular medicine. We found a major role of miR-221 in this view.

Interphase fluorescence in situ hybridization analysis of CD19-selected cells: Utility in detecting disease in post-therapy samples of B-cell neoplasms

Context

The detection of low‐level persistent or relapsed B‐cell neoplasms, particularly post‐therapy, can be challenging, often requiring multiple testing modalities.

Objective

Here we investigate the utility of CD19‐based selection of neoplastic B‐cells (CD19S) as an enrichment strategy to improve the detection rate of cytogenetic abnormalities in post‐therapy samples of B‐cell neoplasms, especially those with low‐level disease.

Design

In a cohort largely comprised of post‐therapy B‐ALL and CLL samples, we performed fluorescence in situ hybridization (FISH) analysis on CD19‐selected cells (CD19S FISH) in 128 specimens from 88 patients, and on non‐selected cells (NS FISH) in a subset of cases. The FISH findings were compared with the concurrent flow cytometry (FC) results in all samples and molecular analysis in a subset.

Results

CD19S FISH was able to detect cytogenetic aberrations in 86.0% of post‐therapy samples with evidence of disease as determined by routine or MRD FC, compared to 59.1% of samples by NS FISH. CD19S FISH detected significantly higher percentages of positive cells compared to NS FISH (p < 0.001). Importantly, CD19S FISH enabled the detection of emergent subclones (clonal evolution) associated with poor prognosis.

Conclusions

CD19S FISH can be useful in daily diagnostic practice. Compared to NS FISH, CD19S FISH is quantitatively and qualitatively superior for the detection of cytogenetic aberrations in B‐cell neoplasms, which are important for risk stratification and optimal management of patients with B‐cell neoplasms, especially in the relapsed setting. Although CD19S FISH has a diagnostic sensitivity inferior to that of MRD FC, the sensitivity of this modality is comparable to routine FC for the evaluation of low‐level disease in the post‐therapy setting. Moreover, CD19S samples are invaluable for additional molecular and genetic analyses.

Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis

BACKGROUND

Chronic lymphocytic leukaemia (CLL) is the most common cancer of the lymphatic system in Western countries. Several clinical and biological factors for CLL have been identified. However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict long-term outcome in people newly-diagnosed with CLL.

OBJECTIVES

To identify, describe and appraise all prognostic models developed to predict overall survival (OS), progression-free survival (PFS) or treatment-free survival (TFS) in newly-diagnosed (previously untreated) adults with CLL, and meta-analyse their predictive performances.

SEARCH METHODS

We searched MEDLINE (from January 1950 to June 2019 via Ovid), Embase (from 1974 to June 2019) and registries of ongoing trials (to 5 March 2020) for development and validation studies of prognostic models for untreated adults with CLL. In addition, we screened the reference lists and citation indices of included studies.

SELECTION CRITERIA

We included all prognostic models developed for CLL which predict OS, PFS, or TFS, provided they combined prognostic factors known before treatment initiation, and any studies that tested the performance of these models in individuals other than the ones included in model development (i.e. 'external model validation studies'). We included studies of adults with confirmed B-cell CLL who had not received treatment prior to the start of the study. We did not restrict the search based on study design.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form to collect information based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Independent pairs of review authors screened references, extracted data and assessed risk of bias according to the Prediction model Risk Of Bias ASsessment Tool (PROBAST). For models that were externally validated at least three times, we aimed to perform a quantitative meta-analysis of their predictive performance, notably their calibration (proportion of people predicted to experience the outcome who do so) and discrimination (ability to differentiate between people with and without the event) using a random-effects model. When a model categorised individuals into risk categories, we pooled outcome frequencies per risk group (low, intermediate, high and very high). We did not apply GRADE as guidance is not yet available for reviews of prognostic models.

MAIN RESULTS

From 52 eligible studies, we identified 12 externally validated models: six were developed for OS, one for PFS and five for TFS. In general, reporting of the studies was poor, especially predictive performance measures for calibration and discrimination; but also basic information, such as eligibility criteria and the recruitment period of participants was often missing. We rated almost all studies at high or unclear risk of bias according to PROBAST. Overall, the applicability of the models and their validation studies was low or unclear; the most common reasons were inappropriate handling of missing data and serious reporting deficiencies concerning eligibility criteria, recruitment period, observation time and prediction performance measures. We report the results for three models predicting OS, which had available data from more than three external validation studies: CLL International Prognostic Index (CLL-IPI) This score includes five prognostic factors: age, clinical stage, IgHV mutational status, B2-microglobulin and TP53 status. Calibration: for the low-, intermediate- and high-risk groups, the pooled five-year survival per risk group from validation studies corresponded to the frequencies observed in the model development study. In the very high-risk group, predicted survival from CLL-IPI was lower than observed from external validation studies. Discrimination: the pooled c-statistic of seven external validation studies (3307 participants, 917 events) was 0.72 (95% confidence interval (CI) 0.67 to 0.77). The 95% prediction interval (PI) of this model for the c-statistic, which describes the expected interval for the model's discriminative ability in a new external validation study, ranged from 0.59 to 0.83. Barcelona-Brno score Aimed at simplifying the CLL-IPI, this score includes three prognostic factors: IgHV mutational status, del(17p) and del(11q). Calibration: for the low- and intermediate-risk group, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of four external validation studies (1755 participants, 416 events) was 0.64 (95% CI 0.60 to 0.67); 95% PI 0.59 to 0.68. MDACC 2007 index score The authors presented two versions of this model including six prognostic factors to predict OS: age, B2-microglobulin, absolute lymphocyte count, gender, clinical stage and number of nodal groups. Only one validation study was available for the more comprehensive version of the model, a formula with a nomogram, while seven studies (5127 participants, 994 events) validated the simplified version of the model, the index score. Calibration: for the low- and intermediate-risk groups, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of the seven external validation studies for the index score was 0.65 (95% CI 0.60 to 0.70); 95% PI 0.51 to 0.77.

AUTHORS' CONCLUSIONS

Despite the large number of published studies of prognostic models for OS, PFS or TFS for newly-diagnosed, untreated adults with CLL, only a minority of these (N = 12) have been externally validated for their respective primary outcome. Three models have undergone sufficient external validation to enable meta-analysis of the model's ability to predict survival outcomes. Lack of reporting prevented us from summarising calibration as recommended. Of the three models, the CLL-IPI shows the best discrimination, despite overestimation. However, performance of the models may change for individuals with CLL who receive improved treatment options, as the models included in this review were tested mostly on retrospective cohorts receiving a traditional treatment regimen. In conclusion, this review shows a clear need to improve the conducting and reporting of both prognostic model development and external validation studies. For prognostic models to be used as tools in clinical practice, the development of the models (and their subsequent validation studies) should adapt to include the latest therapy options to accurately predict performance. Adaptations should be timely.

Associations of high expression of miR-106b-5p detected from FFPE sample with poor prognosis of RCC patients

OBJECTIVE

The present study aims to determine the association of microRNA-106b-5p (miR-106b-5p) expression with the clinicopathological features and prognosis of renal cell carcinoma (RCC).

PATENTS AND METHODS

The formalin-fixed paraffin-embedded(FFPE) Tumor tissues were collected from 284 RCC patients. The expression of miR-106b-5p was examined by Reverse Transcription Real-time Quantitative Polymerase Chain Reaction (RT-qPCR), followed by correlation analysis with clinicopathological features and prognosis. Patient survival analysis was determined by the Kaplan-Meier method using the log-rank test was used for patient survival analysis, and the univariate and multivariate analysis was determined by a Cox's regression model.

RESULTS

Kaplan-Meier analysis indicated that patients with high miR-106b-5p expression showed a significantly shorter overall survival, compared with patients with low miR-106b-5p expression (p = 0.001). Univariate and multivariate analysis considered miR-106b-5p expression as an independent risk factor for predicting the prognosis of RCC patients. No significant evident showed that the expression level of miR-106b was related to gender, age, tumor size or tumor stage. Also, the results above were verified by analyzing the data of 506 cases from The Cancer Genome Atlas database (TCGA).

CONCLUSIONS

The results pointed out that the high expression of miR-106b-5p serves as an independent factor for predicting the worse prognosis of RCC patients.

Assessment of microRNA expression in leukemic cells as predictors of sensitivity to purine nucleoside analogs, fludarabine and cladribine, in chronic lymphocytic leukemia patients

Background: Great progress has been achieved lately in the therapy for chronic lymphocytic leukemia (CLL), one of the most frequently diagnosed adult leukemias. New classes of drugs, such as kinase inhibitors and BCL-2 protein antagonists, have been approved for treatment of CLL patients. Despite the abovementioned therapies the disease can still be effectively treated with purine nucleoside analogs (PNA). However, some patients, for example, those with TP53 gene abnormalities, become resistant, and the other factors involved in the therapy resistance are still being investigated. This study was aimed at analyzing the possible role of microRNAs as markers predicting the outcome of chemotherapy based on PNA – fludarabine and cladribine in CLL patients.

Methods: The expression of miR-21, miR-34a, miR-181a and miR-221 in previously separated leukemic cells was assessed with the use of qRQ-PCR technique at the moment of diagnosis in 40 CLL patients. In turn, apoptosis induced by fludarabine and cladribine in 24-hour cell culture was evaluated by determining the increase in the percentage of apoptotic cells of CD5+/CD19+/Cas3+ phenotype, using a flow cytometry method. Nine of the 40 studied subjects were treated with fludarabine-based regimens and were analyzed with regards to in vivo response to PNA.

Results: We detected a significantly higher PNA-induced apoptosis rate in patients with high miR-34a expression in comparison to low expression ones. Interestingly, such differences were detected particularly in standard cytogenetic patients.

Conclusions: These results may prove an important role of miR-34a expression as a predictor of apoptosis, even in cases when other risk factors like cytogenetic abnormalities are absent. An assessment of microRNAs expression seems to be useful as an indicator of sensitivity to PNA and may help to predict PNA-based therapy outcome.