Short tandem repeat expansions in cortical layer-specific genes implicate in phenotypic severity and adaptability of autism spectrum disorder.

AIM: Short tandem repeats (STRs) are repetitive DNA sequences and highly mutable in various human disorders. While the involvement of STRs in various genetic disorders has been extensively studied, their role in autism spectrum disorder (ASD) remains largely unexplored. In this study, we aimed to investigate genetic association of STR expansions with ASD using whole genome sequencing (WGS) and identify risk loci associated with ASD phenotypes. METHODS: We analyzed WGS data of 634 ASD families and performed genome-wide evaluation for 12,929 STR loci. We found rare STR expansions that exceeded normal repeat lengths in autism cases compared to unaffected controls. By integrating single cell RNA and ATAC sequencing datasets of human postmortem brains, we prioritized STR loci in genes specifically expressed in cortical development stages. A deep learning method was used to predict functionality of ASD-associated STR loci. RESULTS: In ASD cases, rare STR expansions predominantly occurred in early cortical layer-specific genes involved in neurodevelopment, highlighting the cellular specificity of STR-associated genes in ASD risk. Leveraging deep learning prediction models, we demonstrated that these STR expansions disrupted the regulatory activity of enhancers and promoters, suggesting a potential mechanism through which they contribute to ASD pathogenesis. We found that individuals with ASD-associated STR expansions exhibited more severe ASD phenotypes and diminished adaptability compared to non-carriers. CONCLUSION: Short tandem repeat expansions in cortical layer-specific genes are associated with ASD and could potentially be a risk genetic factor for ASD. Our study is the first to show evidence of STR expansion associated with ASD in an under-investigated population.

Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types.

The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

Altered tumor signature and T-cell profile after chemotherapy reveal new therapeutic opportunities in high-grade serous ovarian carcinoma.

Chemotherapy combined with debulking surgery is the standard treatment protocol for high-grade serous ovarian carcinoma (HGSOC). Nonetheless, a significant number of patients encounter relapse due to the development of chemotherapy resistance. To better understand and address this resistance, we conducted a comprehensive study investigating the transcriptional alterations at the single-cell resolution in tissue samples from patients with HGSOC, using single-cell RNA sequencing and T-cell receptor sequencing techniques. Our analyses unveiled notable changes in the tumor signatures after chemotherapy, including those associated with epithelial-mesenchymal transition and cell cycle arrest. Within the immune compartment, we observed alterations in the T-cell profiles, characterized by naïve or pre-exhausted populations following chemotherapy. This phenotypic change was further supported by the examination of adjoining T-cell receptor clonotypes in paired longitudinal samples. These findings underscore the profound impact of chemotherapy on reshaping the tumor landscape and the immune microenvironment. This knowledge may provide clues for the development of future therapeutic strategies to combat treatment resistance in HGSOC.

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer.

Genomic hypomethylation has recently been identified as a determinant of therapeutic responses to immune checkpoint blockade (ICB). However, it remains unclear whether this approach can be applied to cell-free DNA (cfDNA) and whether it can address the issue of low tumor purity encountered in tissue-based methylation profiling. In this study, we developed an assay named iMethyl, designed to estimate the genomic hypomethylation status from cfDNA. This was achieved through deep targeted sequencing of young LINE-1 elements with > 400,000 reads per sample. iMethyl was applied to a total of 653 ICB samples encompassing lung cancer (cfDNA n = 167; tissue n = 137; cfDNA early during treatment n = 40), breast cancer (cfDNA n = 91; tissue n = 50; PBMC n = 50; cfDNA at progression n = 44), and ovarian cancer (tissue n = 74). iMethyl-liquid predicted ICB responses accurately regardless of the tumor purity of tissue samples. iMethyl-liquid was also able to monitor therapeutic responses early during treatment (3 or 6 weeks after initiation of ICB) and detect progressive hypomethylation accompanying tumor progression. iMethyl-tissue had better predictive power than tumor mutation burden and PD-L1 expression. In conclusion, our iMethyl-liquid method allows for reliable noninvasive prediction, early evaluation, and monitoring of clinical responses to ICB therapy.

Pan-cancer analysis reveals multifaceted roles of retrotransposon-fusion RNAs.

Transposon-derived transcripts are abundant in RNA sequences, yet their landscape and function, especially for fusion transcripts derived from unannotated or somatically acquired transposons, remains underexplored. Here, we developed a new bioinformatic tool to detect transposon-fusion transcripts in RNA-sequencing data and performed a pan-cancer analysis of 10,257 cancer samples across 34 cancer types as well as 3,088 normal tissue samples. We identified 52,277 cancer-specific fusions with ~30 events per cancer and hotspot loci within transposons vulnerable to fusion formation. Exonization of intronic transposons was the most prevalent genic fusions, while somatic L1 insertions constituted a small fraction of cancer-specific fusions. Source L1s and HERVs, but not Alus showed decreased DNA methylation in cancer upon fusion formation. Overall cancer-specific L1 fusions were enriched in tumor suppressors while Alu fusions were enriched in oncogenes, including recurrent Alu fusions in EZH2 predictive of patient survival. We also demonstrated that transposon-derived peptides triggered CD8+ T-cell activation to the extent comparable to EBV viruses. Our findings reveal distinct epigenetic and tumorigenic mechanisms underlying transposon fusions across different families and highlight transposons as novel therapeutic targets and the source of potent neoantigens.

Integrative analysis of risk factors for immune-related adverse events of checkpoint blockade therapy in cancer.

Immune-related adverse events (irAEs) induced by checkpoint inhibitors involve a multitude of different risk factors. Here, to interrogate the multifaceted underlying mechanisms, we compiled germline exomes and blood transcriptomes with clinical data, before and after checkpoint inhibitor treatment, from 672 patients with cancer. Overall, irAE samples showed a substantially lower contribution of neutrophils in terms of baseline and on-therapy cell counts and gene expression markers related to neutrophil function. Allelic variation of HLA-B correlated with overall irAE risk. Analysis of germline coding variants identified a nonsense mutation in an immunoglobulin superfamily protein, TMEM162. In our cohort and the Cancer Genome Atlas (TCGA) data, TMEM162 alteration was associated with higher peripheral and tumor-infiltrating B cell counts and suppression of regulatory T cells in response to therapy. We developed machine learning models for irAE prediction, validated using additional data from 169 patients. Our results provide valuable insights into risk factors of irAE and their clinical utility.

DeepNeo: a webserver for predicting immunogenic neoantigens.

Non-self epitopes, whether originated from foreign substances or somatic mutations, trigger immune responses when presented by major histocompatibility complex (MHC) molecules and recognized by T cells. Identification of immunogenically active neoepitopes has significant implications in cancer and virus medicine. However, current methods are mostly limited to predicting physical binding of mutant peptides and MHCs. We previously developed a deep-learning based model, DeepNeo, to identify immunogenic neoepitopes by capturing the structural properties of peptide-MHC pairs with T cell reactivity. Here, we upgraded our DeepNeo model with up-to-date training data. The upgraded model (DeepNeo-v2) was improved in evaluation metrics and showed prediction score distribution that better fits known neoantigen behavior. The immunogenic neoantigen prediction can be conducted at https://deepneo.net.

Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

Multi-cancer early detection remains a key challenge in cell-free DNA (cfDNA)-based liquid biopsy. Here, we perform cfDNA whole-genome sequencing to generate two test datasets covering 2125 patient samples of 9 cancer types and 1241 normal control samples, and also a reference dataset for background variant filtering based on 20,529 low-depth healthy samples. An external cfDNA dataset consisting of 208 cancer and 214 normal control samples is used for additional evaluation. Accuracy for cancer detection and tissue-of-origin localization is achieved using our algorithm, which incorporates cancer type-specific profiles of mutation distribution and chromatin organization in tumor tissues as model references. Our integrative model detects early-stage cancers, including those of pancreatic origin, with high sensitivity that is comparable to that of late-stage detection. Model interpretation reveals the contribution of cancer type-specific genomic and epigenomic features. Our methodologies may lay the groundwork for accurate cfDNA-based cancer diagnosis, especially at early stages.

Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

MHC II immunogenicity shapes the neoepitope landscape in human tumors.

Despite advances in predicting physical peptide-major histocompatibility complex I (pMHC I) binding, it remains challenging to identify functionally immunogenic neoepitopes, especially for MHC II. By using the results of >36,000 immunogenicity assay, we developed a method to identify pMHC whose structural alignment facilitates T cell reaction. Our method predicted neoepitopes for MHC II and MHC I that were responsive to checkpoint blockade when applied to >1,200 samples of various tumor types. To investigate selection by spontaneous immunity at the single epitope level, we analyzed the frequency spectrum of >25 million mutations in >9,000 treatment-naive tumors with >100 immune phenotypes. MHC II immunogenicity specifically lowered variant frequencies in tumors under high immune pressure, particularly with high TCR clonality and MHC II expression. A similar trend was shown for MHC I neoepitopes, but only in particular tissue types. In summary, we report immune selection imposed by MHC II-restricted natural or therapeutic T cell reactivity.

Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder.

Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD). We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions. Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development. Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.

Whole-Genome and Transcriptome Sequencing Identified NOTCH2 and HES1 as Potential Markers of Response to Imatinib in Desmoid Tumor (Aggressive Fibromatosis): A Phase II Trial Study.

PURPOSE: Desmoid tumor, also known as aggressive fibromatosis, is well-characterized by abnormal Wnt/ß-catenin signaling. Various therapeutic options, including imatinib, are available to treat desmoid tumor. However, the molecular mechanism of why imatinib works remains unclear. Here, we describe potential roles of NOTCH2 and HES1 in clinical response to imatinib at genome and transcriptome levels. MATERIALS AND METHODS: We identified somatic mutations in coding and noncoding regions via whole-genome sequencing. To validate the genetic interaction with expression level in desmoid-tumor condition, we utilized large-scale whole-genome sequencing and transcriptome datasets from the Pan-Cancer Analysis of Whole Genomes project. RNA-sequencing was performed using prospective and retrospective cohort samples to evaluate the expressional relevance with clinical response. RESULTS: Among 20 patients, four (20%) had a partial response and 14 (66.7%) had stable disease, 11 of which continued for ≥ 1 year. With gene-wise functional analyses, we detected a significant correlation between recurrent NOTCH2 noncoding mutations and clinical response to imatinib. Based on Pan-Cancer Analysis of Whole Genomes data analyses, NOTCH2 mutations affect expression levels particularly in the presence of CTNNB1 missense mutations. By analyzing RNA-sequencing with additional desmoid tumor samples, we found that NOTCH2 expression was significantly correlated with HES1 expression. Interestingly, NOTCH2 had no statistical power to discriminate between responders and non-responders. Instead, HES1 was differentially expressed with statistical significance between responders and non-responders. CONCLUSION: Imatinib was effective and well tolerated for advanced desmoid tumor treatment. Our results show that HES1, regulated by NOTCH2, as an indicator of sensitivity to imatinib, and an important therapeutic consideration for desmoid tumor.

Aberrant Transcript Usage Is Associated with Homologous Recombination Deficiency and Predicts Therapeutic Response.

BRCA1/2 mutations account for only a small fraction of homologous recombination (HR) deficiency (HRD) cases. Recently developed genomic HRD (gHRD) tests suffer confounding factors that cause low precision in predicting samples that will respond to PARP inhibitors and DNA damaging agents. Here we present molecular and clinical evidence of transcriptional HRD (tHRD) that is based on aberrant transcript usage (aTU) of minor isoforms. Specifically, increased TU of nonfunctional isoforms of DNA repair genes was prevalent in breast and ovarian cancer with gHRD. Functional assays validated the association of aTU with impaired HR activity. Machine learning-based tHRD detection by the transcript usage (TU) pattern of key genes was superior to directly screening for gHRD or BRCA1/2 mutations in accurately predicting responses of cell lines and patients with cancer to PARP inhibitors and genotoxic drugs. This approach demonstrated the capability of tHRD status to reflect functional HR status, including in a cohort of olaparib-treated ovarian cancer with acquired platinum resistance. Diagnostic tests based on tHRD are expected to broaden the clinical utility of PARP inhibitors. SIGNIFICANCE: A novel but widespread transcriptional mechanism by which homologous recombination deficiency arises independently of BRCA1/2 mutations can be utilized as a companion diagnostic for PARP inhibitors.

LncRNA HSPA7 in human atherosclerotic plaques sponges miR-223 and promotes the proinflammatory vascular smooth muscle cell transition.

Although there are many genetic loci in noncoding regions associated with vascular disease, studies on long noncoding RNAs (lncRNAs) discovered from human plaques that affect atherosclerosis have been highly limited. We aimed to identify and functionally validate a lncRNA using human atherosclerotic plaques. Human aortic samples were obtained from patients who underwent aortic surgery, and tissues were classified according to atherosclerotic plaques. RNA was extracted and analyzed for differentially expressed lncRNAs in plaques. Human aortic smooth muscle cells (HASMCs) were stimulated with oxidized low-density lipoprotein (oxLDL) to evaluate the effect of the identified lncRNA on the inflammatory transition of the cells. Among 380 RNAs differentially expressed between the plaque and control tissues, lncRNA HSPA7 was selected and confirmed to show upregulated expression upon oxLDL treatment. HSPA7 knockdown inhibited the migration of HASMCs and the secretion and expression of IL-1ß and IL-6; however, HSPA7 knockdown recovered the oxLDL-induced reduction in the expression of contractile markers. Although miR-223 inhibition promoted the activity of Nf-κB and the secretion of inflammatory proteins such as IL-1ß and IL-6, HSPA7 knockdown diminished these effects. The effects of miR-223 inhibition and HSPA7 knockdown were also found in THP-1 cell-derived macrophages. The impact of HSPA7 on miR-223 was mediated in an AGO2-dependent manner. HSPA7 is differentially increased in human atheroma and promotes the inflammatory transition of vascular smooth muscle cells by sponging miR-223. For the first time, this study elucidated the molecular mechanism of action of HSPA7, a lncRNA of previously unknown function, in humans.

The emerging genetic diversity of hereditary spastic paraplegia in Korean patients.

Hereditary Spastic Paraplegias (HSP) are a group of rare inherited neurological disorders characterized by progressive loss of corticospinal motor-tract function. Numerous patients with HSP remain undiagnosed despite screening for known genetic causes of HSP. Therefore, identification of novel genetic variations related to HSP is needed. In this study, we identified 88 genetic variants in 54 genes from whole-exome data of 82 clinically well-defined Korean HSP families. Fifty-six percent were known HSP genes, and 44% were composed of putative candidate HSP genes involved in the HSPome and originally reported neuron-related genes, not previously diagnosed in HSP patients. Their inheritance modes were 39, de novo; 33, autosomal dominant; and 10, autosomal recessive. Notably, ALDH18A1 showed the second highest frequency. Fourteen known HSP genes were firstly reported in Koreans, with some of their variants being predictive of HSP-causing protein malfunction. SPAST and REEP1 mutants with unknown function induced neurite abnormality. Further, 54 HSP-related genes were closely linked to the HSP progression-related network. Additionally, the genetic spectrum and variation of known HSP genes differed across ethnic groups. These results expand the genetic spectrum for HSP and may contribute to the accurate diagnosis and treatment for rare HSP.

L1 retrotransposons exploit RNA m6A modification as an evolutionary driving force.

L1 retrotransposons can pose a threat to genome integrity. The host has evolved to restrict L1 replication. However, mechanisms underlying L1 propagation out of the host surveillance remains unclear. Here, we propose an evolutionary survival strategy of L1, which exploits RNA m6A modification. We discover that m6A 'writer' METTL3 facilitates L1 retrotransposition, whereas m6A 'eraser' ALKBH5 suppresses it. The essential m6A cluster that is located on L1 5' UTR serves as a docking site for eukaryotic initiation factor 3 (eIF3), enhances translational efficiency and promotes the formation of L1 ribonucleoprotein. Furthermore, through the comparative analysis of human- and primate-specific L1 lineages, we find that the most functional m6A motif-containing L1s have been positively selected and became a distinctive feature of evolutionarily young L1s. Thus, our findings demonstrate that L1 retrotransposons hijack the RNA m6A modification system for their successful replication.

Comprehensive characterisation of intronic mis-splicing mutations in human cancers.

Previous studies studying mis-splicing mutations were based on exome data and thus our current knowledge is largely limited to exons and the canonical splice sites. To comprehensively characterise intronic mis-splicing mutations, we analysed 1134 pan-cancer whole genomes and transcriptomes together with 3022 normal control samples. The ratio-based splicing analysis resulted in 678 somatic intronic mutations, with 46% residing in deep introns. Among the 309 deep intronic single nucleotide variants, 245 altered core splicing codes, with 38% activating cryptic splice sites, 12% activating cryptic polypyrimidine tracts, and 36% and 12% disrupting authentic polypyrimidine tracts and branchpoints, respectively. All the intronic cryptic splice sites were created at pre-existing GT/AG dinucleotides or by GC-to-GT conversion. Notably, 85 deep intronic mutations indicated gain of splicing enhancers or loss of splicing silencers. We found that 64 tumour suppressors were affected by intronic mutations and blood cancers showed higher proportion of deep intronic mutations. In particular, a telomere maintenance gene, POT1, was recurrently mis-spliced by deep intronic mutations in blood cancers. We validated a pseudoexon activation involving a splicing silencer in POT1 by CRISPR/Cas9. Our results shed light on previously unappreciated mechanisms by which noncoding mutations acting on splicing codes in deep introns contribute to tumourigenesis.

Matrix stiffness epigenetically regulates the oncogenic activation of the Yes-associated protein in gastric cancer.

In many cancers, tumour progression is associated with increased tissue stiffness. Yet, the mechanisms associating tissue stiffness with tumorigenesis and malignant transformation are unclear. Here we show that in gastric cancer cells, the stiffness of the extracellular matrix reversibly regulates the DNA methylation of the promoter region of the mechanosensitive Yes-associated protein (YAP). Reciprocal interactions between YAP and the DNA methylation inhibitors GRHL2, TET2 and KMT2A can cause hypomethylation of the YAP promoter and stiffness-induced oncogenic activation of YAP. Direct alteration of extracellular cues via in situ matrix softening reversed YAP activity and the epigenetic program. Our findings suggest that epigenetic reprogramming of the mechanophysical properties of the extracellular microenvironment of solid tumours may represent a therapeutic strategy for the inhibition of cancer progression.

Genetic variants beyond amyloid and tau associated with cognitive decline: A cohort study.

OBJECTIVE: To identify single nucleotide polymorphisms (SNPs) associated with cognitive decline independent of ß-amyloid (Aß) and tau pathology in Alzheimer disease (AD). METHODS: Discovery and replication datasets consisting of 414 individuals (94 cognitively normal control [CN], 185 with mild cognitive impairment [MCI], and 135 with AD) and 72 individuals (22 CN, 39 with MCI, and 11 with AD), respectively, were obtained from the Alzheimer's Disease Neuroimaging Initiative database. Genome-wide association analysis was conducted to identify SNPs associated with individual cognitive function (measured with the Mini-Mental State Examination and Alzheimer's Disease Assessment Scale-Cognitive Subscale ) while controlling for the level of Aß and tau (measured as CSF phosphorylated-tau/Aß1-42). Gene ontology analysis was performed on SNP-associated genes. RESULTS: We identified 1 significant (rs55906536, ß = -1.91, standard error 0.34, p = 4.07 × 10-8) and 4 suggestive variants on chromosome 6 that were associated with poorer cognitive function. Congruent results were found in the replication data. A structural equation model showed that the identified SNP deteriorated cognitive function partially through cortical thinning of the brain in a region-specific manner. Furthermore, a bioinformatics analysis showed that the identified SNPs were associated with genes related to glutathione metabolism. CONCLUSIONS: In this study, we identified SNPs related to cognitive decline in a manner that could not be explained by Aß and tau levels. Our findings provide insight into the complexity of AD pathogenesis and support the growing literature on the role of glutathione in AD.