The landscape and clinical relevance of intronic polyadenylation in human cancers.

Intronic polyadenylation (IPA) is an RNA 3' end processing event which has been reported to play important roles in cancer development. However, the comprehensive landscape of IPA events across various cancer types is lacking. Here, we apply IPAFinder to identify and quantify IPA events in 10,383 samples covering all 33 cancer types from The Cancer Genome Atlas (TCGA) project. We totally identify 21,835 IPA events, almost half of which are ubiquitously expressed. We identify 2,761 unique dynamically changed IPA events across cancer types. Furthermore, we observe 8,855 non-redundant clinically relevant IPA events, which could potentially be used as prognostic indicators. Our analysis also reveals that dynamic IPA usage within cancer signaling pathways may affect drug response. Finally, we develop a user-friendly data portal, IPACancer Atlas (http://www.tingni-lab.com/Pancan_IPA/), to search and explore IPAs in cancer.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

The Tumor Microenvironment: Signal Transduction.

In the challenging tumor microenvironment (TME), tumors coexist with diverse stromal cell types. During tumor progression and metastasis, a reciprocal interaction occurs between cancer cells and their environment. These interactions involve ongoing and evolving paracrine and proximal signaling. Intrinsic signal transduction in tumors drives processes such as malignant transformation, epithelial-mesenchymal transition, immune evasion, and tumor cell metastasis. In addition, cancer cells embedded in the tumor microenvironment undergo metabolic reprogramming. Their metabolites, serving as signaling molecules, engage in metabolic communication with diverse matrix components. These metabolites act as direct regulators of carcinogenic pathways, thereby activating signaling cascades that contribute to cancer progression. Hence, gaining insights into the intrinsic signal transduction of tumors and the signaling communication between tumor cells and various matrix components within the tumor microenvironment may reveal novel therapeutic targets. In this review, we initially examine the development of the tumor microenvironment. Subsequently, we delineate the oncogenic signaling pathways within tumor cells and elucidate the reciprocal communication between these pathways and the tumor microenvironment. Finally, we give an overview of the effect of signal transduction within the tumor microenvironment on tumor metabolism and tumor immunity.

Life cycle environmental impact assessment of natural gas distributed energy system.

Natural gas distributed energy is recognized as a pivotal means to enhance energy efficiency and mitigate carbon dioxide emissions through localized energy cascading. Positioned as a key option for advancing the Sustainable Development Goals, this system optimizes energy utilization near end-users. While maximizing energy efficiency, it is imperative to address potential environmental challenges. A thorough, comprehensive environmental assessment, facilitated by the life cycle assessment method, proves instrumental in meeting this standard. Employing this method enables an intuitive grasp of the environmental strengths and weaknesses inherent in natural gas distributed energy within the power structure. This insight serves as a foundation for informed project decision-making, fostering the growth of the industry. We selected six environmental impact assessment categories based on the CML 2001 method, and conducted the life cycle analysis across four stages. China's inaugural natural gas distributed energy demonstration project was chosen as a model case, and an environmental impact assessment inventory was established, utilizing survey data and literature for comprehensive data collection and analysis. Results from case testing yield environmental impact assessment outcomes, with a specific sensitivity analysis for stages with notable environmental impact factors. The study underscores that the operation phase has the highest environmental impact, comprising 78.37% of the total combined environmental impact, followed by the fuel production phase. Comparative analyses with coal-fired and conventional natural gas power generation, based on dimensionless literature data, reveal that abiotic resources depletion potential is the primary contributor to the environmental impact of 1 kWh of electricity product, constituting 52.76% of the total impact value, followed by global warming potential. Concrete strategies have been outlined for decision-making in both the operational and planning phases of natural gas distributed energy projects. The strengthening of policies is pinpointed towards grid connection and scale expansion.

A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study.

Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3' untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3' untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.

Characterization and optimization of 5´ untranslated region containing poly-adenine tracts in Kluyveromyces marxianus using machine-learning model.

BACKGROUND: The 5´ untranslated region (5´ UTR) plays a key role in regulating translation efficiency and mRNA stability, making it a favored target in genetic engineering and synthetic biology. A common feature found in the 5´ UTR is the poly-adenine (poly(A)) tract. However, the effect of 5´ UTR poly(A) on protein production remains controversial. Machine-learning models are powerful tools for explaining the complex contributions of features, but models incorporating features of 5´ UTR poly(A) are currently lacking. Thus, our goal is to construct such a model, using natural 5´ UTRs from Kluyveromyces marxianus, a promising cell factory for producing heterologous proteins. RESULTS: We constructed a mini-library consisting of 207 5´ UTRs harboring poly(A) and 34 5´ UTRs without poly(A) from K. marxianus. The effects of each 5´ UTR on the production of a GFP reporter were evaluated individually in vivo, and the resulting protein abundance spanned an approximately 450-fold range throughout. The data were used to train a multi-layer perceptron neural network (MLP-NN) model that incorporated the length and position of poly(A) as features. The model exhibited good performance in predicting protein abundance (average R2 = 0.7290). The model suggests that the length of poly(A) is negatively correlated with protein production, whereas poly(A) located between 10 and 30 nt upstream of the start codon (AUG) exhibits a weak positive effect on protein abundance. Using the model as guidance, the deletion or reduction of poly(A) upstream of 30 nt preceding AUG tended to improve the production of GFP and a feruloyl esterase. Deletions of poly(A) showed inconsistent effects on mRNA levels, suggesting that poly(A) represses protein production either with or without reducing mRNA levels. CONCLUSION: The effects of poly(A) on protein production depend on its length and position. Integrating poly(A) features into machine-learning models improves simulation accuracy. Deleting or reducing poly(A) upstream of 30 nt preceding AUG tends to enhance protein production. This optimization strategy can be applied to enhance the yield of K. marxianus and other microbial cell factories.

Pan-Cancer Profiling of Intron Retention and Its Clinical Significance in Diagnosis and Prognosis.

Alternative splicing can produce transcripts that affect cancer development and thus shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been studied less in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention inside the 5'UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification in certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets.

The Role of Tumor Metabolic Reprogramming in Tumor Immunity.

The occurrence and development of tumors require the metabolic reprogramming of cancer cells, namely the alteration of flux in an autonomous manner via various metabolic pathways to meet increased bioenergetic and biosynthetic demands. Tumor cells consume large quantities of nutrients and produce related metabolites via their metabolism; this leads to the remodeling of the tumor microenvironment (TME) to better support tumor growth. During TME remodeling, the immune cell metabolism and antitumor immune activity are affected. This further leads to the escape of tumor cells from immune surveillance and therefore to abnormal proliferation. This review summarizes the regulatory functions associated with the abnormal biosynthesis and activity of metabolic signaling molecules during the process of tumor metabolic reprogramming. In addition, we provide a comprehensive description of the competition between immune cells and tumor cells for nutrients in the TME, as well as the metabolites required for tumor metabolism, the metabolic signaling pathways involved, and the functionality of the immune cells. Finally, we summarize current research targeted at the development of tumor immunotherapy. We aim to provide new concepts for future investigations of the mechanisms underlying the metabolic reprogramming of tumors and explore the association of these mechanisms with tumor immunity.

Downregulation of apoptotic repressor AVEN exacerbates cardiac injury after myocardial infarction.

Myocardial infarction (MI) is a leading cause of heart failure (HF), associated with morbidity and mortality worldwide. As an essential part of gene expression regulation, the role of alternative polyadenylation (APA) in post-MI HF remains elusive. Here, we revealed a global, APA-mediated, 3' untranslated region (3' UTR)-lengthening pattern in both human and murine post-MI HF samples. Furthermore, the 3' UTR of apoptotic repressor gene, AVEN, is lengthened after MI, contributing to its downregulation. AVEN knockdown increased cardiomyocyte apoptosis, whereas restoration of AVEN expression substantially improved cardiac function. Mechanistically, AVEN 3' UTR lengthening provides additional binding sites for miR-30b-5p and miR-30c-5p, thus reducing AVEN expression. Additionally, PABPN1 (poly(A)-binding protein 1) was identified as a potential regulator of AVEN 3' UTR lengthening after MI. Altogether, our findings revealed APA as a unique mechanism regulating cardiac injury in response to MI and also indicated that the APA-regulated gene, AVEN, holds great potential as a critical therapeutic target for treating post-MI HF.

Strategies adopted by Salmonella to survive in host: a review.

Salmonella, a Gram-negative bacterium that infects humans and animals, causes diseases ranging from gastroenteritis to severe systemic infections. Here, we discuss various strategies used by Salmonella against host cell defenses. Epithelial cell invasion largely depends on a Salmonella pathogenicity island (SPI)-1-encoded type 3 secretion system, a molecular syringe for injecting effector proteins directly into host cells. The internalization of Salmonella into macrophages is primarily driven by phagocytosis. After entering the host cell cytoplasm, Salmonella releases many effectors to achieve intracellular survival and replication using several secretion systems, primarily an SPI-2-encoded type 3 secretion system. Salmonella-containing vacuoles protect Salmonella from contacting bactericidal substances in epithelial cells and macrophages. Salmonella modulates the immunity, metabolism, cell cycle, and viability of host cells to expand its survival in the host, and the intracellular environment of Salmonella-infected cells promotes its virulence. This review provides insights into how Salmonella subverts host cell defenses for survival.

Approximate estimation of cell-type resolution transcriptome in bulk tissue through matrix completion.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for uncovering cellular heterogeneity. However, the high costs associated with this technique have rendered it impractical for studying large patient cohorts. We introduce ENIGMA (Deconvolution based on Regularized Matrix Completion), a method that addresses this limitation through accurately deconvoluting bulk tissue RNA-seq data into a readout with cell-type resolution by leveraging information from scRNA-seq data. By employing a matrix completion strategy, ENIGMA minimizes the distance between the mixture transcriptome obtained with bulk sequencing and a weighted combination of cell-type-specific expression. This allows the quantification of cell-type proportions and reconstruction of cell-type-specific transcriptomes. To validate its performance, ENIGMA was tested on both simulated and real datasets, including disease-related tissues, demonstrating its ability in uncovering novel biological insights.

Changes in expression levels of erythrocyte and immune-related genes are associated with high altitude polycythemia.

BACKGROUND: As a chronic mountain sickness(CMS) with the highest incidence and the greatest harm, the pathogenesis of high altitude polycythemia (HAPC) is still not fully understood. METHODS: 37 HAPC patients and 42 healthy subjects were selected from plateau, and peripheral venous blood samples were collected for transcriptome sequencing on Illumina NovaSeq platform. The sequenced data were analyzed by bioinformatics and phenotypic association analysis. RESULTS: The results showed significant differences in multiple clinical indicators including RBC and HGB et al. existed between HAPC and control. Based on the RNA-seq data, 550 genes with significant differential expression were identified in HAPC patients. GO and KEGG pathway enrichment analysis showed that the up-regulated genes were mainly enriched in processes such as erythrocyte differentiation and development and homeostasis of number of cells, while the down-regulated genes were mainly enriched in categories such as immunoglobulin production, classical pathway of complement activation and other biological processes. The coupling analysis of differential expression genes(DEGs) and pathological phenotypes revealed that 91 DEGs were in close correlation with in the phenotype of red blood cell volume distribution (width-CV and width-SD), and they were all up-regulated in HAPC and involved in the process of erythrocyte metabolism. Combined with the functional annotation of DEGs and literature survey, we found that the expression of several potential genes might be responsible for pathogenesis of HAPC. Besides, cell type deconvolution analysis result suggested that the changes in the number of some immune cell types was significantly lower in HAPC patients than control, implying the autoimmune level of HAPC patients was affected to a certain extent. CONCLUSION: This study provides an important data source for understanding the pathogenesis and screening pathogenic genes of HAPC. We found for the first time that there was a significant correlation between HAPC and the pathological phenotype of width-CV and width-SD, wherein the enriched genes were all up-regulated expressed and involved in the process of erythrocyte metabolism. Although the role of these genes needs to be further studied, the candidate genes can provide a starting point for functionally pinning down the underlying mechanism of HAPC.

Low level of ARID1A contributes to adaptive immune resistance and sensitizes triple-negative breast cancer to immune checkpoint inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) shed new light on triple-negative breast cancer (TNBC), but only a minority of patients demonstrate response. Therefore, adaptive immune resistance (AIR) needs to be further defined to guide the development of ICI regimens. METHODS: Databases, including The Cancer Genome Atlas, Gene Ontology Resource, University of California Santa Cruz Genome Browser, and Pubmed, were used to screen epigenetic modulators, regulators for CD8+ T cells, and transcriptional regulators of programmed cell death-ligand 1 (PD-L1). Human peripheral blood mononuclear cell (Hu-PBMC) reconstruction mice were adopted for xenograft transplantation. Tumor specimens from a TNBC cohort and the clinical trial CTR20191353 were retrospectively analyzed. RNA-sequencing, Western blotting, qPCR and immunohistochemistry were used to assess gene expression. Coculture assays were performed to evaluate the regulation of TNBC cells on T cells. Chromatin immunoprecipitation and transposase-accessible chromatin sequencing were used to determine chromatin-binding and accessibility. RESULTS: The epigenetic modulator AT-rich interaction domain 1A (ARID1A) gene demonstrated the highest expression association with AIR relative to other epigenetic modulators in TNBC patients. Low ARID1A expression in TNBC, causing an immunosuppressive microenvironment, promoted AIR and inhibited CD8+ T cell infiltration and activity through upregulating PD-L1. However, ARID1A did not directly regulate PD-L1 expression. We found that ARID1A directly bound the promoter of nucleophosmin 1 (NPM1) and that low ARID1A expression increased NPM1 chromatin accessibility as well as gene expression, further activating PD-L1 transcription. In Hu-PBMC mice, atezolizumab demonstrated the potential to reverse ARID1A deficiency-induced AIR in TNBC by reducing tumor malignancy and activating anti-tumor immunity. In CTR20191353, ARID1A-low patients derived more benefit from pucotenlimab compared to ARID1A-high patients. CONCLUSIONS: In AIR epigenetics, low ARID1A expression in TNBC contributed to AIR via the ARID1A/NPM1/PD-L1 axis, leading to poor outcome but sensitivity to ICI treatment.

Juxtaposing Sub-Sahara Africa's energy poverty and renewable energy potential.

Recently, the International Energy Agency (IEA) released a comprehensive roadmap for the global energy sector to achieve net-zero emission by 2050. Considering the sizeable share of (Sub-Sahara) Africa in the global population, the attainment of global energy sector net-zero emission is practically impossible without a commitment from African countries. Therefore, it is important to study and analyze feasible/sustainable ways to solve the energy/electricity poverty in Africa. In this paper, the energy poverty in Africa and the high renewable energy (RE) potential are reviewed. Beyond this, the generation of electricity from the abundant RE potential in this region is analyzed in hourly timestep. This study is novel as it proposes a Sub-Sahara Africa (SSA) central grid as one of the fastest/feasible solutions to the energy poverty problem in this region. The integration of a sizeable share of electric vehicles with the proposed central grid is also analyzed. This study aims to determine the RE electricity generation capacities, economic costs, and supply strategies required to balance the projected future electricity demand in SSA. The analysis presented in this study is done considering 2030 and 2040 as the targeted years of implementation. EnergyPLAN simulation program is used to simulate/analyze the generation of electricity for the central grid. The review of the energy poverty in SSA showed that the electricity access of all the countries in this region is less than 100%. The analysis of the proposed central RE grid system is a viable and sustainable option, however, it requires strategic financial planning for its implementation. The cheapest investment cost from all the case scenarios in this study is $298 billion. Considering the use of a single RE technology, wind power systems implementation by 2030 and 2040 are the most feasible options as they have the least economic costs. Overall, the integration of the existing/fossil-fueled power systems with RE technologies for the proposed central grid will be the cheapest/easiest pathway as it requires the least economic costs. While this does not require the integration of storage systems, it will help the SSA countries reduce their electricity sector carbon emission by 56.6% and 61.8% by 2030 and 2040 respectively.

Tox4 regulates transcriptional elongation and reinitiation during murine T cell development.

HMG protein Tox4 is a regulator of PP1 phosphatases with unknown function in development. Here we show that Tox4 conditional knockout in mice reduces thymic cellularity, partially blocks T cell development, and decreases ratio of CD8 to CD4 through decreasing proliferation and increasing apoptosis of CD8 cells. In addition, single-cell RNA-seq discovered that Tox4 loss also impairs proliferation of the fast-proliferating double positive (DP) blast population within DP cells in part due to downregulation of genes critical for proliferation, notably Cdk1. Moreover, genes with high and low expression level are more dependent on Tox4 than genes with medium expression level. Mechanistically, Tox4 may facilitate transcriptional reinitiation and restrict elongation in a dephosphorylation-dependent manner, a mechanism that is conserved between mouse and human. These results provide insights into the role of TOX4 in development and establish it as an evolutionarily conserved regulator of transcriptional elongation and reinitiation.

[Contamination status and exposure risk of mycotoxins in Coicis Semen].

By investigating the contamination status and predicting the exposure risk of mycotoxin in Coicis Semen, we aim to provide guidance for the safety supervision of Chinese medicinal materials and the formulation(revision) of mycotoxin limit standards. The content of 14 mycotoxins in the 100 Coicis Semen samples collected from five major markets of Chinese medicinal materials in China was determined by UPLC-MS/MS. The probability evaluation model based on Monte Carlo simulation method was established after Chi-square test and One-way ANOVA of the sample contamination data. Health risk assessment was performed on the basis of margin of exposure(MOE) and margin of safety(MOS). The results showed that zearalenone(ZEN), aflatoxin B_1(AFB_1), deoxynivalenol(DON), sterigmatocystin(ST), and aflatoxin B_2(AFB_2) in the Coicis Semen samples had the detection rates of 84%, 75%, 36%, 19%, and 18%, and the mean contamination levels of 117.42, 4.78, 61.16, 6.61, and 2.13 µg·kg~(-1), respectively. According to the limit standards in the Chinese Pharmacopoeia(2020 edition), AFB_1, AFs and ZEN exceeded the standards to certain extents, with the over-standard rates of 12.0%, 9.0%, and 6.0%, respectively. The exposure risks of Coicis Semen to AFB_1, AFB2, ST, DON, and ZEN were low, while 86% of the samples were contaminated with two or more toxins, which needs more attention. It is suggested that the research on the combined toxicity of different mycotoxins should be strengthened to accelerate the cumulative exposure assessment of mixed contaminations and the formulation(revision) of toxin limit standards.

Structural insights into RNase J that plays an essential role in Mycobacterium tuberculosis RNA metabolism.

Ribonucleases (RNases) are responsible for RNA metabolism. RNase J, the core enzyme of the RNA degradosome, plays an essential role in global mRNA decay. Emerging evidence showed that the RNase J of Mycobacterium tuberculosis (Mtb-RNase J) could be an excellent target for treating Mtb infection. Here, crystal structures of Mtb-RNase J in apo-state and complex with the single-strand RNA reveal the conformational change upon RNA binding and hydrolysis. Mtb-RNase J forms an active homodimer through the interactions between the ß-CASP and the ß-lactamase domain. Knockout of RNase J slows the growth rate and changes the colony morphologies and cell length in Mycobacterium smegmatis, which is restored by RNase J complementation. Finally, RNA-seq analysis shows that the knockout strain significantly changes the expression levels of 49 genes in metabolic pathways. Thus, our current study explores the structural basis of Mtb-RNase J and might provide a promising candidate in pharmacological treatment for tuberculosis.

The landscape of cryptic antisense transcription in human cancers reveals an oncogenic noncoding RNA in lung cancer.

Cryptic transcription initiation has been previously linked to activation of oncogenic transcripts. However, the prevalence and impact of cryptic antisense transcription from the opposite strand of protein-coding genes were mostly unknown in cancer. Applying a robust computational pipeline to publicly available transcriptome and epigenome datasets, we identified hundreds of previously unannotated cryptic antisense polyadenylated transcripts (CAPTs) that were enriched in tumor samples. We showed that the activation of cryptic antisense transcription was associated with increased chromatin accessibility and active histone marks. Accordingly, we found that many of the antisense transcripts were inducible by treatment of epigenetic drugs. Moreover, CRISPR-mediated epigenetic editing assays revealed that transcription of a noncoding RNA LRRK1-CAPT promoted LUSC cell proliferation, suggesting its oncogenic role. Our findings largely expand our understanding of cancer-associated transcription events, which may facilitate the development of novel strategies for cancer diagnosis and treatment.

New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis.

Introduction: Brain metastases (BM) from lung cancer are heterogeneous, and accurate prognosis is required for effective treatment strategies. This study aimed to identify prognostic factors and develop a prognostic system exclusively for epidermal growth factor receptor (EGFR)-mutated lung cancer BM. Methods: In total, 173 patients with EGFR-mutated lung cancer from two hospitals who developed BM and received tyrosine kinase inhibitor (TKI) and brain radiation therapy (RT) were included. Univariate and multivariate analyses were performed to identify significant EGFR-mutated BM prognostic factors to construct a new EGFR recursive partitioning analysis (RPA) prognostic index. The predictive discrimination of five prognostic scoring systems including RPA, diagnosis-specific prognostic factors indexes (DS-GPA), basic score for brain metastases (BS-BM), lung cancer using molecular markers (lung-mol GPA) and EGFR-RPA were analyzed using log-rank test, concordance index (C-index), and receiver operating characteristic curve (ROC). The potential predictive factors in the multivariable analysis to construct a prognostic index included Karnofsky performance status, BM at initial lung cancer diagnosis, BM progression after TKI, EGFR mutation type, uncontrolled primary tumors, and number of BM. Results and discussion: In the log-rank test, indices of RPA, DS-GPA, lung-mol GPA, BS-BM, and EGFR-RPA were all significant predictors of overall survival (OS) (p ≤ 0.05). The C-indices of each prognostic score were 0.603, 0.569, 0.613, 0.595, and 0.671, respectively; The area under the curve (AUC) values predicting 1-year OS were 0.565 (p=0.215), 0.572 (p=0.174), 0.641 (p=0.007), 0.585 (p=0.106), and 0.781 (p=0.000), respectively. Furthermore, EGFR-RPA performed better in terms of calibration than other prognostic indices.BM progression after TKI and EGFR mutation type were specific prognostic factors for EGFR-mutated lung cancer BM. EGFR-RPA was more precise than other models, and useful for personal treatment.

Single-cell RNA-seq uncovers dynamic processes orchestrated by RNA-binding protein DDX43 in chromatin remodeling during spermiogenesis.

Mammalian spermatogenesis shows prominent chromatin and transcriptomic switches in germ cells, but it is unclear how such dynamics are controlled. Here we identify RNA helicase DDX43 as an essential regulator of the chromatin remodeling process during spermiogenesis. Testis-specific Ddx43 knockout mice show male infertility with defective histone-to-protamine replacement and post-meiotic chromatin condensation defects. The loss of its ATP hydrolysis activity by a missense mutation replicates the infertility phenotype in global Ddx43 knockout mice. Single-cell RNA sequencing analyses of germ cells depleted of Ddx43 or expressing the Ddx43 ATPase-dead mutant reveals that DDX43 regulates dynamic RNA regulatory processes that underlie spermatid chromatin remodeling and differentiation. Transcriptomic profiling focusing on early-stage spermatids combined with enhanced crosslinking immunoprecipitation and sequencing further identifies Elfn2 as DDX43-targeted hub gene. These findings illustrate an essential role for DDX43 in spermiogenesis and highlight the single-cell-based strategy to dissect cell-state-specific regulation of male germline development.