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Roza Teshome,1 Irene Yang,2 Edom Woldetsadik,3 Eshetu Girma,4 Melinda Higgins,2 Jessica Wells2 1Department of Midwifery, School of Nursing & Midwifery, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; 2Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA; 3Department of Oncology, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; 4Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, EthiopiaCorrespondence: Roza Teshome, Tel +251-911028610, Email rozateshome2007@gmail.comBackground: Cervical cancer is one of the leading causes of cancer death in women, even though it is a preventable disease. Most deaths occur in low- and middle-income countries. In addition to early detection and receipt of standard treatments, survivorship is an important component of high quality of care across the cancer continuum.Objective: To assess the survival status of advanced-stage cervical cancer patients after cancer treatment has started.Methods and Materials: A one-year prospective cohort study was employed to assess the survival status of women with advanced stages of cervical cancer. A total of 180 cervical cancer patients were recruited, and the study was conducted from January 10, 2022, to September 20, 2023. Data entry and analysis were done in the SPSS 29 version. Descriptive statistics were used to examine participant characteristics. The Kaplan-Meier procedure and log rank test were used to estimate the duration of survival. Bivariate and multivariate Cox regression analyses were computed for predictor variables with survival status.Results: Patients receiving cancer treatment at FIGO stages IVA and IVB had survived by 56% and 24%, respectively, whereas patients receiving treatment at stages IIB and IIIA had survived by 100%. The estimated mean survival time at one-year follow-up was 5.706 months (95% CI: 3.785– 7.627) for patients with FIGO stage IVB, but 11.537 months (95% CI: 11.199– 11.887) for those with stages II and III (P < 0.001). Women over 60 years old had a 1.5-fold higher risk of death than those under 60 (HR: 1.482, P = 0.040).Conclusion: The one-year cumulative survival rate among advanced-stage cervical cancer patients was 77%. Major factors associated with survival were age, cancer stage, the presence of anemia, and waiting time for treatment.Keywords: survival status, advanced stage, cervical cancer, tikur anbessa specialized hospital, Ethiopia

Roza Teshome,1 Irene Yang,2 Edom Woldetsadik,3 Eshetu Girma,4 Melinda Higgins,2 Jessica Wells2 1Department of Midwifery, School of Nursing & Midwifery, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; 2Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA; 3Department of Oncology, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; 4Department of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, EthiopiaCorrespondence: Roza Teshome, Tel +251-911028610, Email rozateshome2007@gmail.comBackground: The development of health concepts beyond traditional markers of illness and death has made the evaluation of quality of life (QoL) crucial to patient care. Yet, there is little research evaluating the pre- and post-treatment QoL of cervical cancer survivors in Ethiopia.Objective: This study aimed to assess the pre- and post-treatment QoL of women diagnosed with advanced-stage cervical cancer.Methods and Materials: A cohort design was conducted at the Tikur Anbessa Specialized Hospital Oncology Center. A total of 166 cervical cancer patients were recruited consecutively. Data was collected through interviews with standardized questionnaires before and after treatment. The Wilcoxon rank test was used to assess the significant differences in pre-treatment and post-treatment quality of life. Additionally, the Mann-Whitney U-test was also employed. Statistical significance was determined with p-values < 0.05 and a 95% confidence interval.Results: Women who were in stages IVA and IVB were 24.7% and 10.2%, respectively. Both the global health scale (66.67 [47.92– 75] to 83.33 [66.67– 83.33]) and the functional domain QoL (66.67 [40– 80] to 70 [46.67– 86.66]) showed statistically significant improvements from pre-treatment to post-treatment QoL. Women under the age of 45 were found to have higher global health QOL (P < 0.001) and functional domain QOL (P = 0.029). Women presented in stages II and III had comparatively higher global health QoL (P = 0.008) and functional domain QoL (P = 0.021).Conclusion: Global health QOL and the majority of functional quality of life significantly improved following six months of cancer treatment. But there was no discernible change in terms of sexual enjoyment, sexual function, or activity. Age, marital status, the duration since diagnosis, the stage of the cancer, and the presence of comorbidities were the factors that affected the improvement of post-treatment quality of life.Keywords: pre-treatment, post-treatment, quality of life, cervical cancer, Ethiopia

Abstract Recent progress in deep learning has greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues. Pangolin outperforms state-of-the-art methods for predicting RNA splicing on a variety of prediction tasks. Pangolin improves prediction of the impact of genetic variants on RNA splicing, including common, rare, and lineage-specific genetic variation. In addition, Pangolin identifies loss-of-function mutations with high accuracy and recall, particularly for mutations that are not missense or nonsense, demonstrating remarkable potential for identifying pathogenic variants.

Abstract Background Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3′ ends. Most APA occurs within 3′ UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization. Results APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools—TAPAS, QAPA, DaPars2, GETUTR, and APATrap— against 3′-Seq, a specialized RNA-seq protocol that enriches for reads at the 3′ ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3′-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3′-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL). Conclusions We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3′-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.

Abstract Background The vast majority of trait-associated variants identified using genome-wide association studies (GWAS) are noncoding, and therefore assumed to impact gene regulation. However, the majority of trait-associated loci are unexplained by regulatory quantitative trait loci (QTLs). Results We perform a comprehensive characterization of the putative mechanisms by which GWAS loci impact human immune traits. By harmonizing four major immune QTL studies, we identify 26,271 expression QTLs (eQTLs) and 23,121 splicing QTLs (sQTLs) spanning 18 immune cell types. Our colocalization analyses between QTLs and trait-associated loci from 72 GWAS reveals that genetic effects on RNA expression and splicing in immune cells colocalize with 40.4% of GWAS loci for immune-related traits, in many cases increasing the fraction of colocalized loci by two fold compared to previous studies. Notably, we find that the largest contributors of this increase are splicing QTLs, which colocalize on average with 14% of all GWAS loci that do not colocalize with eQTLs. By contrast, we find that cell type-specific eQTLs, and eQTLs with small effect sizes contribute very few new colocalizations. To investigate the 60% of GWAS loci that remain unexplained, we collect H3K27ac CUT&Tag data from rheumatoid arthritis and healthy controls, and find large-scale differences between immune cells from the different disease contexts, including at regions overlapping unexplained GWAS loci. Conclusion Altogether, our work supports RNA splicing as an important mediator of genetic effects on immune traits, and suggests that we must expand our study of regulatory processes in disease contexts to improve functional interpretation of as yet unexplained GWAS loci.

GWAS have identified over 41 susceptibility loci for Parkinson’s disease (PD). Here, the authors integrate PD GWAS summary statistics with transcriptome data from monocytes and DLFPC tissue in a TWAS approach and find 66 significant associations with PD risk highlighting lysosomal and innate immune functions.

Quantification of gene expression levels at the single cell level has revealed that gene expression can vary substantially even across a population of homogeneous cells. However, it is currently unclear what genomic features control variation in gene expression levels, and whether common genetic variants may impact gene expression variation. Here, we take a genome-wide approach to identify expression variance quantitative trait loci (vQTLs). To this end, we generated single cell RNA-seq (scRNA-seq) data from induced pluripotent stem cells (iPSCs) derived from 53 Yoruba individuals. We collected data for a median of 95 cells per individual and a total of 5,447 single cells, and identified 235 mean expression QTLs (eQTLs) at 10% FDR, of which 79% replicate in bulk RNA-seq data from the same individuals. We further identified 5 vQTLs at 10% FDR, but demonstrate that these can also be explained as effects on mean expression. Our study suggests that dispersion QTLs (dQTLs) which could alter the variance of expression independently of the mean can have larger fold changes, but explain less phenotypic variance than eQTLs. We estimate 4,015 individuals as a lower bound to achieve 80% power to detect the strongest dQTLs in iPSCs. These results will guide the design of future studies on understanding the genetic control of gene expression variance.

The bowhead whale (Balaena mysticetus) is estimated to live over 200 years and is possibly the longest-living mammal. These animals should possess protective molecular adaptations relevant to age-related diseases, particularly cancer. Here, we report the sequencing and comparative analysis of the bowhead whale genome and two transcriptomes from different populations. Our analysis identifies genes under positive selection and bowhead-specific mutations in genes linked to cancer and aging. In addition, we identify gene gain and loss involving genes associated with DNA repair, cell-cycle regulation, cancer, and aging. Our results expand our understanding of the evolution of mammalian longevity and suggest possible players involved in adaptive genetic changes conferring cancer resistance. We also found potentially relevant changes in genes related to additional processes, including thermoregulation, sensory perception, dietary adaptations, and immune response. Our data are made available online (http://www.bowhead-whale.org) to facilitate research in this long-lived species.

Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7273 novel coding sequences, including 2442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

Achieving high cell transfection efficiency is essential for various cell types in numerous disease applications. However, the efficient introduction of genes into natural killer (NK) cells remains a challenge. In this study, we proposed a design strategy for delivering exogenous genes into the NK cell line, NK-92, using a modified non-viral gene transfection method. Calcium phosphate/DNA nanoparticles (pDNA-CaP NPs) were prepared using co-precipitation methods and combined with low-voltage pulse electroporation to facilitate NK-92 transfection. The results demonstrated that the developed pDNA-CaP NPs exhibited a uniform diameter of approximately 393.9 nm, a DNA entrapment efficiency of 65.8%, and a loading capacity of 15.9%. Furthermore, at three days post-transfection, both the transfection efficiency and cell viability of NK-92 were significantly improved compared to standalone plasmid DNA (pDNA) electroporation or solely relying on the endocytosis pathway of pDNA-CaP NPs. This study provides valuable insights into a novel approach that combines calcium phosphate nanoparticles with low-voltage electroporation for gene delivery into NK-92 cells, offering potential advancements in cell therapy. [ABSTRACT FROM AUTHOR]