Primary central nervous system lymphoma (PCNSL) is a rare, highly aggressive, extranodal form of non-Hodgkin lymphoma, predominantly diagnosed as primary diffuse large B-cell lymphoma of the central nervous system (CNS DLBCL). Fast and precise diagnosis of PCNSL is critical yet challenging. microRNAs, important regulators in physiology and pathology are potential biomarkers. In 131 patients with CNS DLBCL and with non-malignant brain lesions (n-ML), miR-21, miR-19b and miR-92a, miR-155, miR-196b, miR-let-7b, miR-125b, and miR-9 were examined by RT-qPCR in brain biopsy samples (formalin-fixed paraffin-embedded tissues, FFPET; CNS DLBCL, n = 52; n-ML, n = 42) and cerebrospinal fluid samples (CSF; CNS DLBCL, n = 30; n-ML, n = 23) taken for routine diagnosis. FFPET samples were split into study and validation sets. Significantly higher CSF levels of miR-21, miR-19b, and miR-92a were identified in PCNSL but not in n-ML, and differentiated PCNSL from n-ML with 63.33% sensitivity and 80.77% specificity. In FFPETs, miR-155 and miR-196b were significantly overexpressed and miR-let-7b, miR-125b, and miR-9 were downregulated in PCNSL as compared to n-ML. Combined miR-155 and miR-let-7b expression levels in FFPETs discriminated PCNSL and n-ML with a 97% accuracy. In conclusion, tissue miR-155, miR-196b, miR-9, miR-125b, and miR-let-7b expression profiles differentiate PCNSL from n-ML. PCNSL CSFs and the relevant biopsy samples are characterized by specific, different microRNA profiles. A logistic regression model is proposed to discriminate between PCNSL and non-malignant brain lesions. None of the examined microRNAs influenced overall survival of PCNSL patients. Further ongoing developments involve next generation sequencing-based profiling of biopsy and CSF samples.

The diagnosis of primary central nervous system (CNS) lymphoma, which is predominantly of the diffuse large B-cell lymphoma type (CNS DLBCL), is challenging. MicroRNAs (miRs) are gene expression-regulating non-coding RNAs that are potential biomarkers. We aimed to distinguish miR expression patterns differentiating CNS DLBCL and non-malignant CNS diseases with tumor presentation (n-ML). Next generation sequencing-based miR profiling of cerebrospinal fluids (CSFs) and brain tumors was performed. Sample source-specific (CSF vs. brain tumor) miR patterns were revealed. Even so, a set of 17 miRs differentiating CNS DLBCL from n-ML, no matter if assessed in CSF or in a tumor, was identified. Along with the results of pathway analyses, this suggests their pathogenic role in CNS DLBCL. A combination of just four of those miRs (miR-16-5p, miR-21-5p, miR-92a-3p, and miR-423-5p), assessed in CSFs, discriminated CNS DLBCL from n-ML samples with 100% specificity and 67.0% sensitivity. Analyses of paired CSF-tumor samples from patients with CNS DLBCL showed significantly lower CSF levels of miR-26a, and higher CSF levels of miR-15a-5p, miR-15b-5p, miR-19a-3p, miR-106b-3p, miR-221-3p, and miR-423-5p. Noteworthy, the same miRs belonged to the abovementioned set differentiating CNS DLBCL from non-malignant CNS diseases. Our results not only add to the basic knowledge, but also hold significant translational potential.

Molecular alterations in tumor-adjacent tissues have recently been recognized in some types of cancer. This phenomenon has not been studied in endometrial cancer. We aimed to analyze the expression of genes associated with cancer progression and metabolism in primary endometrial cancer samples and the matched tumor-adjacent tissues and in the samples of endometria from cancer-free patients with uterine leiomyomas. Paired samples of tumor-adjacent tissues and primary tumors from 49 patients with endometrial cancer (EC), samples of endometrium from 25 patients with leiomyomas of the uterus, and 4 endometrial cancer cell lines were examined by the RT-qPCR, for MYC, NR5A2, CXCR2, HMGA2, LIN28A, OCT4A, OCT4B, OCT4B1, TWIST1, STK11, SNAI1, and miR-205-5p expression. The expression levels of MYC, NR5A2, SNAI1, TWIST1, and STK11 were significantly higher in tumor-adjacent tissues than in the matched EC samples, and this difference was not influenced by the content of cancer cells in cancer-adjacent tissues. The expression of MYC, NR5A2, and SNAI1 was also higher in EC-adjacent tissues than in samples from cancer-free patients. In addition, the expression of MYC and CXCR2 in the tumor related to non-endometrioid adenocarcinoma and reduced the risk of recurrence, respectively, and higher NR5A2 expression in tumor-adjacent tissue increased the risk of death. In conclusion, tissues proximal to EC present higher levels of some cancer-promoting genes than the matched tumors. Malignant tumor-adjacent tissues carry a diagnostic potential and emerge as new promising target of anticancer therapy.