Updated Review and Perspective on 20S Proteasome Inhibitors in the Treatment of Lung Cancer

The cytotoxic activity of carfilzomib together with nelfinavir is superior to the bortezomib/nelfinavir combination in non-small cell lung carcinoma

Chemotherapy resistance is still a major problem in the treatment of patients with non-small-cell-lung carcinoma (NSCLC), and novel concepts for the induction of cytotoxicity in NSCLC are highly warranted. Proteotoxicity, the induction of cytotoxicity by targeting the ubiquitin proteasome system, represents an appealing innovative strategy. The combination of the proteasome inhibitor bortezomib (BTZ) and the proteotoxic stress-inducing HIV drug nelfinavir (NFV) synergistically induces proteotoxicity and shows encouraging preclinical efficacy in NSCLC. The second-generation proteasome inhibitor carfilzomib (CFZ) is superior to BTZ and overcomes BTZ resistance in multiple myeloma patients. Here, we show that CFZ together with NFV is superior to the BTZ + NFV combination in inducing endoplasmic reticulum stress and proteotoxicity through the accumulation of excess proteasomal substrate protein in NSCLC in vitro and ex vivo. Interestingly, NFV increases the intracellular availability of CFZ through inhibition of CFZ export from NSCLC cells that express multidrug resistance (MDR) protein. Combining CFZ with NFV may therefore represent a future treatment option for NSCLC, which warrants further investigation.

Pan-cancer analysis identifies proteasome 26S subunit, ATPase (PSMC) family genes, and related signatures associated with prognosis, immune profile, and therapeutic response in lung adenocarcinoma

Background: Proteasome 26S subunit, ATPase gene (PSMC) family members play a critical role in regulating protein degradation and are essential for tumor development. However, little is known about the integrative function and prognostic significance of the PSMC gene family members in lung cancer. Methods: First, we assessed the expression and prognostic features of six PSMC family members in pan-cancer from The Cancer Genome Atlas (TCGA) dataset. Hence, by focusing on the relationship between PSMC genes and the prognostic, genomic, and tumor microenvironment features in lung adenocarcinoma (LUAD), a PSMC-based prognostic signature was established using consensus clustering and multiple machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO) Cox regression, CoxBoost, and survival random forest analysis in TCGA and GSE72094. We then validated it in three independent cohorts from GEO and estimated the correlation between risk score and clinical features: genomic features (alterations, tumor mutation burden, and copy number variants), immune profiles (immune score, TIDE score, tumor-infiltrated immune cells, and immune checkpoints), sensitivity to chemotherapy (GDSC, GSE42127, and GSE14814), and immunotherapy (IMvigor210, GSE63557, and immunophenoscore). Twenty-one patients with LUAD were included in our local cohort, and tumor samples were submitted for evaluation of risk gene and PD-L1 expression. Results: Nearly all six PSMC genes were overexpressed in pan-cancer tumor tissues; however, in LUAD alone, they were all significantly correlated with overall survival. Notably, they all shared a positive association with increased TMB, TIDE score, expression of immune checkpoints (CD276 and PVR), and more M1 macrophages but decreased B-cell abundance. A PSMC-based prognostic signature was established based on five hub genes derived from the differential expression clusters of PSMC genes, and it was used to dichotomize LUAD patients into high- and low-risk groups according to the median risk score. The area under the curve (AUC) values for predicting survival at 1, 3, and 5 years in the training cohorts were all >.71, and the predictive accuracy was also robust and stable in the GSE72094, GSE31210, and GSE13213 datasets. The risk score was significantly correlated with advanced tumor, lymph node, and neoplasm disease stages as an independent risk factor for LUAD. Furthermore, the risk score shared a similar genomic and immune feature as PSMC genes, and high-risk tumors exhibited significant genomic and chromosomal instability, a higher TIDE score but lower immune score, and a decreased abundance of B and CD8⁺ T cells. Finally, high-risk patients were suggested to be less sensitive to immunotherapy but had a higher possibility of responding to platinum-based chemotherapy. The LUAD samples from the local cohort supported the difference in the expression levels of these five hub genes between tumor and normal tissues and the correlation between the risk score and PD-L1 expression. Conclusion: Overall, our results provide deep insight into PSMC genes in LUAD, especially the prognostic effect and related immune profile that may predict therapeutic responses.

Knockdown of RNF183 suppressed proliferation of lung adenocarcinoma cells via inactivating the STAT3 signaling pathway

Proteins of the RNF183 (RING finger 183) family proteins have been reported to be of great importance in tumor the initiation and progression. However, the biological role and regulatory mechanism of RNF183 in non small cell lung cancer (NSCLC) development and progression are poorly defined. Hence, lung adenocarcinoma (LUAD) cell proliferation, cell apoptosis and cell cycle were measured using Cell Counting Kit-8 and flow cytometry analysis, respectively. The correlation between RNF183 and SHP2 (Src homology-2 domain-containing protein tyrosine phosphatase) was measured using coimmunoprecipitation and ubiquitination analysis in vitro. Tumor growth of NSCLC cells in vivo was measured using the nude mouse xenograft model. In this study, we verify that elevated RNF183 expression in tumor tissues of LUAD, origin from the TCGA, GEPIA, TIMER, and UALCAN database. RNF183 regulates apoptosis and cell cycle in vitro and tumor growth in vivo by activating the STAT3 pathway through ubiquitination of SHP2, a negative feedback regulator of the STAT3 pathway. Taken together, our results demonstrate that RNF183 regulates proliferation, apoptosis, and cell cycle in LUAD cells via modulation of SHP2/STAT3 signaling, suggesting the potential for targeting the RNF183-SHP2/STAT3 pathway for use in LUAD treatment.

Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine

Relevance

Proteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM / 3P medicine).

Purpose

This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers.

Methods

Proteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types.

Results

Differentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan-Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways.

Conclusions

This study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00256-z.

Quantitative Proteomic Approach Reveals Altered Metabolic Pathways in Response to the Inhibition of Lysine Deacetylases in A549 Cells under Normoxia and Hypoxia

Growing evidence is showing that acetylation plays an essential role in cancer, but studies on the impact of KDAC inhibition (KDACi) on the metabolic profile are still in their infancy. Here, we analyzed, by using an iTRAQ-based quantitative proteomics approach, the changes in the proteome of KRAS-mutated non-small cell lung cancer (NSCLC) A549 cells in response to trichostatin-A (TSA) and nicotinamide (NAM) under normoxia and hypoxia. Part of this response was further validated by molecular and biochemical analyses and correlated with the proliferation rates, apoptotic cell death, and activation of ROS scavenging mechanisms in opposition to the ROS production. Despite the differences among the KDAC inhibitors, up-regulation of glycolysis, TCA cycle, oxidative phosphorylation and fatty acid synthesis emerged as a common metabolic response underlying KDACi. We also observed that some of the KDACi effects at metabolic levels are enhanced under hypoxia. Furthermore, we used a drug repositioning machine learning approach to list candidate metabolic therapeutic agents for KRAS mutated NSCLC. Together, these results allow us to better understand the metabolic regulations underlying KDACi in NSCLC, taking into account the microenvironment of tumors related to hypoxia, and bring new insights for the future rational design of new therapies.