MiR-375 promotes cisplatin sensitivity of lung adenocarcinoma.

BACKGROUND: Cisplatin-based chemotherapy has been widely used in the treatment of lung adenocarcinoma (LUAD). However, the development of cisplatin resistance becomes a major obstacle impeding the curative effect. It remains necessary to uncover the molecular mechanism of cisplatin resistance. METHODS: Based on the CCLE database, lung cancer cell lines were divided into cisplatin-resistant and cisplatin-sensitive groups. The differentially expressed miRNAs were filtered and further identified by survival prognosis analysis. After transfection with miR-375 inhibitor or mimic, cell cytotoxicity assay, flow cytometry and western blot were conducted to validate the role of miR-375. The transcription factor (TF)-miRNA network was constructed based on TransmiR. The target genes of miR-375 were predicted by Starbase and further verified by RT-qPCR and immunohistochemistry results in the Human Protein Atlas. Functional enrichment analysis was performed with GO terms and KEGG. RESULTS: In this study, miR-375 showed the ability to promote cisplatin sensitivity and apoptosis of LUAD. Genes correlated with miR-375 in LUAD were analyzed and ABCC8 showed the strongest positive correlation. Moreover, transcription factors that regulate miR-375 expression were predicted. MBNL1, PTPN3, PRKD1 and RPN1 were identified as the target genes of miR-375. Enrichment analysis demonstrated that miR-375-related genes associated with promoting cell proliferation and anti-apoptosis were involved in the MAPK signaling pathway. CONCLUSION: Overall, this study provides new insights into the role of miR-375 in the cisplatin sensitivity of LUAD. Our present findings may serve as a theoretical basis for new therapeutic strategies and predictive models of cisplatin resistance in LUAD.

A novel extrachromosomal circular DNA related genes signature for overall survival prediction in patients with ovarian cancer.

OBJECTIVE: Ovarian cancer (OV) has a high mortality rate all over the world, and extrachromosomal circular DNA (eccDNA) plays a key role in carcinogenesis. We wish to study more about the molecular structure of eccDNA in the UACC-1598-4 cell line and how its genes are associated with ovarian cancer prognosis. METHODS: We sequenced and annotated the eccDNA by Circle_seq of the OV cell line UACC-1598-4. To acquire the amplified genes of OV on eccDNA, the annotated eccDNA genes were intersected with the overexpression genes of OV in TCGA. Univariate Cox regression was used to find the genes on eccDNA that were linked to OV prognosis. The least absolute shrinkage and selection operator (LASSO) and cox regression models were used to create the OV prognostic model, as well as the receiver operating characteristic curve (ROC) curve and nomogram of the prediction model. By applying the median value of the risk score, the samples were separated into high-risk and low-risk groups, and the differences in immune infiltration between the two groups were examined using ssGSEA. RESULTS: EccDNA in UACC-1598-4 has a length of 0-2000 bp, and some of them include the whole genes or gene fragments. These eccDNA originated from various parts of chromosomes, especially enriched in repeatmasker, introns, and coding regions. They were annotated with 2188 genes by Circle_seq. Notably, the TCGA database revealed that a total of 198 of these eccDNA genes were overexpressed in OV (p < 0.05). They were mostly enriched in pathways associated with cell adhesion, ECM receptors, and actin cytoskeleton. Univariate Cox analysis showed 13 genes associated with OV prognosis. LASSO and Cox regression analysis were used to create a risk model based on remained 9 genes. In both the training (TCGA database) and validation (International Cancer Genome Consortium, ICGC) cohorts, a 9-gene signature could successfully discriminate high-risk individuals (all p < 0.01). Immune infiltration differed significantly between the high-risk and low-risk groups. The model's area under the ROC curve was 0.67, and a nomograph was created to assist clinician. CONCLUSION: EccDNA is found in UACC-1598-4, and part of its genes linked to OV prognosis. Patients with OV may be efficiently evaluated using a prognostic model based on eccDNA genes, including SLC7A1, NTN1, ADORA1, PADI2, SULT2B1, LINC00665, CILP2, EFNA5, TOMM.

Multidimensional difference analysis in gastric cancer patients between high and low latitude.

Genetic variation has been shown to affect tumor growth and progression, and the temperature at different latitudes may promote the evolution of genetic variation. Geographical data with latitudinal information is of importance to understand the interplay between genetic variants and environmental influence, such as the temperature, in gastric cancer (GC). In this study, we classified the GC samples from The Cancer Genome Atlas database into two groups based on the latitudinal information of patients and found that GC samples with low-latitude had better clinical outcomes. Further analyses revealed significant differences in other clinical factors such as disease stage and grade between high and low latitudes GC samples. Then, we analyzed the genomic and transcriptomic differences between the two groups. Furthermore, we evaluated the activity score of metabolic pathways and infiltrating immune cells in GC samples with different latitudes using the single-sample gene set enrichment analysis algorithm. These results showed that GC samples at low-latitude had lower tumor mutation burden and subclones as well as higher DNA repair activities. Meanwhile, we found that most immune cells were associated with the prognosis of low-latitude GC patients. At last, we constructed and validated an immune-related prognostic model to evaluate the prognosis of GC samples at different latitudes. This study has provided a further understanding of the geographical contribution to GC at the multiomic level and may benefit the individualized treatment of GC patients at different latitudes.