Background: Cellular senescence is a novel hallmark of cancer associated with patient outcomes and tumor immunotherapy. However, the value of cellular senescence-related long non-coding RNAs (lncRNAs) in predicting prognosis and immunotherapy response for stomach adenocarcinoma (STAD) patients needs further investigation.Methods: The transcriptome and corresponding clinical information of STAD and cellular senescence-related genes were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and CellAge databases. Differential expression analysis and coexpression analysis were performed to obtain cellular senescence-related lncRNAs. Univariate regression analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were conducted to establish the cellular senescence-related lncRNA prognostic signature (CSLPS). Next, the survival curve, ROC curve, and nomogram were developed to assess the capacity of predictive models. Moreover, principal component analysis (PCA), gene set enrichment analysis (GSEA), tumor microenvironment (TME), tumor mutation burden (TMB), microsatellite instability (MSI), and tumor immune dysfunction and exclusion (TIDE) score analysis were performed between high- and low-risk groups.Results: A novel CSLPS involving fifteen lncRNAs (REPIN1-AS1, AL355574.1, AC104695.3, AL033527.2, AC083902.1, TYMSOS, LINC00460, AC005165.1, AL136115.1, AC007405.2, AL391152.1, SCAT1, AC129507.1, AL121748.1, and ADAMTS9-AS1) was developed. According to the nomogram, the risk model based on the CSLPS was an independent prognostic factor and could predict 1-, 3-, and 5-year overall survival for STAD patients. GSEA suggested that the high-risk group was mainly associated with Toll-like receptor, JAK/STAT, NOD-like receptor, and chemokine signaling pathways. Further analysis revealed that STAD patients in the low-risk group with better clinical outcomes had a higher TMB, higher proportion of high microsatellite instability (MSI-H), better immune infiltration, and lower TIDE scores.Conclusion: A fifteen-CSlncRNA prognostic signature could predict survival outcomes, and patients in the low-risk group may be more sensitive to immunotherapy.

Background Drug resistance is an important factor affecting the efficacy of chemotherapy in patients with colon cancer. However, clinical markers for diagnosing drug resistance of tumor cells are not only a few in number, but also low in specificity, and the mechanism of action of tumor cell drug resistance remains unclear. Methods Dipeptidase 1 (DPEP1) expression was analyzed using the cancer genome atlas (TCGA) and genotype‐Tissue Expression pan‐cancer data. Survival analysis was performed using the survival package in R software to assess the prognostic value of DPEP1 expression in colon cancer. Correlation and Venn analyses were adopted to identify key genes. Immunohistochemistry, western blot, qRT–PCR, Co‐immunoprecipitation, and dual‐luciferase reporter experiments were carried out to explore the underlying associations between DPEP1 and Achaete scute‐like 2 (ASCL2). MTT assays were used to evaluate the role of DPEP1 and ASCL2 in colon cancer drug resistance. Results DPEP1 was highly expressed in colon cancer tissues. DPEP1 expression correlated negatively with disease‐specific survival but not with overall survival. Bioinformatics analysis and experiments showed that the expressions of DPEP1 and ASCL2 in colon cancer tissues were markedly positively correlated. Mechanistic research indicated that DPEP1 enhanced the stability of protein ASCL2 by inhibiting its ubiquitination‐mediated degradation. In turn, ASCL2 functioned as a transcription factor to activate the transcriptional activity of the DPEP1 gene and boost its expression. Furthermore, DPEP1 also could enhance the expression of colon cancer stem cell markers (LGR5, CD133, and CD44), which strengthened the tolerance of colon cancer cells to chemotherapy drugs. Conclusions Our findings reveal that the DPEP1 enhances the stemness of tumor cells by forming a positive feedback loop with ASCL2 to improve resistance to chemotherapy drugs.

A dissolved oxygen sensor was developed based on time‐domain lifetime measurement with an oxygen sensing film. The oxygen sensing film was fabricated by embedding PtOEP in a highly stable and highly hydrophobic fluorinated matrix synthesized from methacrylate, fluorinated methacrylate, and 3‐(tris(trimethylsilyloxy)silyl)propyl methacrylate via free radical polymerization. The fluorinated methacrylate provided the high stability and the 3‐(tris(trimethylsilyloxy)silyl)propyl methacrylate provided the extra hydrophobicity. The PtOEP was excited using pulsed signals from a green‐light LED and the fluorescence lifetime was evaluated by time‐domain lifetime measurement. The dynamical quenching of fluorescence response by dissolved oxygen was calibrated using the Stern‐Volmer plot with a high τ0/τ100 ratio of 5.68 and a Stern‐Volmer constant of 0.112 mg−1 dm3. It was demonstrated that the dissolved oxygen sensing film showed high stability under the varied excitation intensity and long‐term stability in the accelerated aging experiment and the repeated freeze‐thaw‐cycling tests.

Background: Dipeptidase 1 (DPEP1) is associated with several human cancers. However, its function in colon cancer remains unclear.Methods: DPEP1 expression was analyzed by TCGA and GTEx pancancer data. Survival analysis was performed using the R survival package to assess the prognostic value of the DPEP1 expression level in colon cancer. DPEP1 enrichment analysis was conducted by the clusterProfiler R software package. Correlation analysis, differential expression analysis, and Venn analysis were used to obtain key genes. Correlation of DPEP1 or ASCL2 expression with immune cell infiltration in colon cancer was performed by TIMER and GSCA databases. qRT-PCR, Western blot, Co-immunoprecipitation, dual luciferase reporter experiments, and immunohistochemistry were used to explore the correlation between DPEP1 and ASCL2. MTT was used to evaluate the role of DPEP1 in colon cancer drug resistance.Results: DPEP1 was overexpressed in various cancers, including colon cancer. High DPEP1 expression was negatively correlated with the disease-specific survival (DSS) and progression-free interval (PFI) but not significantly correlated with the overall survival (OS). Enrichment analysis showed that DPEP1 may be related to the Wnt signaling pathway and Hippo signaling pathway. Further analysis showed that DPEP1 and ASCL2 had a strong positive correlation, and both correlated with immune cell infiltration. Moreover, DPEP1 enhanced drug resistance in an ASCL2- dependent manner.Conclusions: Our findings revealed that DPEP1 enhanced drug resistance in an ASCL2-dependent manner and correlated with immune infiltration in colon cancer.