Ubiquitin modification in the regulation of tumor immunotherapy resistance mechanisms and potential therapeutic targets

Gasdermin E as a potential target and biomarker for CRISPR-Cas9-based cancer therapy

Gasdermin E (GSDME), a protein pivotal in mediating pyroptosis, has gained significant attention due to its role in cancer pathogenesis and its potential as a therapeutic target. The advent of CRISPR-Cas9, a precise genome editing tool, has revolutionized cancer therapy by enabling the manipulation of GSDME expression and function. This review explores the interplay of GSDME and CRISPR-Cas9 in cancer, emphasizing GSDME's unique mechanism of cleavage-dependent pore formation in the cell membrane and its emerging applications as both a therapeutic target and a diagnostic biomarker. We discuss the potential and challenges of using GSDME-induced pyroptosis as a therapeutic strategy and how can enhance its efficacy and specificity. We conclude by highlighting promising future research directions in this emerging field.

Recent advances in small molecule inhibitors of deubiquitinating enzymes

Proteins play a pivotal role in maintaining cellular homeostasis. Their degradation primarily orchestrated through the ubiquitin-proteasome system (UPS) and cellular autophagy. Dysfunction of the UPS is associated with various human diseases, including cancer, autoimmune disorders, and neurodegenerative conditions. Consequently, the UPS has emerged as a promising therapeutic target. Deubiquitinases (DUBs) have garnered significant attention as potential targets for therapeutic intervention due to their role in modulating protein stability and function. This review focuses on recent advancements of DUBs, particularly their relevance in the UPS and their potential as drug targets. Notably, inhibitors targeting specific DUBs, such as USP1, USP7, USP14, and USP30 have shown promise in preclinical and clinical studies for cancer therapy. Additionally, DUB inhibitors have been involved in novel therapeutic approaches lately, including as targets for proteolysis-targeting chimeras (PROTACs) or as tools in deubiquitinase-targeting chimeras (DUBTACs).

Programmed Cell Death Ligand as a Biomarker for Response to Immunotherapy: Contribution of Mass Spectrometry-Based Analysis

Immune checkpoint inhibition is a major component in today's cancer immunotherapy. In recent years, the FDA has approved a number of immune checkpoint inhibitors (ICIs) for the treatment of melanoma, non-small-cell lung, breast and gastrointestinal cancers. These inhibitors, which target cytotoxic T-lymphocyte antigen-4, programmed cell death (PD-1), and programmed cell death ligand (PD-L1) checkpoints have assumed a leading role in immunotherapy. The same inhibitors exert significant antitumor effects by overcoming tumor cell immune evasion and reversing T-cell exhaustion. The initial impact of this therapy in cancer treatment was justly described as revolutionary, however, clinical as well as research data which followed demonstrated that these innovative drugs are costly, are associated with potentially severe adverse effects, and only benefit a small subset of patients. These limitations encouraged enhanced research and clinical efforts to identify predictive biomarkers to stratify patients who are most likely to benefit from this form of therapy. The discovery and characterization of this class of biomarkers is pivotal in guiding individualized treatment against various forms of cancer. Currently, there are three FDA-approved predictive biomarkers, however, none of which on its own can deliver a reliable and precise response to immune therapy. Present literature identifies the absence of precise predictive biomarkers and poor understanding of the mechanisms behind tumor resistance as the main obstacles facing ICIs immunotherapy. In the present text, we discuss the dual role of PD-L1 as a biomarker for response to immunotherapy and as an immune checkpoint. The contribution of mass spectrometry-based analysis, particularly the impact of protein post-translational modifications on the performance of this protein is underlined.

Post-translational modifications of immune checkpoints: unlocking new potentials in cancer immunotherapy

Immunotherapy targeting immune checkpoints has gained traction across various cancer types in clinical settings due to its notable advantages. Despite this, the overall response rates among patients remain modest, alongside issues of drug resistance and adverse effects. Hence, there is a pressing need to enhance immune checkpoint blockade (ICB) therapies. Post-translational modifications (PTMs) are crucial for protein functionality. Recent research emphasizes their pivotal role in immune checkpoint regulation, directly impacting the expression and function of these key proteins. This review delves into the influence of significant PTMs-ubiquitination, phosphorylation, and glycosylation-on immune checkpoint signaling. By targeting these modifications, novel immunotherapeutic strategies have emerged, paving the way for advancements in optimizing immune checkpoint blockade therapies in the future.

Suppression of CYLD by HER3 confers ovarian cancer platinum resistance via inhibiting apoptosis and by inducing drug efflux

BACKGROUND

Ovarian cancer (OC) is the most pathogenic gynecological malignant tumor in the world. Due to the difficulty of early diagnosis, most of patients developed chemo-resistance and recurrence during/after chemotherapy.

METHODS

CCK8 and flow cytometry were utilized to assess drug sensitivity and apoptosis in parental and drug resistant cell lines. CYLD knockdown or overexpressed cells were employed to investigate its regulatory involvement in DDP resistance. Clinical tumor samples have been utilized to investigate the clinical relevance of CYLD. The drug synergistic effects were investigated through drug combination methods and a nude mice model with ABCB1 inhibitor or HER3 inhibitor.

RESULTS

In this study, we found that CYLD levels were significantly reduced in DDP-resistant cancer tissues and cells compared to the normal tissues and cells. CYLD knockdown in DDP-sensitive cells was sufficient to converse the cells to become DDP resistant by reducing cell apoptosis through increasing Bcl-XL and inhibiting Bax, and by increasing drug efflux via upregulating ABCB1 expression. HER3 expression levels were substantially higher in resistant cancer tissues and cells, and HER3 was the upstream facilitator of suppressing CYLD expression via STAT3 signaling. Furthermore, overexpression of CYLD in resistant cells increased sensitivity to platinum-based chemotherapy both in vitro and in vivo. ABCB1 was a key downstream target of CYLD for regulating tumor growth and therapeutic resistance both in vitro and in vivo, CYLD knockdown promoted the translocation of p65 to nucleus which increased ABCB1 expression through transcriptional activation. High expression levels of HER3 rendered CYLD suppression, consequently, mediated DDP resistance by blocking cell apoptosis pathways and promoting the drug efflux in ovarian cancer.

CONCLUSIONS

Our findings identify novel HER3/CYLD/ABCB1 axis that regulate tumor growth and DDP resistance, which may be used as potential novel therapeutic target(s) to overcome ovarian cancer DDP resistance.

Machine learning-based pan-cancer study of classification and mechanism of BRAF inhibitor resistance

Background

V-raf murine sarcoma viral oncogene homolog B1 (BRAF) inhibitor (BRAFi) therapy resistance affects approximately 15% of cancer patients, leading to disease recurrence and poor prognosis. The aim of the study was to develop a machine-learning based method to identify patients who are at high-risk of BRAFi resistance and potential biomarker.

Methods

From Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases, we collected RNA sequencing and half maximal inhibitory concentration (IC50) data from 235 pan-cancer cell lines and then identified 37 significant differential expression genes associated with BRAFi resistance. Employing machine learning (ML) models, we successfully classified cell lines into resistant and sensitive groups, achieving robust performance in external validation datasets.

Results

AOX1 may play a vital part in BRAFi metabolism and resistance. Further, we found that higher mRNA expression of OXTR, H2AC13, and TBX2, and lower mRNA of SLC2A4, as detected by PCR in WM983B and SKMEL-5 cell lines, were independent risk factors for BRAFi resistance and were associated with poor prognosis.

Conclusions

We established a gene-expression model using ML methods, consisting of 37 variables based on RNA-seq database, which was externally validated and could be used to predict BRAFi resistance. Meanwhile, our findings provide valuable insights into the molecular mechanisms of BRAFi resistance, enabling the identification of high-risk patients.