Integrated analysis identifies microRNA-195 as a suppressor of Hippo-YAP pathway in colorectal cancer

Figure S2. KEGG cell signaling pathway was shown for HIPPO pathway. The most significantly enriched by the predicted targets of miR-195 (P = 6.47E-05). Red frame shows the predicted miR-195 targets. (TIF 83 kb

Identification of novel targets for multiple myeloma through integrative approach with Monte Carlo cross-validation analysis

More than one pathway is involved in disease development and progression, and two or more pathways may be interconnected to further affect the disease onset, as functional proteins participate in multiple pathways. Thus, identifying cross-talk among pathways is necessary to understand the molecular mechanisms of multiple myeloma (MM). Based on this, this paper looked at extracting potential pathway cross-talk in MM through an integrative approach using Monte Carlo cross-validation analysis. The gene expression library of MM (accession number: GSE6477) was downloaded from the Gene Expression Omnibus (GEO) database. The integrative approach was then used to identify potential pathway cross-talk, and included four steps: Firstly, differential expression analysis was conducted to identify differentially expressed genes (DEGs). Secondly, the DEGs obtained were mapped to the pathways downloaded from an ingenuity pathways analysis (IPA), to reveal the underlying relationship between the DEGs and pathways enriched by these DEGs. A subset of pathways enriched by the DEGs was then obtained. Thirdly, a discriminating score (DS) value for each paired pathway was computed. Lastly, random forest (RF) classification was used to identify the paired pathways based on area under the curve (AUC) and Monte Carlo cross-validation, which was repeated 50 times to explore the best paired pathways. These paired pathways were tested with another independently published MM microarray data (GSE85837), using in silico validation. Overall, 60 DEGs and 19 differential pathways enriched by DEGs were extracted. Each pathway was sorted based on their AUC values. The paired pathways, inhibition of matrix metalloproteases and EIF2 signaling pathway, indicated the best AUC value of 1.000. Paired pathways consisting of IL-8 and EIF2 signaling pathways with higher AUC of 0.975, were involved in 7 runs. Furthermore, it was validated consistently in separate microarray data sets (GSE85837). Paired pathways (inhibition of matrix metalloproteases and EIF2 signaling, IL-8 signaling and EIF2 signaling) exhibited the best AUC values and higher frequency of validation. Two paired pathways (inhibition of matrix metalloproteases and EIF2 signaling, IL-8 signaling and EIF2 signaling) were used to accurately classify MM and control samples. These paired pathways may be potential bio-signatures for diagnosis and management of MM

Table_1_PFDN2 promotes cell cycle progression via the hnRNPD-MYBL2 axis in gastric cancer.xlsx

Gastric cancer (GC) is a major health burden worldwide, but our understanding of GC is limited, and the prognosis is poor. Novel therapeutic strategies and biomarkers are urgently needed to improve GC patient outcomes. Previously, we identified PFDN2 as a novel key gene in gastric cancer based on its differential expression between cancer and normal tissues. However, the role and underlying mechanisms of PFDN2 in GC remain elusive. In this article, we demonstrated that PFDN2 is highly expressed in GC and that upregulation of PFDN2 is associated with the progression of GC. We further found that PFDN2 could promote cell cycle progression by promoting MYBL2 expression. Mechanistically, we demonstrated that PFDN2 could upregulate MYBL2 expression by facilitating the nuclear translocation of hnRNPD, and thus promoting MYBL2 transcriptional program. In conclusion, we found that PFDN2 promotes cell cycle progression via the hnRNPD-MYBL2 axis and may serve as a potential biomarker and therapeutic target for GC.</p

Table_2_PFDN2 promotes cell cycle progression via the hnRNPD-MYBL2 axis in gastric cancer.xlsx

Gastric cancer (GC) is a major health burden worldwide, but our understanding of GC is limited, and the prognosis is poor. Novel therapeutic strategies and biomarkers are urgently needed to improve GC patient outcomes. Previously, we identified PFDN2 as a novel key gene in gastric cancer based on its differential expression between cancer and normal tissues. However, the role and underlying mechanisms of PFDN2 in GC remain elusive. In this article, we demonstrated that PFDN2 is highly expressed in GC and that upregulation of PFDN2 is associated with the progression of GC. We further found that PFDN2 could promote cell cycle progression by promoting MYBL2 expression. Mechanistically, we demonstrated that PFDN2 could upregulate MYBL2 expression by facilitating the nuclear translocation of hnRNPD, and thus promoting MYBL2 transcriptional program. In conclusion, we found that PFDN2 promotes cell cycle progression via the hnRNPD-MYBL2 axis and may serve as a potential biomarker and therapeutic target for GC.</p