Genesis Foundation

Circular RNAs (circRNAs) emerged as promising non-invasive cancer biomarkers due to their stability, abundance in body fluids, and regulatory potential. However, circRNA differential expression analysis (DEA) remains challenging, largely owing to lack of consensus on important preprocessing strategies such as filtering and normalization. While well-established bulk RNA-sequencing frameworks are commonly applied to circRNA data, newer approaches such as CIRI-DE (part of CIRI3 suite) integrate both linear and circular transcript information to improve detection. Despite developments, an assessment of these integrative strategies is lacking, and the critical impact of filtering on DEA model performance has not been comprehensively evaluated. Results: In this study, we evaluated the impact of multiple normalization and filtering strategies on circRNA DEA using five experimental datasets, including two in-house blood platelet sets and semi-parametric simulated in silico datasets. Our results emphasize the importance of selecting an appropriate filtering threshold, as overly lenient filtering substantially reduced model performance across datasets. We found edgeR's filterByExpr() strategy particularly effective in handling zero counts in circRNA data, while also generating the most reliable results across most datasets. Furthermore, by incorporating linear and circular information as described in CIRI-DE, most methods identified a higher number of differentially expressed (DE) circRNAs compared to circular counts alone. Notably, circRNAs identified by both CIRI-DE and the modified bulk RNA-sequencing pipelines showed substantial overlap. Conclusion: Our findings demonstrate that automated filtering combined with linear-aware normalization significantly enhances the sensitivity and reproducibility of circRNA DEA, providing a standardized framework for more reliable biomarker discovery in transcriptomic research.

patient characteristics to the publicly available tissue proteome data it could lead to errors in the analysis.

Abstract Predicting whether single amino acid variants (SAVs) in proteins lead to pathogenic outcomes is a critical challenge in molecular biology and precision medicine. Experimental determination of all possible mutation effects is infeasible, and while state-of-the-art tools such as AlphaMissense show promise, their diagnostic performance is insufficient and they are often difficult to run locally. We developed pLM-SAV, a simple yet effective predictor that leverages protein language models (pLMs). Δ-embeddings, computed as the difference between wild-type and mutant sequence embeddings, are used as input for a convolutional neural network. To prevent data leakage, we trained our model on a well-characterized, labeled set of Eff10k and evaluated it on a non-homologous subset of ClinVar data. Our results demonstrate that this approach performs exceptionally well on the Eff10k test folds and reasonably on ClinVar test sets. Notably, pLM-SAV excels in resolving ambiguous predictions by AlphaMissense. We also found that an ensemble method, REVEL, outperforms both AlphaMissense and pLM-SAV, thus, we integrated these REVEL- enhanced predictions into our widely used AlphaMissense web application. Our results demonstrate that an SAV predictor trained on labeled data can achieve high predictive performance. Unlike previous methods such as VESPA, pLM-SAV uses no handcrafted features or substitution matrices, relying solely on pLM-derived representations. We anticipate that incorporating delta-embeddings into other mutation effect predictors or mutant structure prediction methods will further enhance their accuracy and utility in diverse biological contexts. Availability and Implementation Freely available at https://doi.org/10.5281/zenodo.15502498 and https://alphamissense.hegelab.org.

To systematically review the safety and efficacy of nonbiological (NBAL) or biological artificial liver support systems (BAL) and whole-organ extracorporeal liver perfusion (W-ECLP) systems, in adults with acute liver failure (ALF) and acute-on-chronic liver failure (ACLF). Eligible NBAL/BAL studies from PubMed/Embase searches were randomized controlled trials (RCTs) in adult patients with ALF/ACLF, greater than or equal to ten patients per group, reporting outcomes related to survival, adverse events, transplantation rate, and hepatic encephalopathy, and published in English from January 2000 to July 2023. Separately, we searched for studies evaluating W-ECLP in adult patients with ALF or ACLF published between January1990 and July 2023. Two researchers independently screened citations for eligibility and, of eligible studies, retrieved data related to study characteristics, patients and interventions, outcomes definition, and intervention effects. The Cochrane Risk of Bias 2 tool and Joanna Briggs Institute checklists were used to assess individual study risk of bias. Meta-analysis of mortality at 28-30 days post-support system initiation and frequency of at least one serious adverse event (SAE) generated pooled risk ratios (RRs), based on random (mortality) or fixed (SAE) effects models. Of 17 trials evaluating NBAL/BAL systems, 11 reported 28-30 days mortality and five reported frequency of at least one SAE. Overall, NBAL/BAL was not statistically associated with mortality at 28-30 days (RR, 0.85; 95% CI, 0.67-1.07; p = 0.169) or frequency of at least one SAE (RR, 1.15; 95% CI, 0.99-1.33; p = 0.059), compared with standard medical treatment. Subgroup results on ALF patients suggest possible benefit for mortality (RR, 0.67; 95% CI, 0.44-1.03; p = 0.069). From six reports of W-ECLP (12 patients), more than half (58%) of severe patients were bridged to transplantation and survived without transmission of porcine retroviruses. Despite no significant pooled effects of NBAL/BAL devices, the available evidence calls for further research and development of extracorporeal liver support systems, with larger RCTs and optimization of patient selection, perfusion durability, and treatment protocols.

Estrogen receptor-negative (ER-) breast cancer is an aggressive breast cancer subtype with limited therapeutic options. Upregulated expression of both inducible nitric oxide synthase (NOS2) and cyclo-oxygenase (COX2) in breast tumors predicts poor clinical outcomes. Signaling molecules released by these enzymes activate oncogenic pathways, driving cancer stemness, metastasis, and immune suppression. The influence of tumor NOS2/COX2 expression on the landscape of immune markers using multiplex fluorescence imaging of 21 ER- breast tumors were stratified for survival. A powerful relationship between tumor NOS2/COX2 expression and distinct CD8+ T cell phenotypes was observed at 5 years post-diagnosis. These results were confirmed in a validation cohort using gene expression data showing that ratios of NOS2 to CD8 and COX2 to CD8 are strongly associated with poor outcomes in high NOS2/COX2-expressing tumors. Importantly, multiplex imaging identified distinct CD8+ T cell phenotypes relative to tumor NOS2/COX2 expression in Deceased vs Alive patient tumors at 5-year survival. CD8+NOS2-COX2- phenotypes defined fully inflamed tumors with significantly elevated CD8+ T cell infiltration in Alive tumors expressing low NOS2/COX2. In contrast, two distinct phenotypes including inflamed CD8+NOS2+COX2+ regions with stroma-restricted CD8+ T cells and CD8-NOS2-COX2+ immune desert regions with abated CD8+ T cell penetration, were significantly elevated in Deceased tumors with high NOS2/COX2 expression. These results were supported by applying an unsupervised nonlinear dimensionality-reduction technique, UMAP, correlating specific spatial CD8/NOS2/COX2 expression patterns with patient survival. Moreover, spatial analysis of the CD44v6 and EpCAM cancer stem cell (CSC) markers within the CD8/NOS2/COX2 expression landscape revealed positive correlations between EpCAM and inflamed stroma-restricted CD8+NOS2+COX2+ phenotypes at the tumor/stroma interface in deceased patients. Also, positive correlations between CD44v6 and COX2 were identified in immune desert regions in deceased patients. Furthermore, migrating tumor cells were shown to occur only in the CD8-NOS2+COX2+ regions, identifying a metastatic hot spot. Taken together, this study shows the strength of spatial localization analyses of the CD8/NOS2/COX2 landscape, how it shapes the tumor immune microenvironment and the selection of aggressive tumor phenotypes in distinct regions that lead to poor clinical outcomes. This technique could be beneficial for describing tumor niches with increased aggressiveness that may respond to clinically available NOS2/COX2 inhibitors or immune-modulatory agents.

<p>Supplementary Materials and Methods, Figures, and Tables</p>

<div>Abstract<p><b>Purpose:</b> The excision repair cross-complementation group 1 (ERCC1) plays a pivotal role in DNA repair and has been linked to protection against carcinogenesis and resistance to platinum-based anticancer drugs. We tested whether genetic variants in the <i>ERCC1</i> gene are associated with susceptibility to lung cancer and efficacy of platinum-chemotherapy in patients with small cell lung cancer (SCLC).</p><p><b>Experimental Design:</b> Thirty individual DNA samples were sequenced to search for single-nucleotide polymorphisms, and the functions of the variants were investigated by a series of biochemical assays. A case-control study was done in 988 patients with lung cancer and 986 control subjects. According to the genotypes, a comparison of chemotherapy outcome in 162 SCLC patients was executed. Overall survival was computed by Cox model adjusted for clinical factors.</p><p><b>Results:</b> We identified two functional variants in the <i>ERCC1</i> 5′-flanking region, −433T>C and 262G>T, which cooperatively influence transcriptional regulation of <i>ERCC1</i>. The 262G allele had significantly lower affinity to bind nuclear protein(s) and was associated with decreased <i>ERCC1</i> RNA expression. The case-control analysis showed that the −433C and 262G alleles are associated with an increased susceptibility to lung cancer, alone and in a gene-smoking joint effect manner. In contrast, the analysis of chemotherapy outcome of SCLC patients revealed that the 262G allele is associated with better drug response and longer survival time compared with the 262T allele.</p><p><b>Conclusions:</b> These findings are consistent with the notion that DNA repair is a double-edged sword in cancer and suggest that functional single-nucleotide polymorphisms in <i>ERCC1</i> might serve as simple and less invasive biomarkers for personalized chemotherapy of platinum-based anticancer drugs.</p></div>

Long noncoding RNAs (lncRNAs) are often associated with polysomes, indicating coding potential. However, only a handful of endogenous proteins encoded by putative lncRNAs have been identified and assigned a function. Here, we report the discovery of a putative gastrointestinal-tract-specific lncRNA (LINC00675) that is regulated by the pioneer transcription factor FOXA1 and encodes a conserved small protein of 79 amino acids which we termed FORCP (FOXA1-Regulated Conserved Small Protein). FORCP transcript is undetectable in most cell types but is abundant in well-differentiated colorectal cancer (CRC) cells where it functions to inhibit proliferation, clonogenicity, and tumorigenesis. The epitope-tagged and endogenous FORCP protein predominantly localizes to the endoplasmic reticulum (ER). In response to ER stress, FORCP depletion results in decreased apoptosis. Our findings on the initial characterization of FORCP demonstrate that FORCP is a novel, conserved small protein encoded by a mis-annotated lncRNA that regulates apoptosis and tumorigenicity in well-differentiated CRC cells.