Acetylation of interferon regulatory factor-5 suppresses androgen receptor and downregulates expression of Sox2

Association of chondroadherin with leiomyosarcoma

The leiomyosarcoma (LMS) subtype of uterine sarcoma accounts for 1-2 % of uterine neoplasia cases. The present study aimed to demonstrate that the gene and protein chondroadherin (CHAD) levels may serve as novel biomarkers for predicting prognosis and devising novel treatment models for LMS. A total of 12 patients diagnosed with LMS and 13 patients diagnosed with myomas were included in the study. The extent of tumour cell necrosis, cellularity and atypia and the mitotic index of each patient with LMS were determined. CHAD gene expression was significantly increased in cancerous tissues compared with that in fibroid tissues (2.17 ± 0.88 vs 3.19 ± 1.61; P = 0.047). The mean CHAD protein expression in tissues was higher in LMS cases but this was not statistically significant (217.38 ± 93.9 vs 177.13 ± 66.67;P = 0.226). Positive significant correlations were obtained between CHAD gene expression and mitotic index (r = 0.476; P = 0.008), tumour size (r = 0.385; P = 0.029) and necrosis (r = 0.455; P = 0.011). Furthermore, there were significant positive correlations between CHAD protein expression levels and tumour size (r = 0.360; P = 0.039) and necrosis (r = 0.377; P = 0.032). The present study was the first to demonstrate the significance of CHAD in LMS. The results suggested that, due to its association with LMS, CHAD has predictive value in determining the prognosis of patients with LMS.

Cisplatin resistance-related multi-omics differences and the establishment of machine learning models

Objectives

Platinum-based chemotherapies are currently the first-line treatment of non-small cell lung cancer. This study will improve our understanding of the causes of resistance to cisplatin, especially in lung adenocarcinoma (LUAD) and provide a reference for therapeutic decisions in clinical practice.

Methods

Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA) and Zhongshan hospital affiliated to Fudan University (zs-cohort) were used to identify the multi-omics differences related to platinum chemotherapy. Cisplatin-resistant mRNA and miRNA models were constructed by Logistic regression, classification and regression tree and C4.5 decision tree classification algorithm with previous feature selection performed via least absolute shrinkage and selection operator (LASSO). qRT-PCR and western-blotting of A549 and H358 cells, as well as single-cell Seq data of tumor samples were applied to verify the tendency of certain genes.

Results

661 cell lines were divided into three groups according to the IC50 value of cisplatin, and the top 1/3 (220) with a small IC50 value were defined as the sensitive group while the last 1/3 (220) were enrolled in the insensitive group. TP53 was the most common mutation in the insensitive group, in contrast to TTN in the sensitive group. 1348 mRNA, 80 miRNA, and 15 metabolites were differentially expressed between 2 groups (P < 0.05). According to the LASSO penalized logistic modeling, 6 of the 1348 mRNAs, FOXA2, BATF3, SIX1, HOXA1, ZBTB38, IRF5, were selected as the associated features with cisplatin resistance and for the contribution of predictive mRNA model (all of adjusted P-values < 0.001). Three of 6 (BATF3, IRF5, ZBTB38) genes were finally verified in cell level and patients in zs-cohort.

Conclusions

Somatic mutations, mRNA expressions, miRNA expressions, metabolites and methylation were related to the resistance of cisplatin. The models we created could help in the prediction of the reaction and prognosis of patients given platinum-based chemotherapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03372-0.