Expression and clinical significance of ubiquitin‑specific‑processing protease 34 in diffuse large B‑cell lymphoma

Genomic signatures and prognosis of advanced stage Chinese pediatric T cell lymphoblastic lymphoma by whole exome sequencing

Objective

To investigate the genomic signatures and prognosis of advanced-stage T cell lymphoblastic lymphoma (T-LBL) and to examine the relationship between T-LBL and T cell acute lymphoblastic leukemia (T-ALL).

Methods

35 Chinese T-LBL children with stage III or IV disease were recruited for this study. They were treated with combination chemotherapy and whole exome sequencing. The relationship of the clinical features, prognosis and specific gene mutations was researched. Gene chips of T-LBL and T-ALL were downloaded from a database, and differential gene expression was analyzed.

Results

Germline causal gene mutations (CARS or MAP2K2) were detected in 2 patients; 3.06 ± 2.21 somatic causal gene mutations were identified in the 35 patients, and somatic mutations were observed in the NOTCH1, FBXW7, PHF6 and JAK3 genes. NOTCH1 mutations were significantly associated with FBXW7 mutations, and the age at diagnosis of patients with NOTCH1-FBXW7 mutations was less than that of patients without such mutations (P < 0.05). 32 patients achieved complete remission (CR), and 14 and 18 patients were classified into the intermediate risk (IR) group and high risk (HR) group. During a median follow-up of 44 months, 3 patients relapsed. Three-year prospective event free survival (pEFS) was 82.286%, and no significant differences of pEFS were found for different sexes, ages, or statuses of NOTCH1-FBXW7 mutations, (P > 0.05); however, the mean survival time of the IR group was longer than that of the HR group (P < 0.05). Differential expression of genes in the T-LBL and/or T-ALL datasets was analyzed using the R package limma, and 1/3 of the differentially expressed genes were found in both the T-ALL and T-LBL datasets. High expression of PI3K-Akt signal pathway genes and the USP34 gene was found in the T-LBL dataset.

Conclusion

Although T-ALL and T-LBL both originate from precursor T-cells and are considered different manifestations of the same disease and the outcome of T-LBL is favorable when using T-ALL-based chemotherapy, there are differences in the gene distribution between T-LBL and T-ALL. It seems that the PI3K-Akt signaling pathway and the USP34 gene play important roles in T-LBL, but medicines targeting the USP34 gene or the PI3K-Akt pathway may be invalid.

Integrative analysis of circadian clock with prognostic and immunological biomarker identification in ovarian cancer

Objective: To identify circadian clock (CC)-related key genes with clinical significance, providing potential biomarkers and novel insights into the CC of ovarian cancer (OC). Methods: Based on the RNA-seq profiles of OC patients in The Cancer Genome Atlas (TCGA), we explored the dysregulation and prognostic power of 12 reported CC-related genes (CCGs), which were used to generate a circadian clock index (CCI). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to identify potential hub genes. Downstream analyses including differential and survival validations were comprehensively investigated. Results: Most CCGs are abnormally expressed and significantly associated with the overall survival (OS) of OC. OC patients with a high CCI had lower OS rates. While CCI was positively related to core CCGs such as ARNTL, it also showed significant associations with immune biomarkers including CD8⁺ T cell infiltration, the expression of PDL1 and CTLA4, and the expression of interleukins (IL-16, NLRP3, IL-1β, and IL-33) and steroid hormones-related genes. WGCNA screened the green gene module to be mostly correlated with CCI and CCI group, which was utilized to construct a PPI network to pick out 15 hub genes (RNF169, EDC4, CHCHD1, MRPL51, UQCC2, USP34, POM121, RPL37, SNRPC, LAMTOR5, MRPL52, LAMTOR4, NDUFB1, NDUFC1, POLR3K) related to CC. Most of them can exert prognostic values for OS of OC, and all of them were significantly associated with immune cell infiltration. Additionally, upstream regulators including transcription factors and miRNAs of key genes were predicted. Conclusion: Collectively, 15 crucial CC genes showing indicative values for prognosis and immune microenvironment of OC were comprehensively identified. These findings provided insight into the further exploration of the molecular mechanisms of OC.

Identification of influential observations in high-dimensional survival data through robust penalized Cox regression based on trimming

Penalized Cox regression can efficiently be used for the determination of biomarkers in high-dimensional genomic data related to disease prognosis. However, results of Penalized Cox regression is influenced by the heterogeneity of the samples who have different dependent structure between survival time and covariates from most individuals. These observations are called influential observations or outliers. A robust penalized Cox model (Reweighted Elastic Net-type maximum trimmed partial likelihood estimator, Rwt MTPL-EN) is proposed to improve the prediction accuracy and identify influential observations. A new algorithm AR-Cstep to solve Rwt MTPL-EN model is also proposed. This method has been validated by simulation study and application to glioma microarray expression data. When there were no outliers, the results of Rwt MTPL-EN were close to the Elastic Net (EN). When outliers existed, the results of EN were impacted by outliers. And whenever the censored rate was large or low, the robust Rwt MTPL-EN performed better than EN. and could resist the outliers in both predictors and response. In terms of outliers detection accuracy, Rwt MTPL-EN was much higher than EN. The outliers who "lived too long" made EN perform worse, but were accurately detected by Rwt MTPL-EN. Through the analysis of glioma gene expression data, most of the outliers identified by EN were those "failed too early", but most of them were not obvious outliers according to risk estimated from omics data or clinical variables. Most of the outliers identified by Rwt MTPL-EN were those who "lived too long", and most of them were obvious outliers according to risk estimated from omics data or clinical variables. Rwt MTPL-EN can be adopted to detect influential observations in high-dimensional survival data.

Clinical significance of cyclin-dependent kinase inhibitor 2C expression in cancers: from small cell lung carcinoma to pan-cancers

Background

Cyclin-dependent kinase inhibitor 2C (CDKN2C) was identified to participate in the occurrence and development of multiple cancers; however, its roles in small cell lung carcinoma (SCLC) remain unclear.

Methods

Differential expression analysis of CDKN2C between SCLC and non-SCLC were performed based on 937 samples from multiple centers. The prognosis effects of CDKN2C in patients with SCLC were detected using both Kaplan–Meier curves and log-rank tests. Using receiver-operating characteristic curves, whether CDKN2C expression made it feasible to distinguish SCLC was determined. The potential mechanisms of CDKN2C in SCLC were investigated by gene ontology terms and signaling pathways (Kyoto Encyclopedia of Genes and Genomes). Based on 10,080 samples, a pan-cancer analysis was also performed to determine the roles of CDKN2C in multiple cancers.

Results

For the first time, upregulated CDKN2C expression was detected in SCLC samples at both the mRNA and protein levels (p of Wilcoxon rank-sum test < 0.05; standardized mean difference = 2.86 [95% CI 2.20–3.52]). Transcription factor FOXA1 expression may positively regulate CDKN2C expression levels in SCLC. High CDKN2C expression levels were related to the poor prognosis of patients with SCLC (hazard ratio > 1, p < 0.05) and showed pronounced effects for distinguishing SCLC from non-SCLC (sensitivity, specificity, and area under the curve ≥ 0.95). CDKN2C expression may play a role in the development of SCLC by affecting the cell cycle. Furthermore, the first pan-cancer analysis revealed the differential expression of CDKN2C in 16 cancers (breast invasive carcinoma, etc.) and its independent prognostic significance in nine cancers (e.g., adrenocortical carcinoma). CDKN2C expression was related to the immune microenvironment, suggesting its potential usefulness as a prognostic marker in immunotherapy.

Conclusions

This study identified upregulated CDKN2C expression and its clinical significance in SCLC and other multiple cancers, suggesting its potential usefulness as a biomarker in treating and differentiating cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02036-5.

Deubiquitinases in hematological malignancies

Deubiquitinases (DUBs) are enzymes that control the stability, interactions or localization of most cellular proteins by removing their ubiquitin modification. In recent years, some DUBs, such as USP7, USP9X and USP10, have been identified as promising therapeutic targets in hematological malignancies. Importantly, some potent inhibitors targeting the oncogenic DUBs have been developed, showing promising inhibitory efficacy in preclinical models, and some have even undergone clinical trials. Different DUBs perform distinct function in diverse hematological malignancies, such as oncogenic, tumor suppressor or context-dependent effects. Therefore, exploring the biological roles of DUBs and their downstream effectors will provide new insights and therapeutic targets for the occurrence and development of hematological malignancies. We summarize the DUBs involved in different categories of hematological malignancies including leukemia, multiple myeloma and lymphoma. We also present the recent development of DUB inhibitors and their applications in hematological malignancies. Together, we demonstrate DUBs as potential therapeutic drug targets in hematological malignancies.

Quantitative expression of Ikaros, IRF4, and PSMD10 proteins predicts survival in VRD-treated patients with multiple myeloma

The search for biomarkers based on the mechanism of drug action has not been thoroughly addressed in the therapeutic approaches to multiple myeloma (MM), mainly because of the difficulty in analyzing proteins obtained from purified plasma cells. Here, we investigated the prognostic impact of the expression of 12 proteins involved in the mechanism of action of bortezomib, lenalidomide, and dexamethasone (VRD), quantified by capillary nanoimmunoassay, in CD138-purified samples from 174 patients with newly diagnosed MM treated according to the PETHEMA/GEM2012 study. A high level of expression of 3 out of 5 proteasome components tested (PSMD1, PSMD4, and PSMD10) negatively influenced survival. The 5 analyzed proteins involved in lenalidomide's mode of action were associated with time to progression (TTP); low levels of cereblon and IRF4 protein and high levels of Ikaros, AGO2, and Aiolos were significantly associated with shorter TTP. Although the glucocorticoid receptor (GCR) level by itself had no significant impact on MM prognosis, a high XPO1 (exportin 1)/GCR ratio was associated with shorter TTP and progression-free survival (PFS). The multivariate Cox model identified high levels of PSMD10 (hazard ratio [HR] TTP, 3.49; P = .036; HR PFS, 5.33; P = .004) and Ikaros (HR TTP, 3.01, P = .014; HR PFS, 2.57; P = .028), and low levels of IRF4 protein expression (HR TTP, 0.33; P = .004; HR PFS, 0.35; P = .004) along with high-risk cytogenetics (HR TTP, 3.13; P < .001; HR PFS, 2.69; P = .002), as independently associated with shorter TTP and PFS. These results highlight the value of assessing proteins related to the mechanism of action of drugs used in MM for predicting treatment outcome.

Ubiquitin, SUMO, and Nedd8 as Therapeutic Targets in Cancer

Ubiquitin defines a family of approximately 20 peptidic posttranslational modifiers collectively called the Ubiquitin-like (UbLs). They are conjugated to thousands of proteins, modifying their function and fate in many ways. Dysregulation of these modifications has been implicated in a variety of pathologies, in particular cancer. Ubiquitin, SUMO (-1 to -3), and Nedd8 are the best-characterized UbLs. They have been involved in the regulation of the activity and/or the stability of diverse components of various oncogenic or tumor suppressor pathways. Moreover, the dysregulation of enzymes responsible for their conjugation/deconjugation has also been associated with tumorigenesis and cancer resistance to therapies. The UbL system therefore constitutes an attractive target for developing novel anticancer therapeutic strategies. Here, we review the roles and dysregulations of Ubiquitin, SUMO, and Nedd8 pathways in tumorigenesis, as well as recent advances in the identification of small molecules targeting their conjugating machineries for potential application in the fight against cancer.