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Abstract Parkinson's disease (PD) involves multiple forms of neuronal cell death, but the dominant pathway involved in disease progression remains unclear. This study employed RNA sequencing (RNA-seq) of brain tissue to explore gene expression patterns across different stages of PD. Using the Scaden deep learning algorithm, we predicted neurocyte subtypes and modelled dynamic interactions for five classic cell death pathways to identify the predominant routes of neuronal death during PD progression. Our cell type-specific analysis revealed an increasing shift towards necroptosis, which was strongly correlated with nitric oxide synthase (NOS) expression across most neuronal subtypes. In vitro experiments confirmed that nitric oxide (NO) is a key mediator of necroptosis, leading to nuclear shrinkage and decreased mitochondrial membrane potential via phosphorylation of the PIP1/PIP3/MLKL signalling cascade. Importantly, specific necroptosis inhibitors significantly mitigated neuronal damage in both in vitro and in vivo PD models. Further analysis revealed that NO-mediated necroptosis is prevalent in early-onset Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS) and across multiple brain regions but not in brain tumours. Our findings suggest that NO-mediated necroptosis is a critical pathway in PD and other neurodegenerative disorders, providing potential targets for therapeutic intervention.

Abstract Background Checkpoint blockade immunotherapy, represented by PD-1 or PD-L1 antibody treatment, has been of tremendous success in clinical practice. However, the low clinical response rate and lack of biomarkers for prediction of the immune response limit the clinical application of anti-PD-1 immunotherapy. Our recent work showed that a combination of low-dose decitabine and PD-1-ab significantly improved the complete response (CR) rate of cHL patients from 32 to 71%, which indicates that there is a significant correlation between epigenetic regulation and the clinical response to immunotherapy. Methods We recruited two groups of Hodgkin lymphoma patients who were treated with anti-PD-1 and DAC+anti-PD-1. CD8+ T cells were isolated from the patients' peripheral blood, DNA methylation was analyzed by EPIC, the expression profile was analyzed by RNA-seq, and multigroup analysis was performed with IPA and GSEA functional annotations. We explored the effect of DAC on the function of CD8+ T cells in the blood, spleen, tumor and lymph nodes using a mouse model. Furthermore, we explored the function of Tils in the tumor microenvironment. Then, we constructed Runx3-knockout mice to confirm the T-cell-specific function of Runx3 in CD8+ T cells and analyzed various subtypes of T cells and cytokines using mass cytometry (CyTOF). Results Multiomics analysis identified that DNA methylation reprogramming of Runx3 was a crucial mediator of CD8+ T-cell function. Multiomics data showed that reversal of methylation of the Runx3 promoter promoted the infiltration of CD8+ TILs and mitigated the exhaustion of CD8+ T cells. Furthermore, experiments on tissue-specific Runx3-knockout mice showed that Runx3 deficiency reduced CD8+ T infiltration and the differentiation of effector T and memory T cells. Furthermore, Runx3 deficiency significantly decreased CCR3 and CCR5 levels. Immunotherapy experiments in Runx3 conditional knockout mice showed that DAC could not reverse the resistance of anti-PD-1 in the absence of Runx3. Moreover, both our clinical data and data from TISIDB showed that Runx3 could be a potential biomarker for immunotherapy to predict the clinical response rate. Conclusion We demonstrate that the DNA methylation of Runx3 plays a critical role in CD8+ T-cell infiltration and differentiation during decitabine-primed PD-1-ab immunotherapy, which provides a supporting mechanism for the essential role of epiregulation in immunotherapy.

BackgroundGround-glass opacities (GGOs) appearing in computed tomography (CT) scans may indicate potential lung malignancy. Proper management of GGOs based on their features can prevent the development of lung cancer. Electronic health records are rich sources of information on GGO nodules and their granular features, but most of the valuable information is embedded in unstructured clinical notes. ObjectiveWe aimed to develop, test, and validate a deep learning–based natural language processing (NLP) tool that automatically extracts GGO features to inform the longitudinal trajectory of GGO status from large-scale radiology notes. MethodsWe developed a bidirectional long short-term memory with a conditional random field–based deep-learning NLP pipeline to extract GGO and granular features of GGO retrospectively from radiology notes of 13,216 lung cancer patients. We evaluated the pipeline with quality assessments and analyzed cohort characterization of the distribution of nodule features longitudinally to assess changes in size and solidity over time. ResultsOur NLP pipeline built on the GGO ontology we developed achieved between 95% and 100% precision, 89% and 100% recall, and 92% and 100% F1-scores on different GGO features. We deployed this GGO NLP model to extract and structure comprehensive characteristics of GGOs from 29,496 radiology notes of 4521 lung cancer patients. Longitudinal analysis revealed that size increased in 16.8% (240/1424) of patients, decreased in 14.6% (208/1424), and remained unchanged in 68.5% (976/1424) in their last note compared to the first note. Among 1127 patients who had longitudinal radiology notes of GGO status, 815 (72.3%) were reported to have stable status, and 259 (23%) had increased/progressed status in the subsequent notes. ConclusionsOur deep learning–based NLP pipeline can automatically extract granular GGO features at scale from electronic health records when this information is documented in radiology notes and help inform the natural history of GGO. This will open the way for a new paradigm in lung cancer prevention and early detection.

Abstract The recent pandemic of variants of concern (VOC) of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) highlights the need for innovative anti‐SARS‐CoV‐2 approaches in addition to vaccines and antiviral therapeutics. Here, we demonstrate that a CRISPR‐Cas13‐based strategy against SARS‐CoV‐2 can effectively degrade viral RNA. First, we conducted a cytological infection experiment, screened CRISPR‐associated RNAs (crRNAs) targeting conserved regions of viruses, and used an in vitro system to validate functional crRNAs. Reprogrammed Cas13d effectors targeting NSP13, NSP14, and nucleocapsid transcripts achieved >99% silencing efficiency in human cells which are infected with coronavirus 2, including the emerging variants in the last 2 years, B.1, B.1.1.7 (Alpha), D614G B.1.351 (Beta), and B.1.617 (Delta). Furthermore, we conducted bioinformatics data analysis. We collected the sequence information of COVID‐19 and its variants from China, and phylogenetic analysis revealed that these crRNA oligos could target almost 100% of the SARS‐CoV family, including the emerging new variant, Omicron. The reprogrammed Cas13d exhibited high specificity, efficiency, and rapid deployment properties; therefore, it is promising for antiviral drug development. This system could possibly be used to protect against unexpected SARS‐CoV‐2 variants carrying multiple mutations.

Abstract The changes in circulating tumor DNA (ctDNA) methylation are believed to be early events in breast cancer initiation, which makes them suitable as promising biomarkers for early diagnosis. However, applying ctDNA in breast cancer early diagnosis remains highly challenging due to the contamination of background DNA from blood and low DNA methylation signals. Here, we report an improved way to extract ctDNA, reduce background contamination, and build a whole‐genome bisulfite sequencing (WGBS) library from different stages of breast cancer. We first compared the DNA methylation data of 74 breast cancer patients with those of seven normal controls to screen candidate methylation CpG site biomarkers for breast cancer diagnosis. The obtained 26 candidate ctDNA methylation biomarkers produced high accuracy in breast cancer patients (area under the curve [AUC] = 0.889; sensitivity: 100%; specificity: 75%). Furthermore, we revealed potential ctDNA methylated CpG sites for detecting early‐stage breast cancer (AUC = 0.783; sensitivity: 93.44%; specificity: 50%). In addition, different subtypes of breast cancer could be well distinguished by the ctDNA methylome, which was obtained through our improved ctDNA‐WGBS method. Overall, we identified high specificity and sensitivity breast cancer‐specific methylation CpG site biomarkers, and they will be expected to have the potential to be translated to clinical practice.

Abstract Background Cancer cell–specific variation and circulating tumour DNA (ctDNA) methylation are promising biomarkers for non‐invasive cancer detection and molecular classification. Nevertheless, the applications of ctDNA to the early detection and screening of cancer remain highly challenging due to the scarcity of cancer cell–specific ctDNA, the low signal‐to‐noise ratio of DNA variation, and the lack of non‐locus‐specific DNA methylation technologies. Methods We enrolled three cohorts of breast cancer (BC) patients from two hospitals in China (BC: n = 123; healthy controls: n = 40). We developed a ctDNA whole‐genome bisulfite sequencing technology employing robust trace ctDNA capture from up to 200 μL plasma, mini‐input (1 ng) library preparation, unbiased genome‐wide coverage and comprehensive computational methods. Results A diagnostic signature comprising 15 ctDNA methylation markers exhibited high accuracy in the early (area under the curve [AUC] of 0.967) and advanced (AUC of 0.971) BC stages in multicentre patient cohorts. Furthermore, we revealed a ctDNA methylation signature that discriminates estrogen receptor status (Training set: AUC of 0.984 and Test set: AUC of 0.780). Different cancer types, including hepatocellular carcinoma and lung cancer, could also be well distinguished. Conclusions Our study provides a toolset to generate unbiased whole‐genome ctDNA methylomes with a minimal amount of plasma to develop highly specific and sensitive biomarkers for the early diagnosis and molecular subtyping of cancer.

De novo DNA methylation has been associated with T cell exhaustion in cancer immunotherapy. Here the authors show that the pre-treatment of CD19 CAR-T cells with the DNA methyltransferase inhibitor decitabine limits exhaustion and confers enhanced proliferative, effector and memory properties upon antigen exposure, with improved tumor control.

BackgroundPseudohypoaldosteronism (PHA) diseases are difficult to diagnose because symptoms are often non-specific and an in-depth pathogenesis study is still lacking.Case PresentationWe present the case of a 19-day-old neonate who presented with unexplained recurrent hyperkalaemia, hypovolemia and metabolic acidosis, whose parents did not have significant clinical disease characteristics. Whole-exome sequencing was performed to confirm the disease and genetic pattern of the neonate. Sanger sequencing was performed to identify the mutation sites. Secondary structure comparisons and 3D model construction were used to predict changes in protein structure. Two novel frameshift mutations in the SCNN1B gene were identified (c.1290delA and c.1348_1361del), which resulted in amino acid synthesis termination (p.Gln431ArgfsTer2 and p.Thr451AspfsTer6). Considering the clinical phenotype and genetic analysis, this case was finally identified as a PHA type I disease. Genetic analysis showed that the neonate suffered complex heterozygosity in the SCNN1B gene inherited from the parents, which is passed on in an autosomal recessive inheritance pattern. These two deleterious mutations resulted in an incomplete protein 3D structure.ConclusionsOur results have confirmed the associations of mutations in the SCNN1B gene with recurrent hyperkalaemia, which can cause severe PHA type I disease, meanwhile suggested clinical attention should be paid when persistent recurrent hyperkalemia is accompanied by these types of mutations.

Abstract Background Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) like erlotinib are effective for treating patients with EGFR mutant lung cancer; however, drug resistance inevitably emerges. Approaches to combine immunotherapies and targeted therapies to overcome or delay drug resistance have been hindered by limited knowledge of the effect of erlotinib on tumor-infiltrating immune cells. Methods Using mouse models, we studied the immunological profile of mutant EGFR-driven lung tumors before and after erlotinib treatment. Results We found that erlotinib triggered the recruitment of inflammatory T cells into the lungs and increased maturation of alveolar macrophages. Interestingly, this phenotype could be recapitulated by tumor regression mediated by deprivation of the EGFR oncogene indicating that tumor regression alone was sufficient for these immunostimulatory effects. We also found that further efforts to boost the function and abundance of inflammatory cells, by combining erlotinib treatment with anti-PD-1 and/or a CD40 agonist, did not improve survival in an EGFR-driven mouse model. Conclusions Our findings lay the foundation for understanding the effects of TKIs on the tumor microenvironment and highlight the importance of investigating targeted and immuno-therapy combination strategies to treat EGFR mutant lung cancer.

The DNA methylation of human offspring can change due to the use of assisted reproductive technology (ART). In order to find the differentially methylated regions (DMRs) in ART newborns, cord blood maternal cell contamination and parent DNA methylation background, which will add noise to the real difference, must be removed. We analyzed newborns’ heel blood from six families to identify the DMRs between ART and natural pregnancy newborns, and the genetic model of methylation was explored, meanwhile we analyzed 32 samples of umbilical cord blood of infants born with ART and those of normal pregnancy to confirm which differences are consistent with cord blood data. The DNA methylation level was lower in ART-assisted offspring at the whole genome-wide level. Differentially methylated sites, DMRs, and cord blood differentially expressed genes were enriched in the important pathways of the immune system and nervous system, the genetic patterns of DNA methylation could be changed in the ART group. A total of three imprinted genes and 28 housekeeping genes which were involved in the nervous and immune systems were significant different between the two groups, six of them were detected both in heel blood and cord blood. We concluded that there is an ART-specific DNA methylation pattern involved in neuro- and immune-system pathways of human ART neonates, providing an epigenetic basis for the potential long-term health risks in ART-conceived neonates.

Metastasis is a major clinical challenge for cancer treatment. Emerging evidence suggests that aberrant epigenetic modifications contribute significantly to tumor formation and progression. However, the drivers and roles of such epigenetic changes in tumor metastasis are still poorly understood. Using bioinformatic analysis of human breast cancer gene-expression data sets, we identified histone demethylase RBP2 as a putative mediator of metastatic progression. By using both human breast cancer cells and genetically engineered mice, we demonstrated that RBP2 is critical for breast cancer metastasis to the lung in multiple in vivo models. Mechanistically, RBP2 promotes metastasis as a pleiotropic positive regulator of many metastasis genes, including TNC. In addition, RBP2 loss suppresses tumor formation in MMTV-neu transgenic mice. These results suggest that therapeutic targeting of RBP2 is a potential strategy for inhibition of tumor progression and metastasis.

Our results showed that, at the same BMI level, Uygurs have greater WHR values, abdominal visceral fat content, and diabetes risks than Kazaks. In addition, values of HDL-C in Uygur subjects were lower than those in Kazak subjects, and values of creatinine, uric acid, diastolic blood pressure, blood glucose, and fructosamine in Uygur male subjects were lower than those in Kazak male subjects. In contrast, systolic blood pressure values in Uygur subjects were greater than those in Kazak subjects, and blood glucose values were greater in Uygur female subjects than in Kazak female subjects. Additionally, in Uygurs, visceral adipose tissue expression levels of TBX1 and TCF21 were greater in obesity group than in normal and T2DM groups and lower in T2DM group than in normal group (P

MicroRNAs (miRNAs) have been found to regulate gene expression across eukaryotic species, but the function of most miRNA genes remains unknown. Here we describe how the analysis of the expression patterns of a well-conserved miRNA gene, mir-57, at cellular resolution for every minute during early development of Caenorhabditis elegans provided key insights in understanding its function. Remarkably, mir-57 expression shows strong positional bias but little tissue specificity, a pattern reminiscent of Hox gene function. Despite the minor defects produced by a loss of function mutation, overexpression of mir-57 causes dramatic posterior defects, which also mimic the phenotypes of mutant alleles of a posterior Hox gene, nob-1, an Abd homolog. More importantly, nob-1 expression is found in the same two posterior AB sublineages as those expressing mir-57 but with an earlier onset. Intriguingly, nob-1 functions as an activator for mir-57 expression; it is also a direct target of mir-57. In agreement with this, loss of mir-57 function partially rescues the nob-1 allele defects, indicating a negative feedback regulatory loop between the miRNA and Hox gene to provide positional cues. Given the conservation of the miRNA and Hox gene, the regulatory mechanism might be broadly used across species. The strategy used here to explore mir-57 function provides a path to dissect the regulatory relationship between genes.

Genotyping platforms such as single nucleotide polymorphism (SNP) arrays are powerful tools to study genomic aberrations in cancer samples. Allele specific information from SNP arrays provides valuable information for interpreting copy number variation (CNV) and allelic imbalance including loss-of-heterozygosity (LOH) beyond that obtained from the total DNA signal available from array comparative genomic hybridization (aCGH) platforms. Several algorithms based on hidden Markov models (HMMs) have been designed to detect copy number changes and copy-neutral LOH making use of the allele information on SNP arrays. However heterogeneity in clinical samples, due to stromal contamination and somatic alterations, complicates analysis and interpretation of these data.We have developed MixHMM, a novel hidden Markov model using hidden states based on chromosomal structural aberrations. MixHMM allows CNV detection for copy numbers up to 7 and allows more complete and accurate description of other forms of allelic imbalance, such as increased copy number LOH or imbalanced amplifications. MixHMM also incorporates a novel sample mixing model that allows detection of tumor CNV events in heterogeneous tumor samples, where cancer cells are mixed with a proportion of stromal cells.We validate MixHMM and demonstrate its advantages with simulated samples, clinical tumor samples and a dilution series of mixed samples. We have shown that the CNVs of cancer cells in a tumor sample contaminated with up to 80% of stromal cells can be detected accurately using Illumina BeadChip and MixHMM.The MixHMM is available as a Python package provided with some other useful tools at http://genecube.med.yale.edu:8080/MixHMM.

The vertebrate gut harbors a vast community of bacterial mutualists, the composition of which is modulated by the host immune system. Many gastrointestinal (GI) diseases are expected to be associated with disruptions of host-bacterial interactions, but relatively few comprehensive studies have been reported. We have used the rhesus macaque model to investigate forces shaping GI bacterial communities. We used DNA bar coding and pyrosequencing to characterize 141,000 sequences of 16S rRNA genes obtained from 100 uncultured GI bacterial samples, allowing quantitative analysis of community composition in health and disease. Microbial communities of macaques were distinct from those of mice and humans in both abundance and types of taxa present. The macaque communities differed among samples from intestinal mucosa, colonic contents, and stool, paralleling studies of humans. Communities also differed among animals, over time within individual animals, and between males and females. To investigate changes associated with disease, samples of colonic contents taken at necropsy were compared between healthy animals and animals with colitis and undergoing antibiotic therapy. Communities from diseased and healthy animals also differed significantly in composition. This work provides comprehensive data and improved methods for studying the role of commensal microbiota in macaque models of GI diseases and provides a model for the large-scale screening of the human gut microbiome.