Background:For lung adenocarcinoma (LUAD) patients receiving platinum-based adjuvant chemotherapy (ACT), predictive signatures extracted from survival data solely are not directly associated with platinum response. Another limitation of reported signatures, commonly based on risk scores summarised from gene expressions, is that they could not be applied directly to samples measured by different laboratories due to experimental batch effects.Methods:Using 60 samples of LUAD patients receiving platinum-based ACT in TCGA, we pre-selected gene pairs whose within-samples relative expression orderings (REOs) were significantly associated with both pathological response and 5-year survival, from which we selected an optimal signature whose within-samples REOs could identify responders with improved 5-year survival rate.Results:A predictive signature consisting of three gene pairs was developed. In an independent data set integrated from five small data sets, the predicted responders had a significantly higher 5-year survival rate than the predicted non-responders if and only if they received platinum-based ACT (log-rank P=0.0006). The predicted responders showed a 22% absolute benefit of platinum-based ACT in 5-year survival rate compared with untreated patients (log-rank P=0.0019).Conclusions:The REO-based signature can individually predict response to platinum-based ACT with concordant survival benefit directly for LUAD samples measured by different laboratories.
Background: Glioma is one of the most widely diagnosed malignancies worldwide. It has been reported that long noncoding RNAs (lncRNAs) are participators in the tumorgenesis of cancers. Nevertheless, the role and function of lncRNA SNHG17 among glioma is unclear.Methods: RT-qPCR revealed SNHG17, YY1, miR-506-3p, CTNNB1 expression among glioma cells. CCK-8, colony formation, EdU, flow cytometry, TUNEL and western blot assays revealed the function of SNHG17 in glioma. RIP uncovered SNHG17, miR-506-3p and CTNNB1 enrichment in RISC complex. Luciferase reporter assays and RNA pull down revealed interaction of miR-506-3p with SNHG17 and CTNNB1.Results: SNHG17 expression was up-regulated in glioma tissues and cells. SNHG17 silence attenuated cell proliferation and promoted apoptosis and repressed tumor growth. Moreover, SNHG17 was up-regulated by transcription factor YY1. Mechanistically, SNHG17 activated Wnt/β-catenin signaling pathway in glioma. CTNNB1 was referred to as the mRNA of β-catenin, we validated that SNHG17 bound to miR-506-3p to induce CTNNB1 and activate Wnt/β-catenin signaling pathway. Rescue experiments indicated that CTNNB1 overexpression abolished the inhibitory effects of SNHG7 inhibition on glioma progression.
Conclusions:The findings that YY1-induced SNHG17 facilitated the glioma progression through targeting miR-506-3p/CTNNB1 axis to activate Wnt/β-catenin signaling pathway offered a brand-new prospects to molecular-targeted treatment for glioma.
Acupuncture combined with Madopar appears, to some extent, to improve clinical effectiveness and safety in the treatment of PD, compared with Madopar alone. This conclusion must be considered cautiously, given the quality of most of the studies included was low. Therefore, more high-quality, multicentre, prospective, RCTs with large sample sizes are needed to further clarify the effect of acupuncture combined with Madopar for PD.
Our laboratory previously reported an individual‐level signature consisting of nine gene pairs, named 9‐GPS. This signature was developed by training on microarray expression data and validated using three independent integrated microarray data sets, with samples of stage I non‐small‐cell lung cancer after complete surgical resection. In this study, we first validated the cross‐platform robustness of 9‐GPS by demonstrating that 9‐GPS could significantly stratify the overall survival of 213 stage I lung adenocarcinoma (LUAD) patients detected with RNA‐sequencing platform in The Cancer Genome Atlas (TCGA; log‐rank P = 0.0318, C‐index = 0.55). Applying 9‐GPS to all the 423 stage I‐IV LUAD samples in TCGA, the predicted high‐risk samples were significantly enriched with clinically diagnosed metastatic samples (Fisher's exact test, P = 0.0015). We further modified the voting rule of 9‐GPS and found that the modified 9‐GPS had a better performance in predicting metastasis states (Fisher's exact test, P < 0.0001). With the aid of the modified 9‐GPS for reclassifying the metastasis states of patients with LUAD, the reclassified metastatic samples presented clearer transcriptional and genomic characteristics compared to the reclassified nonmetastatic samples. Finally, regulator network analysis identified TP53 and IRF1 with frequent genomic aberrations in the reclassified metastatic samples, indicating their key roles in driving tumor metastasis. In conclusion, 9‐GPS is a robust signature for identifying early‐stage LUAD patients with potential occult metastasis. This occult metastasis prediction was associated with clear transcriptional and genomic characteristics as well as the clinical diagnoses.
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