Non-coding Mutations Research Articles

Global impact of somatic structural variation on the cancer proteome

Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.

BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens

MHC-I-associated peptides deriving from non-coding genomic regions and mutations can generate tumor-specific antigens, including neoantigens. Quantifying tumor-specific antigens’ RNA expression in malignant and benign tissues is critical for discriminating actionable targets. We present BamQuery, a tool attributing an exhaustive RNA expression to MHC-I-associated peptides of any origin from bulk and single-cell RNA-sequencing data. We show that many cryptic and mutated tumor-specific antigens can derive from multiple discrete genomic regions, abundantly expressed in normal tissues. BamQuery can also be used to predict MHC-I-associated peptides immunogenicity and identify actionable tumor-specific antigens de novo.

Using evolutionary constraint to define novel candidate driver genes in medulloblastoma

Current knowledge of cancer genomics remains biased against noncoding mutations. To systematically search for regulatory noncoding mutations, we assessed mutations in conserved positions in the genome under the assumption that these are more likely to be functional than mutations in positions with low conservation. To this end, we use whole-genome sequencing data from the International Cancer Genome Consortium and combined it with evolutionary constraint inferred from 240 mammals, to identify genes enriched in noncoding constraint mutations (NCCMs), mutations likely to be regulatory in nature. We compare medulloblastoma (MB), which is malignant, to pilocytic astrocytoma (PA), a primarily benign tumor, and find highly different NCCM frequencies between the two, in agreement with the fact that malignant cancers tend to have more mutations. In PA, a high NCCM frequency only affects the BRAF locus, which is the most commonly mutated gene in PA. In contrast, in MB, >500 genes have high levels of NCCMs. Intriguingly, several loci with NCCMs in MB are associated with different ages of onset, such as the HOXB cluster in young MB patients. In adult patients, NCCMs occurred in, e.g., the WASF-2/AHDC1/FGR locus. One of these NCCMs led to increased expression of the SRC kinase FGR and augmented responsiveness of MB cells to dasatinib, a SRC kinase inhibitor. Our analysis thus points to different molecular pathways in different patient groups. These newly identified putative candidate driver mutations may aid in patient stratification in MB and could be valuable for future selection of personalized treatment options.

Noncoding RNA mutations in cancer.

Cancer is driven by both germline and somatic genetic changes. Efforts have been devoted to characterizing essential genetic variations in cancer initiation and development. Most attention has been given to mutations in protein-coding genes and associated regulatory elements such as promoters and enhancers. The development of sequencing technologies and in silico and experimental methods has allowed further exploration of cancer predisposition variants and important somatic mutations in noncoding RNAs, mainly for long noncoding RNAs and microRNAs. Association studies including GWAS have revealed hereditary variations including SNPs and indels in lncRNA or miRNA genes and regulatory regions. These mutations altered RNA secondary structures, expression levels, and target recognition and then conferred cancer predisposition to carriers. Whole-exome/genome sequencing comparing cancer and normal tissues has revealed important somatic mutations in noncoding RNA genes. Mutation hotspots and somatic copy number alterations have been identified in various tumor-associated noncoding RNAs. Increasing focus and effort have been devoted to studying the noncoding region of the genome. The complex genetic network of cancer initiation is being unveiled. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Zebrafish regulatory genomic resources for disease modelling and regeneration.

In the past decades, the zebrafish has become a disease model with increasing popularity owing to its advantages that include fast development, easy genetic manipulation, simplicity for imaging, and sharing conserved disease-associated genes and pathways with those of human. In parallel, studies of disease mechanisms are increasingly focusing on non-coding mutations, which require genome annotation maps of regulatory elements, such as enhancers and promoters. In line with this, genomic resources for zebrafish research are expanding, producing a variety of genomic data that help in defining regulatory elements and their conservation between zebrafish and humans. Here, we discuss recent developments in generating functional annotation maps for regulatory elements of the zebrafish genome and how this can be applied to human diseases. We highlight community-driven developments, such as DANIO-CODE, in generating a centralised and standardised catalogue of zebrafish genomics data and functional annotations; consider the advantages and limitations of current annotation maps; and offer considerations for interpreting and integrating existing maps with comparative genomics tools. We also discuss the need for developing standardised genomics protocols and bioinformatic pipelines and provide suggestions for the development of analysis and visualisation tools that will integrate various multiomic bulk sequencing data together with fast-expanding data on single-cell methods, such as single-cell assay for transposase-accessible chromatin with sequencing. Such integration tools are essential to exploit the multiomic chromatin characterisation offered by bulk genomics together with the cell-type resolution offered by emerging single-cell methods. Together, these advances will build an expansive toolkit for interrogating the mechanisms of human disease in zebrafish.

A non-coding insertional mutation of Grhl2 causes gene over-expression and multiple structural anomalies including cleft palate, spina bifida and encephalocele.

Orofacial clefts, including cleft lip and palate (CL/P) and neural tube defects (NTDs) are among the most common congenital anomalies, but knowledge of the genetic basis of these conditions remains incomplete. The extent to which genetic risk factors are shared between CL/P, NTDs and related anomalies is also unclear. While identification of causative genes has largely focused on coding and loss of function mutations, it is hypothesized that regulatory mutations account for a portion of the unidentified heritability. We found that excess expression of Grainyhead-like 2 (Grhl2) causes not only spinal NTDs in Axial defects (Axd) mice but also multiple additional defects affecting the cranial region. These include orofacial clefts comprising midline cleft lip and palate and abnormalities of the craniofacial bones and frontal and/or basal encephalocele, in which brain tissue herniates through the cranium or into the nasal cavity. To investigate the causative mutation in the Grhl2Axd strain, whole genome sequencing identified an approximately 4kb LTR retrotransposon insertion that disrupts the non-coding regulatory region, lying approximately 300 base pairs upstream of the 5' UTR. This insertion also lies within a predicted long non-coding RNA, oriented on the reverse strand, which like Grhl2 is over-expressed in Axd (Grhl2Axd) homozygous mutant embryos. Initial analysis of the GRHL2 upstream region in individuals with NTDs or cleft palate revealed rare or novel variants in a small number of cases. We hypothesize that mutations affecting the regulation of GRHL2 may contribute to craniofacial anomalies and NTDs in humans.

A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs

Abstract Three prevalent SARS-CoV-2 variants of concern (VOCs) emerged and caused epidemic waves. It is essential to uncover advantageous mutations that cause the high transmissibility of VOCs. However, viral mutations are tightly linked, so traditional population genetic methods, including machine learning–based methods, cannot reliably detect mutations conferring a fitness advantage. In this study, we developed an approach based on the sequential occurrence order of mutations and the accelerated furcation rate in the pandemic-scale phylogenomic tree. We analyzed 3,777,753 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata using the Coronavirus GenBrowser. We found that two noncoding mutations at the same position (g.a28271−/u) may be crucial to the high transmissibility of Alpha, Delta, and Omicron VOCs although the noncoding mutations alone cannot increase viral transmissibility. Both mutations cause an A-to-U change at the core position −3 of the Kozak sequence of the N gene and significantly reduce the protein expression ratio of ORF9b to N. Using a convergent evolutionary analysis, we found that g.a28271−/u, S:p.P681H/R, and N:p.R203K/M occur independently on three VOC lineages, suggesting that coordinated changes of S, N, and ORF9b proteins are crucial to high viral transmissibility. Our results provide new insights into high viral transmissibility co-modulated by advantageous noncoding and nonsynonymous changes.

Deep learning model accurately classifies metastatic tumors from primary tumors based on mutational signatures

Metastatic propagation is the leading cause of death for most cancers. Prediction and elucidation of metastatic process is crucial for the treatment of cancer. Even though somatic mutations have been linked to tumorigenesis and metastasis, it is less explored whether metastatic events can be identified through genomic mutational signatures, which are concise descriptions of the mutational processes. Here, we developed MetaWise, a Deep Neural Network (DNN) model, by applying mutational signatures as input features calculated from Whole-Exome Sequencing (WES) data of TCGA and other metastatic cohorts. This model can accurately classify metastatic tumors from primary tumors and outperform traditional machine learning (ML) models and a deep learning (DL) model, DiaDeL. Signatures of non-coding mutations also have a major impact on the model’s performance. SHapley Additive exPlanations (SHAP) and Local Surrogate (LIME) analyses identify several mutational signatures which are directly correlated to metastatic spread in cancers, including APOBEC-mutagenesis, UV-induced signatures, and DNA damage response deficiency signatures.

Genetic subdivisions of follicular lymphoma defined by distinct coding and noncoding mutation patterns

AbstractFollicular lymphoma (FL) accounts for ∼20% of all new lymphoma cases. Increases in cytological grade are a feature of the clinical progression of this malignancy, and eventual histologic transformation (HT) to the aggressive diffuse large B-cell lymphoma (DLBCL) occurs in up to 15% of patients. Clinical or genetic features to predict the risk and timing of HT have not been described comprehensively. In this study, we analyzed whole-genome sequencing data from 423 patients to compare the protein coding and noncoding mutation landscapes of untransformed FL, transformed FL, and de novo DLBCL. This revealed 2 genetically distinct subgroups of FL, which we have named DLBCL-like (dFL) and constrained FL (cFL). Each subgroup has distinguishing mutational patterns, aberrant somatic hypermutation rates, and biological and clinical characteristics. We implemented a machine learning–derived classification approach to stratify patients with FL into cFL and dFL subgroups based on their genomic features. Using separate validation cohorts, we demonstrate that cFL status, whether assigned with this full classifier or a single-gene approximation, is associated with a reduced rate of HT. This implies distinct biological features of cFL that constrain its evolution, and we highlight the potential for this classification to predict HT from genetic features present at diagnosis.

Identification of Liver Cancer Driver Mutations from COSMIC Data

Background: Liver cancer accounts for more than 700,000 deaths each year making it the third leading cause of cancer-related deaths worldwide. Late diagnosis of the disease is the reason behind most deaths. Driver mutations are genetic alterations in tumor cells, which are responsible for the development of liver cancer; therefore, the identification of genetic biomarkers is necessary for the prediction and early diagnosis of liver cancer. Objectives: The main objective of this study is to identify pathogenic alleles that may act as potential biomarkers for the prediction of liver cancer. It also identifies the role of novel genes in liver cancer that are not known to cause the disease. Methods: The mutation data of non-coding variants were downloaded from the catalogue of somatic mutations in cancer (COSMIC) databases. Different bioinformatics tools were, then, used to retrieve mutations in liver cancer. The genetic alterations in hepatocellular carcinoma (HCC) were analyzed. Results: The present study successfully identified pathogenic alleles (consistent mutations) along with a set of novel genes that might be involved in the development of liver cancer. It identified non-coding mutations near human genes and transcription factor binding sites of HepG2 cells. This study also identified mutations near the genes that are involved in the Ras/MAFK signaling pathway of the Hepatitis B virus. Conclusions: The pathogenic alleles identified in this study may provide targeted therapy for the treatment of liver cancer. The identification of novel genes may help to understand the progression of liver cancer at the molecular level. The identified driver mutations may act as potential biomarkers and therapeutic targets for early prediction and treatment of liver cancer.

Genomic landscape of Down syndrome–associated acute lymphoblastic leukemia

AbstractTrisomy 21, the genetic cause of Down syndrome (DS), is the most common congenital chromosomal anomaly. It is associated with a 20-fold increased risk of acute lymphoblastic leukemia (ALL) during childhood and results in distinctive leukemia biology. To comprehensively define the genomic landscape of DS-ALL, we performed whole-genome sequencing and whole-transcriptome sequencing (RNA-Seq) on 295 cases. Our integrated genomic analyses identified 15 molecular subtypes of DS-ALL, with marked enrichment of CRLF2-r, IGH::IGF2BP1, and C/EBP altered (C/EBPalt) subtypes compared with 2257 non–DS-ALL cases. We observed abnormal activation of the CEBPD, CEBPA, and CEBPE genes in 10.5% of DS-ALL cases via a variety of genomic mechanisms, including chromosomal rearrangements and noncoding mutations leading to enhancer hijacking. A total of 42.3% of C/EBP-activated DS-ALL also have concomitant FLT3 point mutations or insertions/deletions, compared with 4.1% in other subtypes. CEBPD overexpression enhanced the differentiation of mouse hematopoietic progenitor cells into pro-B cells in vitro, particularly in a DS genetic background. Notably, recombination-activating gene–mediated somatic genomic abnormalities were common in DS-ALL, accounting for a median of 27.5% of structural alterations, compared with 7.7% in non–DS-ALL. Unsupervised hierarchical clustering analyses of CRLF2-rearranged DS-ALL identified substantial heterogeneity within this group, with the BCR::ABL1-like subset linked to an inferior event-free survival, even after adjusting for known clinical risk factors. These results provide important insights into the biology of DS-ALL and point to opportunities for targeted therapy and treatment individualization.

Abstract 3481: A local tumor microenvironment acquired super-enhancer induces an oncogenic driver in colorectal carcinoma

Abstract Tumors exhibit widespread enhancer landscape reprogramming compared to normal tissue. The etiology is believed to be largely cell-intrinsic in non-hormonal cancers, attributed to such genomic alterations as focal amplification of non-coding regions, aberrant activation of transcription factors, and non-coding mutations creating de novo transcription factor binding sites. Here, using freshly resected primary CRC tumors and patient-matched adjacent normal colon epithelia, we find divergent epigenetic landscapes between primary CRC tumors and CRC cell lines. We identify a unique super-enhancer signature largely absent in cell culture. Intriguingly, this phenomenon extends to highly recurrent aberrant super-enhancers gained in CRC over patient-matched normal epithelium suggesting novel insight into the etiology of enhancer reprogramming in CRC and its downstream relevance to tumor biology. We find one such super-enhancer activated in epithelial cancer cells due to surrounding inflammation in the tumor microenvironment. CRISPR-dcas9-KRAB interference of this super-enhancer identifies PDZK1IP1 as its target gene. PDZK1IP1 is previously observed to be highly up-regulated in CRC. However, the mechanism behind its transcriptional activation is not fully understood. We restore both the super-enhancer and PDZK1IP1 levels following treatment with cytokines or xenotransplantation into nude mice, thus demonstrating its etiology via local tumor microenvironment acquisition. Deletion of inflammatory transcription factors RELA and STAT3 in human CRC cells inhibits PDZK1IP1 induction in xenografts. PDZK1IP1 appears to be critical for CRC growth in the setting of its super-enhancer induction as xenografts, but not in cell culture where the super-enhancer is absent and expression is largely silent. Building on its known role in glucose uptake via SGLT receptors, we demonstrate mechanistically that PDZK1IP1 enhances the reductive capacity CRC cancer cells via the pentose phosphate pathway using polar metabolomic profiling. We show this activation enables efficient growth under oxidative conditions both in vitro and in vivo, challenging the previous notion that PDZK1IP1 acts as a tumor suppressor in CRC. Collectively, these observations highlight the biologic significance of epigenomic profiling on patient-matched primary specimens and identify this microenvironment-acquired super-enhancer as an oncogenic driver in the setting of the inflamed tumor. Citation Format: Royce Zhou, Jia Xu, Tiphaine Martin, Alexis Zachem, John He, Sait Ozturk, Deniz Demircioglu, Ankita Bansal, Andrew Trotta, Bruno Giotti, Berkley Gryder, Yao Shen, Saul Carcamo, Xuewei Wu, Kaitlyn Bosch, Benjamin Hopkins, Alexander Tsankov, Randolph Steinhagen, Drew Jones, John Asara, Jerry Chipuk, Rachel Brody, Steven Itzkowitz, Iok In Christine Chio, Dan Hasson, Emily Bernstein, Ramon Parsons. A local tumor microenvironment acquired super-enhancer induces an oncogenic driver in colorectal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3481.

Abstract 991: Leveraging sequences missing from the human genome to detect cancer

Abstract Introduction: Cancer diagnosis using cell-free DNA (cfDNA) has the potential to improve treatment and survival but has several technical limitations. Methods: Here, we used neomers, short DNA sequences (13-17bp in length) that are largely absent from the healthy human genome, but appear in the tumor genome due to somatic mutations, to detect cancer at early stages from cfDNA. cfDNA was extracted from 1mL of plasma, and utilized from Whole Genome Sequencing at 5X coverage. Results: First, we analyzed over 2,500 cancer whole-genome sequences (WGS), to show that a neomer-based classifier can distinguish twenty-one different tumor types with higher accuracy than state-of-the-art methods. Refinement of this classifier via manually selected neomer sets, identified additional cancer features with greater precision. We next generated cfDNA WGS data from >600 patients and non-cancerous controls across four different types of cancers (prostate, lung, ovarian, colorectal), and demonstrated that neomers can precisely identify cancer from a limited amount of plasma for all four cancer types, with exampled sensitivities of 93.73% and 73.47% for lung and ovarian cancers, respectively. Additionally, using both luciferase and massively parallel reporter assays (MPRAs), we show that our neomer-driven approach can detect cancer-associated non-coding mutations that affect gene regulatory activity. Conclusions: Our results show that neomers provide a novel, sensitive, specific and potentially broadly applicable cancer detection tool. This approach has several advantages over existing strategies for liquid biopsies: 1) it is based on standard next-generation sequencing which is already widely available in the clinic; 2) it requires low amounts of starting material and is completely tumor agnostic; 3) it searches the entire genome and is not restricted to known driver mutations. 4) it allows the detection of early-stage disease. Citation Format: Ofer Yizhar Barnea, Ilias Georgakopoulos-Soares, Nadav Ahituv, Jocelyn Chapman, Martin Hemberg, Ioannis Mouratidis, Konstantinos Syrigos, Nikolaos Syrigos, Ioannis Vathiotis, Mayank Mahajan, Emmanouil Panagiotou, Andriani Charpidou, Mark Kvale, Candace S. Chan, Ryder Easterlin. Leveraging sequences missing from the human genome to detect cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 991.

Abstract 1435: A GABP dominant negative approach to targeting tumor cell immortality

Abstract Immortality is a hallmark of human cancer cells and therapeutic reversal is of great interest. Telomerase Reverse Transcriptase promoter (TERTp) mutations reactivate TERT expression, the rate limiting step in telomerase activity and cellular immortality. While prior telomerase blocking therapies lack tumor selectivity and were poorly tolerated, TERTp mutations and their regulation offer a unique opportunity for tumor specific reversal of cellular immortality. TERTp mutations are the most common non-coding mutation across all cancers, including glioblastoma (GBM), melanoma, urothelial carcinoma, and many others. The mutations generate a de novo E26 Transformation Specific (ETS) binding motif that recruits the GA-Binding Protein (GABP) multimeric complex to reactivate TERT expression. While GABP can form both a dimeric and tetrameric complex, we found that the tetrameric complex is responsible for reactivation of the mutant TERTp, suggesting selectively targeting the tetramer may induce telomere shortening and tumor cell death. However, through knocking out the tetramer, we found that the GABP dimer is sufficiently upregulated to maintain TERT expression. In the absence of the dimer and the tetramer isoform, many tumor cells senesce or undergo cell death. However, some escape this fate via upregulation of a second tetramer forming GABP paralogue that maintains TERT expression. Therefore, we devised a transactivation domain null GABP subunit that we hypothesized would act in a dominant negative manner to block the GABP dimer and both GABP tetramers. Introduction of the dominant negative construct into TERTp mutant GBM, meningioma, medulloblastoma, oligodendroglioma, and urothelial carcinoma cells significantly reduced TERT expression while not altering expression in TERTp wildtype GBM cells. Furthermore, the dominant negative is able to shorten telomere length in TERTp mutant GBM cells. While therapeutic targeting of the three GABP complexes seems particularly challenging, our initial dominant negative appears to do so. Ultimately the dominant negative could be delivered directly into tumors via clinically approved viral delivery systems such as retroviral replicating vectors. Citation Format: Nicholas O. Stevers, Sara A. Collins, Samuel H. Wu, Noriyuki Kasahara, Joseph F. Costello. A GABP dominant negative approach to targeting tumor cell immortality [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1435.

Protein Arginine Methyltransferase 5 (PRMT5) Mutations in Cancer Cells.

Arginine methylation is a form of posttranslational modification that regulates many cellular functions such as development, DNA damage repair, inflammatory response, splicing, and signal transduction, among others. Protein arginine methyltransferase 5 (PRMT5) is one of nine identified methyltransferases, and it can methylate both histone and non-histone targets. It has pleiotropic functions, including recruitment of repair machinery to a chromosomal DNA double strand break (DSB) and coordinating the interplay between repair and checkpoint activation. Thus, PRMT5 has been actively studied as a cancer treatment target, and small molecule inhibitors of its enzymatic activity have already been developed. In this report, we analyzed all reported PRMT5 mutations appearing in cancer cells using data from the Catalogue of Somatic Mutations in Cancers (COSMIC). Our goal is to classify mutations as either drivers or passengers to understand which ones are likely to promote cellular transformation. Using gold standard artificial intelligence algorithms, we uncovered several key driver mutations in the active site of the enzyme (D306H, L315P, and N318K). In silico protein modeling shows that these mutations may affect the affinity of PRMT5 for S-adenosylmethionine (SAM), which is required as a methyl donor. Electrostatic analysis of the enzyme active site shows that one of these mutations creates a tunnel in the vicinity of the SAM binding site, which may allow interfering molecules to enter the enzyme active site and decrease its activity. We also identified several non-coding mutations that appear to affect PRMT5 splicing. Our analyses provide insights into the role of PRMT5 mutations in cancer cells. Additionally, since PRMT5 single molecule inhibitors have already been developed, this work may uncover future directions in how mutations can affect targeted inhibition.

Cell type-specific interpretation of noncoding variants using deep learning-based methods.

Interpretation of noncoding genomic variants is one of the most important challenges in human genetics. Machine learning methods have emerged recently as a powerful tool to solve this problem. State-of-the-art approaches allow prediction of transcriptional and epigenetic effects caused by noncoding mutations. However, these approaches require specific experimental data for training and cannot generalize across cell types where required features were not experimentally measured. We show here that available epigenetic characteristics of human cell types are extremely sparse, limiting those approaches that rely on specific epigenetic input. We propose a new neural network architecture, DeepCT, which can learn complex interconnections of epigenetic features and infer unmeasured data from any available input. Furthermore, we show that DeepCT can learn cell type-specific properties, build biologically meaningful vector representations of cell types, and utilize these representations to generate cell type-specific predictions of the effects of noncoding variations in the human genome.

Invivo interrogation of regulatory genomes reveals extensive quasi-insufficiency in cancer evolution.

In contrast to mono- or biallelic loss of tumor-suppressor function, effects of discrete gene dysregulations, as caused by non-coding (epi)genome alterations, are poorly understood. Here, by perturbing the regulatory genome in mice, we uncover pervasive roles of subtle gene expression variation in cancer evolution. Genome-wide screens characterizing 1,450 tumors revealed that such quasi-insufficiency is extensive across entities and displays diverse context dependencies, such as distinct cell-of-origin associations in T-ALL subtypes. We compile catalogs of non-coding regions linked to quasi-insufficiency, show their enrichment with human cancer risk variants, and provide functional insights by engineering regulatory alterations in mice. As such, kilo-/megabase deletions in a Bcl11b-linked non-coding region triggered aggressive malignancies, with allele-specific tumor spectra reflecting gradual gene dysregulations through modular and cell-type-specific enhancer activities. Our study constitutes a first survey toward a systems-level understanding of quasi-insufficiency in cancer and gives multifaceted insights into tumor evolution and the tissue-specific effects of non-coding mutations.

Miswired Proprioception in Amyotrophic Lateral Sclerosis in Relation to Pain Sensation (and in Delayed Onset Muscle Soreness)—Is Piezo2 Channelopathy a Principal Transcription Activator in Proprioceptive Terminals Besides Being the Potential Primary Damage?

Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative multisystem disease, with an unknown pathomechanism, resulting in progressive motoneuron loss. In 90-95% of cases, ALS is sporadic, but close to 10% of ALS is familial with inherited gene mutations from family members. Recently, a non-contact dying-back injury mechanism theory of ALS postulated that irreversible intrafusal proprioceptive terminal degeneration induces the non-resolving progressive impairment of the proprioceptive circuitry, leading to motoneuron loss, progressive overloading and depletion of the central nervous system, and eventually to death. The current manuscript proposes that irreversible Piezo2 channelopathy of this proprioceptive terminal degeneration induces constantly activated and dysregulated transcription process in ALS, providing access to underlying pathogenic gene variants and letting the cell-type-specific noncoding DNA mutations become more apparent. This opinion piece proposes that ALS genes are associated with the Piezo2 channelopathy mechanism both downstream and upstream, and their mutations, along with the aging process, could explain the non-contact dying-back injury mechanism theory of ALS. Moreover, irreversible microinjury of the Piezo2 ion channel could be the primary damage or the root cause of death in ALS. Finally, the current manuscript also depicts the pathomechanism as to why ALS is considered a painless disease.

Novel Biomarkers for Diagnosis and Monitoring of Immune Thrombocytopenia

Lower-than-normal platelet counts are a hallmark of the acquired autoimmune illness known as immune thrombocytopenia, which can affect both adults and children. Immune thrombocytopenia patients' care has evolved significantly in recent years, but the disease's diagnosis has not, and it is still only clinically achievable with the elimination of other causes of thrombocytopenia. The lack of a valid biomarker or gold-standard diagnostic test, despite ongoing efforts to find one, adds to the high rate of disease misdiagnosis. However, in recent years, several studies have helped to elucidate a number of features of the disease's etiology, highlighting how the platelet loss is not only caused by an increase in peripheral platelet destruction but also involves a number of humoral and cellular immune system effectors. This made it possible to identify the role of immune-activating substances such cytokines and chemokines, complement, non-coding genetic material, the microbiome, and gene mutations. Furthermore, platelet and megakaryocyte immaturity indices have been emphasized as new disease markers, and prognostic signs and responses to particular types of therapy have been suggested. Our review's goal was to compile information from the literature on novel immune thrombocytopenia biomarkers, markers that will help us improve the management of these patients.

Report of the GNPTAB c.3598G>A, p.Glu1200Lys founder mutation associated with persistent stuttering in South Indian population

Stuttering is a disorder that affects the fluency of speech resulting in interruptions that are highly heritable. The present study aimed to evaluate the occurrence of the founder mutation GNPTAB c.3598G>A, p.Glu1200Lys (rs137853825) which is associated with stuttering. A total of 96 unrelated persistent stutterers from south India were included in this study. Genotyping the exon 19 of the GNPTAB gene by Sanger sequencing identified the pathogenic mutation in 5/96 (5.2 %) participants. A noncoding mutation GNPTAB c.3602+62A>G (rs1952847841) was also detected in 16/96 (16.6 %) cases. Further studies are warranted to identify the pathogenic loci of other genes of the lysosomal pathway, which would provide further insights into the genetic constitution of stuttering.