This study proposed a deep learning (DL) algorithm to predict survival in patients with colon adenocarcinoma (COAD) based on multi-omics integration. The survival-sensitive model was constructed using an autoencoder for DL implementation based on The Cancer Genome Atlas (TCGA) data of patients with COAD. The autoencoder framework was compared to PCA, NMF, t-SNE, and univariable Cox-PH model for identifying survival-related features. The prognostic robustness of the inferred survival risk groups was validated using three independent confirmation cohorts. Differential expression analysis, Pearson’s correlation analysis, construction of miRNA-target gene network, and function enrichment analysis were performed. Two risk groups with significant survival differences were identified in TCGA set using the autoencoder-based model (log-rank p-value = 5.51e-07). The autoencoder framework showed superior performance compared to PCA, NMF, t-SNE, and the univariable Cox-PH model based on the C-index, log-rank p-value, and Brier score. The robustness of the classification model was successfully verified in three independent validation sets. There were 1271 differentially expressed genes, 10 differentially expressed miRNAs, and 12 hypermethylated genes between the survival risk groups. Among these, miR-133b and its target genes (GNB4, PTPRZ1, RUNX1T1, EPHA7, GPM6A, BICC1, and ADAMTS5) were used to construct a network. These genes were significantly enriched in ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and glucose metabolism-related pathways. The risk subgroups obtained through a multi-omics data integration pipeline using the DL algorithm had good robustness. miR-133b and its target genes could be potential diagnostic markers. The results would assist in elucidating the possible pathogenesis of COAD.

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Accumulating evidence has presented that microRNA-148a/152 (miR-148a/152) acts as the tumor inhibitor in various cancers. In this article, we aimed to probe the inhibition of colon cancer stem cells by miR-148a/152 cluster via regulation of CCT6A. miR-148a/152 and CCT6A expression in colon cancer tissues and cells was detected. The relationship between miR-148a/152 expression and the clinicopathological features of patients with colon cancer was analyzed. Colon cancer stem cells (CD44 + / CD133 + ) were selected and high/low expression of miR-148a/152 plasmids were synthesized to intervene CD44 + / CD133 + colon cancer stem cells to investigate the function of miR-148a/152 in invasion, migration, proliferation, colony formation and apoptosis of cells. The growth status of nude mice was observed to verify the in-vitro results. The relationship between miR-148a/152 and CCT6A was analyzed. CCT6A upregulated and miR-148a/152 downregulated in colon cancer tissues. MiR-148a/152 expression was correlated with tumor node metastasis stage, lymph node metastasis and differentiation degree. Upregulated miR-148a/152 depressed CCT6A expression and restrained invasion and migration ability, colony formation and proliferation, induced cell apoptosis, depressed OCT4, Nanog and SOX2 mRNA expression of colon cancer stem cells, and descended tumor weight and volume in nude mice. CCT6A was a target gene of miR-148a/152. Overexpression of CCT6A protected colon cancer stem cells. Functional studies showed that upregulation of miR-148a/152 can suppress the migration, invasion and proliferation of CD44 + /CD133 + colon cancer stem cells, advance its apoptosis via inhibition of CCT6A expression. Anti-Cancer Drugs 33: e610-e621

An aptasensor was developed on an interdigitated microelectrode (IDME) by current-volt sensing for the diagnosis of ulcerative colitis by detecting the biomarker lipocalin-2. Higher immobilization of the anti-lipocalin-2 aptamer as a probe was achieved by using sodium dodecyl benzenesulfonate-aided zeolite particles. FESEM and FETEM observations revealed that the size of the zeolite particles was <200 nm, and they displayed a uniform distribution and spherical shape. XPS analysis attested the occurrence of Si, Al, and O groups on the zeolite particles. Zeolite particles were immobilized on IDME by a (3-aminopropyl)-trimethoxysilane amine linker, and then, the aptamer as the probe was tethered on the zeolite particles through a biotin-streptavidin strategy assisted by a bifunctional aldehyde linker. Due to the high occupancy of the aptamer and the efficient electric transfer from zeolite particles, higher changes in current can be observed upon interaction of the aptamer with lipocalin-2. The lower detection of lipocalin-2 was noted as 10 pg/mL, with a linear range from 10 pg/mL to 1 μg/mL and a linear regression equation of y=8E−07x+8E−08; R2 = 0.991. Control experiments with complementary aptamer and matrix metalloproteinase-9 indicate the specific detection of lipocalin-2. Furthermore, spiking lipocalin-2 in human serum does not interfere with the identification.