Positive Caricature Transcriptomic Effects Associated with Broad Genomic Aberrations in Colorectal Cancer

Gain-Type Aneuploidies Influence the Burden of Selective Long Non-Coding Transcripts in Colorectal Cancer

Chromosomal instability is a hallmark of colorectal carcinogenesis and produces an accumulation of different forms of aneuploidies or broad copy number aberrations. Colorectal cancer is characterized by gain-type broad copy number aberrations, specifically in Chr20, Chr8q, Chr13 and Chr7, but their roles and mechanisms in cancer progression are not fully understood. It has been suggested that broad copy number gains might contribute to tumor development through the so-called caricature transcriptomic effect. We intend to investigate the impact of broad copy number gains on long non-coding RNAs' expression in colorectal cancer, given their well-known role in oncogenesis. The influence of such chromosomal aberrations on lncRNAs' transcriptome profile was investigated by SNP and transcriptome arrays in our series of colorectal cancer samples and cell lines. The correlation between aneuploidies and transcriptomic profiles led us to obtain a class of Over-UpT lncRNAs, which are transcripts upregulated in CRC and further overexpressed in colon tumors bearing specific chromosomal aberrations. The identified lncRNAs can contribute to a wide interaction network to establish the cancer driving effect of gain-type aneuploidies.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

The Crucial Findings Derived from the Special Issue "Inside Cancer Genomics: From Structure to Therapy"

Cancer initiation, growth, and progression are sustained by multiple types of genetic alterations, ranging in size from single point mutations, focal genomic errors to broad chromosomal copy number alterations, gains, and losses [...].

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

Transcript-Targeted Therapy Based on RNA Interference and Antisense Oligonucleotides: Current Applications and Novel Molecular Targets

The development of novel target therapies based on the use of RNA interference (RNAi) and antisense oligonucleotides (ASOs) is growing in an exponential way, challenging the chance for the treatment of the genetic diseases and cancer by hitting selectively targeted RNA in a sequence-dependent manner. Multiple opportunities are taking shape, able to remove defective protein by silencing RNA (e.g., Inclisiran targets mRNA of protein PCSK9, permitting a longer half-life of LDL receptors in heterozygous familial hypercholesteremia), by arresting mRNA translation (i.e., Fomivirsen that binds to UL123-RNA and blocks the translation into IE2 protein in CMV-retinitis), or by reactivating modified functional protein (e.g., Eteplirsen able to restore a functional shorter dystrophin by skipping the exon 51 in Duchenne muscular dystrophy) or a not very functional protein. In this last case, the use of ASOs permits modifying the expression of specific proteins by modulating splicing of specific pre-RNAs (e.g., Nusinersen acts on the splicing of exon 7 in SMN2 mRNA normally not expressed; it is used for spinal muscular atrophy) or by downregulation of transcript levels (e.g., Inotersen acts on the transthryretin mRNA to reduce its expression; it is prescribed for the treatment of hereditary transthyretin amyloidosis) in order to restore the biochemical/physiological condition and ameliorate quality of life. In the era of precision medicine, recently, an experimental splice-modulating antisense oligonucleotide, Milasen, was designed and used to treat an 8-year-old girl affected by a rare, fatal, progressive form of neurodegenerative disease leading to death during adolescence. In this review, we summarize the main transcriptional therapeutic drugs approved to date for the treatment of genetic diseases by principal regulatory government agencies and recent clinical trials aimed at the treatment of cancer. Their mechanism of action, chemical structure, administration, and biomedical performance are predominantly discussed.

Methyladenosine Modification in RNAs: From Regulatory Roles to Therapeutic Implications in Cancer

Simple Summary

Cancer remains a burden to the public health all over the world. An increasing number of studies have concentrated on the role of methyladenosine modifications on cancers. Methyladenosine modifications mainly include N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), and 2’-O-methyladenosine (m⁶A_m), of which dynamic changes could modulate the metabolism of RNAs in eukaryotic cells. Mounting evidence has confirmed the crucial role of methyladenosine modification in cancer, offering possibilities for cancer therapy. In this review, we discussed the regulatory role of methyladenosine modification on cancer, as well as their potential for treatment.

Abstract

Methyladenosine modifications are the most abundant RNA modifications, including N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), and 2’-O-methyladenosine (m⁶A_m). As reversible epigenetic modifications, methyladenosine modifications in eukaryotic RNAs are not invariable. Drastic alterations of m⁶A are found in a variety of diseases, including cancers. Dynamic changes of m⁶A modification induced by abnormal methyltransferase, demethylases, and readers can regulate cancer progression via interfering with the splicing, localization, translation, and stability of mRNAs. Meanwhile, m⁶A, m¹A, and m⁶A_m modifications also exert regulatory effects on noncoding RNAs in cancer progression. In this paper, we reviewed recent findings concerning the underlying biomechanism of methyladenosine modifications in oncogenesis and metastasis and discussed the therapeutic potential of methyladenosine modifications in cancer treatments.

Evolutionary patterns of chromosomal instability and mismatch repair deficiency in proximal and distal colorectal cancer

AIM

Colorectal carcinomas (CRCs) progress through heterogeneous pathways. The aim of this study was to analyse whether or not the cytogenetic evolution of CRC is linked to tumour site, level of chromosomal imbalance and metastasis.

METHOD

A set of therapy-naïve pT3 CRCs comprising 26 proximal and 49 distal pT3 CRCs was studied by combining immunohistochemistry of mismatch repair (MMR) proteins, microsatellite analyses and molecular karyotyping as well as clinical parameters.

RESULTS

A MMR deficient/microsatellite-unstable (dMMR/MSI-H) status was associated with location of the primary tumour proximal to the splenic flexure, and dMMR/MSI-H tumours presented with significantly lower levels of chromosomal imbalances compared with MMR proficient/microsatellite-stable (pMMR/MSS) tumours. Oncogenetic tree modelling suggested two evolutionary clusters characterized by dMMR/MSI-H and chromosomal instability (CIN), respectively, for both proximal and distal CRCs. In CIN cases, +13q, -18q and +20q were predicted as preferentially early events, and -1p, -4 -and -5q as late events. Separate oncogenetic tree models of proximal and distal cases indicated similar early events independent of tumour site. However, in cases with high CIN defined by more than 10 copy number aberrations, loss of 17p occurred earlier in cytogenetic evolution than in cases showing low to moderate CIN. Differences in the oncogenetic trees were observed for CRCs with lymph node and distant metastasis. Loss of 8p was modelled as an early event in node-positive CRC, while +7p and +8q comprised early events in CRC with distant metastasis.

CONCLUSION

CRCs characterized by CIN follow multiple, interconnected genetic pathways in line with the basic 'Vogelgram' concept proposed for the progression of CRC that places the accumulation of genetic changes at centre of tumour evolution. However, the timing of specific genetic events may favour metastatic potential.

NUP-98 Rearrangements Led to the Identification of Candidate Biomarkers for Primary Induction Failure in Pediatric Acute Myeloid Leukemia

Conventional chemotherapy for acute myeloid leukemia regimens generally encompass an intensive induction phase, in order to achieve a morphological remission in terms of bone marrow blasts (<5%). The majority of cases are classified as Primary Induction Response (PIR); unfortunately, 15% of children do not achieve remission and are defined Primary Induction Failure (PIF). This study aims to characterize the gene expression profile of PIF in children with Acute Myeloid Leukemia (AML), in order to detect molecular pathways dysfunctions and identify potential biomarkers. Given that NUP98-rearrangements are enriched in PIF-AML patients, we investigated the association of NUP98-driven genes in primary chemoresistance. Therefore, 85 expression arrays, deposited on GEO database, and 358 RNAseq AML samples, from TARGET program, were analyzed for “Differentially Expressed Genes” (DEGs) between NUP98+ and NUP98-, identifying 110 highly confident NUP98/PIF-associated DEGs. We confirmed, by qRT-PCR, the overexpression of nine DEGs, selected on the bases of the diagnostic accuracy, in a local cohort of PIF patients: SPINK2, TMA7, SPCS2, CDCP1, CAPZA1, FGFR1OP2, MAN1A2, NT5C3A and SRP54. In conclusion, the integrated analysis of NUP98 mutational analysis and transcriptome profiles allowed the identification of novel putative biomarkers for the prediction of PIF in AML.

Aberrations of Chromosomes 1 and 16 in Breast Cancer: A Framework for Cooperation of Transcriptionally Dysregulated Genes

Derivative chromosome der(1;16), isochromosome 1q, and deleted 16q-producing arm-level 1q-gain and/or 16q-loss-are recurrent cytogenetic abnormalities in breast cancer, but their exact role in determining the malignant phenotype is still largely unknown. We exploited The Cancer Genome Atlas (TCGA) data to generate and analyze groups of breast invasive carcinomas, called 1,16-chromogroups, that are characterized by a pattern of arm-level somatic copy number aberrations congruent with known cytogenetic aberrations of chromosome 1 and 16. Substantial differences were found among 1,16-chromogroups in terms of other chromosomal aberrations, aneuploidy scores, transcriptomic data, single-point mutations, histotypes, and molecular subtypes. Breast cancers with a co-occurrence of 1q-gain and 16q-loss can be distinguished in a "low aneuploidy score" group, congruent to der(1;16), and a "high aneuploidy score" group, congruent to the co-occurrence of isochromosome 1q and deleted 16q. Another three groups are formed by cancers showing separately 1q-gain or 16q-loss or no aberrations of 1q and 16q. Transcriptome comparisons among the 1,16-chromogroups, integrated with functional pathway analysis, suggested the cooperation of overexpressed 1q genes and underexpressed 16q genes in the genesis of both ductal and lobular carcinomas, thus highlighting the putative role of genes encoding gamma-secretase subunits (APH1A, PSEN2, and NCSTN) and Wnt enhanceosome components (BCL9 and PYGO2) in 1q, and the glycoprotein E-cadherin (CDH1), the E3 ubiquitin-protein ligase WWP2, the deubiquitinating enzyme CYLD, and the transcription factor CBFB in 16q. The analysis of 1,16-chromogroups is a strategy with far-reaching implications for the selection of cancer cell models and novel experimental therapies.

Identification of long non-coding RNA SCARNA9L as a novel molecular target for colorectal cancer

The aim of the present study was to analyze the microarray data of human colorectal cancer (CRC) tissues and identify novel therapeutic targets for CRC. Microarray analysis from the GSE73360 and GSE84984 datasets was performed to identify novel long non-coding RNAs (lncRNAs) that were differentially expressed in human CRC tissues. Additionally, small interfering RNAs were used to deplete the expression of the indicated lncRNAs in cells. Colony-formation, wound-closure, and transwell assays were performed on CRC cells to assess their proliferation and migration capacities. Through microarray analysis, SCARNA9L, SLMO2-ATP5E and LOC100132062 were identified as differentially expressed lncRNAs in CRC tissues. The present study demonstrated that the ablation of SCARNA9L inhibited cell proliferation and arrested the cell cycle of SW480 and SW620 CRC cells. Additionally, depletion of SCARNA9L restrained the migration of CRC cells in vitro. Overall, the present study investigated the potential involvement of SCARNA9L in CRC and suggests SCARNA9L as a potential biomarker.

Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis

Colorectal cancer (CRC) is a life-threatening disease with a poor prognosis. Therefore, it is crucial to identify molecular prognostic biomarkers for CRC. The present study aimed to identify potential key genes that could be used to predict the prognosis of patients with CRC. Three CRC microarray datasets (GSE20916, GSE73360 and GSE44861) were downloaded from the Gene Expression Omnibus (GEO) database, and one dataset was obtained from The Cancer Genome Atlas (TCGA) database. The three GEO datasets were analyzed to detect differentially expressed genes (DEGs) using the BRB-ArrayTools software. Functional and pathway enrichment analyses of these DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network of DEGs was constructed, hub genes were extracted, and modules of the PPI network were analyzed. To investigate the prognostic values of the hub genes in CRC, data from the CRC datasets of TCGA were used to perform the survival analyses based on the sample splitting method and Cox regression model. Correlation among the hub genes was evaluated using Spearman's correlation analysis. In the three GEO datasets, a total of 105 common DEGs were identified, including 51 down- and 54 up-regulated genes in CRC compared with normal colorectal tissues. A PPI network consisting of 100 DEGs and 551 edges was constructed, and 44 nodes were identified as hub genes. Among these 44 genes, the four hub genes TIMP metallopeptidase inhibitor 1 (TIMP1), solute carrier family 4 member 4 (SLC4A4), aldo-keto reductase family 1 member B10 (AKR1B10) and ATP binding cassette subfamily E member 1 (ABCE1) were associated with overall survival (OS) in patients with CRC. Three significant modules were extracted from the PPI network. The hub gene TIMP1 was present in Module 1, ABCE1 was involved in Module 2 and SLC4A4 was identified in Module 3. Univariate analysis revealed that TIMP1, SLC4A4, AKR1B10 and ABCE1 were associated with the OS of patients with CRC. Multivariate analysis demonstrated that SLC4A4 may be an independent prognostic factor associated with OS. Furthermore, the results from correlation analysis revealed that there was no correlation between TIMP1, SLC4A4 and ABCE1, whereas AKR1B10 was positively correlated with SLC4A4. In conclusion, the four key genes TIMP1, SLC4A4, AKR1B10 and ABCE1 associated with the OS of patients with CRC were identified by integrated bioinformatics analysis. These key genes may be used as prognostic biomarkers to predict the survival of patients with CRC, and may therefore represent novel therapeutic targets for CRC.

Fusion Transcripts of Adjacent Genes: New Insights into the World of Human Complex Transcripts in Cancer

The awareness of genome complexity brought a radical approach to the study of transcriptome, opening eyes to single RNAs generated from two or more adjacent genes according to the present consensus. This kind of transcript was thought to originate only from chromosomal rearrangements, but the discovery of readthrough transcription opens the doors to a new world of fusion RNAs. In the last years many possible intergenic cis-splicing mechanisms have been proposed, unveiling the origins of transcripts that contain some exons of both the upstream and downstream genes. In some cases, alternative mechanisms, such as trans-splicing and transcriptional slippage, have been proposed. Five databases, containing validated and predicted Fusion Transcripts of Adjacent Genes (FuTAGs), are available for the scientific community. A comparative analysis revealed that two of them contain the majority of the results. A complete analysis of the more widely characterized FuTAGs is provided in this review, including their expression pattern in normal tissues and in cancer. Gene structure, intergenic splicing patterns and exon junction sequences have been determined and here reported for well-characterized FuTAGs. The available functional data and the possible roles in cancer progression are discussed.

Chromosomal Density of Cancer Up-Regulated Genes, Aberrant Enhancer Activity and Cancer Fitness Genes Are Associated with Transcriptional Cis-Effects of Broad Copy Number Gains in Colorectal Cancer

Broad Copy Number Gains (BCNGs) are copy-number increases of chromosomes or large segments of chromosomal arms. Publicly-available single-nucleotide polymorphism (SNP) array and RNA-Seq data of colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) consortium allowed us to design better control groups in order to identify changes in expression due to highly recurrent BCNGs (in chromosomes 20, 8, 7, 13). We identified: (1) Overexpressed Transcripts (OverT), transcripts whose expression increases in "COAD groups bearing a specific BCNG" in comparison to "control COAD groups" not bearing it, and (2) up-regulated/down-regulated transcripts, transcripts whose expression increases/decreases in COAD groups in comparison to normal colon tissue. An analysis of gene expression reveals a correlation between the density of up-regulated genes per selected chromosome and the recurrence rate of their BCNGs. We report an enrichment of gained enhancer activity and of cancer fitness genes among OverT genes. These results support the hypothesis that the chromosomal density of overexpressed cancer fitness genes might play a significant role in the selection of gained chromosomes during cancer evolution. Analysis of functional pathways associated with OverT suggest that some multi-subunit protein complexes (eIF2, eIF3, CSTF and CPSF) are candidate targets for silencing transcriptional therapy.