Distribution of copy number variations and rearrangement endpoints in human cancers with a review of literature

Copy number variations in autistic children

Autism spectrum disorder (ASD) manifests as a neurodevelopmental condition marked by challenges in social communication, interaction and the performing of repetitive behaviors. The prevalence of autism increases markedly on an annual basis; however, the etiology remains incompletely understood. Cytogenetically visible chromosomal abnormalities, including copy number variations (CNVs), have been shown to contribute to the pathogenesis of ASD. More than 1% of ASD conditions can be explained based on a known genetic locus, whereas CNVs account for 5-10% of cases. However, there are no studies on the Saudi Arabian population for the detection of CNVs linked to ASD, to the best of our knowledge. Therefore, the aim of the present study was to explore the prevalence of CNVs in autistic Saudi Arabian children. Genomic DNA was extracted from the peripheral blood of 14 autistic children along with four healthy control children and then array-based comparative genomic hybridization (aCGH) was used to detect CNVs. Bioinformatics analysis of the aCGH results showed the presence of recurrent and non-recurrent deletion/duplication CNVs in several regions of the genome of autistic children. The most frequent CNVs were 1q21.2, 3p26.3, 4q13.2, 6p25.3, 6q24.2, 7p21.1, 7q34, 7q11.1, 8p23.2, 13q32.3, 14q11.1-q11.2 and 15q11.1-q11.2. In the present study, CNVs in autistic Saudi Arabian children were identified to improve the understanding of the etiology of autism and facilitate its diagnosis. Additionally, the present study identified certain possible pathogenic genes in the CNV region associated with several developmental and neurogenetic diseases.

Multi-Omics Integration for Liver Cancer Using Regression Analysis

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant p-values. Further, these regressors were trained using linear and logistic regression with k-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers.

Iridium-Catalyzed 1,3-Rearrangement of Allylic Ethers

The 1,3-rearrangement of allylic derivatives has rarely been reported, except for allylic alcohols. Herein, we describe an iridium-catalyzed 1,3-rearrangement of readily available allylic ethers to access the difficultly prepared allylic ethers with a large steric hindrance. The developed method shows a broad substrate scope and could be used in the late-stage modification of several natural products. In addition, a possible reaction pathway is also provided on the basis of the control experiments.

The Association of R-Loop Binding Proteins Subtypes with CIN Implicates Therapeutic Strategies in Colorectal Cancer

Chromosomal instability (CIN) covers approximately 65 to 70% of colorectal cancer patients and plays an essential role in cancer progression. However, the molecular features and therapeutic strategies related to those patients are still controversial. R-loop binding proteins (RLBPs) exert significant roles in transcription and replication. Here, integrative colorectal cancer proteogenomic analysis identified two RLBPs subtypes correlated with distinct prognoses. Cluster I (CI), represented by high expression of RLBPs, was associated with the CIN phenotype. While Cluster II (CII) with the worst prognosis and low expression of RLBPs was composed of a high percentage of patients with mucinous adenocarcinoma or right-sided colon cancer. The molecular feature analysis revealed that the active RNA processing, ribosome synthesis, and aberrant DNA damage repair were shown in CI, a high inflammatory signaling pathway, and lymphocyte infiltration was enriched in CII. In addition, we revealed 42 tumor-associated RLBPs proteins. The CI with high expression of tumor-associated proteins was sensitive to drugs targeting genome integrity and EGFR in both cell and organoid models. Thus, our study unveils a significant molecular association of the CIN phenotype with RLBPs, and also provides a powerful resource for further functional exploration of RLBPs in cancer progression and therapeutic application.

Systematic Analysis of Copy Number Variations in the Pathogenic Yeast Candida parapsilosis Identifies a Gene Amplification in RTA3 That is Associated with Drug Resistance

We analyzed the genomes of 170 C. parapsilosis isolates and identified multiple copy number variations (CNVs). We identified two genes, RTA3 (CPAR2_104610) and ARR3 (CPAR2_601050), each of which was the target of multiple independent amplification events. Phylogenetic analysis shows that most of these amplifications originated only once. For ARR3, which encodes a putative arsenate transporter, 8 distinct CNVs were identified, ranging in size from 2.3 kb to 10.5 kb with 3 to 23 copies. For RTA3, 16 distinct CNVs were identified, ranging in size from 0.3 kb to 4.5 kb with 2 to ~50 copies. One unusual amplification resulted in a DUP-TRP/INV-DUP structure similar to some human CNVs. RTA3 encodes a putative phosphatidylcholine (PC) floppase which is known to regulate the inward translocation of PC in Candida albicans. We found that an increased copy number of RTA3 correlated with resistance to miltefosine, an alkylphosphocholine drug that affects PC metabolism. Additionally, we conducted an adaptive laboratory evolution experiment in which two C. parapsilosis isolates were cultured in increasing concentrations of miltefosine. Two genes, CPAR2_303950 and CPAR2_102700, coding for putative PC flippases homologous to S. cerevisiae DNF1 gained homozygous protein-disrupting mutations in the evolved strains. Overall, our results show that C. parapsilosis can gain resistance to miltefosine, a drug that has recently been granted orphan drug designation approval by the United States Food and Drug Administration for the treatment of invasive candidiasis, through both CNVs or loss-of-function alleles in one of the flippase genes. IMPORTANCE Copy number variations (CNVs) are an important source of genomic diversity that have been associated with drug resistance. We identify two unusual CNVs in the human fungal pathogen Candida parapsilosis. Both target a single gene (RTA3 or ARR3), and they have occurred multiple times in multiple isolates. The copy number of RTA3, a putative floppase that controls the inward translocation of lipids in the cell membrane, correlates with resistance to miltefosine, a derivative of phosphatidylcholine (PC) that was originally developed as an anticancer drug. In 2021, miltefosine was designated an orphan drug by the United States Food and Drug Administration for the treatment of invasive candidiasis. Importantly, we find that resistance to miltefosine is also caused by mutations in flippases, which control the outward movement of lipids, and that many C. parapsilosis isolates are prone to easily acquiring an increased resistance to miltefosine.

Pan-cancer analysis of co-occurring mutations in RAD52 and the BRCA1-BRCA2-PALB2 axis in human cancers

In human cells homologous recombination (HR) is critical for repair of DNA double strand breaks (DSBs) and rescue of stalled or collapsed replication forks. HR is facilitated by RAD51 which is loaded onto DNA by either BRCA2-BRCA1-PALB2 or RAD52. In human culture cells, double-knockdowns of RAD52 and genes in the BRCA1-BRCA2-PALB2 axis are lethal. Mutations in BRCA2, BRCA1 or PALB2 significantly impairs error free HR as RAD51 loading relies on RAD52 which is not as proficient as BRCA2-BRCA1-PALB2. RAD52 also facilitates Single Strand Annealing (SSA) that produces intra-chromosomal deletions. Some RAD52 mutations that affect the SSA function or decrease RAD52 association with DNA can suppress certain BRCA2 associated phenotypes in breast cancers. In this report we did a pan-cancer analysis using data reported on the Catalogue of Somatic Mutations in Cancers (COSMIC) to identify double mutants between RAD52 and BRCA1, BRCA2 or PALB2 that occur in cancer cells. We find that co-occurring mutations are likely in certain cancer tissues but not others. However, all mutations occur in a heterozygous state. Further, using computational and machine learning tools we identified only a handful of pathogenic or driver mutations predicted to significantly affect the function of the proteins. This supports previous findings that co-inactivation of RAD52 with any members of the BRCA2-BRCA1-PALB2 axis is lethal. Molecular modeling also revealed that pathogenic RAD52 mutations co-occurring with mutations in BRCA2-BRCA1-PALB2 axis are either expected to attenuate its SSA function or its interaction with DNA. This study extends previous breast cancer findings to other cancer types and shows that co-occurring mutations likely destabilize HR by similar mechanisms as in breast cancers.

BRCA Mutations in Ovarian and Prostate Cancer: Bench to Bedside

Simple Summary

DNA damage is one of the hallmarks of cancer. Epithelial ovarian cancer (EOC) —especially the high-grade serous subtype—harbors a defect in at least one DNA damage response (DDR) pathway. Defective DDR results from a variety of lesions affecting homologous recombination (HR) and nonhomologous end joining (NHEJ) for double strand breaks, base excision repair (BER), and nucleotide excision repair (NER) for single strand breaks and mismatch repair (MMR). Apart from the EOC, mutations in the DDR genes, such as BRCA1 and BRCA2, are common in prostate cancer as well. Among them, BRCA2 lesions are found in 12% of metastatic castration-resistant prostate cancers, but very rarely in primary prostate cancer. Better understanding of the DDR pathways is essential in order to optimize the therapeutic choices, and has led to the design of biomarker-driven clinical trials. Poly(ADP-ribose) polymerase (PARP) inhibitors are now a standard therapy for EOC patients, and more recently have been approved for the metastatic castration-resistant prostate cancer with alterations in DDR genes. They are particularly effective in tumours with HR deficiency.

Abstract

DNA damage repair (DDR) defects are common in different cancer types, and these alterations can be exploited therapeutically. Epithelial ovarian cancer (EOC) is among the tumours with the highest percentage of hereditary cases. BRCA1 and BRCA2 predisposing pathogenic variants (PVs) were the first to be associated with EOC, whereas additional genes comprising the homologous recombination (HR) pathway have been discovered with DNA sequencing technologies. The incidence of DDR alterations among patients with metastatic prostate cancer is much higher compared to those with localized disease. Genetic testing is playing an increasingly important role in the treatment of patients with ovarian and prostate cancer. The development of poly (ADP-ribose) polymerase (PARP) inhibitors offers a therapeutic strategy for patients with EOC. One of the mechanisms of PARP inhibitors exploits the concept of synthetic lethality. Tumours with BRCA1 or BRCA2 mutations are highly sensitive to PARP inhibitors. Moreover, the synthetic lethal interaction may be exploited beyond germline BRCA mutations in the context of HR deficiency, and this is an area of ongoing research. PARP inhibitors are in advanced stages of development as a treatment for metastatic castration-resistant prostate cancer. However, there is a major concern regarding the need to identify reliable biomarkers predictive of treatment response. In this review, we explore the mechanisms of DDR, the potential for genomic analysis of ovarian and prostate cancer, and therapeutics of PARP inhibitors, along with predictive biomarkers.

GraphChrom: A Novel Graph-Based Framework for Cancer Classification Using Chromosomal Rearrangement Endpoints

Chromosomal rearrangements are generally a consequence of improperly repaired double-strand breaks in DNA. These genomic aberrations can be a driver of cancers. Here, we investigated the use of chromosomal rearrangements for classification of cancer tumors and the effect of inter- and intrachromosomal rearrangements in cancer classification. We used data from the Catalogue of Somatic Mutations in Cancer (COSMIC) for breast, pancreatic, and prostate cancers, for which the COSMIC dataset reports the highest number of chromosomal aberrations. We developed a framework known as GraphChrom for cancer classification. GraphChrom was developed using a graph neural network which models the complex structure of chromosomal aberrations (CA) and provides local connectivity between the aberrations. The proposed framework illustrates three important contributions to the field of cancers. Firstly, it successfully classifies cancer types and subtypes. Secondly, it evolved into a novel data extraction technique which can be used to extract more informative graphs (informative aberrations associated with a sample); and thirdly, it predicts that interCAs (rearrangements between two or more chromosomes) are more effective in cancer prediction than intraCAs (rearrangements within the same chromosome), although intraCAs are three times more likely to occur than intraCAs.