Computational identification and experimental verification of a novel signature based on SARS-CoV-2-related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients.

Background: Early research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined. Methods: We acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-CoV-2 score (Cov-2S) signature across The Cancer Genome Atlas and datasets GSE72094, GSE68465, and GSE31210. Comprehensive multi-omics analysis, including assessments of genetic mutations and copy number variations, was conducted to deepen our understanding of the prognosis signature. We also analyzed the response of different Cov-2S subgroups to immunotherapy and identified targeted drugs for these subgroups, advancing personalized medicine strategies. The expression of Cov-2S genes was confirmed through qRT-PCR, with GGH emerging as a critical gene for further functional studies to elucidate its role in LUAD. Results: Out of 34 differentially expressed CRGs identified, 16 correlated with overall survival. We utilized 10 machine learning algorithms, creating 101 combinations, and selected the RFS as the optimal algorithm for constructing a Cov-2S based on the average C-index across four cohorts. This was achieved after integrating several essential clinicopathological features and 58 established signatures. We observed significant differences in biological functions and immune cell statuses within the tumor microenvironments of high and low Cov-2S groups. Notably, patients with a lower Cov-2S showed enhanced sensitivity to immunotherapy. We also identified five potential drugs targeting Cov-2S. In vitro experiments revealed a significant upregulation of GGH in LUAD, and its knockdown markedly inhibited tumor cell proliferation, migration, and invasion. Conclusion: Our research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor's local immune condition, and supports clinical decision-making in tumor therapies.

Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment.

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.

Clinical phenotype of a Kallmann syndrome patient with IL17RD and CPEB4 variants.

Background: This study aimed to characterize the clinical phenotype and genetic variations in patients with Kallmann syndrome (KS). Methods: This study involved the collection and analysis of clinical data from an individual with sporadic KS. Following this, peripheral blood samples were obtained from the patient and his parents. Genomic deoxyribonucleic acid was extracted and subjected to whole-exome sequencing and genomic copy number variation (CNV) detection. Finally, Sanger sequencing was performed to validate the suspected pathogenic variants. Results: Whole-exome sequencing confirmed that the child carried both the IL17RD variant (c.2101G>A, p.Gly701Ser) inherited from the mother and the new CPEB4 variant (c.1414C>T, p.Arg472*). No pathogenic CNVs were identified in CNV testing. Conclusion: Bioinformatics analysis shows that the IL17RD protein undergoing Gly701Ser mutation and is speculated to be phosphorylated and modified, thereby disrupting fibroblast growth factor signaling. This study also suggested that the CPEB4 might play a crucial role in the key signaling process affecting olfactory bulb morphogenesis. Overall, the findings of this study broaden the gene expression profile of KS-related pathogenic genes. This offers a new avenue for exploring the pathogenic mechanism of KS and provides valuable insights for precise clinical diagnosis and treatment strategies for this condition.

Genomic Copy Number Analysis Using Droplet Digital PCR: A Simple Method with EvaGreen Single-Color Fluorescent Design.

Droplet digital PCR (ddPCR) is an emerging method for the absolute quantification of PCR products, and it can detect DNA copy numbers accurately. It analyzes the end-point absolute fluorescence signals of the PCR-positive droplets and calculates the target concentration. EvaGreen is a nonspecific double-stranded DNA-binding fluorescent dye, and the ddPCR system also supports assays using this cost-effective hydrolysis probe. Here, we describe a simple method of quantification for DNA copy numbers using the EvaGreen single-color fluorescent design.

Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival.

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.

Ancient Duplication and Lineage-Specific Transposition Determine Evolutionary Trajectory of ERF Subfamily across Angiosperms.

AP2/ERF transcription factor family plays an important role in plant development and stress responses. Previous studies have shed light on the evolutionary trajectory of the AP2 and DREB subfamilies. However, knowledge about the evolutionary history of the ERF subfamily in angiosperms still remains limited. In this study, we performed a comprehensive analysis of the ERF subfamily from 107 representative angiosperm species by combining phylogenomic and synteny network approaches. We observed that the expansion of the ERF subfamily was driven not only by whole-genome duplication (WGD) but also by tandem duplication (TD) and transposition duplication events. We also found multiple transposition events in Poaceae, Brassicaceae, Poales, Brassicales, and Commelinids. These events may have had notable impacts on copy number variation and subsequent functional divergence of the ERF subfamily. Moreover, we observed a number of ancient tandem duplications occurred in the ERF subfamily across angiosperms, e.g., in Subgroup IX, IXb originated from ancient tandem duplication events within IXa. These findings together provide novel insights into the evolution of this important transcription factor family.

Hfq-Antisense RNA I Binding Regulates RNase E-Dependent RNA Stability and ColE1 Plasmid Copy Number.

The mechanisms and consequences of gene regulation by Hfq on trans-encoded small RNAs (sRNAs) have been well studied and documented. Recent employment of Genomic SELEX to search for Hfq-binding motifs has indicated that Hfq might frequently regulate gene expression controlled by cis-antisense RNAs. Here, we use the classic ColE1 plasmid antisense RNA-based regulation model (i.e., RNA I) to study the role of Hfq in controlling antisense regulatory functions. We show that Hfq exhibits a high binding affinity for RNA I and that binding limits RNase E cleavage, thereby stabilizing RNA I and reducing the plasmid copy number. Full-length RNA I displays a binding affinity for Hfq in the sub-micromolar range. In vivo overexpression of Hfq prolongs RNA I stability and reduces the ColE1 plasmid copy number, whereas deletion of hfq reduces RNA I stability and increases the plasmid copy number. RNA I predominantly binds to the proximal face of Hfq and exhibits competitive ability against a chromosome-borne proximal face-bound sRNA (DsrA) for Hfq binding. Through its strong promoter and high gene dosage features, plasmid-encoded antisense RNA I results in high RNA I expression, so it may antagonize the effects of trans-encoded RNAs in controlling target gene expression.

Putative climate adaptation in American pikas (Ochotona princeps) is associated with copy number variation across environmental gradients.

Improved understanding of the genetic basis of adaptation to climate change is necessary for maintaining global biodiversity moving forward. Studies to date have largely focused on sequence variation, yet there is growing evidence that suggests that changes in genome structure may be an even more significant source of adaptive potential. The American pika (Ochotona princeps) is an alpine specialist that shows some evidence of adaptation to climate along elevational gradients, but previous work has been limited to single nucleotide polymorphism based analyses within a fraction of the species range. Here, we investigated the role of copy number variation underlying patterns of local adaptation in the American pika using genome-wide data previously collected across the entire species range. We identified 37-193 putative copy number variants (CNVs) associated with environmental variation (temperature, precipitation, solar radiation) within each of the six major American pika lineages, with patterns of divergence largely following elevational and latitudinal gradients. Genes associated (n = 158) with independent annotations across lineages, variables, and/or CNVs had functions related to mitochondrial structure/function, immune response, hypoxia, olfaction, and DNA repair. Some of these genes have been previously linked to putative high elevation and/or climate adaptation in other species, suggesting they may serve as important targets in future studies.

[Prenatal diagnosis of a case with Congenital myasthenic syndrome due to compound heterozygous variants of SCN4A gene].

OBJECTIVE: To explore the clinical and genetic characteristics of a fetus diagnosed with Congenital myasthenic syndrome type 16 (CMS16). METHODS: A couple who had visited Tianjin Medical University General Hospital in February 2018 due to "adverse outcome of two pregnancies" was selected as the study subject. Clinical data was gathered. Peripheral blood and amniotic fluid samples were collected and subjected to whole exome sequencing (WES). Candidate variant was verified by Sanger sequencing. Low-depth whole-genome sequencing was carried out to detect copy number variation (CNV) in the fetus. RESULTS: The couple's first pregnancy had resulted in a miscarriage at 27+5 weeks, when ultrasound had revealed pleural effusion and polyhydramnios in the fetus. Their second pregnancy was terminated at 30+5 weeks due to fetal hand malformations, polyhydramnios and pleural fluid. Both couple had denied family history of genetic conditions. For their third pregnancy, no CNV abnormality was detected, whilst a compound heterozygous variants, including a maternally derived c.3172C>T (p.R1058W) and paternal c.1431delG (p.K477fs*89) in the SCN4A gene were detected. Based on the guidelines from the American College of Medical Genetics and Genomics, the c.3172C>T (p.R1058W) was predicted as a likely pathogenic variant (PM1+PM2_supporting+PP3+PP4), whilst the c.1431delG (p.K477fs*89) was predicted as a pathogenic variant (PVS1+PM2_supporting+PP4). CONCLUSION: The c.3172C>T (p.R1058W) and c.1431delG (p.K477fs*89) compound heterozygous variants of the SCN4A gene probably underlay the CMS16 in the third fetus.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

IQGAP3 promotes the progression of glioma as an immune and prognostic marker.

Background: IQGAP3 plays a crucial role in regulating cell proliferation, division, and cytoskeletal organization. Abnormal expression of IQGAP3 has been linked to various tumors, but its function in glioma is not well understood. Methods: Various methods, including genetic differential analysis, single-cell analysis, ROC curve analysis, Cox regression, Kaplan-Meier analysis, and enrichment analysis, were employed to analyze the expression patterns, diagnostic potential, prognostic implications, and biological processes involving IQGAP3 in normal and tumor tissues. The impact of IQGAP3 on immune infiltration and the immune microenvironment in gliomas was evaluated using immunofluorescence. Additionally, the cBioPortal database was used to analyze copy number variations and mutation sites of IQGAP3. Experimental validation was also performed to assess the effects of IQGAP3 on glioma cells and explore underlying mechanisms. Results: High IQGAP3 expression in gliomas is associated with an unfavorable prognosis, particularly in wild-type IDH and 1p/19q non-codeleted gliomas. Enrichment analysis revealed that IQGAP3 is involved in regulating the cell cycle, PI3K/AKT signaling, p53 signaling, and PLK1-related pathways. Furthermore, IQGAP3 expression may be closely related to the immunosuppressive microenvironment of glioblastoma. BRD-K88742110 and LY-303511 are potential drugs for targeting IQGAP3 in anti-glioma therapy. In vitro experiments showed that downregulation of IQGAP3 inhibits the proliferation and migration of glioma cells, with the PLK1/PI3K/AKT pathway potentially playing a crucial role in IQGAP3-mediated glioma progression. Conclusion: IQGAP3 shows promise as a valuable biomarker for diagnosis, prognosis, and immunotherapeutic strategies in gliomas.

An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy.

Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient's survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Identification and validation of a novel anoikis-related prognostic model for prostate cancer.

BACKGROUND: Anoikis resistance is a hallmark characteristic of oncogenic transformation, which is crucial for tumor progression and metastasis. The aim of this study was to identify and validate a novel anoikis-related prognostic model for prostate cancer (PCa). METHODS: We collected a gene expression profile, single nucleotide polymorphism mutation and copy number variation (CNV) data of 495 PCa patients from the TCGA database and 140 PCa samples from the MSKCC dataset. We extracted 434 anoikis-related genes and unsupervised consensus cluster analysis was used to identify molecular subtypes. The immune infiltration, molecular function, and genome alteration of subtypes were evaluated. A risk signature was developed using Cox regression analysis and validated with the MSKCC dataset. We also identify potential drugs for high-risk group patients. RESULTS: Two subtypes were identified. C1 exhibited a higher level of CNV amplification, immune score, stromal score, aneuploidy score, homologous recombination deficiency, intratumor heterogeneity, single-nucleotide variant neoantigens, and tumor mutational burden compared to C2. C2 showed a better survival outcome and had a high level of gamma delta T cell and activated B cell infiltration. The risk signature consisting of four genes (HELLS, ZWINT, ABCC5, and TPSB2) was developed (area under the curve = 0.780) and was found to be an independent prognostic factor for overall survival in PCa patients. Four CTRP-derived and four PRISM-derived compounds were identified for high-risk patients. CONCLUSIONS: The anoikis-related prognostic model developed in this study could be a useful tool for clinical decision-making. This study may provide a new perspective for the treatment of anoikis-related PCa.

Malformations of cortical development: Fetal imaging and genetics.

BACKGROUND: Malformations of cortical development (MCD) are a group of congenital disorders characterized by structural abnormalities in the brain cortex. The clinical manifestations include refractory epilepsy, mental retardation, and cognitive impairment. Genetic factors play a key role in the etiology of MCD. Currently, there is no curative treatment for MCD. Phenotypes such as epilepsy and cerebral palsy cannot be observed in the fetus. Therefore, the diagnosis of MCD is typically based on fetal brain magnetic resonance imaging (MRI), ultrasound, or genetic testing. The recent advances in neuroimaging have enabled the in-utero diagnosis of MCD using fetal ultrasound or MRI. METHODS: The present study retrospectively reviewed 32 cases of fetal MCD diagnosed by ultrasound or MRI. Then, the chromosome karyotype analysis, single nucleotide polymorphism array or copy number variation sequencing, and whole-exome sequencing (WES) findings were presented. RESULTS: Pathogenic copy number variants (CNVs) or single-nucleotide variants (SNVs) were detected in 22 fetuses (three pathogenic CNVs [9.4%, 3/32] and 19 SNVs [59.4%, 19/32]), corresponding to a total detection rate of 68.8% (22/32). CONCLUSION: The results suggest that genetic testing, especially WES, should be performed for fetal MCD, in order to evaluate the outcomes and prognosis, and predict the risk of recurrence in future pregnancies.

Genetic underpinnings explored: OPA1 deletion and complex phenotypes on chromosome 3q29.

BACKGROUND: Copy number variations (CNVs) have emerged as significant contributors to the elusive genetic causality of inherited eye diseases. In this study, we describe a case with optic atrophy and a brain aneurysm, in which a de novo CNV 3q29 deletion was identified. CASE PRESENTATION: A 40-year-old female patient was referred to our department after undergoing aneurysm transcatheter arterial embolization for a brain aneurysm. She had no history of systemic diseases, except for unsatisfactory best-corrected visual acuity (BCVA) since elementary school. Electrophysiological tests confirmed the findings in retinal images, indicating optic nerve atrophy. Chromosomal microarray analysis revealed a de novo deletion spanning 960 kb on chromosome 3q29, encompassing OPA1 and six neighboring genes. Unlike previously reported deletions in this region associated with optic atrophy, neuropsychiatric disorders, and obesity, this patient displayed a unique combination of optic atrophy and a brain aneurysm. However, there is no causal relationship between the brain aneurysm and the CNV. CONCLUSION: In conclusion, the optic atrophy is conclusively attributed to the OPA1 deletion, and the aneurysm could be a coincidental association. The report emphasizes the likelihood of underestimating OPA1 deletions due to sequencing technology limitations. Recognizing these constraints, healthcare professionals must acknowledge these limitations and consistently search for OPA1 variants/deletions in Autosomal Dominant Optic Atrophy (ADOA) patients with negative sequencing results. This strategic approach ensures a more comprehensive exploration of copy-number variations, ultimately enhancing diagnostic precision in the field of genetic disorders.

Expanding deep phenotypic spectrum associated with atypical pathogenic structural variations overlapping 15q11-q13 imprinting region.

BACKGROUND: The 15q11-q13 region is a genetic locus with genes subject to genomic imprinting, significantly influencing neurodevelopment. Genomic imprinting is an epigenetic phenomenon that causes differential gene expression based on the parent of origin. In most diploid organisms, gene expression typically involves an equal contribution from both maternal and paternal alleles, shaping the phenotype. Nevertheless, in mammals, including humans, mice, and marsupials, the functional equivalence of parental alleles is not universally maintained. Notably, during male and female gametogenesis, parental alleles may undergo differential marking or imprinting, thereby modifying gene expression without altering the underlying DNA sequence. Neurodevelopmental disorders, such as Prader-Willi syndrome (PWS) (resulting from the absence of paternally expressed genes in this region), Angelman syndrome (AS) (associated with the absence of the maternally expressed UBE3A gene), and 15q11-q13 duplication syndrome (resulting from the two common forms of duplications-either an extra isodicentric 15 chromosome or an interstitial 15 duplication), are the outcomes of genetic variations in this imprinting region. METHODS: Conducted a genomic study to identify the frequency of pathogenic variants impacting the 15q11-q13 region in an ethnically homogenous population from Bangladesh. Screened all known disorders from the DECIPHER database and identified variant enrichment within this cohort. Using the Horizon analysis platform, performed enrichment analysis, requiring at least >60% overlap between a copy number variation and a disorder breakpoint. Deep clinical phenotyping was carried out through multiple examination sessions to evaluate a range of clinical symptoms. RESULTS: This study included eight individuals with clinically suspected PWS/AS, all previously confirmed through chromosomal microarray analysis, which revealed chromosomal breakpoints within the 15q11-q13 region. Among this cohort, six cases (75%) exhibited variable lengths of deletions, whereas two cases (25%) showed duplications. These included one type 2 duplication, one larger atypical duplication, one shorter type 2 deletion, one larger type 1 deletion, and four cases with atypical deletions. Furthermore, thorough clinical assessments led to the diagnosis of four PWS patients, two AS patients, and two individuals with 15q11-q13 duplication syndrome. CONCLUSION: Our deep phenotypic observations identified a spectrum of clinical features that overlap and are unique to PWS, AS, and Dup15q syndromes. Our findings establish genotype-phenotype correlation for patients impacted by variable structural variations within the 15q11-q13 region.

Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations.

Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

Biomarkers for progressive multifocal leukoencephalopathy: emerging data for use of JC virus DNA copy number in clinical trials.

Progressive multifocal leukoencephalopathy is a rare but devastating demyelinating disease caused by the JC virus (JCV), for which no therapeutics are approved. To make progress towards addressing this unmet medical need, innovations in clinical trial design are needed. Quantitative JCV DNA in CSF has the potential to serve as a valuable biomarker of progressive multifocal leukoencephalopathy disease and treatment response in clinical trials to expedite therapeutic development, as do neuroimaging and other fluid biomarkers such as neurofilament light chain. Specifically, JCV DNA in CSF could be used in clinical trials as an entry criterion, stratification factor, or predictor of clinical outcomes. Insights from the investigation of candidate biomarkers for progressive multifocal leukoencephalopathy might inform approaches to biomarker development for other rare diseases.

Coupled scRNA-seq and Bulk-seq reveal the role of HMMR in hepatocellular carcinoma.

Background: Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear. Methods: The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks. Recursive partitioning analysis (RPA) was used to re-stage HCC patients. The IC50 values of various drugs were evaluated using the "pRRophetic" package. In addition, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm HMMR expression in an HCC tissue microarray. Flow cytometry (FCM) and cloning, Edu and wound healing assays were used to explore the capacity of HMMR to regulate HCC tumour. Results: Multiple cohort studies and qRT-PCR demonstrated that HMMR was overexpressed in HCC tissue compared with normal tissue. In addition, HMMR had excellent diagnostic performance. HMMR knockdown inhibited the proliferation and migration of HCC cells in vitro. Moreover, high HMMR expression was associated with "G2M checkpoint" and "E2F targets" in bulk RNA and scRNA-seq, and FCM confirmed that HMMR could regulate the cell cycle. In addition, HMMR was involved in the regulation of the tumour immune microenvironment via immune cell infiltration and intercellular interactions. Furthermore, HMMR was positively associated with genomic heterogeneity with patients with high HMMR expression potentially benefitting more from immunotherapy. Moreover, HMMR was associated with poor prognosis in patients with HCC and the re-staging by recursive partitioning analysis (RPA) gave a good prognosis prediction value and could guide chemotherapy and targeted therapy. Conclusion: The results of the present study show that HMMR could play a role in the diagnosis, prognosis, and treatments of patients with HCC based on bulk RNA-seq and scRAN-seq analyses and is a promising molecular marker for HCC.