The study, led by Can Chen and colleagues at the Department of Hematology, School of Medicine, Affiliated Hangzhou First People’s Hospital, West Lake University, in collaboration with researchers at Wuhan Polytechnic University, was published in BMC Cancer. The research represents the first systematic investigation of how genes related to both ubiquitination and liquid-liquid phase separation (LLPS) contribute to the prognosis of patients with multiple myeloma, and it identifies UBA1 as a primary candidate biomarker for the disease.

Ubiquitination is a post-translational modification process in which the small protein ubiquitin is attached to target proteins, marking them for degradation by the proteasome or altering their localization and activity. This pathway is central to protein homeostasis, and its dysregulation has long been implicated in cancer development. Indeed, the proteasome inhibitor bortezomib, a cornerstone of multiple myeloma therapy, works by exploiting the cancer cell’s dependence on this very system. Liquid-liquid phase separation, on the other hand, is a physical process by which proteins and nucleic acids condense into membraneless organelles within cells, such as stress granules and nucleoli. This process has emerged as a critical regulator of gene expression, signal transduction, and cellular organization, and its disruption has been increasingly linked to tumor initiation and progression.

Despite growing evidence that both ubiquitination and LLPS play important roles in cancer biology, their combined contribution to multiple myeloma had not been systematically explored. The research team set out to fill this gap by identifying a set of genes — termed ubiquitination and liquid-liquid phase separation related genes, or ULLPSRGs — that are involved in both processes and that carry prognostic significance in multiple myeloma.

The researchers began by compiling a comprehensive list of genes associated with both ubiquitination and LLPS from publicly available databases and the scientific literature. They then analyzed gene expression data from multiple myeloma patients using large-scale genomic datasets, applying consistent clustering analysis and prognostic difference analysis to identify which of these genes were most closely associated with patient survival outcomes. Through this rigorous bioinformatic pipeline, the team identified four ULLPSRGs that were significantly associated with prognosis in multiple myeloma patients.

Using these four genes, the researchers performed consensus clustering analysis, which grouped patients into distinct molecular subtypes based on their expression patterns of the ULLPSRGs. The two identified clusters showed clear prognostic differences, suggesting that the activity of these genes can stratify patients into groups with different clinical outcomes. This finding underscores the potential of ULLPSRGs not just as individual biomarkers but as a coordinated molecular signature that captures biologically meaningful differences between tumors.

Building on this foundation, the team constructed a prognostic risk model using multivariate Cox regression, incorporating the expression levels of the four ULLPSRGs. The model was then validated on an independent dataset, confirming its predictive power. The signature emerged as an independent risk factor for multiple myeloma patients, meaning that its prognostic value held even when accounting for other established clinical variables. Importantly, the signature also correlated significantly with clinical factors, suggesting that it captures information that complements traditional staging and risk assessment tools.

To further understand the biological relevance of the ULLPSRG signature, the researchers conducted immune infiltration analysis, examining how the expression patterns of these genes related to the composition of immune cells within the tumor microenvironment. They found that the signature was significantly associated with the tumor microenvironment, suggesting that ubiquitination and LLPS-related genes may influence not only the intrinsic biology of myeloma cells but also their interactions with surrounding immune and stromal cells. This finding opens potential avenues for combining ULLPSRG-based prognostic stratification with immunotherapeutic approaches.

The team also performed enrichment analysis and drug sensitivity evaluation to explore the therapeutic implications of their findings. Enrichment analysis helps identify which biological pathways and processes are most active in patients with high versus low risk scores, providing clues about the molecular mechanisms driving poor outcomes. Drug sensitivity evaluation, meanwhile, assesses whether patients with different expression patterns of the ULLPSRGs might respond differently to existing therapies, potentially guiding personalized treatment decisions.

Perhaps the most clinically significant finding of the study came from the laboratory experiments. The researchers conducted cell experiments to confirm the functional role of UBA1, one of the four identified ULLPSRGs and the primary candidate biomarker highlighted in the study. UBA1 encodes the ubiquitin-activating enzyme E1, the enzyme that initiates the ubiquitination cascade by activating ubiquitin molecules before they are transferred to target proteins. When the researchers inhibited the expression of UBA1 in multiple myeloma cells, they observed two critical effects: the cells’ cycle progression was halted, and apoptosis — programmed cell death — was promoted. These results provide direct experimental evidence that UBA1 plays a functional role in supporting the survival and proliferation of myeloma cells, positioning it as a potential therapeutic target as well as a biomarker.

The identification of UBA1 as a central player in multiple myeloma biology is particularly noteworthy given the existing clinical context. Proteasome inhibitors like bortezomib and carfilzomib already target the downstream machinery of the ubiquitination pathway, and their success in treating myeloma validates the pathway as therapeutically actionable. However, resistance to proteasome inhibitors eventually develops in most patients, and targeting upstream components of the ubiquitination cascade — such as the E1 activating enzyme encoded by UBA1 — represents a potentially complementary strategy that could overcome or delay the emergence of resistance.

The study’s integration of liquid-liquid phase separation into the analysis adds an additional layer of biological insight. LLPS has been shown to regulate the formation of biomolecular condensates that concentrate specific proteins and nucleic acids, thereby controlling cellular processes ranging from transcription to DNA damage repair. In cancer, aberrant phase separation can contribute to the misregulation of tumor suppressors and oncogenes. By identifying genes that bridge both ubiquitination and LLPS, the researchers have highlighted a class of molecules that may coordinate protein degradation with spatial organization within the cell, offering a more nuanced understanding of how myeloma cells maintain their malignant state.

From a clinical perspective, the prognostic model developed in this study could provide oncologists with a powerful tool for risk stratification. By incorporating the expression levels of the four ULLPSRGs into a quantitative score, clinicians may be able to identify patients at higher risk of poor outcomes who might benefit from more aggressive or alternative therapeutic approaches. The fact that the model was validated on an independent dataset strengthens confidence in its generalizability, although further prospective validation in larger, more diverse patient cohorts will be necessary before clinical implementation.

The researchers also note that their findings could inform the development of novel therapeutic strategies. If UBA1 and the other ULLPSRGs are confirmed to play critical roles in myeloma cell survival through additional experimental studies, they could become targets for small-molecule inhibitors or other therapeutic modalities. The convergence of ubiquitination and LLPS biology in these genes suggests that disrupting their function could simultaneously impair multiple survival mechanisms that myeloma cells rely upon, potentially leading to more effective and durable treatments.

This study also exemplifies the growing power of integrative bioinformatics approaches in cancer research. By combining data from multiple genomic databases, applying sophisticated clustering and regression techniques, and validating findings through laboratory experiments, the researchers have demonstrated how computational analysis can generate testable hypotheses that translate into meaningful biological insights. The identification of ULLPSRGs as a previously unexplored class of prognostic markers in multiple myeloma illustrates the value of looking beyond traditionally studied pathways to uncover novel molecular determinants of cancer behavior.

As the field of multiple myeloma research continues to evolve, studies like this one that bridge fundamental cell biology with clinical outcomes are likely to play an increasingly important role. The identification of UBA1 as a primary candidate biomarker, along with the demonstration that its inhibition can halt cell cycle progression and promote apoptosis in myeloma cells, provides a compelling foundation for future research aimed at developing targeted therapies. With further validation and the development of pharmacological tools to modulate UBA1 activity, this finding could ultimately contribute to improved treatment strategies for patients battling this challenging disease.

Subject of Research: The role of ubiquitination and liquid-liquid phase separation related genes, particularly UBA1, in the prognosis and treatment of multiple myeloma.

Article Title: A study of ubiquitination and liquid-liquid phase separation related genes yields uba1 as a primary candidate biomarker for a role in multiple myeloma

Article References: Chen, C., Li, Y., Chen, Z., Shi, P., Li, Y., Qian, S., & Shan, L. (2026). A study of ubiquitination and liquid-liquid phase separation related genes yields uba1 as a primary candidate biomarker for a role in multiple myeloma. BMC Cancer. https://doi.org/10.1186/s12885-026-16899-y

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16899-y

Keywords: multiple myeloma, UBA1, ubiquitination, liquid-liquid phase separation, biomarker, prognosis, tumor microenvironment, apoptosis, cell cycle, proteasome inhibitors, bioinformatics, hematologic malignancy