Computational prediction and analysis of deleterious cancer associated missense mutations in DYNC1H1

DYNC1I1 acts as a promising prognostic biomarker and is correlated with immune infiltration in head and neck squamous cell carcinoma

BACKGROUND/PURPOSE

Dynein Cytoplasmic 1 Intermediate Chain 1 (DYNC1I1) is a crucial cytoplasmic dynein binding component, its high expression levels are associated with malignant progression and poor survival in different types of cancer; however, the oncogenic role of DYNC1I1 in Head and neck squamous cell carcinomas (HNSCC) remains to be elucidated. In our present study, we aimed to explore the potential role of DYNC1I1 expression in the tumorigenesis of HNSCC and the shaping of the immune microenvironment.

MATERIALS AND METHODS

The expression levels of DYNC1I1 were analyzed in The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset, and then real-time quantitative polymerase chain reaction (RT-qPCR) was used to validate the DYNC1I1 expression in oral squamous cell carcinoma (OSCC) tumor samples, one of the major types of HNSCC. The functional pathway, tumor immune infiltration, and gene expression correlation for DYNC1I1 were performed using different bioinformatic tools.

RESULTS

We found that the expression of DYNC1I1 was significantly increased in HNSCC and was a predictor of poor survival. The DYNC1I1 high expression has also been associated with an increased risk of HPV-negative HNSCC and decreased immune cell infiltration. Functional enrichment analysis identified that DYNC1I1 is involved in several important signaling pathways that contribute to the cancer cell's survival and proliferation.

CONCLUSION

Our findings indicate that DYNC1I1 plays an important role in the tumorigenesis of HNSCC, and could be a promising prognostic biomarker for HNSCC diagnosis and treatment.

Non-synonymous, synonymous, and non-coding nucleotide variants contribute to recurrently altered biological processes during retinoblastoma progression

Retinoblastomas form in response to biallelic RB1 mutations or MYCN amplification and progress to more aggressive and therapy-resistant phenotypes through accumulation of secondary genomic changes. Progression-related changes include recurrent somatic copy number alterations and typically non-recurrent nucleotide variants, including synonymous and non-coding variants, whose significance has been unclear. To determine if nucleotide variants recurrently affect specific biological processes, we identified altered genes and over-represented variant gene ontologies in 168 exome or whole-genome-sequenced retinoblastomas and 12 tumor-matched cell lines. In addition to RB1 mutations, MYCN amplification, and established retinoblastoma somatic copy number alterations, the analyses revealed enrichment of variant genes related to diverse biological processes including histone monoubiquitination, mRNA processing (P) body assembly, and mitotic sister chromatid segregation and cytokinesis. Importantly, non-coding and synonymous variants increased the enrichment significance of each over-represented biological process term. To assess the effects of such mutations, we examined the consequences of a 3' UTR variant of PCGF3 (a BCOR-binding component of Polycomb repressive complex I), dual 3' UTR variants of CDC14B (a regulator of sister chromatid segregation), and a synonymous variant of DYNC1H1 (a regulator of P-body assembly). One PCGF3 and one of two CDC14B 3' UTR variants impaired gene expression whereas a base-edited DYNC1H1 synonymous variant altered protease sensitivity and stability. Retinoblastoma cell lines retained only ~50% of variants detected in tumors and enriched for new variants affecting p53 signaling. These findings reveal potentially important differences in retinoblastoma cell lines and tumors and implicate synonymous and non-coding variants, along with non-synonymous variants, in retinoblastoma oncogenesis.

DYNC1H1-related epilepsy: Genotype-phenotype correlation

AIM

To explore the phenotypic spectrum and refine the genotype-phenotype correlation of DYNC1H1-related epilepsy.

METHOD

The clinical data of 15 patients with epilepsy in our cohort and 50 patients with epilepsy from 24 published studies with the DYNC1H1 variants were evaluated.

RESULTS

In our cohort, 13 variants were identified from 15 patients (seven males, eight females). Twelve variants were de novo and seven were new. Age at seizure onset ranged from 3 months to 4 years 5 months (median age 1 year). Common seizure types were epileptic spasms, focal seizures, tonic seizures, and myoclonic seizures. Mild-to-severe developmental delay was present in all patients. Six patients were diagnosed with West syndrome and one was diagnosed with epileptic encephalopathy with continuous spikes and waves during slow sleep (CSWS). Collectively, in our cohort and published studies, 17% had ophthalmic diseases, 31% of variants were located in the stalk domain, and 92% patients with epilepsy had a malformation of cortical development (MCD).

INTERPRETATION

The phenotypes of DYNC1H1-related epilepsy included multiple seizure types; the most common epileptic syndrome was West syndrome. CSWS is a new phenotype of DYNC1H1-related epilepsy. One-third of the variants in patients with epilepsy were located in the stalk domain. Most patients had a MCD and developmental delay.

WHAT THIS PAPER ADDS

Nearly 40% of patients with DYNC1H1 variants had epilepsy. Ninety-two percent of patients with DYNC1H1-related epilepsy had malformation of cortical development. More than 10% of patients with DYNC1H1-related epilepsy were diagnosed with West syndrome. Continuous spikes and waves during slow sleep could be a new phenotype of DYNC1H1 variants. One-third of the variants in patients with epilepsy were located in the stalk domain.

Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks

Cancer is a heterogeneous disease that is driven by the accumulation of both genetic and nongenetic alterations, so integrating multiomics data and extracting effective information from them is expected to be an effective way to predict cancer driver genes. In this paper, we first generate comprehensive instructive features for each gene from genomic, epigenomic, transcriptomic levels together with protein–protein interaction (PPI)-networks-derived attributes and then propose a novel semisupervised deep graph learning framework GGraphSAGE to predict cancer driver genes according to the impact of the alterations on a biological system. When applied to eight tumor types, experimental results suggest that GGraphSAGE outperforms several state-of-the-art computational methods for driver genes identification. Moreover, it broadens our current understanding of cancer driver genes from multiomics level and identifies driver genes specific to the tumor type rather than pan-cancer. We expect GGraphSAGE to open new avenues in precision medicine and even further predict drivers for other complex diseases.

Could microtubule inhibitors be the best choice of therapy in gastric cancer with high immune activity: mutant DYNC1H1 as a biomarker

Immune checkpoint blockade (ICB) has achieved unprecedented breakthroughs in various cancers, including gastric cancer (GC) with high immune activity (MSI-H or TMB-H), yet clinical benefits from ICB were moderate. Here we aimed to identify the most appropriate drugs which can improve outcomes in GC. We firstly compared MSI-H and TMB-H GC samples with normal samples in TCGA-STAD cohort, respectively. After that, Connectivity Map database repurposed nine candidate drugs (CMap score < -90). Then, microtubule inhibitors (MTIs) were screened as the significant candidate drugs with their representative gene sets strongly enriched (p < 0.05) via GSEA. GDSC database validated higher activities of some MTIs in GC cells with MSI-H and TMB-H (p < 0.05). Furthermore, some MTIs activities were positively associated with mutant Dynein Cytoplasmic 1 Heavy Chain 1 (DYNC1H1) (p < 0.05) based on NCI-60 cancer cell line panel. DYNC1H1 was high frequently alteration in GC and was positively associated with TMB-H and MSI-H. Mutant DYNC1H1 may be accompanied with down-regulation of MTIs-related genes in GC or change the binding pocket to sensitize MTIs. Overall, this study suggested that some MTIs may be the best candidate drugs to treat GC with high immune activity, especially patients with DYNC1H1 mutated.

Discovery of specific mutations in spinal muscular atrophy patients by next-generation sequencing

Spinal muscular atrophy (SMA) is a type of autosomal recessive genetic disease, which seriously threatens the health and lives of children and adolescents. We attempted to find some genes and mutations related to the onset of SMA. Eighty-three whole-blood samples were collected from 28 core families, including 28 probands with clinically suspected SMA (20 SMA patients, 5 non-SMA children, and 3 patients with unknown etiology) and their parents. The multiplex ligation probe amplification (MLPA) was performed for preliminary diagnosis. The high-throughput sequencing technology was used to conduct the whole-exome sequencing analysis. We analyzed the mutations in adjacent genes of SMN1 gene and the unique mutations that only occurred in SMA patients. According to the MLPA results, 20 probands were regarded as experimental group and 5 non-SMA children as control group. A total of 10 mutations were identified in the adjacent genes of SMN1 gene. GUSBP1 g.[69515863G>A], GUSBP1 g.[69515870C>T], and SMA4 g.[69515738C>A] were the top three most frequent sites. SMA4 g.[69515726A>G] and OCLN c.[818G>T] have not been reported in the existing relevant researches. Seventeen point mutations in the DYNC1H1 gene were only recognized in SMA children, and the top two most common mutations were c.[2869-34A>T] and c.[345-89A>G]; c.[7473+105C>T] was the splicing mutation that might change the mRNA splicing site. The mutations of SMA4 g.[69515726A>G], OCLN c.[818G>T], DYNC1H1 c.[2869-34A>T], DYNC1H1 c.[345-89A>G], and DYNC1H1 c.[7473+105C>T] in the adjacent genes of SMN1 gene and other genes might be related to the onset of SMA.

Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes

Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since therapeutic advance can be obtained based on gene signatures, there is an urgent need to discover genes related to breast cancer that may help uncover the mechanisms in cancer progression. We propose a deep learning method for the discovery of breast cancer-related genes by using Capsule Network based Modeling of Multi-omics Data (CapsNetMMD). In CapsNetMMD, we make use of known breast cancer-related genes to transform the issue of gene identification into the issue of supervised classification. The features of genes are generated through comprehensive integration of multi-omics data, e.g., mRNA expression, z scores for mRNA expression, DNA methylation, and two forms of DNA copy-number alterations (CNAs). By modeling features based on the capsule network, we identify breast cancer-related genes with a significantly better performance than other existing machine learning methods. The predicted genes with prognostic values play potential important roles in breast cancer and may serve as candidates for biologists and medical scientists in the future studies of biomarkers.

c-Myc-mediated SNRPB upregulation functions as an oncogene in hepatocellular carcinoma

Dysregulation of genes involved in alternative splicing contributes to hepatocarcinogenesis. SNRPB, a component of spliceosome, is implicated in human cancers, yet its clinical significance and biological function in hepatocellular carcinoma (HCC) remains unknown. Here, we show that SNRPB expression is increased in HCC tissues, compared with the nontumorous tissues, at both messenger RNA and protein levels in two independent cohorts. High expression of SNRPB is significantly associated with higher pathological grade, vascular invasion, serum alpha-fetoprotein level, tumor metastasis, and poor disease-free and overall survivals. Luciferase reporter and chromatin immunoprecipitation assays demonstrate that SNRPB upregulation in HCC is mediated by c-Myc. Positive correlation is found between SNRPB and c-Myc expression in clinical samples. In vitro studies show that ectopic expression of SNRPB promotes HCC cell proliferation and migration, whereas knockdown of SNRPB results in the opposite phenotypes. Collectively, our data suggest SNRPB function as an oncogene and serve as a potential prognostic factor in HCC.

DYNC1I1 Promotes the Proliferation and Migration of Gastric Cancer by Up-Regulating IL-6 Expression

Gastric cancer is one of the top five malignant tumors worldwide. At present, the molecular mechanisms of gastric cancer progression are still not completely clear. Cytoplasmic dynein regulates intracellular transport and mitotic spindle localization, and its abnormal function is crucial for tumorigenesis, promotes tumor cell cycle progression, and tumor migration. DYNC1I1 is an important binding subunit of cytoplasmic dynein. However, studies on DYNC1I1 in tumors are currently limited. In the current study, we found that high DYNC1I1 expression in gastric cancer is associated with poor prognosis and is an independent prognostic factor. DYNC1I1 promoted the proliferation and migration of gastric cancer cells both in vitro and in vivo. DYNC1I1 also upregulated IL-6 expression by increasing NF-κB nuclear translocation. Collectively, these data revealed an important role for the DYNC1I1-driven IL-6/STAT pathway in gastric cancer proliferation and migration, suggesting that DYNC1I1 may be a potential therapeutic target for gastric cancer.

Synonymous mutation adenomatous polyposis coliΔ486s affects exon splicing and may predispose patients to adenomatous polyposis coli/mutY DNA glycosylase mutation‑negative familial adenomatous polyposis

Familial adenomatous polyposis (FAP) is an autosomal dominant-inherited colorectal cancer. Recent advances in genetics have indicated that the majority of patients with FAP carry germline mutations of the adenomatous polyposis coli (APC) and mutY DNA glycosylase (MUTYH) genes. However, a large subset of families with a history of FAP have undetectable pathogenic alterations, termed APC/MUTYH mutation-negative FAP. To investigate the germline mutations in the APC and MUTYH genes in Chinese patients with FAP, 13 unrelated patients were enrolled. Through genetic sequencing, four known pathogenic alterations (Lys1061LysfsTer2, Glu1309AspfsTer4, Arg283Ter and Ser1196Ter) of APC and two novel disease-associated pathogenic mutations (Tyr152Ter and Ter522Gly) in MUTYH were identified in six individuals. For samples that did not present with pathogenic alterations, the functional effects of missense, synonymous and intronic mutations were analyzed using bioinformatics tools and databases. Bioinformatics prediction suggested that the synonymous mutation Tyr486Tyr in APC (APC^∆486s) was likely a disease-causing polymorphism and may have induced the exon skipping of APC. A hybrid mini-gene assay was performed, which confirmed that the synonymous single nucleotide polymorphism APC^∆486s induced major splicing defects with skipping of exon 12 in APC. The data of the present study suggested that the synonymous polymorphism APC^∆486s was a potential pathogenic alteration that predisposed APC/MUTYH mutation-negative patients to FAP.

Mutational analysis of epidermal and hyperproliferative type I keratins in mild and moderate psoriasis vulgaris patients: a possible role in the pathogenesis of psoriasis along with disease severity

Background

Mutations in keratin proteins have been vastly associated with a wide array of genodermatoses; however, mutations of keratins in psoriasis have not been fully investigated. The main aim of the current research was to identify the mutation in K14, K10, K16, and K17 genes in two stages of psoriasis patients.

Methods

Ninety-six psoriatic skin biopsies were collected. mRNA transcript of K14, K10, K16, and K17 was prepared, amplified, and sequenced. Sanger sequences of all keratins were further validated for mutational analysis using Mutation Surveyor and Alamut Visual. Then, in silico analysis of protein stability and protein and gene expression of all keratins was performed and validated.

Results

Out of 44 mutations, about 75% of keratins are highly pathogenic and deleterious. Remaining 25% mutations are less pathogenic and tolerated in nature. In these 33 deleterious mutations were immensely found to decrease keratin protein stability. We also found a correlation between keratin and Psoriasis Area and Severity Index score which added that alteration in keratin gene in skin causes severity of psoriasis.

Conclusions

We strongly concluded that acanthosis and abnormal terminal differentiation was mainly due to the mutation in epidermal keratins. In turn, disease severity and relapsing of psoriasis are mainly due to the mutation of hyperproliferative keratins. These novel keratin mutations in psoriatic epidermis might be one of the causative factors for psoriasis.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0158-2) contains supplementary material, which is available to authorized users.