Protein-gene Expression Nexus: Comprehensive characterization of human cancer cell lines with proteogenomic analysis

N-linked glycosylation of the M-protein variable region: glycoproteogenomics reveals a new layer of personalized complexity in multiple myeloma

OBJECTIVES

Multiple myeloma (MM) is a plasma cell malignancy characterized by a monoclonal expansion of plasma cells that secrete a characteristic M-protein. This M-protein is crucial for diagnosis and monitoring of MM in the blood of patients. Recent evidence has emerged suggesting that N-glycosylation of the M-protein variable (Fab) region contributes to M-protein pathogenicity, and that it is a risk factor for disease progression of plasma cell disorders. Current methodologies lack the specificity to provide a site-specific glycoprofile of the Fab regions of M-proteins. Here, we introduce a novel glycoproteogenomics method that allows detailed M-protein glycoprofiling by integrating patient specific Fab region sequences (genomics) with glycoprofiling by glycoproteomics.

METHODS

Glycoproteogenomics was used for the detailed analysis of de novo N-glycosylation sites of M-proteins. First, Genomic analysis of the M-protein variable region was used to identify de novo N-glycosylation sites. Subsequently glycopeptide analysis with LC-MS/MS was used for detailed analysis of the M-protein glycan sites.

RESULTS

Genomic analysis uncovered a more than two-fold increase in the Fab Light Chain N-glycosylation of M-proteins of patients with Multiple Myeloma compared to Fab Light Chain N-glycosylation of polyclonal antibodies from healthy individuals. Subsequent glycoproteogenomics analysis of 41 patients enrolled in the IFM 2009 clinical trial revealed that the majority of the Fab N-glycosylation sites were fully occupied with complex type glycans, distinguishable from Fc region glycans due to high levels of sialylation, fucosylation and bisecting structures.

CONCLUSIONS

Together, glycoproteogenomics is a powerful tool to study de novo Fab N-glycosylation in plasma cell dyscrasias.

A Novel Oncogenic Role of Disulfidptosis-related Gene SLC7A11 in Anti-tumor Immunotherapy Response to Human Cancers

BACKGROUND

The protein Solute Carrier Family 7 Member 11 (SLC7A11) plays a pivotal role in cellular redox homeostasis by suppressing disulfidptosis, which restricts tumor growth. Yet, its relevance in prognosis, immunity, and cancer treatment efficacy is not well understood.

METHODS

We conducted a comprehensive analysis of the expression of SLC7A11 across 33 cancer types, employing datasets from public databases. Methods, such as Cox regression and survival analyses assessed its prognostic significance, while functional enrichment explored the biological processes tied to SLC7A11. The association between SLC7A11 expression, immune cell infiltration, and immune-related gene expression was also scrutinized.

RESULTS

Notably, SLC7A11 expression was more pronounced in cancerous compared to normal samples and correlated with higher tumor grades. Increased SLC7A11 expression was linked to poor outcomes, particularly in liver hepatocellular carcinoma (LIHC). This protein's expression also showcased significant relationships with diverse molecular and immune subtypes. Additionally, a prognostic nomogram was devised, integrating SLC7A11 expression and clinical variables. High SLC7A11 levels corresponded with cell growth and senescence pathways in various cancers and with lipid and cholesterol metabolism in LIHC. Furthermore, potential therapeutic compounds for LIHC with high SLC7A11 were identified. Real-time PCR (qPCR) and Western blot were conducted to explore the expression of SLC7A11 in tumor tissues and cancer cell lines.

CONCLUSION

In summation, this study emphasizes the prognostic and immunological importance of SLC7A11, spotlighting its potential as a therapeutic target in LIHC.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.