SEC61 translocon gamma subunit is correlated with glycolytic activity, epithelial mesenchymal transition and the immune suppressive phenotype of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) remains a predominant cause of cancer-related mortality globally, underscoring the urgency for targeted therapeutic strategies. The specific role and impact of the SEC61 translocon gamma subunit (SEC61G) in LUAD progression and metastasis remain largely unexplored. In this study, we use a multifaceted approach, combining bioinformatics analysis with experimental validation, to elucidate the pivotal role of SEC61G and its associated molecular mechanisms in LUAD. Our integrated analyses reveal a significant positive correlation between SEC61G expression and the glycolytic activity of LUAD, as evidenced by increased fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET)/CT scans. Further investigations show the potential influence of SEC61G on metabolic reprogramming, which contributes to the immunosuppressive tumor microenvironment (TME). Remarkably, we identify a negative association between SEC61G expression levels and the infiltration of critical immune cell populations within the TME, along with correlations with immune checkpoint gene expression and tumor heterogeneity scores in LUAD. Functional studies demonstrate that SEC61G knockdown markedly inhibits the migration of A549 and H2030 LUAD cells. This inhibitory effect is accompanied by a significant downregulation of key regulators of tumor progression, including hypoxia-inducible factor-1 alpha (HIF-1α), lactate dehydrogenase A, and genes involved in the epithelial-mesenchymal transition pathway. In conclusion, our comprehensive analyses position SEC61G as a potential prognostic biomarker intricately linked to glycolytic metabolism, the EMT pathway, and the establishment of an immune-suppressive phenotype in LUAD. These findings underscore the potential of SEC61G as a therapeutic target and predictive marker for immunotherapeutic responses in LUAD patients.

Structure-aware diffusion for low-dose CT imaging.

Reducing the radiation dose leads to the x-ray computed tomography (CT) images suffering from heavy noise and artifacts, which inevitably interferes with the subsequent clinic diagnostic and analysis. Leading works have explored diffusion models for low-dose CT imaging to avoid the structure degeneration and blurring effects of previous deep denoising models. However, most of them always begin their generative processes with Gaussian noise, which has little or no structure priors of the clean data distribution, thereby leading to long-time inference and unpleasant reconstruction quality. To alleviate these problems, this paper presents a Structure-Aware Diffusion model (SAD), an end-to-end self-guided learning framework for high-fidelity CT image reconstruction. First, SAD builds a nonlinear diffusion bridge between clean and degraded data distributions, which could directly learn the implicit physical degradation prior from observed measurements. Second, SAD integrates the prompt learning mechanism and implicit neural representation into the diffusion process, where rich and diverse structure representations extracted by degraded inputs are exploited as prompts, which provides global and local structure priors, to guide CT image reconstruction. Finally, we devise an efficient self-guided diffusion architecture using an iterative updated strategy, which further refines structural prompts during each generative step to drive finer image reconstruction. Extensive experiments on AAPM-Mayo and LoDoPaB-CT datasets demonstrate that our SAD could achieve superior performance in terms of noise removal, structure preservation, and blind-dose generalization, with few generative steps, even one step only.

Pooled CRISPR Screening Identifies P-Bodies as Repressors of Cancer Epithelial-Mesenchymal Transition.

Epithelial-mesenchymal transition (EMT) is a fundamental cellular process frequently hijacked by cancer cells to promote tumor progression, especially metastasis. EMT is orchestrated by a complex molecular network acting at different layers of gene regulation. In addition to transcriptional regulation, posttranscriptional mechanisms may also play a role in EMT. Here, we performed a pooled CRISPR screen analyzing the influence of 1,547 RNA-binding proteins on cell motility in colon cancer cells and identified multiple core components of P-bodies (PB) as negative modulators of cancer cell migration. Further experiments demonstrated that PB depletion by silencing DDX6 or EDC4 could activate hallmarks of EMT thereby enhancing cell migration in vitro as well as metastasis formation in vivo. Integrative multiomics analysis revealed that PBs could repress the translation of the EMT driver gene HMGA2, which contributed to PB-meditated regulation of EMT. This mechanism is conserved in other cancer types. Furthermore, endoplasmic reticulum stress was an intrinsic signal that induced PB disassembly and translational derepression of HMGA2. Taken together, this study has identified a function of PBs in the regulation of EMT in cancer. SIGNIFICANCE: Systematic investigation of the influence of posttranscriptional regulation on cancer cell motility established a connection between P-body-mediated translational control and EMT, which could be therapeutically exploited to attenuate metastasis formation.

Specific multivalent molecules boost CRISPR-mediated transcriptional activation.

CRISPR/Cas-based transcriptional activators can be enhanced by intrinsically disordered regions (IDRs). However, the underlying mechanisms are still debatable. Here, we examine 12 well-known IDRs by fusing them to the dCas9-VP64 activator, of which only seven can augment activation, albeit independently of their phase separation capabilities. Moreover, modular domains (MDs), another class of multivalent molecules, though ineffective in enhancing dCas9-VP64 activity on their own, show substantial enhancement in transcriptional activation when combined with dCas9-VP64-IDR. By varying the number of gRNA binding sites and fusing dCas9-VP64 with different IDRs/MDs, we uncover that optimal, rather than maximal, cis-trans cooperativity enables the most robust activation. Finally, targeting promoter-enhancer pairs yields synergistic effects, which can be further amplified via enhancing chromatin interactions. Overall, our study develops a versatile platform for efficient gene activation and sheds important insights into CRIPSR-based transcriptional activators enhanced with multivalent molecules.