Available biomarkers for pancreatic adenocarcinoma (PAC) are inadequate to guide individual patient prognosis or therapy. Therefore, herein we aimed to verify the hypothesis that differences in the expression of KIF11 and KIF14, i.e., molecular motor proteins being primarily implicated in cell division events could account for the differences in the clinical outcome of PAC patients. In-house immunohistochemistry was used to evaluate the protein expressions of KIF11 and KIF14 in PAC, whereas RNA-seq datasets providing transcript expression data were obtained from public sources. IHC and mRNA results were correlated with clinicopathological features and overall survival (OS). Furthermore, the genes co-expressed with KIF11 or KIF14 were predicted and functionally annotated. In our series, malignant ducts displayed more intense but less abundant KIF11 staining than normal-appearing ducts. The former was also true for KIF14, whereas the prevalence of positive staining was similar in tumor and normal adjacent tissues. Based on categorical immunoreactive scores, we found KIF11 and KIF14 to be frequently downregulated or upregulated in PAC cases, respectively, and those with elevated levels of either protein, or both together, were associated with better prognosis. Specifically, we provide the first evidence that KIF11 or KIF14 proteins can robustly discriminate between patients with better and worse OS, independently of other relevant clinical risk factors. In turn, mRNA levels of KIF11 and KIF14 were markedly elevated in tumor tissues compared to normal tissues, and this coincided with adverse prognosis, even after adjusting for multiple confounders. Tumors with low predicted KIF11 or KIF14 expression were seen to have enrichment for circadian clock, whereas those with high levels were enriched for the genomic instability-related gene set. KIF11 and KIF14 were strongly correlated with one another, and CEP55, ASPM, and GAMT were identified as the main hub genes. Importantly, the combined expression of these five genes emerged as the most powerful independent prognostic indicator associated with poor survival outcome compared to classical clinicopathological factors and any marker alone. In conclusion, our study identifies novel prognostic biomarkers for PAC, which await validation.

Genomic instability (GIN) has an important contribution to the pathology of colorectal cancer (CRC). Therefore, we selected mitosis and cytokinesis kinesins, KIF11 and KIF14, as factors of potential clinical and functional value in CRC, as their aberrant expression has been suspected to underlie GIN. We examined the expression and the prognostic and biological significance of KIF11 and KIF14 in CRC via in-house immunohistochemistry on tissue microarrays, public mRNA expression datasets, as well as bioinformatics tools. We found that KIF11 and KIF14 expression, at both the protein and mRNA level, was markedly altered in cancer tissues compared to respective controls, which was reflected in the clinical outcome of CRC patients. Specifically, we provide the first evidence that KIF11 protein and mRNA, KIF14 mRNA, as well as both proteins together, can significantly discriminate between CRC patients with better and worse overall survival independently of other relevant clinical risk factors. The negative prognostic factors for OS were high KIF11 protein, high KIF11 protein + low KIF14 protein, low KIF11 mRNA and low KIF14 mRNA. Functional enrichment analysis revealed that the gene sets related to the cell cycle, DNA replication, DNA repair and recombination, among others, were positively associated with KIF11 or KIF14 expression in CRC tissues. In TCGA cohort, the positive correlations between several measures related to GIN and the expression of KIFs were also demonstrated. In conclusion, our results suggest that CRC patients can be stratified into distinct risk categories by biological and molecular determinants, such as KIF11 and KIF14 expression and, mechanistically, this is likely attributable to their role in maintaining genome integrity.

The possible application of BRAF-targeted therapy in brain tumors is growing continuously. We have analyzed clinical strategies that address BRAF activation in primary brain tumors and verified current recommendations regarding screening for BRAF mutations. There is preliminary evidence for a range of positive responses in certain brain tumor types harboring the BRAF V600E mutation. National Comprehensive Cancer Network Guidelines for central nervous system cancers recommend screening for the BRAF V600E mutation in pilocytic astrocytoma, pleomorphic xanthoastrocytoma, and ganglioglioma. We suggest additional testing in glioblastomas WHO grade IV below the age of 30 years, especially those with epithelioid features, papillary craniopharyngiomas, and pediatric low-grade astrocytomas. BRAF-targeted therapy should be limited to the setting of a clinical trial. If the patient harboring a V600E mutation does not qualify for a trial, multimodality treatment is recommended. Dual inhibition of both RAF and MEK is expected to provide more potent and durable effects than anti-BRAF monotherapy. First-generation RAF inhibitors should be avoided. Gain-of-function mutations of EGFR and KIAA fusions may compromise BRAF-targeted therapy. BRAF alterations that result in MAPK pathway activation are common events in several types of brain tumors. BRAF V600E mutation emerges as a promising molecular target. The proposed algorithm was designed to help oncologists to provide the best therapeutic options for brain tumor patients.

In the present study, we aimed to assess the selected components of cell cycle machinery, checkpoint, DNA repair, and synthesis, namely RRM2, cyclin F, and SPDL1 in pancreatic adenocarcinomas (PAC) by in-house immunohistochemistry (IHC) and bioinformatic analysis of public datasets, in terms of expression, correlation with clinicopathological parameters, and patient survival. Sixty eight patients with pancreatic ductal adenocarcinoma (PDAC) were included in our cohort study, and IHC was performed on tissue macroarrays. RNA-Seq-based transcriptome data for 177 PACs were retrieved from the Cancer Genome Atlas (TCGA). We found cyclin F, RRM2, and SPDL1 to be overexpressed at both protein and mRNA levels in tumor tissues compared to respective controls. Based on TCGA dataset, we have demonstrated that CCNF, RRM2, and SPDL1 are potent independent prognostic markers for poor overall survival, both by themselves and even more in combination with each other. Furthermore, high CCNF mRNA expression was associated with features of cancer progression. By contrast, overexpression of cyclin F or SPDL1 proteins denoted a good prognosis in PDAC patients; however, in the case of the former protein, the results did not reach statistical significance. Specifically, high levels of SPDL1 protein emerged as the most powerful independent prognostic factor associated with a better outcome. If validated, the CCNF/RRM2/SPDL1 three-gene panel developed in this study, as well as SPDL1 protein, may provide significant clinical implications for the prognosis prediction of PAC patients.

This study aimed to explore the prognostic value of SATB1, SMAD3, and TLR2 expression in non–small-cell lung carcinoma patients with clinical stages I-II. To investigate, we evaluated immunohistochemical staining to each of these markers using tissue sections from 69 patients from our cohort and gene expression data for The Cancer Genome Atlas (TCGA) cohort. We found that, in our cohort, high expression levels of nuclear SATB1ⁿ and SMAD3 were independent prognostic markers for better overall survival (OS) in NSCLC patients. Interestingly, expression of cytoplasmic SATB1^c exhibited a significant but inverse association with survival rate, and it was an independent predictor of unfavorable prognosis. Likewise, TLR2 was a negative outcome biomarker for NSCLC even when adjusting for covariates. Importantly, stratification of NSCLCs with respect to combined expression of the three biomarkers allowed us to identify subgroups of patients with the greatest difference in duration of survival. Specifically, expression profile of SATB1^n-high/SMAD3^high/TLR2^low was associated with the best OS, and it was superior to each single protein alone in predicting patient prognosis. Furthermore, based on the TCGA dataset, we found that overexpression of SATB1 mRNA was significantly associated with better OS, whereas high mRNA levels of SMAD3 and TLR2 with poor OS. In conclusion, the present study identified a set of proteins that may play a significant role in predicting prognosis of NSCLC patients with clinical stages I-II.