Prognostic and clinical significance of subcellular CDC27 for patients with rectal adenocarcinoma treated with adjuvant chemotherapy

Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

BACKGROUND

Imprinted genes are epigenetically regulated in normal tissues to follow monoallelic expression according to the parent of origin of each allele. Some of these patterns are dysregulated in cancer.

RESULTS

We developed a novel computational multi-omic pipeline to evaluate monoallelic and biallelic expression patterns based on matched RNA-seq expression data, whole-exome sequencing information, and copy number data. We analyzed allelic expression of the entire genes, individual isoforms, and each exon of 59,283 autosomal protein-coding and ncRNA genes, with a focus on 94 genes previously reported to be imprinted. We analyzed 108 cell lines from 9 different tumor histologies using molecular data from the DepMap Portal for the Cancer Cell Line Encyclopedia. Allelic expression patterns of imprinted genes and isoforms in tumor cells were variable. We also identified additional genes and isoforms with predominantly monoallelic expression due to a variety of potential mechanisms. We provide a novel public dataset of transcriptome-wide allelic expression patterns in cell lines from diverse tumor categories, which can serve as a resource for future cancer studies. We examined associations of in vitro cell line response to antitumor agents and repurposed drugs with allelic patterns and overall levels of isoform expression of imprinted genes and of additional genes with predominantly monoallelic expression. Drug response was associated with isoform expression patterns of multiple imprinted genes including CPA4, DGCR6, DNMT1, GNAS, GRB10, H19, NAA60, OSBPL5, PHACTR2, and ZFAT, predominantly monoallelically expressed MAP2K5 and BCLAF1, and additional predominantly monoallelically expressed genes. Multiple associations may be related to mechanisms of drug activity, including associations between the response to the DNA damaging agents and allelic expression of ZFAT, CDC27, and BCLAF1 isoforms, and the response to inhibitors of multiple signaling pathways with expression patterns of GNAS isoforms.

CONCLUSIONS

Tumor cells have a range of monoallelic and biallelic expression patterns in both imprinted and non-imprinted genes and are likely affected by the complex interplay among changes in allelic expression, sequence variants, copy number changes, and expression changes of biologically important genes. Multiple isoform-specific patterns of allelic expression were associated with drug response, indicating complex mechanisms of cancer chemoresistance.

CDC27 gene expression patterns as a potential biomarker in Acute Leukemia

BACKGROUND

Treating Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) is difficult due to high relapse rates and drug resistance. Tumorigenesis is largely dependent on disruption of the cell cycle progression. While the role of Cell Division Cycle 27 (CDC27) in the anaphase-promoting complex/cyclosome is well-known, its significance in the pathophysiology of acute leukemia and its potential as a biomarker are less well understood.

METHODS AND RESULTS

This case-control study used samples from 100 leukemia patients (50 with ALL and 50 with AML) at Shariati Hospital in Tehran, Iran, along with 50 healthy individuals. The expression of CDC27 was analyzed using quantitative real-time PCR (RQ-PCR). Statistical analysis was done using the nonparametric Mann-Whitney U test. The results showed that AML and ALL patients had significantly higher levels of CDC27 expression compared to the control group. Although a weak correlation between CDC27 expression and hematological parameters was found, there was no significant correlation with sample type, demographics, clinical variables or prognosis.

CONCLUSIONS

This study highlights the potential of CDC27 as an oncogene, as well as a possible prognostic and diagnostic marker in acute leukemias. It suggests that CDC27 could be a valuable biomarker or therapeutic target in the treatment of AML and ALL.

Epidemiological and transcriptome data identify shared gene signatures and immune cell infiltration in type 2 diabetes and non-small cell lung cancer

BACKGROUND

Numerous previous studies have reported an association between type 2 diabetes mellitus (T2DM) and lung cancer risk, but the underlying mechanism of the interaction remains unclear. This study aimed to investigate the shared genetic features and immune infiltration processes between lung cancer and T2DM.

METHODS

Epidemiological data from the National Health and Nutrition Examination Survey (NHANES) 2000-2018 was used to explore the relationship between lung cancer and diabetes systematically. In addition, we also used bioinformatics methods to analyze the transcriptome data from the Gene Expression Omnibus (GEO) to explore the potential functional mechanisms from the perspective of genes and immune infiltration.

RESULTS

Logistic regression analysis showed that prediabetes (OR = 3.289,95%CI 1.231, 8.788, p = 0.01760, model 3)and type 2 diabetes (OR = 3.032 95%CI,1.015, 9.054, p = 0.04689) were significantly associated with an increased risk of lung cancer after adjusting for multiple covariates. Data from NHANES showed an inverted U-shaped relationship between fasting blood glucose and glycosylated haemoglobin and the risk of lung cancer (P for non-linear < 0.001). Transcriptome data showed that we screened 57 co-DEGs, of which 25 were up-regulated co-DEGs and 32 were down-regulated. Ten core DEGs were identified by bioinformatics analysis, which were SMC6, CDC27, CDC7, RACGAP1, SMC4, NCF4, NCF1, NCF2, SELPLG and CFP. Correlation analysis showed that some core DEGs were significantly associated with simultaneous dysregulation of immune cells.

CONCLUSION

The identified core genes of NSCLC and T2DM are associated with dysregulated immune cells, which provides a potential research avenue for diagnosing and treating lung cancer combined with diabetes.