Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are neurodegenerative disorders characterized by the accumulation of α-synuclein aggregates. α-synuclein forms droplets via liquid-liquid phase separation (LLPS), followed by liquid-solid phase separation (LSPS) to form amyloids, how this process is physiologically-regulated remains unclear. β-synuclein colocalizes with α-synuclein in presynaptic terminals. Here, we report that β-synuclein partitions into α-synuclein condensates promotes the LLPS, and slows down LSPS of α-synuclein, while disease-associated β-synuclein mutations lose these capacities. Exogenous β-synuclein improves the movement defects and prolongs the lifespan of an α-synuclein-expressing NL5901 Caenorhabditis elegans strain, while disease-associated β-synuclein mutants aggravate the symptoms. Decapeptides targeted at the α-/β-synuclein interaction sites are rationally designed, which suppress the LSPS of α-synuclein, rescue the movement defects, and prolong the lifespan of C. elegans NL5901. Together, we unveil a Yin-Yang balance between α- and β-synuclein underlying the normal and disease states of PD and DLB with therapeutical potentials.

Translation is a decoding process that synthesizes proteins from RNA, typically mRNA. The conventional translation process consists of four stages: initiation, elongation, termination, and ribosome recycling. Precise control over the translation mechanism is crucial, as dysregulation in this process is often linked to human diseases such as cancer. Recent discoveries have unveiled translation mechanisms that extend beyond typical well-characterized components like the m⁷G cap, poly(A)-tail, or translation factors like eIFs. These mechanisms instead utilize atypical elements, such as non-canonical ORF, m⁶A-modification, and circular RNA, as key components for protein synthesis. Collectively, these mechanisms are classified as non-canonical translations. It is increasingly clear that non-canonical translation mechanisms significantly impact the various regulatory pathways of cancer, including proliferation, tumorigenicity, and the behavior of cancer stem cells. This review explores the involvement of a variety of non-canonical translation mechanisms in cancer biology and provides insights into potential therapeutic strategies for cancer treatment.

Background: Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variability due to tumor heterogeneity necessitates robust biomarkers for predicting immunotherapy response.Methods: We used weighted gene co-expression network analysis (WGCNA), consensus clustering, and 10 machine learning algorithms to develop the immunotherapy-related gene model (ITRGM) signature. Multi-omics analyses included bulk and single-cell RNA sequencing of melanoma patients, mouse bulk RNA sequencing, and pathology sections of melanoma patients.Results: We identified 66 consensus immunotherapy prognostic genes (CITPGs) using WGCNA and differentially expressed genes (DEGs) from two melanoma cohorts. The CITPG-high group showed better prognosis and enriched immune activities. DEGs between CITPG-high and CITPG-low groups in the TCGA-SKCM cohort were analyzed in three additional melanoma cohorts using univariate Cox regression, resulting in 44 consensus genes. Using 101 machine learning algorithm combinations, we constructed the ITRGM signature based on seven model genes. The ITRGM outperformed 37 published signatures in predicting immunotherapy prognosis across the training cohort, three testing cohorts, and a meta-cohort. It effectively stratified patients into high-risk or low-risk groups for immunotherapy response. The low-risk group, with high levels of model genes, correlated with increased immune characteristics such as tumor mutation burden and immune cell infiltration, indicating immune-hot tumors with a better prognosis. The ITRGM’s relationship with the tumor immune microenvironment was further validated in our experiments using pathology sections with GBP5, an important model gene, and CD8 IHC analysis. The ITRGM also predicted better immunotherapy response in eight cohorts, including urothelial carcinoma and stomach adenocarcinoma, indicating broad applicability.Conclusions: The ITRGM signature is a stable and robust predictor for stratifying melanoma patients into ‘immune-hot’ and ‘immune-cold’ tumors, enhancing prognosis and response to immunotherapy.

Multisensory integration refers to sensory inputs from different sensory modalities being processed simultaneously to produce a unitary output. Surrounded by stimuli from multiple modalities, animals utilize multisensory integration to form a coherent and robust representation of the complex environment. Even though multisensory integration is fundamentally essential for animal life, our understanding of the underlying mechanisms, especially at the molecular, synaptic and circuit levels, remains poorly understood. The study of sensory perception in Caenorhabditis elegans has begun to fill this gap. We have gained a considerable amount of insight into the general principles of sensory neurobiology owing to C. elegans’ highly sensitive perceptions, relatively simple nervous system, ample genetic tools and completely mapped neural connectome. Many interesting paradigms of multisensory integration have been characterized in C. elegans, for which input convergence occurs at the sensory neuron or the interneuron level. In this narrative review, we describe some representative cases of multisensory integration in C. elegans, summarize the underlying mechanisms and compare them with those in mammalian systems. Despite the differences, we believe C. elegans is able to provide unique insights into how processing and integrating multisensory inputs can generate flexible and adaptive behaviors. With the emergence of whole brain imaging, the ability of C. elegans to monitor nearly the entire nervous system may be crucial for understanding the function of the brain as a whole.

Neurodegenerative diseases such as Alzheimer's disease and polyglutamine diseases are characterized by abnormal accumulation of misfolded proteins, leading to neuronal dysfunction and subsequent neuron death. However, there is a lack of studies that integrate molecular, morphological, and functional analyses in neurodegenerative models to fully characterize these time-dependent processes. In this study, we used C. elegans models expressing Aβ1-42 and polyglutamine to investigate early neuronal pathogenic features in olfactory neurons. Both models demonstrated significant reductions in odor sensitivity in AWB and AWC chemosensory neurons as early as day 1 of adulthood, while AWA chemosensory neurons showed no such decline, suggesting cell-type-specific early neuronal dysfunction. At the molecular level, Aβ1-42 or Q40 expression caused age-dependent protein aggregation and morphological changes in neurons. By day 6, both models displayed prominent protein aggregates in neuronal cell bodies and neurites. Notably, AWB neurons in both models showed significantly shortened cilia and increased instances of enlarged cilia as early as day 1 of adulthood. Furthermore, AWC neurons expressing Aβ1-42 displayed calcium signaling defects, with significantly reduced responses to odor stimuli on day 1, further supporting early behavioral dysfunction. In contrast, AWA neuron did not exhibit reduced calcium responses, consistent with the absence of detectable decreases in olfactory sensitivity in these neurons. These findings suggest that decreased calcium signaling and dysfunction in specific sensory neuron subtypes are early indicators of neurodegeneration in C. elegans, occurring prior to the formation of visible protein aggregates. We found that the ER unfolded protein response (UPR) is significantly activated in worms expressing Aβ1-42. Activation of the AMPK pathway alleviates olfactory defects and reduces fibrillar Aβ in these worms. This study underscores the use of C. elegans olfactory neurons as a model to elucidate mechanisms of proteostasis in neurodegenerative diseases and highlights the importance of integrated approaches.

Cancer cells can induce molecular changes that reshape cellular metabolism, creating specific vulnerabilities for targeted therapeutic interventions. Given the importance of reactive oxygen species (ROS) in tumor development and drug resistance, and the abundance of reduced glutathione (GSH) as the primary cellular antioxidant, we examined an integrated panel of 56 glutathione metabolism-related genes (GMRGs) across diverse cancer types. This analysis revealed a remarkable association between GMRGs and low-grade glioma (LGG) survival. Unsupervised clustering and a GMRGs-based risk score (GS) categorized LGG patients into two groups, linking elevated glutathione metabolism to poorer prognosis and treatment outcomes. Our GS model outperformed established clinical prognostic factors, acting as an independent prognostic factor. GS also exhibited correlations with pro-tumor M2 macrophage infiltration, upregulated immunosuppressive genes, and diminished responses to various cancer therapies. Experimental validation in glioma cell lines confirmed the critical role of glutathione metabolism in glioma cell proliferation and chemoresistance. Our findings highlight the presence of a unique metabolic susceptibility in LGG and introduce a novel GS system as a highly effective tool for predicting the prognosis of LGG.